removed space from event handler

.claude/settings.json

@@ -1,5 +0,0 @@
-{
-  "attribution": {
-    "commit": ""
-  }
-}

.claude/skills/changelog/SKILL.md

@@ -1,47 +0,0 @@
----
-name: changelog
-description: Create changelog files for important commits in a PR
----
-
-Create changelog files for the important commits in this PR. The PR number is provided as an argument.
-
-## Instructions
-
-1. Skip changelog for: documentation-only, internal refactoring, test-only, CI changes.
-
-2. First, check what commits are on the current branch compared to main:
-   ```
-   git log main..HEAD --oneline
-   ```
-
-3. For each significant change, create a changelog file in the `changelog/` folder using the format:
-   Allowed types: `added`, `changed`, `deprecated`, `removed`, `fixed`, `security`, `performance`, `other`
-   - `{PR_NUMBER}.added.md` - for new features
-   - `{PR_NUMBER}.added.2.md`, `{PR_NUMBER}.added.3.md` - for additional entries of the same type
-   - `{PR_NUMBER}.changed.md` - for changes to existing functionality
-   - `{PR_NUMBER}.fixed.md` - for bug fixes
-   - `{PR_NUMBER}.deprecated.md` - for deprecations
-   - `{PR_NUMBER}.removed.md` - for removed features
-   - `{PR_NUMBER}.security.md` - for security fixes
-   - `{PR_NUMBER}.performance.md` - for performance improvements
-   - `{PR_NUMBER}.other.md` - for other changes
-
-4. Each changelog file should at least contain a main single line starting with `- ` followed by a clear description of the change. No line wrapping.
-
-5. If the change is complicated, changelog files can have indented lines after the main line with additional details or code samples.
-
-6. Use ⚠️ emoji prefix for breaking changes.
-
-## Example
-
-For PR #3519 with a new feature and a bug fix:
-
-`changelog/3519.added.md`:
-```
-- Added `SomeNewFeature` for doing something useful.
-```
-
-`changelog/3519.fixed.md`:
-```
-- Fixed an issue where something was not working correctly.
-```

.claude/skills/cleanup/SKILL.md

@@ -1,307 +0,0 @@
-# Code Cleanup Skill
-
-The **Code Cleanup Skill** reviews, refactors, and documents code changes in your current branch, ensuring alignment with **Pipecat’s architecture, coding standards, and example patterns**.
-It focuses on **readability, correctness, performance, and consistency**, while avoiding breaking changes.
-
----
-
-## Skill Overview
-
-This skill analyzes all changes introduced in your branch and performs the following actions:
-
-1. **Analyze Branch Changes**
-   - Review uncommitted changes and outgoing commits
-2. **Refactor for Readability**
-   - Improve clarity, naming, structure, and modern Python usage
-3. **Enhance Performance**
-   - Identify safe, conservative optimization opportunities
-4. **Add Documentation**
-   - Apply Pipecat-style, Google-format docstrings
-5. **Ensure Pattern Consistency**
-   - Match existing Pipecat services, pipelines, and examples
-6. **Validate Examples**
-   - Ensure examples follow foundational patterns (e.g. `07-interruptible.py`)
-
----
-
-## Usage
-
-Invoke the skill using any of the following commands:
-
-- “Clean up my branch code”
-- “Refactor the changes in my branch”
-- “Review and improve my branch code”
-- `/cleanup`
-
----
-
-## What This Skill Does
-
-### 1. Analyze Branch Changes
-
-The skill retrieves all uncommitted changes and outgoing commits to understand:
-
-- New files added
-- Modified files
-- Code additions and deletions
-- Overall scope and intent of changes
-
----
-
-### 2. Code Refactoring
-
-#### Readability Improvements
-
-- Replace tuples with named classes or dataclasses
-- Improve variable, method, and class naming
-- Extract complex logic into well-named helper methods
-- Add missing type hints
-- Simplify nested or complex conditionals
-- Replace deprecated methods and features
-- Normalize formatting to match Pipecat style
-
-#### Performance Enhancements
-
-- Identify inefficient loops or repeated work
-- Suggest appropriate data structures
-- Optimize async workflows and I/O
-- Remove redundant operations
-
-> Performance changes are conservative and non-breaking.
-
----
-
-### 3. Documentation
-
-Documentation follows **Google-style docstrings**, consistent with Pipecat conventions.
-
-#### Class Documentation
-
-```python
-class ExampleService:
-    """Brief one-line description.
-
-    Detailed explanation of the class purpose, responsibilities,
-    and important behaviors.
-
-    Supported features:
-
-    - Feature 1
-    - Feature 2
-    - Feature 3
-    """
-```
-
-#### Method Documentation
-
-```python
-def process_data(self, data: str, options: Optional[dict] = None) -> bool:
-    """Process incoming data with optional configuration.
-
-    Args:
-        data: The input data to process.
-        options: Optional configuration dictionary.
-
-    Returns:
-        True if processing succeeded, False otherwise.
-
-    Raises:
-        ValueError: If data is empty or invalid.
-    """
-```
-
-#### Pydantic Model Parameters
-
-```python
-class InputParams(BaseModel):
-    """Configuration parameters for the service.
-
-    Parameters:
-        timeout: Request timeout in seconds.
-        retry_count: Number of retry attempts.
-        enable_logging: Whether to enable debug logging.
-    """
-
-    timeout: Optional[float] = None
-    retry_count: int = 3
-    enable_logging: bool = False
-```
-
----
-
-### 4. Pattern Consistency Checks
-
-#### Service Classes
-
-- Correct inheritance (`TTSService`, `STTService`, `LLMService`)
-- Consistent constructor signatures
-- Frame emission patterns
-- Metrics support:
-  - `can_generate_metrics()`
-  - TTFB metrics
-  - Usage metrics
-- Alignment with similar existing services
-
-#### Examples
-
-Validated against `examples/foundational/07-interruptible.py`:
-
-- Proper `create_transport()` usage
-- Correct pipeline structure
-- Task setup and observers
-- Event handler registration
-- Runner and bot entrypoint consistency
-
----
-
-### 5. Specific Implementation Patterns
-
-#### Service Implementation
-
-```python
-class ExampleTTSService(TTSService):
-
-    def __init__(self, *, api_key: Optional[str] = None, **kwargs):
-        super().__init__(**kwargs)
-        self._api_key = api_key or os.getenv("SERVICE_API_KEY")
-
-    def can_generate_metrics(self) -> bool:
-        return True
-
-    async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
-        try:
-            await self.start_ttfb_metrics()
-            yield TTSStartedFrame()
-            # ... processing ...
-            yield TTSAudioRawFrame(...)
-        finally:
-            await self.stop_ttfb_metrics()
-```
-
----
-
-#### Example Structure Pattern
-
-```python
-transport_params = {
-    "daily": lambda: DailyParams(...),
-    "twilio": lambda: FastAPIWebsocketParams(...),
-    "webrtc": lambda: TransportParams(...),
-}
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    stt = DeepgramSTTService(...)
-    tts = SomeTTSService(...)
-    llm = OpenAILLMService(...)
-
-    context = LLMContext(messages)
-    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(...)
-
-    pipeline = Pipeline([...])
-    task = PipelineTask(pipeline, params=..., observers=[...])
-
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        await task.queue_frames([LLMRunFrame()])
-
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-    await runner.run(task)
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-```
-
----
-
-## Execution Flow
-
-1. Fetch uncommitted and outgoing changes
-2. Categorize files (services, examples, tests, utilities)
-3. Analyze each file:
-   - Readability
-   - Performance
-   - Documentation
-   - Pattern consistency
-4. Generate actionable recommendations
-5. Apply Pipecat standards
-
----
-
-## Examples
-
-### Before: Tuple Usage
-
-```python
-def get_audio_info(self) -> Tuple[int, int]:
-    return (48000, 1)
-```
-
-### After: Named Class
-
-```python
-class AudioInfo:
-    """Audio configuration information.
-
-    Parameters:
-        sample_rate: Sample rate in Hz.
-        num_channels: Number of audio channels.
-    """
-
-    sample_rate: int
-    num_channels: int
-
-def get_audio_info(self) -> AudioInfo:
-    return AudioInfo(sample_rate=48000, num_channels=1)
-```
-
----
-
-### Before: Missing Documentation
-
-```python
-class NewTTSService(TTSService):
-    def __init__(self, api_key: str, voice: str):
-        self._api_key = api_key
-        self._voice = voice
-```
-
-### After: Fully Documented
-
-```python
-class NewTTSService(TTSService):
-    """Text-to-speech service using NewProvider API.
-
-    Streams PCM audio and emits TTSAudioRawFrame frames compatible
-    with Pipecat transports.
-
-    Supported features:
-    - Text-to-speech synthesis
-    - Streaming PCM audio
-    - Voice customization
-    - TTFB metrics
-    """
-
-    def __init__(self, *, api_key: str, voice: str, **kwargs):
-        """Initialize the NewTTSService.
-
-        Args:
-            api_key: API key for authentication.
-            voice: Voice identifier to use.
-            **kwargs: Additional arguments passed to the parent service.
-        """
-        super().__init__(**kwargs)
-        self._api_key = api_key
-        self.set_voice(voice)
-```
-
----
-
-## Notes
-
-- Non-breaking improvements only
-- Backward compatibility preserved
-- Conservative performance changes
-- Google-style docstrings
-- Pattern checks follow recent Pipecat code

.claude/skills/code-review/SKILL.md

@@ -1,107 +0,0 @@
----
-name: code-review
-description: Automated code review for pull requests using multiple specialized agents
-disable-model-invocation: true
-allowed-tools: Bash(gh issue view:*), Bash(gh search:*), Bash(gh issue list:*), Bash(gh pr comment:*), Bash(gh pr diff:*), Bash(gh pr view:*), Bash(gh pr list:*)
----
-
-Provide a code review for the given pull request.
-
-**Agent assumptions (applies to all agents and subagents):**
-
-- All tools are functional and will work without error. Do not test tools or make exploratory calls. Make sure this is clear to every subagent that is launched.
-- Only call a tool if it is required to complete the task. Every tool call should have a clear purpose.
-
-To do this, follow these steps precisely:
-
-1. Launch a haiku agent to check if any of the following are true:
-   - The pull request is closed
-   - The pull request is a draft
-   - The pull request does not need code review (e.g. automated PR, trivial change that is obviously correct)
-   - Claude has already commented on this PR (check `gh pr view <PR> --comments` for comments left by claude)
-
-   If any condition is true, stop and do not proceed.
-
-Note: Still review Claude generated PR's.
-
-2. Launch a haiku agent to return a list of file paths (not their contents) for all relevant CLAUDE.md files including:
-   - The root CLAUDE.md file, if it exists
-   - Any CLAUDE.md files in directories containing files modified by the pull request
-
-3. Launch a sonnet agent to view the pull request and return a summary of the changes
-
-4. Launch 4 agents in parallel to independently review the changes. Each agent should return the list of issues, where each issue includes a description and the reason it was flagged (e.g. "CLAUDE.md adherence", "bug"). The agents should do the following:
-
-   Agents 1 + 2: CLAUDE.md compliance sonnet agents
-   Audit changes for CLAUDE.md compliance in parallel. Note: When evaluating CLAUDE.md compliance for a file, you should only consider CLAUDE.md files that share a file path with the file or parents.
-
-   Agent 3: Opus bug agent (parallel subagent with agent 4)
-   Scan for obvious bugs. Focus only on the diff itself without reading extra context. Flag only significant bugs; ignore nitpicks and likely false positives. Do not flag issues that you cannot validate without looking at context outside of the git diff.
-
-   Agent 4: Opus bug agent (parallel subagent with agent 3)
-   Look for problems that exist in the introduced code. This could be security issues, incorrect logic, etc. Only look for issues that fall within the changed code.
-
-   **CRITICAL: We only want HIGH SIGNAL issues.** Flag issues where:
-   - The code will fail to compile or parse (syntax errors, type errors, missing imports, unresolved references)
-   - The code will definitely produce wrong results regardless of inputs (clear logic errors)
-   - Clear, unambiguous CLAUDE.md violations where you can quote the exact rule being broken
-
-   Do NOT flag:
-   - Code style or quality concerns
-   - Potential issues that depend on specific inputs or state
-   - Subjective suggestions or improvements
-
-   If you are not certain an issue is real, do not flag it. False positives erode trust and waste reviewer time.
-
-   In addition to the above, each subagent should be told the PR title and description. This will help provide context regarding the author's intent.
-
-5. For each issue found in the previous step by agents 3 and 4, launch parallel subagents to validate the issue. These subagents should get the PR title and description along with a description of the issue. The agent's job is to review the issue to validate that the stated issue is truly an issue with high confidence. For example, if an issue such as "variable is not defined" was flagged, the subagent's job would be to validate that is actually true in the code. Another example would be CLAUDE.md issues. The agent should validate that the CLAUDE.md rule that was violated is scoped for this file and is actually violated. Use Opus subagents for bugs and logic issues, and sonnet agents for CLAUDE.md violations.
-
-6. Filter out any issues that were not validated in step 5. This step will give us our list of high signal issues for our review.
-
-7. If issues were found, skip to step 8 to post comments.
-
-   If NO issues were found, post a summary comment using `gh pr comment` (if `--comment` argument is provided):
-   "No issues found. Checked for bugs and CLAUDE.md compliance."
-
-8. Create a list of all comments that you plan on leaving. This is only for you to make sure you are comfortable with the comments. Do not post this list anywhere.
-
-9. Post inline comments for each issue using `gh pr review` with inline comments. For each comment:
-   - Provide a brief description of the issue
-   - For small, self-contained fixes, include a committable suggestion block
-   - For larger fixes (6+ lines, structural changes, or changes spanning multiple locations), describe the issue and suggested fix without a suggestion block
-   - Never post a committable suggestion UNLESS committing the suggestion fixes the issue entirely. If follow up steps are required, do not leave a committable suggestion.
-
-   **IMPORTANT: Only post ONE comment per unique issue. Do not post duplicate comments.**
-
-Use this list when evaluating issues in Steps 4 and 5 (these are false positives, do NOT flag):
-
-- Pre-existing issues
-- Something that appears to be a bug but is actually correct
-- Pedantic nitpicks that a senior engineer would not flag
-- Issues that a linter will catch (do not run the linter to verify)
-- General code quality concerns (e.g., lack of test coverage, general security issues) unless explicitly required in CLAUDE.md
-- Issues mentioned in CLAUDE.md but explicitly silenced in the code (e.g., via a lint ignore comment)
-
-Notes:
-
-- Use gh CLI to interact with GitHub (e.g., fetch pull requests, create comments). Do not use web fetch.
-- Create a todo list before starting.
-- You must cite and link each issue in inline comments (e.g., if referring to a CLAUDE.md, include a link to it).
-- If no issues are found, post a comment with the following format:
-
----
-
-## Code review
-
-No issues found. Checked for bugs and CLAUDE.md compliance.
-
----
-
-- When linking to code in inline comments, follow the following format precisely, otherwise the Markdown preview won't render correctly: `https://github.com/OWNER/REPO/blob/FULL_SHA/path/to/file.py#L10-L15`
-  - Requires full git sha
-  - You must provide the full sha. Commands like `https://github.com/owner/repo/blob/$(git rev-parse HEAD)/foo/bar` will not work, since your comment will be directly rendered in Markdown.
-  - Repo name must match the repo you're code reviewing
-  - # sign after the file name
-  - Line range format is L[start]-L[end]
-  - Provide at least 1 line of context before and after, centered on the line you are commenting about (eg. if you are commenting about lines 5-6, you should link to `L4-7`)

.claude/skills/docstring/SKILL.md

@@ -1,257 +0,0 @@
----
-name: docstring
-description: Document a Python module and its classes using Google style
----
-
-Document a Python module and its classes using Google-style docstrings following project conventions. The class name is provided as an argument.
-
-## Instructions
-
-1. First, find the class in the codebase:
-   ```
-   Search for "class ClassName" in src/pipecat/
-   ```
-
-2. If multiple files contain that class name:
-   - List all matches with their file paths
-   - Ask the user which one they want to document
-   - Wait for confirmation before proceeding
-
-3. Once the file is identified, read the module to understand its structure:
-   - Identify all classes, functions, and important type aliases
-   - Understand the purpose of each component
-
-4. Apply documentation in this order:
-   - Module docstring (at top, after imports)
-   - Class docstrings
-   - `__init__` methods (always document constructor parameters)
-   - Public methods (not starting with `_`)
-   - Dataclass/config classes with field descriptions
-
-5. Skip documentation for:
-   - Private methods (starting with `_`)
-   - Simple dunder methods (`__str__`, `__repr__`, `__post_init__`)
-   - Very simple pass-through properties
-   - **Already documented code** - If a class, method, or function already has a complete docstring that follows the project style, do not modify it. A docstring is complete if it has:
-     - A one-line summary
-     - Args section (if it has parameters)
-     - Returns section (if it returns something meaningful)
-   - Only add or improve documentation where it is missing or incomplete
-
-## Module Docstring Format
-
-```python
-"""[One-line description of module purpose].
-
-[Optional: Longer explanation of functionality, key classes, or use cases.]
-"""
-```
-
-Example:
-```python
-"""Neuphonic text-to-speech service implementations.
-
-This module provides WebSocket and HTTP-based integrations with Neuphonic's
-text-to-speech API for real-time audio synthesis.
-"""
-```
-
-## Class Docstring Format
-
-```python
-class ClassName:
-    """One-line summary describing what the class does.
-
-    [Longer description explaining purpose, behavior, and key features.
-    Use action-oriented language.]
-
-    [Optional: Event handlers, usage notes, or important caveats.]
-    """
-```
-
-Example:
-```python
-class FrameProcessor(BaseObject):
-    """Base class for all frame processors in the pipeline.
-
-    Frame processors are the building blocks of Pipecat pipelines, they can be
-    linked to form complex processing pipelines. They receive frames, process
-    them, and pass them to the next or previous processor in the chain.
-
-    Event handlers available:
-
-    - on_before_process_frame: Called before a frame is processed
-    - on_after_process_frame: Called after a frame is processed
-
-    Example::
-
-        @processor.event_handler("on_before_process_frame")
-        async def on_before_process_frame(processor, frame):
-            ...
-
-        @processor.event_handler("on_after_process_frame")
-        async def on_after_process_frame(processor, frame):
-            ...
-    """
-```
-
-Note: When listing event handlers, do NOT use backticks. Include an `Example::` section (with double colon for Sphinx) showing the decorator pattern and function signature for each event.
-
-## Constructor (`__init__`) Format
-
-```python
-def __init__(self, *, param1: Type, param2: Type = default, **kwargs):
-    """Initialize the [ClassName].
-
-    Args:
-        param1: Description of param1 and its purpose.
-        param2: Description of param2. Defaults to [default].
-        **kwargs: Additional arguments passed to parent class.
-    """
-```
-
-Example:
-```python
-def __init__(
-    self,
-    *,
-    api_key: str,
-    voice_id: Optional[str] = None,
-    sample_rate: Optional[int] = 22050,
-    **kwargs,
-):
-    """Initialize the Neuphonic TTS service.
-
-    Args:
-        api_key: Neuphonic API key for authentication.
-        voice_id: ID of the voice to use for synthesis.
-        sample_rate: Audio sample rate in Hz. Defaults to 22050.
-        **kwargs: Additional arguments passed to parent InterruptibleTTSService.
-    """
-```
-
-## Method Docstring Format
-
-```python
-async def method_name(self, param1: Type) -> ReturnType:
-    """One-line summary of what method does.
-
-    [Longer description if behavior isn't obvious.]
-
-    Args:
-        param1: Description of param1.
-
-    Returns:
-        Description of return value.
-
-    Raises:
-        ExceptionType: When this exception is raised.
-    """
-```
-
-Example:
-```python
-async def put(self, item: Tuple[Frame, FrameDirection, FrameCallback]):
-    """Put an item into the priority queue.
-
-    System frames (`SystemFrame`) have higher priority than any other
-    frames. If a non-frame item is provided it will have the highest priority.
-
-    Args:
-        item: The item to enqueue.
-    """
-```
-
-## Dataclass/Config Format
-
-```python
-@dataclass
-class ConfigName:
-    """One-line description of configuration.
-
-    [Explanation of when/how to use this config.]
-
-    Parameters:
-        field1: Description of field1.
-        field2: Description of field2. Defaults to [default].
-    """
-
-    field1: Type
-    field2: Type = default_value
-```
-
-Example:
-```python
-@dataclass
-class FrameProcessorSetup:
-    """Configuration parameters for frame processor initialization.
-
-    Parameters:
-        clock: The clock instance for timing operations.
-        task_manager: The task manager for handling async operations.
-        observer: Optional observer for monitoring frame processing events.
-    """
-
-    clock: BaseClock
-    task_manager: BaseTaskManager
-    observer: Optional[BaseObserver] = None
-```
-
-## Enum Documentation Format
-
-```python
-class EnumName(Enum):
-    """One-line description of the enum purpose.
-
-    [Longer description of how the enum is used.]
-
-    Parameters:
-        VALUE1: Description of VALUE1.
-        VALUE2: Description of VALUE2.
-    """
-
-    VALUE1 = 1
-    VALUE2 = 2
-```
-
-## Writing Style Guidelines
-
-- **Concise and professional** - No casual language or filler words
-- **Action-oriented** - Start with verbs: "Processes...", "Manages...", "Converts..."
-- **Purpose before implementation** - Explain WHY before HOW
-- **Clear parameter descriptions** - Include type hints, defaults, and purpose
-- **No redundant type info** - Type hints are in the signature, don't repeat in description
-- **Use backticks for code references** - Wrap class names, method names, event names, parameter names, and code snippets in backticks
-
-Good: "Neuphonic API key for authentication."
-Bad: "str: The API key (string) that is used for authenticating with Neuphonic."
-
-Good: "Triggers `on_speech_started` when the `VADAnalyzer` detects speech."
-Bad: "Triggers on_speech_started when the VADAnalyzer detects speech."
-
-## Deprecation Notice Format
-
-When documenting deprecated code:
-
-```python
-"""[Description].
-
-.. deprecated:: X.X.X
-    `ClassName` is deprecated and will be removed in a future version.
-    Use `NewClassName` instead.
-"""
-```
-
-## Checklist
-
-Before finishing, verify:
-
-- [ ] Module has a docstring at the top (after copyright header and imports)
-- [ ] All public classes have docstrings
-- [ ] All `__init__` methods document their parameters
-- [ ] All public methods have docstrings with Args/Returns/Raises as needed
-- [ ] Dataclasses use "Parameters:" section for field descriptions
-- [ ] Enums document each value in "Parameters:" section
-- [ ] Writing is concise and action-oriented
-- [ ] No documentation added to private methods (starting with `_`)
-- [ ] Existing complete docstrings were left unchanged

.claude/skills/pr-description/SKILL.md

@@ -1,128 +0,0 @@
----
-name: pr-description
-description: Update a GitHub PR description with a summary of changes
----
-
-Update a GitHub pull request description based on the changes in the PR.
-
-## Arguments
-
-```
-/pr-description <PR_NUMBER> [--fixes <ISSUE_NUMBERS>]
-```
-
-- `PR_NUMBER` (required): The pull request number to update
-- `--fixes` (optional): Comma-separated issue numbers that this PR fixes (e.g., `--fixes 123,456`)
-
-Examples:
-- `/pr-description 3534`
-- `/pr-description 3534 --fixes 123`
-- `/pr-description 3534 --fixes 123,456,789`
-
-## Instructions
-
-1. First, gather information about the PR:
-   - Use GitHub plugin to get PR details (title, current description, base branch)
-   - Use local git to get commits: `git log main..HEAD --oneline`
-   - Use local git to get the diff: `git diff main..HEAD`
-   - Parse any `--fixes` argument for issue numbers
-
-2. Check the existing PR description:
-   - If it already has a complete, accurate description that reflects the changes, do nothing
-   - If it's missing sections, incomplete, or outdated compared to the actual changes, proceed to update
-   - If it only has the template placeholder text, generate a full description
-
-3. Analyze the changes:
-   - Understand the purpose of each commit
-   - Identify any breaking changes (API changes, removed features, behavior changes)
-   - Look for new features, bug fixes, refactoring, or documentation changes
-   - Collect issue numbers from:
-     - The `--fixes` argument (if provided)
-     - Commit messages (patterns like "Fixes #123", "Closes #456", "Resolves #789")
-
-4. Generate or update the PR description with these sections:
-
-## PR Description Format
-
-### Summary (always include)
-
-Brief bullet points describing what changed and why. Focus on the *purpose* and *impact*, not implementation details.
-
-```markdown
-## Summary
-
-- Added X to enable Y
-- Fixed bug where Z would happen
-- Refactored W for better maintainability
-```
-
-### Breaking Changes (include only if applicable)
-
-Document any changes that affect existing users or APIs.
-
-```markdown
-## Breaking Changes
-
-- `ClassName.method()` now requires a `param` argument
-- Removed deprecated `old_function()` - use `new_function()` instead
-```
-
-### Testing (include when non-obvious)
-
-How to verify the changes work. Skip for trivial changes.
-
-```markdown
-## Testing
-
-- Run `uv run pytest tests/test_feature.py` to verify the fix
-- Example usage: `uv run examples/new_feature.py`
-```
-
-### Fixes (include if issues are provided or found in commits)
-
-List issues this PR fixes. GitHub will automatically close these issues when the PR is merged.
-
-```markdown
-## Fixes
-
-- Fixes #123
-- Fixes #456
-```
-
-Note: Use "Fixes #X" format (not "Closes" or "Resolves") for consistency. Each issue should be on its own line with "Fixes" to ensure GitHub auto-closes them.
-
-## Guidelines
-
-- **Be concise** - Reviewers should understand the PR in 30 seconds
-- **Focus on why** - The diff shows *what* changed, explain *why*
-- **Skip empty sections** - Only include sections that have content
-- **Use bullet points** - Easier to scan than paragraphs
-- **Don't duplicate the diff** - Avoid listing every file or line changed
-
-## Example Output
-
-```markdown
-## Summary
-
-- Added `/docstring` skill for documenting Python modules with Google-style docstrings
-- Skill finds classes by name and handles conflicts when multiple matches exist
-- Skips already-documented code to avoid unnecessary changes
-
-## Testing
-
-/docstring ClassName
-
-## Fixes
-
-- Fixes #123
-```
-
-## Checklist
-
-Before updating the PR:
-
-- [ ] Verified existing description needs updating (not already complete)
-- [ ] Summary accurately reflects the changes
-- [ ] Breaking changes are clearly documented (if any)
-- [ ] No unnecessary sections included
-- [ ] Description is concise and scannable

.claude/skills/pr-submit/SKILL.md

@@ -1,28 +0,0 @@
----
-name: pr-submit
-description: Create and submit a GitHub PR from the current branch
----
-
-Submit the current changes as a GitHub pull request.
-
-## Instructions
-
-1. Check the current state of the repository:
-   - Run `git status` to see staged, unstaged, and untracked changes
-   - Run `git diff` to see current changes
-   - Run `git log --oneline -10` to see recent commits
-
-2. If there are uncommitted changes relevant to the PR:
-   - Ask the user if they want a specific prefix for the branch name (e.g., `alice/`, `fix/`, `feat/`)
-   - Create a new branch based on the current branch
-   - Commit the changes using multiple commits if the changes are unrelated
-
-3. Push the branch and create the PR:
-   - Push with `-u` flag to set upstream tracking
-   - Create the PR using `gh pr create`
-
-4. After the PR is created:
-   - Run `/changelog <pr_number>` to generate changelog files, then commit and push them
-   - Run `/pr-description <pr_number>` to update the PR description
-
-5. Return the PR URL to the user.

