id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
076e04903e55-6 | self.payload[run_id] = {"prompts": prompts, "kwargs": kwargs}
def _get_message_role(self, message: BaseMessage) -> str:
"""Get the role of the message."""
if isinstance(message, ChatMessage):
return message.role
else:
return message.__class__.__name__
[docs] def on... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
076e04903e55-7 | "run_id": run_id,
"parent_run_id": parent_run_id,
"kwargs": kwargs,
}
[docs] def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
"""Do nothing when a new token is generated."""
pass
[docs] def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
076e04903e55-8 | """Do nothing when agent takes a specific action."""
pass
[docs] def on_tool_end(
self,
output: str,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,
) -> None:
"""Do nothing when tool ends."""
pass
[docs] ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
7b2f031dc873-0 | Source code for langchain.callbacks.promptlayer_callback
"""Callback handler for promptlayer."""
from __future__ import annotations
import datetime
from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Tuple
from uuid import UUID
from langchain.callbacks.base import BaseCallbackHandler
from langchain.s... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/promptlayer_callback.html |
7b2f031dc873-1 | tags: Optional[List[str]] = None,
**kwargs: Any,
) -> Any:
self.runs[run_id] = {
"messages": [self._create_message_dicts(m)[0] for m in messages],
"invocation_params": kwargs.get("invocation_params", {}),
"name": ".".join(serialized["id"]),
"request_st... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/promptlayer_callback.html |
7b2f031dc873-2 | generation = response.generations[i][0]
resp = {
"text": generation.text,
"llm_output": response.llm_output,
}
model_params = run_info.get("invocation_params", {})
is_chat_model = run_info.get("messages", None) is not None
model... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/promptlayer_callback.html |
7b2f031dc873-3 | elif isinstance(message, SystemMessage):
message_dict = {"role": "system", "content": message.content}
elif isinstance(message, ChatMessage):
message_dict = {"role": message.role, "content": message.content}
else:
raise ValueError(f"Got unknown type {message}")
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/promptlayer_callback.html |
6c87e5f00f8d-0 | Source code for langchain.callbacks.infino_callback
import time
from typing import Any, Dict, List, Optional
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
[docs]def import_infino() -> Any:
"""Import the infino client."""
try:
fr... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/infino_callback.html |
6c87e5f00f8d-1 | key: value,
"labels": {
"model_id": self.model_id,
"model_version": self.model_version,
},
}
if self.verbose:
print(f"Tracking {key} with Infino: {payload}")
# Append to Infino time series only if is_ts is True, otherwise
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/infino_callback.html |
6c87e5f00f8d-2 | self._send_to_infino("latency", duration)
# Track success or error flag.
self._send_to_infino("error", self.error)
# Track token usage.
if (response.llm_output is not None) and isinstance(response.llm_output, Dict):
token_usage = response.llm_output["token_usage"]
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/infino_callback.html |
6c87e5f00f8d-3 | self,
serialized: Dict[str, Any],
input_str: str,
**kwargs: Any,
) -> None:
"""Do nothing when tool starts."""
pass
[docs] def on_agent_action(self, action: AgentAction, **kwargs: Any) -> Any:
"""Do nothing when agent takes a specific action."""
pass
[docs]... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/infino_callback.html |
1a40a56df824-0 | Source code for langchain.callbacks.whylabs_callback
from __future__ import annotations
import logging
from typing import TYPE_CHECKING, Any, Optional
from langchain.callbacks.base import BaseCallbackHandler
from langchain.utils import get_from_env
if TYPE_CHECKING:
from whylogs.api.logger.logger import Logger
diag... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/whylabs_callback.html |
1a40a56df824-1 | """
Callback Handler for logging to WhyLabs. This callback handler utilizes
`langkit` to extract features from the prompts & responses when interacting with
an LLM. These features can be used to guardrail, evaluate, and observe interactions
over time to detect issues relating to hallucinations, prompt e... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/whylabs_callback.html |
1a40a56df824-2 | Optional because the preferred way to specify the dataset id is
with environment variable WHYLABS_DEFAULT_DATASET_ID.
sentiment (bool): Whether to enable sentiment analysis. Defaults to False.
toxicity (bool): Whether to enable toxicity analysis. Defaults to False.
