Update app.py

app.py

@@ -278,57 +278,58 @@ def rephrase_query(chat_history, query, temperature=0.2):
     system_prompt = f"""
 You are a highly intelligent and context-aware conversational assistant. Your tasks are as follows:
 
-1. **Entity Identification and Quotation**:
-    - Analyze the user's query to identify the main entities (e.g., organizations, brands, products, locations).
-    - For each identified entity, enclose ONLY the entity itself in double quotes within the query.
-    - If no identifiable entities are found, proceed without adding quotes.
-
-2. **Query Preservation**:
-    - Maintain the entire original query, including any parts after commas or other punctuation.
-    - Do not remove or truncate any part of the original query.
-
-3. **Appending Current Year**:
-    - Append "after: {current_year}" to the end of the rephrased query.
-    - Ensure there is a space before "after:" for proper formatting.
-    - Do not use quotes or the "+" operator when adding the year.
-
-4. **Output**:
-    - Return ONLY the rephrased query, ensuring it is concise, clear, and contextually accurate.
-    - Do not include any additional commentary or explanation.
+1. Determine if the new query is a continuation of the previous conversation or an entirely new topic.
+
+2. For both continuations and new topics:
+   a. **Entity Identification and Quotation**:
+      - Analyze the user's query to identify the main entities (e.g., organizations, brands, products, locations).
+      - For each identified entity, enclose ONLY the entity itself in double quotes within the query.
+      - If no identifiable entities are found, proceed without adding quotes.
+   b. **Query Preservation**:
+      - Maintain the entire original query, including any parts after commas or other punctuation.
+      - Do not remove or truncate any part of the original query.
+
+3. If it's a continuation:
+   - Incorporate relevant information from the context to make the query more specific and contextual.
+   - Ensure that entities from the previous context are properly quoted if they appear in the rephrased query.
+
+4. For both continuations and new topics:
+   - Append "after: {current_year}" to the end of the rephrased query.
+   - Ensure there is a space before "after:" for proper formatting.
+   - Do not use quotes or the "+" operator when adding the year.
+
+5. **Output**:
+   - Return ONLY the rephrased query, ensuring it is concise, clear, and contextually accurate.
+   - Do not include any additional commentary or explanation.
 
 ### Example Scenarios
-
-**Scenario 1: Query with One Entity**
-
+**Scenario 1: New Topic**
 - **User Query**: "What is the latest news on Golomt Bank?"
 - **Rephrased Query**: "What is the latest news on \"Golomt Bank\" after: {current_year}"
 
-**Scenario 2: Query with Multiple Entities and Comma**
+**Scenario 2: Continuation**
+- **Previous Query**: "What is the latest news on Golomt Bank?"
+- **User Query**: "How did the Bank perform in Q2 2024?"
+- **Rephrased Query**: "How did \"Golomt Bank\" perform in Q2 2024 after: {current_year}"
 
+**Scenario 3: Query with Multiple Entities and Comma**
 - **User Query**: "What is the latest news about Prospect Capital, did the rating change?"
 - **Rephrased Query**: "What is the latest news about \"Prospect Capital\", did the rating change after: {current_year}"
 
-**Scenario 3: Query Without Recognizable Entities**
-
+**Scenario 4: Query Without Recognizable Entities**
 - **User Query**: "How does photosynthesis work?"
 - **Rephrased Query**: "How does photosynthesis work? after: {current_year}"
-
 """
-
     user_prompt = f"""
 Conversation context:
 {chat_history}
-
 New query: {query}
-
 Rephrased query:
 """
-
     messages = [
         {"role": "system", "content": system_prompt},
         {"role": "user", "content": user_prompt}
     ]
-
     try:
         logger.info(f"Sending rephrasing request to LLM with temperature {temperature}")
         response = client.chat_completion(
@@ -338,12 +339,10 @@ Rephrased query:
         )
         logger.info("Received rephrased query from LLM")
         rephrased_question = response.choices[0].message.content.strip()
-
         # Remove surrounding quotes if present
         if (rephrased_question.startswith('"') and rephrased_question.endswith('"')) or \
            (rephrased_question.startswith("'") and rephrased_question.endswith("'")):
             rephrased_question = rephrased_question[1:-1].strip()
-
         logger.info(f"Rephrased Query (cleaned): {rephrased_question}")
         return rephrased_question
     except Exception as e:
@@ -533,7 +532,7 @@ Your response should be detailed, informative, accurate, and directly relevant t
             response = groq_client.chat.completions.create(
                 messages=messages,
                 model="llama-3.1-8b-instant",
-                max_tokens=4192,
+                max_tokens=5500,
                 temperature=temperature,
                 top_p=0.9,
                 frequency_penalty=1.2,