Update app.py

app.py

@@ -328,17 +328,52 @@ textarea::placeholder {
 }
 """
 
+# def process_question(question: str) -> Iterator[str]:
+#     """
+#     Process the question and return a response generator for streaming.
+#     """
+#     if question in question_cache:
+#         yield question_cache[question][0]
+#         return
+
+#     relevant_docs = retriever(question)
+#     context = "\n".join([doc.page_content for doc in relevant_docs])
+
+#     prompt = prompt_template.format_messages(
+#         context=context,
+#         question=question
+#     )
+
+#     full_response = ""
+#     try:
+#         for chunk in llm.stream(prompt):
+#             if isinstance(chunk, str):
+#                 current_chunk = chunk
+#             else:
+#                 current_chunk = chunk.content
+
+#             full_response += current_chunk
+#             yield full_response  # Send the updated response in streaming
+
+#         question_cache[question] = (full_response, context)
+#     except Exception as e:
+#         yield f"Erreur lors du traitement : {str(e)}"
+
 def process_question(question: str) -> Iterator[str]:
     """
-    Process the question and return a response generator for streaming.
+    Process the question and return a response generator for streaming, including sources.
     """
     if question in question_cache:
         yield question_cache[question][0]
         return
 
+    # Récupérer les documents pertinents
     relevant_docs = retriever(question)
     context = "\n".join([doc.page_content for doc in relevant_docs])
+    sources = [doc.metadata.get("source", "Source inconnue") for doc in relevant_docs]
+    # sources = os.path.splitext(sources[0])[0] if sources else "غير معروف"
 
+    # Générer le prompt
     prompt = prompt_template.format_messages(
         context=context,
         question=question
@@ -346,6 +381,7 @@ def process_question(question: str) -> Iterator[str]:
 
     full_response = ""
     try:
+        # Streaming de la réponse
         for chunk in llm.stream(prompt):
             if isinstance(chunk, str):
                 current_chunk = chunk
@@ -353,12 +389,20 @@ def process_question(question: str) -> Iterator[str]:
                 current_chunk = chunk.content
 
             full_response += current_chunk
-            yield full_response  # Send the updated response in streaming
+            yield full_response  # Envoyer la réponse mise à jour en streaming
 
+        # Ajouter les sources à la réponse finale
+        if sources:
+            sources_str = "\nSources :\n" + "\n".join(f"- {source}" for source in sources)
+            full_response += sources_str
+            yield sources_str  # Envoyer les sources
+
+        # Mettre en cache la réponse complète
         question_cache[question] = (full_response, context)
     except Exception as e:
         yield f"Erreur lors du traitement : {str(e)}"
 
+
 # def process_question(question: str) -> tuple[str, list[str]]:
 #     # Check cache first
 #     if question in question_cache:
@@ -396,19 +440,41 @@ def process_question(question: str) -> Iterator[str]:
 
 
 
+# def gradio_stream(question: str, chat_history: list) -> Iterator[list]:
+#     """
+#     Format the output for Gradio Chatbot component with streaming.
+#     """
+#     full_response = ""
+#     try:
+#         for partial_response in process_question(question):
+#             full_response = partial_response
+#             # Append the latest assistant response to chat history
+#             updated_chat = chat_history + [[question, partial_response]]
+#             yield updated_chat
+#     except Exception as e:
+#         # Handle errors during streaming
+#         updated_chat = chat_history + [[question, f"Erreur : {str(e)}"]]
+#         yield updated_chat
+
 def gradio_stream(question: str, chat_history: list) -> Iterator[list]:
     """
-    Format the output for Gradio Chatbot component with streaming.
+    Format the output for Gradio Chatbot component with streaming, including sources.
     """
     full_response = ""
+    sources_str = ""
     try:
         for partial_response in process_question(question):
-            full_response = partial_response
-            # Append the latest assistant response to chat history
-            updated_chat = chat_history + [[question, partial_response]]
+            if "Sources :" in partial_response:
+                # Les sources sont ajoutées à la réponse finale
+                sources_str = partial_response
+                updated_chat = chat_history + [[question, full_response + "\n" + sources_str]]
+            else:
+                # Construire progressivement la réponse
+                full_response = partial_response
+                updated_chat = chat_history + [[question, full_response]]
             yield updated_chat
     except Exception as e:
-        # Handle errors during streaming
+        # Gestion des erreurs lors du streaming
         updated_chat = chat_history + [[question, f"Erreur : {str(e)}"]]
         yield updated_chat