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import os, asyncio
import gradio as gr
from dotenv import load_dotenv
from nemoguardrails import LLMRails, RailsConfig
from chain import initialize_llm, rag_chain
from ui import chat, demo_header_settings, custom_css, chat_examples
load_dotenv()
os.environ["TOKENIZERS_PARALLELISM"] = "false"
MODEL_LIST = {
"openai": "gpt-4o-mini",
"groq": "llama-3.2-11b-text-preview",
"gemini": "gemini-1.5-pro-002",
}
def init_app(api_key, provider):
try:
loop = asyncio.get_event_loop()
except RuntimeError:
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
try:
llm = initialize_llm(api_key, provider, MODEL_LIST[provider])
config = RailsConfig.from_path("nemo")
app = LLMRails(config=config, llm=llm)
gr.Info(f"Chat initialized with {provider}")
return app, llm
except Exception as e:
gr.Error(f"Error initializing the app: {e}")
return None, None
# Prediction function to generate responses
def predict(message, history, app, llm, is_guardrails=True):
if not app or not llm:
return "Chatbot not initialized. Please start chat first."
if is_guardrails:
history.append({"role": "user", "content": message})
options = {"output_vars": ["triggered_input_rail", "triggered_output_rail"]}
output = app.generate(messages=history, options=options)
info = app.explain()
info.print_llm_calls_summary()
warning_message = output.output_data["triggered_input_rail"] or output.output_data["triggered_output_rail"]
if warning_message:
gr.Warning(f"Guardrail triggered: {warning_message}")
return output.response[0]['content']
else:
return rag_chain(llm, message)
def respond(message, chat_history, app, llm, guardrail_enabled):
bot_message = predict(message, chat_history, app, llm, guardrail_enabled)
chat_history.append({"role": "assistant", "content": bot_message})
return "", chat_history
# Gradio UI setup
with gr.Blocks(css=custom_css) as demo:
app_state = gr.State(None)
llm_state = gr.State(None)
model_key, provider, guardrail, start_chat = demo_header_settings(MODEL_LIST)
start_chat.click(
init_app,
[model_key, provider],
[app_state, llm_state]
)
chatbot = chat()
msg = gr.Textbox(placeholder="Type your message here...", type="text", show_label=False, submit_btn=True)
examples = gr.Examples(chat_examples, msg)
msg.submit(
respond,
[msg, chatbot, app_state, llm_state, guardrail],
[msg, chatbot]
)
# Launch the application
if __name__ == "__main__":
demo.launch()
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