Update app.py

app.py

@@ -21,12 +21,12 @@ def text_to_json(text):
 # Function to restrict query results to the PDF dataset (returns relevant content)
 def restrict_to_pdf_query(query, dataset):
     relevant_content = []
-    query_keywords = query.lower().split()  # Split query into keywords
-    
+    query_lower = query.lower()
+
     for section in dataset["dataset"]:
         section_content = section["content"].lower()
-        # Check if any of the keywords are present in the section content
-        if any(keyword in section_content for keyword in query_keywords):
+        # Check if the query is mentioned directly in the content
+        if query_lower in section_content:
             relevant_content.append(section["content"])
 
     return relevant_content if relevant_content else ["No relevant content found."]
@@ -85,11 +85,15 @@ if user_query:
 
         # Use only the first chunk (you can modify this to iterate over chunks or dynamically choose a chunk)
         if chunks:
+            # Prepare a prompt that asks the model to act as an expert lawyer
+            prompt = f"""You are a Pakistani lawyer. Answer the following query based on the Pakistan Penal Code, explaining it in a professional and detailed manner, including references to specific sections of the code when applicable. If the information is found in the dataset, provide it accordingly. Query: "{user_query}"\nAnswer: {chunks[0]}"""
+            
+            # Request answer from the model
             chat_completion = client.chat.completions.create(
                 messages=[
                     {
                         "role": "user",
-                        "content": chunks[0],  # Send the first chunk of relevant content
+                        "content": prompt,
                     }
                 ],
                 model="llama3-groq-70b-8192-tool-use-preview",  # Updated model