app.py

app.py

@@ -1,18 +1,5 @@
 import os
-import subprocess
-
-def install(package):
-    subprocess.check_call([os.sys.executable, "-m", "pip", "install", package])
-
-# Install required packages
-install("transformers==4.41.0")
-install("langchain==0.0.175")
-install("huggingface_hub==0.14.1")
-install("streamlit==1.17.0")
-
-
-from transformers import pipeline
-# from langchain_huggingface import HuggingFaceEndpoint
+from langchain_huggingface import HuggingFaceEndpoint
 import streamlit as st
 from langchain_core.prompts import PromptTemplate
 from langchain_core.output_parsers import StrOutputParser
@@ -31,10 +18,12 @@ def get_llm_hf_inference(model_id=model_id, max_new_tokens=128, temperature=0.1)
     Returns:
     - llm (HuggingFaceEndpoint): The language model for HuggingFace inference.
     """
-    llm = pipeline('text-generation',
-                    model=model_id,
-                      tokenizer=model_id,
-                        use_auth_token=os.getenv("HF_TOKEN"))
+    llm = HuggingFaceEndpoint(
+        repo_id=model_id,
+        max_new_tokens=max_new_tokens,
+        temperature=temperature,
+        token = os.getenv("HF_TOKEN")
+    )
     return llm
 
 # Configure the Streamlit app