themes (bool): Whe... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/whylabs_callback.html |
1a40a56df824-3 | [docs] @classmethod
def from_params(
cls,
*,
api_key: Optional[str] = None,
org_id: Optional[str] = None,
dataset_id: Optional[str] = None,
sentiment: bool = False,
toxicity: bool = False,
themes: bool = False,
logger: Optional[Logger] = Non... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/whylabs_callback.html |
1a40a56df824-4 | import whylogs as why
from langkit.callback_handler import get_callback_instance
from whylogs.api.writer.whylabs import WhyLabsWriter
from whylogs.experimental.core.udf_schema import udf_schema
if logger is None:
api_key = api_key or get_from_env("api_key", "WHYLABS_API_KEY")... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/whylabs_callback.html |
3ebdbfd4f159-0 | Source code for langchain.callbacks.manager
from __future__ import annotations
import asyncio
import functools
import logging
import os
import uuid
from concurrent.futures import ThreadPoolExecutor
from contextlib import asynccontextmanager, contextmanager
from contextvars import ContextVar
from typing import (
TYP... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-1 | "openai_callback", default=None
)
tracing_callback_var: ContextVar[
Optional[LangChainTracerV1]
] = ContextVar( # noqa: E501
"tracing_callback", default=None
)
wandb_tracing_callback_var: ContextVar[
Optional[WandbTracer]
] = ContextVar( # noqa: E501
"tracing_wandb_callback", default=None
)
tracing_v2... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-2 | """Get the Deprecated LangChainTracer in a context manager.
Args:
session_name (str, optional): The name of the session.
Defaults to "default".
Returns:
TracerSessionV1: The LangChainTracer session.
Example:
>>> with tracing_enabled() as session:
... # Use the L... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-3 | Args:
project_name (str, optional): The name of the project.
Defaults to "default".
example_id (str or UUID, optional): The ID of the example.
Defaults to None.
tags (List[str], optional): The tags to add to the run.
Defaults to None.
Returns:
None... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-4 | example_id: Optional[Union[str, UUID]] = None,
run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
) -> Generator[CallbackManagerForChainGroup, None, None]:
"""Get a callback manager for a chain group in a context manager.
Useful for grouping different calls together as a single run even if... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-5 | ]
if callback_manager is None
else callback_manager,
)
cm = CallbackManager.configure(
inheritable_callbacks=cb,
inheritable_tags=tags,
)
run_manager = cm.on_chain_start({"name": group_name}, inputs or {}, run_id=run_id)
child_cm = run_manager.get_child()
group_cm... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-6 | they aren't composed in a single chain.
Args:
group_name (str): The name of the chain group.
callback_manager (AsyncCallbackManager, optional): The async callback manager to use,
which manages tracing and other callback behavior.
project_name (str, optional): The name of the proj... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-7 | child_cm.handlers,
child_cm.inheritable_handlers,
child_cm.parent_run_id,
parent_run_manager=run_manager,
tags=child_cm.tags,
inheritable_tags=child_cm.inheritable_tags,
metadata=child_cm.metadata,
inheritable_metadata=child_cm.inheritable_metadata,
)
try:... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-8 | *args[2:],
**kwargs,
)
else:
handler_name = handler.__class__.__name__
logger.warning(
f"NotImplementedError in {handler_name}.{event_name}"
f" callback: {e}"
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-9 | for coro in coros:
runner.run(coro)
# Run pending tasks scheduled by coros until they are all done
while pending := asyncio.all_tasks(runner.get_loop()):
runner.run(asyncio.wait(pending))
else:
# Before Python 3.11 we need to run each coroutine in a ne... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-10 | f" callback: {e}"
)
except Exception as e:
logger.warning(
f"Error in {handler.__class__.__name__}.{event_name} callback: {e}"
)
if handler.raise_error:
raise e
async def _ahandle_event(
handlers: List[BaseCallbackHandler],
event_name: str,
ign... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-11 | ) -> None:
"""Initialize the run manager.
Args:
run_id (UUID): The ID of the run.
handlers (List[BaseCallbackHandler]): The list of handlers.
inheritable_handlers (List[BaseCallbackHandler]):
The list of inheritable handlers.
parent_run_id ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-12 | ) -> Any:
"""Run when text is received.
Args:
text (str): The received text.
Returns:
Any: The result of the callback.
"""
_handle_event(
self.handlers,
"on_text",
None,
text,
run_id=self.run_id,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-13 | [docs] async def on_text(
self,
text: str,
**kwargs: Any,
) -> Any:
"""Run when text is received.
Args:
text (str): The received text.
Returns:
Any: The result of the callback.
"""
await _ahandle_event(
self.handl... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-14 | manager.add_tags([tag], False)
return manager
[docs]class CallbackManagerForLLMRun(RunManager, LLMManagerMixin):
"""Callback manager for LLM run."""
