Update alternative.py

alternative.py

@@ -28,13 +28,14 @@ import subprocess
 from typing import Tuple
 
 import gradio as gr
+from bs4 import BeautifulSoup as Soup
 from dotenv import load_dotenv
-from langchain_community.embeddings import HuggingFaceInferenceAPIEmbeddings
-from langchain_community.llms import HuggingFaceEndpoint
+
 from scrapegraphai.graphs import SmartScraperGraph
 from scrapegraphai.utils import prettify_exec_info
 
-from bs4 import BeautifulSoup as Soup
+from langchain_community.embeddings import HuggingFaceInferenceAPIEmbeddings
+from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
 from langchain_community.document_loaders import (AsyncHtmlLoader,
                                                NewsURLLoader, PubMedLoader,
                                                PlaywrightURLLoader,
@@ -49,12 +50,18 @@ from langchain_community.document_loaders import (AsyncHtmlLoader,
 # ------------------------------------------------------------------------------
 
 # Load environment variables
+load_dotenv()
 HUGGINGFACEHUB_API_TOKEN = os.getenv('HUGGINGFACEHUB_API_TOKEN')
 
+# Foudational Model HF repo ID
+REPO_ID = "mistralai/Mistral-7B-Instruct-v0.3"
+
 # Initialize the model instances
-repo_id = "mistralai/Mistral-7B-Instruct-v0.2"
 llm_model_instance = HuggingFaceEndpoint(
-    repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 8192, "token": HUGGINGFACEHUB_API_TOKEN}
+    repo_id=repo_id, 
+    huggingfacehub_api_token = HUGGINGFACEHUB_API_TOKEN,
+    task = "conversational",
+    **model_kwargs={"temperature": 0.5, "max_length": 8192, "timeout": 6000},
 )
 
 embedder_model_instance = HuggingFaceInferenceAPIEmbeddings(