Merge pull request #831 from pipecat-ai/mb/gemini-simple-chatbot

Gemini updates to the simple-chatbot demo

examples/simple-chatbot/README.md

@@ -2,7 +2,18 @@
 
 <img src="image.png" width="420px">
 
-This repository demonstrates a simple AI chatbot with real-time audio/video interaction, implemented in three different ways. The bot server remains the same, but you can connect to it using three different client approaches.
+This repository demonstrates a simple AI chatbot with real-time audio/video interaction, implemented in three different ways. The bot server supports multiple AI backends, and you can connect to it using three different client approaches.
+
+## Two Bot Options
+
+1. **OpenAI Bot** (Default)
+
+   - Uses gpt-4o for conversation
+   - Requires OpenAI API key
+
+2. **Gemini Bot**
+   - Uses Google's Gemini Multimodal Live model
+   - Requires Gemini API key
 
 ## Three Ways to Connect
 
@@ -13,13 +24,13 @@ This repository demonstrates a simple AI chatbot with real-time audio/video inte
 
 2. **JavaScript**
 
-   - Basic implementation using RTVI JavaScript SDK
+   - Basic implementation using [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/reference/js/introduction)
    - No framework dependencies
    - Good for learning the fundamentals
 
 3. **React**
-   - Basic impelmentation using RTVI React SDK
+   - Basic impelmentation using [Pipecat React SDK](https://docs.pipecat.ai/client/reference/react/introduction)
-   - Demonstrates the basic client principles with RTVI React
+   - Demonstrates the basic client principles with Pipecat React
 
 ## Quick Start
 
@@ -38,8 +49,12 @@ This repository demonstrates a simple AI chatbot with real-time audio/video inte
    ```bash
    pip install -r requirements.txt
    ```
-4. Copy env.example to .env and add your credentials
+4. Copy env.example to .env and configure:
-
+   - Add your API keys
+   - Choose your bot implementation:
+     ```ini
+     BOT_IMPLEMENTATION=      # Options: 'openai' (default) or 'gemini'
+     ```
 5. Start the server:
    ```bash
    python server.py
@@ -48,7 +63,7 @@ This repository demonstrates a simple AI chatbot with real-time audio/video inte
 ### Next, connect using your preferred client app:
 
 - [Daily Prebuilt](examples/prebuilt/README.md)
-- [Vanilla JavaScript Guide](examples/javascript/README.md)
+- [JavaScript Guide](examples/javascript/README.md)
 - [React Guide](examples/react/README.md)
 
 ## Important Note
@@ -60,21 +75,23 @@ The bot server must be running for any of the client implementations to work. St
 - Python 3.10+
 - Node.js 16+ (for JavaScript and React implementations)
 - Daily API key
-- OpenAI API key
+- OpenAI API key (for OpenAI bot)
-- Cartesia API key
+- Gemini API key (for Gemini bot)
+- ElevenLabs API key
 - Modern web browser with WebRTC support
 
 ## Project Structure
 
 ```
-simple-chatbot-full-stack/
+simple-chatbot/
-├── server/             # Bot server implementation
+├── server/              # Bot server implementation
-│   ├── bot.py          # Bot logic and media handling
+│   ├── bot-openai.py    # OpenAI bot implementation
-│   ├── runner.py       # Server runner utilities
+│   ├── bot-gemini.py    # Gemini bot implementation
-│   ├── server.py       # FastAPI server
+│   ├── runner.py        # Server runner utilities
+│   ├── server.py        # FastAPI server
 │   └── requirements.txt
-└── examples/           # Client implementations
+└── examples/            # Client implementations
-    ├── prebuilt/       # Daily Prebuilt connection
+    ├── prebuilt/        # Daily Prebuilt connection
-    ├── javascript/     # JavaScript RTVI client
+    ├── javascript/      # Pipecat JavaScript client
-    └── react/          # React RTVI client
+    └── react/           # Pipecat React client
 ```

examples/simple-chatbot/examples/javascript/README.md

@@ -1,10 +1,10 @@
 # JavaScript Implementation
 
-Basic implementation using the RTVI JavaScript SDK.
+Basic implementation using the [Pipecat JavaScript SDK](https://docs.pipecat.ai/client/reference/js/introduction).
 
 ## Setup
 
-1. Run the bot server; see [README](../../README).
+1. Run the bot server. See the [server README](../../README).
 
 2. Navigate to the `examples/javascript` directory:
 

examples/simple-chatbot/examples/react/README.md

@@ -1,6 +1,6 @@
 # React Implementation
 
-Basic implementation using the RTVI React SDK.
+Basic implementation using the [Pipecat React SDK](https://docs.pipecat.ai/client/reference/react/introduction).
 
 ## Setup
 

examples/simple-chatbot/examples/react/index.html

@@ -4,7 +4,7 @@
 <head>
   <meta charset="UTF-8" />
   <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-  <title>RTVI React Client</title>
+  <title>Pipecat React Client</title>
 </head>
 
 <body>

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 +1,223 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+"""Gemini Bot Implementation.
+
+This module implements a chatbot using Google's Gemini Multimodal Live model.
+It includes:
+- Real-time audio/video interaction through Daily
+- Animated robot avatar
+- Speech-to-speech model
+
+The bot runs as part of a pipeline that processes audio/video frames and manages
+the conversation flow using Gemini's streaming capabilities.
+"""
+
+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,
+    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))
+
+# Create a smooth animation by adding reversed frames
+flipped = sprites[::-1]
+sprites.extend(flipped)
+
+# Define static and animated states
+quiet_frame = sprites[0]  # Static frame for when bot is listening
+talking_frame = SpriteFrame(images=sprites)  # Animation sequence for when bot is talking
+
+
+class TalkingAnimation(FrameProcessor):
+    """Manages the bot's visual animation states.
+
+    Switches between static (listening) and animated (talking) states based on
+    the bot's current speaking status.
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._is_talking = False
+
+    async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and update animation state.
+
+        Args:
+            frame: The incoming frame to process
+            direction: The direction of frame flow in the pipeline
+        """
+        await super().process_frame(frame, direction)
+
+        # Switch to talking animation when bot starts speaking
+        if isinstance(frame, BotStartedSpeakingFrame):
+            if not self._is_talking:
+                await self.push_frame(talking_frame)
+                self._is_talking = True
+        # Return to static frame when bot stops speaking
+        elif isinstance(frame, BotStoppedSpeakingFrame):
+            await self.push_frame(quiet_frame)
+            self._is_talking = False
+
+        await self.push_frame(frame, direction)
+
+
+async def main():
+    """Main bot execution function.
+
+    Sets up and runs the bot pipeline including:
+    - Daily video transport with specific audio parameters
+    - Gemini Live multimodal model integration
+    - Voice activity detection
+    - Animation processing
+    - RTVI event handling
+    """
+    async with aiohttp.ClientSession() as session:
+        (room_url, token) = await configure(session)
+
+        # Set up Daily transport with specific audio/video parameters for Gemini
+        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)),
+            ),
+        )
+
+        # Initialize the Gemini Multimodal Live model
+        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.",
+            },
+        ]
+
+        # Set up conversation context and management
+        # The context_aggregator will automatically collect conversation context
+        context = OpenAILLMContext(messages)
+        context_aggregator = llm.create_context_aggregator(context)
+
+        ta = TalkingAnimation()
+
+        #
+        # RTVI events for Pipecat client UI
+        #
+
+        # 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

@@ -4,6 +4,19 @@
 # SPDX-License-Identifier: BSD 2-Clause License
 #
 
+"""OpenAI Bot Implementation.
+
+This module implements a chatbot using OpenAI's GPT-4 model for natural language
+processing. It includes:
+- Real-time audio/video interaction through Daily
+- Animated robot avatar
+- Text-to-speech using ElevenLabs
+- Support for both English and Spanish
+
+The bot runs as part of a pipeline that processes audio/video frames and manages
+the conversation flow.
+"""
+
 import asyncio
 import os
 import sys
@@ -31,6 +44,8 @@ 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
@@ -38,14 +53,13 @@ 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__)
 
