from transformers.agents.agent_types import AgentAudio, AgentImage, AgentText, AgentType from transformers.agents import ReactAgent def pull_message(step_log: dict): try: from gradio import ChatMessage except ImportError: raise ImportError("Gradio should be installed in order to launch a gradio demo.") if step_log.get("rationale"): yield ChatMessage(role="assistant", content=step_log["rationale"]) if step_log.get("tool_call"): used_code = step_log["tool_call"]["tool_name"] == "code interpreter" content = step_log["tool_call"]["tool_arguments"] if used_code: content = f"```py\n{content}\n```" yield ChatMessage( role="assistant", metadata={"title": f"🛠️ Used tool {step_log['tool_call']['tool_name']}"}, content=content, ) if step_log.get("observation"): yield ChatMessage(role="assistant", content=f"```\n{step_log['observation']}\n```") if step_log.get("error"): yield ChatMessage( role="assistant", content=str(step_log["error"]), metadata={"title": "💥 Error"}, ) def stream_to_gradio(agent: ReactAgent, task: str, **kwargs): """Runs an agent with the given task and streams the messages from the agent as gradio ChatMessages.""" try: from gradio import ChatMessage except ImportError: raise ImportError("Gradio should be installed in order to launch a gradio demo.") class Output: output: AgentType | str = None for step_log in agent.run(task, stream=True, **kwargs): if isinstance(step_log, dict): for message in pull_message(step_log): print("message", message) yield message Output.output = step_log if isinstance(Output.output, AgentText): yield ChatMessage(role="assistant", content=f"**Final answer:**\n```\n{Output.output.to_string()}\n```") elif isinstance(Output.output, AgentImage): yield ChatMessage( role="assistant", content={"path": Output.output.to_string(), "mime_type": "image/png"}, ) elif isinstance(Output.output, AgentAudio): yield ChatMessage( role="assistant", content={"path": Output.output.to_string(), "mime_type": "audio/wav"}, ) else: yield ChatMessage(role="assistant", content=Output.output)