from transformers.agents import ReactCodeAgent, HfApiEngine, DuckDuckGoSearchTool, ManagedAgent

llm_engine = HfApiEngine()

web_agent = ReactCodeAgent(tools=[DuckDuckGoSearchTool()], llm_engine=llm_engine)

managed_web_agent = ManagedAgent(
    agent=web_agent,
    name="web_search",
    description="Runs web searches for you. Give it your query as an argument."
)

manager_agent = ReactCodeAgent(
    tools=[], llm_engine=llm_engine, managed_agents=[managed_web_agent]
)

manager_agent.run("Who is the CEO of Hugging Face?")

from transformers import Tool
from huggingface_hub import list_models

class HFModelDownloadsTool(Tool):
    name = "model_download_counter"
    description = """
    This is a tool that returns the most downloaded model of a given task on the Hugging Face Hub.
    It returns the name of the checkpoint."""

    inputs = {
        "task": {
            "type": "string",
            "description": "the task category (such as text-classification, depth-estimation, etc)",
        }
    }
    output_type = "string"

    def forward(self, task: str):
        model = next(iter(list_models(filter=task, sort="downloads", direction=-1)))
        return model.id

from model_downloads import HFModelDownloadsTool

tool = HFModelDownloadsTool()

tool.push_to_hub("{your_username}/hf-model-downloads")

from transformers import load_tool, CodeAgent

model_download_tool = load_tool("m-ric/hf-model-downloads")

from transformers import Tool
image_generation_tool = Tool.from_space(
    "black-forest-labs/FLUX.1-dev",
    name="image_generator",
    description="Generate an image from a prompt")
image_generation_tool("A sunny beach")

from transformers import ReactCodeAgent

agent = ReactCodeAgent(tools=[image_generation_tool])

agent.run(
    "Improve this prompt, then generate an image of it.", prompt='A rabbit wearing a space suit'
)

=== Agent thoughts:
improved_prompt could be "A bright blue space suit wearing rabbit, on the surface of the moon, under a bright orange sunset, with the Earth visible in the background"
Now that I have improved the prompt, I can use the image generator tool to generate an image based on this prompt.
>>> Agent is executing the code below:
image = image_generator(prompt="A bright blue space suit wearing rabbit, on the surface of the moon, under a bright orange sunset, with the Earth visible in the background")
final_answer(image)

from gradio_tools import StableDiffusionPromptGeneratorTool
from transformers import Tool, load_tool, CodeAgent

gradio_prompt_generator_tool = StableDiffusionPromptGeneratorTool()
prompt_generator_tool = Tool.from_gradio(gradio_prompt_generator_tool)

from langchain.agents import load_tools
from transformers import Tool, ReactCodeAgent

search_tool = Tool.from_langchain(load_tools(["serpapi"])[0])

agent = ReactCodeAgent(tools=[search_tool])

agent.run("How many more blocks (also denoted as layers) are in BERT base encoder compared to the encoder from the architecture proposed in Attention is All You Need?")

import gradio as gr
from transformers import (
    load_tool,
    ReactCodeAgent,
    HfApiEngine,
    stream_to_gradio,
)

# Import tool from Hub
image_generation_tool = load_tool("m-ric/text-to-image")

llm_engine = HfApiEngine("meta-llama/Meta-Llama-3-70B-Instruct")

# Initialize the agent with the image generation tool
agent = ReactCodeAgent(tools=[image_generation_tool], llm_engine=llm_engine)


def interact_with_agent(task):
    messages = []
    messages.append(gr.ChatMessage(role="user", content=task))
    yield messages
    for msg in stream_to_gradio(agent, task):
        messages.append(msg)
        yield messages + [
            gr.ChatMessage(role="assistant", content="⏳ Task not finished yet!")
        ]
    yield messages


with gr.Blocks() as demo:
    text_input = gr.Textbox(lines=1, label="Chat Message", value="Make me a picture of the Statue of Liberty.")
    submit = gr.Button("Run illustrator 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()