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import asyncio
import chainlit as cl
from metagpt.environment import Environment
from metagpt.logs import logger, set_llm_stream_logfunc
from metagpt.roles import Role
from metagpt.utils.common import any_to_name
def log_llm_stream_chainlit(msg):
# Stream the message token into Chainlit UI.
cl.run_sync(chainlit_message.stream_token(msg))
set_llm_stream_logfunc(func=log_llm_stream_chainlit)
class ChainlitEnv(Environment):
"""Chainlit Environment for UI Integration"""
async def run(self, k=1):
"""处理一次所有信息的运行
Process all Role runs at once
"""
for _ in range(k):
futures = []
for role in self.roles.values():
# Call role.run with chainlit configuration
future = self._chainlit_role_run(role=role)
futures.append(future)
await asyncio.gather(*futures)
logger.debug(f"is idle: {self.is_idle}")
async def _chainlit_role_run(self, role: Role) -> None:
"""To run the role with chainlit config
Args:
role (Role): metagpt.role.Role
"""
global chainlit_message
chainlit_message = cl.Message(content="")
message = await role.run()
# If message is from role._act() publish to UI.
if message is not None and message.content != "No actions taken yet":
# Convert a message from action node in json format
chainlit_message.content = await self._convert_message_to_markdownjson(message=chainlit_message.content)
# message content from which role and its action...
chainlit_message.content += f"---\n\nAction: `{any_to_name(message.cause_by)}` done by `{role._setting}`."
await chainlit_message.send()
# for clean view in UI
async def _convert_message_to_markdownjson(self, message: str) -> str:
"""If the message is from MetaGPT Action Node output, then
convert it into markdown json for clear view in UI.
Args:
message (str): message by role._act
Returns:
str: message in mardown from
"""
if message.startswith("[CONTENT]"):
return f"```json\n{message}\n```\n"
return message
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