.claude/skills/update-docs/SKILL.md

@@ -1,250 +0,0 @@
----
-name: update-docs
-description: Update documentation pages to match source code changes on the current branch
----
-
-Update documentation pages to reflect source code changes on the current branch. Analyzes the diff against main, maps changed source files to their corresponding doc pages, and makes targeted edits.
-
-## Arguments
-
-```
-/update-docs [DOCS_PATH]
-```
-
-- `DOCS_PATH` (optional): Path to the docs repository root. If not provided, ask the user.
-
-Examples:
-- `/update-docs /Users/me/src/docs`
-- `/update-docs`
-
-## Instructions
-
-### Step 1: Resolve docs path
-
-If `DOCS_PATH` was provided as an argument, use it. Otherwise, ask the user for the path to their docs repository.
-
-Verify the path exists and contains `server/services/` subdirectory.
-
-### Step 2: Create docs branch
-
-Get the current pipecat branch name:
-```bash
-git rev-parse --abbrev-ref HEAD
-```
-
-In the docs repo, create a new branch off main with a matching name:
-```bash
-cd DOCS_PATH && git checkout main && git pull && git checkout -b {branch-name}-docs
-```
-
-For example, if the pipecat branch is `feat/new-service`, the docs branch becomes `feat/new-service-docs`.
-
-All doc edits in subsequent steps are made on this branch.
-
-### Step 3: Detect changed source files
-
-Run:
-```bash
-git diff main..HEAD --name-only
-```
-
-Filter to files that could affect documentation:
-- `src/pipecat/services/**/*.py` (service implementations)
-- `src/pipecat/transports/**/*.py` (transport implementations)
-- `src/pipecat/serializers/**/*.py` (serializer implementations)
-- `src/pipecat/processors/**/*.py` (processor implementations)
-- `src/pipecat/audio/**/*.py` (audio utilities)
-- `src/pipecat/turns/**/*.py` (turn management)
-- `src/pipecat/observers/**/*.py` (observers)
-- `src/pipecat/pipeline/**/*.py` (pipeline core)
-
-Ignore `__init__.py`, `__pycache__`, test files, and files that only contain type re-exports.
-
-### Step 4: Map source files to doc pages
-
-For each changed source file, find the corresponding doc page. Read the mapping file at `.claude/skills/update-docs/SOURCE_DOC_MAPPING.md` and apply its tiered lookup: tier 1 (known exceptions) → tier 2 (pattern matching) → tier 3 (search fallback). **First match wins.**
-
-### Step 5: Analyze each source-doc pair
-
-For each mapped pair:
-
-1. **Read the full source file** to understand current state
-2. **Read the diff** for that file: `git diff main..HEAD -- <source_file>`
-3. **Read the current doc page** in full
-
-Identify what changed by comparing source to docs:
-
-- **Constructor parameters**: Compare `__init__` signature to the Configuration section's `<ParamField>` entries
-- **InputParams fields**: Compare `InputParams(BaseModel)` class fields to the InputParams table
-- **Event handlers**: Compare `_register_event_handler` calls and event handler definitions to Event Handlers section
-- **Class names / imports**: Check if Usage examples reference correct names
-- **Behavioral changes**: Check if Notes section needs updating
-
-### Step 6: Make targeted edits
-
-For each doc page that needs updates, edit **only the sections that need changes**. Preserve all other content exactly as-is.
-
-#### Rules
-
-- **Never remove content** unless the corresponding source code was removed
-- **Never rewrite sections** that are already accurate
-- **Match existing formatting** — if the page uses `<ParamField>` tags, use them; if it uses tables, use tables
-- **Keep descriptions concise** — match the tone and length of surrounding content
-- **Preserve CardGroup, links, and examples** unless they reference removed functionality
-- **Don't touch frontmatter** unless the class was renamed
-
-#### Section-specific guidance
-
-**Configuration** (constructor params):
-- Use `<ParamField path="name" type="type" default="value">` format if the page already uses it
-- Add new params in logical order (required first, then optional)
-- Remove params that no longer exist in source
-- Update types/defaults that changed
-
-**InputParams** (runtime settings):
-- Use markdown table format: `| Parameter | Type | Default | Description |`
-- Match the field names and types from the `InputParams(BaseModel)` class
-- Include the default values from the source
-
-**Usage** (code examples):
-- Update import paths, class names, and parameter names
-- Only modify examples if they would break or be misleading with the new API
-- Don't rewrite working examples just to add new optional params
-
-**Notes**:
-- Add notes for new behavioral gotchas or breaking changes
-- Remove notes about limitations that were fixed
-- Keep existing notes that are still accurate
-
-**Event Handlers**:
-- Update the event table and example code
-- Add new events, remove deleted ones
-- Update handler signatures if they changed
-
-**Overview / Key Features / Prerequisites**:
-- Only update if the PR fundamentally changes what the service does (new capability, removed capability, renamed class)
-- Most PRs will NOT need changes to these sections
-
-### Step 7: Update guides
-
-Guides at `DOCS_PATH/guides/` reference specific class names, parameters, imports, and code patterns. After completing reference doc edits, check if any guides need updates too.
-
-For each changed source file, collect the class names, renamed parameters, and changed imports from the diff. Search the guides directory:
-```bash
-grep -rl "ClassName\|old_param_name" DOCS_PATH/guides/
-```
-
-For each guide that references changed code:
-1. Read the full guide
-2. Update class names, parameter names, import paths, and code examples that are now incorrect
-3. **Don't rewrite prose** — only fix the specific references that changed
-4. Leave guides alone if they reference the service generally but don't use any changed APIs
-
-Guide directories:
-- `guides/learn/` — conceptual tutorials (pipeline, LLM, STT, TTS, etc.)
-- `guides/fundamentals/` — practical how-tos (metrics, recording, transcripts, etc.)
-- `guides/features/` — feature-specific guides (Gemini Live, OpenAI audio, WhatsApp, etc.)
-- `guides/telephony/` — telephony integration guides (Twilio, Plivo, Telnyx, etc.)
-
-### Step 8: Identify doc gaps
-
-After processing all mapped pairs, check for two kinds of gaps:
-
-**Missing pages**: Source files that had no doc page mapping (neither tier 1, 2, nor 3) and are not marked as "(skip)". For each, tell the user:
-- The source file path
-- The main class(es) it defines
-- Whether a new doc page should be created
-
-**Missing sections**: Mapped doc pages that are missing standard sections compared to the source. For example, a transport page with no Configuration section, or a service page with no InputParams table when the source defines `InputParams(BaseModel)`. Flag these and offer to add the missing sections.
-
-If the user wants a new page, create it using this template structure:
-```
----
-title: "Service Name"
-description: "Brief description"
----
-
-## Overview
-
-[Description from class docstring or source analysis]
-
-<CardGroup cols={2}>
-  [Cards for API reference and examples if available]
-</CardGroup>
-
-## Installation
-
-```bash
-pip install "pipecat-ai[package-name]"
-```
-
-## Prerequisites
-
-[Environment variables and account setup]
-
-## Configuration
-
-[ParamField entries for constructor params]
-
-## InputParams
-
-[Table of InputParams fields, if the service has them]
-
-## Usage
-
-### Basic Setup
-
-```python
-[Minimal working example]
-```
-
-## Notes
-
-[Important caveats]
-
-## Event Handlers
-
-[Event table and example code]
-```
-
-### Step 9: Output summary
-
-After all edits are complete, print a summary:
-
-```
-## Documentation Updates
-
-### Updated reference pages
-- `server/services/stt/deepgram.mdx` — Updated Configuration (added `new_param`), InputParams (updated `language` default)
-- `server/services/tts/elevenlabs.mdx` — Updated Event Handlers (added `on_connected`)
-
-### Updated guides
-- `guides/learn/speech-to-text.mdx` — Updated code example (renamed `old_param` → `new_param`)
-
-### Unmapped source files
-- `src/pipecat/services/newprovider/tts.py` — NewProviderTTSService (no doc page exists)
-
-### Skipped files
-- `src/pipecat/services/ai_service.py` — internal base class
-```
-
-## Guidelines
-
-- **Be conservative** — only change what the diff warrants. Don't "improve" docs beyond what changed in source.
-- **Read before editing** — always read the full doc page before making changes so you understand the existing structure.
-- **Preserve voice** — match the writing style of the existing doc page, don't impose a different tone.
-- **One PR at a time** — this skill operates on the current branch's diff against main. Don't look at other branches.
-- **Parallel analysis** — when multiple source files map to different doc pages, analyze and edit them in parallel for efficiency.
-- **Shared source files** — files like `services/google/google.py` are shared bases. Check which services import from them and update all affected doc pages.
-
-## Checklist
-
-Before finishing, verify:
-
-- [ ] All changed source files were checked against the mapping table
-- [ ] Each doc page edit matches the actual source code change (not guessed)
-- [ ] No content was removed unless the corresponding source was removed
-- [ ] New parameters have accurate types and defaults from source
-- [ ] Formatting matches the existing page style
-- [ ] Guides referencing changed APIs were checked and updated
-- [ ] Unmapped files were reported to the user

.claude/skills/update-docs/SOURCE_DOC_MAPPING.md

@@ -1,79 +0,0 @@
-# Source-to-Doc Mapping
-
-Maps pipecat source files to their documentation pages. Source paths are relative to `src/pipecat/`. Doc paths are relative to `DOCS_PATH`.
-
-## Name mismatches
-
-These source paths don't follow the standard `services/{provider}/{type}.py` → `server/services/{type}/{provider}.mdx` pattern.
-
-| Source path | Doc page |
-|---|---|
-| `services/google/llm.py` | `server/services/llm/gemini.mdx` |
-| `services/google/llm_vertex.py` | `server/services/llm/google-vertex.mdx` |
-| `services/google/google.py` | (shared base — check which services use it) |
-| `services/google/gemini_live/**` | `server/services/s2s/gemini-live.mdx` |
-| `services/google/gemini_live/llm_vertex.py` | `server/services/s2s/gemini-live-vertex.mdx` |
-| `services/aws_nova_sonic/**` | `server/services/s2s/aws.mdx` |
-| `services/ultravox/**` | `server/services/s2s/ultravox.mdx` |
-| `services/grok/realtime/**` | `server/services/s2s/grok.mdx` |
-| `services/openai/realtime/**` | `server/services/s2s/openai.mdx` |
-| `processors/frameworks/rtvi.py` | `server/frameworks/rtvi/rtvi-processor.mdx` and `server/frameworks/rtvi/rtvi-observer.mdx` |
-| `processors/transcript_processor.py` | `server/utilities/transcript-processor.mdx` |
-| `processors/user_idle_processor.py` | `server/utilities/user-idle-processor.mdx` |
-| `processors/idle_frame_processor.py` | `server/pipeline/pipeline-idle-detection.mdx` |
-| `pipeline/task.py` | `server/pipeline/pipeline-task.mdx` |
-| `pipeline/runner.py` | `server/utilities/runner/guide.mdx` |
-| `transports/base_transport.py` | `server/services/transport/transport-params.mdx` |
-
-## Skip list
-
-These files should never trigger doc updates.
-
-| Pattern | Reason |
-|---|---|
-| `services/ai_service.py` | Internal base class |
-| `services/stt_service.py` | Internal base class |
-| `services/tts_service.py` | Internal base class |
-| `services/llm_service.py` | Internal base class |
-| `services/websocket_service.py` | Internal base class |
-| `services/openai_realtime_beta/**` | Deprecated |
-| `services/openai_realtime/**` | Deprecated |
-| `services/gemini_multimodal_live/**` | Deprecated |
-| `services/aws/agent_core.py` | Internal |
-| `services/aws/sagemaker/**` | No doc page |
-| `transports/base_input.py` | Internal base class |
-| `transports/base_output.py` | Internal base class |
-| `transports/websocket/client.py` | No doc page |
-| `serializers/base_serializer.py` | Internal base class |
-| `serializers/protobuf.py` | Internal |
-| `processors/audio/**` | Internal |
-| `pipeline/pipeline.py` | Core architecture, not a service doc |
-
-## Pattern matching
-
-For files not in the tables above, apply these patterns. Convert underscores to hyphens in provider names for doc filenames.
-
-| Source pattern | Doc pattern |
-|---|---|
-| `services/{provider}/stt*.py` | `server/services/stt/{provider}.mdx` |
-| `services/{provider}/tts*.py` | `server/services/tts/{provider}.mdx` |
-| `services/{provider}/llm*.py` | `server/services/llm/{provider}.mdx` |
-| `services/{provider}/image*.py` | `server/services/image-generation/{provider}.mdx` |
-| `services/{provider}/video*.py` | `server/services/video/{provider}.mdx` |
-| `services/{provider}/realtime/**` | `server/services/s2s/{provider}.mdx` |
-| `transports/{name}/**` | `server/services/transport/{name}.mdx` |
-| `serializers/{name}.py` | `server/services/serializers/{name}.mdx` |
-| `observers/**` | `server/utilities/observers/` (match by class name) |
-| `audio/vad/**` | `server/utilities/audio/` (match by class name) |
-| `audio/filters/**` | `server/utilities/audio/` (match by class name) |
-| `audio/mixers/**` | `server/utilities/audio/` (match by class name) |
-| `processors/filters/**` | `server/utilities/filters/` (match by class name) |
-
-If the doc file doesn't exist at the resolved path, the file is **unmapped**.
-
-## Search fallback
-
-For files that don't match any table or pattern above:
-1. Extract the main class name(s) from the source file
-2. Search the docs directory for that class name: `grep -r "ClassName" DOCS_PATH/server/`
-3. If found in a doc page, use that as the mapping

.github/ISSUE_TEMPLATE/1-bug_report.yml

@@ -1,87 +0,0 @@
-name: Bug report
-description: Report a bug or unexpected behavior
-type: Bug
-body:
-  - type: markdown
-    attributes:
-      value: |
-        ## Bug Report
-
-        Thank you for taking the time to fill out this bug report.
-
-  - type: markdown
-    attributes:
-      value: |
-        ### Environment
-
-  - type: input
-    id: pipecat-version
-    attributes:
-      label: pipecat version
-      description: Which version are you using?
-      placeholder: e.g., 0.0.63
-    validations:
-      required: true
-
-  - type: input
-    id: python-version
-    attributes:
-      label: Python version
-      description: Which Python version are you using?
-      placeholder: e.g., 3.12.8
-    validations:
-      required: true
-
-  - type: input
-    id: os
-    attributes:
-      label: Operating System
-      description: Which OS are you using?
-      placeholder: e.g., Ubuntu 24.04, Windows 11, macOS 12.5
-    validations:
-      required: true
-
-  - type: textarea
-    id: description
-    attributes:
-      label: Issue description
-      description: Provide a clear description of the issue.
-    validations:
-      required: true
-
-  - type: textarea
-    id: repro
-    attributes:
-      label: Reproduction steps
-      description: List the steps to reproduce the issue.
-      placeholder: |
-        1. Do this...
-        2. Then do that...
-        3. Observe the error...
-    validations:
-      required: true
-
-  - type: textarea
-    id: expected
-    attributes:
-      label: Expected behavior
-      description: What did you expect to happen?
-    validations:
-      required: true
-
-  - type: textarea
-    id: actual
-    attributes:
-      label: Actual behavior
-      description: What actually happened?
-    validations:
-      required: true
-
-  - type: textarea
-    id: logs
-    attributes:
-      label: Logs
-      description: If applicable, include any relevant logs or error messages
-      render: shell
-    validations:
-      required: false

.github/ISSUE_TEMPLATE/2-question.yml

@@ -1,67 +0,0 @@
-name: Question
-description: Ask a question or get help
-type: Question
-body:
-  - type: markdown
-    attributes:
-      value: |
-        ## Question
-
-        Use this form to ask a question about pipecat.
-
-  - type: markdown
-    attributes:
-      value: |
-        ### Environment (if applicable)
-
-  - type: input
-    id: pipecat-version
-    attributes:
-      label: pipecat version
-      description: Which version are you using? (if applicable)
-      placeholder: e.g., 0.0.63
-    validations:
-      required: false
-
-  - type: input
-    id: python-version
-    attributes:
-      label: Python version
-      description: Which Python version are you using? (if applicable)
-      placeholder: e.g., 3.12.8
-    validations:
-      required: false
-
-  - type: input
-    id: os
-    attributes:
-      label: Operating System
-      description: Which OS are you using? (if applicable)
-      placeholder: e.g., Ubuntu 24.04, Windows 11, macOS 12.5
-    validations:
-      required: false
-
-  - type: textarea
-    id: question
-    attributes:
-      label: Question
-      description: Provide your question in detail here.
-    validations:
-      required: true
-
-  - type: textarea
-    id: tried
-    attributes:
-      label: What I've tried
-      description: Describe what you've already tried or research you've done.
-      placeholder: I've looked at the documentation and tried...
-    validations:
-      required: false
-
-  - type: textarea
-    id: context
-    attributes:
-      label: Context
-      description: Any additional context or information that might help others understand your question better.
-    validations:
-      required: false

.github/ISSUE_TEMPLATE/3-feature_request.yml

@@ -1,52 +0,0 @@
-name: Feature request
-description: Suggest an enhancement or new feature
-type: Enhancement
-body:
-  - type: markdown
-    attributes:
-      value: |
-        ## Feature Request
-
-        Thank you for suggesting an enhancement to pipecat.
-
-  - type: textarea
-    id: problem
-    attributes:
-      label: Problem Statement
-      description: A clear description of the problem this feature would solve.
-      placeholder: I'm always frustrated when...
-    validations:
-      required: true
-
-  - type: textarea
-    id: solution
-    attributes:
-      label: Proposed Solution
-      description: A clear and concise description of what you want to happen.
-    validations:
-      required: true
-
-  - type: textarea
-    id: alternatives
-    attributes:
-      label: Alternative Solutions
-      description: Any alternative solutions or features you've considered.
-    validations:
-      required: false
-
-  - type: textarea
-    id: context
-    attributes:
-      label: Additional Context
-      description: Add any other context, mockups, or screenshots about the feature request here.
-      placeholder: You can drag and drop images here to include them.
-    validations:
-      required: false
-
-  - type: checkboxes
-    id: contribution
-    attributes:
-      label: Would you be willing to help implement this feature?
-      options:
-        - label: Yes, I'd like to contribute
-        - label: No, I'm just suggesting

.github/ISSUE_TEMPLATE/4-service-issue.yml

@@ -1,82 +0,0 @@
-name: Service Issue
-description: An issue with a third-party service
-type: Service Issue
-body:
-  - type: markdown
-    attributes:
-      value: |
-        ## Service Issue
-
-        Use this form to report an issue with a third-party service integration.
-
-  - type: input
-    id: pipecat-version
-    attributes:
-      label: pipecat version
-      description: Which version are you using?
-      placeholder: e.g., 0.0.63
-    validations:
-      required: true
-
-  - type: input
-    id: service-name
-    attributes:
-      label: Service Name
-      description: Which third-party service is having issues?
-      placeholder: e.g., OpenAI, ElevenLabs, Anthropic
-    validations:
-      required: true
-
-  - type: input
-    id: service-version
-    attributes:
-      label: Service or model version
-      description: Which version of the service API or model are you using?
-      placeholder: e.g., v1, gpt-4.1
-    validations:
-      required: false
-
-  - type: textarea
-    id: description
-    attributes:
-      label: Issue Description
-      description: Provide a clear description of the service issue.
-    validations:
-      required: true
-
-  - type: textarea
-    id: reproduction
-    attributes:
-      label: Reproduction Steps
-      description: Provide steps to reproduce the issue.
-      placeholder: |
-        1. Configure service X
-        2. Call method Y
-        3. See error Z
-    validations:
-      required: true
-
-  - type: textarea
-    id: expected
-    attributes:
-      label: Expected Behavior
-      description: What did you expect to happen?
-    validations:
-      required: true
-
-  - type: textarea
-    id: actual
-    attributes:
-      label: Actual Behavior
-      description: What actually happened?
-    validations:
-      required: true
-
-  - type: textarea
-    id: logs
-    attributes:
-      label: Error Logs
-      description: If available, include any error messages or logs.
-      render: shell
-    validations:
-      required: false

.github/ISSUE_TEMPLATE/5-new-service.yml

@@ -1,56 +0,0 @@
-name: New Service
-description: Request to support a new third-party service
-type: New Service
-body:
-  - type: markdown
-    attributes:
-      value: |
-        ## New Service Request
-
-        Use this form to request support for a new third-party service in pipecat.
-
-  - type: input
-    id: service-name
-    attributes:
-      label: Service Name
-      description: What is the name of the third-party service?
-      placeholder: e.g., NewAPI, SomeService
-    validations:
-      required: true
-
-  - type: input
-    id: service-website
-    attributes:
-      label: Service Website
-      description: Link to the service's website or documentation
-      placeholder: e.g., https://newapi.com
-    validations:
-      required: true
-
-  - type: textarea
-    id: service-description
-    attributes:
-      label: Service Description
-      description: Briefly describe what this service does and how it works.
-    validations:
-      required: true
-
-  - type: textarea
-    id: api-info
-    attributes:
-      label: API Information
-      description: If available, provide details about the service's API.
-      placeholder: |
-        - API documentation link
-        - Authentication method
-        - Key endpoints you'd like supported
-    validations:
-      required: false
-
-  - type: checkboxes
-    id: contribution
-    attributes:
-      label: Would you be willing to help implement this service?
-      options:
-        - label: Yes, I'd like to contribute
-        - label: No, I'm just suggesting

.github/ISSUE_TEMPLATE/6-dependency.yml

@@ -1,74 +0,0 @@
-name: Dependency Issue
-description: An issue with a Pipecat dependency (not a third-party service)
-type: Dependency Issue
-body:
-  - type: markdown
-    attributes:
-      value: |
-        ## Dependency Issue
-
-        Use this form to report an issue with a Pipecat dependency.
-
-  - type: input
-    id: pipecat-version
-    attributes:
-      label: pipecat version
-      description: Which version are you using?
-      placeholder: e.g., 0.0.63
-    validations:
-      required: true
-
-  - type: input
-    id: dependency-name
-    attributes:
-      label: Dependency Name
-      description: Which Pipecat dependency is causing the issue?
-      placeholder: e.g., openai, anthropic, fastapi
-    validations:
-      required: true
-
-  - type: input
-    id: dependency-version
-    attributes:
-      label: Dependency Version
-      description: Which version of the dependency are you using?
-      placeholder: e.g., 1.2.3
-    validations:
-      required: true
-
-  - type: textarea
-    id: description
-    attributes:
-      label: Issue Description
-      description: Provide a clear description of the dependency issue.
-    validations:
-      required: true
-
-  - type: textarea
-    id: impact
-    attributes:
-      label: Impact
-      description: How is this dependency issue affecting your usage of pipecat?
-    validations:
-      required: true
-
-  - type: textarea
-    id: reproduction
-    attributes:
-      label: Reproduction Steps
-      description: If applicable, provide steps to reproduce the issue.
-      placeholder: |
-        1. Install dependency X
-        2. Run command Y
-        3. See error Z
-    validations:
-      required: false
-
-  - type: textarea
-    id: logs
-    attributes:
-      label: Error Logs
-      description: If applicable, include any relevant error messages or logs.
-      render: shell
-    validations:
-      required: false

.github/ISSUE_TEMPLATE/7-troubleshooting.yml

@@ -1,70 +0,0 @@
-name: Troubleshooting
-description: Help with a specific use case
-type: Troubleshooting
-body:
-  - type: markdown
-    attributes:
-      value: |
-        ## Troubleshooting Request
-
-        Use this form to get help with a specific use case or implementation.
-
-  - type: input
-    id: pipecat-version
-    attributes:
-      label: pipecat version
-      description: Which version are you using?
-      placeholder: e.g., 0.0.63
-    validations:
-      required: true
-
-  - type: input
-    id: python-version
-    attributes:
-      label: Python version
-      description: Which version of Python are you using?
-      placeholder: e.g., 3.12.8
-    validations:
-      required: true
-
-  - type: input
-    id: os
-    attributes:
-      label: Operating System
-      description: Which OS are you using?
-      placeholder: e.g., Ubuntu 24.04, Windows 11, macOS 12.5
-    validations:
-      required: true
-
-  - type: textarea
-    id: use-case
-    attributes:
-      label: Use Case Description
-      description: Describe what you're trying to accomplish with pipecat.
-    validations:
-      required: true
-
-  - type: textarea
-    id: current-approach
-    attributes:
-      label: Current Approach
-      description: What have you tried so far? Include code snippets if relevant.
-      render: python
-    validations:
-      required: true
-
-  - type: textarea
-    id: errors
-    attributes:
-      label: Errors or Unexpected Behavior
-      description: Describe any errors or unexpected behavior you're encountering.
-    validations:
-      required: true
-
-  - type: textarea
-    id: additional-context
-    attributes:
-      label: Additional Context
-      description: Any other information that might help us understand your situation.
-    validations:
-      required: false

.github/ISSUE_TEMPLATE/config.yml

@@ -1 +0,0 @@
-blank_issues_enabled: false

.github/PULL_REQUEST_TEMPLATE.md

@@ -1 +0,0 @@
-#### Please describe the changes in your PR. If it is addressing an issue, please reference that as well.

.github/workflows/build.yaml

@@ -21,20 +21,24 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v3
-        with:
-          version: "latest"
-
       - name: Set up Python
-        run: uv python install 3.12
-
-      - name: Install development dependencies
-        run: uv sync --group dev
-
+        id: setup_python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+      - name: Setup virtual environment
+        run: |
+          python -m venv .venv
+      - name: Install basic Python dependencies
+        run: |
+          source .venv/bin/activate
+          python -m pip install --upgrade pip
+          pip install -r dev-requirements.txt
       - name: Build project
-        run: uv build
-
-      - name: Install project in editable mode
-        run: uv pip install --editable .
+        run: |
+          source .venv/bin/activate
+          python -m build
+      - name: Install project and other Python dependencies
+        run: |
+          source .venv/bin/activate
+          pip install --editable .

.github/workflows/coverage.yaml

@@ -1,57 +0,0 @@
-name: coverage
-
-on:
-  workflow_dispatch:
-  push:
-    branches:
-      - main
-  pull_request:
-    branches:
-      - "**"
-    paths-ignore:
-      - "docs/**"
-
-jobs:
-  coverage:
-    name: "Coverage"
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repo
-        uses: actions/checkout@v4
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v3
-        with:
-          version: "latest"
-
-      - name: Set up Python
-        run: uv python install 3.12
-
-      - name: Install system packages
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y portaudio19-dev
-
-      - name: Install dependencies
-        run: |
-          uv sync --group dev \
-            --extra anthropic \
-            --extra aws \
-            --extra google \
-            --extra langchain \
-            --extra livekit \
-            --extra local-smart-turn-v3 \
-            --extra piper \
-            --extra tracing \
-            --extra websocket
-
-      - name: Run tests with coverage
-        run: |
-          uv run coverage run
-          uv run coverage xml
-
-      - name: Upload coverage to Codecov
-        uses: codecov/codecov-action@v5
-        with:
-          token: ${{ secrets.CODECOV_TOKEN }}
-          slug: pipecat-ai/pipecat

.github/workflows/format.yaml

@@ -1,43 +0,0 @@
-name: format
-
-on:
-  workflow_dispatch:
-  push:
-    branches:
-      - main
-  pull_request:
-    branches:
-      - "**"
-    paths-ignore:
-      - "docs/**"
-
-concurrency:
-  group: build-format-${{ github.event.pull_request.number || github.ref }}
-  cancel-in-progress: true
-
-jobs:
-  ruff-format:
-    name: "Code quality checks"
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repo
-        uses: actions/checkout@v4
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v3
-        with:
-          version: "latest"
-
-      - name: Set up Python
-        run: uv python install 3.12
-
-      - name: Install development dependencies
-        run: uv sync --group dev
-
-      - name: Ruff formatter
-        id: ruff-format
-        run: uv run ruff format --diff
-
-      - name: Ruff linter (all rules)
-        id: ruff-check
-        run: uv run ruff check

.github/workflows/generate-changelog.yml

@@ -1,174 +0,0 @@
-name: Generate Changelog for Release
-
-on:
-  workflow_dispatch:
-    inputs:
-      version:
-        description: "Release version (e.g., 0.0.97)"
-        required: true
-        type: string
-      date:
-        description: "Release date (YYYY-MM-DD format, defaults to today)"
-        required: false
-        type: string
-        default: ""
-
-permissions:
-  contents: write
-  pull-requests: write
-
-jobs:
-  generate-changelog:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-
-      - name: Set up Python
-        uses: actions/setup-python@v5
-        with:
-          python-version: "3.12"
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v4
-        with:
-          enable-cache: true
-
-      - name: Install dependencies
-        run: |
-          uv sync --group dev
-
-      - name: Set release date
-        id: set_date
-        run: |
-          if [ -z "${{ inputs.date }}" ]; then
-            RELEASE_DATE=$(date +%Y-%m-%d)
-            echo "Using today's date: $RELEASE_DATE"
-          else
-            RELEASE_DATE="${{ inputs.date }}"
-            echo "Using provided date: $RELEASE_DATE"
-          fi
-          echo "release_date=$RELEASE_DATE" >> $GITHUB_OUTPUT
-
-      - name: Validate inputs
-        run: |
-          # Validate version format (basic check)
-          if ! [[ "${{ inputs.version }}" =~ ^[0-9]+\.[0-9]+\.[0-9]+.*$ ]]; then
-            echo "Error: Version must be in format X.Y.Z (e.g., 0.0.97)"
-            exit 1
-          fi
-
-          # Validate date format if provided
-          if [ -n "${{ inputs.date }}" ]; then
-            if ! date -d "${{ inputs.date }}" >/dev/null 2>&1; then
-              # Try macOS date format
-              if ! date -j -f "%Y-%m-%d" "${{ inputs.date }}" >/dev/null 2>&1; then
-                echo "Error: Date must be in YYYY-MM-DD format (e.g., 2025-12-04)"
-                exit 1
-              fi
-            fi
-          fi
-
-      - name: Check for changelog fragments
-        id: check_fragments
-        run: |
-          FRAGMENT_COUNT=$(find changelog -name "*.md" ! -name "_template.md.j2" | wc -l | tr -d ' ')
-          echo "fragment_count=$FRAGMENT_COUNT" >> $GITHUB_OUTPUT
-
-          if [ "$FRAGMENT_COUNT" -eq "0" ]; then
-            echo "❌ Error: No changelog fragments found in changelog/"
-            echo ""
-            echo "Cannot create a release without changelog entries."
-            echo "Add changelog fragments to the changelog/ directory (e.g., 1234.added.md) and try again."
-            exit 1
-          fi
-
-          # Validate fragment types
-          VALID_TYPES="added changed deprecated removed fixed performance security other"
-          INVALID_FRAGMENTS=""
-
-          for file in changelog/*.md; do
-            # Skip template
-            if [[ "$file" == "changelog/_template.md.j2" ]]; then
-              continue
-            fi
-            
-            # Extract type from filename (e.g., 1234.added.md -> added)
-            filename=$(basename "$file")
-            # Handle both 1234.added.md and 1234.added.2.md patterns
-            type=$(echo "$filename" | sed -E 's/^[0-9]+\.([a-z]+)(\.[0-9]+)?\.md$/\1/')
-            
-            # Check if type is valid
-            if ! echo "$VALID_TYPES" | grep -wq "$type"; then
-              INVALID_FRAGMENTS="$INVALID_FRAGMENTS\n  - $filename (type: '$type')"
-            fi
-          done
-
-          if [ -n "$INVALID_FRAGMENTS" ]; then
-            echo "❌ Error: Invalid changelog fragment types found:"
-            echo -e "$INVALID_FRAGMENTS"
-            echo ""
-            echo "Valid types are: $VALID_TYPES"
-            echo "Example: 1234.added.md, 5678.fixed.md"
-            exit 1
-          fi
-
-          echo "✓ Found $FRAGMENT_COUNT changelog fragment(s)"
-          echo "has_fragments=true" >> $GITHUB_OUTPUT
-
-      - name: Preview changelog
-        run: |
-          echo "## Preview of changelog for version ${{ inputs.version }}"
-          echo ""
-          uv run towncrier build --draft --version "${{ inputs.version }}" --date "${{ steps.set_date.outputs.release_date }}"
-
-      - name: Build changelog
-        run: |
-          uv run towncrier build --version "${{ inputs.version }}" --date "${{ steps.set_date.outputs.release_date }}" --yes
-
-      - name: Create Pull Request
-        uses: peter-evans/create-pull-request@v7
-        with:
-          token: ${{ secrets.GITHUB_TOKEN }}
-          commit-message: "Update changelog for version ${{ inputs.version }}"
-          title: "Release ${{ inputs.version }} - Changelog Update"
-          body: |
-            ## Changelog Update for Release ${{ inputs.version }}
-
-            This PR updates the CHANGELOG.md with all changes for version **${{ inputs.version }}**.
-
-            ### Summary
-            - **Version:** ${{ inputs.version }}
-            - **Date:** ${{ steps.set_date.outputs.release_date }}
-            - **Fragments processed:** ${{ steps.check_fragments.outputs.fragment_count }}
-
-            ### What this PR does
-            - ✅ Adds new release section to CHANGELOG.md
-            - ✅ Removes processed changelog fragments
-            - ✅ Ready to merge for release
-
-            ### Next Steps
-            1. Review the changelog entries below
-            2. Make any necessary edits to CHANGELOG.md if needed
-            3. Merge this PR
-            4. Continue with your release process
-
-            ---
-
-            <details>
-            <summary>📋 Preview of changes</summary>
-
-            The changelog has been updated with entries from the following fragments:
-
-            ```bash
-            ${{ steps.check_fragments.outputs.fragment_count }} fragments processed
-            ```
-
-            </details>
-          branch: changelog-${{ inputs.version }}
-          delete-branch: true
-          labels: |
-            changelog
-            release

.github/workflows/lint.yaml

@@ -0,0 +1,44 @@
+name: lint
+
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - "**"
+    paths-ignore:
+      - "docs/**"
+
+concurrency:
+  group: build-lint-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  autopep8:
+    name: "Formatting lints"
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repo
+        uses: actions/checkout@v4
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+      - name: Setup virtual environment
+        run: |
+          python -m venv .venv
+      - name: Install development Python dependencies
+        run: |
+          source .venv/bin/activate
+          python -m pip install --upgrade pip
+          pip install -r dev-requirements.txt
+      - name: autopep8
+        id: autopep8
+        run: |
+          source .venv/bin/activate
+          autopep8 --max-line-length 100 --exit-code -r -d --exclude "*_pb2.py" -a -a src/
+      - name: Fail if autopep8 requires changes
+        if: steps.autopep8.outputs.exit-code == 2
+        run: exit 1

.github/workflows/publish.yaml

@@ -5,29 +5,35 @@ on:
     inputs:
       gitref:
         type: string
-        description: 'what git tag to build (e.g. v0.0.74)'
+        description: "what git ref to build"
         required: true
 
 jobs:
   build:
-    name: 'Build and upload wheels'
+    name: "Build and upload wheels"
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
         with:
           ref: ${{ github.event.inputs.gitref }}
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v3
-        with:
-          version: 'latest'
       - name: Set up Python
-        run: uv python install 3.12
-      - name: Install development dependencies
-        run: uv sync --group dev
+        id: setup_python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+      - name: Setup virtual environment
+        run: |
+          python -m venv .venv
+      - name: Install basic Python dependencies
+        run: |
+          source .venv/bin/activate
+          python -m pip install --upgrade pip
+          pip install -r dev-requirements.txt
       - name: Build project
-        run: uv build
+        run: |
+          source .venv/bin/activate
+          python -m build
       - name: Upload wheels
         uses: actions/upload-artifact@v4
         with:
@@ -35,9 +41,9 @@ jobs:
           path: ./dist
 
   publish-to-pypi:
-    name: 'Publish to PyPI'
+    name: "Publish to PyPI"
     runs-on: ubuntu-latest
-    needs: [build]
+    needs: [ build ]
     environment:
       name: pypi
       url: https://pypi.org/p/pipecat-ai
@@ -56,12 +62,12 @@ jobs:
           print-hash: true
 
   publish-to-test-pypi:
-    name: 'Publish to Test PyPI'
+    name: "Publish to Test PyPI"
     runs-on: ubuntu-latest
-    needs: [build]
+    needs: [ build ]
     environment:
       name: testpypi
-      url: https://test.pypi.org/p/pipecat-ai
+      url: https://pypi.org/p/pipecat-ai
     permissions:
       id-token: write
     steps:
@@ -70,7 +76,7 @@ jobs:
         with:
           name: wheels
           path: ./dist
-      - name: Publish to Test PyPI
+      - name: Publish to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
           verbose: true

.github/workflows/publish_test.yaml

@@ -1,27 +1,39 @@
 name: publish-test
 
-on: workflow_dispatch
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
 
 jobs:
   build:
-    name: 'Build and upload wheels'
+    name: "Build and upload wheels"
     runs-on: ubuntu-latest
     steps:
       - name: Checkout repo
         uses: actions/checkout@v4
         with:
+          ref: ${{ github.event.inputs.gitref }}
           fetch-tags: true
           fetch-depth: 100
-      - name: Install uv
-        uses: astral-sh/setup-uv@v3
-        with:
-          version: 'latest'
       - name: Set up Python
-        run: uv python install 3.12
-      - name: Install development dependencies
-        run: uv sync --group dev
+        id: setup_python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+      - name: Setup virtual environment
+        run: |
+          python -m venv .venv
+      - name: Install basic Python dependencies
+        run: |
+          source .venv/bin/activate
+          python -m pip install --upgrade pip
+          pip install -r dev-requirements.txt
       - name: Build project
-        run: uv build
+        run: |
+          source .venv/bin/activate
+          python -m build
       - name: Upload wheels
         uses: actions/upload-artifact@v4
         with:
@@ -29,12 +41,12 @@ jobs:
           path: ./dist
 
   publish-to-test-pypi:
-    name: 'Publish to Test PyPI'
+    name: "Publish to Test PyPI"
     runs-on: ubuntu-latest
-    needs: [build]
+    needs: [ build ]
     environment:
       name: testpypi
-      url: https://test.pypi.org/p/pipecat-ai
+      url: https://pypi.org/p/pipecat-ai
     permissions:
       id-token: write
     steps:
@@ -43,7 +55,7 @@ jobs:
         with:
           name: wheels
           path: ./dist
-      - name: Publish to Test PyPI
+      - name: Publish to PyPI
         uses: pypa/gh-action-pypi-publish@release/v1
         with:
           verbose: true

.github/workflows/python-compatibility.yaml

@@ -1,50 +0,0 @@
-name: Python Compatibility Test
-
-on:
-  push:
-    branches: [main, develop]
-    paths: ['pyproject.toml']
-  pull_request:
-    branches: [main, develop]
-    paths: ['pyproject.toml']
-
-jobs:
-  test-compatibility:
-    runs-on: ubuntu-latest
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ['3.10.19', '3.11.14', '3.12.12', '3.13.12']
-
-    name: Python ${{ matrix.python-version }}
-    steps:
-      - name: Checkout code
-        uses: actions/checkout@v4
-
-      - name: Install system dependencies
-        run: |
-          sudo apt-get update
-          sudo apt-get install -y \
-            portaudio19-dev \
-            libcairo2-dev \
-            libgirepository1.0-dev \
-            pkg-config
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v4
-        with:
-          version: 'latest'
-
-      - name: Set up Python ${{ matrix.python-version }}
-        run: |
-          uv python install ${{ matrix.python-version }}
-          uv python pin ${{ matrix.python-version }}
-
-      - name: Test uv sync with all extras
-        run: |
-          uv sync --group dev --all-extras --no-extra krisp
-
-      - name: Verify installation
-        run: |
-          uv run python --version
-          uv run python -c "import pipecat; print('✅ Pipecat imports successfully')"

.github/workflows/sync-quickstart.yaml

@@ -1,51 +0,0 @@
-name: Sync Quickstart to pipecat-quickstart repo
-
-on:
-  push:
-    branches: [main]
-    paths:
-      - 'examples/quickstart/**'
-  workflow_dispatch: # Manual trigger
-
-jobs:
-  sync-quickstart:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Checkout main repo
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-
-      - name: Checkout quickstart repo
-        uses: actions/checkout@v4
-        with:
-          repository: pipecat-ai/pipecat-quickstart
-          token: ${{ secrets.QUICKSTART_SYNC_TOKEN }}
-          path: quickstart-repo
-
-      - name: Sync files (excluding uv.lock and README.md)
-        run: |
-          # Copy all files except uv.lock and README.md
-          find examples/quickstart -type f \
-            -not -name "README.md" \
-            -not -name "uv.lock" \
-            -exec cp {} quickstart-repo/ \;
-
-      - name: Commit and push changes
-        run: |
-          cd quickstart-repo
-          git config user.name "GitHub Action"
-          git config user.email "action@github.com"
-          git add .
-
-          # Only commit if there are changes
-          if ! git diff --staged --quiet; then
-            git commit -m "Sync from pipecat main repo
-            
-            Updated files from examples/quickstart/
-            Commit: ${{ github.sha }}
-            "
-            git push
-          else
-            echo "No changes to sync"
-          fi

.github/workflows/tests.yaml

@@ -1,4 +1,4 @@
-name: tests
+name: test
 
 on:
   workflow_dispatch:
@@ -20,35 +20,30 @@ jobs:
     name: "Unit and Integration Tests"
     runs-on: ubuntu-latest
     steps:
-      - name: Checkout repo
-        uses: actions/checkout@v4
-
-      - name: Install uv
-        uses: astral-sh/setup-uv@v3
-        with:
-          version: "latest"
-
+      - uses: actions/checkout@v4
       - name: Set up Python
-        run: uv python install 3.12
-
+        id: setup_python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.10'
+      - name: Cache virtual environment
+        uses: actions/cache@v3
+        with:
+          # We are hashing requirements-dev.txt and requirements-extra.txt which
+          # contain all dependencies needed to run the tests and examples.
+          key: venv-${{ runner.os }}-${{ steps.setup_python.outputs.python-version}}-${{ hashFiles('linux-py3.10-requirements.txt') }}-${{ hashFiles('dev-requirements.txt') }}
+          path: .venv
       - name: Install system packages
+        run: sudo apt-get install -y portaudio19-dev
+      - name: Setup virtual environment
         run: |
-          sudo apt-get update
-          sudo apt-get install -y portaudio19-dev
-
-      - name: Install dependencies
+          python -m venv .venv
+      - name: Install basic Python dependencies
         run: |
-          uv sync --group dev \
-            --extra anthropic \
-            --extra aws \
-            --extra google \
-            --extra langchain \
-            --extra livekit \
-            --extra local-smart-turn-v3 \
-            --extra piper \
-            --extra tracing \
-            --extra websocket
-
+          source .venv/bin/activate
+          python -m pip install --upgrade pip
+          pip install -r linux-py3.10-requirements.txt -r dev-requirements.txt
       - name: Test with pytest
         run: |
-          uv run pytest
+          source .venv/bin/activate
+          pytest --doctest-modules --ignore-glob="*to_be_updated*" src tests

.gitignore

@@ -4,17 +4,9 @@ __pycache__/
 *~
 venv
 .venv
-.idea
-.gradle
-.next
-next-env.d.ts
-local.properties
-*.log
-*.lock
-smart_turn_audio_log
 #*#
 
-# Distribution / Packaging
+# Distribution / packaging
 .Python
 build/
 develop-eggs/
@@ -34,31 +26,5 @@ share/python-wheels/
 *.egg
 MANIFEST
 .DS_Store
-.env*
-fly.toml
-
-# Examples
-examples/**/node_modules/
-examples/**/.expo/
-examples/**/dist/
-examples/**/npm-debug.*
-examples/**/*.jks
-examples/**/*.p8
-examples/**/*.p12
-examples/**/*.key
-examples/**/*.mobileprovision
-examples/**/*.orig.*
-examples/**/web-build/
-
-# macOS
-.DS_Store
-
-# Documentation
-docs/api/_build/
-docs/api/api
-
-# uv
-.python-version
-
-# Pipecat
-whisker_setup.py
+.env
+fly.toml

.pre-commit-config.yaml

@@ -1,8 +0,0 @@
-repos:
-  - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.12.1
-    hooks:
-      - id: ruff
-        language_version: python3
-        args: [--fix]
-      - id: ruff-format

.readthedocs.yaml

@@ -1,28 +0,0 @@
-version: 2
-
-build:
-  os: ubuntu-22.04
-  tools:
-    python: '3.12'
-  apt_packages:
-    - portaudio19-dev
-    - python3-dev
-    - libasound2-dev
-  jobs:
-    post_install:
-      - pip install uv
-      - UV_PROJECT_ENVIRONMENT=$READTHEDOCS_VIRTUALENV_PATH uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
-
-sphinx:
-  configuration: docs/api/conf.py
-  fail_on_warning: false
-
-search:
-  ranking:
-    api/*: 5
-    getting-started/*: 4
-    guides/*: 3
-
-submodules:
-  include: all
-  recursive: true

CLAUDE.md

@@ -1,155 +0,0 @@
-# CLAUDE.md
-
-This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
-
-## Project Overview
-
-Pipecat is an open-source Python framework for building real-time voice and multimodal conversational AI agents. It orchestrates audio/video, AI services, transports, and conversation pipelines using a frame-based architecture.
-
-## Common Commands
-
-```bash
-# Setup development environment
-uv sync --group dev --all-extras --no-extra gstreamer --no-extra krisp
-
-# Install pre-commit hooks
-uv run pre-commit install
-
-# Run all tests
-uv run pytest
-
-# Run a single test file
-uv run pytest tests/test_name.py
-
-# Run a specific test
-uv run pytest tests/test_name.py::test_function_name
-
-# Preview changelog
-towncrier build --draft --version Unreleased
-
-# Lint and format check
-uv run ruff check
-uv run ruff format --check
-
-# Update dependencies (after editing pyproject.toml)
-uv lock && uv sync
-```
-
-## Architecture
-
-### Frame-Based Pipeline Processing
-
-All data flows as **Frame** objects through a pipeline of **FrameProcessors**:
-
-```
-[Processor1] → [Processor2] → ... → [ProcessorN]
-```
-
-**Key components:**
-
-- **Frames** (`src/pipecat/frames/frames.py`): Data units (audio, text, video) and control signals. Flow DOWNSTREAM (input→output) or UPSTREAM (acknowledgments/errors).
-
-- **FrameProcessor** (`src/pipecat/processors/frame_processor.py`): Base processing unit. Each processor receives frames, processes them, and pushes results downstream.
-
-- **Pipeline** (`src/pipecat/pipeline/pipeline.py`): Chains processors together.
-
-- **ParallelPipeline** (`src/pipecat/pipeline/parallel_pipeline.py`): Runs multiple pipelines in parallel.
-
-- **Transports** (`src/pipecat/transports/`): Transports are frame processors used for external I/O layer (Daily WebRTC, LiveKit WebRTC, WebSocket, Local). Abstract interface via `BaseTransport`, `BaseInputTransport` and `BaseOutputTransport`.
-
-- **Pipeline Task (`src/pipecat/pipeline/task.py`)**: Runs and manages a pipeline. Pipeline tasks send the first frame, `StartFrame`, to the pipeline in order for processors to know they can start processing and pushing frames. Pipeline tasks internally create a pipeline with two additional processors, a source processor before the user-defined pipeline and a sink processor at the end. Those are used for multiple things: error handling, pipeline task level events, heartbeat monitoring, etc.
-
-- **Pipeline Runner (`src/pipecat/pipeline/runner.py`)**: High-level entry point for executing pipeline tasks. Handles signal management (SIGINT/SIGTERM) for graceful shutdown and optional garbage collection. Run a single pipeline task with `await runner.run(task)` or multiple concurrently with `await asyncio.gather(runner.run(task1), runner.run(task2))`.
-
-- **Services** (`src/pipecat/services/`): 60+ AI provider integrations (STT, TTS, LLM, etc.). Extend base classes: `AIService`, `LLMService`, `STTService`, `TTSService`, `VisionService`.
-
-- **Serializers** (`src/pipecat/serializers/`): Convert frames to/from wire formats for WebSocket transports. `FrameSerializer` base class defines `serialize()` and `deserialize()`. Telephony serializers (Twilio, Plivo, Vonage, Telnyx, Exotel, Genesys) handle provider-specific protocols and audio encoding (e.g., μ-law).
-
-- **RTVI** (`src/pipecat/processors/frameworks/rtvi.py`): Real-Time Voice Interface protocol bridging clients and the pipeline. `RTVIProcessor` handles incoming client messages (text input, audio, function call results). `RTVIObserver` converts pipeline frames to outgoing messages: user/bot speaking events, transcriptions, LLM/TTS lifecycle, function calls, metrics, and audio levels.
-
-- **Observers** (`src/pipecat/observers/`): Monitor frame flow without modifying the pipeline. Passed to `PipelineTask` via the `observers` parameter. Implement `on_process_frame()` and `on_push_frame()` callbacks.
-
-### Important Patterns
-
-- **Context Aggregation**: `LLMContext` accumulates messages for LLM calls; `UserResponse` aggregates user input
-
-- **Turn Management**: Turn management is done through `LLMUserAggregator` and
-`LLMAssistantAggregator`, created with `LLMContextAggregatorPair`
-
-- **User turn strategies**: Detection of when the user starts and stops speaking is done via user turn start/stop strategies. They push `UserStartedSpeakingFrame` and `UserStoppedSpeakingFrame` respectively.
-
-- **Interruptions**: Interruptions are usually triggered by a user turn start strategy (e.g. `VADUserTurnStartStrategy`) but they can be triggered by other processors as well, in which case the user turn start strategies don't need to. An `InterruptionFrame` carries an optional `asyncio.Event` that is set when the frame reaches the pipeline sink. If a processor stops an `InterruptionFrame` from propagating downstream (i.e., doesn't push it), it **must** call `frame.complete()` to avoid stalling `push_interruption_task_frame_and_wait()` callers.
-
-- **Uninterruptible Frames**: These are frames that will not be removed from internal queues even if there's an interruption. For example, `EndFrame` and `StopFrame`.
-
-- **Events**: Most classes in Pipecat have `BaseObject` as the very base class. `BaseObject` has support for events. Events can run in the background in an async task (default) or synchronously (`sync=True`) if we want immediate action. Synchronous event handlers need to execute fast.
-
-- **Async Task Management**: Always use `self.create_task(coroutine, name)` instead of raw `asyncio.create_task()`. The `TaskManager` automatically tracks tasks and cleans them up on processor shutdown. Use `await self.cancel_task(task, timeout)` for cancellation.
-
-- **Error Handling**: Use `await self.push_error(msg, exception, fatal)` to push errors upstream. Services should use `fatal=False` (the default) so application code can handle errors and take action (e.g. switch to another service).
-
-### Key Directories
-
-| Directory                 | Purpose                                            |
-|---------------------------|----------------------------------------------------|
-| `src/pipecat/frames/`     | Frame definitions (100+ types)                     |
-| `src/pipecat/processors/` | FrameProcessor base + aggregators, filters, audio  |
-| `src/pipecat/pipeline/`   | Pipeline orchestration                             |
-| `src/pipecat/services/`   | AI service integrations (60+ providers)            |
-| `src/pipecat/transports/` | Transport layer (Daily, LiveKit, WebSocket, Local) |
-| `src/pipecat/serializers/`| Frame serialization for WebSocket protocols        |
-| `src/pipecat/observers/`  | Pipeline observers for monitoring frame flow       |
-| `src/pipecat/audio/`      | VAD, filters, mixers, turn detection, DTMF         |
-| `src/pipecat/turns/`      | User turn management                               |
-
-## Code Style
-
-- **Docstrings**: Google-style. Classes describe purpose; `__init__` has `Args:` section; dataclasses use `Parameters:` section.
-- **Linting**: Ruff (line length 100). Pre-commit hooks enforce formatting.
-- **Type hints**: Required for complex async code.
-
-### Docstring Example
-
-```python
-class MyService(LLMService):
-    """Description of what the service does.
-
-    More detailed description.
-
-    Event handlers available:
-
-    - on_connected: Called when we are connected
-
-    Example::
-
-        @service.event_handler("on_connected")
-        async def on_connected(service, frame):
-            ...
-    """
-
-    def __init__(self, param1: str, **kwargs):
-        """Initialize the service.
-
-        Args:
-            param1: Description of param1.
-            **kwargs: Additional arguments passed to parent.
-        """
-        super().__init__(**kwargs)
-```
-
-## Service Implementation
-
-When adding a new service:
-
-1. Extend the appropriate base class (`STTService`, `TTSService`, `LLMService`, etc.)
-2. Implement required abstract methods
-3. Handle necessary frames
-4. By default, all frames should be pushed in the direction they came
-5. Push `ErrorFrame` on failures
-6. Add metrics tracking via `MetricsData` if relevant
-7. Follow the pattern of existing services in `src/pipecat/services/`
-
-## Testing
-
-Test utilities live in `src/pipecat/tests/utils.py`. Use `run_test()` to send frames through a pipeline and assert expected output frames in each direction. Use `SleepFrame(sleep=N)` to add delays between frames.
-

