Fixed the RAG with openrouter

features/rag_chatbot/rag_pipeline.py

@@ -86,11 +86,31 @@ Respond with only the category name (COMPANY, CYBERSECURITY, or OFF_TOPIC):"""
             prompt=router_prompt
         )
         
-        # Company QA Chain
-        company_qa_chain = load_qa_chain(llm, chain_type="stuff")
+        # Custom Company QA Chain with natural prompt
+        company_qa_template = """You are a helpful assistant for CyberAlertNepal. Answer the following question about our company using the information provided and links if only available. Give a natural, direct and polite response .
+
+Question: {question}
+
+Information:
+{context}
+
+Answer:"""
+        
+        company_qa_prompt = PromptTemplate(
+            input_variables=["question", "context"],
+            template=company_qa_template
+        )
+        
+        company_qa_chain = LLMChain(
+            llm=llm,
+            prompt=company_qa_prompt
+        )
         
         # Cybersecurity Chain
-        cybersecurity_template = """You are a cybersecurity expert. Answer the following cybersecurity question based on your knowledge without claiming yourself as expert:
+        cybersecurity_template = """You are a cybersecurity professional. Answer the following question truthfully and concisely. 
+If you are not 100% sure about the answer, simply respond with: "I am not sure about the answer." 
+Do not add extra explanations or assumptions. Do not provide false or speculative information. 
+
 
 Question: {question}
 
@@ -170,8 +190,11 @@ def route_and_process_query(query: str):
                     "route": "COMPANY"
                 }
             
-            # Run the QA chain
-            answer = company_qa_chain.run(input_documents=docs, question=query)
+            # Combine document content for context
+            context = "\n\n".join([doc.page_content for doc in docs])
+            
+            # Run the custom QA chain
+            answer = company_qa_chain.run(question=query, context=context)
             sources = list(set([doc.metadata.get("source", "Unknown") for doc in docs]))
             
             return {