Fix: Added code to allow for other data sources to be added

phoebe/train_gpt_model.py

@@ -171,7 +171,13 @@ def check_input_chars(s, string_to_int):
     return unknown_chars
 
 
+# Maintain conversation history
+conversation_history = []
+
+
 def process_message(message):
+    global conversation_history
+
     print(f"Processing message: '{message}'")
     if not message.strip():
         print("Message is empty or invalid.")
@@ -182,27 +188,40 @@ def process_message(message):
         print(f"Message contains unknown characters: {unknown_chars}")
         return f"Message contains unknown characters: {unknown_chars}"
 
+    # Add the new message to the conversation history
+    conversation_history.append(message)
+    # Limit the conversation history to the last 5 messages to avoid excessive length
+    if len(conversation_history) > 5:
+        conversation_history = conversation_history[-5:]
+
+    # Concatenate the conversation history to form the input prompt
+    context = " ".join(conversation_history)
     encoded_text = torch.tensor(
-        [encode(message, string_to_int)], dtype=torch.long
+        [encode(context, string_to_int)], dtype=torch.long
     ).to(device)
     print(f"Encoded text shape: {encoded_text.shape}")
+
     if encoded_text.size(1) == 0:
         print("Message could not be processed.")
         return "Message could not be processed."
 
     with torch.no_grad():
         generated_tokens = model.generate(
-            encoded_text, max_new_tokens=50, temperature=0.7
+            encoded_text, max_new_tokens=100, temperature=1.0
         )
         generated_tokens = generated_tokens[0, len(encoded_text[0]) :]
 
     decoded_response = decode(generated_tokens.tolist(), int_to_string)
     print(f"Generated response: '{decoded_response}'")
 
-    if decoded_response.startswith(message):
-        decoded_response = decoded_response[len(message) :].strip()
+    if decoded_response.startswith(context):
+        decoded_response = decoded_response[len(context) :].strip()
 
     print(f"Final response: '{decoded_response}'")
+
+    # Add the response to the conversation history
+    conversation_history.append(decoded_response)
+
     return decoded_response