COMMUNITY_INTEGRATIONS.md

@@ -1,336 +0,0 @@
-# Community Integrations Guide
-
-Pipecat welcomes community-maintained integrations! As our ecosystem grows, we've established a process for any developer to create and maintain their own service integrations while ensuring discoverability for the Pipecat community.
-
-## Overview
-
-**What we support:** Community-maintained integrations that live in separate repositories and are maintained by their authors.
-
-**What we don't do:** The Pipecat team does not code review, test, or maintain community integrations. We provide guidance and list approved integrations for discoverability.
-
-**Why this approach:** This allows the community to move quickly while keeping the Pipecat core team focused on maintaining the framework itself.
-
-## Submitting your Integration
-
-To be listed as an official community integration, follow these steps:
-
-### Step 1: Build Your Integration
-
-Create your integration following the patterns and examples shown in the "Integration Patterns and Examples" section below.
-
-### Step 2: Set Up Your Repository
-
-Your repository must contain these components:
-
-- **Source code** - Complete implementation following Pipecat patterns
-- **Foundational example** - Single file example showing basic usage (see [Pipecat examples](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational))
-- **README.md** - Must include:
-
-  - Introduction and explanation of your integration
-  - Installation instructions
-  - Usage instructions with Pipecat Pipeline
-  - How to run your example
-  - Pipecat version compatibility (e.g., "Tested with Pipecat v0.0.86")
-  - Company attribution: If you work for the company providing the service, please mention this in your README. This helps build confidence that the integration will be actively maintained.
-
-- **LICENSE** - Permissive license (BSD-2 like Pipecat, or equivalent open source terms)
-- **Code documentation** - Source code with docstrings (we recommend following [Pipecat's docstring conventions](https://github.com/pipecat-ai/pipecat/blob/main/CONTRIBUTING.md#docstring-conventions))
-- **Changelog** - Maintain a changelog for version updates
-
-### Step 3: Join Discord
-
-Join our Discord: https://discord.gg/pipecat
-
-### Step 4: Submit for Listing
-
-Submit a pull request to add your integration to our [Community Integrations documentation page](https://docs.pipecat.ai/server/services/community-integrations).
-
-**To submit:**
-
-1. Fork the [Pipecat docs repository](https://github.com/pipecat-ai/docs)
-2. Edit the file `server/services/community-integrations.mdx`
-3. Add your integration to the appropriate service category table with:
-   - Service name
-   - Link to your repository
-   - Maintainer GitHub username(s)
-4. Include a link to your demo video (approx 30-60 seconds) in your PR description showing:
-   - Core functionality of your integration
-   - Handling of an interruption (if applicable to service type)
-5. Submit your pull request
-
-Once your PR is submitted, post in the `#community-integrations` Discord channel to let us know.
-
-## Integration Patterns and Examples
-
-### STT (Speech-to-Text) Services
-
-#### Websocket-based Services
-
-**Base class:** `STTService`
-
-**Examples:**
-
-- [DeepgramSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/deepgram/stt.py)
-- [SpeechmaticsSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/speechmatics/stt.py)
-
-#### File-based Services
-
-**Base class:** `SegmentedSTTService`
-
-**Examples:**
-
-- [NvidiaSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/nvidia/stt.py)
-- [FalSTTService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/fal/stt.py)
-
-#### Key requirements:
-
-- STT services should push `InterimTranscriptionFrames` and `TranscriptionFrames`
-- If confidence values are available, filter for values >50% confidence
-
-### LLM (Large Language Model) Services
-
-#### OpenAI-Compatible Services
-
-**Base class:** `OpenAILLMService`
-
-**Examples:**
-
-- [AzureLLMService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/azure/llm.py)
-- [GrokLLMService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/grok/llm.py) - Shows overriding the base class where needed
-
-#### Non-OpenAI Compatible Services
-
-**Requires:** Full implementation
-
-**Examples:**
-
-- [AnthropicLLMService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/anthropic/llm.py)
-- [GoogleLLMService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/google/llm.py)
-
-#### Key requirements:
-
-- **Frame sequence:** Output must follow this frame sequence pattern:
-
-  - `LLMFullResponseStartFrame` - Signals the start of an LLM response
-  - `LLMTextFrame` - Contains LLM content, typically streamed as tokens
-  - `LLMFullResponseEndFrame` - Signals the end of an LLM response
-
-- **Context aggregation:** Implement context aggregation to collect user and assistant content:
-  - Aggregators come in pairs with a `user()` instance and `assistant()` instance
-  - Context must adhere to the `LLMContext` universal format
-  - Aggregators should handle adding messages, function calls, and images to the context
-
-### TTS (Text-to-Speech) Services
-
-#### AudioContextWordTTSService
-
-**Use for:** Websocket-based services supporting word/timestamp alignment
-
-**Example:**
-
-- [CartesiaTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/cartesia/tts.py)
-
-#### InterruptibleTTSService
-
-**Use for:** Websocket-based services without word/timestamp alignment, requiring disconnection on interruption
-
-**Example:**
-
-- [SarvamTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/sarvam/tts.py)
-
-#### WordTTSService
-
-**Use for:** HTTP-based services supporting word/timestamp alignment
-
-**Example:**
-
-- [ElevenLabsHttpTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/elevenlabs/tts.py)
-
-#### TTSService
-
-**Use for:** HTTP-based services without word/timestamp alignment
-
-**Example:**
-
-- [GoogleHttpTTSService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/google/tts.py)
-
-#### Key requirements:
-
-- For websocket services, use asyncio WebSocket implementation (required for v13+ support)
-- Handle idle service timeouts with keepalives
-- TTSServices push both audio (`TTSRawAudioFrame`) and text (`TTSTextFrame`) frames
-
-### Telephony Serializers
-
-Pipecat supports telephony provider integration using websocket connections to exchange MediaStreams. These services use a FrameSerializer to serialize and deserialize inputs from the FastAPIWebsocketTransport.
-
-**Examples:**
-
-- [Twilio](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/serializers/twilio.py)
-- [Telnyx](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/serializers/telnyx.py)
-
-#### Key requirements:
-
-- Include hang-up functionality using the provider's native API, ideally using `aiohttp`
-- Support DTMF (dual-tone multi-frequency) events if the provider supports them:
-  - Deserialize DTMF events from the provider's protocol to `InputDTMFFrame`
-  - Use `KeypadEntry` enum for valid keypad entries (0-9, \*, #, A-D)
-  - Handle invalid DTMF digits gracefully by returning `None`
-
-### Image Generation Services
-
-**Base class:** `ImageGenService`
-
-**Examples:**
-
-- [FalImageGenService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/fal/image.py)
-- [GoogleImageGenService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/google/image.py)
-
-#### Key requirements:
-
-- Must implement `run_image_gen` method returning an `AsyncGenerator`
-
-### Vision Services
-
-Vision services process images and provide analysis such as descriptions, object detection, or visual question answering.
-
-**Base class:** `VisionService`
-
-**Example:**
-
-- [MoondreamVisionService](https://github.com/pipecat-ai/pipecat/blob/main/src/pipecat/services/moondream/vision.py)
-
-#### Key requirements:
-
-- Must implement `run_vision` method that takes an `LLMContext` and returns an `AsyncGenerator[Frame, None]`
-- The method processes the latest image in the context and yields frames with analysis results
-- Typically yields `TextFrame` objects containing descriptions or answers
-
-## Implementation Guidelines
-
-### Naming Conventions
-
-- **STT:** `VendorSTTService`
-- **LLM:** `VendorLLMService`
-- **TTS:**
-  - Websocket: `VendorTTSService`
-  - HTTP: `VendorHttpTTSService`
-- **Image:** `VendorImageGenService`
-- **Vision:** `VendorVisionService`
-- **Telephony:** `VendorFrameSerializer`
-
-### Metrics Support
-
-Enable metrics in your service:
-
-```python
-def can_generate_metrics(self) -> bool:
-    """Check if this service can generate processing metrics.
-
-    Returns:
-        True, as this service supports metrics.
-    """
-    return True
-```
-
-### Dynamic Settings Updates
-
-STT, LLM, and TTS services support `ServiceUpdateSettingsFrame` for dynamic configuration changes. The base STTService has an `_update_settings()` method that handles settings, and the private `_settings` `Dict` is used to store settings and provide access to the subclass.
-
-```python
-async def set_language(self, language: Language):
-    """Set the recognition language and reconnect.
-
-    Args:
-        language: The language to use for speech recognition.
-    """
-    logger.info(f"Switching STT language to: [{language}]")
-    self._settings["language"] = language
-    await self._disconnect()
-    await self._connect()
-```
-
-Note that, in this example, Deepgram requires the websocket connection be disconnected and reconnected to reinitialize the service with the new value. Consider if your service requires reconnection.
-
-### Sample Rate Handling
-
-Sample rates are set via PipelineParams and passed to each frame processor at initialization. The pattern is to _not_ set the sample rate value in the constructor of a given service. Instead, use the `start()` method to initialize sample rates from the frame:
-
-```python
-async def start(self, frame: StartFrame):
-    """Start the service."""
-    await super().start(frame)
-    self._settings["output_format"]["sample_rate"] = self.sample_rate
-    await self._connect()
-```
-
-Note that `self.sample_rate` is a `@property` set in the TTSService base class, which provides access to the private sample rate value obtained from the StartFrame.
-
-### Tracing Decorators
-
-Use Pipecat's tracing decorators:
-
-- **STT:** `@traced_stt` - decorate a function that handles `transcript`, `is_final`, `language` as args
-- **LLM:** `@traced_llm` - decorate the `_process_context()` method
-- **TTS:** `@traced_tts` - decorate the `run_tts()` method
-
-## Best Practices
-
-### Packaging and Distribution
-
-- Use [uv](https://docs.astral.sh/uv/) for packaging (encouraged)
-- Consider releasing to PyPI for easier installation
-- Follow semantic versioning principles
-- Maintain a changelog
-
-### HTTP Communication
-
-For REST-based communication, use aiohttp. Pipecat includes this as a required dependency, so using it prevents adding an additional dependency to your integration.
-
-### Error Handling
-
-- Wrap API calls in appropriate try/catch blocks
-- Handle rate limits and network failures gracefully
-- Provide meaningful error messages
-- When errors occur, raise exceptions AND push `ErrorFrame`s to notify the pipeline:
-
-```python
-from pipecat.frames.frames import ErrorFrame
-
-try:
-    # Your API call
-    result = await self._make_api_call()
-except Exception as e:
-    # Push error frame to pipeline
-    await self.push_error(ErrorFrame(error=f"{self} error: {e}"))
-    # Raise or handle as appropriate
-    raise
-```
-
-### Testing
-
-- Your foundational example serves as a valuable integration-level test
-- Unit tests are nice to have. As the Pipecat teams provides better guidance, we will encourage unit testing more
-
-## Disclaimer
-
-Community integrations are community-maintained and not officially supported by the Pipecat team. Users should evaluate these integrations independently. The Pipecat team reserves the right to remove listings that become unmaintained or problematic.
-
-## Staying Up to Date
-
-Pipecat evolves rapidly to support the latest AI technologies and patterns. While we strive to minimize breaking changes, they do occur as the framework matures.
-
-**We strongly recommend:**
-
-- Join our Discord at https://discord.gg/pipecat and monitor the `#announcements` channel for release notifications
-- Follow our changelog: https://github.com/pipecat-ai/pipecat/blob/main/CHANGELOG.md
-- Test your integration against new Pipecat releases promptly
-- Update your README with the last tested Pipecat version
-
-This helps ensure your integration remains compatible and your users have clear expectations about version support.
-
-## Questions?
-
-Join our Discord community at https://discord.gg/pipecat and post in the `#community-integrations` channel for guidance and support.
-
-For additional questions, you can also reach out to us at pipecat-ai@daily.co.

CONTRIBUTING.md

@@ -1,439 +0,0 @@
-## Contributing to Pipecat
-
-**Want to add a new service integration?**
-We encourage community-maintained integrations! Please see our [Community Integration Guide](COMMUNITY_INTEGRATIONS.md) for the process and requirements.
-
-**Want to contribute to Pipecat core?**
-We welcome contributions of all kinds! Your help is appreciated. Follow these steps to get involved:
-
-1. **Fork this repository**: Start by forking the Pipecat Documentation repository to your GitHub account.
-
-2. **Clone the repository**: Clone your forked repository to your local machine.
-   ```bash
-   git clone https://github.com/your-username/pipecat
-   ```
-3. **Create a branch**: For your contribution, create a new branch.
-   ```bash
-   git checkout -b your-branch-name
-   ```
-4. **Make your changes**: Edit or add files as necessary.
-5. **Add a changelog entry**: Create a changelog fragment file (see [Changelog Entries](#changelog-entries) below).
-6. **Test your changes**: Ensure that your changes look correct and follow the style set in the codebase.
-7. **Commit your changes**: Once you're satisfied with your changes, commit them with a meaningful message.
-
-```bash
-git commit -m "Description of your changes"
-```
-
-8. **Push your changes**: Push your branch to your forked repository.
-
-```bash
-git push origin your-branch-name
-```
-
-9. **Submit a Pull Request (PR)**: Open a PR from your forked repository to the main branch of this repo.
-   > Important: Describe the changes you've made clearly!
-
-Our maintainers will review your PR, and once everything is good, your contributions will be merged!
-
-## Changelog Entries
-
-Every pull request that makes a user-facing change should include a changelog entry. We use a changelog fragment system to avoid merge conflicts.
-
-### Creating a Changelog Fragment
-
-1. Create a new file in the `changelog/` directory with this naming pattern:
-
-   ```
-   <PR_number>.<type>.md
-   ```
-
-2. Choose the appropriate type:
-
-   - `added.md` - New features
-   - `changed.md` - Changes in existing functionality
-   - `deprecated.md` - Soon-to-be removed features
-   - `removed.md` - Removed features
-   - `fixed.md` - Bug fixes
-   - `security.md` - Security fixes
-   - `other.md` - Other changes (documentation, dependencies, etc.)
-
-3. Write your changelog entry as a Markdown bullet point. Include the `-` at the start:
-
-**Example files:**
-
-`changelog/1234.added.md`:
-
-```markdown
-- Added support for Anthropic Claude 3.5 Sonnet with improved streaming performance.
-```
-
-`changelog/5678.fixed.md`:
-
-```markdown
-- Fixed an issue where audio frames were dropped during high-load scenarios.
-```
-
-**For entries with nested bullets:**
-
-`changelog/1234.changed.md`:
-
-```markdown
-- Updated service configuration:
-
-  - Changed default timeout to 30 seconds
-  - Added retry logic for failed connections
-```
-
-### Multiple Changes in One PR
-
-**Different types of changes:** Create separate fragment files for each type:
-
-```
-changelog/1234.added.md
-changelog/1234.fixed.md
-```
-
-**Multiple changes of the same type:** Create numbered fragment files:
-
-```
-changelog/1234.changed.md
-changelog/1234.changed.2.md
-```
-
-**Related changes:** Use nested bullets in a single fragment:
-
-```markdown
-- Updated service configuration:
-
-  - Changed default timeout to 30 seconds
-  - Added retry logic for failed connections
-```
-
-**Rule of thumb:** One logical change per fragment file. If changes are unrelated, use separate files.
-
-### Preview Your Changes
-
-To see what your changelog entry will look like:
-
-```bash
-towncrier build --draft --version Unreleased
-```
-
-This won't modify any files, just show you a preview.
-
-### When to Skip Changelog Entries
-
-You can skip adding a changelog entry for:
-
-- Documentation-only changes
-- Internal refactoring with no user-facing impact
-- Test-only changes
-- CI/build configuration changes
-
-If you're unsure whether your change needs a changelog entry, ask in your PR!
-
-## Dependency Management
-
-This project uses [uv](https://docs.astral.sh/uv/) for dependency management. The `uv.lock` file is committed to ensure reproducible builds.
-
-### Adding or Updating Dependencies
-
-1. Edit `pyproject.toml` to add/update dependencies
-2. Run `uv lock` to update the lockfile with new dependency resolution
-3. Run `uv sync` to install the updated dependencies locally
-4. Always commit both files together:
-   ```bash
-   git add pyproject.toml uv.lock
-   git commit -m "feat: add new dependency for feature X"
-   ```
-
-**Important:** Never manually edit `uv.lock`. It's auto-generated by `uv lock`.
-
-## Code Style and Documentation
-
-### Python Code Style
-
-We use Ruff for code linting and formatting. Please ensure your code passes all linting checks before submitting a PR.
-
-### Docstring Conventions
-
-We follow Google-style docstrings with these specific conventions:
-
-**Regular Classes:**
-
-- Class docstring describes the class purpose and key functionality
-- `__init__` method has its own docstring with complete `Args:` section documenting all parameters
-- All public methods must have docstrings with `Args:` and `Returns:` sections as appropriate
-
-**Dataclasses:**
-
-- Class docstring describes the purpose and documents all fields in a `Parameters:` section
-- No `__init__` docstring (auto-generated)
-
-**Properties:**
-
-- Must have docstrings with `Returns:` section
-
-**Abstract Methods:**
-
-- Must have docstrings explaining what subclasses should implement
-
-**`__init__.py` Files:**
-
-- **Skip docstrings** for pure import/re-export modules
-- **Add brief docstrings** for top-level packages or those with initialization logic
-
-**Enums:**
-
-- Class docstring describes the enumeration purpose
-- Use `Parameters:` section to document each enum value and its meaning
-- No `__init__` docstring (Enums don't have custom constructors)
-
-**Code Examples in Docstrings:**
-
-- Use `Examples:` as a section header for multiple examples
-- Use descriptive text followed by double colons (`::`) for each example
-- **Always include a blank line after the `::"`**
-- Indent all code consistently within each block
-- Separate multiple examples with blank lines for readability
-
-**Lists and Bullets in Docstrings:**
-
-- Use dashes (`-`) for bullet points, not asterisks (`*`)
-- **Add a blank line before bullet lists** when they follow a colon
-- Use section headers like "Supported features:" or "Behavior:" before lists
-- For complex nested information, consider using paragraph format instead
-
-**Deprecations:**
-
-- Use `warnings.warn()` in code for runtime deprecation warnings
-- Add `.. deprecated::` directive in docstrings for documentation visibility
-- Include version information and describe current status
-- Describe parameters in present tense, use directive to indicate deprecation status
-
-#### Examples:
-
-```python
-# Regular class
-class MyService(BaseService):
-    """Description of what the service does.
-
-    Provides detailed explanation of the service's functionality,
-    key features, and usage patterns.
-
-    Supported features:
-
-    - Feature one with detailed explanation
-    - Feature two with additional context
-    - Feature three for advanced use cases
-    """
-
-    def __init__(self, param1: str, old_param: str = None, **kwargs):
-        """Initialize the service.
-
-        Args:
-            param1: Description of param1.
-            old_param: Controls legacy behavior.
-
-                .. deprecated:: 1.2.0
-                    This parameter no longer has any effect and will be removed in version 2.0.
-
-            **kwargs: Additional arguments passed to parent.
-        """
-        if old_param is not None:
-            import warnings
-            warnings.warn(
-                "Parameter 'old_param' is deprecated and will be removed in version 2.0.",
-                DeprecationWarning,
-            )
-        super().__init__(**kwargs)
-
-    @property
-    def sample_rate(self) -> int:
-        """Get the current sample rate.
-
-        Returns:
-            The sample rate in Hz.
-        """
-        return self._sample_rate
-
-    async def process_data(self, data: str) -> bool:
-        """Process the provided data.
-
-        Args:
-            data: The data to process.
-
-        Returns:
-            True if processing succeeded.
-        """
-        pass
-
-# Dataclass with code examples
-@dataclass
-class MessageFrame:
-    """Frame containing messages in OpenAI format.
-
-    Supports both simple and content list message formats.
-
-    Example::
-
-        [
-            {"role": "user", "content": "Hello"},
-            {"role": "assistant", "content": "Hi there!"}
-        ]
-
-    Parameters:
-        messages: List of messages in OpenAI format.
-    """
-
-    messages: List[dict]
-
-# Enum class
-class Status(Enum):
-    """Status codes for processing operations.
-
-    Parameters:
-        PENDING: Operation is queued but not started.
-        RUNNING: Operation is currently in progress.
-        COMPLETED: Operation finished successfully.
-        FAILED: Operation encountered an error.
-    """
-
-    PENDING = "pending"
-    RUNNING = "running"
-    COMPLETED = "completed"
-    FAILED = "failed"
-```
-
-# Contributor Covenant Code of Conduct
-
-## Our Pledge
-
-We as members, contributors, and leaders pledge to make participation in our
-community a harassment-free experience for everyone, regardless of age, body
-size, visible or invisible disability, ethnicity, sex characteristics, gender
-identity and expression, level of experience, education, socio-economic status,
-nationality, personal appearance, race, caste, color, religion, or sexual
-identity and orientation.
-
-We pledge to act and interact in ways that contribute to an open, welcoming,
-diverse, inclusive, and healthy community.
-
-## Our Standards
-
-Examples of behavior that contributes to a positive environment for our
-community include:
-
-- Demonstrating empathy and kindness toward other people
-- Being respectful of differing opinions, viewpoints, and experiences
-- Giving and gracefully accepting constructive feedback
-- Accepting responsibility and apologizing to those affected by our mistakes,
-  and learning from the experience
-- Focusing on what is best not just for us as individuals, but for the overall
-  community
-
-Examples of unacceptable behavior include:
-
-- The use of sexualized language or imagery, and sexual attention or advances of
-  any kind
-- Trolling, insulting or derogatory comments, and personal or political attacks
-- Public or private harassment
-- Publishing others' private information, such as a physical or email address,
-  without their explicit permission
-- Other conduct which could reasonably be considered inappropriate in a
-  professional setting
-
-## Enforcement Responsibilities
-
-Community leaders are responsible for clarifying and enforcing our standards of
-acceptable behavior and will take appropriate and fair corrective action in
-response to any behavior that they deem inappropriate, threatening, offensive,
-or harmful.
-
-Community leaders have the right and responsibility to remove, edit, or reject
-comments, commits, code, wiki edits, issues, and other contributions that are
-not aligned to this Code of Conduct, and will communicate reasons for moderation
-decisions when appropriate.
-
-## Scope
-
-This Code of Conduct applies within all community spaces, and also applies when
-an individual is officially representing the community in public spaces.
-Examples of representing our community include using an official email address,
-posting via an official social media account, or acting as an appointed
-representative at an online or offline event.
-
-## Enforcement
-
-Instances of abusive, harassing, or otherwise unacceptable behavior may be
-reported to the community leaders responsible for enforcement at pipecat-ai@daily.co.
-All complaints will be reviewed and investigated promptly and fairly.
-
-All community leaders are obligated to respect the privacy and security of the
-reporter of any incident.
-
-## Enforcement Guidelines
-
-Community leaders will follow these Community Impact Guidelines in determining
-the consequences for any action they deem in violation of this Code of Conduct:
-
-### 1. Correction
-
-**Community Impact**: Use of inappropriate language or other behavior deemed
-unprofessional or unwelcome in the community.
-
-**Consequence**: A private, written warning from community leaders, providing
-clarity around the nature of the violation and an explanation of why the
-behavior was inappropriate. A public apology may be requested.
-
-### 2. Warning
-
-**Community Impact**: A violation through a single incident or series of
-actions.
-
-**Consequence**: A warning with consequences for continued behavior. No
-interaction with the people involved, including unsolicited interaction with
-those enforcing the Code of Conduct, for a specified period of time. This
-includes avoiding interactions in community spaces as well as external channels
-like social media. Violating these terms may lead to a temporary or permanent
-ban.
-
-### 3. Temporary Ban
-
-**Community Impact**: A serious violation of community standards, including
-sustained inappropriate behavior.
-
-**Consequence**: A temporary ban from any sort of interaction or public
-communication with the community for a specified period of time. No public or
-private interaction with the people involved, including unsolicited interaction
-with those enforcing the Code of Conduct, is allowed during this period.
-Violating these terms may lead to a permanent ban.
-
-### 4. Permanent Ban
-
-**Community Impact**: Demonstrating a pattern of violation of community
-standards, including sustained inappropriate behavior, harassment of an
-individual, or aggression toward or disparagement of classes of individuals.
-
-**Consequence**: A permanent ban from any sort of public interaction within the
-community.
-
-## Attribution
-
-This Code of Conduct is adapted from the [Contributor Covenant][homepage],
-version 2.1, available at
-[https://www.contributor-covenant.org/version/2/1/code_of_conduct.html][v2.1].
-
-Community Impact Guidelines were inspired by
-[Mozilla's code of conduct enforcement ladder][Mozilla CoC].
-
-For answers to common questions about this code of conduct, see the FAQ at
-[https://www.contributor-covenant.org/faq][FAQ]. Translations are available at
-[https://www.contributor-covenant.org/translations][translations].
-
-[homepage]: https://www.contributor-covenant.org
-[v2.1]: https://www.contributor-covenant.org/version/2/1/code_of_conduct.html
-[Mozilla CoC]: https://github.com/mozilla/diversity
-[FAQ]: https://www.contributor-covenant.org/faq
-[translations]: https://www.contributor-covenant.org/translations

Dockerfile

@@ -0,0 +1,40 @@
+# setup
+FROM python:3.11.5
+
+WORKDIR /app
+COPY requirements.txt /app
+COPY *.py /app
+COPY pyproject.toml /app
+
+COPY src/ /app/src/
+COPY examples/ /app/examples/
+
+WORKDIR /app
+RUN ls --recursive /app/
+RUN pip3 install --upgrade -r requirements.txt
+RUN python -m build .
+RUN pip3 install .
+RUN pip3 install gunicorn
+# If running on Ubuntu, Azure TTS requires some extra config
+# https://learn.microsoft.com/en-us/azure/ai-services/speech-service/quickstarts/setup-platform?pivots=programming-language-python&tabs=linux%2Cubuntu%2Cdotnetcli%2Cdotnet%2Cjre%2Cmaven%2Cnodejs%2Cmac%2Cpypi
+
+RUN wget -O - https://www.openssl.org/source/openssl-1.1.1w.tar.gz | tar zxf -
+WORKDIR openssl-1.1.1w
+RUN ./config --prefix=/usr/local
+RUN make -j $(nproc)
+RUN make install_sw install_ssldirs
+RUN ldconfig -v
+ENV SSL_CERT_DIR=/etc/ssl/certs
+
+#ENV LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
+RUN apt clean
+RUN apt-get update
+RUN apt-get -y install build-essential libssl-dev ca-certificates libasound2 wget
+
+ENV PYTHONUNBUFFERED=1
+
+WORKDIR /app
+
+EXPOSE 8000
+# run
+CMD ["gunicorn", "--workers=2", "--log-level", "debug", "--chdir", "examples/server", "--capture-output", "daily-bot-manager:app", "--bind=0.0.0.0:8000"]

LICENSE

@@ -1,6 +1,6 @@
 BSD 2-Clause License
 
-Copyright (c) 2024–2026, Daily
+Copyright (c) 2024, Daily
 
 Redistribution and use in source and binary forms, with or without
 modification, are permitted provided that the following conditions are met:

MANIFEST.in

@@ -1,4 +0,0 @@
-prune docs
-prune examples
-prune scripts
-prune tests

README.md

@@ -1,199 +1,221 @@
-<h1><div align="center">
- <img alt="pipecat" width="300px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png">
-</div></h1>
+<div align="center">
+ <img alt="pipecat" width="300px" height="auto" src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/pipecat.png">
+</div>
 
-[![PyPI](https://img.shields.io/pypi/v/pipecat-ai)](https://pypi.org/project/pipecat-ai) ![Tests](https://github.com/pipecat-ai/pipecat/actions/workflows/tests.yaml/badge.svg) [![codecov](https://codecov.io/gh/pipecat-ai/pipecat/graph/badge.svg?token=LNVUIVO4Y9)](https://codecov.io/gh/pipecat-ai/pipecat) [![Docs](https://img.shields.io/badge/Documentation-blue)](https://docs.pipecat.ai) [![Discord](https://img.shields.io/discord/1239284677165056021)](https://discord.gg/pipecat) [![Ask DeepWiki](https://deepwiki.com/badge.svg)](https://deepwiki.com/pipecat-ai/pipecat)
+# Pipecat
 
-# 🎙️ Pipecat: Real-Time Voice & Multimodal AI Agents
+[![PyPI](https://img.shields.io/pypi/v/pipecat-ai)](https://pypi.org/project/pipecat-ai) [![Discord](https://img.shields.io/discord/1239284677165056021
+)](https://discord.gg/pipecat)
 
-**Pipecat** is an open-source Python framework for building real-time voice and multimodal conversational agents. Orchestrate audio and video, AI services, different transports, and conversation pipelines effortlessly—so you can focus on what makes your agent unique.
+`pipecat` is a framework for building voice (and multimodal) conversational agents. Things like personal coaches, meeting assistants, [story-telling toys for kids](https://storytelling-chatbot.fly.dev/), customer support bots, [intake flows](https://www.youtube.com/watch?v=lDevgsp9vn0), and snarky social companions.
 
