Update app.py

app.py

@@ -27,6 +27,9 @@ from huggingface_hub import InferenceClient
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
+# Get HF token from environment
+HF_TOKEN = os.getenv('HF_TOKEN')
+
 # MCP Message Structure
 @dataclass
 class MCPMessage:
@@ -244,11 +247,11 @@ class RetrievalAgent(BaseAgent):
 
 # LLM Response Agent
 class LLMResponseAgent(BaseAgent):
-    def __init__(self, hf_token: str = None):
+    def __init__(self):
         super().__init__("LLMResponseAgent")
         self.client = InferenceClient(
             model="meta-llama/Llama-3.1-8B-Instruct",
-            token=hf_token
+            token=HF_TOKEN
         )
     
     def format_prompt(self, query: str, context_chunks: List[Dict]) -> str:
@@ -292,11 +295,11 @@ Answer:"""
 
 # Coordinator Agent
 class CoordinatorAgent(BaseAgent):
-    def __init__(self, hf_token: str = None):
+    def __init__(self):
         super().__init__("CoordinatorAgent")
         self.ingestion_agent = IngestionAgent()
         self.retrieval_agent = RetrievalAgent()
-        self.llm_agent = LLMResponseAgent(hf_token)
+        self.llm_agent = LLMResponseAgent()
         self.documents_processed = False
     
     async def process_documents(self, files: List[str]) -> str:
@@ -367,48 +370,31 @@ class CoordinatorAgent(BaseAgent):
             return f"Error processing query: {str(e)}", []
 
 # Global coordinator instance
-coordinator = None
-
-def initialize_app(hf_token):
-    """Initialize the application with HuggingFace token"""
-    global coordinator
-    coordinator = CoordinatorAgent(hf_token)
-    return "✅ Application initialized successfully!"
+coordinator = CoordinatorAgent()
 
 async def process_files(files):
     """Process uploaded files"""
-    if not coordinator:
-        return "❌ Please set your HuggingFace token first!"
-    
     if not files:
         return "❌ Please upload at least one file."
     
     # Save uploaded files to temporary directory
     file_paths = []
     for file in files:
-        temp_path = os.path.join(tempfile.gettempdir(), file.name)
-        with open(temp_path, 'wb') as f:
-            f.write(file.read())
-        file_paths.append(temp_path)
+        # Handle file path - Gradio returns file path as string
+        if hasattr(file, 'name'):
+            file_path = file.name
+        else:
+            file_path = str(file)
+        file_paths.append(file_path)
     
     result = await coordinator.process_documents(file_paths)
     
-    # Cleanup temporary files
-    for path in file_paths:
-        try:
-            os.remove(path)
-        except:
-            pass
-    
     return result
 
 async def answer_question(query, history):
     """Answer user question"""
-    if not coordinator:
-        return "❌ Please set your HuggingFace token first!"
-    
     if not query.strip():
-        return "❌ Please enter a question."
+        return history, ""
     
     response, context_chunks = await coordinator.answer_query(query)
     
@@ -419,7 +405,10 @@ async def answer_question(query, history):
             sources += f"{i}. {chunk['source']} (Chunk {chunk['chunk_id']})\n"
         response += sources
     
-    return response
+    # Add to chat history
+    history.append((query, response))
+    
+    return history, ""
 
 # Custom CSS
 custom_css = """
@@ -593,36 +582,6 @@ def create_interface():
         """)
         
         with gr.Tabs() as tabs:
-            # Setup Tab
-            with gr.TabItem("⚙️ Setup", elem_classes=["tab-nav"]):
-                gr.HTML("""
-                <div class="setup-card">
-                    <h3>🔑 Configuration</h3>
-                    <p>Enter your HuggingFace token to get started. This token is used to access the Llama-3.1-8B-Instruct model.</p>
-                </div>
-                """)
-                
-                with gr.Row():
-                    hf_token_input = gr.Textbox(
-                        label="HuggingFace Token",
-                        placeholder="hf_xxxxxxxxxxxxxxxxxxxxxxxxx",
-                        type="password",
-                        elem_classes=["input-container"]
-                    )
-                
-                with gr.Row():
-                    init_button = gr.Button(
-                        "Initialize Application", 
-                        variant="primary",
-                        elem_classes=["primary-button"]
-                    )
-                
-                init_status = gr.Textbox(
-                    label="Status",
-                    interactive=False,
-                    elem_classes=["input-container"]
-                )
-            
             # Upload Tab
             with gr.TabItem("📁 Upload Documents", elem_classes=["tab-nav"]):
                 gr.HTML("""
@@ -741,12 +700,6 @@ def create_interface():
                 """)
         
         # Event handlers
-        init_button.click(
-            fn=initialize_app,
-            inputs=[hf_token_input],
-            outputs=[init_status]
-        )
-        
         upload_button.click(
             fn=process_files,
             inputs=[file_upload],
@@ -756,13 +709,13 @@ def create_interface():
         ask_button.click(
             fn=answer_question,
             inputs=[query_input, chatbot],
-            outputs=[chatbot]
+            outputs=[chatbot, query_input]
         )
         
         query_input.submit(
             fn=answer_question,
             inputs=[query_input, chatbot],
-            outputs=[chatbot]
+            outputs=[chatbot, query_input]
         )
     
     return demo