Add Gemini Live bot file

examples/simple-chatbot/server/README.md

@@ -1,11 +1,11 @@
 # Simple Chatbot Server
 
-A FastAPI server that manages bot instances and provides endpoints for both Daily Prebuilt and RTVI client connections.
+A FastAPI server that manages bot instances and provides endpoints for both Daily Prebuilt and Pipecat client connections.
 
 ## Endpoints
 
 - `GET /` - Direct browser access, redirects to a Daily Prebuilt room
-- `POST /connect` - RTVI client connection endpoint
+- `POST /connect` - Pipecat client connection endpoint
 - `GET /status/{pid}` - Get status of a specific bot process
 
 ## Environment Variables
@@ -13,14 +13,37 @@ A FastAPI server that manages bot instances and provides endpoints for both Dail
 Copy `env.example` to `.env` and configure:
 
 ```ini
+# Required API Keys
 DAILY_API_KEY=           # Your Daily API key
+OPENAI_API_KEY=          # Your OpenAI API key (required for OpenAI bot)
+GEMINI_API_KEY=          # Your Gemini API key (required for Gemini bot)
+ELEVENLABS_API_KEY=      # Your ElevenLabs API key
+
+# Bot Selection
+BOT_IMPLEMENTATION=      # Options: 'openai' or 'gemini'
+
+# Optional Configuration
 DAILY_API_URL=           # Optional: Daily API URL (defaults to https://api.daily.co/v1)
-OPENAI_API_KEY=          # Your OpenAI API key
+DAILY_SAMPLE_ROOM_URL=   # Optional: Fixed room URL for development
-CARTESIA_API_KEY=        # Your Cartesia API key
 HOST=                    # Optional: Host address (defaults to 0.0.0.0)
 FAST_API_PORT=           # Optional: Port number (defaults to 7860)
 ```
 
+## Available Bots
+
+The server supports two bot implementations:
+
+1. **OpenAI Bot** (Default)
+
+   - Uses GPT-4 for conversation
+   - Requires OPENAI_API_KEY
+
+2. **Gemini Bot**
+   - Uses Google's Gemini model
+   - Requires GEMINI_API_KEY
+
+Select your preferred bot by setting `BOT_IMPLEMENTATION` in your `.env` file.
+
 ## Running the Server
 
 Set up and activate your virtual environment:

examples/simple-chatbot/server/bot-gemini.py

@@ -0,0 +1,188 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+import asyncio
+import os
+import sys
+
+import aiohttp
+from dotenv import load_dotenv
+from loguru import logger
+from PIL import Image
+from runner import configure
+
+from pipecat.audio.vad.silero import SileroVADAnalyzer
+from pipecat.audio.vad.vad_analyzer import VADParams
+from pipecat.frames.frames import (
+    BotStartedSpeakingFrame,
+    BotStoppedSpeakingFrame,
+    EndFrame,
+    Frame,
+    LLMMessagesFrame,
+    OutputImageRawFrame,
+    SpriteFrame,
+)
+from pipecat.pipeline.pipeline import Pipeline
+from pipecat.pipeline.runner import PipelineRunner
+from pipecat.pipeline.task import PipelineParams, PipelineTask
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
+from pipecat.processors.frameworks.rtvi import (
+    RTVIBotTranscriptionProcessor,
+    RTVIMetricsProcessor,
+    RTVISpeakingProcessor,
+    RTVIUserTranscriptionProcessor,
+)
+from pipecat.services.elevenlabs import ElevenLabsTTSService
+from pipecat.services.gemini_multimodal_live.gemini import GeminiMultimodalLiveLLMService
+from pipecat.services.openai import OpenAILLMService
+from pipecat.transports.services.daily import DailyParams, DailyTransport
+
+load_dotenv(override=True)
+
+logger.remove(0)
+logger.add(sys.stderr, level="DEBUG")
+
+sprites = []
+
+script_dir = os.path.dirname(__file__)
+
+for i in range(1, 26):
+    # Build the full path to the image file
+    full_path = os.path.join(script_dir, f"assets/robot0{i}.png")
+    # Get the filename without the extension to use as the dictionary key
+    # Open the image and convert it to bytes
+    with Image.open(full_path) as img:
+        sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
+
+flipped = sprites[::-1]
+sprites.extend(flipped)
+
+# When the bot isn't talking, show a static image of the cat listening
+quiet_frame = sprites[0]
+talking_frame = SpriteFrame(images=sprites)
+
+
+class TalkingAnimation(FrameProcessor):
+    """This class starts a talking animation when it receives an first AudioFrame.
+
+    It then returns to a "quiet" sprite when it sees a TTSStoppedFrame.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._is_talking = False
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        await super().process_frame(frame, direction)
+
+        if isinstance(frame, BotStartedSpeakingFrame):
+            if not self._is_talking:
+                await self.push_frame(talking_frame)
+                self._is_talking = True
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(quiet_frame)
+            self._is_talking = False
+
+        await self.push_frame(frame, direction)
+
+
+async def main():
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        transport = DailyTransport(
+            room_url,
+            token,
+            "Chatbot",
+            DailyParams(
+                audio_in_sample_rate=16000,
+                audio_out_sample_rate=24000,
+                audio_out_enabled=True,
+                camera_out_enabled=True,
+                camera_out_width=1024,
+                camera_out_height=576,
+                vad_enabled=True,
+                vad_audio_passthrough=True,
+                vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
+            ),
+        )
+
+        llm = GeminiMultimodalLiveLLMService(
+            api_key=os.getenv("GEMINI_API_KEY"),
+            voice_id="Puck",  # Aoede, Charon, Fenrir, Kore, Puck
+            transcribe_user_audio=True,
+            transcribe_model_audio=True,
+        )
+
+        messages = [
+            {
+                "role": "user",
+                "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 introducing yourself.",
+            },
+        ]
+
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        ta = TalkingAnimation()
+
+        # RTVI
+
+        # This will send `user-*-speaking` and `bot-*-speaking` messages.
+        rtvi_speaking = RTVISpeakingProcessor()
+
+        # This will emit UserTranscript events.
+        rtvi_user_transcription = RTVIUserTranscriptionProcessor()
+
+        # This will emit BotTranscript events.
+        rtvi_bot_transcription = RTVIBotTranscriptionProcessor()
+
+        # This will send `metrics` messages.
+        rtvi_metrics = RTVIMetricsProcessor()
+
+        pipeline = Pipeline(
+            [
+                transport.input(),
+                context_aggregator.user(),
+                llm,
+                rtvi_speaking,
+                rtvi_user_transcription,
+                rtvi_bot_transcription,
+                ta,
+                rtvi_metrics,
+                transport.output(),
+                context_aggregator.assistant(),
+            ]
+        )
+
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+            ),
+        )
+        await task.queue_frame(quiet_frame)
+
+        @transport.event_handler("on_first_participant_joined")
+        async def on_first_participant_joined(transport, participant):
+            await transport.capture_participant_transcription(participant["id"])
+            await task.queue_frames([context_aggregator.user().get_context_frame()])
+
+        @transport.event_handler("on_participant_left")
+        async def on_participant_left(transport, participant, reason):
+            print(f"Participant left: {participant}")
+            await task.queue_frame(EndFrame())
+
+        runner = PipelineRunner()
+
+        await runner.run(task)
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/simple-chatbot/server/bot-openai.py

@@ -31,6 +31,8 @@ from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
 from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
 from pipecat.processors.frameworks.rtvi import (
     RTVIBotTranscriptionProcessor,
+    RTVIMetricsProcessor,
+    RTVISpeakingProcessor,
     RTVIUserTranscriptionProcessor,
 )
 from pipecat.services.elevenlabs import ElevenLabsTTSService
@@ -63,9 +65,9 @@ talking_frame = SpriteFrame(images=sprites)
 
 
 class TalkingAnimation(FrameProcessor):
-    """
+    """This class starts a talking animation when it receives an first AudioFrame.
-    This class starts a talking animation when it receives an first AudioFrame,
+
-    and then returns to a "quiet" sprite when it sees a TTSStoppedFrame.
+    It then returns to a "quiet" sprite when it sees a TTSStoppedFrame.
     """
 
     def __init__(self):
@@ -149,27 +151,42 @@ async def main():
 
         # RTVI
 
+        # This will send `user-*-speaking` and `bot-*-speaking` messages.
+        rtvi_speaking = RTVISpeakingProcessor()
+
         # This will emit UserTranscript events.
         rtvi_user_transcription = RTVIUserTranscriptionProcessor()
 
         # This will emit BotTranscript events.
         rtvi_bot_transcription = RTVIBotTranscriptionProcessor()
 
+        # This will send `metrics` messages.
+        rtvi_metrics = RTVIMetricsProcessor()
+
         pipeline = Pipeline(
             [
                 transport.input(),
+                rtvi_speaking,
                 rtvi_user_transcription,
                 context_aggregator.user(),
                 llm,
                 rtvi_bot_transcription,
                 tts,
                 ta,
+                rtvi_metrics,
                 transport.output(),
                 context_aggregator.assistant(),
             ]
         )
 
-        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))
+        task = PipelineTask(
+            pipeline,
+            PipelineParams(
+                allow_interruptions=True,
+                enable_metrics=True,
+                enable_usage_metrics=True,
+            ),
+        )
         await task.queue_frame(quiet_frame)
 