-> Want to dive right in? Try the [quickstart](https://docs.pipecat.ai/getting-started/quickstart).
-
-## 🚀 What You Can Build
-
-- **Voice Assistants** – natural, streaming conversations with AI
-- **AI Companions** – coaches, meeting assistants, characters
-- **Multimodal Interfaces** – voice, video, images, and more
-- **Interactive Storytelling** – creative tools with generative media
-- **Business Agents** – customer intake, support bots, guided flows
-- **Complex Dialog Systems** – design logic with structured conversations
-
-## 🧠 Why Pipecat?
-
-- **Voice-first**: Integrates speech recognition, text-to-speech, and conversation handling
-- **Pluggable**: Supports many AI services and tools
-- **Composable Pipelines**: Build complex behavior from modular components
-- **Real-Time**: Ultra-low latency interaction with different transports (e.g. WebSockets or WebRTC)
-
-## 🌐 Pipecat Ecosystem
-
-### 📱 Client SDKs
-
-Building client applications? You can connect to Pipecat from any platform using our official SDKs:
-
-<a href="https://docs.pipecat.ai/client/js/introduction">JavaScript</a> | <a href="https://docs.pipecat.ai/client/react/introduction">React</a> | <a href="https://docs.pipecat.ai/client/react-native/introduction">React Native</a> |
-<a href="https://docs.pipecat.ai/client/ios/introduction">Swift</a> | <a href="https://docs.pipecat.ai/client/android/introduction">Kotlin</a> | <a href="https://docs.pipecat.ai/client/c++/introduction">C++</a> | <a href="https://github.com/pipecat-ai/pipecat-esp32">ESP32</a>
-
-### 🧭 Structured conversations
-
-Looking to build structured conversations? Check out [Pipecat Flows](https://github.com/pipecat-ai/pipecat-flows) for managing complex conversational states and transitions.
-
-### 🪄 Beautiful UIs
-
-Want to build beautiful and engaging experiences? Checkout the [Voice UI Kit](https://github.com/pipecat-ai/voice-ui-kit), a collection of components, hooks and templates for building voice AI applications quickly.
-
-### 🛠️ Create and deploy projects
-
-Create a new project in under a minute with the [Pipecat CLI](https://github.com/pipecat-ai/pipecat-cli). Then use the CLI to monitor and deploy your agent to production.
-
-### 🔍 Debugging
-
-Looking for help debugging your pipeline and processors? Check out [Whisker](https://github.com/pipecat-ai/whisker), a real-time Pipecat debugger.
-
-### 🖥️ Terminal
-
-Love terminal applications? Check out [Tail](https://github.com/pipecat-ai/tail), a terminal dashboard for Pipecat.
-
-### 📺️ Pipecat TV Channel
-
-Catch new features, interviews, and how-tos on our [Pipecat TV](https://www.youtube.com/playlist?list=PLzU2zoMTQIHjqC3v4q2XVSR3hGSzwKFwH) channel.
-
-## 🎬 See it in action
+Take a look at some example apps:
 
 <p float="left">
-    <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/simple-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/simple-chatbot/image.png" width="400" /></a>&nbsp;
-    <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/storytelling-chatbot/image.png" width="400" /></a>
+    <a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/simple-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/simple-chatbot/image.png" width="280" /></a>&nbsp;
+    <a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/storytelling-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/storytelling-chatbot/image.png" width="280" /></a>
     <br/>
-    <a href="https://github.com/pipecat-ai/pipecat-examples/tree/main/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat-examples/main/translation-chatbot/image.png" width="400" /></a>&nbsp;
-    <a href="https://github.com/pipecat-ai/pipecat/blob/main/examples/foundational/12-describe-video.py"><img src="https://github.com/pipecat-ai/pipecat/blob/main/examples/foundational/assets/moondream.png" width="400" /></a>
+    <a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/translation-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/translation-chatbot/image.png" width="280" /></a>&nbsp;
+    <a href="https://github.com/pipecat-ai/pipecat/tree/main/examples/moondream-chatbot"><img src="https://raw.githubusercontent.com/pipecat-ai/pipecat/main/examples/moondream-chatbot/image.png" width="280" /></a>
 </p>
 
-## 🧩 Available services
+## Getting started with voice agents
 
-| Category            | Services                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
-| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| Speech-to-Text      | [AssemblyAI](https://docs.pipecat.ai/server/services/stt/assemblyai), [AWS](https://docs.pipecat.ai/server/services/stt/aws), [Azure](https://docs.pipecat.ai/server/services/stt/azure), [Cartesia](https://docs.pipecat.ai/server/services/stt/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/stt/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/stt/elevenlabs), [Fal Wizper](https://docs.pipecat.ai/server/services/stt/fal), [Gladia](https://docs.pipecat.ai/server/services/stt/gladia), [Google](https://docs.pipecat.ai/server/services/stt/google), [Gradium](https://docs.pipecat.ai/server/services/stt/gradium), [Groq (Whisper)](https://docs.pipecat.ai/server/services/stt/groq), [Hathora](https://docs.pipecat.ai/server/services/stt/hathora), [NVIDIA Riva](https://docs.pipecat.ai/server/services/stt/riva), [OpenAI (Whisper)](https://docs.pipecat.ai/server/services/stt/openai), [SambaNova (Whisper)](https://docs.pipecat.ai/server/services/stt/sambanova), [Sarvam](https://docs.pipecat.ai/server/services/stt/sarvam), [Soniox](https://docs.pipecat.ai/server/services/stt/soniox), [Speechmatics](https://docs.pipecat.ai/server/services/stt/speechmatics), [Whisper](https://docs.pipecat.ai/server/services/stt/whisper)                                                                                                                                                                                                                                                            |
-| LLMs                | [Anthropic](https://docs.pipecat.ai/server/services/llm/anthropic), [AWS](https://docs.pipecat.ai/server/services/llm/aws), [Azure](https://docs.pipecat.ai/server/services/llm/azure), [Cerebras](https://docs.pipecat.ai/server/services/llm/cerebras), [DeepSeek](https://docs.pipecat.ai/server/services/llm/deepseek), [Fireworks AI](https://docs.pipecat.ai/server/services/llm/fireworks), [Gemini](https://docs.pipecat.ai/server/services/llm/gemini), [Grok](https://docs.pipecat.ai/server/services/llm/grok), [Groq](https://docs.pipecat.ai/server/services/llm/groq), [Mistral](https://docs.pipecat.ai/server/services/llm/mistral), [NVIDIA NIM](https://docs.pipecat.ai/server/services/llm/nim), [Ollama](https://docs.pipecat.ai/server/services/llm/ollama), [OpenAI](https://docs.pipecat.ai/server/services/llm/openai), [OpenRouter](https://docs.pipecat.ai/server/services/llm/openrouter), [Perplexity](https://docs.pipecat.ai/server/services/llm/perplexity), [Qwen](https://docs.pipecat.ai/server/services/llm/qwen), [SambaNova](https://docs.pipecat.ai/server/services/llm/sambanova) [Together AI](https://docs.pipecat.ai/server/services/llm/together)                                                                                                                                                                                                                                                                                              |
-| Text-to-Speech      | [Async](https://docs.pipecat.ai/server/services/tts/asyncai), [AWS](https://docs.pipecat.ai/server/services/tts/aws), [Azure](https://docs.pipecat.ai/server/services/tts/azure), [Camb AI](https://docs.pipecat.ai/server/services/tts/camb), [Cartesia](https://docs.pipecat.ai/server/services/tts/cartesia), [Deepgram](https://docs.pipecat.ai/server/services/tts/deepgram), [ElevenLabs](https://docs.pipecat.ai/server/services/tts/elevenlabs), [Fish](https://docs.pipecat.ai/server/services/tts/fish), [Google](https://docs.pipecat.ai/server/services/tts/google), [Gradium](https://docs.pipecat.ai/server/services/tts/gradium), [Groq](https://docs.pipecat.ai/server/services/tts/groq), [Hathora](https://docs.pipecat.ai/server/services/tts/hathora), [Hume](https://docs.pipecat.ai/server/services/tts/hume), [Inworld](https://docs.pipecat.ai/server/services/tts/inworld), [LMNT](https://docs.pipecat.ai/server/services/tts/lmnt), [MiniMax](https://docs.pipecat.ai/server/services/tts/minimax), [Neuphonic](https://docs.pipecat.ai/server/services/tts/neuphonic), [NVIDIA Riva](https://docs.pipecat.ai/server/services/tts/riva), [OpenAI](https://docs.pipecat.ai/server/services/tts/openai), [Piper](https://docs.pipecat.ai/server/services/tts/piper), [PlayHT](https://docs.pipecat.ai/server/services/tts/playht), [Resemble](https://docs.pipecat.ai/server/services/tts/resemble), [Rime](https://docs.pipecat.ai/server/services/tts/rime), [Sarvam](https://docs.pipecat.ai/server/services/tts/sarvam), [Speechmatics](https://docs.pipecat.ai/server/services/tts/speechmatics), [XTTS](https://docs.pipecat.ai/server/services/tts/xtts) |
-| Speech-to-Speech    | [AWS Nova Sonic](https://docs.pipecat.ai/server/services/s2s/aws), [Gemini Multimodal Live](https://docs.pipecat.ai/server/services/s2s/gemini), [Grok Voice Agent](https://docs.pipecat.ai/server/services/s2s/grok), [OpenAI Realtime](https://docs.pipecat.ai/server/services/s2s/openai), [Ultravox](https://docs.pipecat.ai/server/services/s2s/ultravox),                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
-| Transport           | [Daily (WebRTC)](https://docs.pipecat.ai/server/services/transport/daily), [FastAPI Websocket](https://docs.pipecat.ai/server/services/transport/fastapi-websocket), [SmallWebRTCTransport](https://docs.pipecat.ai/server/services/transport/small-webrtc), [WebSocket Server](https://docs.pipecat.ai/server/services/transport/websocket-server), Local                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
-| Serializers         | [Exotel](https://docs.pipecat.ai/server/utilities/serializers/exotel), [Plivo](https://docs.pipecat.ai/server/utilities/serializers/plivo), [Twilio](https://docs.pipecat.ai/server/utilities/serializers/twilio), [Telnyx](https://docs.pipecat.ai/server/utilities/serializers/telnyx), [Vonage](https://docs.pipecat.ai/server/utilities/serializers/vonage)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
-| Video               | [HeyGen](https://docs.pipecat.ai/server/services/video/heygen), [Tavus](https://docs.pipecat.ai/server/services/video/tavus), [Simli](https://docs.pipecat.ai/server/services/video/simli)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                |
-| Memory              | [mem0](https://docs.pipecat.ai/server/services/memory/mem0)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
-| Vision & Image      | [fal](https://docs.pipecat.ai/server/services/image-generation/fal), [Google Imagen](https://docs.pipecat.ai/server/services/image-generation/google-imagen), [Moondream](https://docs.pipecat.ai/server/services/vision/moondream)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
-| Audio Processing    | [Silero VAD](https://docs.pipecat.ai/server/utilities/audio/silero-vad-analyzer), [Krisp](https://docs.pipecat.ai/server/utilities/audio/krisp-filter), [Koala](https://docs.pipecat.ai/server/utilities/audio/koala-filter), [ai-coustics](https://docs.pipecat.ai/server/utilities/audio/aic-filter)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                    |
-| Analytics & Metrics | [OpenTelemetry](https://docs.pipecat.ai/server/utilities/opentelemetry), [Sentry](https://docs.pipecat.ai/server/services/analytics/sentry)                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
+You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when you’re ready. You can also add a 📞 telephone number, 🖼️ image output, 📺 video input, use different LLMs, and more.
 
-📚 [View full services documentation →](https://docs.pipecat.ai/server/services/supported-services)
+```shell
+# install the module
+pip install pipecat-ai
 
-## ⚡ Getting started
+# set up an .env file with API keys
+cp dot-env.template .env
+```
 
-You can get started with Pipecat running on your local machine, then move your agent processes to the cloud when you're ready.
+By default, in order to minimize dependencies, only the basic framework functionality is available. Some third-party AI services require additional dependencies that you can install with:
 
-1. Install uv
+```shell
+pip install "pipecat-ai[option,...]"
+```
 
-   ```bash
-   curl -LsSf https://astral.sh/uv/install.sh | sh
-   ```
+Your project may or may not need these, so they're made available as optional requirements. Here is a list:
 
-   > **Need help?** Refer to the [uv install documentation](https://docs.astral.sh/uv/getting-started/installation/).
+- **AI services**: `anthropic`, `azure`, `deepgram`, `google`, `fal`, `moondream`, `openai`, `openpipe`, `playht`, `silero`, `whisper`
+- **Transports**: `local`, `websocket`, `daily`
 
-2. Install the module
+## Code examples
 
-   ```bash
-   # For new projects
-   uv init my-pipecat-app
-   cd my-pipecat-app
-   uv add pipecat-ai
+- [foundational](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational) — small snippets that build on each other, introducing one or two concepts at a time
+- [example apps](https://github.com/pipecat-ai/pipecat/tree/main/examples/) — complete applications that you can use as starting points for development
 
-   # Or for existing projects
-   uv add pipecat-ai
-   ```
+## A simple voice agent running locally
 
-3. Set up your environment
+Here is a very basic Pipecat bot that greets a user when they join a real-time session. We'll use [Daily](https://daily.co) for real-time media transport, and [ElevenLabs](https://elevenlabs.io/) for text-to-speech.
 
-   ```bash
-   cp env.example .env
-   ```
+```python
+#app.py
 
-4. To keep things lightweight, only the core framework is included by default. If you need support for third-party AI services, you can add the necessary dependencies with:
+import asyncio
+import aiohttp
 
-   ```bash
-   uv add "pipecat-ai[option,...]"
-   ```
+from pipecat.frames.frames import EndFrame, TextFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.task import PipelineTask
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
 
-> **Using pip?** You can still use `pip install pipecat-ai` and `pip install "pipecat-ai[option,...]"` to get set up.
+async def main():
+  async with aiohttp.ClientSession() as session:
+    # Use Daily as a real-time media transport (WebRTC)
+    transport = DailyTransport(
+      room_url=...,
+      token=...,
+      "Bot Name",
+      DailyParams(audio_out_enabled=True))
 
-## 🧪 Code examples
+    # Use Eleven Labs for Text-to-Speech
+    tts = ElevenLabsTTSService(
+      aiohttp_session=session,
+      api_key=...,
+      voice_id=...,
+      )
 
-- [Foundational](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational) — small snippets that build on each other, introducing one or two concepts at a time
-- [Example apps](https://github.com/pipecat-ai/pipecat-examples) — complete applications that you can use as starting points for development
+    # Simple pipeline that will process text to speech and output the result
+    pipeline = Pipeline([tts, transport.output()])
 
-## 🛠️ Contributing to the framework
+    # Create Pipecat processor that can run one or more pipelines tasks
+    runner = PipelineRunner()
 
-### Prerequisites
+    # Assign the task callable to run the pipeline
+    task = PipelineTask(pipeline)
 
-**Minimum Python Version:** 3.10
-**Recommended Python Version:** 3.12
+    # Register an event handler to play audio when a
+    # participant joins the transport WebRTC session
+    @transport.event_handler("on_participant_joined")
+    async def on_new_participant_joined(transport, participant):
+      participant_name = participant["info"]["userName"] or ''
+      # Queue a TextFrame that will get spoken by the TTS service (Eleven Labs)
+      await task.queue_frames([TextFrame(f"Hello there, {participant_name}!"), EndFrame()])
 
-### Setup Steps
+    # Run the pipeline task
+    await runner.run(task)
 
-1. Clone the repository and navigate to it:
+if __name__ == "__main__":
+  asyncio.run(main())
+```
 
-   ```bash
-   git clone https://github.com/pipecat-ai/pipecat.git
-   cd pipecat
-   ```
+Run it with:
 
-2. Install development and testing dependencies:
+```shell
+python app.py
+```
 
-   ```bash
-   uv sync --group dev --all-extras \
-     --no-extra gstreamer \
-     --no-extra krisp \
-     --no-extra local \
-   ```
+Daily provides a prebuilt WebRTC user interface. Whilst the app is running, you can visit at `https://<yourdomain>.daily.co/<room_url>` and listen to the bot say hello!
 
-3. Install the git pre-commit hooks:
 
-   ```bash
-   uv run pre-commit install
-   ```
+## WebRTC for production use
 
-> **Note**: Some extras (local, gstreamer) require system dependencies. See documentation if you encounter build errors.
+WebSockets are fine for server-to-server communication or for initial development. But for production use, you’ll need client-server audio to use a protocol designed for real-time media transport. (For an explanation of the difference between WebSockets and WebRTC, see [this post.](https://www.daily.co/blog/how-to-talk-to-an-llm-with-your-voice/#webrtc))
+
+One way to get up and running quickly with WebRTC is to sign up for a Daily developer account. Daily gives you SDKs and global infrastructure for audio (and video) routing. Every account gets 10,000 audio/video/transcription minutes free each month.
+
+Sign up [here](https://dashboard.daily.co/u/signup) and [create a room](https://docs.daily.co/reference/rest-api/rooms) in the developer Dashboard.
+
+## What is VAD?
+
+Voice Activity Detection &mdash; very important for knowing when a user has finished speaking to your bot. If you are not using press-to-talk, and want Pipecat to detect when the user has finished talking, VAD is an essential component for a natural feeling conversation.
+
+Pipecast makes use of WebRTC VAD by default when using a WebRTC transport layer. Optionally, you can use Silero VAD for improved accuracy at the cost of higher CPU usage.
+
+```shell
+pip install pipecat-ai[silero]
+```
+
+The first time your run your bot with Silero, startup may take a while whilst it downloads and caches the model in the background. You can check the progress of this in the console.
+
+
+## Hacking on the framework itself
+
+_Note that you may need to set up a virtual environment before following the instructions below. For instance, you might need to run the following from the root of the repo:_
+
+```shell
+python3 -m venv venv
+source venv/bin/activate
+```
+
+From the root of this repo, run the following:
+
+```shell
+pip install -r dev-requirements.txt -r {env}-requirements.txt
+python -m build
+```
+
+This builds the package. To use the package locally (eg to run sample files), run
+
+```shell
+pip install --editable .
+```
+
+If you want to use this package from another directory, you can run:
+
+```shell
+pip install path_to_this_repo
+```
 
 ### Running tests
 
-To run all tests, from the root directory:
+From the root directory, run:
 
-```bash
-uv run pytest
+```shell
+pytest --doctest-modules --ignore-glob="*to_be_updated*" src tests
 ```
 
-Run a specific test suite:
+## Setting up your editor
 
-```bash
-uv run pytest tests/test_name.py
+This project uses strict [PEP 8](https://peps.python.org/pep-0008/) formatting.
+
+### Emacs
+
+You can use [use-package](https://github.com/jwiegley/use-package) to install [py-autopep8](https://codeberg.org/ideasman42/emacs-py-autopep8) package and configure `autopep8` arguments:
+
+```elisp
+(use-package py-autopep8
+  :ensure t
+  :defer t
+  :hook ((python-mode . py-autopep8-mode))
+  :config
+  (setq py-autopep8-options '("-a" "-a", "--max-line-length=100")))
 ```
 
-## 🤝 Contributing
+`autopep8` was installed in the `venv` environment described before, so you should be able to use [pyvenv-auto](https://github.com/ryotaro612/pyvenv-auto) to automatically load that environment inside Emacs.
 
-We welcome contributions from the community! Whether you're fixing bugs, improving documentation, or adding new features, here's how you can help:
+```elisp
+(use-package pyvenv-auto
+  :ensure t
+  :defer t
+  :hook ((python-mode . pyvenv-auto-run)))
 
-- **Found a bug?** Open an [issue](https://github.com/pipecat-ai/pipecat/issues)
-- **Have a feature idea?** Start a [discussion](https://discord.gg/pipecat)
-- **Want to contribute code?** Check our [CONTRIBUTING.md](CONTRIBUTING.md) guide
-- **Documentation improvements?** [Docs](https://github.com/pipecat-ai/docs) PRs are always welcome
+```
 
-Before submitting a pull request, please check existing issues and PRs to avoid duplicates.
+### Visual Studio Code
 
-We aim to review all contributions promptly and provide constructive feedback to help get your changes merged.
+Install the
+[autopep8](https://marketplace.visualstudio.com/items?itemName=ms-python.autopep8) extension. Then edit the user settings (_Ctrl-Shift-P_ `Open User Settings (JSON)`) and set it as the default Python formatter, enable formatting on save and configure `autopep8` arguments:
 
-## 🛟 Getting help
+```json
+"[python]": {
+    "editor.defaultFormatter": "ms-python.autopep8",
+    "editor.formatOnSave": true
+},
+"autopep8.args": [
+    "-a",
+    "-a",
+    "--max-line-length=100"
+],
+```
+
+## Getting help
 
 ➡️ [Join our Discord](https://discord.gg/pipecat)
 
-➡️ [Read the docs](https://docs.pipecat.ai)
-
 ➡️ [Reach us on X](https://x.com/pipecat_ai)

SECURITY.md

@@ -1,5 +0,0 @@
-# Security Policy
-
-## Reporting a Vulnerability
-
-Please email `disclosures@daily.co`.

changelog/3759.performance.md

@@ -1 +0,0 @@
-- Switched `GradiumTTSService` from `InterruptibleWordTTSService` to `AudioContextWordTTSService`, eliminating websocket disconnect/reconnect on every interruption by using `client_req_id`-based multiplexing.

changelog/3802.fixed.md

@@ -1 +0,0 @@
-- Fixed self-referential `pipecat-ai[local-smart-turn-v3]` dependency in `pyproject.toml` that caused Poetry 2.x to fail with a circular dependency error. The underlying packages (`transformers`, `onnxruntime`) are now listed directly in main dependencies.

changelog/_template.md.j2

@@ -1,16 +0,0 @@
-{% for section, _ in sections.items() %}
-{% if sections[section] %}
-{% for category, val in definitions.items() if category in sections[section]%}
-### {{ definitions[category]['name'] }}
-
-{% for text, values in sections[section][category].items() %}
-{{ text }}
-(PR {{ values|join(', ') }})
-
-{% endfor %}
-{% endfor %}
-{% else %}
-No significant changes.
-
-{% endif %}
-{% endfor %}

codecov.yml

@@ -1,11 +0,0 @@
-coverage:
-  range: 50..90 # coverage lower than 50 is red, higher than 90 green, between color code
-
-  status:
-    project:
-      default:
-        target: auto # auto % coverage target
-        threshold: 5%  # allow for 5% reduction of coverage without failing
-
-    # do not run coverage on patch nor changes
-    patch: false

dev-requirements.txt

@@ -0,0 +1,8 @@
+autopep8~=2.1.0
+build~=1.2.1
+grpcio-tools~=1.62.2
+pip-tools~=7.4.1
+pyright~=1.1.367
+pytest~=8.2.0
+setuptools~=69.5.1
+setuptools_scm~=8.1.0

docs/README.md

@@ -0,0 +1,10 @@
+# Pipecat Docs
+
+## [Architecture Overview](architecture.md)
+
+Learn about the thinking behind the framework's design.
+
+## [A Frame's Progress](frame-progress.md)
+
+See how a Frame is processed through a Transport, a Pipeline, and a series of Frame Processors.
+

docs/api/Makefile

@@ -1,20 +0,0 @@
-# Minimal makefile for Sphinx documentation
-#
-
-# You can set these variables from the command line, and also
-# from the environment for the first two.
-SPHINXOPTS    ?=
-SPHINXBUILD   ?= sphinx-build
-SOURCEDIR     = .
-BUILDDIR      = _build
-
-# Put it first so that "make" without argument is like "make help".
-help:
-	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
-
-.PHONY: help Makefile
-
-# Catch-all target: route all unknown targets to Sphinx using the new
-# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
-%: Makefile
-	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/api/README.md

