Update app.py

app.py

@@ -110,7 +110,12 @@ if 'chat_history' not in st.session_state:
 class CustomLanguageModel:
     def generate(self, prompt, context):
         # Implement logic to generate a response based on prompt and context
-        return f"Generated response based on prompt: '{prompt}' and context: '{context}'."
+        return f"Generated response: '{prompt}'. Key points from the context: '{self.summarize_context(context)}'."
+
+    def summarize_context(self, context):
+        # Summarize the context to extract key information
+        # You could use an NLP summarization model for a more sophisticated approach
+        return " ".join(context.split()[:100])  # Returning the first 100 words as a simple summary
 
 # Define a callable class for RAGPrompt
 class RAGPrompt:
@@ -163,7 +168,7 @@ if st.button("Submit Query"):
         # Apply the prompt directly to the data (no chaining using `|`)
         prompt_data = prompt({"question": query, "context": context})
 
-        # Generate the response using the language model
+        # Generate the response using the language model, focusing on the answer from the retrieved context
         result = custom_llm.generate(prompt_data["question"], prompt_data["context"])
 
         # Store query and response in session for chat history