mirror of
https://github.com/Mintplex-Labs/langchain-python.git
synced 2026-07-24 20:15:34 -04:00
Ankush Gola
bc7e56e8df
Supporting asyncio in langchain primitives allows for users to run them concurrently and creates more seamless integration with asyncio-supported frameworks (FastAPI, etc.) Summary of changes: **LLM** * Add `agenerate` and `_agenerate` * Implement in OpenAI by leveraging `client.Completions.acreate` **Chain** * Add `arun`, `acall`, `_acall` * Implement them in `LLMChain` and `LLMMathChain` for now **Agent** * Refactor and leverage async chain and llm methods * Add ability for `Tools` to contain async coroutine * Implement async SerpaPI `arun` Create demo notebook. Open questions: * Should all the async stuff go in separate classes? I've seen both patterns (keeping the same class and having async and sync methods vs. having class separation)
93 lines
2.8 KiB
Python
93 lines
2.8 KiB
Python
"""Callback Handler that prints to std out."""
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from typing import Any, Dict, List, Optional, Union
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from langchain.callbacks.base import BaseCallbackHandler
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from langchain.input import print_text
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from langchain.schema import AgentAction, AgentFinish, LLMResult
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class StdOutCallbackHandler(BaseCallbackHandler):
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"""Callback Handler that prints to std out."""
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def __init__(self, color: str = "green") -> None:
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"""Initialize callback handler."""
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self.color = color
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def on_llm_start(
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self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
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) -> None:
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"""Print out the prompts."""
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pass
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def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
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"""Do nothing."""
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pass
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def on_llm_error(
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self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
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) -> None:
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"""Do nothing."""
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pass
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def on_chain_start(
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self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any
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) -> None:
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"""Print out that we are entering a chain."""
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class_name = serialized["name"]
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print(f"\n\n\033[1m> Entering new {class_name} chain...\033[0m")
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def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
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"""Print out that we finished a chain."""
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print("\n\033[1m> Finished chain.\033[0m")
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def on_chain_error(
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self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
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) -> None:
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"""Do nothing."""
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pass
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def on_tool_start(
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self,
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serialized: Dict[str, Any],
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action: AgentAction,
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color: Optional[str] = None,
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**kwargs: Any,
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) -> None:
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"""Print out the log in specified color."""
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print_text(action.log, color=color if color else self.color)
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def on_tool_end(
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self,
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output: str,
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color: Optional[str] = None,
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observation_prefix: Optional[str] = None,
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llm_prefix: Optional[str] = None,
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**kwargs: Any,
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) -> None:
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"""If not the final action, print out observation."""
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print_text(f"\n{observation_prefix}")
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print_text(output, color=color if color else self.color)
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print_text(f"\n{llm_prefix}")
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def on_tool_error(
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self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
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) -> None:
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"""Do nothing."""
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pass
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def on_text(
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self,
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text: str,
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color: Optional[str] = None,
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end: str = "",
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**kwargs: Optional[str],
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) -> None:
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"""Run when agent ends."""
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print_text(text, color=color if color else self.color, end=end)
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def on_agent_finish(
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self, finish: AgentFinish, color: Optional[str] = None, **kwargs: Any
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) -> None:
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"""Run on agent end."""
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print_text(finish.log, color=color if self.color else color, end="\n")
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