@@ -1,109 +0,0 @@
-# Pipecat Documentation
-
-This directory contains the source files for auto-generating Pipecat's server API reference documentation.
-
-## Setup
-
-1. Install documentation dependencies:
-
-```bash
-pip install -r requirements.txt
-```
-
-2. Make the build scripts executable:
-
-```bash
-chmod +x build-docs.sh rtd-test.py
-```
-
-## Building Documentation
-
-From this directory, you can build the documentation in several ways:
-
-### Local Build
-
-```bash
-# Using the build script (automatically opens docs when done)
-./build-docs.sh
-
-# Or directly with sphinx-build
-sphinx-build -b html . _build/html -W --keep-going
-```
-
-### ReadTheDocs Test Build
-
-To test the documentation build process exactly as it would run on ReadTheDocs:
-
-```bash
-./rtd-test.py
-```
-
-This script:
-
-- Creates a fresh virtual environment
-- Installs all dependencies as specified in requirements files
-- Handles conflicting dependencies (like grpcio versions for Riva and PlayHT)
-- Builds the documentation in an isolated environment
-- Provides detailed logging of the build process
-
-Use this script to verify your documentation will build correctly on ReadTheDocs before pushing changes.
-
-## Viewing Documentation
-
-The built documentation will be available at `_build/html/index.html`. To open:
-
-```bash
-# On MacOS
-open _build/html/index.html
-
-# On Linux
-xdg-open _build/html/index.html
-
-# On Windows
-start _build/html/index.html
-```
-
-## Directory Structure
-
-```
-.
-├── api/            # Auto-generated API documentation
-├── _build/         # Built documentation
-├── _static/        # Static files (images, css, etc.)
-├── conf.py         # Sphinx configuration
-├── index.rst       # Main documentation entry point
-├── requirements-base.txt    # Base documentation dependencies
-├── requirements-riva.txt    # Riva-specific dependencies
-├── requirements-playht.txt  # PlayHT-specific dependencies
-├── build-docs.sh   # Local build script
-└── rtd-test.py     # ReadTheDocs test build script
-```
-
-## Notes
-
-- Documentation is auto-generated from Python docstrings
-- Service modules are automatically detected and included
-- The build process matches our ReadTheDocs configuration
-- Warnings are treated as errors (-W flag) to maintain consistency
-- The --keep-going flag ensures all errors are reported
-- Dependencies are split into multiple requirements files to handle version conflicts
-
-## Troubleshooting
-
-If you encounter missing service modules:
-
-1. Verify the service is installed with its extras: `pip install pipecat-ai[service-name]`
-2. Check the build logs for import errors
-3. Ensure the service module is properly initialized in the package
-4. Run `./rtd-test.py` to test in an isolated environment matching ReadTheDocs
-
-For dependency conflicts:
-
-1. Check the requirements files for version specifications
-2. Use `rtd-test.py` to verify dependency resolution
-3. Consider adding service-specific requirements files if needed
-
-For more information:
-
-- [ReadTheDocs Configuration](.readthedocs.yaml)
-- [Sphinx Documentation](https://www.sphinx-doc.org/)

docs/api/build-docs.sh

@@ -1,27 +0,0 @@
-#!/bin/bash
-
-# Build docs using uv
-echo "Installing dependencies with uv..."
-uv sync --group docs --all-extras --no-extra krisp --no-extra gstreamer --no-extra local_smart_turn --no-extra moondream --no-extra riva --no-extra mlx-whisper
-
-# Check if sphinx-build is available
-if ! uv run sphinx-build --version &> /dev/null; then
-    echo "Error: sphinx-build is not available" >&2
-    exit 1
-fi
-
-# Clean previous build
-rm -rf _build
-
-echo "Building documentation..."
-# Build docs matching ReadTheDocs configuration
-uv run sphinx-build -b html -d _build/doctrees . _build/html -W --keep-going
-
-if [ $? -eq 0 ]; then
-    echo "Documentation built successfully!"
-    # Open docs (MacOS)
-    open _build/html/index.html
-else
-    echo "Documentation build failed!" >&2
-    exit 1
-fi

docs/api/conf.py

@@ -1,226 +0,0 @@
-import logging
-import os
-import sys
-from datetime import datetime
-from pathlib import Path
-
-# Configure logging
-logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
-logger = logging.getLogger("sphinx-build")
-
-# Add source directory to path
-docs_dir = Path(__file__).parent
-project_root = docs_dir.parent.parent
-sys.path.insert(0, str(project_root / "src"))
-
-# Project information
-project = "pipecat-ai"
-current_year = datetime.now().year
-copyright = f"2024-{current_year}, Daily" if current_year > 2024 else "2024, Daily"
-author = "Daily"
-
-# General configuration
-extensions = [
-    "sphinx.ext.autodoc",
-    "sphinx.ext.napoleon",
-    "sphinx.ext.viewcode",
-    "sphinx.ext.intersphinx",
-]
-
-suppress_warnings = [
-    "autodoc.mocked_object",
-    "toc.not_included",
-]
-
-# Napoleon settings
-napoleon_google_docstring = True
-napoleon_include_init_with_doc = True
-
-# AutoDoc settings
-autodoc_default_options = {
-    "members": True,
-    "member-order": "bysource",
-    "undoc-members": False,
-    "exclude-members": "__weakref__,model_config",
-    "show-inheritance": True,
-}
-
-# Mock imports for optional dependencies
-autodoc_mock_imports = [
-    # Krisp - has build issues on some platforms
-    "pipecat_ai_krisp",
-    "krisp",
-    "krisp_audio",
-    # System-specific GUI libraries
-    "_tkinter",
-    "tkinter",
-    # Platform-specific audio libraries (if needed)
-    "gi",
-    "gi.require_version",
-    "gi.repository",
-    # OpenCV - sometimes has import issues during docs build
-    "cv2",
-    # Heavy ML packages excluded from ReadTheDocs
-    # local-smart-turn dependencies
-    "coremltools",
-    "coremltools.models",
-    "coremltools.models.MLModel",
-    "torch",
-    "torch.nn",
-    "torch.nn.functional",
-    "torchaudio",
-    # moondream dependencies
-    "transformers",
-    "transformers.AutoTokenizer",
-    "transformers.AutoFeatureExtractor",
-    "AutoFeatureExtractor",
-    "timm",
-    "einops",
-    "intel_extension_for_pytorch",
-    "huggingface_hub",
-    # riva dependencies
-    "riva",
-    "riva.client",
-    "riva.client.Auth",
-    "riva.client.ASRService",
-    "riva.client.StreamingRecognitionConfig",
-    "riva.client.RecognitionConfig",
-    "riva.client.AudioEncoding",
-    "riva.client.proto.riva_tts_pb2",
-    "riva.client.SpeechSynthesisService",
-    # MLX dependencies (Apple Silicon specific)
-    "mlx",
-    "mlx_whisper",  # Note: might need underscore format too
-    # Pydantic v2 compatibility issues in third-party SDKs
-    "hume",
-    "hume.tts",
-    "hume.tts.types",
-    "cartesia",
-    "camb",
-    "sarvamai",
-    "openpipe",
-    "openai.types.beta.realtime",
-    "langchain_core",
-    "langchain_core.messages",
-    # FastAPI - Pydantic v2 compatibility issues during Sphinx autodoc
-    "fastapi",
-    "fastapi.applications",
-    "fastapi.routing",
-    "fastapi.params",
-    "fastapi.middleware",
-    "fastapi.responses",
-    "uvicorn",
-]
-
-# HTML output settings
-html_theme = "sphinx_rtd_theme"
-html_static_path = ["_static"] if os.path.exists("_static") else []
-autodoc_typehints = "signature"  # Show type hints in the signature only, not in the docstring
-html_show_sphinx = False
-
-
-def import_core_modules():
-    """Import core pipecat modules for autodoc to discover."""
-    core_modules = [
-        "pipecat",
-        "pipecat.frames",
-        "pipecat.pipeline",
-        "pipecat.processors",
-        "pipecat.services",
-        "pipecat.transports",
-        "pipecat.audio",
-        "pipecat.adapters",
-        "pipecat.clocks",
-        "pipecat.metrics",
-        "pipecat.observers",
-        "pipecat.runner",
-        "pipecat.serializers",
-        "pipecat.transcriptions",
-        "pipecat.utils",
-    ]
-
-    for module_name in core_modules:
-        try:
-            __import__(module_name)
-            logger.info(f"Successfully imported {module_name}")
-        except ImportError as e:
-            logger.warning(f"Failed to import {module_name}: {e}")
-
-
-def clean_title(title: str) -> str:
-    """Automatically clean module titles."""
-    # Remove everything after space (like 'module', 'processor', etc.)
-    title = title.split(" ")[0]
-
-    # Get the last part of the dot-separated path
-    parts = title.split(".")
-    title = parts[-1]
-
-    return title
-
-
-def setup(app):
-    """Generate API documentation during Sphinx build."""
-    from sphinx.ext.apidoc import main
-
-    docs_dir = Path(__file__).parent
-    project_root = docs_dir.parent.parent
-    output_dir = str(docs_dir / "api")
-    source_dir = str(project_root / "src" / "pipecat")
-
-    # Clean existing files
-    if Path(output_dir).exists():
-        import shutil
-
-        shutil.rmtree(output_dir)
-        logger.info(f"Cleaned existing documentation in {output_dir}")
-
-    logger.info(f"Generating API documentation...")
-    logger.info(f"Output directory: {output_dir}")
-    logger.info(f"Source directory: {source_dir}")
-
-    excludes = [
-        str(project_root / "src/pipecat/pipeline/to_be_updated"),
-        str(project_root / "src/pipecat/examples"),
-        str(project_root / "src/pipecat/tests"),
-        "**/test_*.py",
-        "**/tests/*.py",
-    ]
-
-    try:
-        main(
-            [
-                "-f",  # Force overwriting
-                "-e",  # Don't generate empty files
-                "-M",  # Put module documentation before submodule documentation
-                "--no-toc",  # Don't create a table of contents file
-                "--separate",  # Put documentation for each module in its own page
-                "--module-first",  # Module documentation before submodule documentation
-                "--implicit-namespaces",  # Added: Handle implicit namespace packages
-                "-o",
-                output_dir,
-                source_dir,
-            ]
-            + excludes
-        )
-
-        logger.info("API documentation generated successfully!")
-
-        # Process generated RST files to update titles
-        for rst_file in Path(output_dir).glob("**/*.rst"):  # Changed to recursive glob
-            content = rst_file.read_text()
-            lines = content.split("\n")
-
-            # Find and clean up the title
-            if lines and "=" in lines[1]:  # Title is typically the first line
-                old_title = lines[0]
-                new_title = clean_title(old_title)
-                content = content.replace(old_title, new_title)
-                rst_file.write_text(content)
-                logger.info(f"Updated title: {old_title} -> {new_title}")
-
-    except Exception as e:
-        logger.error(f"Error generating API documentation: {e}", exc_info=True)
-
-
-import_core_modules()

docs/api/index.rst

@@ -1,35 +0,0 @@
-Pipecat API Reference
-=====================
-
-Welcome to the Pipecat API reference.
-
-Use the navigation on the left to browse modules, or search using the search box.
-
-**New to Pipecat?** Check out the `main documentation <https://docs.pipecat.ai>`_ for tutorials, guides, and client SDK information.
-
-Quick Links
------------
-
-* `GitHub Repository <https://github.com/pipecat-ai/pipecat>`_
-* `Join our Community <https://discord.gg/pipecat>`_
-
-.. toctree::
-   :maxdepth: 2
-   :caption: API Reference
-   :hidden:
-
-   Adapters <api/pipecat.adapters>
-   Audio <api/pipecat.audio>
-   Clocks <api/pipecat.clocks>
-   Extensions <api/pipecat.extensions>
-   Frames <api/pipecat.frames>
-   Metrics <api/pipecat.metrics>
-   Observers <api/pipecat.observers>
-   Pipeline <api/pipecat.pipeline>
-   Processors <api/pipecat.processors>
-   Runner <api/pipecat.runner>
-   Serializers <api/pipecat.serializers>
-   Services <api/pipecat.services>
-   Transcriptions <api/pipecat.transcriptions>
-   Transports <api/pipecat.transports>
-   Utils <api/pipecat.utils>

docs/api/make.bat

@@ -1,35 +0,0 @@
-@ECHO OFF
-
-pushd %~dp0
-
-REM Command file for Sphinx documentation
-
-if "%SPHINXBUILD%" == "" (
-	set SPHINXBUILD=sphinx-build
-)
-set SOURCEDIR=.
-set BUILDDIR=_build
-
-%SPHINXBUILD% >NUL 2>NUL
-if errorlevel 9009 (
-	echo.
-	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
-	echo.installed, then set the SPHINXBUILD environment variable to point
-	echo.to the full path of the 'sphinx-build' executable. Alternatively you
-	echo.may add the Sphinx directory to PATH.
-	echo.
-	echo.If you don't have Sphinx installed, grab it from
-	echo.https://www.sphinx-doc.org/
-	exit /b 1
-)
-
-if "%1" == "" goto help
-
-%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-goto end
-
-:help
-%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-
-:end
-popd

docs/api/rtd-test.sh

@@ -1,38 +0,0 @@
-#!/bin/bash
-set -e
-
-# Configuration
-DOCS_DIR=$(pwd)
-PROJECT_ROOT=$(cd ../../ && pwd)
-TEST_DIR="/tmp/rtd-test-$(date +%Y%m%d_%H%M%S)"
-
-echo "Creating test directory: $TEST_DIR"
-mkdir -p "$TEST_DIR"
-cd "$TEST_DIR"
-
-# Create virtual environment
-python -m venv venv
-source venv/bin/activate
-
-echo "Installing build dependencies..."
-pip install --upgrade pip wheel setuptools
-
-echo "Installing documentation dependencies..."
-pip install -r "$DOCS_DIR/requirements.txt"
-
-echo "Building documentation..."
-cd "$DOCS_DIR"
-sphinx-build -b html . "_build/html"
-
-echo "Build complete. Check _build/html directory for output."
-
-# Print summary
-echo -e "\n=== Build Summary ==="
-echo "Documentation: $DOCS_DIR/_build/html"
-echo "Test environment: $TEST_DIR"
-echo -e "\nTo view the documentation:"
-echo "open $DOCS_DIR/_build/html/index.html"
-
-# Print installed packages for verification
-echo -e "\n=== Installed Packages ==="
-pip freeze | grep -E "sphinx|pipecat"

docs/architecture.md

@@ -0,0 +1,17 @@
+# Pipecat architecture guide
+
+## Frames
+
+Frames can represent discrete chunks of data, for instance a chunk of text, a chunk of audio, or an image. They can also be used to as control flow, for instance a frame that indicates that there is no more data available, or that a user started or stopped talking. They can also represent more complex data structures, such as a message array used for an LLM completion.
+
+## FrameProcessors
+
+Frame processors operate on frames. Every frame processor implements a `process_frame` method that consumes one frame and produces zero or more frames. Frame processors can do simple transforms, such as concatenating text fragments into sentences, or they can treat frames as input for an AI Service, and emit chat completions based on message arrays or transform text into audio or images.
+
+## Pipelines
+
+Pipelines are lists of frame processors linked together. Frame processors can push frames upstream or downstream to their peers. A very simple pipeline might chain an LLM frame processor to a text-to-speech frame processor, with a transport as an output.
+
+## Transports
+
+Transports provide input and output frame processors to receive or send frames respectively. For example, the `DailyTransport` does this with a WebRTC session joined to a Daily.co room.

docs/frame-progress.md

@@ -0,0 +1,46 @@
+# A Frame's Progress
+
+1. A user says “Hello, LLM” and the cloud transcription service delivers a transcription to the Transport.
+![A transcript frame arrives](images/frame-progress-01.png)
+
+2. The Transport places a Transcription frame in the Pipeline’s source queue.
+![Frame in source queue](images/frame-progress-02.png)
+
+3. The Pipeline passes the Transcription frame to the first Frame Processor in its list, the LLM User Message Aggregator.
+![To UMA](images/frame-progress-03.png)
+
+4. The LLM User Message Aggregator updates the LLM Context with a `{“user”: “Hello LLM”}` message.
+![Update context](images/frame-progress-04.png)
+
+5. The LLM User Message Aggregator yields an LLM Message Frame, containing the updated LLM Context. The Pipeline passes this frame to the LLM Frame Processor.
+![Update context](images/frame-progress-05.png)
+
+6. The LLM Frame Processor creates a streaming chat completion based on the LLM context and yields the first chunk of a response, Text Frame with the value “Hi, “. The Pipeline passes this frame to the TTS Frame Processor. The TTS Frame Processor aggregates this response but doesn’t yield anything, yet, because it’s waiting for a full sentence.
+![LLM yields Text](images/frame-progress-06.png)
+
+7. The LLM Frame Processor yields another Text Frame with the value “there.”. The Pipeline passes this frame to the TTS Frame Processor.
+![LLM yields more Text](images/frame-progress-07.png)
+
+8. The TTS Frame Processor now has a full sentence, so it starts streaming audio based on “Hi, there.” It yields the first chunk of streaming audio as an Audio frame, which the Pipeline passes to the LLM Assistant Message Aggregator.
+![TTS yields Audio](images/frame-progress-08.png)
+
+9. The LLM Assistant Message Aggregator doesn’t do anything with Audio frames, so it immediately yields the frame, unchanged. This is the convention for all Frame Processors: frames that the processor doesn’t process should be immediately yielded.
+![pass-through](images/frame-progress-09.png)
+
+10. The Pipeline places the first Audio frame in its sink queue, which is being watched by the Transport. Since the frame is now in a queue, the Pipeline can continue processing other frames. Note that the source and sink queues form a sort of “boundary of concurrent processing” between a Pipeline and the outside world. In a Pipeline, Frames are processed sequentially; once a Frame is on a queue it can be processed in parallel with the frames being processed by the Pipeline. TODO: link to a more in-depth section about this.
+![sink queue](images/frame-progress-10.png)
+
+11. The TTS Frame Processor yields another Audio frame as the Transport transmits the first Audio frame.
+![parallel audio](images/frame-progress-11.png)
+
+12. As before, the LLM Assistant Message Aggregator immediately yields the Audio frame and the Pipeline places the Audio frame in the sink queue.
+![sink queue 2](images/frame-progress-12.png)
+
+13. The TTS Frame Processor has no more frames to yield. The LLM Frame Processor emits an LLM Response End Frame, which the Pipeline passes to the TTS Frame Processor.
+![response end](images/frame-progress-13.png)
+
+14. The TTS Frame Processor immediately yields the LLM Response End Frame, so the Pipeline passes it along to the LLM Assistant Message Aggregator. The LLM Assistant Message Aggregator updates the LLM Context with the full response from the LLM. TODO TODO: I realized I forgot that the TSS Frame Processor also yields the Text frames that the LLM emitted so that the LLM Assistant Message Aggregator could accumulate them, arrggh.
+![response end](images/frame-progress-14.png)
+
+15. The system is quiet, and waiting for the next message from the Transport.
+![response end](images/frame-progress-15.png)

dot-env.template

@@ -0,0 +1,38 @@
+# Anthropic
+ANTHROPIC_API_KEY=...
+
+# Azure
+AZURE_SPEECH_REGION=...
+AZURE_SPEECH_API_KEY=...
+
+AZURE_CHATGPT_API_KEY=...
+AZURE_CHATGPT_ENDPOINT=https://...
+AZURE_CHATGPT_MODEL=...
+
+AZURE_DALLE_API_KEY=...
+AZURE_DALLE_ENDPOINT=https://...
+AZURE_DALLE_MODEL=...
+
+# Daily
+DAILY_API_KEY=...
+DAILY_SAMPLE_ROOM_URL=https://...
+
+# ElevenLabs
+ELEVENLABS_API_KEY=...
+ELEVENLABS_VOICE_ID=...
+
+# Fal
+FAL_KEY=...
+
+# Fireworks
+FIREWORKS_API_KEY=...
+
+# PlayHT
+PLAY_HT_USER_ID=...
+PLAY_HT_API_KEY=...
+
+# OpenAI
+OPENAI_API_KEY=...
+
+#OpenPipe
+OPENPIPE_API_KEY=...

env.example

@@ -1,213 +0,0 @@
-# AI-COUSTICS
-AICOUSTICS_LICENSE_KEY=...
-
-# Anthropic
-ANTHROPIC_API_KEY=...
-
-# Assembly AI
-ASSEMBLYAI_API_KEY=...
-
-# Async
-ASYNCAI_API_KEY=...
-ASYNCAI_VOICE_ID=...
-
-# AWS
-AWS_SECRET_ACCESS_KEY=...
-AWS_ACCESS_KEY_ID=...
-AWS_REGION=...
-
-# Azure
-AZURE_SPEECH_REGION=...
-AZURE_SPEECH_API_KEY=...
-
-AZURE_CHATGPT_API_KEY=...
-AZURE_CHATGPT_ENDPOINT=https://...
-AZURE_CHATGPT_MODEL=...
-
-AZURE_REALTIME_API_KEY=...
-AZURE_REALTIME_BASE_URL=...
-
-AZURE_DALLE_API_KEY=...
-AZURE_DALLE_ENDPOINT=https://...
-AZURE_DALLE_MODEL=...
-
-# Camb.ai
-CAMB_API_KEY=...
-
-# Cartesia
-CARTESIA_API_KEY=...
-CARTESIA_VOICE_ID=...
-
-# Cerebras
-CEREBRAS_API_KEY=...
-
-# Daily
-DAILY_API_KEY=...
-DAILY_ROOM_URL=https://...
-
-# Deepgram
-DEEPGRAM_API_KEY=...
-SAGEMAKER_STT_ENDPOINT_NAME=...
-SAGEMAKER_TTS_ENDPOINT_NAME=...
-
-# DeepSeek
-DEEPSEEK_API_KEY=...
-
-# ElevenLabs
-ELEVENLABS_API_KEY=...
-ELEVENLABS_VOICE_ID=...
-
-# Fal
-FAL_KEY=...
-
-# Fireworks
-FIREWORKS_API_KEY=...
-
-# Fish Audio
-FISH_API_KEY=...
-
-# Gladia
-GLADIA_API_KEY=...
-GLADIA_REGION=...
-
-# Google
-GOOGLE_API_KEY=...
-GOOGLE_VERTEX_TEST_CREDENTIALS=...
-GOOGLE_CLOUD_PROJECT_ID=...
-GOOGLE_CLOUD_LOCATION=...
-GOOGLE_TEST_CREDENTIALS=...
-
-# Gradium
-GRAPDIUM_API_KEY=...
-
-# Grok
-GROK_API_KEY=...
-
-# Groq
-GROQ_API_KEY=...
-
-# Hathora
-HATHORA_API_KEY=...
-
-# Heygen
-HEYGEN_API_KEY=...
-HEYGEN_LIVE_AVATAR_API_KEY=...
-
-# Hume
-HUME_API_KEY=...
-HUME_VOICE_ID=...
-
-# Inworld
-INWORLD_API_KEY=...
-
-# Krisp
-KRISP_MODEL_PATH=...
-
-# Krisp Viva
-KRISP_VIVA_FILTER_MODEL_PATH=...
-KRISP_VIVA_TURN_MODEL_PATH=...
-
-# LiveKit
-LIVEKIT_API_KEY=...
-LIVEKIT_API_SECRET=...
-
-# LMNT
-LMNT_API_KEY=...
-LMNT_VOICE_ID=...
-
-# MiniMax
-MINIMAX_API_KEY=...
-MINIMAX_GROUP_ID=...
-
-# Mistral
-MISTRAL_API_KEY=...
-
-# Neuphonic
-NEUPHONIC_API_KEY=...
-
-# NVIDIA
-NVIDIA_API_KEY=...
-
-# OpenAI
-OPENAI_API_KEY=...
-
-# OpenPipe
-OPENPIPE_API_KEY=...
-
-# OpenRouter
-OPENROUTER_API_KEY=...
-
-# Perplexity
-PERPLEXITY_API_KEY=...
-
-# Picovoice Koala
-KOALA_ACCESS_KEY=...
-
-# Piper
-PIPER_BASE_URL=...
-
-# PlayHT
-PLAYHT_USER_ID=...
-PLAYHT_API_KEY=...
-
-# Plivo
-PLIVO_AUTH_ID=...
-PLIVO_AUTH_TOKEN=...
-
-# Qwen
-QWEN_API_KEY=...
-
-# Resemble AI
-RESEMBLE_API_KEY=
-RESEMBLE_VOICE_UUID=
-
-# Rime
-RIME_API_KEY=...
-RIME_VOICE_ID=...
-
-# SambaNova
-SAMBANOVA_API_KEY=...
-
-# Sarvam AI
-SARVAM_API_KEY=...
-
-# Sentry
-SENTRY_DSN=...
-
-# Simli
-SIMLI_API_KEY=...
-SIMLI_FACE_ID=...
-
-# Smart turn
-LOCAL_SMART_TURN_MODEL_PATH=...
-FAL_SMART_TURN_API_KEY=...
-
-# Soniox
-SONIOX_API_KEY=...
-
-# Speechmatics
-SPEECHMATICS_API_KEY=...
-
-# Tavus
-TAVUS_API_KEY=...
-TAVUS_REPLICA_ID=...
-
-# Telnyx
-TELNYX_API_KEY=...
-TELNYX_ACCOUNT_SID=...
-
-# Together.ai
-TOGETHER_API_KEY=...
-
-# Twilio
-TWILIO_ACCOUNT_SID=...
-TWILIO_AUTH_TOKEN=...
-
-# Ultravox Realtime
-ULTRAVOX_API_KEY=...
-
-# WhatsApp
-WHATSAPP_TOKEN=...
-WHATSAPP_WEBHOOK_VERIFICATION_TOKEN=...
-WHATSAPP_PHONE_NUMBER_ID=...
-WHATSAPP_APP_SECRET=...

examples/README.md

@@ -1,31 +1,86 @@
-# Pipecat Examples
 
-This directory contains examples to help you learn how to build with Pipecat.
 
-## Getting Started
+# Pipecat — Examples
 
-New to Pipecat? Start here:
+## Foundational snippets
+Small snippets that build on each other, introducing one or two concepts at a time.
 
-- **[Quickstart](quickstart/)** - Get your first voice AI bot running in 5 minutes _(coming soon)_
-- **[Client/Server Web](client-server-web/)** - Learn to build web applications with Pipecat's client SDKs _(coming soon)_
-- **[Phone Bot with Twilio](phone-bot-twilio/)** - Connect your bot to a phone number _(coming soon)_
+➡️ [Take a look](https://github.com/pipecat-ai/pipecat/tree/main/examples/foundational)
 
-## Foundational Examples
+## Chatbot examples
+Collection of self-contained real-time voice and video AI demo applications built with Pipecat.
 
-Single-file examples that introduce core Pipecat concepts one at a time. These examples:
+### Quickstart
 
-- Build on each other progressively
-- Focus on specific features or integrations
-- Are used for testing with every Pipecat release
+Each project has its own set of dependencies and configuration variables. They intentionally avoids shared code across projects — you can grab whichever demo folder you want to work with as a starting point.
 
