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import functools
from typing import Optional, List, Any, Dict, Tuple
from llama_index.core.agent import ReActAgent
from llama_index.core.llama_pack import BaseLlamaPack
from llama_index.core.llms import LLM
from llama_index.packs.gradio_react_agent_chatbot.base import SUPPORTED_TOOLS, Capturing
class GradioReActAgentPack(BaseLlamaPack):
"""Gradio chatbot to chat with a ReActAgent pack."""
def __init__(
self,
tools_list: Optional[List[str]] = list(SUPPORTED_TOOLS.keys()),
llm: LLM,
**kwargs: Any,
) -> None:
"""Init params."""
try:
from ansi2html import Ansi2HTMLConverter
except ImportError:
raise ImportError("Please install ansi2html via `pip install ansi2html`")
tools = []
for t in tools_list:
try:
tools.append(SUPPORTED_TOOLS[t]())
except KeyError:
raise KeyError(f"Tool {t} is not supported.")
self.tools = tools
self.llm = llm
self.agent = ReActAgent.from_tools(
tools=functools.reduce(
lambda x, y: x.to_tool_list() + y.to_tool_list(), self.tools
),
llm=self.llm,
verbose=True,
)
self.thoughts = ""
self.conv = Ansi2HTMLConverter()
def get_modules(self) -> Dict[str, Any]:
"""Get modules."""
return {"agent": self.agent, "llm": self.llm, "tools": self.tools}
def _handle_user_message(self, user_message, history):
"""Handle the user submitted message. Clear message box, and append
to the history.
"""
return "", [*history, (user_message, "")]
def _generate_response(
self, chat_history: List[Tuple[str, str]]
) -> Tuple[str, List[Tuple[str, str]]]:
"""Generate the response from agent, and capture the stdout of the
ReActAgent's thoughts.
"""
with Capturing() as output:
response = self.agent.stream_chat(chat_history[-1][0])
ansi = "\n========\n".join(output)
html_output = self.conv.convert(ansi)
for token in response.response_gen:
chat_history[-1][1] += token
yield chat_history, str(html_output)
def _reset_chat(self) -> Tuple[str, str]:
"""Reset the agent's chat history. And clear all dialogue boxes."""
# clear agent history
self.agent.reset()
return "", "", "" # clear textboxes
def run(self, *args: Any, **kwargs: Any) -> Any:
"""Run the pipeline."""
import gradio as gr
demo = gr.Blocks(
theme="gstaff/xkcd",
css="#box { height: 420px; overflow-y: scroll !important}",
)
with demo:
gr.Markdown(
"# Gradio ReActAgent Powered by LlamaIndex and LlamaHub 🦙\n"
"This Gradio app is powered by LlamaIndex's `ReActAgent` with\n"
"OpenAI's GPT-4-Turbo as the LLM. The tools are listed below.\n"
"## Tools\n"
"- [ArxivToolSpec](https://llamahub.ai/l/tools-arxiv)\n"
"- [WikipediaToolSpec](https://llamahub.ai/l/tools-wikipedia)"
)
with gr.Row():
chat_window = gr.Chatbot(
label="Message History",
scale=3,
)
console = gr.HTML(elem_id="box")
with gr.Row():
message = gr.Textbox(label="Write A Message", scale=4)
clear = gr.ClearButton()
message.submit(
self._handle_user_message,
[message, chat_window],
[message, chat_window],
queue=False,
).then(
self._generate_response,
chat_window,
[chat_window, console],
)
clear.click(self._reset_chat, None, [message, chat_window, console])
demo.launch(debug=True, share=True, **kwargs)
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