+# Load sequential animation frames
 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")
@@ -54,18 +68,20 @@ for i in range(1, 26):
     with Image.open(full_path) as img:
         sprites.append(OutputImageRawFrame(image=img.tobytes(), size=img.size, format=img.format))
 
+# Create a smooth animation by adding reversed frames
 flipped = sprites[::-1]
 sprites.extend(flipped)
 
-# When the bot isn't talking, show a static image of the cat listening
+# Define static and animated states
-quiet_frame = sprites[0]
+quiet_frame = sprites[0]  # Static frame for when bot is listening
-talking_frame = SpriteFrame(images=sprites)
+talking_frame = SpriteFrame(images=sprites)  # Animation sequence for when bot is talking
 
 
 class TalkingAnimation(FrameProcessor):
-    """
+    """Manages the bot's visual animation states.
-    This class starts a talking animation when it receives an first AudioFrame,
+
-    and then returns to a "quiet" sprite when it sees a TTSStoppedFrame.
+    Switches between static (listening) and animated (talking) states based on
+    the bot's current speaking status.
     """
 
     def __init__(self):
@@ -73,12 +89,20 @@ class TalkingAnimation(FrameProcessor):
         self._is_talking = False
 
     async def process_frame(self, frame: Frame, direction: FrameDirection):
+        """Process incoming frames and update animation state.
+
+        Args:
+            frame: The incoming frame to process
+            direction: The direction of frame flow in the pipeline
+        """
         await super().process_frame(frame, direction)
 
+        # Switch to talking animation when bot starts speaking
         if isinstance(frame, BotStartedSpeakingFrame):
             if not self._is_talking:
                 await self.push_frame(talking_frame)
                 self._is_talking = True
+        # Return to static frame when bot stops speaking
         elif isinstance(frame, BotStoppedSpeakingFrame):
             await self.push_frame(quiet_frame)
             self._is_talking = False
@@ -87,9 +111,19 @@ class TalkingAnimation(FrameProcessor):
 
 
 async def main():
+    """Main bot execution function.
+
+    Sets up and runs the bot pipeline including:
+    - Daily video transport
+    - Speech-to-text and text-to-speech services
+    - Language model integration
+    - Animation processing
+    - RTVI event handling
+    """
     async with aiohttp.ClientSession() as session:
         (room_url, token) = await configure(session)
 
+        # Set up Daily transport with video/audio parameters
         transport = DailyTransport(
             room_url,
             token,
@@ -113,6 +147,7 @@ async def main():
             ),
         )
 
+        # Initialize text-to-speech service
         tts = ElevenLabsTTSService(
             api_key=os.getenv("ELEVENLABS_API_KEY"),
             #
@@ -126,6 +161,7 @@ async def main():
             # voice_id="gD1IexrzCvsXPHUuT0s3",
         )
 
+        # Initialize LLM service
         llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
 
         messages = [
@@ -142,12 +178,19 @@ async def main():
             },
         ]
 
+        # Set up conversation context and management
+        # The context_aggregator will automatically collect conversation context
         context = OpenAILLMContext(messages)
         context_aggregator = llm.create_context_aggregator(context)
 
         ta = TalkingAnimation()
 
-        # RTVI
+        #
+        # RTVI events for Pipecat client UI
+        #
+
+        # This will send `user-*-speaking` and `bot-*-speaking` messages.
+        rtvi_speaking = RTVISpeakingProcessor()
 
         # This will emit UserTranscript events.
         rtvi_user_transcription = RTVIUserTranscriptionProcessor()
@@ -155,21 +198,33 @@ async def main():
         # 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...
+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