-See the **[Foundational Examples README](foundational/)** for the complete list.
+We recommend you start with a virtual environment:
 
-## More Advanced Examples
+```shell
+cd pipecat-ai/examples/simple-chatbot
 
-Ready to explore complex use cases? Visit **[pipecat-examples](https://github.com/pipecat-ai/pipecat-examples)** for:
+python -m venv venv
 
-- Production-ready applications
-- Multi-platform client implementations
-- Telephony integrations
-- Multimodal and creative applications
-- Deployment and monitoring examples
+source venv/bin/activate
+
+pip install -r requirements.txt
+```
+
+Next, follow the steps in the README for each demo.
+
+ℹ️ Make sure you `pip install -r requirements.txt` for each demo project, so you can be sure to have the necessary service dependencies that extend the functionality of Pipecat. You can read more about the framework architecture [here](https://github.com/pipecat-ai/pipecat/tree/main/docs).
+
+## Projects:
+
+| Project                                      | Description                                                                                                                                | Services                                                          |
+|----------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------|
+| [Simple Chatbot](simple-chatbot)             | Basic voice-driven conversational bot. A good starting point for learning the flow of the framework.                                       | Deepgram, ElevenLabs, OpenAI, Daily, Daily Prebuilt UI            |
+| [Storytelling Chatbot](storytelling-chatbot) | Stitches together multiple third-party services to create a collaborative storytime experience.                                            | Deepgram, ElevenLabs, OpenAI, Fal, Daily, Custom UI               |
+| [Translation Chatbot](translation-chatbot)   | Listens for user speech, then translates that speech to Spanish and speaks the translation back. Demonstrates multi-participant use-cases. | Deepgram, Azure, OpenAI, Daily, Daily Prebuilt UI                 |
+| [Moondream Chatbot](moondream-chatbot)       | Demonstrates how to add vision capabilities to GPT4. **Note: works best with a GPU**                                                       | Deepgram, ElevenLabs, OpenAI, Moondream, Daily, Daily Prebuilt UI |
+| [Patient intake](patient-intake)             | A chatbot that can call functions in response to user input.                                                                               | Deepgram, ElevenLabs, OpenAI, Daily, Daily Prebuilt UI            |
+| [Dialin Chatbot](dialin-chatbot)             | A chatbot that connects to an incoming phone call from Daily or Twilio.                                                                    | Deepgram, ElevenLabs, OpenAI, Daily, Twilio                       |
+| [Twilio Chatbot](twilio-chatbot)             | A chatbot that connects to an incoming phone call from Twilio.                                                                             | Deepgram, ElevenLabs, OpenAI, Daily, Twilio                       |
+
+> [!IMPORTANT]
+> These example projects use Daily as a WebRTC transport and can be joined using their hosted Prebuilt UI.
+> It provides a quick way to join a real-time session with your bot and test your ideas without building any frontend code. If you'd like to see an example of a custom UI, try Storybot.
+
+
+## FAQ
+
+### Deployment
+
+For each of these demos we've included a `Dockerfile`. Out of the box, this should provide everything needed to get the respective demo running on a VM:
+
+```shell
+docker build username/app:tag .
+
+docker run -p 7860:7860 --env-file ./.env username/app:tag
+
+docker push ...
+```
+
+### SSL
+
+If you're working with a custom UI (such as with the Storytelling Chatbot), it's important to ensure your deployment platform supports HTTPS, as accessing user devices such as mics and webcams requires SSL.
+
+If you try to run a custom UI without SSL, you may see an error in the console telling you that `navigator` is undefined, or no devices are available.
+
+### Are these examples production ready?
+
+Yes, kind of.
+
+These demos attempt to keep things simple and are unopinionated regarding environment or scalability.
+
+We're using FastAPI to spawn a subprocess for the bots / agents — useful for small tests, but not so great for production grade apps with many concurrent users. You can see how this works in each project's `start` endpoint in `server.py`.
+
+Creating virtualized worker pools and on-demand instances is out of scope for these examples, but we hope to add some examples to this repo soon!
+
+For projects that have CUDA as a requirement, such as Moondream Chatbot, be sure to deploy to a GPU-powered platform (such as [fly.io](https://fly.io) or [Runpod](https://runpod.io).)
+
+## Getting help
+
+➡️ [Join our Discord](https://discord.gg/pipecat)
+
+➡️ [Reach us on Twitter](https://x.com/pipecat_ai)

examples/dialin-chatbot/.dockerignore

@@ -0,0 +1,3 @@
+**/.DS_Store
+.env
+.env.*

examples/dialin-chatbot/.gitignore

@@ -0,0 +1,165 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+runpod.toml
+
+# custom script to recursively upgrade items in requirements.py
+upgrade_requirements.py
+.DS_Store

examples/dialin-chatbot/Dockerfile

@@ -0,0 +1,40 @@
+FROM python:3.11-bullseye
+
+ARG DEBIAN_FRONTEND=noninteractive
+ARG USE_PERSISTENT_DATA
+ENV PYTHONUNBUFFERED=1
+# Expose FastAPI port
+ENV FAST_API_PORT=7860
+EXPOSE 7860
+
+# Install system dependencies
+RUN apt-get update && apt-get install --no-install-recommends -y \
+    build-essential \
+    git \
+    ffmpeg \
+    google-perftools \
+    ca-certificates curl gnupg \
+    && apt-get clean && rm -rf /var/lib/apt/lists/*
+
+# Set up a new user named "user" with user ID 1000
+RUN useradd -m -u 1000 user
+
+# Set home to the user's home directory
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH \
+    PYTHONPATH=$HOME/app \
+    PYTHONUNBUFFERED=1
+
+# Switch to the "user" user
+USER user
+
+# Set the working directory to the user's home directory
+WORKDIR $HOME/app
+
+# Install Python dependencies
+COPY *.py .
+COPY ./requirements.txt requirements.txt
+RUN pip3 install --no-cache-dir --upgrade -r requirements.txt
+
+# Start the FastAPI server
+CMD python3 bot_runner.py --host "0.0.0.0" --port ${FAST_API_PORT}

examples/dialin-chatbot/README.md

@@ -0,0 +1,85 @@
+<div align="center">
+ <img alt="pipecat" width="300px" height="auto" src="image.png">
+</div>
+
+# Dialin example
+
+Example project that demonstrates how to add phone number dialin to your Pipecat bots. We include examples for both Daily (`bot_daily.py`) and Twilio (`bot_twilio.py`), depending on who you want to use as a phone vendor.
+
+- 🔁 Transport: Daily WebRTC
+- 💬 Speech-to-Text: Deepgram via Daily transport
+- 🤖 LLM: GPT4-o / OpenAI
+- 🔉 Text-to-Speech: ElevenLabs
+
+#### Should I use Daily or Twilio as a vendor?
+
+If you're starting from scratch, using Daily to provision phone numbers alongside Daily as a transport offers some convenience (such as automatic call forwarding.)
+
+If you already have Twilio numbers and workflows that you want to connect to your Pipecat bots, there is some additional configuration required (you'll need to create a `on_dialin_ready` and use the Twilio client to trigger the forward.)
+
+You can read more about this, as well as see respective walkthroughs in our docs.
+
+## Setup
+
+```shell
+# Install the requirements
+pip install -r requirements.txt
+
+# Setup your env
+mv env.example .env
+```
+
+## Using Daily numbers
+
+Run `bot_runner.py` to handle incoming HTTP requests:
+
+`python bot_runner.py --host localhost`
+
+Then target the following URL:
+
+`POST /daily_start_bot`
+
+For more configuration options, please consult Daily's API documentation.
+
+
+## Using Twilio numbers
+
+As above, but target the following URL:
+
+`POST /twilio_start_bot`
+
+For more configuration options, please consult Twilio's API documentation.
+
+## Deployment example
+
+A Dockerfile is included in this demo for convenience. Here is an example of how to build and deploy your bot to [fly.io](https://fly.io).
+
+*Please note: This demo spawns agents as subprocesses for convenience / demonstration purposes. You would likely not want to do this in production as it would limit concurrency to available system resources. For more information on how to deploy your bots using VMs, refer to the Pipecat documentation.*
+
+### Build the docker image
+
+`docker build -t tag:project .`
+
+### Launch the fly project
+
+`mv fly.example.toml fly.toml`
+
+`fly launch` (using the included fly.toml)
+
+### Setup your secrets on Fly
+
+Set the necessary secrets (found in `env.example`)
+
+`fly secrets set DAILY_API_KEY=... OPENAI_API_KEY=... ELEVENLABS_API_KEY=... ELEVENLABS_VOICE_ID=...`
+
+If you're using Twilio as a number vendor:
+
+`fly secrets set TWILIO_ACCOUNT_SID=... TWILIO_AUTH_TOKEN=...`
+
+### Deploy!
+
+`fly deploy`
+
+## Need to do something more advanced?
+
+This demo covers the basics of bot telephony. If you want to know more about working with PSTN / SIP, please ping us on [Discord](https://discord.gg/pipecat).

examples/dialin-chatbot/bot_daily.py

@@ -0,0 +1,111 @@
+import asyncio
+import aiohttp
+import os
+import sys
+import argparse
+
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
+from pipecat.frames.frames import (
+    LLMMessagesFrame,
+    EndFrame
+)
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport, DailyDialinSettings
+from pipecat.vad.silero import SileroVADAnalyzer
+from loguru import logger
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+daily_api_key = os.getenv("DAILY_API_KEY", "")
+daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")
+
+
+async def main(room_url: str, token: str, callId: str, callDomain: str):
+    async with aiohttp.ClientSession() as session:
+        # diallin_settings are only needed if Daily's SIP URI is used
+        # If you are handling this via Twilio, Telnyx, set this to None
+        # and handle call-forwarding when on_dialin_ready fires.
+        diallin_settings = DailyDialinSettings(
+            call_id=callId,
+            call_domain=callDomain
+        )
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Chatbot",
+            DailyParams(
+                api_url=daily_api_url,
+                api_key=daily_api_key,
+                dialin_settings=diallin_settings,
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                camera_out_enabled=False,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+                transcription_enabled=True,
+            )
+        )
+
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY", ""),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
+        )
+
+        llm = OpenAILLMService(
+            api_key=os.getenv("OPENAI_API_KEY"),
+            model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are Chatbot, a friendly, helpful robot. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way, but keep your responses brief. Start by saying 'Oh, hello! Who dares dial me at this hour?!'.",
+            },
+        ]
+
+        tma_in = LLMUserResponseAggregator(messages)
+        tma_out = LLMAssistantResponseAggregator(messages)
+
+        pipeline = Pipeline([
+            transport.input(),
+            tma_in,
+            llm,
+            tts,
+            transport.output(),
+            tma_out,
+        ])
+
+        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            transport.capture_participant_transcription(participant["id"])
+            await task.queue_frames([LLMMessagesFrame(messages)])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.queue_frame(EndFrame())
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Pipecat Simple ChatBot")
+    parser.add_argument("-u", type=str, help="Room URL")
+    parser.add_argument("-t", type=str, help="Token")
+    parser.add_argument("-i", type=str, help="Call ID")
+    parser.add_argument("-d", type=str, help="Call Domain")
+    config = parser.parse_args()
+
+    asyncio.run(main(config.u, config.t, config.i, config.d))

examples/dialin-chatbot/bot_runner.py

@@ -0,0 +1,220 @@
+"""
+bot_runner.py
+
+HTTP service that listens for incoming calls from either Daily or Twilio,
+provisioning a room and starting a Pipecat bot in response.
+
+Refer to README for more information.
+"""
+import os
+import argparse
+import subprocess
+from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomObject, DailyRoomProperties, DailyRoomSipParams, DailyRoomParams
+from fastapi import FastAPI, Request, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse, PlainTextResponse
+from twilio.twiml.voice_response import VoiceResponse
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+
+# ------------ Configuration ------------ #
+
+MAX_SESSION_TIME = 5 * 60  # 5 minutes
+REQUIRED_ENV_VARS = ['OPENAI_API_KEY', 'DAILY_API_KEY',
+                     'ELEVENLABS_API_KEY', 'ELEVENLABS_VOICE_ID']
+
+daily_rest_helper = DailyRESTHelper(
+    os.getenv("DAILY_API_KEY", ""),
+    os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'))
+
+
+# ----------------- API ----------------- #
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"]
+)
+
+"""
+Create Daily room, tell the bot if the room is created for Twilio's SIP or Daily's SIP (vendor).
+When the vendor is Daily, the bot handles the call forwarding automatically,
+i.e, forwards the call from the "hold music state" to the Daily Room's SIP URI.
+
+Alternatively, when the vendor is Twilio (not Daily), the bot is responsible for
+updating the state on Twilio. So when `dialin-ready` fires, it takes appropriate
+action using the Twilio Client library.
+"""
+
+
+def _create_daily_room(room_url, callId, callDomain=None, vendor="daily"):
+    if not room_url:
+        params = DailyRoomParams(
+            properties=DailyRoomProperties(
+                # Note: these are the default values, except for the display name
+                sip=DailyRoomSipParams(
+                    display_name="dialin-user",
+                    video=False,
+                    sip_mode="dial-in",
+                    num_endpoints=1
+                )
+            )
+        )
+
+        print(f"Creating new room...")
+        room: DailyRoomObject = daily_rest_helper.create_room(params=params)
+
+    else:
+        # Check passed room URL exist (we assume that it already has a sip set up!)
+        try:
+            print(f"Joining existing room: {room_url}")
+            room: DailyRoomObject = daily_rest_helper.get_room_from_url(
+                room_url)
+        except Exception:
+            raise HTTPException(
+                status_code=500, detail=f"Room not found: {room_url}")
+
+    print(f"Daily room: {room.url} {room.config.sip_endpoint}")
+
+    # Give the agent a token to join the session
+    token = daily_rest_helper.get_token(room.url, MAX_SESSION_TIME)
+
+    if not room or not token:
+        raise HTTPException(
+            status_code=500, detail=f"Failed to get room or token token")
+
+    # Spawn a new agent, and join the user session
+    # Note: this is mostly for demonstration purposes (refer to 'deployment' in docs)
+    if vendor == "daily":
+        bot_proc = f"python3 -m bot_daily -u {room.url} -t {token} -i {
+            callId} -d {callDomain}"
+    else:
+        bot_proc = f"python3 -m bot_twilio -u {room.url} -t {
+            token} -i {callId} -s {room.config.sip_endpoint}"
+
+    try:
+        subprocess.Popen(
+            [bot_proc],
+            shell=True,
+            bufsize=1,
+            cwd=os.path.dirname(os.path.abspath(__file__))
+        )
+    except Exception as e:
+        raise HTTPException(
+            status_code=500, detail=f"Failed to start subprocess: {e}")
+
+    return room
+
+
+@app.post("/twilio_start_bot", response_class=PlainTextResponse)
+async def twilio_start_bot(request: Request):
+    print(f"POST /twilio_voice_bot")
+
+    # twilio_start_bot is invoked directly by Twilio (as a web hook).
+    # On Twilio, under Active Numbers, pick the phone number
+    # Click Configure and under Voice Configuration,
+    # "a call comes in" choose webhook and point the URL to
+    # where this code is hosted.
+    data = {}
+    try:
+        # shouldnt have received json, twilio sends form data
+        form_data = await request.form()
+        data = dict(form_data)
+    except Exception:
+        pass
+
+    room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", None)
+    callId = data.get('CallSid')
+
+    if not callId:
+        raise HTTPException(
+            status_code=500, detail="Missing 'CallSid' in request")
+
+    print("CallId: %s" % callId)
+
+    # create room and tell the bot to join the created room
+    # note: Twilio does not require a callDomain
+    room: DailyRoomObject = _create_daily_room(
+        room_url, callId, None, "twilio")
+
+    print(f"Put Twilio on hold...")
+    # We have the room and the SIP URI,
+    # but we do not know if the Daily SIP Worker and the Bot have joined the call
+    # put the call on hold until the 'on_dialin_ready' fires.
+    # Then, the bot will update the called sid with the sip uri.
+    # http://com.twilio.music.classical.s3.amazonaws.com/BusyStrings.mp3
+    resp = VoiceResponse()
+    resp.play(
+        url="http://com.twilio.sounds.music.s3.amazonaws.com/MARKOVICHAMP-Borghestral.mp3", loop=10)
+    return str(resp)
+
+
+@app.post("/daily_start_bot")
+async def daily_start_bot(request: Request) -> JSONResponse:
+    # The /daily_start_bot is invoked when a call is received on Daily's SIP URI
+    # daily_start_bot will create the room, put the call on hold until
+    # the bot and sip worker are ready. Daily will automatically
+    # forward the call to the SIP URi when dialin_ready fires.
+
+    # Use specified room URL, or create a new one if not specified
+    room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", None)
+    # Get the dial-in properties from the request
+    try:
+        data = await request.json()
+        if "test" in data:
+            # Pass through any webhook checks
+            return JSONResponse({"test": True})
+        callId = data.get("callId", None)
+        callDomain = data.get("callDomain", None)
+    except Exception:
+        raise HTTPException(
+            status_code=500,
+            detail="Missing properties 'callId' or 'callDomain'")
+
+    print(f"CallId: {callId}, CallDomain: {callDomain}")
+    room: DailyRoomObject = _create_daily_room(
+        room_url, callId, callDomain, "daily")
+
+    # Grab a token for the user to join with
+    return JSONResponse({
+        "room_url": room.url,
+        "sipUri": room.config.sip_endpoint
+    })
+
+# ----------------- Main ----------------- #
+
+
+if __name__ == "__main__":
+    # Check environment variables
+    for env_var in REQUIRED_ENV_VARS:
+        if env_var not in os.environ:
+            raise Exception(f"Missing environment variable: {env_var}.")
+
+    parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
+    parser.add_argument("--host", type=str,
+                        default=os.getenv("HOST", "0.0.0.0"), help="Host address")
+    parser.add_argument("--port", type=int,
+                        default=os.getenv("PORT", 7860), help="Port number")
+    parser.add_argument("--reload", action="store_true",
+                        default=True, help="Reload code on change")
+
+    config = parser.parse_args()
+
+    try:
+        import uvicorn
+
+        uvicorn.run(
+            "bot_runner:app",
+            host=config.host,
+            port=config.port,
+            reload=config.reload
+        )
+
+    except KeyboardInterrupt:
+        print("Pipecat runner shutting down...")

examples/dialin-chatbot/bot_twilio.py

@@ -0,0 +1,125 @@
+import asyncio
+import aiohttp
+import os
+import sys
+import argparse
+
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
+from pipecat.frames.frames import (
+    LLMMessagesFrame,
+    EndFrame
+)
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.vad.silero import SileroVADAnalyzer
+
+from twilio.rest import Client
+
+from loguru import logger
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+
+twilio_account_sid = os.getenv('TWILIO_ACCOUNT_SID')
+twilio_auth_token = os.getenv('TWILIO_AUTH_TOKEN')
+twilioclient = Client(twilio_account_sid, twilio_auth_token)
+
+daily_api_key = os.getenv("DAILY_API_KEY", "")
+
+
+async def main(room_url: str, token: str, callId: str, sipUri: str):
+    async with aiohttp.ClientSession() as session:
+        # diallin_settings are only needed if Daily's SIP URI is used
+        # If you are handling this via Twilio, Telnyx, set this to None
+        # and handle call-forwarding when on_dialin_ready fires.
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Chatbot",
+            DailyParams(
+                api_key=daily_api_key,
+                dialin_settings=None,  # Not required for Twilio
+                audio_in_enabled=True,
+                audio_out_enabled=True,
+                camera_out_enabled=False,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(),
+                transcription_enabled=True,
+            )
+        )
+
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY", ""),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
+        )
+
+        llm = OpenAILLMService(
+            api_key=os.getenv("OPENAI_API_KEY"),
+            model="gpt-4o")
+
+        messages = [
+            {
+                "role": "system",
+                "content": "You are Chatbot, a friendly, helpful robot. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way, but keep your responses brief. Start by saying 'Hello! Who dares dial me at this hour?!'.",
+            },
+        ]
+
+        tma_in = LLMUserResponseAggregator(messages)
+        tma_out = LLMAssistantResponseAggregator(messages)
+
+        pipeline = Pipeline([
+            transport.input(),
+            tma_in,
+            llm,
+            tts,
+            transport.output(),
+            tma_out,
+        ])
+
+        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            transport.capture_participant_transcription(participant["id"])
+            await task.queue_frames([LLMMessagesFrame(messages)])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.queue_frame(EndFrame())
+
+        @transport.event_handler("on_dialin_ready")
+        async def on_dialin_ready(transport, cdata):
+            # For Twilio, Telnyx, etc. You need to update the state of the call
+            # and forward it to the sip_uri..
+            print(f"Forwarding call: {callId} {sipUri}")
+
+            try:
+                # The TwiML is updated using Twilio's client library
+                call = twilioclient.calls(callId).update(
+                    twiml=f'<Response><Dial><Sip>{sipUri}</Sip></Dial></Response>'
+                )
+            except Exception as e:
+                raise Exception(f"Failed to forward call: {str(e)}")
+
+        runner = PipelineRunner()
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Pipecat Simple ChatBot")
+    parser.add_argument("-u", type=str, help="Room URL")
+    parser.add_argument("-t", type=str, help="Token")
+    parser.add_argument("-i", type=str, help="Call ID")
+    parser.add_argument("-s", type=str, help="SIP URI")
+    config = parser.parse_args()
+
+    asyncio.run(main(config.u, config.t, config.i, config.s))

examples/dialin-chatbot/env.example

@@ -0,0 +1,8 @@
+DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (optional: for joining the bot to the same room repeatedly for local dev)
+DAILY_API_KEY=.
+DAILY_API_URL=api.daily.co/v1
+OPENAI_API_KEY=
+ELEVENLABS_API_KEY=
+ELEVENLABS_VOICE_ID=
+TWILIO_ACCOUNT_SID=
+TWILIO_AUTH_TOKEN=

examples/dialin-chatbot/fly.example.toml

@@ -0,0 +1,19 @@
+# fly.toml app configuration file generated for pipecat-dialin-demo on 2024-06-03T15:57:57+02:00
+#
+# See https://fly.io/docs/reference/configuration/ for information about how to use this file.
+#
+
+app = 'pipecat-dialin-demo'
+primary_region = 'sjc'
+
+[build]
+
+[http_service]
+  internal_port = 7860
+  force_https = true
+  auto_stop_machines = true
+  auto_start_machines = true
+  min_machines_running = 1
+
+[[vm]]
+  size = 'performance-1x'

examples/dialin-chatbot/requirements.txt

@@ -0,0 +1,7 @@
+pipecat-ai[daily,openai,silero]
+fastapi
+uvicorn
+requests
+python-dotenv
+loguru
+twilio

examples/fast-chatbot/.gitignore

@@ -0,0 +1,165 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/#use-with-ide
+.pdm.toml
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+runpod.toml
+
+# custom script to recursively upgrade items in requirements.py
+upgrade_requirements.py
+.DS_Store

examples/fast-chatbot/bot.py

@@ -0,0 +1,164 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+from loguru import logger
+import argparse
+import asyncio
+import aiohttp
+import os
+import sys
+import time
+from typing import Optional
+
+from pydantic import BaseModel, ValidationError
+
+from pipecat.vad.vad_analyzer import VADParams
+from pipecat.vad.silero import SileroVADAnalyzer
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+from pipecat.services.openai import OpenAILLMService
+from pipecat.services.deepgram import DeepgramSTTService
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.frames.frames import LLMMessagesFrame, EndFrame
+
+from pipecat.processors.aggregators.llm_response import (
+    LLMAssistantResponseAggregator, LLMUserResponseAggregator
+)
+
+from helpers import (
+    ClearableDeepgramTTSService,
+    AudioVolumeTimer,
+    TranscriptionTimingLogger
+)
+
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level=os.getenv("LOG_LEVEL", "DEBUG"))
+
+
+class BotSettings(BaseModel):
+    room_url: str
+    room_token: str
+    bot_name: str = "Pipecat"
+    prompt: Optional[str] = "You are a helpful assistant."
+    deepgram_api_key: Optional[str] = os.getenv("DEEPGRAM_API_KEY", None)
+    deepgram_voice: Optional[str] = os.getenv("DEEPGRAM_VOICE", "aura-asteria-en")
+    deepgram_tts_base_url: Optional[str] = os.getenv(
+        "DEEPGRAM_TTS_BASE_URL", "https://api.deepgram.com/v1/speak")
+    deepgram_stt_base_url: Optional[str] = os.getenv(
+        "DEEPGRAM_STT_BASE_URL", "https://api.deepgram.com/v1/speak")
+    openai_api_key: Optional[str] = os.getenv("OPENAI_API_KEY", None),
+    openai_model: Optional[str] = os.getenv("OPENAI_MODEL", None),
+    openai_base_url: Optional[str] = os.getenv("OPENAI_BASE_URL", None)
+    vad_stop_secs: Optional[float] = os.getenv("VAD_STOP_SECS", 0.200)
+
+
+async def main(settings: BotSettings):
+    async with aiohttp.ClientSession() as session:
+        transport = DailyTransport(
+            settings.room_url,
+            settings.room_token,
+            settings.bot_name,
+            DailyParams(
+                audio_out_enabled=True,
+                transcription_enabled=False,
+                vad_enabled=True,
+                vad_analyzer=SileroVADAnalyzer(params=VADParams(
+                    stop_secs=settings.vad_stop_secs
+                )),
+                vad_audio_passthrough=True
+            )
+        )
+
+        stt = DeepgramSTTService(
+            name="STT",
+            api_key=settings.deepgram_api_key,
+            url=settings.deepgram_stt_base_url
+        )
+
+        tts = ClearableDeepgramTTSService(
+            name="Voice",
+            aiohttp_session=session,
+            api_key=settings.deepgram_api_key,
+            voice=settings.deepgram_voice,
+            **({'base_url': url} if (url := settings.deepgram_tts_base_url) else {})
+        )
+
+        llm = OpenAILLMService(
+            name="LLM",
+            api_key=settings.openai_api_key,
+            model=settings.openai_model,
+            base_url=settings.openai_base_url,
+        )
+
+        messages = [
+            {
+                "role": "system",
+                "content": settings.prompt,
+            },
+        ]
+
+        avt = AudioVolumeTimer()
+        tl = TranscriptionTimingLogger(avt)
+
+        tma_in = LLMUserResponseAggregator(messages)
+        tma_out = LLMAssistantResponseAggregator(messages)
+
+        pipeline = Pipeline([
+            transport.input(),   # Transport user input
+            avt,                 # Audio volume timer
+            stt,                 # Speech-to-text
+            tl,                  # Transcription timing logger
+            tma_in,              # User responses
+            llm,                 # LLM
+            tts,                 # TTS
+            transport.output(),  # Transport bot output
+            tma_out,             # Assistant spoken responses
+        ])
+
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                report_only_initial_ttfb=True
+            ))
+
+        # When the participant leaves, we exit the bot.
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            await task.queue_frame(EndFrame())
+
+        # When the first participant joins, the bot should introduce itself.
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            # Provide some air whilst tracks subscribe
+            time.sleep(2)
+            messages.append(
+                {
+                    "role": "system",
+                    "content": "Briefly introduce yourself by saying 'hello, I'm FastBot, how can I help you today?'"})
+            await task.queue_frames([LLMMessagesFrame(messages)])
+
+        runner = PipelineRunner()
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Pipecat Bot")
+    parser.add_argument("-s", "--settings", type=str, required=True, help="Pipecat bot settings")
+
+    args, unknown = parser.parse_known_args()
+
+    try:
+        settings = BotSettings.model_validate_json(args.settings)
+        asyncio.run(main(settings))
+    except ValidationError as e:
+        print(e)

examples/fast-chatbot/bot_runner.py

@@ -0,0 +1,164 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import os
+import argparse
+import subprocess
+
+from pydantic import BaseModel, ValidationError
+from typing import Optional
+
+from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper, DailyRoomObject, DailyRoomProperties, DailyRoomParams
+
+from fastapi import FastAPI, Request, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+
+from bot import BotSettings
+
+from dotenv import load_dotenv
+load_dotenv(override=True)
+
+
+# ------------ Configuration ------------ #
+
+MAX_SESSION_TIME = 5 * 60  # 5 minutes
+REQUIRED_ENV_VARS = ['DAILY_API_URL', 'DAILY_API_KEY', 'DEEPGRAM_API_KEY']
+
+daily_rest_helper = DailyRESTHelper(
+    os.getenv("DAILY_API_KEY", ""),
+    os.getenv("DAILY_API_URL", 'https://api.daily.co/v1'))
+
+
+class RunnerSettings(BaseModel):
+    prompt: Optional[
+        str] = "You are a fast, low-latency chatbot. Your goal is to demonstrate voice-driven AI capabilities at human-like speeds. When introducing yourself briefly mention your goal is to showcase speed and conversational flow. The technology powering you is Daily for transport, Cerebrium for GPU hosting, Llama 3 (8-B version) LLM, and Deepgram for speech-to-text and text-to-speech. You are hosted on the east coast of the United States. Respond to what the user said in a creative and helpful way, but keep responses short and legible. Ensure responses contain only words. Check again that you have not included special characters other than '?' or '!'."
+    deepgram_voice: Optional[str] = os.getenv("DEEPGRAM_VOICE")
+    openai_model: Optional[str] = os.getenv("OPENAI_MODEL", "gpt-4o")
+    openai_api_key: Optional[str] = os.getenv("OPENAI_API_KEY")
+    test: Optional[bool] = None
+
+# ----------------- API ----------------- #
+
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"]
+)
+
+# ----------------- Main ----------------- #
+
+
+@app.post("/start_bot")
+async def start_bot(request: Request) -> JSONResponse:
+    runner_settings = RunnerSettings()
+    try:
+        request_body = await request.body()
+        if len(request_body) > 0:
+            runner_settings = RunnerSettings.model_validate_json(request_body)
+    except ValidationError as e:
+        raise HTTPException(
+            status_code=400,
+            detail=f"Invalid request: {e}")
+    except Exception as e:
+        # If no data in request, pass
+        pass
+
+    # Is this a webhook creation request?
+    if runner_settings.test is not None:
+        return JSONResponse({"test": True})
+
+    # Use specified room URL, or create a new one if not specified
+    room_url = os.getenv("DAILY_SAMPLE_ROOM_URL", "")
+
+    if not room_url:
+        params = DailyRoomParams(
+            properties=DailyRoomProperties()
+        )
+        try:
+            room: DailyRoomObject = daily_rest_helper.create_room(params=params)
+        except Exception as e:
+            raise HTTPException(
+                status_code=500,
+                detail=f"Unable to provision room {e}")
+    else:
+        # Check passed room URL exists, we should assume that it already has a sip set up
+        try:
+            room: DailyRoomObject = daily_rest_helper.get_room_from_url(room_url)
+        except Exception:
+            raise HTTPException(
+                status_code=500, detail=f"Room not found: {room_url}")
+
+    # Give the agent a token to join the session
+    token = daily_rest_helper.get_token(room.url, MAX_SESSION_TIME)
+
+    if not room or not token:
+        raise HTTPException(
+            status_code=500, detail=f"Failed to get token for room: {room_url}")
+
+    # Spawn a new agent, and join the user session
+    try:
+        bot_settings = BotSettings(
+            room_url=room.url,
+            room_token=token,
+            prompt=runner_settings.prompt,
+            deepgram_voice=runner_settings.deepgram_voice,
+            openai_model=runner_settings.openai_model,
+            openai_api_key=runner_settings.openai_api_key,
+        )
+        bot_settings_str = bot_settings.model_dump_json(exclude_none=True)
+
+        subprocess.Popen(
+            [f"python3 -m bot -s '{bot_settings_str}'"],
+            shell=True,
+            bufsize=1,
+            cwd=os.path.dirname(os.path.abspath(__file__)))
+    except Exception as e:
+        raise HTTPException(
+            status_code=500, detail=f"Failed to start subprocess: {e}")
+
+    # Grab a token for the user to join with
+    user_token = daily_rest_helper.get_token(room.url, MAX_SESSION_TIME)
+
+    return JSONResponse({
+        "room_url": room.url,
+        "token": user_token,
+    })
+
+
+if __name__ == "__main__":
+    # Check environment variables
+    for env_var in REQUIRED_ENV_VARS:
+        if env_var not in os.environ:
+            raise Exception(f"Missing environment variable: {env_var}.")
+
+    parser = argparse.ArgumentParser(description="Pipecat Bot Runner")
+    parser.add_argument("--host", type=str,
+                        default=os.getenv("HOST", "0.0.0.0"), help="Host address")
+    parser.add_argument("--port", type=int,
+                        default=os.getenv("PORT", 7860), help="Port number")
+    parser.add_argument("--reload", action="store_true",
+                        default=True, help="Reload code on change")
+
+    config = parser.parse_args()
+
+    try:
+        import uvicorn
+
+        uvicorn.run(
+            "bot_runner:app",
+            host=config.host,
+            port=config.port,
+            reload=config.reload
+        )
+
+    except KeyboardInterrupt:
+        print("Pipecat runner shutting down...")

