fix: use ASGI middleware to intercept /api/* before Gradio catch-all route

app.py

@@ -11,6 +11,8 @@ import gradio as gr
 from fastapi import FastAPI, File, UploadFile, Form, HTTPException, Request
 from fastapi.responses import JSONResponse, FileResponse
 from fastapi.middleware.cors import CORSMiddleware
+from starlette.middleware.base import BaseHTTPMiddleware
+from starlette.responses import Response
 
 # ---------------------------------------------------------------------------
 # Hugging Face ZeroGPU startup probe
@@ -206,22 +208,9 @@ def teach_new_object(name, category, description, reference_images):
 
 
 # ---------------------------------------------------------------------------
-# API helper functions (non-GPU, used inside Gradio's FastAPI)
+# API handler functions (non-GPU)
 # ---------------------------------------------------------------------------
 
-def _run_api_detection(img_bgr, mode, lock_mode, lock_target, prompts, conf_val, sim_val):
-    annotated_bgr, detections, metadata = orchestrator.process_frame(
-        image=img_bgr,
-        mode=mode,
-        lock_mode=lock_mode,
-        lock_target=lock_target,
-        open_vocab_prompts=prompts,
-        confidence_thresh=conf_val,
-        similarity_thresh=sim_val
-    )
-    return annotated_bgr, detections, metadata
-
-
 def _handle_api_health():
     return {
         "status": "healthy",
@@ -251,14 +240,14 @@ def _handle_api_detect(file_bytes, mode, lock_mode, lock_target, open_vocab_prom
     raw_vocab = open_vocab_prompts or vocabulary
     prompts = [p.strip() for p in raw_vocab.split(",") if p.strip()] if raw_vocab else None
 
-    annotated_frame, detections, metadata = _run_api_detection(
-        img_bgr=img,
+    annotated_frame, detections, metadata = orchestrator.process_frame(
+        image=img,
         mode=mode,
         lock_mode=is_lock_mode,
         lock_target=target_val,
-        prompts=prompts,
-        conf_val=conf_val,
-        sim_val=SPECIFIC_SIMILARITY_THRESHOLD
+        open_vocab_prompts=prompts,
+        confidence_thresh=conf_val,
+        similarity_thresh=SPECIFIC_SIMILARITY_THRESHOLD
     )
 
     _, buffer = cv2.imencode(".png", annotated_frame)
@@ -307,6 +296,80 @@ def _handle_api_export_db():
     return zip_path
 
 
+# ---------------------------------------------------------------------------
+# ASGI Middleware — intercepts /api/* routes BEFORE Gradio's catch-all
+# ---------------------------------------------------------------------------
+
+class CustomAPIMiddleware(BaseHTTPMiddleware):
+    async def dispatch(self, request: Request, call_next):
+        path = request.url.path
+        method = request.method
+
+        if not path.startswith("/api/"):
+            return await call_next(request)
+
+        try:
+            if method == "GET" and path == "/api/health":
+                return JSONResponse(content=_handle_api_health())
+
+            elif method == "POST" and path == "/api/detect":
+                form = await request.form()
+                file = form.get("file")
+                if not file:
+                    return JSONResponse(status_code=400, content={"detail": "Missing 'file' field"})
+                file_bytes = await file.read()
+                result = _handle_api_detect(
+                    file_bytes,
+                    form.get("mode", "combined"),
+                    form.get("lock_mode", "false"),
+                    form.get("lock_target", ""),
+                    form.get("open_vocab_prompts", ""),
+                    form.get("vocabulary", ""),
+                    form.get("confidence", ""),
+                )
+                return JSONResponse(content=result)
+
+            elif method == "GET" and path == "/api/objects":
+                return JSONResponse(content=_handle_api_objects())
+
+            elif method == "POST" and path == "/api/objects":
+                form = await request.form()
+                name = form.get("name", "")
+                category = form.get("category", "custom")
+                description = form.get("description", "")
+                files_bytes = []
+                for key in form:
+                    if key == "files" or key.startswith("files"):
+                        upload_file = form[key]
+                        content = await upload_file.read()
+                        files_bytes.append((content, getattr(upload_file, "filename", "image")))
+                result = _handle_api_teach(name, category, description, files_bytes)
+                return JSONResponse(content=result)
+
+            elif method == "DELETE" and path.startswith("/api/objects/"):
+                object_id = path.split("/api/objects/")[-1]
+                try:
+                    result = _handle_api_delete_object(object_id)
+                    return JSONResponse(content=result)
+                except ValueError as e:
+                    return JSONResponse(status_code=404, content={"detail": str(e)})
+
+            elif method == "GET" and path == "/api/downloads/export-db":
+                zip_path = _handle_api_export_db()
+                return FileResponse(zip_path, filename="custom_objects_library.zip", media_type="application/zip")
+
+            elif method == "GET" and path == "/api/downloads/requirements":
+                req_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "requirements.txt")
+                if os.path.exists(req_path):
+                    return FileResponse(req_path, filename="requirements.txt", media_type="text/plain")
+                return JSONResponse(status_code=404, content={"detail": "requirements.txt not found"})
+
+        except Exception as e:
+            return JSONResponse(status_code=500, content={"detail": str(e)})
+
+        return await call_next(request)
+
+
 # ---------------------------------------------------------------------------
 # Building Modern Glassmorphic Gradio UI
 # ---------------------------------------------------------------------------
@@ -374,9 +437,6 @@ with gr.Blocks(css=custom_css, title="Open-World Object Intelligence Platform")
 
     with gr.Tabs():
 
