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Include examples in type checking

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Remove `examples/` from the `pyrightconfig.json` ignore list and fix
the resulting type errors across all example files. Common fixes:

- Required API keys: `os.getenv("X")` -> `os.environ["X"]` so the
  return type is `str` rather than `str | None`, and misconfiguration
  fails fast.
- Narrow `LLMContextMessage` union members with `isinstance(..., dict)`
  before dict-style access.
- `assert isinstance(params.llm, ...)` before calling service-specific
  methods that aren't on the base `LLMService`.
- Guard optional frame fields (e.g. `LLMSearchResponseFrame.search_result`)
  before use.
This commit is contained in:
Mark Backman
2026-04-20 15:50:49 -04:00
parent 103ced1eaa
commit 58a17c7b1b
293 changed files with 884 additions and 1006 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
examples/update-settings/llm/llm-anthropic.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = AnthropicLLMService(
api_key=os.getenv("ANTHROPIC_API_KEY"),
api_key=os.environ["ANTHROPIC_API_KEY"],
settings=AnthropicLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

4
examples/update-settings/llm/llm-aws-bedrock.py
View File

@@ -50,10 +50,10 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),

6
examples/update-settings/llm/llm-aws-nova-sonic.py
View File

@@ -49,9 +49,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
llm = AWSNovaSonicLLMService(
secret_access_key=os.getenv("AWS_SECRET_ACCESS_KEY"),
access_key_id=os.getenv("AWS_ACCESS_KEY_ID"),
region=os.getenv("AWS_REGION"),
secret_access_key=os.environ["AWS_SECRET_ACCESS_KEY"],
access_key_id=os.environ["AWS_ACCESS_KEY_ID"],
region=os.environ["AWS_REGION"],
settings=AWSNovaSonicLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

7
examples/update-settings/llm/llm-azure-realtime.py
View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.adapters.base_llm_adapter import LLMContextMessage
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -51,11 +52,11 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
llm = AzureRealtimeLLMService(
api_key=os.getenv("AZURE_REALTIME_API_KEY"),
base_url=os.getenv("AZURE_REALTIME_BASE_URL"),
api_key=os.environ["AZURE_REALTIME_API_KEY"],
base_url=os.environ["AZURE_REALTIME_BASE_URL"],
)
messages = [
messages: list[LLMContextMessage] = [
{
"role": "system",
"content": "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",

8
examples/update-settings/llm/llm-azure.py
View File

@@ -50,18 +50,18 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = AzureLLMService(
api_key=os.getenv("AZURE_CHATGPT_API_KEY"),
endpoint=os.getenv("AZURE_CHATGPT_ENDPOINT"),
api_key=os.environ["AZURE_CHATGPT_API_KEY"],
endpoint=os.environ["AZURE_CHATGPT_ENDPOINT"],
settings=AzureLLMService.Settings(
model=os.getenv("AZURE_CHATGPT_MODEL"),
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",

6
examples/update-settings/llm/llm-cerebras.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = CerebrasLLMService(
api_key=os.getenv("CEREBRAS_API_KEY"),
api_key=os.environ["CEREBRAS_API_KEY"],
settings=CerebrasLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-deepseek.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = DeepSeekLLMService(
api_key=os.getenv("DEEPSEEK_API_KEY"),
api_key=os.environ["DEEPSEEK_API_KEY"],
settings=DeepSeekLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-fireworks.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = FireworksLLMService(
api_key=os.getenv("FIREWORKS_API_KEY"),
api_key=os.environ["FIREWORKS_API_KEY"],
settings=FireworksLLMService.Settings(
model="accounts/fireworks/models/gpt-oss-20b",
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",

6
examples/update-settings/llm/llm-gemini-live-vertex.py
View File

@@ -49,9 +49,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
llm = GeminiLiveVertexLLMService(
credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"),
project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"),
location=os.getenv("GOOGLE_CLOUD_LOCATION"),
credentials=os.environ["GOOGLE_VERTEX_TEST_CREDENTIALS"],
project_id=os.environ["GOOGLE_CLOUD_PROJECT_ID"],
location=os.environ["GOOGLE_CLOUD_LOCATION"],
settings=GeminiLiveVertexLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