[docs] def on_llm_new_token(
self,
token: str,
*,
chunk: Optional[Union[GenerationChunk, ChatGenerationChunk]] = None,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-15 | _handle_event(
self.handlers,
"on_llm_error",
"ignore_llm",
error,
run_id=self.run_id,
parent_run_id=self.parent_run_id,
tags=self.tags,
**kwargs,
)
[docs]class AsyncCallbackManagerForLLMRun(AsyncRunManager, LLMManag... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-16 | self,
error: BaseException,
**kwargs: Any,
) -> None:
"""Run when LLM errors.
Args:
error (Exception or KeyboardInterrupt): The error.
"""
await _ahandle_event(
self.handlers,
"on_llm_error",
"ignore_llm",
er... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-17 | tags=self.tags,
**kwargs,
)
[docs] def on_agent_action(self, action: AgentAction, **kwargs: Any) -> Any:
"""Run when agent action is received.
Args:
action (AgentAction): The agent action.
Returns:
Any: The result of the callback.
"""
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-18 | "on_chain_end",
"ignore_chain",
outputs,
run_id=self.run_id,
parent_run_id=self.parent_run_id,
tags=self.tags,
**kwargs,
)
[docs] async def on_chain_error(
self,
error: BaseException,
**kwargs: Any,
) -> None:... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-19 | "on_agent_finish",
"ignore_agent",
finish,
run_id=self.run_id,
parent_run_id=self.parent_run_id,
tags=self.tags,
**kwargs,
)
[docs]class CallbackManagerForToolRun(ParentRunManager, ToolManagerMixin):
"""Callback manager for tool run."""... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-20 | Args:
output (str): The output of the tool.
"""
await _ahandle_event(
self.handlers,
"on_tool_end",
"ignore_agent",
output,
run_id=self.run_id,
parent_run_id=self.parent_run_id,
tags=self.tags,
**... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-21 | """Run when retriever errors."""
_handle_event(
self.handlers,
"on_retriever_error",
"ignore_retriever",
error,
run_id=self.run_id,
parent_run_id=self.parent_run_id,
tags=self.tags,
**kwargs,
)
[docs]class As... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-22 | prompts: List[str],
**kwargs: Any,
) -> List[CallbackManagerForLLMRun]:
"""Run when LLM starts running.
Args:
serialized (Dict[str, Any]): The serialized LLM.
prompts (List[str]): The list of prompts.
run_id (UUID, optional): The ID of the run. Defaults to... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-23 | Args:
serialized (Dict[str, Any]): The serialized LLM.
messages (List[List[BaseMessage]]): The list of messages.
run_id (UUID, optional): The ID of the run. Defaults to None.
Returns:
List[CallbackManagerForLLMRun]: A callback manager for each
list... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-24 | inputs (Union[Dict[str, Any], Any]): The inputs to the chain.
run_id (UUID, optional): The ID of the run. Defaults to None.
Returns:
CallbackManagerForChainRun: The callback manager for the chain run.
"""
if run_id is None:
run_id = uuid.uuid4()
_handl... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-25 | Returns:
CallbackManagerForToolRun: The callback manager for the tool run.
"""
if run_id is None:
run_id = uuid.uuid4()
_handle_event(
self.handlers,
"on_tool_start",
"ignore_agent",
serialized,
input_str,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-26 | run_id=run_id,
handlers=self.handlers,
inheritable_handlers=self.inheritable_handlers,
parent_run_id=self.parent_run_id,
tags=self.tags,
inheritable_tags=self.inheritable_tags,
metadata=self.metadata,
inheritable_metadata=self.inheritab... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-27 | local_callbacks,
verbose,
inheritable_tags,
local_tags,
inheritable_metadata,
local_metadata,
)
[docs]class CallbackManagerForChainGroup(CallbackManager):
[docs] def __init__(
self,
handlers: List[BaseCallbackHandler],
inheri... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-28 | """Return whether the handler is async."""
return True
[docs] async def on_llm_start(
self,
serialized: Dict[str, Any],
prompts: List[str],
**kwargs: Any,
) -> List[AsyncCallbackManagerForLLMRun]:
"""Run when LLM starts running.
Args:
serialized... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-29 | return managers
[docs] async def on_chat_model_start(
self,
serialized: Dict[str, Any],
messages: List[List[BaseMessage]],
**kwargs: Any,
) -> List[AsyncCallbackManagerForLLMRun]:
"""Run when LLM starts running.
