update chatglm_llm.py

chatglm_llm.py

@@ -3,26 +3,24 @@ from typing import Optional, List
 from langchain.llms.utils import enforce_stop_tokens
 from transformers import AutoTokenizer, AutoModel
 
-"""ChatGLM_G is a wrapper around the ChatGLM model to fit LangChain framework. May not be an optimal implementation"""
-
-
-class ChatGLM(LLM):
-    max_token: int = 10000
-    temperature: float = 0.1
-    top_p = 0.9
-    history = []
-    tokenizer = AutoTokenizer.from_pretrained(
+tokenizer = AutoTokenizer.from_pretrained(
     "THUDM/chatglm-6b",
     trust_remote_code=True
-    )
-    model = (
+)
+model = (
     AutoModel.from_pretrained(
         "THUDM/chatglm-6b",
         trust_remote_code=True)
     .half()
     .cuda()
-    )
+)
+
 
+class ChatGLM(LLM):
+    max_token: int = 10000
+    temperature: float = 0.1
+    top_p = 0.9
+    history = []
 
     def __init__(self):
         super().__init__()
@@ -34,13 +32,12 @@ class ChatGLM(LLM):
     def _call(self,
               prompt: str,
               stop: Optional[List[str]] = None) -> str:
-        response, updated_history = self.model.chat(
-            self.tokenizer,
+        response, updated_history = model.chat(
+            tokenizer,
             prompt,
             history=self.history,
             max_length=self.max_token,
             temperature=self.temperature,
-
         )
         print("history: ", self.history)
         if stop is not None: