gradio/demo/agent_chatbot/utils.py
Freddy Boulton 5e36144232
Add guides for msg format and llm agents (#8750)
* Add guides

* add changeset

* Add code

* Add code

* Add notebook

* rename msg_format to type

* Fix docs

* notebooks

* missing link

* Update guides

---------

Co-authored-by: gradio-pr-bot <gradio-pr-bot@users.noreply.github.com>
Co-authored-by: Abubakar Abid <abubakar@huggingface.co>
2024-07-12 11:53:28 +00:00

64 lines
2.2 KiB
Python

from gradio import ChatMessage
from transformers.agents import ReactCodeAgent, agent_types
from typing import Generator
def pull_message(step_log: dict):
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_from_transformers_agent(
agent: ReactCodeAgent, prompt: str
) -> Generator[ChatMessage, None, ChatMessage | None]:
"""Runs an agent with the given prompt and streams the messages from the agent as ChatMessages."""
class Output:
output: agent_types.AgentType | str = None
for step_log in agent.run(prompt, stream=True):
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, agent_types.AgentText):
yield ChatMessage(
role="assistant", content=f"**Final answer:**\n```\n{Output.output.to_string()}\n```")
elif isinstance(Output.output, agent_types.AgentImage):
yield ChatMessage(
role="assistant",
content={"path": Output.output.to_string(), "mime_type": "image/png"},
)
elif isinstance(Output.output, agent_types.AgentAudio):
yield ChatMessage(
role="assistant",
content={"path": Output.output.to_string(), "mime_type": "audio/wav"},
)
else:
return ChatMessage(role="assistant", content=Output.output)