fix: add gradio ui react

Gradio_UI_React.py

@@ -0,0 +1,114 @@
+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)