         @transport.event_handler("on_first_participant_joined")

examples/simple-chatbot/server/env.example

@@ -1,4 +1,6 @@
 DAILY_SAMPLE_ROOM_URL=https://yourdomain.daily.co/yourroom # (for joining the bot to the same room repeatedly for local dev)
 DAILY_API_KEY=7df...
 OPENAI_API_KEY=sk-PL...
-ELEVENLABS_API_KEY=aeb...
+GEMINI_API_KEY=AIza...
+ELEVENLABS_API_KEY=aeb...
+BOT_IMPLEMENTATION= # Options: 'openai' or 'gemini'

examples/simple-chatbot/server/runner.py

@@ -4,14 +4,16 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-import aiohttp
 import argparse
 import os
 
+import aiohttp
+
 from pipecat.transports.services.helpers.daily_rest import DailyRESTHelper
 
 
 async def configure(aiohttp_session: aiohttp.ClientSession):
+    """Configure the Daily room and Daily REST helper."""
     parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
     parser.add_argument(
         "-u", "--url", type=str, required=False, help="URL of the Daily room to join"

examples/simple-chatbot/server/server.py

@@ -4,8 +4,7 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
-"""
+"""RTVI Bot Server Implementation.
-RTVI Bot Server Implementation
 
 This FastAPI server manages RTVI bot instances and provides endpoints for both
 direct browser access and RTVI client connections. It handles:
@@ -49,8 +48,8 @@ daily_helpers = {}
 
 
 def cleanup():
-    """
+    """Cleanup function to terminate all bot processes.
-    Cleanup function to terminate all bot processes.
+
     Called during server shutdown.
     """
     for entry in bot_procs.values():
@@ -59,10 +58,22 @@ def cleanup():
         proc.wait()
 
 
+def get_bot_file():
+    bot_implementation = os.getenv("BOT_IMPLEMENTATION", "openai").lower().strip()
+    # If blank or None, default to openai
+    if not bot_implementation:
+        bot_implementation = "openai"
+    if bot_implementation not in ["openai", "gemini"]:
+        raise ValueError(
+            f"Invalid BOT_IMPLEMENTATION: {bot_implementation}. Must be 'openai' or 'gemini'"
+        )
+    return f"bot-{bot_implementation}"
+
+
 @asynccontextmanager
 async def lifespan(app: FastAPI):
-    """
+    """FastAPI lifespan manager that handles startup and shutdown tasks.
-    FastAPI lifespan manager that handles startup and shutdown tasks:
+
     - Creates aiohttp session
     - Initializes Daily API helper
     - Cleans up resources on shutdown
@@ -92,8 +103,7 @@ app.add_middleware(
 
 
 async def create_room_and_token() -> tuple[str, str]:
-    """
+    """Helper function to create a Daily room and generate an access token.
-    Helper function to create a Daily room and generate an access token.
 
     Returns:
         tuple[str, str]: A tuple containing (room_url, token)
@@ -114,8 +124,8 @@ async def create_room_and_token() -> tuple[str, str]:
 
 @app.get("/")
 async def start_agent(request: Request):
-    """
+    """Endpoint for direct browser access to the bot.
-    Endpoint for direct browser access to the bot.
+
     Creates a room, starts a bot instance, and redirects to the Daily room URL.
 
     Returns:
@@ -137,8 +147,9 @@ async def start_agent(request: Request):
 
     # Spawn a new bot process
     try:
+        bot_file = get_bot_file()
         proc = subprocess.Popen(
-            [f"python3 -m bot -u {room_url} -t {token}"],
+            [f"python3 -m {bot_file} -u {room_url} -t {token}"],
             shell=True,
             bufsize=1,
             cwd=os.path.dirname(os.path.abspath(__file__)),
@@ -152,8 +163,8 @@ async def start_agent(request: Request):
 
 @app.post("/connect")
 async def rtvi_connect(request: Request) -> Dict[Any, Any]:
-    """
+    """RTVI connect endpoint that creates a room and returns connection credentials.
-    RTVI connect endpoint that creates a room and returns connection credentials.
+
     This endpoint is called by RTVI clients to establish a connection.
 
     Returns:
@@ -168,8 +179,9 @@ async def rtvi_connect(request: Request) -> Dict[Any, Any]:
 
     # Start the bot process
     try:
+        bot_file = get_bot_file()
         proc = subprocess.Popen(
-            [f"python3 -m bot -u {room_url} -t {token}"],
+            [f"python3 -m {bot_file} -u {room_url} -t {token}"],
             shell=True,
             bufsize=1,
             cwd=os.path.dirname(os.path.abspath(__file__)),
@@ -184,8 +196,7 @@ async def rtvi_connect(request: Request) -> Dict[Any, Any]:
 
 @app.get("/status/{pid}")
 def get_status(pid: int):
-    """
+    """Get the status of a specific bot process.
-    Get the status of a specific bot process.
 
     Args:
         pid (int): Process ID of the bot