examples/fast-chatbot/env.example

@@ -0,0 +1,12 @@
+DAILY_SAMPLE_ROOM_URL= #optional: use the same room each time, or create a new one if unset
+DAILY_API_KEY=
+DAILY_API_URL=
+
+DEEPGRAM_API_KEY=
+DEEPGRAM_VOICE=
+DEEPGRAM_STT_URL=
+DEEPGRAM_TTS_BASE_URL=
+
+OPENAI_API_KEY=
+OPENAI_MODEL=
+OPENAI_BASE_URL=

examples/fast-chatbot/helpers.py

@@ -0,0 +1,267 @@
+from loguru import logger
+import asyncio
+import math
+import struct
+import time
+from dataclasses import dataclass, field
+from typing import List
+
+
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.frames.frames import (
+    Frame,
+    AudioRawFrame,
+    InterimTranscriptionFrame,
+    TranscriptionFrame,
+    TextFrame,
+    StartInterruptionFrame,
+    LLMFullResponseStartFrame,
+    TTSStoppedFrame,
+    MetricsFrame
+)
+
+from pipecat.vad.vad_analyzer import VADAnalyzer, VADState
+from pipecat.services.deepgram import DeepgramTTSService
+from pipecat.services.openai import OpenAILLMContext, OpenAILLMContextFrame
+
+
+class GreedyLLMAggregator(FrameProcessor):
+    def __init__(self, context: OpenAILLMContext = None, **kwargs):
+        super().__init__(**kwargs)
+        self.context: OpenAILLMContext = context if context else OpenAILLMContext()
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        logger.debug(f"{frame}")
+
+        try:
+            if isinstance(frame, InterimTranscriptionFrame):
+                return
+
+            if isinstance(frame, TranscriptionFrame):
+                # append transcribed text to last "user" frame
+                if self.context.messages and self.context.messages[-1]["role"] == "user":
+                    last_frame = self.context.messages.pop()
+                else:
+                    last_frame = {"role": "user", "content": ""}
+
+                last_frame["content"] += " " + frame.text
+                self.context.messages.append(last_frame)
+
+                oai_context_frame = OpenAILLMContextFrame(context=self.context)
+                logger.debug(f"pushing frame {oai_context_frame}")
+                await self.push_frame(oai_context_frame)
+                return
+
+            await self.push_frame(frame, direction)
+        except Exception as e:
+            logger.debug(f"error: {e}")
+
+
+class ClearableDeepgramTTSService(DeepgramTTSService):
+    def __init___(self, **kwargs):
+        super().__init(**kwargs)
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, StartInterruptionFrame):
+            self._current_sentence = ""
+
+
+@dataclass
+class BufferedSentence:
+    audio_frames: List[AudioRawFrame] = field(default_factory=list)
+    text_frame: TextFrame = None
+
+
+class VADGate(FrameProcessor):
+
+    def __init__(
+            self,
+            vad_analyzer: VADAnalyzer = None,
+            context: OpenAILLMContext = None,
+            **kwargs):
+        super().__init__(**kwargs)
+        self.vad_analyzer = vad_analyzer
+        self.context = context
+
+        self._audio_pusher_task = None
+        self._expect_text_frame_next = False
+        self._sentences: List[BufferedSentence] = []
+
+    # queue output from tts one sentence at a time. associate a buffer of audio frames with the content of
+    # each text frame.
+    #
+    # start a coroutine to service the queue and send sentences down the pipeline when possible.
+    # 1. do not send anything when we are not in VADState.QUIET
+    # 2. if we are in VADState.QUIET, send a sentence, estimate how long it will take for that sentence
+    #    to output, sleep until it's time to send another sentence
+    # 3. each time we send a sentence, append it to the conversation context
+    # 3. when the sentence buffer becomes empty, cancel the coroutine
+    # 4. if we get a new LLMFullResponse, treat that as a cancellation, too
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        try:
+
+            # A TTSService will emit a series of AudioRawFrame objects, then a TTSStoppedFrame,
+            # then a TextFrame.
+
+            if self._expect_text_frame_next:
+                self._expect_text_frame_next = False
+                if isinstance(frame, TextFrame):
+                    self._sentences[-1].text_frame = frame
+                else:
+                    logger.debug(f"expected a text frame, but received {frame}")
+                    await self.push_frame(frame, direction)
+                return
+            else:
+                if isinstance(frame, TextFrame):
+                    logger.error(f"XXXXXXXXXXXXXXXXXXX received a text frame, wasn't expecting it.")
+
+            if isinstance(frame, AudioRawFrame):
+                # if our buffer is empty or has a "finished" sentence at the end,
+                # then we need to start buffering a new sentence
+                if not self._sentences or self._sentences[-1].text_frame:
+                    self._sentences.append(BufferedSentence())
+                self._sentences[-1].audio_frames.append(frame)
+                await self.maybe_start_audio_pusher_task()
+                return
+
+            if isinstance(frame, TTSStoppedFrame):
+                self._expect_text_frame_next = True
+                await self.push_frame(frame, direction)
+                return
+
+            # There are two ways we can be interrupted. During greedy inference, a new
+            # LLM response can start. Or, during playout, we can get a traditional
+            # user interruption frame.
+            if (isinstance(frame, LLMFullResponseStartFrame) or
+                    isinstance(frame, StartInterruptionFrame)):
+                logger.debug(f"{frame} - Handle interruption in VADGate")
+                self._sentences = []
+                if self._audio_pusher_task:
+                    self._audio_pusher_task.cancel()
+                    self._audio_pusher_task = None
+                await self.push_frame(frame, direction)
+                return
+
+            await self.push_frame(frame, direction)
+        except Exception as e:
+            logger.debug(f"error: {e}")
+
+    async def maybe_start_audio_pusher_task(self):
+        try:
+            if self._audio_pusher_task:
+                return
+            self._audio_pusher_task = self.get_event_loop().create_task(self.push_audio())
+
+        except Exception as e:
+            logger.debug(f"Exception {e}")
+
+    async def push_audio(self):
+        try:
+            while True:
+                if not self._sentences:
+                    await asyncio.sleep(0.01)
+                    continue
+
+                if self.vad_analyzer._vad_state != VADState.QUIET:
+                    await asyncio.sleep(0.01)
+                    continue
+
+                # we only want to push completed sentence buffers
+                if not self._sentences[0].text_frame:
+                    await asyncio.sleep(0.01)
+                    continue
+
+                s = self._sentences.pop(0)
+                if not s.audio_frames:
+                    continue
+                sample_rate = s.audio_frames[0].sample_rate
+                duration = 0
+                logger.debug(f"Pushing {len(s.audio_frames)} audio frames")
+                for frame in s.audio_frames:
+                    await self.push_frame(frame)
+                    # assume linear16 encoding (2 bytes per sample). todo: add some more
+                    # metadata to AudioRawFrame, maybe
+                    duration += (len(frame.audio) / 2 / frame.num_channels) / sample_rate
+                await asyncio.sleep(duration - 20 / 1000)
+                if self.context:
+                    logger.debug(f"Appending assistant message to context: [{s.text_frame.text}]")
+                    self.context.messages.append(
+                        {"role": "assistant", "content": s.text_frame.text}
+                    )
+                await self.push_frame(s.text_frame)
+
+        except Exception as e:
+            logger.debug(f"Exception {e}")
+
+
+class TranscriptionTimingLogger(FrameProcessor):
+    def __init__(self, avt):
+        super().__init__()
+        self.name = "Transcription"
+        self._avt = avt
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        try:
+            await super().process_frame(frame, direction)
+            if isinstance(frame, TranscriptionFrame):
+                elapsed = time.time() - self._avt.last_transition_ts
+                logger.debug(f"Transcription TTF: {elapsed}")
+                await self.push_frame(MetricsFrame(ttfb={self.name: elapsed}))
+
+            await self.push_frame(frame, direction)
+        except Exception as e:
+            logger.debug(f"Exception {e}")
+
+
+class AudioVolumeTimer(FrameProcessor):
+    def __init__(self):
+        super().__init__()
+        self.last_transition_ts = 0
+        self._prev_volume = -80
+        self._speech_volume_threshold = -50
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, AudioRawFrame):
+            volume = self.calculate_volume(frame)
+            # print(f"Audio volume: {volume:.2f} dB")
+            if (volume >= self._speech_volume_threshold and
+                    self._prev_volume < self._speech_volume_threshold):
+                # logger.debug("transition above speech volume threshold")
+                self.last_transition_ts = time.time()
+            elif (volume < self._speech_volume_threshold and
+                    self._prev_volume >= self._speech_volume_threshold):
+                # logger.debug("transition below non-speech volume threshold")
+                self.last_transition_ts = time.time()
+            self._prev_volume = volume
+
+        await self.push_frame(frame, direction)
+
+    def calculate_volume(self, frame: AudioRawFrame) -> float:
+        if frame.num_channels != 1:
+            raise ValueError(f"Expected 1 channel, got {frame.num_channels}")
+
+        # Unpack audio data into 16-bit integers
+        fmt = f"{len(frame.audio) // 2}h"
+        audio_samples = struct.unpack(fmt, frame.audio)
+
+        # Calculate RMS
+        sum_squares = sum(sample**2 for sample in audio_samples)
+        rms = math.sqrt(sum_squares / len(audio_samples))
+
+        # Convert RMS to decibels (dB)
+        # Reference: maximum value for 16-bit audio is 32767
+        if rms > 0:
+            db = 20 * math.log10(rms / 32767)
+        else:
+            db = -96  # Minimum value (almost silent)
+
+        return db

examples/fast-chatbot/requirements.txt

@@ -0,0 +1,6 @@
+pipecat-ai[daily,openai,silero,deepgram]
+fastapi
+uvicorn
+requests
+python-dotenv
+loguru

examples/foundational/01-say-one-thing-piper.py

@@ -1,69 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import os
-
-import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.frames.frames import EndFrame, TTSSpeakFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.piper.tts import PiperHttpTTSService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(audio_out_enabled=True),
-    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
-    "webrtc": lambda: TransportParams(audio_out_enabled=True),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    # Create an HTTP session
-    async with aiohttp.ClientSession() as session:
-        tts = PiperHttpTTSService(
-            base_url=os.getenv("PIPER_BASE_URL"), aiohttp_session=session, sample_rate=24000
-        )
-
-        task = PipelineTask(
-            Pipeline([tts, transport.output()]),
-            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-        )
-
-        # Register an event handler so we can play the audio when the client joins
-        @transport.event_handler("on_client_connected")
-        async def on_client_connected(transport, client):
-            await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
-
-        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-        await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/foundational/01-say-one-thing-rime.py

@@ -1,70 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import os
-
-import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.frames.frames import EndFrame, TTSSpeakFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.rime.tts import RimeHttpTTSService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(audio_out_enabled=True),
-    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
-    "webrtc": lambda: TransportParams(audio_out_enabled=True),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    # Create an HTTP session
-    async with aiohttp.ClientSession() as session:
-        tts = RimeHttpTTSService(
-            api_key=os.getenv("RIME_API_KEY", ""),
-            voice_id="rex",
-            aiohttp_session=session,
-        )
-
-        task = PipelineTask(
-            Pipeline([tts, transport.output()]),
-            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-        )
-
-        # Register an event handler so we can play the audio when the client joins
-        @transport.event_handler("on_client_connected")
-        async def on_client_connected(transport, client):
-            await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
-
-        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-        await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/foundational/01-say-one-thing.py

@@ -1,67 +1,56 @@
 #
-# Copyright (c) 2024-2026, Daily
+# Copyright (c) 2024, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import asyncio
+import aiohttp
 import os
+import sys
+
+from pipecat.frames.frames import EndFrame, TextFrame
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.task import PipelineTask
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+from runner import configure
 
-from dotenv import load_dotenv
 from loguru import logger
 
-from pipecat.frames.frames import EndFrame, TTSSpeakFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
+from dotenv import load_dotenv
 load_dotenv(override=True)
 
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(audio_out_enabled=True),
-    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
-    "webrtc": lambda: TransportParams(audio_out_enabled=True),
-}
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
 
 
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
+async def main(room_url):
+    async with aiohttp.ClientSession() as session:
+        transport = DailyTransport(
+            room_url, None, "Say One Thing", DailyParams(audio_out_enabled=True))
 
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
-        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-    )
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY"),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
+        )
 
-    task = PipelineTask(
-        Pipeline([tts, transport.output()]),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
+        runner = PipelineRunner()
 
-    # Register an event handler so we can play the audio when the client joins
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
+        task = PipelineTask(Pipeline([tts, transport.output()]))
 
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
+        # Register an event handler so we can play the audio when the
+        # participant joins.
+        @transport.event_handler("on_participant_joined")
+        async def on_new_participant_joined(transport, participant):
+            participant_name = participant["info"]["userName"] or ''
+            await task.queue_frames([TextFrame(f"Hello there, {participant_name}!"), EndFrame()])
 
+        await runner.run(task)
 
 if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()
+    (url, token) = configure()
+    asyncio.run(main(url))

examples/foundational/01a-local-audio.py

@@ -1,23 +1,25 @@
 #
-# Copyright (c) 2024-2026, Daily
+# Copyright (c) 2024, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
 import asyncio
+import aiohttp
 import os
 import sys
 
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.frames.frames import EndFrame, TTSSpeakFrame
+from pipecat.frames.frames import EndFrame, TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.transports.local.audio import LocalAudioTransport, LocalAudioTransportParams
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.transports.base_transport import TransportParams
+from pipecat.transports.local.audio import LocalAudioTransport
 
+from loguru import logger
+
+from dotenv import load_dotenv
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -25,24 +27,26 @@ logger.add(sys.stderr, level="DEBUG")
 
 
 async def main():
-    transport = LocalAudioTransport(LocalAudioTransportParams(audio_out_enabled=True))
+    async with aiohttp.ClientSession() as session:
+        transport = LocalAudioTransport(TransportParams(audio_out_enabled=True))
 
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
-        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-    )
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY"),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
+        )
 
-    pipeline = Pipeline([tts, transport.output()])
+        pipeline = Pipeline([tts, transport.output()])
 
-    task = PipelineTask(pipeline)
+        task = PipelineTask(pipeline)
 
-    async def say_something():
-        await asyncio.sleep(1)
-        await task.queue_frames([TTSSpeakFrame("Hello there, how is it going!"), EndFrame()])
+        async def say_something():
+            await asyncio.sleep(1)
+            await task.queue_frames([TextFrame("Hello there!"), EndFrame()])
 
-    runner = PipelineRunner(handle_sigint=False if sys.platform == "win32" else True)
+        runner = PipelineRunner()
 
-    await asyncio.gather(runner.run(task), say_something())
+        await asyncio.gather(runner.run(task), say_something())
 
 
 if __name__ == "__main__":

examples/foundational/01b-livekit-audio.py

@@ -1,62 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import asyncio
-import os
-import sys
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.frames.frames import TTSSpeakFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
-from pipecat.runner.livekit import configure
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.transports.livekit.transport import LiveKitParams, LiveKitTransport
-
-load_dotenv(override=True)
-
-logger.remove(0)
-logger.add(sys.stderr, level="DEBUG")
-
-
-async def main():
-    (url, token, room_name) = await configure()
-
-    transport = LiveKitTransport(
-        url=url,
-        token=token,
-        room_name=room_name,
-        params=LiveKitParams(audio_out_enabled=True),
-    )
-
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
-        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-    )
-
-    runner = PipelineRunner()
-
-    task = PipelineTask(Pipeline([tts, transport.output()]))
-
-    # Register an event handler so we can play the audio when the
-    # participant joins.
-    @transport.event_handler("on_first_participant_joined")
-    async def on_first_participant_joined(transport, participant_id):
-        await asyncio.sleep(1)
-        await task.queue_frame(
-            TTSSpeakFrame(
-                "Hello there! How are you doing today? Would you like to talk about the weather?"
-            )
-        )
-
-    await runner.run(task)
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

examples/foundational/01c-nvidia-riva-tts.py

@@ -1,64 +0,0 @@
-#
-# Copyright (c) 2024-2026, Daily
-#
-# SPDX-License-Identifier: BSD 2-Clause License
-#
-
-import os
-
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.frames.frames import EndFrame, TTSSpeakFrame
-from pipecat.pipeline.pipeline import Pipeline
-from pipecat.pipeline.runner import PipelineRunner
-from pipecat.pipeline.task import PipelineTask
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.nvidia.tts import NvidiaTTSService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
-
-load_dotenv(override=True)
-
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(audio_out_enabled=True),
-    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
-    "webrtc": lambda: TransportParams(audio_out_enabled=True),
-}
-
-
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    tts = NvidiaTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
-
-    task = PipelineTask(
-        Pipeline([tts, transport.output()]),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
-
-    # Register an event handler so we can play the audio when the client joins
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
-
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
-
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
-if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()

examples/foundational/02-llm-say-one-thing.py

@@ -1,78 +1,68 @@
 #
-# Copyright (c) 2024-2026, Daily
+# Copyright (c) 2024, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+import asyncio
+import aiohttp
 import os
+import sys
 
-from dotenv import load_dotenv
-from loguru import logger
-
-from pipecat.frames.frames import EndFrame, LLMContextFrame
+from pipecat.frames.frames import EndFrame, LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.processors.aggregators.llm_context import LLMContext
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.cartesia.tts import CartesiaTTSService
-from pipecat.services.openai.llm import OpenAILLMService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
-from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
 
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
 load_dotenv(override=True)
 
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(audio_out_enabled=True),
-    "twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
-    "webrtc": lambda: TransportParams(audio_out_enabled=True),
-}
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
 
 
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
+async def main(room_url):
+    async with aiohttp.ClientSession() as session:
+        transport = DailyTransport(
+            room_url,
+            None,
+            "Say One Thing From an LLM",
+            DailyParams(audio_out_enabled=True))
 
-    tts = CartesiaTTSService(
-        api_key=os.getenv("CARTESIA_API_KEY"),
-        voice_id="71a7ad14-091c-4e8e-a314-022ece01c121",  # British Reading Lady
-    )
+        tts = ElevenLabsTTSService(
+            aiohttp_session=session,
+            api_key=os.getenv("ELEVENLABS_API_KEY"),
+            voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
+        )
 
-    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
+        llm = OpenAILLMService(
+            api_key=os.getenv("OPENAI_API_KEY"),
+            model="gpt-4o")
 
-    messages = [
-        {
-            "role": "system",
-            "content": "You are an LLM in a WebRTC session, and this is a 'hello world' demo. Say hello to the world.",
-        }
-    ]
+        messages = [
+            {
+                "role": "system",
+                "content": "You are an LLM in a WebRTC session, and this is a 'hello world' demo. Say hello to the world.",
+            }]
 
-    task = PipelineTask(
-        Pipeline([llm, tts, transport.output()]),
-        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-    )
+        runner = PipelineRunner()
 
-    # Register an event handler so we can play the audio when the client joins
-    @transport.event_handler("on_client_connected")
-    async def on_client_connected(transport, client):
-        await task.queue_frames([LLMContextFrame(LLMContext(messages)), EndFrame()])
+        task = PipelineTask(Pipeline([llm, tts, transport.output()]))
 
-    runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await task.queue_frames([LLMMessagesFrame(messages), EndFrame()])
 
-    await runner.run(task)
-
-
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
+        await runner.run(task)
 
 
 if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()
+    (url, token) = configure()
+    asyncio.run(main(url))

examples/foundational/03-still-frame.py

@@ -1,82 +1,68 @@
 #
-# Copyright (c) 2024-2026, Daily
+# Copyright (c) 2024, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import os
-
+import asyncio
 import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
+import os
+import sys
 
 from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.runner.types import RunnerArguments
-from pipecat.runner.utils import create_transport
-from pipecat.services.fal.image import FalImageGenService
-from pipecat.transports.base_transport import BaseTransport, TransportParams
-from pipecat.transports.daily.transport import DailyParams
+from pipecat.services.fal import FalImageGenService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
 
+from runner import configure
+
+from loguru import logger
+
+from dotenv import load_dotenv
 load_dotenv(override=True)
 
-
-# We use lambdas to defer transport parameter creation until the transport
-# type is selected at runtime.
-transport_params = {
-    "daily": lambda: DailyParams(
-        video_out_enabled=True,
-        video_out_width=1024,
-        video_out_height=1024,
-    ),
-    "webrtc": lambda: TransportParams(
-        video_out_enabled=True,
-        video_out_width=1024,
-        video_out_height=1024,
-    ),
-}
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
 
 
-async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
-    logger.info(f"Starting bot")
-
-    # Create an HTTP session
+async def main(room_url):
     async with aiohttp.ClientSession() as session:
+        transport = DailyTransport(
+            room_url,
+            None,
+            "Show a still frame image",
+            DailyParams(
+                camera_out_enabled=True,
+                camera_out_width=1024,
+                camera_out_height=1024
+            )
+        )
+
         imagegen = FalImageGenService(
-            params=FalImageGenService.InputParams(image_size="square_hd"),
+            params=FalImageGenService.InputParams(
+                image_size="square_hd"
+            ),
             aiohttp_session=session,
             key=os.getenv("FAL_KEY"),
         )
 
-        task = PipelineTask(
-            Pipeline([imagegen, transport.output()]),
-            idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
-        )
+        runner = PipelineRunner()
 
-        # Register an event handler so we can play the audio when the client joins
-        @transport.event_handler("on_client_connected")
-        async def on_client_connected(transport, client):
-            await task.queue_frame(TextFrame("a cat in the style of picasso"))
+        task = PipelineTask(Pipeline([imagegen, transport.output()]))
 
-        @transport.event_handler("on_client_disconnected")
-        async def on_client_disconnected(transport, client):
-            logger.info(f"Client disconnected")
-            await task.cancel()
-
-        runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            # Note that we do not put an EndFrame() item in the pipeline for this demo.
+            # This means that the bot will stay in the channel until it times out.
+            # An EndFrame() in the pipeline would cause the transport to shut
+            # down.
+            await task.queue_frames([TextFrame("a cat in the style of picasso")])
 
         await runner.run(task)
 
 
-async def bot(runner_args: RunnerArguments):
-    """Main bot entry point compatible with Pipecat Cloud."""
-    transport = await create_transport(runner_args, transport_params)
-    await run_bot(transport, runner_args)
-
-
 if __name__ == "__main__":
-    from pipecat.runner.run import main
-
-    main()
+    (url, token) = configure()
+    asyncio.run(main(url))

examples/foundational/03a-local-still-frame.py

@@ -1,25 +1,27 @@
 #
-# Copyright (c) 2024-2026, Daily
+# Copyright (c) 2024, Daily
 #
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
 import asyncio
+import aiohttp
 import os
 import sys
-import tkinter as tk
 
-import aiohttp
-from dotenv import load_dotenv
-from loguru import logger
+import tkinter as tk
 
 from pipecat.frames.frames import TextFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineTask
-from pipecat.services.fal.image import FalImageGenService
-from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
+from pipecat.services.fal import FalImageGenService
+from pipecat.transports.base_transport import TransportParams
+from pipecat.transports.local.tk import TkLocalTransport
 
+from loguru import logger
+
+from dotenv import load_dotenv
 load_dotenv(override=True)
 
 logger.remove(0)
@@ -33,11 +35,15 @@ async def main():
 
         transport = TkLocalTransport(
             tk_root,
-            TkTransportParams(video_out_enabled=True, video_out_width=1024, video_out_height=1024),
-        )
+            TransportParams(
+                camera_out_enabled=True,
+                camera_out_width=1024,
+                camera_out_height=1024))
 
         imagegen = FalImageGenService(
-            params=FalImageGenService.InputParams(image_size="square_hd"),
+            params=FalImageGenService.InputParams(
+                image_size="square_hd"
+            ),
             aiohttp_session=session,
             key=os.getenv("FAL_KEY"),
         )
@@ -50,7 +56,7 @@ async def main():
         runner = PipelineRunner()
 
         async def run_tk():
-            while not task.has_finished():
+            while runner.is_active():
                 tk_root.update()
                 tk_root.update_idletasks()
                 await asyncio.sleep(0.1)