Update app.py

app.py

@@ -2,11 +2,10 @@ import numpy as np
 import streamlit as st
 from openai import OpenAI
 import os
-import sys
-from dotenv import load_dotenv, dotenv_values
+from dotenv import load_dotenv
 load_dotenv()
 
-# initialize the client
+# Initialize the OpenAI client
 client = OpenAI(
   base_url="https://api-inference.huggingface.co/v1",
   api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')  # Replace with your token
@@ -20,42 +19,33 @@ model_links = {
 # Pull info about the model to display
 model_info = {
     "Meta-Llama-3-8B": {
-        'description': """The Llama (3) model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n
-        \nIt was created by the [**Meta's AI**](https://llama.meta.com/) team and has over **8 billion parameters.** \n""",
-        'logo': 'Llama_logo.png'
+        'description': """The Llama (3) model is a **Large Language Model (LLM)** designed to assist with question and answer interactions.\n
+        \nThis model was created by Meta's AI team and has over 8 billion parameters.\n
+        **Training**: The model was fine-tuned on science textbooks from the NCERT curriculum using Docker AutoTrain to ensure it can provide relevant and accurate responses in the education domain.\n
+        **Purpose**: This version of Llama has been trained specifically for educational purposes, focusing on answering science-related queries in a clear and simple manner to help students and teachers alike.\n"""
     }
 }
 
-# Random dog images for error message
-random_dog = ["0f476473-2d8b-415e-b944-483768418a95.jpg", "1bd75c81-f1d7-4e55-9310-a27595fa8762.jpg"]
-
+# Reset the conversation
 def reset_conversation():
-    '''Resets Conversation'''
     st.session_state.conversation = []
     st.session_state.messages = []
     return None
 
-# Define the available models
-models = [key for key in model_links.keys()]
-
-# Create the sidebar with the dropdown for model selection
-selected_model = st.sidebar.selectbox("Select Model", models)
-
-# Custom description for SciMom
-st.sidebar.write("Built for my mom, with love. This model is pretrained with textbooks of Science NCERT.")
-st.sidebar.write("Model used: Meta Llama, trained using: Docker AutoTrain.")
+# App title and description
+st.title("Sci-Mom 👩‍🏫 ")
+st.subheader("AI chatbot for Solving your doubts 📚 :)")
 
-# Create a temperature slider
-temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5))
+# Custom description for SciMom in the sidebar
+st.sidebar.write("Built for my mom, with love ❤️. This model is pretrained with textbooks of Science NCERT.")
+st.sidebar.write("Base-Model used: Meta Llama, trained using: Docker AutoTrain.")
 
-# Add reset button to clear conversation
-st.sidebar.button('Reset Chat', on_click=reset_conversation)
+# Add technical details in the sidebar
+st.sidebar.markdown(model_info["Meta-Llama-3-8B"]['description'])
+st.sidebar.markdown("*By Gokulnath ♔ *")
 
-# Create model description
-st.sidebar.write(f"You're now chatting with **{selected_model}**")
-st.sidebar.markdown(model_info[selected_model]['description'])
-st.sidebar.image(model_info[selected_model]['logo'])
-st.sidebar.markdown("*Generated content may be inaccurate or false.*")
+# If model selection was needed (now removed)
+selected_model = "Meta-Llama-3-8B"  # Only one model remains
 
 if "prev_option" not in st.session_state:
     st.session_state.prev_option = selected_model
@@ -68,12 +58,6 @@ if st.session_state.prev_option != selected_model:
 # Pull in the model we want to use
 repo_id = model_links[selected_model]
 
-st.subheader(f'AI - {selected_model}')
-
-# Set a default model
-if selected_model not in st.session_state:
-    st.session_state[selected_model] = model_links[selected_model]
-
 # Initialize chat history
 if "messages" not in st.session_state:
     st.session_state.messages = []
@@ -84,7 +68,7 @@ for message in st.session_state.messages:
         st.markdown(message["content"])
 
 # Accept user input
-if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
+if prompt := st.chat_input("Ask Scimom!"):
     # Display user message in chat message container
     with st.chat_message("user"):
         st.markdown(prompt)
@@ -99,17 +83,15 @@ if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
                     {"role": m["role"], "content": m["content"]}
                     for m in st.session_state.messages
                 ],
-                temperature=temp_values,
+                temperature=0.5,  # Default temperature setting
                 stream=True,
                 max_tokens=3000,
             )
             response = st.write_stream(stream)
 
         except Exception as e:
-            response = "😵‍💫 Looks like something went wrong! Here's a random pic of a 🐶:"
+            response = "😵‍💫 Something went wrong. Please try again later."
             st.write(response)
-            random_dog_pick = 'https://random.dog/' + random_dog[np.random.randint(len(random_dog))]
-            st.image(random_dog_pick)
             st.write("This was the error message:")
             st.write(e)