chore: fix

main.py

@@ -43,7 +43,7 @@ class LoggingDisabled:
 
 def main():
     app = Application.builder().token(
-        '6207542226:AAGPOQrKiVdQJuHE0dQ1hKJm64ZXK-6z7-0',).build()
+        '6207542226:AAEeWfZzrMcGTiCmUkQSp3oXkedQJnrEaXc',).build()
 
     run_agent(
         agent=GirlfriendGPT(

src/agent/tools/conversation.py

@@ -1,6 +1,6 @@
 import logging
 from telegram import Update
-from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import torch
 from telegram.ext import (
     CallbackContext,
@@ -16,25 +16,39 @@ Output: A text
 
 GET_CON = range(1)
 
-class Conversation():
-    tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
-    model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-medium")
-
-    
 
-    async def talk(self, message: str):
-        logging.info(f"{message}")
-        chat_history_ids = torch.tensor([], dtype=torch.long)
-        new_user_input_ids = self.tokenizer.encode(message + self.tokenizer.eos_token, return_tensors='pt')
-        bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1)
-        chat_history_ids =self.model.generate(bot_input_ids, max_length=1000, pad_token_id=self.tokenizer.eos_token_id)
-        return "{}".format(self.tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True))
+class Conversation():
+    tokenizer = AutoTokenizer.from_pretrained(
+        "microsoft/GODEL-v1_1-large-seq2seq")
+    model = AutoModelForSeq2SeqLM.from_pretrained(
+        "microsoft/GODEL-v1_1-large-seq2seq")
+
+    # async def talk(self, message: str):
+    #     logging.info(f"{message}")
+    #     chat_history_ids = torch.tensor([], dtype=torch.long)
+    #     new_user_input_ids = self.tokenizer.encode(message + self.tokenizer.eos_token, return_tensors='pt')
+    #     bot_input_ids = torch.cat([chat_history_ids, new_user_input_ids], dim=-1)
+    #     chat_history_ids =self.model.generate(bot_input_ids, max_length=1000, pad_token_id=self.tokenizer.eos_token_id)
+    #     return "{}".format(self.tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True))
+
+    def generate(self, instruction, knowledge, dialog):
+        if knowledge != '':
+            knowledge = '[KNOWLEDGE] ' + knowledge
+        dialog = ' EOS '.join(dialog)
+        query = f"{instruction} [CONTEXT] {dialog} {knowledge}"
+        input_ids = self.tokenizer(f"{query}", return_tensors="pt").input_ids
+        outputs = self.model.generate(
+            input_ids, max_length=128,
+            min_length=8,
+            top_p=0.9,
+            do_sample=True,
+        )
+        output = self.tokenizer.decode(outputs[0], skip_special_tokens=True)
+        return output
 
-    
     async def process_conversation(self, update: Update, context: CallbackContext) -> int:
         message = update.message.text
-        text = await self.talk(message)
+        instruction = f'Instruction: given a dialog context, you need to response empathically.'
+        knowledge = ''
+        text = await self.generate(instruction, knowledge,message)
         await update.message.reply_text(f'{text}')
-
-    
-