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import gradio as gr
import os
from rag_langgraph import run_multi_agent
os.environ["LANGCHAIN_TRACING_V2"] = "true"
os.environ["LANGCHAIN_PROJECT"] = "langgraph-multi-agent"
def invoke(openai_api_key, topic, word_count=1000):
if (openai_api_key == ""):
raise gr.Error("OpenAI API Key is required.")
if (topic == ""):
raise gr.Error("Topic is required.")
os.environ["OPENAI_API_KEY"] = openai_api_key
return run_multi_agent(topic, word_count)
gr.close_all()
demo = gr.Interface(fn = invoke,
inputs = [gr.Textbox(label = "OpenAI API Key", type = "password", lines = 1),
gr.Textbox(label = "Topic", value=os.environ["TOPIC"], lines = 1),
gr.Number(label = "Word Count", value=1000, minimum=500, maximum=5000)],
outputs = [gr.Textbox(label = "Generated Blog Post", value=os.environ["OUTPUT"])],
title = "Multi-Agent RAG: Blog Post Generation",
description = os.environ["DESCRIPTION"])
demo.launch() |