Update app.py

app.py

@@ -1,4 +1,4 @@
-# app.py -- HF-ready single-server FastAPI + Gradio mounted app
+# app.py -- HF-ready single-server FastAPI + Gradio mounted app (fixed)
 import os
 import shutil
 import asyncio
@@ -25,28 +25,29 @@ class FileWrapper:
         self._path = path
 
     async def download_to_drive(self, dst_path: str) -> None:
-        # keep API similar to your GradioFileWrapper
         loop = asyncio.get_event_loop()
         await loop.run_in_executor(None, shutil.copyfile, self._path, dst_path)
 
-def save_upload_to_tmp(up: UploadFile) -> str:
-    """Save FastAPI UploadFile to /tmp and return path."""
-    assert up and up.filename, "UploadFile missing filename"
+async def save_upload_to_tmp(up: UploadFile) -> str:
+    """Save FastAPI UploadFile to /tmp and return path. Uses async read."""
+    if not up or not up.filename:
+        raise ValueError("UploadFile missing or has no filename")
     dest = os.path.join(TMP_DIR, up.filename)
-    # overwrite if exists
+    data = await up.read()              # <-- important: async read
     with open(dest, "wb") as f:
-        f.write(up.file.read())
+        f.write(data)
     return dest
 
 async def call_ai(fn, *args, **kwargs):
     """
     Call AI functions safely: if fn is async, await it; if sync, run in thread.
-    This avoids blocking the event loop.
+    If fn is None, raise a clear error.
     """
+    if fn is None:
+        raise AttributeError("Requested AI method is not implemented in multimodal_module")
     if inspect.iscoroutinefunction(fn):
         return await fn(*args, **kwargs)
     else:
-        # run sync function in a thread to avoid blocking
         return await asyncio.to_thread(lambda: fn(*args, **kwargs))
 
 # ---------- FastAPI app ----------
@@ -56,7 +57,7 @@ app = FastAPI(title="Multimodal Module API")
 from fastapi.middleware.cors import CORSMiddleware
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],  # change to specific domains for production
+    allow_origins=["*"],  # tighten in production
     allow_credentials=True,
     allow_methods=["*"],
     allow_headers=["*"],
@@ -71,7 +72,8 @@ async def api_predict(inputs: str = Form(...), user_id: Optional[int] = Form(0),
     Form field 'inputs' used as text.
     """
     try:
-        reply = await call_ai(getattr(AI, "generate_response", getattr(AI, "process_text", None)), inputs, int(user_id), lang)
+        fn = getattr(AI, "generate_response", getattr(AI, "process_text", None))
+        reply = await call_ai(fn, inputs, int(user_id), lang)
         # HF-style returns "data" array
         return {"data": [reply]}
     except Exception as e:
@@ -80,7 +82,8 @@ async def api_predict(inputs: str = Form(...), user_id: Optional[int] = Form(0),
 @app.post("/api/text")
 async def api_text(text: str = Form(...), user_id: Optional[int] = Form(0), lang: str = Form("en")):
     try:
-        reply = await call_ai(getattr(AI, "generate_response", getattr(AI, "process_text", None)), text, int(user_id), lang)
+        fn = getattr(AI, "generate_response", getattr(AI, "process_text", None))
+        reply = await call_ai(fn, text, int(user_id), lang)
         return {"status": "ok", "reply": reply}
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
@@ -91,8 +94,9 @@ async def api_voice(user_id: Optional[int] = Form(0), audio_file: UploadFile = F
     Upload audio file (multipart/form-data). Returns whatever your AI.process_voice_message returns (JSON/dict).
     """
     try:
-        path = save_upload_to_tmp(audio_file)
-        result = await call_ai(getattr(AI, "process_voice_message", None), FileWrapper(path), int(user_id))
+        path = await save_upload_to_tmp(audio_file)
+        fn = getattr(AI, "process_voice_message", None)
+        result = await call_ai(fn, FileWrapper(path), int(user_id))
         return JSONResponse(result)
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
@@ -100,7 +104,8 @@ async def api_voice(user_id: Optional[int] = Form(0), audio_file: UploadFile = F
 @app.post("/api/voice_reply")
 async def api_voice_reply(user_id: Optional[int] = Form(0), reply_text: str = Form(...), fmt: str = Form("ogg")):
     try:
-        result = await call_ai(getattr(AI, "generate_voice_reply", None), reply_text, int(user_id), fmt)
+        fn = getattr(AI, "generate_voice_reply", None)
+        result = await call_ai(fn, reply_text, int(user_id), fmt)
         return {"status": "ok", "file": result}
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
@@ -108,8 +113,9 @@ async def api_voice_reply(user_id: Optional[int] = Form(0), reply_text: str = Fo
 @app.post("/api/image_caption")
 async def api_image_caption(user_id: Optional[int] = Form(0), image_file: UploadFile = File(...)):
     try:
-        path = save_upload_to_tmp(image_file)
-        caption = await call_ai(getattr(AI, "process_image_message", None), FileWrapper(path), int(user_id))
+        path = await save_upload_to_tmp(image_file)
+        fn = getattr(AI, "process_image_message", None)
+        caption = await call_ai(fn, FileWrapper(path), int(user_id))
         return {"status": "ok", "caption": caption}
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
@@ -117,7 +123,8 @@ async def api_image_caption(user_id: Optional[int] = Form(0), image_file: Upload
 @app.post("/api/generate_image")
 async def api_generate_image(user_id: Optional[int] = Form(0), prompt: str = Form(...), width: int = Form(512), height: int = Form(512), steps: int = Form(30)):
     try:
-        out_path = await call_ai(getattr(AI, "generate_image_from_text", None), prompt, int(user_id), width, height, steps)
+        fn = getattr(AI, "generate_image_from_text", None)
+        out_path = await call_ai(fn, prompt, int(user_id), width, height, steps)
         return {"status": "ok", "file": out_path}
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
@@ -125,11 +132,12 @@ async def api_generate_image(user_id: Optional[int] = Form(0), prompt: str = For
 @app.post("/api/edit_image")
 async def api_edit_image(user_id: Optional[int] = Form(0), image_file: UploadFile = File(...), mask_file: Optional[UploadFile] = File(None), prompt: str = Form("")):
     try:
-        img_path = save_upload_to_tmp(image_file)
+        img_path = await save_upload_to_tmp(image_file)
         mask_path = None
         if mask_file:
-            mask_path = save_upload_to_tmp(mask_file)
-        out_path = await call_ai(getattr(AI, "edit_image_inpaint", None), FileWrapper(img_path), FileWrapper(mask_path) if mask_path else None, prompt, int(user_id))
+            mask_path = await save_upload_to_tmp(mask_file)
+        fn = getattr(AI, "edit_image_inpaint", None)
+        out_path = await call_ai(fn, FileWrapper(img_path), FileWrapper(mask_path) if mask_path else None, prompt, int(user_id))
         return {"status": "ok", "file": out_path}
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
@@ -137,8 +145,9 @@ async def api_edit_image(user_id: Optional[int] = Form(0), image_file: UploadFil
 @app.post("/api/video")
 async def api_video(user_id: Optional[int] = Form(0), video_file: UploadFile = File(...)):
     try:
-        path = save_upload_to_tmp(video_file)
-        result = await call_ai(getattr(AI, "process_video", None), FileWrapper(path), int(user_id))
+        path = await save_upload_to_tmp(video_file)
+        fn = getattr(AI, "process_video", None)
+        result = await call_ai(fn, FileWrapper(path), int(user_id))
         return JSONResponse(result)
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
@@ -146,8 +155,9 @@ async def api_video(user_id: Optional[int] = Form(0), video_file: UploadFile = F
 @app.post("/api/file")
 async def api_file(user_id: Optional[int] = Form(0), file_obj: UploadFile = File(...)):
     try:
-        path = save_upload_to_tmp(file_obj)
-        result = await call_ai(getattr(AI, "process_file", None), FileWrapper(path), int(user_id))
+        path = await save_upload_to_tmp(file_obj)
+        fn = getattr(AI, "process_file", None)
+        result = await call_ai(fn, FileWrapper(path), int(user_id))
         return JSONResponse(result)
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
@@ -155,20 +165,26 @@ async def api_file(user_id: Optional[int] = Form(0), file_obj: UploadFile = File
 @app.post("/api/code")
 async def api_code(user_id: Optional[int] = Form(0), prompt: str = Form(...), max_tokens: int = Form(512)):
     try:
-        result = await call_ai(getattr(AI, "code_complete", None), int(user_id), prompt, max_tokens)
-        # Some modules return string/code, others dict — normalize:
+        fn = getattr(AI, "code_complete", None)
+        # Many implementations expect (user_id, prompt, max_tokens) or (prompt, max_tokens)
+        # Try user-first signature first, fallback to prompt-first
+        try:
+            result = await call_ai(fn, int(user_id), prompt, max_tokens)
+        except TypeError:
+            result = await call_ai(fn, prompt, max_tokens=max_tokens)
         return {"status": "ok", "code": result}
     except Exception as e:
         return JSONResponse({"error": str(e)}, status_code=500)
 
 # ---------- Minimal Gradio UI (mounted) ----------
 def gradio_text_fn(text, user_id, lang):
-    # call AI synchronously from Gradio (blocking safe in Gradio)
-    if inspect.iscoroutinefunction(getattr(AI, "generate_response", getattr(AI, "process_text", None))):
-        return asyncio.run(call_ai(getattr(AI, "generate_response", getattr(AI, "process_text", None)), text, int(user_id or 0), lang))
+    fn = getattr(AI, "generate_response", getattr(AI, "process_text", None))
+    if fn is None:
+        return "Error: text handler not implemented in multimodal_module"
+    if inspect.iscoroutinefunction(fn):
+        return asyncio.run(call_ai(fn, text, int(user_id or 0), lang))
     else:
-        # sync
-        return getattr(AI, "generate_response", getattr(AI, "process_text", None))(text, int(user_id or 0), lang)
+        return fn(text, int(user_id or 0), lang)
 
 with gr.Blocks(title="Multimodal Bot (UI)") as demo:
     gr.Markdown("# 🧠 Multimodal Bot — UI")