| import os |
| import uuid |
|
|
| import gradio as gr |
| from agent import construct_agent, initialize_agent_llm, initialize_instrumentor |
| from dotenv import load_dotenv |
| from langchain_core.messages import HumanMessage, SystemMessage |
| from openinference.instrumentation import using_session |
| from opentelemetry.trace import Status, StatusCode |
| from rag import initialize_vector_store |
|
|
| load_dotenv() |
|
|
| SYSTEM_MESSAGE_FOR_AGENT_WORKFLOW = """ |
| You are a Retrieval-Augmented Generation (RAG) assistant designed to provide responses by leveraging provided tools |
| Your goal is to ensure the user's query is addressed with quality. If further clarification is required, |
| you can request additional input from the user. |
| """ |
|
|
|
|
| def initialize_agent(phoenix_key, project_name, openai_key, user_session_id, vector_source_web_url): |
| from tools import initialize_tool_llm |
|
|
| os.environ["PHOENIX_API_KEY"] = phoenix_key |
| os.environ["OPENAI_API_KEY"] = openai_key |
| os.environ["PHOENIX_COLLECTOR_ENDPOINT"] = "https://app.phoenix.arize.com/v1/traces" |
| agent_tracer = initialize_instrumentor(project_name) |
| initialize_agent_llm("gpt-4o-mini") |
| tool_model = initialize_tool_llm("gpt-4o-mini") |
| initialize_vector_store(vector_source_web_url) |
| copilot_agent = construct_agent() |
| return ( |
| copilot_agent, |
| agent_tracer, |
| tool_model, |
| user_session_id, |
| (f"Configuration Set: Project " f"'{project_name}' is Ready!"), |
| ) |
|
|
|
|
| def chat_with_agent( |
| copilot_agent, |
| agent_tracer, |
| tool_model, |
| user_input_message, |
| user_session_id, |
| user_chat_history, |
| conversation_history, |
| ): |
| if not agent: |
| return "Error: RAG Agent is not initialized. Please set API keys first." |
| if not conversation_history: |
| messages = [SystemMessage(content=SYSTEM_MESSAGE_FOR_AGENT_WORKFLOW)] |
| else: |
| messages = conversation_history["messages"] |
| messages.append(HumanMessage(content=user_input_message)) |
| with using_session(session_id=user_session_id): |
| with agent_tracer.start_as_current_span( |
| f"agent-{user_session_id}", |
| openinference_span_kind="chain", |
| ) as span: |
| span.set_input(user_input_message) |
| conversation_history = copilot_agent.invoke( |
| {"messages": messages}, |
| config={ |
| "configurable": { |
| "thread_id": user_session_id, |
| "user_session_id": user_session_id, |
| "tool_model": tool_model, |
| } |
| }, |
| ) |
| span.set_output(conversation_history["messages"][-1].content) |
| span.set_status(Status(StatusCode.OK)) |
|
|
| user_chat_history.append( |
| (user_input_message, conversation_history["messages"][-1].content) |
| ) |
| return ( |
| copilot_agent, |
| "", |
| user_chat_history, |
| user_session_id, |
| user_chat_history, |
| conversation_history, |
| ) |
|
|
|
|
| with gr.Blocks() as demo: |
| agent = gr.State(None) |
| tracer = gr.State(None) |
| openai_tool_model = gr.State(None) |
| history = gr.State({}) |
| session_id = gr.State(str(uuid.uuid4())) |
| chat_history = gr.State([]) |
| gr.Markdown("## Chat with RAG Agent 🔥") |
|
|
| with gr.Row(): |
| with gr.Column(scale=1, min_width=250): |
| gr.Markdown("### Configuration Panel ⚙️") |
|
|
| phoenix_input = gr.Textbox(label="Phoenix API Key", type="password") |
| project_input = gr.Textbox(label="Project Name", value="Agentic Rag") |
| openai_input = gr.Textbox(label="OpenAI API Key", type="password") |
| web_url = gr.Textbox( |
| label="Vector Source Web URL", |
| value="https://lilianweng.github.io/posts/2023-06-23-agent/", |
| ) |
| set_button = gr.Button("Set API Keys & Initialize") |
| output_message = gr.Textbox(label="Status", interactive=False) |
|
|
| set_button.click( |
| fn=initialize_agent, |
| inputs=[phoenix_input, project_input, openai_input, session_id, web_url], |
| outputs=[agent, tracer, openai_tool_model, session_id, output_message], |
| ) |
|
|
| with gr.Column(scale=4): |
| gr.Markdown("### Chat with RAG Agent 💬") |
|
|
| chat_display = gr.Chatbot(label="Chat History", height=400) |
|
|
| user_input = gr.Textbox(label="Your Message", placeholder="Type your message here...") |
| submit_button = gr.Button("Send") |
|
|
| submit_button.click( |
| fn=chat_with_agent, |
| inputs=[ |
| agent, |
| tracer, |
| openai_tool_model, |
| user_input, |
| session_id, |
| chat_display, |
| history, |
| ], |
| outputs=[agent, user_input, chat_display, session_id, chat_history, history], |
| ) |
|
|
| if __name__ == "__main__": |
| port = int(os.environ.get("PORT", 10000)) |
| demo.launch(share=True,server_name="0.0.0.0", server_port=port) |
|
|
