Fix API endpoints - use correct backend endpoints (/upload-dataset and /process-pipeline)

app.py

@@ -79,7 +79,7 @@ def upload_dataset(uploaded_file):
     
     try:
         files = {'file': uploaded_file}
-        response = requests.post(f"{st.session_state.backend_url}/api/upload", files=files)
+        response = requests.post(f"{st.session_state.backend_url}/upload-dataset", files=files)
         if response.status_code == 200:
             return response.json(), None
         else:
@@ -87,14 +87,15 @@ def upload_dataset(uploaded_file):
     except Exception as e:
         return None, f"Upload error: {str(e)}"
 
-def process_pipeline(file_path, prompt):
+def process_pipeline(uploaded_file, prompt):
     """Process dataset through ML pipeline"""
     if 'backend_url' not in st.session_state:
         return None, "Backend not connected"
     
     try:
-        data = {'file_path': file_path, 'prompt': prompt}
-        response = requests.post(f"{st.session_state.backend_url}/process-pipeline", json=data)
+        files = {'file': uploaded_file}
+        data = {'prompt': prompt}
+        response = requests.post(f"{st.session_state.backend_url}/process-pipeline", files=files, data=data)
         if response.status_code == 200:
             return response.json(), None
         else:
@@ -233,10 +234,9 @@ python app/main.py
         
         with col2:
             if st.button("🚀 Start Processing", type="primary"):
-                if st.session_state.upload_result:
-                    file_path = st.session_state.upload_result.get('file_path')
+                if uploaded_file is not None:
                     with st.spinner("Processing dataset... This may take a few minutes."):
-                        result, error = process_pipeline(file_path, prompt)
+                        result, error = process_pipeline(uploaded_file, prompt)
                         if error:
                             st.error(f"❌ Processing failed: {error}")
                         else: