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import os
import time
import random
import spaces
import gradio as gr
from transformers import (
ReactCodeAgent,
ReactJsonAgent,
HfApiEngine,
ManagedAgent,
stream_to_gradio,
)
from transformers.agents.search import DuckDuckGoSearchTool
from visit_webpage_tool import VisitWebpageTool # Import the VisitWebpageTool class
from huggingface_hub import login
# Define the model
model = "meta-llama/Meta-Llama-3.1-70B-Instruct"
# Initialize the LLM engine with the Hugging Face token
hf_token = os.getenv("HF_TOKEN")
if not hf_token:
raise ValueError("Hugging Face API token not found. Please set the hf_token environment variable.")
# Authenticate with Hugging Face
login(hf_token)
# Initialize the LLM engine with reduced max_new_tokens
llm_engine = HfApiEngine(model)
# Create the web agent
web_agent = ReactJsonAgent(
tools=[DuckDuckGoSearchTool(), VisitWebpageTool()],
llm_engine=llm_engine,
max_iterations=10,
)
# Wrap the web agent into a ManagedAgent
managed_web_agent = ManagedAgent(
agent=web_agent,
name="search_agent",
description="Runs web searches for you. Give it your query as an argument.",
)
# Create the manager agent
manager_agent = ReactCodeAgent(
tools=[],
llm_engine=llm_engine,
managed_agents=[managed_web_agent],
additional_authorized_imports=["time", "datetime"],
)
# Define a retry mechanism with exponential backoff
def retry_with_backoff(func, retries=5, backoff_factor=2):
for attempt in range(retries):
try:
return func()
except Exception as e:
if attempt < retries - 1:
sleep_time = backoff_factor ** attempt + random.uniform(0, 1)
time.sleep(sleep_time)
else:
raise e
# Define the Gradio interaction function
def interact_with_agent(task):
messages = []
messages.append(gr.ChatMessage(role="user", content=task))
yield messages
for msg in stream_to_gradio(manager_agent, task):
messages.append(msg)
yield messages + [
gr.ChatMessage(role="assistant", content="⏳ Task not finished yet!")
]
yield messages
# Create the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# multi-agent-web-browser")
gr.Markdown("Gradio space based on the multiagent_web_assistant cookbook https://huggingface.co/learn/cookbook/multiagent_web_assistant")
text_input = gr.Textbox(lines=1, label="Chat Message", value="How many years ago was Stripe founded?")
submit = gr.Button("Run web search agent!")
chatbot = gr.Chatbot(
label="Agent",
type="messages",
avatar_images=(
None,
"https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png",
),
)
submit.click(interact_with_agent, [text_input], [chatbot])
if __name__ == "__main__":
demo.launch() |