Update app.py

app.py

@@ -8,27 +8,38 @@ from langchain_google_genai import ChatGoogleGenerativeAI
 import google.generativeai as genai
 from langchain.chains.question_answering import load_qa_chain  # Import load_qa_chain
 
-
 async def initialize(file_path, question):
     genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
     model = genai.GenerativeModel('gemini-pro')
     model = ChatGoogleGenerativeAI(model="gemini-pro", temperature=0.3)
-    prompt_template = """Understand the question answer to the question as precise as possible using the provided context. 
-                        If the answer is not contained in the context, say "answer not available in context" \n\n
-                          Context: \n {context}?\n
-                          Question: \n {question} \n
+    
+    # Refined prompt template to encourage precise and concise answers
+    prompt_template = """Answer the question precisely and concisely using the provided context. Avoid any additional commentary or system messages.
+                          If the answer is not contained in the context, respond with "answer not available in context".
+                          
+                          Context:
+                          {context}
+                          
+                          Question:
+                          {question}
+                          
                           Answer:
                         """
     prompt = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
+    
     if os.path.exists(file_path):
         pdf_loader = PyPDFLoader(file_path)
         pages = pdf_loader.load_and_split()
         context = "\n".join(f"Page {i+1}: {page.page_content}" for i, page in enumerate(pages[:30]))
         stuff_chain = load_qa_chain(model, chain_type="stuff", prompt=prompt)
         
-        # Use ainvoke instead of arun
+        # Use ainvoke to get the result
         stuff_answer = await stuff_chain.ainvoke({"input_documents": pages, "question": question, "context": context})
         
+        # Post-process the answer to remove any unnecessary text or system messages
+        answer = stuff_answer.strip()
+        answer = answer.split("Answer:")[1] if "Answer:" in answer else answer
+
         # Extract the page number where the context was found
         sources = []
         for i, page in enumerate(pages):
@@ -43,11 +54,10 @@ async def initialize(file_path, question):
         # Add the clickable link to the source
         file_name = os.path.basename(file_path)
         source_link = f"[{file_name}](file://{os.path.abspath(file_path)})"
-        return f"{stuff_answer} {source_str} - [Document: {source_link}]"
+        return f"{answer} {source_str} - [Document: {source_link}]"
     else:
         return "Error: Unable to process the document. Please ensure the PDF file is valid."
 
-
 # Define Gradio Interface
 input_file = gr.File(label="Upload PDF File")
 input_question = gr.Textbox(label="Ask about the document")