Update app.py

app.py

@@ -1,98 +1,92 @@
+import numpy as np
 import streamlit as st
 from openai import OpenAI
 import os
-import numpy as np
 from dotenv import load_dotenv
-import openai
 
 # Load environment variables
 load_dotenv()
 
-# Initialize the OpenAI client for OpenAI models
-openai.api_key = os.getenv("OPENAI_API_KEY")
+# Initialize the OpenAI client
+client = OpenAI(
+    base_url="https://api-inference.huggingface.co/v1",
+    api_key=os.environ.get('API_KEY')  # Replace with your token
+)
 
-# Hugging Face API client setup (if needed)
-HF_API_KEY = os.getenv("HF_API_KEY")
-huggingface_url = "https://api-inference.huggingface.co/models/"
-
-# Create supported models dictionary
+# Define model links
 model_links = {
-    "ChatGPT": "openai/gpt-4",
     "Meta-Llama-3.1-70B-Instruct": "meta-llama/Meta-Llama-3.1-70B-Instruct",
-    "Mistral-7B-Instruct-v0.1": "mistralai/Mistral-7B-Instruct-v0.1",
+    "Meta-Llama-3.1-8B-Instruct": "meta-llama/Meta-Llama-3.1-8B-Instruct",
     # Add more models as needed
 }
 
-# Define functions to interact with OpenAI and Hugging Face
-def query_openai(prompt, temperature):
-    """Query OpenAI's GPT model."""
-    response = openai.ChatCompletion.create(
-        model="gpt-4",
-        messages=[{"role": "user", "content": prompt}],
-        temperature=temperature,
-    )
-    return response.choices[0].message['content']
-
-def query_huggingface(prompt, model, temperature):
-    """Query Hugging Face's API."""
-    headers = {"Authorization": f"Bearer {HF_API_KEY}"}
-    payload = {
-        "inputs": prompt,
-        "parameters": {"temperature": temperature, "return_full_text": False},
-    }
-    response = requests.post(f"{huggingface_url}{model}", headers=headers, json=payload)
-    return response.json()[0]['generated_text']
-
 # Function to reset conversation
 def reset_conversation():
+    st.session_state.conversation = []
     st.session_state.messages = []
-    st.session_state.responses = []
-    st.session_state.current_model = None
 
 # Sidebar setup
-st.sidebar.title("ChatBot Configuration")
-selected_model = st.sidebar.selectbox("Select Model", list(model_links.keys()))
-temperature = st.sidebar.slider("Temperature", 0.0, 1.0, 0.5)
-
-# Reset chat button
+models = [key for key in model_links.keys()]
+selected_model = st.sidebar.selectbox("Select Model", models)
+temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, 0.5)
 st.sidebar.button('Reset Chat', on_click=reset_conversation)
 
-# Initialize session state variables
-if 'messages' not in st.session_state:
-    st.session_state.messages = []
-if 'responses' not in st.session_state:
-    st.session_state.responses = []
-if 'current_model' not in st.session_state:
-    st.session_state.current_model = selected_model
+st.sidebar.write(f"You're now chatting with **{selected_model}**")
+st.sidebar.markdown("*Generated content may be inaccurate or false.*")
+st.sidebar.markdown("\n[TypeGPT](https://typegpt.net).")
+
+# Manage session state
+if "prev_option" not in st.session_state:
+    st.session_state.prev_option = selected_model
 
-# Check if the model was changed
-if st.session_state.current_model != selected_model:
+if st.session_state.prev_option != selected_model:
+    st.session_state.messages = []
+    st.session_state.prev_option = selected_model
     reset_conversation()
-    st.session_state.current_model = selected_model
 
-# Chat Interface
-st.title(f"Chat with {selected_model}")
+# Model repository id
+repo_id = model_links[selected_model]
+
+# Main chat interface
+st.subheader(f'TypeGPT.net - {selected_model}')
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
 
-# Display previous chat messages
+# Display chat messages from history on app rerun
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
 # Accept user input
-if prompt := st.chat_input("Ask me anything..."):
+if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
+    with st.chat_message("user"):
+        st.markdown(prompt)
     st.session_state.messages.append({"role": "user", "content": prompt})
 
     with st.chat_message("assistant"):
-        if selected_model == "ChatGPT":
-            response = query_openai(prompt, temperature)
-        else:
-            response = query_huggingface(prompt, model_links[selected_model], temperature)
-        st.markdown(response)
+        try:
+            stream = client.chat.completions.create(
+                model=model_links[selected_model],
+                messages=[
+                    {"role": m["role"], "content": m["content"]}
+                    for m in st.session_state.messages
+                ],
+                temperature=temp_values,
+                stream=True,
+                max_tokens=3000,
+            )
+            response = st.write_stream(stream)
+        except Exception as e:
+            response = "😵‍💫 Looks like something went wrong! Please try again later."
+            st.write(response)
 
-    st.session_state.responses.append(response)
     st.session_state.messages.append({"role": "assistant", "content": response})
 
 
+
+
 # import gradio as gr
 # from huggingface_hub import InferenceClient