Update app.py

app.py

@@ -2,46 +2,43 @@
 #Once you have Streamlit installed, you can import it into your Python script using the import statement,
 
 import streamlit as st
+from langchain import HuggingFaceHub  # Correct import for Hugging Face
 
-from langchain_openai import OpenAI
-from langchain_huggingface import HuggingFaceEndpoint
+# Set your Hugging Face API token
+HUGGINGFACE_API_TOKEN = "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"
 
-
-
-#import os
-
-#os.environ["HUGGINGFACEHUB_API_TOKEN"] = "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"
-
-#Function to return the response
+# Function to return the response from Hugging Face model
 def load_answer(question):
-    llm = OpenAI(model_name="gpt-3.5-turbo-instruct",temperature=0)
-   # llm = HuggingFaceEndpoint(
-    #repo_id="mistralai/Mistral-7B-Instruct-v0.3") # Model link : https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.3
-
-    answer=llm.invoke(question)
+    # Initialize the Hugging Face model
+    llm = HuggingFaceHub(
+        repo_id="mistralai/Mistral-7B-Instruct-v0.3",  # Specify the Hugging Face model
+        huggingfacehub_api_token=HUGGINGFACE_API_TOKEN,  # Pass your API token
+        model_kwargs={"temperature": 0}  # Optional: Control response randomness
+    )
+    
+    # Call the model with the user's question and get the response
+    answer = llm(question)
     return answer
 
-
-#App UI starts here
+# Streamlit App UI starts here
 st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
 st.header("LangChain Demo")
 
-#Gets the user input
+# Function to get user input
 def get_text():
     input_text = st.text_input("You: ", key="input")
     return input_text
 
+# Get user input
+user_input = get_text()
 
-user_input=get_text()
-if user_input!= "":
-    response = load_answer(user_input)
-
-submit = st.button('Generate')  
-
-#If generate button is clicked
-if submit:
+# Create a button for generating the response
+submit = st.button('Generate')
 
+# If generate button is clicked and user input is not empty
+if submit and user_input:
+    response = load_answer(user_input)
     st.subheader("Answer:")
-
     st.write(response)
-
+elif submit:
+    st.warning("Please enter a question.")  # Warning for empty input