Update app.py

app.py

@@ -1,172 +1,15 @@
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+import gradio as gr
+import groq_gradio
 import os
-from dotenv import find_dotenv, load_dotenv
-import streamlit as st
-from typing import Generator
-from groq import Groq
-
-_ = load_dotenv(find_dotenv())
-st.set_page_config(page_icon="📃", layout="wide", page_title="Groq & LLaMA3.1 Chat Bot...")
-
-
-def icon(emoji: str):
-    """Shows an emoji as a Notion-style page icon."""
-    st.write(
-        f'<span style="font-size: 78px; line-height: 1">{emoji}</span>',
-        unsafe_allow_html=True,
-    )
-
-
-# icon("⚡️")
-
-st.subheader("Groq Chat with LLaMA3.1 App", divider="rainbow", anchor=False)
-
-client = Groq(
-    api_key=os.environ['GROQ_API_KEY'],
-)
-
-# Initialize chat history and selected model
-if "messages" not in st.session_state:
-    st.session_state.messages = []
-
-if "selected_model" not in st.session_state:
-    st.session_state.selected_model = None
-
-# Define model details
-models = {
-    "llama-3.1-70b-versatile": {"name": "LLaMA3.1-70b", "tokens": 4096, "developer": "Meta"},
-    "llama-3.1-8b-instant": {"name": "LLaMA3.1-8b", "tokens": 4096, "developer": "Meta"},
-    "llama3-70b-8192": {"name": "Meta Llama 3 70B", "tokens": 4096, "developer": "Meta"},
-    "llama3-8b-8192": {"name": "Meta Llama 3 8B", "tokens": 4096, "developer": "Meta"},
-    "llama3-groq-70b-8192-tool-use-preview": {"name": "Llama 3 Groq 70B Tool Use (Preview)", "tokens": 4096, "developer": "Groq"},
-    "gemma-7b-it": {"name": "Gemma-7b-it", "tokens": 4096, "developer": "Google"},
-    "mixtral-8x7b-32768": {
-        "name": "Mixtral-8x7b-Instruct-v0.1",
-        "tokens": 32768,
-        "developer": "Mistral",
-    },
-}
-
-# Layout for model selection and max_tokens slider
-col1, col2 = st.columns([1, 3])  # Adjust the ratio to make the first column smaller
-
-
-with col1:
-    model_option = st.selectbox(
-        "Choose a model:",
-        options=list(models.keys()),
-        format_func=lambda x: models[x]["name"],
-        index=0,  # Default to the first model in the list
-    )
-    max_tokens_range = models[model_option]["tokens"]
-    max_tokens = st.slider(
-        "Max Tokens:",
-        min_value=512,
-        max_value=max_tokens_range,
-        value=min(32768, max_tokens_range),
-        step=512,
-        help=f"Adjust the maximum number of tokens (words) for the model's response. Max for selected model: {max_tokens_range}",
-    )
-
-# Detect model change and clear chat history if model has changed
-if st.session_state.selected_model != model_option:
-    st.session_state.messages = []
-    st.session_state.selected_model = model_option
-
-# Add a "Clear Chat" button
-if st.button("Clear Chat"):
-    st.session_state.messages = []
-    
-# Display chat messages from history on app rerun
-for message in st.session_state.messages:
-    avatar = "🔋" if message["role"] == "assistant" else "🧑‍💻"
-    with st.chat_message(message["role"], avatar=avatar):
-        st.markdown(message["content"])
-
-
-def generate_chat_responses(chat_completion) -> Generator[str, None, None]:
-    """Yield chat response content from the Groq API response."""
-    for chunk in chat_completion:
-        if chunk.choices[0].delta.content:
-            yield chunk.choices[0].delta.content
-
-
-if prompt := st.chat_input("Enter your prompt here..."):
-    st.session_state.messages.append({"role": "user", "content": prompt})
-
-    with st.chat_message("user", avatar="🧑‍💻"):  
-        st.markdown(prompt)
-
-    # Fetch response from Groq API
-    try:
-        chat_completion = client.chat.completions.create(
-            model=model_option,
-            messages=[
-                {"role": m["role"], "content": m["content"]}
-                for m in st.session_state.messages
-            ],
-            max_tokens=max_tokens,
-            stream=True,
-        )
-
-        # Use the generator function with st.write_stream
-        with st.chat_message("assistant", avatar="🔋"):
-            chat_responses_generator = generate_chat_responses(chat_completion)
-            full_response = st.write_stream(chat_responses_generator)
-    except Exception as e:
-        st.error(e, icon="❌")
 
-    # Append the full response to session_state.messages
-    if isinstance(full_response, str):
-        st.session_state.messages.append(
-            {"role": "assistant", "content": full_response}
-        )
-    else:
-        # Handle the case where full_response is not a string
-        combined_response = "\n".join(str(item) for item in full_response)
-        st.session_state.messages.append(
-            {"role": "assistant", "content": combined_response}
-        )
+os.environ["GROQ_API_KEY"] = "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"
+gr.load(
+    name = "llama-3.2-3b-preview",
+    src = groq_gradio.registry,
+    title = "Groq-Gradio Chat",
+    theme =  "upsatwal/mlsc_tiet",
+    examples = ["Tell me a short story about a puppy",
+                "Write a 14 line poem about travelling in Shakespeare style",
+                "What are the wonders of the world?",
+                "List the countries in Africa and their capitals"]
+).launch()