2
examples/update-settings/llm/llm-gemini-live.py
View File

@@ -49,7 +49,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
llm = GeminiLiveLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
api_key=os.environ["GOOGLE_API_KEY"],
settings=GeminiLiveLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

8
examples/update-settings/llm/llm-google-vertex.py
View File

@@ -50,10 +50,10 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
@@ -61,8 +61,8 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm = GoogleVertexLLMService(
credentials=os.getenv("GOOGLE_VERTEX_TEST_CREDENTIALS"),
project_id=os.getenv("GOOGLE_CLOUD_PROJECT_ID"),
location=os.getenv("GOOGLE_CLOUD_LOCATION"),
project_id=os.environ["GOOGLE_CLOUD_PROJECT_ID"],
location=os.environ["GOOGLE_CLOUD_LOCATION"],
settings=GoogleVertexLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-google.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = GoogleLLMService(
api_key=os.getenv("GOOGLE_API_KEY"),
api_key=os.environ["GOOGLE_API_KEY"],
settings=GoogleLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

5
examples/update-settings/llm/llm-grok-realtime.py
View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.adapters.base_llm_adapter import LLMContextMessage
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -50,9 +51,9 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
llm = GrokRealtimeLLMService(api_key=os.getenv("XAI_API_KEY"))
llm = GrokRealtimeLLMService(api_key=os.environ["XAI_API_KEY"])
messages = [
messages: list[LLMContextMessage] = [
{
"role": "system",
"content": "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",

6
examples/update-settings/llm/llm-grok.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = GrokLLMService(
api_key=os.getenv("XAI_API_KEY"),
api_key=os.environ["XAI_API_KEY"],
settings=GrokLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-groq.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = GroqLLMService(
api_key=os.getenv("GROQ_API_KEY"),
api_key=os.environ["GROQ_API_KEY"],
settings=GroqLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-mistral.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = MistralLLMService(
api_key=os.getenv("MISTRAL_API_KEY"),
api_key=os.environ["MISTRAL_API_KEY"],
settings=MistralLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-nvidia.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = NvidiaLLMService(
api_key=os.getenv("NVIDIA_API_KEY"),
api_key=os.environ["NVIDIA_API_KEY"],
settings=NvidiaLLMService.Settings(
model="meta/llama-3.1-405b-instruct",
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",

4
examples/update-settings/llm/llm-ollama.py
View File

@@ -50,10 +50,10 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),

5
examples/update-settings/llm/llm-openai-realtime.py
View File

@@ -10,6 +10,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.adapters.base_llm_adapter import LLMContextMessage
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -50,9 +51,9 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
llm = OpenAIRealtimeLLMService(api_key=os.getenv("OPENAI_API_KEY"))
llm = OpenAIRealtimeLLMService(api_key=os.environ["OPENAI_API_KEY"])
messages = [
messages: list[LLMContextMessage] = [
{
"role": "system",
"content": "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",

6
examples/update-settings/llm/llm-openai-responses-http.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = OpenAIResponsesHttpLLMService(
api_key=os.getenv("OPENAI_API_KEY"),
api_key=os.environ["OPENAI_API_KEY"],
settings=OpenAIResponsesHttpLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-openai-responses.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = OpenAIResponsesLLMService(
api_key=os.getenv("OPENAI_API_KEY"),
api_key=os.environ["OPENAI_API_KEY"],
settings=OpenAIResponsesLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-openai.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = OpenAILLMService(
api_key=os.getenv("OPENAI_API_KEY"),
api_key=os.environ["OPENAI_API_KEY"],
settings=OpenAILLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

6
examples/update-settings/llm/llm-openrouter.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = OpenRouterLLMService(
api_key=os.getenv("OPENROUTER_API_KEY"),
api_key=os.environ["OPENROUTER_API_KEY"],
settings=OpenRouterLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

