Update app.py

app.py

@@ -1,4 +1,3 @@
-
 import subprocess 
 import os
 import torch
@@ -53,6 +52,13 @@ class ChatHistory:
     def clear(self):
         self.messages = []
 
+# Function to log questions and answers to a file
+def log_to_file(question: str, answer: str):
+    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+    log_entry = f"Timestamp: {timestamp}\nQuestion: {question}\nAnswer: {answer}\n\n"
+    with open("Logs.txt", "a") as log_file:
+        log_file.write(log_entry)
+
 # Load environment variables and setup
 load_dotenv()
 
@@ -102,25 +108,6 @@ retriever = db.as_retriever(
     search_kwargs={"k": 5}
 )
 
-#llm = ChatCerebras(
-  #  model="llama-3.3-70b",
-  #  api_key=C_apikey,
-  #  streaming=True
-#)
-
-# llm = ChatOpenAI(
-#     model="meta-llama/Llama-3.3-70B-Instruct",
-#     temperature=0,
-#     max_tokens=None,
-#     timeout=None,
-#     max_retries=2,
-#     api_key=HF_TOKEN,  # if you prefer to pass api key in directly instaed of using env vars
-#     base_url="https://api-inference.huggingface.co/v1/",
-#     stream=True,
-    
-# )
-
-
 llm = ChatGoogleGenerativeAI(
     model="gemini-2.0-flash-thinking-exp-01-21",
     temperature=0,
@@ -129,7 +116,6 @@ llm = ChatGoogleGenerativeAI(
     max_retries=2,
     api_key=GEMINI,
     stream=True,
-    
 )
 
 template = """
@@ -142,113 +128,70 @@ Core Principles
 
 1. Source of Truth: Rely exclusively on the information available in the retrieved context and chat history. Avoid fabricating details or using external knowledge.
 
-
 2. Clarity and Precision: Provide clear, concise, and professional responses, ensuring they are easy to understand.
 
-
 3. Actionable Guidance: Offer practical solutions, step-by-step workflows, and troubleshooting advice tailored to Mawared HR queries.
 
-
 4. Structured Instructions: Use numbered or bullet-point lists for complex processes to ensure clarity.
 
-
 5. Targeted Clarification: Ask specific, polite questions to gather missing details when a query lacks sufficient information.
 
-
 6. Exclusive Focus: Limit your responses strictly to Mawared HR-related topics, avoiding unrelated discussions.
 
-
 7. Professional Tone: Maintain a friendly, approachable, and professional demeanor in all communications.
 
-
-
-
 ---
 
 Response Guidelines
 
 1. Analyze the Query Thoughtfully
-
-Carefully review the user’s question and the chat history.
-
-Identify the user’s explicit intent and infer additional context where applicable.
-
-Note any gaps in the provided information.
-
+   Carefully review the user’s question and the chat history.
+   Identify the user’s explicit intent and infer additional context where applicable.
+   Note any gaps in the provided information.
 
 2. Break Down Context Relevance
-
-Extract and interpret relevant details from the provided context or chat history.
-
-Match the user's needs to the most applicable information available.
-
+   Extract and interpret relevant details from the provided context or chat history.
+   Match the user's needs to the most applicable information available.
 
 3. Develop the Response Step-by-Step
-
-Frame a clear, logical structure to your response:
-
-What is the user trying to achieve?
-
-Which parts of the context directly address this?
-
-What steps or details should be highlighted for clarity?
-
-
-Provide answers in a structured, easy-to-follow format, using numbered steps or bullet points.
-
+   Frame a clear, logical structure to your response:
+   - What is the user trying to achieve?
+   - Which parts of the context directly address this?
+   - What steps or details should be highlighted for clarity?
+   Provide answers in a structured, easy-to-follow format, using numbered steps or bullet points.
 
 4. Ask for Clarifications Strategically
-
-If details are insufficient, specify the missing information politely and clearly (e.g., “Could you confirm [specific detail] to proceed with [action/task]?”).
-
+   If details are insufficient, specify the missing information politely and clearly (e.g., “Could you confirm [specific detail] to proceed with [action/task]?”).
 
 5. Ensure Directness and Professionalism
-
-Keep responses focused, avoiding unnecessary elaboration or irrelevant details.
-
-Uphold a professional and courteous tone throughout.
-
+   Keep responses focused, avoiding unnecessary elaboration or irrelevant details.
+   Uphold a professional and courteous tone throughout.
 
 6. Double-Check for Exclusivity
-
-Verify that all guidance is strictly derived from the retrieved context or chat history.
-
-Avoid speculating or introducing external information about Mawared HR.
-
-
+   Verify that all guidance is strictly derived from the retrieved context or chat history.
+   Avoid speculating or introducing external information about Mawared HR.
 
 ---
 
 Handling Information Gaps
 
 If the context is insufficient to answer the query:
-
-Clearly state that additional details are needed.
-
-Specify what information is required.
-
-Avoid fabricating or making assumptions to fill gaps.
-
-
-
+- Clearly state that additional details are needed.
+- Specify what information is required.
+- Avoid fabricating or making assumptions to fill gaps.
 
 ---
 
 Critical Constraints
 
-Strict Context Reliance: Base all responses solely on the provided context and chat history.
-
-Non-Mawared HR Queries: Politely decline to answer questions unrelated to Mawared HR.
-
-Answer Format: Always provide accurate answers in numbered steps without revealing your thought process or using code.
-
-
+- Strict Context Reliance: Base all responses solely on the provided context and chat history.
+- Non-Mawared HR Queries: Politely decline to answer questions unrelated to Mawared HR.
+- Answer Format: Always provide accurate answers in numbered steps without revealing your thought process or using code.
 
 ---
 
 By adhering to these principles and guidelines, ensure every response is accurate, professional, and easy to follow.
 
-
 Previous Conversation: {chat_history}
 Retrieved Context: {context}
 Current Question: {question}
@@ -324,6 +267,9 @@ def ask_question_gradio(question: str, history: List[List[str]]) -> Generator[tu
         # Add final response to chat history
         chat_history.add_message("assistant", response)
         
+        # Log the question and answer to a file
+        log_to_file(question, response)
+        
     except Exception as e:
         logger.error(f"Error during question processing: {e}")
         if not history: