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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"π οΈ 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": "π₯ 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) |