Update app.py

app.py

@@ -41,7 +41,7 @@ class RetrievalAugmentedQAPipeline:
         messages = chat_prompt.format_prompt(context=context_prompt, question=user_query).to_messages()
 
         response = await self.llm.agenerate([messages])
-        return {"response": response.generations[0][0].text, "context": context_list}
+        return {"response": response.generations[0][0].text}
 
 # PDF processing functions
 async def fetch_pdf(session, url):
@@ -49,7 +49,6 @@ async def fetch_pdf(session, url):
         if response.status == 200:
             return await response.read()
         else:
-            st.error(f"Failed to fetch PDF from {url}")
             return None
 
 async def process_pdf(pdf_content):
@@ -78,8 +77,6 @@ async def main():
             chunks = await process_pdf(pdf_content)
             all_chunks.extend(chunks)
 
-    st.write(f"Created {len(all_chunks)} chunks from {len(pdf_urls)} PDF files")
-
     embeddings = OpenAIEmbeddings()
     vector_db = Chroma.from_texts(all_chunks, embeddings)
     
@@ -99,7 +96,3 @@ if user_query:
     
     st.write("Response:")
     st.write(result["response"])
-    
-    st.write("Context used:")
-    for i, context in enumerate(result["context"], 1):
-        st.write(f"{i}. {context[:100]}...")