Initial commit

token_server.py

@@ -0,0 +1,81 @@
+"""
+token_server.py
+Serves:
+  GET /token?room=<name>  → LiveKit JWT token
+  GET /models             → list of Ollama/LM Studio models
+  static/index.html       → browser UI
+"""
+
+import os, json, asyncio, httpx
+from pathlib import Path
+from dotenv import load_dotenv
+from fastapi import FastAPI, Query
+from fastapi.responses import JSONResponse
+from fastapi.staticfiles import StaticFiles
+import uvicorn
+from livekit.api import AccessToken, VideoGrants, RoomConfiguration, RoomAgentDispatch
+
+load_dotenv()
+
+LIVEKIT_API_KEY    = os.getenv("LIVEKIT_API_KEY", "devkey")
+LIVEKIT_API_SECRET = os.getenv("LIVEKIT_API_SECRET", "secret")
+OLLAMA_BASE_URL    = os.getenv("OLLAMA_BASE_URL", "http://localhost:11434/v1")
+
+app = FastAPI()
+
+@app.get("/token")
+async def get_token(
+    room: str = Query("my-room"),
+    identity: str = Query("browser-user"),
+    model: str = Query(""),
+    prompt: str = Query(""),
+):
+    attributes = {}
+    if model:
+        attributes["model"] = model
+    if prompt:
+        attributes["prompt"] = prompt
+
+    token = (
+        AccessToken(LIVEKIT_API_KEY, LIVEKIT_API_SECRET)
+        .with_identity(identity)
+        .with_name(identity)
+        .with_grants(VideoGrants(room_join=True, room=room))
+        .with_room_config(RoomConfiguration(
+            agents=[RoomAgentDispatch(agent_name="")]
+        ))
+    )
+    if attributes:
+        token = token.with_attributes(attributes)
+
+    return {"token": token.to_jwt(), "room": room}
+
+@app.get("/models")
+async def list_models():
+    """Proxy to Ollama/LM Studio model list endpoint."""
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            # OpenAI-compat endpoint (works for Ollama & LM Studio)
+            r = await client.get(OLLAMA_BASE_URL.rstrip("/v1").rstrip("/") + "/api/tags")
+            if r.status_code == 200:
+                data = r.json()
+                models = [m["name"] for m in data.get("models", [])]
+                return {"models": models}
+    except Exception:
+        pass
+    # Fallback: OpenAI /v1/models
+    try:
+        async with httpx.AsyncClient(timeout=5) as client:
+            r = await client.get(OLLAMA_BASE_URL.rstrip("/") + "/models")
+            if r.status_code == 200:
+                data = r.json()
+                models = [m["id"] for m in data.get("data", [])]
+                return {"models": models}
+    except Exception:
+        pass
+    return {"models": [], "error": "Could not reach local model server"}
+
+app.mount("/", StaticFiles(directory="static", html=True), name="static")
+
+if __name__ == "__main__":
+    uvicorn.run(app, host="0.0.0.0", port=7731)