Update app.py

app.py

@@ -1,47 +1,55 @@
+from dotenv import load_dotenv
+import os
 import streamlit as st
 from transformers import pipeline
 
-# Initialize the Hugging Face pipeline
-pipe = pipeline("text-generation", model="mistralai/mathstral-7B-v0.1")
-
-# Function to get response from the model
-def get_response(input_text, keywords, blog_style, max_new_tokens=250):
-    # Prompt Template
-    template = """
-    Generate technical project ideas for {blog_style} job profile for a topic {input_text} using these keywords: {keywords}.
-    """
-    
-    prompt = template.format(blog_style=blog_style, input_text=input_text, keywords=keywords)
-    
-    # Generate the response from the model
-    response = pipe(prompt, max_new_tokens=max_new_tokens)
-    return response[0]['generated_text']  # Extract the generated text
-
-# Streamlit configuration
-st.set_page_config(page_title="Generate Project Idea",
-                   page_icon='🤖',
-                   layout='centered',
-                   initial_sidebar_state='collapsed')
-
-st.header("Generate Project Idea 🤖")
-
-input_text = st.text_input("Enter the Topic")
-
-# Creating two more columns for additional fields
-col1, col2 = st.columns([5, 5])
-
-with col1:
-    keywords = st.text_input('Keywords')
-with col2:
-    blog_style = st.selectbox('Generating project idea for',
-                              ('Researchers', 'Data Scientist', 'Software Developer', 'Common People'), index=0)
-    
-
-
-
-submit = st.button("Generate")
-
-# Final response
-if submit:
-    response = get_response(input_text, keywords, blog_style, max_new_tokens)
-    st.write(response)
+# Load environment variables from .env file
+load_dotenv()
+
+# Get the Hugging Face API token from environment variables
+hf_token = os.getenv("textgen")
+
+if not hf_token:
+    st.error("Hugging Face API token is not set. Please set the HUGGINGFACE_HUB_TOKEN environment variable.")
+else:
+    # Initialize the Hugging Face pipeline with authentication
+    pipe = pipeline("text-generation", model="mistralai/mathstral-7B-v0.1", use_auth_token=hf_token)
+
+    # Function to get response from the model
+    def get_response(input_text, keywords, blog_style, max_new_tokens=250):
+        # Prompt Template
+        template = """
+        Generate technical project ideas for {blog_style} job profile for a topic {input_text} using these keywords: {keywords}.
+        """
+        
+        prompt = template.format(blog_style=blog_style, input_text=input_text, keywords=keywords)
+        
+        # Generate the response from the model
+        response = pipe(prompt, max_new_tokens=max_new_tokens)
+        return response[0]['generated_text']  # Extract the generated text
+
+    # Streamlit configuration
+    st.set_page_config(page_title="Generate Project Idea",
+                       page_icon='🤖',
+                       layout='centered',
+                       initial_sidebar_state='collapsed')
+
+    st.header("Generate Project Idea 🤖")
+
+    input_text = st.text_input("Enter the Topic")
+
+    # Creating two more columns for additional fields
+    col1, col2 = st.columns([5, 5])
+
+    with col1:
+        keywords = st.text_input('Keywords')
+    with col2:
+        blog_style = st.selectbox('Generating project idea for',
+                                  ('Researchers', 'Data Scientist', 'Software Developer', 'Common People'), index=0)
+
+    submit = st.button("Generate")
+
+    # Final response
+    if submit:
+        response = get_response(input_text, keywords, blog_style)
+        st.write(response)