Spaces:
Sleeping
Sleeping
import os | |
import streamlit as st | |
from typing import Generator | |
from groq import Groq | |
from dotenv import load_dotenv | |
import yaml | |
# Load environment variables from .env file | |
load_dotenv() | |
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 | |
def load_config(): | |
"""Load and validate the configuration from config.yaml""" | |
try: | |
with open("config.yaml", "r") as f: | |
config = yaml.safe_load(f) | |
if "models" not in config: | |
st.error("The 'models' section is missing from the config file.") | |
st.stop() | |
if "default_max_tokens" not in config: | |
st.warning("'default_max_tokens' is not specified in the config. Using 1024 as default.") | |
config["default_max_tokens"] = 1024 | |
if "prompt_templates" not in config: | |
st.warning("No prompt templates found in the config.") | |
config["prompt_templates"] = {} | |
return config | |
except FileNotFoundError: | |
st.error("config.yaml file not found. Please ensure it exists in the same directory as this script.") | |
st.stop() | |
except yaml.YAMLError as e: | |
st.error(f"Error reading config.yaml: {e}") | |
st.stop() | |
# Set up the Streamlit page | |
st.set_page_config(page_icon="π¬", layout="wide", page_title="Llama 3.3 Chat App") | |
# Load configuration | |
config = load_config() | |
# Load Groq API key from environment variable | |
GROQ_API_KEY = os.getenv("GROQ_API_KEY") | |
if not GROQ_API_KEY: | |
st.error("GROQ_API_KEY environment variable not found. Please set it in the .env file.") | |
st.stop() | |
client = Groq(api_key=GROQ_API_KEY) | |
# Initialize chat history | |
if "messages" not in st.session_state: | |
st.session_state.messages = [] | |
# Define model details | |
model_option = "llama-3.3-70b-versatile" | |
if model_option not in config["models"]: | |
st.error(f"The model '{model_option}' is not defined in the config file.") | |
st.stop() | |
model_info = config["models"][model_option] | |
# Display model information | |
st.sidebar.header("Model Information") | |
st.sidebar.markdown(f"**Name:** {model_info.get('name', 'N/A')}") | |
st.sidebar.markdown(f"**Developer:** {model_info.get('developer', 'N/A')}") | |
st.sidebar.markdown(f"**Description:** {model_info.get('description', 'N/A')}") | |
max_tokens_range = model_info.get("tokens", 1024) # Default to 1024 if not specified | |
# Adjust max_tokens slider | |
max_tokens = st.sidebar.slider( | |
"Max Tokens:", | |
min_value=512, | |
max_value=max_tokens_range, | |
value=min(config["default_max_tokens"], 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}" | |
) | |
# Display chat messages from history on app rerun | |
for message in st.session_state.messages: | |
avatar = 'π€' if message["role"] == "assistant" else 'π¨βπ»' | |
with st.chat_message(message["role"], avatar=avatar): | |
st.markdown(message["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='π¨βπ»'): | |
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="π€"): | |
chat_responses_generator = generate_chat_responses(chat_completion) | |
full_response = st.write_stream(chat_responses_generator) | |
except Exception as e: | |
st.error(f"Error: {e}", icon="π¨") | |
else: | |
# 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}) | |
# Add a clear chat button | |
if st.sidebar.button("Clear Chat"): | |
st.session_state.messages = [] | |
# Add a download chat history button | |
if st.sidebar.button("Download Chat History"): | |
chat_history = "\n".join([f"{m['role'].capitalize()}: {m['content']}" for m in st.session_state.messages]) | |
st.download_button( | |
label="Download Chat History", | |
data=chat_history, | |
file_name="chat_history.txt", | |
mime="text/plain", | |
) | |
# Add a prompt templates section | |
st.sidebar.header("Prompt Templates") | |
template_options = list(config["prompt_templates"].keys()) | |
if template_options: | |
selected_template = st.sidebar.selectbox("Choose a prompt template", options=template_options) | |
if st.sidebar.button("Load Template"): | |
prompt_template = config["prompt_templates"][selected_template] | |
st.session_state.messages.append({"role": "user", "content": prompt_template}) | |
st.experimental_rerun() | |
else: | |
st.sidebar.info("No prompt templates available.") |