Upload chatbot_logic.py

utils/chatbot_logic.py

@@ -0,0 +1,41 @@
+import os
+from utils.response_manager import ResponseManager  # Import the ResponseManager class
+
+# Vector store ID for the retrieval of knowledge base documents
+# Load the vector store ID from the environment variable
+vector_store_id = os.getenv('VECTOR_STORE_ID')
+
+# Check if the VECTOR_STORE_ID environment variable is set
+if not vector_store_id:
+    raise ValueError("VECTOR_STORE_ID environment variable is not set.")
+
+# Initialize the ResponseManager with the vector store ID
+response_manager = ResponseManager(vector_store_id)
+
+# Set parameters for the response generation
+model = "gpt-4o-mini"  # Set the model to be used for response generation
+temperature = 0  # Set the temperature for response generation
+max_output_tokens = 800  # Set the maximum number of output tokens
+max_num_results = 15  # Set the maximum number of knowledge base documents to return for retrieval
+
+
+def conversation(query: str, history):
+    """
+    Function to handle the chatbot interaction and maintain conversation history.
+    :param query: The user query to respond to.
+    :param history: The conversation history (list of [input, output] pairs).
+    :return: Updated conversation history.
+    """
+    try:
+        if query.strip():
+            response = response_manager.create_response(query, model, temperature, max_output_tokens, max_num_results)
+            if not response:
+                response = "Sorry, I couldn't generate a response at this time. Please try again later."
+            # Append the conversation
+            history.append((query, response))
+        else:
+            history.append((query, "Please enter a valid query."))
+        return history
+    except Exception as e:
+        history.append((query, str(e)))
+        return history