Change worker to be a python file

software/main.py

@@ -1,16 +1,3 @@
-"""
-01 # Runs light server and light simulator
-
-01 --server livekit # Runs livekit server only
-01 --server light # Runs light server only
-
-01 --client light-python
-
-... --expose # Exposes the server with ngrok
-... --expose --domain <domain> # Exposes the server on a specific ngrok domain
-... --qr # Displays a qr code
-"""
-
 from yaspin import yaspin
 spinner = yaspin()
 spinner.start()
@@ -29,6 +16,9 @@ import segno
 import time
 from dotenv import load_dotenv
 import signal
+from source.server.livekit.worker import main as worker_main
+import warnings
+import requests
 
 load_dotenv()
 
@@ -162,24 +152,13 @@ def run(
 
             # Start the livekit server
             livekit_thread = threading.Thread(
-                target=run_command, args=(f'livekit-server --dev --bind "{server_host}" --port {server_port}',)
+                target=run_command, args=(f'livekit-server --dev --bind "{server_host}" --port {server_port} > /dev/null 2>&1',)
             )
             time.sleep(7)
             livekit_thread.start()
             threads.append(livekit_thread)
 
-            # We communicate with the livekit worker via environment variables:
-            os.environ["INTERPRETER_SERVER_HOST"] = server_host
-            os.environ["INTERPRETER_LIGHT_SERVER_PORT"] = str(light_server_port)
-            os.environ["LIVEKIT_URL"] = f"ws://{server_host}:{server_port}"
-
-            # Start the livekit worker
-            worker_thread = threading.Thread(
-                target=run_command, args=("python source/server/livekit/worker.py dev",) # TODO: This should not be a CLI, it should just run the python file
-            )
-            time.sleep(7)
-            worker_thread.start()
-            threads.append(worker_thread)
+            livekit_url = f"ws://{server_host}:{server_port}"
 
         if expose:
 
@@ -200,7 +179,6 @@ def run(
         if server == "livekit":
             print("Livekit server will run at:", url)
 
-
         ### DISPLAY QR CODE
 
         if qr:
@@ -241,6 +219,28 @@ def run(
     signal.signal(signal.SIGTERM, signal_handler)
 
     try:
+
+        # Verify the server is running
+        for attempt in range(10):
+            try:
+                response = requests.get(url)
+                status = "OK" if response.status_code == 200 else "Not OK"
+                if status == "OK":
+                    break
+            except requests.RequestException:
+                pass
+            time.sleep(1)
+        else:
+            raise Exception(f"Server at {url} failed to respond after 10 attempts")
+
+        # Start the livekit worker
+        if server == "livekit":
+            time.sleep(7)
+            # These are needed to communicate with the worker's entrypoint
+            os.environ['INTERPRETER_SERVER_HOST'] = light_server_host
+            os.environ['INTERPRETER_SERVER_PORT'] = str(light_server_port)
+            worker_main(livekit_url)
+
         # Wait for all threads to complete
         for thread in threads:
             thread.join()

software/source/server/livekit/worker.py

@@ -7,9 +7,15 @@ from livekit import rtc
 from livekit.agents.voice_assistant import VoiceAssistant
 from livekit.plugins import deepgram, openai, silero, elevenlabs
 from dotenv import load_dotenv
+import sys
+import numpy as np
 
 load_dotenv()
 
+start_message = """Hi! You can hold the white circle below to speak to me.
+
+Try asking what I can do."""
+
 # This function is the entrypoint for the agent.
 async def entrypoint(ctx: JobContext):
     # Create an initial chat context with a system prompt
@@ -23,17 +29,47 @@ async def entrypoint(ctx: JobContext):
     # Connect to the LiveKit room
     await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY)
 
+    # Create a black background with a white circle
+    width, height = 640, 480
+    image_np = np.zeros((height, width, 4), dtype=np.uint8)
+    
+    # Create a white circle
+    center = (width // 2, height // 2)
+    radius = 50
+    y, x = np.ogrid[:height, :width]
+    mask = ((x - center[0])**2 + (y - center[1])**2) <= radius**2
+    image_np[mask] = [255, 255, 255, 255]  # White color with full opacity
+
+    source = rtc.VideoSource(width, height)
+    track = rtc.LocalVideoTrack.create_video_track("static_image", source)
+    
+    options = rtc.TrackPublishOptions()
+    options.source = rtc.TrackSource.SOURCE_CAMERA
+    publication = await ctx.room.local_participant.publish_track(track, options)
+
+    # Function to continuously publish the static image
+    async def publish_static_image():
+        while True:
+            frame = rtc.VideoFrame(width, height, rtc.VideoBufferType.RGBA, image_np.tobytes())
+            source.capture_frame(frame)
+            await asyncio.sleep(1/30)  # Publish at 30 fps
+
+    # Start publishing the static image
+    asyncio.create_task(publish_static_image())
+
     # VoiceAssistant is a class that creates a full conversational AI agent.
     # See https://github.com/livekit/agents/blob/main/livekit-agents/livekit/agents/voice_assistant/assistant.py
     # for details on how it works.
 
-    interpreter_server_host = os.getenv('INTERPRETER_SERVER_HOST', '0.0.0.0')
-    interpreter_server_port = os.getenv('INTERPRETER_LIGHT_SERVER_PORT', '8000')
-
+    interpreter_server_host = os.getenv('INTERPRETER_SERVER_HOST', 'localhost')
+    interpreter_server_port = os.getenv('INTERPRETER_SERVER_PORT', '8000')
     base_url = f"http://{interpreter_server_host}:{interpreter_server_port}/openai"
 
+    # For debugging
+    # base_url = "http://127.0.0.1:8000/openai"
+
     open_interpreter = openai.LLM(
-        model="open-interpreter", base_url=base_url
+        model="open-interpreter", base_url=base_url, api_key="x"
     )
 
     assistant = VoiceAssistant(
@@ -65,13 +101,20 @@ async def entrypoint(ctx: JobContext):
     await asyncio.sleep(1)
 
     # Greets the user with an initial message
-    await assistant.say("""Hi! You can hold the white circle below to speak to me.
-
-Try asking what I can do.""", allow_interruptions=True)
+    await assistant.say(start_message,
+    allow_interruptions=True)
 
 
-if __name__ == "__main__":
+def main(livekit_url):
+    
+    # Workers have to be run as CLIs right now.
+    # So we need to simualte running "[this file] dev"
+
+    # Modify sys.argv to set the path to this file as the first argument
+    # and 'dev' as the second argument
+    sys.argv = [str(__file__), 'dev']
+
     # Initialize the worker with the entrypoint
     cli.run_app(
-        WorkerOptions(entrypoint_fnc=entrypoint, api_key="devkey", api_secret="secret", ws_url=os.getenv("LIVEKIT_URL"))
-    )
+        WorkerOptions(entrypoint_fnc=entrypoint, api_key="devkey", api_secret="secret", ws_url=livekit_url)
+    )