Update main.py

main.py

@@ -1,38 +1,40 @@
-from fastapi import FastAPI
-from fastapi.responses import RedirectResponse
-import gradio as gr
-
-from app import answer_question_from_doc
-from appImage import answer_question_from_image
-
-app = FastAPI()
-
-# === Document QA Tab ===
-with gr.Blocks() as doc_interface:
-    gr.Markdown("## 📄 Document QA")
-    doc_file = gr.File(label="Upload File (PDF, DOCX, PPTX, XLSX)")
-    doc_question = gr.Textbox(label="Ask a question")
-    doc_answer = gr.Textbox(label="Answer")
-    doc_submit = gr.Button("Get Answer")
-    doc_submit.click(fn=answer_question_from_doc, inputs=[doc_file, doc_question], outputs=doc_answer)
-
-# === Image QA Tab ===
-with gr.Blocks() as img_interface:
-    gr.Markdown("## 🖼️ Image QA")
-    img_input = gr.Image(label="Upload an Image")
-    img_question = gr.Textbox(label="Ask a question")
-    img_answer = gr.Textbox(label="Answer")
-    img_submit = gr.Button("Get Answer")
-    img_submit.click(fn=answer_question_from_image, inputs=[img_input, img_question], outputs=img_answer)
-
-# === Combine Tabs ===
-demo = gr.TabbedInterface([doc_interface, img_interface], tab_names=["Document QA", "Image QA"])
-
-# Mount Gradio App
-app = gr.mount_gradio_app(app, demo, path="/")
-
-@app.get("/")
-def root():
-    return RedirectResponse(url="/")
-
-
+from fastapi import UploadFile, Form
+from fastapi.middleware.cors import CORSMiddleware
+from fastapi.responses import JSONResponse
+import shutil
+import os
+
+# Enable CORS so frontend can talk to backend
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+@app.post("/predict")
+async def predict(question: str = Form(...), file: UploadFile = Form(...)):
+    try:
+        # Save uploaded file
+        temp_path = f"temp_{file.filename}"
+        with open(temp_path, "wb") as f:
+            shutil.copyfileobj(file.file, f)
+
+        if file.content_type.startswith("image/"):
+            from appImage import answer_question_from_image
+            from PIL import Image
+            image = Image.open(temp_path)
+            answer = answer_question_from_image(image, question)
+        else:
+            from app import answer_question_from_doc
+            class NamedFile:
+                def __init__(self, name):
+                    self.name = name
+            answer = answer_question_from_doc(NamedFile(temp_path), question)
+
+        os.remove(temp_path)
+        return JSONResponse(content={"answer": answer})
+
+    except Exception as e:
+        return JSONResponse(content={"error": str(e)}, status_code=500)