-        # -------------------------------------------------------------------
-        # TAB 1: Live Testing & Lock Mode
-        # -------------------------------------------------------------------
         with gr.TabItem("👁️ Live Testing & Lock Mode"):
             with gr.Row():
                 with gr.Column(scale=1):
@@ -431,9 +491,6 @@ with gr.Blocks(css=custom_css, title="Open-World Object Intelligence Platform")
                 api_name="run_detection"
             )
 
-        # -------------------------------------------------------------------
-        # TAB 2: Object Studio (Teach & Manage)
-        # -------------------------------------------------------------------
         with gr.TabItem("🎓 Object Studio (Teach & Manage)"):
             gr.Markdown("## Teach Specific Objects to the System")
             gr.Markdown("Upload reference photos of your personal physical object (e.g. *My Cup*, *Lab Keyring*). The system extracts L2 normalized visual embeddings to recognize this exact object identity.")
@@ -470,9 +527,6 @@ with gr.Blocks(css=custom_css, title="Open-World Object Intelligence Platform")
                 outputs=[teach_status, objects_df]
             )
 
-        # -------------------------------------------------------------------
-        # TAB 3: Model & Database Downloads
-        # -------------------------------------------------------------------
         with gr.TabItem("💾 Downloads & Package Export"):
             gr.Markdown("## Downloads, Models & Custom Object Database Export")
             gr.Markdown("Download pretrained models, database export packages, SDK packages, and verified checksum manifests.")
@@ -494,9 +548,6 @@ with gr.Blocks(css=custom_css, title="Open-World Object Intelligence Platform")
                     | **ResNet18 Backbone** | Feature Embedding Extractor | `7d88e2...03` | Torchvision |
                     """)
 
-        # -------------------------------------------------------------------
-        # TAB 4: Developer Guides & Documentation
-        # -------------------------------------------------------------------
         with gr.TabItem("📚 Developer Guides"):
             with gr.Row():
                 doc_selector = gr.Dropdown(
@@ -517,9 +568,6 @@ with gr.Blocks(css=custom_css, title="Open-World Object Intelligence Platform")
 
             doc_selector.change(fn=load_doc_file, inputs=[doc_selector], outputs=[doc_markdown_view])
 
-        # -------------------------------------------------------------------
-        # TAB 5: REST API Reference
-        # -------------------------------------------------------------------
         with gr.TabItem("🔌 REST API"):
             gr.Markdown("## REST API & FastAPI Endpoint Specifications")
             gr.Markdown("""
@@ -541,7 +589,7 @@ with gr.Blocks(css=custom_css, title="Open-World Object Intelligence Platform")
 
 
 # ---------------------------------------------------------------------------
-# Monkey-patch Gradio's create_app to inject our FastAPI routes
+# Monkey-patch Gradio's create_app to inject our ASGI middleware
 # ---------------------------------------------------------------------------
 from gradio.routes import App as _GradioApp
 
@@ -559,71 +607,12 @@ def _patched_create_app(blocks, *args, **kwargs):
         allow_headers=["*"],
     )
 
+    fastapi_app.add_middleware(CustomAPIMiddleware)
+
     @fastapi_app.on_event("startup")
     async def _startup():
         _zerogpu_startup_probe()
 
-    @fastapi_app.get("/api/health")
-    async def api_health():
-        return _handle_api_health()
-
-    @fastapi_app.post("/api/detect")
-    async def api_detect_route(
-        file: UploadFile = File(...),
-        mode: str = Form("combined"),
-        lock_mode: str = Form("false"),
-        lock_target: str = Form(""),
-        open_vocab_prompts: str = Form(""),
-        vocabulary: str = Form(""),
-        confidence: str = Form(""),
-    ):
-        contents = await file.read()
-        if not contents:
-            raise HTTPException(status_code=400, detail="Uploaded file is empty")
-        try:
-            return JSONResponse(content=_handle_api_detect(contents, mode, lock_mode, lock_target, open_vocab_prompts, vocabulary, confidence))
-        except ValueError as e:
-            raise HTTPException(status_code=400, detail=str(e))
-
-    @fastapi_app.get("/api/objects")
-    async def api_get_objects():
-        return _handle_api_objects()
-
-    @fastapi_app.post("/api/objects")
-    async def api_teach_object(
-        name: str = Form(...),
-        category: str = Form("custom"),
-        description: str = Form(""),
-        files: list[UploadFile] = File(default=[]),
-    ):
-        try:
-            files_bytes = []
-            for uf in files:
-                content = await uf.read()
-                files_bytes.append((content, uf.filename))
-            return JSONResponse(content=_handle_api_teach(name, category, description, files_bytes))
-        except ValueError as e:
-            raise HTTPException(status_code=400, detail=str(e))
-
-    @fastapi_app.delete("/api/objects/{object_id}")
-    async def api_delete_object(object_id: str):
-        try:
-            return JSONResponse(content=_handle_api_delete_object(object_id))
-        except ValueError as e:
-            raise HTTPException(status_code=404, detail=str(e))
-
-    @fastapi_app.get("/api/downloads/export-db")
-    async def api_export_db():
-        zip_path = _handle_api_export_db()
-        return FileResponse(zip_path, filename="custom_objects_library.zip", media_type="application/zip")
-
-    @fastapi_app.get("/api/downloads/requirements")
-    async def api_download_requirements():
-        req_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), "requirements.txt")
-        if os.path.exists(req_path):
-            return FileResponse(req_path, filename="requirements.txt", media_type="text/plain")
-        raise HTTPException(status_code=404, detail="requirements.txt not found")
-
     return fastapi_app