Create wrapper.py

wrapper.py

@@ -0,0 +1,29 @@
+from langchain_community.llms.ctransformers import CTransformers
+import os
+
+MODEL_TYPE = 'mistral'
+MODEL_BIN_PATH = "mistral-7b-instruct-v0.1.Q3_K_S.gguf"
+MAX_NEW_TOKEN =  600
+TEMPRATURE =  0.01
+CONTEXT_LENGTH =  6000
+
+
+
+
+
+
+class LLMWrapper:
+    def __init__(self):
+        self.llm = CTransformers(
+            model=MODEL_BIN_PATH,
+            config={
+                'max_new_tokens': MAX_NEW_TOKEN,
+                'temperature': TEMPRATURE,
+                'context_length': CONTEXT_LENGTH
+            },
+            model_type=MODEL_TYPE
+        )
+
+    def generate_text(self, prompt):
+        return self.llm(prompt)
+