18
examples/update-settings/llm/llm-perplexity.py
View File

@@ -50,25 +50,18 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = PerplexityLLMService(api_key=os.getenv("PERPLEXITY_API_KEY"))
llm = PerplexityLLMService(api_key=os.environ["PERPLEXITY_API_KEY"])
messages = [
{
"role": "developer",
"content": "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way. Start by introducing yourself.",
},
]
context = LLMContext(messages)
context = LLMContext()
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
context,
user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
@@ -98,6 +91,9 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
logger.info(f"Client connected")
context.add_message(
{"role": "developer", "content": "Please introduce yourself to the user."}
)
await task.queue_frames([LLMRunFrame()])
await asyncio.sleep(10)

6
examples/update-settings/llm/llm-qwen.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = QwenLLMService(
api_key=os.getenv("QWEN_API_KEY"),
api_key=os.environ["QWEN_API_KEY"],
settings=QwenLLMService.Settings(
model="qwen2.5-72b-instruct",
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",

6
examples/update-settings/llm/llm-sambanova.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = SambaNovaLLMService(
api_key=os.getenv("SAMBANOVA_API_KEY"),
api_key=os.environ["SAMBANOVA_API_KEY"],
settings=SambaNovaLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

21
examples/update-settings/llm/llm-sarvam.py
View File

@@ -47,31 +47,26 @@ transport_params = {
}
def _require_env(name: str) -> str:
value = os.getenv(name)
if not value:
raise ValueError(f"Environment variable `{name}` is required.")
return value
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info("Starting bot")
stt = SarvamSTTService(
settings=SarvamSTTService.Settings(model="saaras:v3"),
api_key=_require_env("SARVAM_API_KEY"),
api_key=os.environ["SARVAM_API_KEY"],
)
tts = SarvamTTSService(
settings=SarvamTTSService.Settings(model="bulbul:v3"),
api_key=_require_env("SARVAM_API_KEY"),
api_key=os.environ["SARVAM_API_KEY"],
)
llm = SarvamLLMService(
api_key=_require_env("SARVAM_API_KEY"),
settings=SarvamLLMService.Settings(model="sarvam-30b"),
system_instruction=(
"You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way."
api_key=os.environ["SARVAM_API_KEY"],
settings=SarvamLLMService.Settings(
model="sarvam-30b",
system_instruction=(
"You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be spoken aloud, so avoid special characters that can't easily be spoken, such as emojis or bullet points. Respond to what the user said in a creative and helpful way."
),
),
)

6
examples/update-settings/llm/llm-together.py
View File

@@ -50,17 +50,17 @@ transport_params = {
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot")
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
api_key=os.environ["CARTESIA_API_KEY"],
settings=CartesiaTTSService.Settings(
voice="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
),
)
llm = TogetherLLMService(
api_key=os.getenv("TOGETHER_API_KEY"),
api_key=os.environ["TOGETHER_API_KEY"],
settings=TogetherLLMService.Settings(
system_instruction="You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way.",
),

5
examples/update-settings/llm/llm-ultravox-realtime.py
View File

@@ -11,6 +11,7 @@ import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.adapters.base_llm_adapter import LLMContextMessage
from pipecat.adapters.schemas.tools_schema import ToolsSchema
from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.frames.frames import LLMRunFrame, LLMUpdateSettingsFrame
@@ -55,7 +56,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm = UltravoxRealtimeLLMService(
params=OneShotInputParams(
api_key=os.getenv("ULTRAVOX_API_KEY"),
api_key=os.environ["ULTRAVOX_API_KEY"],
system_prompt=system_prompt,
temperature=0.3,
max_duration=datetime.timedelta(minutes=3),
@@ -63,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
one_shot_selected_tools=ToolsSchema(standard_tools=[]),
)
messages = [
messages: list[LLMContextMessage] = [
{
"role": "system",
"content": system_prompt,