Langchain-Chatchat/libs/chatchat-server/chatchat/server/callback_handler/agent_callback_handler.py

216 lines
6.1 KiB
Python

from __future__ import annotations
import asyncio
import json
from typing import Any, Dict, List, Optional
from uuid import UUID
from langchain.callbacks import AsyncIteratorCallbackHandler
from langchain.schema import AgentAction, AgentFinish
from langchain_core.outputs import LLMResult
from chatchat.utils import build_logger
logger = build_logger()
def dumps(obj: Dict) -> str:
return json.dumps(obj, ensure_ascii=False)
class AgentStatus:
llm_start: int = 1
llm_new_token: int = 2
llm_end: int = 3
agent_action: int = 4
agent_finish: int = 5
tool_start: int = 6
tool_end: int = 7
error: int = 8
class AgentExecutorAsyncIteratorCallbackHandler(AsyncIteratorCallbackHandler):
def __init__(self):
super().__init__()
self.queue = asyncio.Queue()
self.done = asyncio.Event()
self.out = True
logger.info(f"init....")
async def on_llm_start(
self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
) -> None:
data = {
"status": AgentStatus.llm_start,
"text": "",
}
self.done.clear()
self.queue.put_nowait(dumps(data))
logger.info(f"prompts:{prompts}")
async def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
special_tokens = ["\nAction:", "\nObservation:", "<|observation|>"]
for stoken in special_tokens:
if stoken in token:
before_action = token.split(stoken)[0]
data = {
"status": AgentStatus.llm_new_token,
"text": before_action + "\n",
}
self.queue.put_nowait(dumps(data))
self.out = False
break
if token is not None and token != "" and self.out:
data = {
"status": AgentStatus.llm_new_token,
"text": token,
}
self.queue.put_nowait(dumps(data))
async def on_chat_model_start(
self,
serialized: Dict[str, Any],
messages: List[List],
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
metadata: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> None:
data = {
"status": AgentStatus.llm_start,
"text": "",
}
self.done.clear()
self.queue.put_nowait(dumps(data))
logger.info(f"messages:{messages}")
async def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
data = {
"status": AgentStatus.llm_end,
"text": response.generations[0][0].message.content,
}
self.queue.put_nowait(dumps(data))
logger.info(f"response:{response.json}")
async def on_llm_error(
self, error: Exception | KeyboardInterrupt, **kwargs: Any
) -> None:
data = {
"status": AgentStatus.error,
"text": str(error),
}
self.queue.put_nowait(dumps(data))
async def on_tool_start(
self,
serialized: Dict[str, Any],
input_str: str,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
metadata: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> None:
data = {
"run_id": str(run_id),
"status": AgentStatus.tool_start,
"tool": serialized["name"],
"tool_input": input_str,
}
self.queue.put_nowait(dumps(data))
logger.info(f"input_str:{input_str}")
async def on_tool_end(
self,
output: str,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
**kwargs: Any,
) -> None:
"""Run when tool ends running."""
data = {
"run_id": str(run_id),
"status": AgentStatus.tool_end,
"tool_output": output,
}
# self.done.clear()
self.queue.put_nowait(dumps(data))
logger.info(f"output:{output}")
async def on_tool_error(
self,
error: BaseException,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
**kwargs: Any,
) -> None:
"""Run when tool errors."""
data = {
"run_id": str(run_id),
"status": AgentStatus.tool_end,
"tool_output": str(error),
"is_error": True,
}
# self.done.clear()
self.queue.put_nowait(dumps(data))
logger.error(f"error:{error.__class__}")
async def on_agent_action(
self,
action: AgentAction,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
**kwargs: Any,
) -> None:
data = {
"status": AgentStatus.agent_action,
"tool_name": action.tool,
"tool_input": action.tool_input,
"text": action.log,
}
self.queue.put_nowait(dumps(data))
logger.error(f"tool_name:{action.tool},tool_input:{ action.tool_input}")
async def on_agent_finish(
self,
finish: AgentFinish,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
**kwargs: Any,
) -> None:
if "Thought:" in finish.return_values["output"]:
finish.return_values["output"] = finish.return_values["output"].replace(
"Thought:", ""
)
data = {
"status": AgentStatus.agent_finish,
"text": finish.return_values["output"],
}
self.queue.put_nowait(dumps(data))
logger.error(f"data:{data}")
async def on_chain_end(
self,
outputs: Dict[str, Any],
*,
run_id: UUID,
parent_run_id: UUID | None = None,
tags: List[str] | None = None,
**kwargs: Any,
) -> None:
self.done.set()
self.out = True
logger.info(f"outputs:{outputs}")