Fix: remove Dockerfile, restructure app for Gradio SDK on HF Spaces

Dockerfile

@@ -1,12 +0,0 @@
-FROM python:3.11-slim
-
-WORKDIR /app
-
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
-
-COPY . .
-
-EXPOSE 7860
-
-CMD ["python", "app.py"]

app.py

@@ -2,8 +2,8 @@
 Jarvis AI Automation Planner — Hugging Face Space Application
 
 Exposes two interfaces:
-  1. Gradio chat UI for browser-based testing
-  2. OpenAI-compatible  POST /v1/chat/completions  API for mobile clients
+  1. Gradio chat UI at /  (browser testing)
+  2. OpenAI-compatible  POST /v1/chat/completions  (mobile clients)
 """
 
 import json
@@ -11,10 +11,8 @@ import logging
 import os
 import time
 import uuid
-from contextlib import asynccontextmanager
 
 import gradio as gr
-import uvicorn
 from fastapi import FastAPI, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse
@@ -36,25 +34,44 @@ logger = logging.getLogger("jarvis.app")
 # ---------------------------------------------------------------------------
 registry = ToolRegistry()
 agent = JarvisAgent(registry=registry)
+logger.info("Jarvis agent ready  •  model=%s  •  tools=%s", agent.model, registry.tool_names())
 
 # ---------------------------------------------------------------------------
-# FastAPI application
+# Gradio chat interface
 # ---------------------------------------------------------------------------
 
 
-@asynccontextmanager
-async def lifespan(application: FastAPI):
-    logger.info("Jarvis agent ready  •  model=%s  •  tools=%s", agent.model, registry.tool_names())
-    yield
+def chat_fn(message: str, _history: list) -> str:
+    """Gradio handler — takes a user message and returns the JSON plan."""
+    plan = agent.plan(message)
+    return json.dumps(plan, indent=2)
 
 
-api = FastAPI(
-    title="Jarvis – AI Automation Planner",
-    version="1.0.0",
-    lifespan=lifespan,
+demo = gr.ChatInterface(
+    fn=chat_fn,
+    title="🤖 Jarvis — AI Automation Planner",
+    description=(
+        "Type a command (e.g. *\"download a galaxy image\"*) and Jarvis will "
+        "return a structured JSON automation plan for your mobile device."
+    ),
+    examples=[
+        "Download a galaxy image",
+        "Open YouTube",
+        "Search water bottle for boys",
+        "Download a galaxy image and send it to Arun",
+        "Set an alarm for 7 AM",
+        "Search Google for latest AI news",
+    ],
+    type="messages",
 )
 
-api.add_middleware(
+# ---------------------------------------------------------------------------
+# Custom FastAPI routes (mounted alongside Gradio)
+# ---------------------------------------------------------------------------
+
+app = FastAPI(title="Jarvis – AI Automation Planner", version="1.0.0")
+
+app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
     allow_methods=["*"],
@@ -62,20 +79,9 @@ api.add_middleware(
 )
 
 
-# ----------  POST /v1/chat/completions  (OpenAI-compatible)  ---------------
-
-
-@api.post("/v1/chat/completions")
+@app.post("/v1/chat/completions")
 async def chat_completions(request: Request):
-    """
-    OpenAI-compatible chat completions endpoint.
-
-    Expects:
-      { "messages": [ {"role": "user", "content": "..."} ] }
-
-    Returns an OpenAI-shaped response whose assistant content is
-    the Jarvis JSON automation plan.
-    """
+    """OpenAI-compatible chat completions endpoint for mobile clients."""
     try:
         body = await request.json()
     except Exception:
@@ -85,7 +91,6 @@ async def chat_completions(request: Request):
     if not messages:
         return JSONResponse({"error": "No messages provided."}, status_code=400)
 
-    # Use the last user message as the command
     user_msg = ""
     for m in reversed(messages):
         if m.get("role") == "user":
@@ -95,10 +100,8 @@ async def chat_completions(request: Request):
     if not user_msg:
         return JSONResponse({"error": "No user message found."}, status_code=400)
 
-    # Run the Jarvis planning pipeline
     plan = agent.plan(user_msg)
 
-    # Wrap in OpenAI-compatible response shape
     return JSONResponse({
         "id": f"chatcmpl-{uuid.uuid4().hex[:12]}",
         "object": "chat.completion",
@@ -118,65 +121,20 @@ async def chat_completions(request: Request):
     })
 
 
-# ----------  GET /v1/models  -----------------------------------------------
-
-@api.get("/v1/models")
+@app.get("/v1/models")
 async def list_models():
     return {
         "object": "list",
-        "data": [
-            {
-                "id": agent.model,
-                "object": "model",
-                "owned_by": "jarvis",
-            }
-        ],
+        "data": [{"id": agent.model, "object": "model", "owned_by": "jarvis"}],
     }
 
 
-# ----------  GET /health  --------------------------------------------------
-
-@api.get("/health")
+@app.get("/health")
 async def health():
     return {"status": "ok", "model": agent.model, "tools": registry.tool_names()}
 
 
 # ---------------------------------------------------------------------------
-# Gradio chat interface (mounted on the same server)
-# ---------------------------------------------------------------------------
-
-
-def chat_fn(message: str, _history: list) -> str:
-    """Gradio handler — takes a user message and returns the JSON plan."""
-    plan = agent.plan(message)
-    return json.dumps(plan, indent=2)
-
-
-gradio_app = gr.ChatInterface(
-    fn=chat_fn,
-    title="🤖 Jarvis — AI Automation Planner",
-    description=(
-        "Type a command (e.g. *\"download a galaxy image\"*) and Jarvis will "
-        "return a structured JSON automation plan for your mobile device."
-    ),
-    examples=[
-        "Download a galaxy image",
-        "Open YouTube",
-        "Search water bottle for boys",
-        "Download a galaxy image and send it to Arun",
-        "Set an alarm for 7 AM",
-        "Search Google for latest AI news",
-    ],
-    type="messages",
-)
-
-# Mount Gradio inside FastAPI
-app = gr.mount_gradio_app(api, gradio_app, path="/")
-
-# ---------------------------------------------------------------------------
-# Entry point
+# Mount Gradio onto the FastAPI app at root
 # ---------------------------------------------------------------------------
-
-if __name__ == "__main__":
-    port = int(os.getenv("PORT", "7860"))
-    uvicorn.run("app:app", host="0.0.0.0", port=port, log_level="info")
+app = gr.mount_gradio_app(app, demo, path="/")

requirements.txt

@@ -1,4 +1 @@
-gradio>=4.0.0
-fastapi>=0.110.0
-uvicorn[standard]>=0.29.0
 huggingface_hub>=0.23.0