update chatglm_llm.py

chatglm_llm.py

@@ -3,7 +3,17 @@ 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"""
+tokenizer = AutoTokenizer.from_pretrained(
+    "THUDM/chatglm-6b",
+    trust_remote_code=True
+)
+model = (
+    AutoModel.from_pretrained(
+        "THUDM/chatglm-6b",
+        trust_remote_code=True)
+    .half()
+    .cuda()
+)
 
 
 class ChatGLM(LLM):
@@ -11,18 +21,6 @@ class ChatGLM(LLM):
     temperature: float = 0.1
     top_p = 0.9
     history = []
-    tokenizer = AutoTokenizer.from_pretrained(
-        "THUDM/chatglm-6b",
-        trust_remote_code=True
-    )
-    model = (
-        AutoModel.from_pretrained(
-            "THUDM/chatglm-6b",
-            trust_remote_code=True)
-        .half()
-        .cuda()
-    )
-
 
     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: