Update alternative.py

alternative.py

@@ -54,7 +54,7 @@ HUGGINGFACEHUB_API_TOKEN = os.getenv('HUGGINGFACEHUB_API_TOKEN')
 # Initialize the model instances
 repo_id = "mistralai/Mistral-7B-Instruct-v0.2"
 llm_model_instance = HuggingFaceEndpoint(
-    repo_id=repo_id, max_length=8192, temperature=0.5, token=HUGGINGFACEHUB_API_TOKEN
+    repo_id=repo_id, model_kwargs={"temperature": 0.5, "max_length": 8192, "token": HUGGINGFACEHUB_API_TOKEN}
 )
 
 embedder_model_instance = HuggingFaceInferenceAPIEmbeddings(
@@ -150,8 +150,8 @@ choices = [
 ]
 
 # Create the Gradio interface with tabs
-with gr.Blocks() as demo:
-    gr.Markdown("# Web Scraping and Summarization")
+with gr.Blocks(theme="sudeepshouche/minimalist") as demo:
+    gr.Markdown("# THE BIG SCRAPER")
 
     with gr.Tabs():
         # Tab 1: Data Extraction
@@ -171,11 +171,7 @@ with gr.Blocks() as demo:
             )
 
         # Tab 2: Website Scraping and Summarization
-        with gr.TabItem("Website Scraping & Summarization"):
-            gr.Markdown("# Scrape websites, no-code version")
-            gr.Markdown("""Easily scrape and summarize web content using advanced AI models on the Hugging Face Hub without writing any code. Input your desired prompt and source URL to get started.
-                        This is a no-code version of the excellent lib [ScrapeGraphAI](https://github.com/VinciGit00/Scrapegraph-ai).
-                        It's a basic demo and a work in progress. Please contribute to it to make it more useful!""")
+        with gr.TabItem("Scraping & Summarization"):
             with gr.Row():
                 with gr.Column():
                     model_dropdown = gr.Textbox(label="Model", value="Mistral-7B-Instruct-v0.2")