Args:
serialized (Dict[str, Any]): The se... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-30 | return managers
[docs] async def on_chain_start(
self,
serialized: Dict[str, Any],
inputs: Union[Dict[str, Any], Any],
run_id: Optional[UUID] = None,
**kwargs: Any,
) -> AsyncCallbackManagerForChainRun:
"""Run when chain starts running.
Args:
se... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-31 | parent_run_id: Optional[UUID] = None,
**kwargs: Any,
) -> AsyncCallbackManagerForToolRun:
"""Run when tool starts running.
Args:
serialized (Dict[str, Any]): The serialized tool.
input_str (str): The input to the tool.
run_id (UUID, optional): The ID of th... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-32 | """Run when retriever starts running."""
if run_id is None:
run_id = uuid.uuid4()
await _ahandle_event(
self.handlers,
"on_retriever_start",
"ignore_retriever",
serialized,
query,
run_id=run_id,
parent_run_id... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-33 | Defaults to None.
local_tags (Optional[List[str]], optional): The local tags.
Defaults to None.
inheritable_metadata (Optional[Dict[str, Any]], optional): The inheritable
metadata. Defaults to None.
local_metadata (Optional[Dict[str, Any]], optional): ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-34 | [docs] async def on_chain_error(
self,
error: BaseException,
**kwargs: Any,
) -> None:
"""Run when chain errors.
Args:
error (Exception or KeyboardInterrupt): The error.
"""
self.ended = True
await self.parent_run_manager.on_chain_error(... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-35 | verbose (bool, optional): Whether to enable verbose mode. Defaults to False.
inheritable_tags (Optional[List[str]], optional): The inheritable tags.
Defaults to None.
local_tags (Optional[List[str]], optional): The local tags. Defaults to None.
inheritable_metadata (Optional[Dict[str... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-36 | callback_manager.add_tags(local_tags or [], False)
if inheritable_metadata or local_metadata:
callback_manager.add_metadata(inheritable_metadata or {})
callback_manager.add_metadata(local_metadata or {}, False)
tracer = tracing_callback_var.get()
wandb_tracer = wandb_tracing_callback_var.get... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-37 | ):
callback_manager.add_handler(ConsoleCallbackHandler(), True)
if tracing_enabled_ and not any(
isinstance(handler, LangChainTracerV1)
for handler in callback_manager.handlers
):
if tracer:
callback_manager.add_handler(tracer, True)
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
3ebdbfd4f159-38 | for handler in callback_manager.handlers
):
callback_manager.add_handler(run_collector_, False)
return callback_manager | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
44c17c4e3eb6-0 | Source code for langchain.callbacks.openai_info
"""Callback Handler that prints to std out."""
from typing import Any, Dict, List
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import LLMResult
MODEL_COST_PER_1K_TOKENS = {
# GPT-4 input
"gpt-4": 0.03,
"gpt-4-0314": 0.03,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
44c17c4e3eb6-1 | "gpt-3.5-turbo-16k-0613": 0.003,
# GPT-3.5 output
"gpt-3.5-turbo-completion": 0.002,
"gpt-3.5-turbo-0301-completion": 0.002,
"gpt-3.5-turbo-0613-completion": 0.002,
"gpt-3.5-turbo-instruct-completion": 0.002,
"gpt-3.5-turbo-16k-completion": 0.004,
"gpt-3.5-turbo-16k-0613-completion": 0.004,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
44c17c4e3eb6-2 | "gpt-35-turbo-0613-completion": 0.002,
"gpt-35-turbo-instruct-completion": 0.002,
"gpt-35-turbo-16k-completion": 0.004,
"gpt-35-turbo-16k-0613-completion": 0.004,
# Others
"text-ada-001": 0.0004,
"ada": 0.0004,
"text-babbage-001": 0.0005,
"babbage": 0.0005,
"text-curie-001": 0.002,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
44c17c4e3eb6-3 | model_name = model_name.lower()
if "ft-" in model_name:
return model_name.split(":")[0] + "-finetuned"
elif is_completion and (
model_name.startswith("gpt-4")
or model_name.startswith("gpt-3.5")
or model_name.startswith("gpt-35")
):
return model_name + "-completion"
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
44c17c4e3eb6-4 | successful_requests: int = 0
total_cost: float = 0.0
def __repr__(self) -> str:
return (
f"Tokens Used: {self.total_tokens}\n"
f"\tPrompt Tokens: {self.prompt_tokens}\n"
f"\tCompletion Tokens: {self.completion_tokens}\n"
f"Successful Requests: {self.succes... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
44c17c4e3eb6-5 | completion_cost = get_openai_token_cost_for_model(
model_name, completion_tokens, is_completion=True
)
prompt_cost = get_openai_token_cost_for_model(model_name, prompt_tokens)
self.total_cost += prompt_cost + completion_cost
self.total_tokens += token_usage.ge... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
b8c38bc8d1b8-0 | Source code for langchain.callbacks.argilla_callback
import os
import warnings
from typing import Any, Dict, List, Optional
from packaging.version import parse
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
[docs]class ArgillaCallbackHandler(Bas... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
b8c38bc8d1b8-1 | ... dataset_name="my-dataset",
... workspace_name="my-workspace",
... api_url="http://localhost:6900",
... api_key="argilla.apikey",
... )
>>> llm = OpenAI(
... temperature=0,
... callbacks=[argilla_callback],
... verbose=True,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
b8c38bc8d1b8-2 | workspace_name: name of the workspace in Argilla where the specified
`FeedbackDataset` lives in. Defaults to `None`, which means that the
default workspace will be used.
api_url: URL of the Argilla Server that we want to use, and where the
`FeedbackDataset` li... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
b8c38bc8d1b8-3 | )
# Show a warning message if Argilla will assume the default values will be used
if api_url is None and os.getenv("ARGILLA_API_URL") is None:
warnings.warn(
(
"Since `api_url` is None, and the env var `ARGILLA_API_URL` is not"
f" set, ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
b8c38bc8d1b8-4 | ) from e
# Set the Argilla variables
self.dataset_name = dataset_name
self.workspace_name = workspace_name or rg.get_workspace()
# Retrieve the `FeedbackDataset` from Argilla (without existing records)
try:
extra_args = {}
if parse(self.ARGILLA_VERSION) < ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
b8c38bc8d1b8-5 | f"`langchain` integration. Supported fields are: {supported_fields},"
f" and the current `FeedbackDataset` fields are {[field.name for field in self.dataset.fields]}." # noqa: E501
" For more information on how to create a `langchain`-compatible"
f" `FeedbackDataset` in ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
b8c38bc8d1b8-6 | prompts = self.prompts[str(kwargs["run_id"])]
for prompt, generations in zip(prompts, response.generations):
self.dataset.add_records(
records=[
{
"fields": {
"prompt": prompt,
"respon... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
b8c38bc8d1b8-7 | """If either the `parent_run_id` or the `run_id` is in `self.prompts`, then
log the outputs to Argilla, and pop the run from `self.prompts`. The behavior
differs if the output is a list or not.
"""
if not any(
key in self.prompts
for key in [str(kwargs["parent_run... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
b8c38bc8d1b8-8 | self.prompts.pop(str(kwargs["run_id"]))
if parse(self.ARGILLA_VERSION) < parse("1.14.0"):
# Push the records to Argilla
self.dataset.push_to_argilla()
[docs] def on_chain_error(self, error: BaseException, **kwargs: Any) -> None:
"""Do nothing when LLM chain outputs an error.""... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/argilla_callback.html |
47a42c897b6b-0 | Source code for langchain.callbacks.confident_callback
# flake8: noqa
import os
import warnings
from typing import Any, Dict, List, Optional, Union
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
[docs]class DeepEvalCallbackHandler(BaseCallbackHa... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/confident_callback.html |
47a42c897b6b-1 | [docs] def __init__(
self,
metrics: List[Any],
implementation_name: Optional[str] = None,
) -> None:
"""Initializes the `deepevalCallbackHandler`.
Args:
implementation_name: Name of the implementation you want.
metrics: What metrics do you want to t... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/confident_callback.html |
47a42c897b6b-2 | ) -> None:
"""Store the prompts"""
self.prompts = prompts
[docs] def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
"""Do nothing when a new token is generated."""
pass
[docs] def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
"""Log records to de... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/confident_callback.html |
47a42c897b6b-3 | pass
[docs] def on_chain_start(
self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any
) -> None:
"""Do nothing when chain starts"""
pass
[docs] def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
"""Do nothing when chain ends."""
pa... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/confident_callback.html |
093fcef40689-0 | Source code for langchain.callbacks.clearml_callback
import tempfile
from copy import deepcopy
from pathlib import Path
from typing import Any, Dict, List, Optional, Sequence
from langchain.callbacks.base import BaseCallbackHandler
from langchain.callbacks.utils import (
BaseMetadataCallbackHandler,
flatten_dic... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-1 | and adds the response to the list of records for both the {method}_records and
action. It then logs the response to the ClearML console.
"""
[docs] def __init__(
self,
task_type: Optional[str] = "inference",
project_name: Optional[str] = "langchain_callback_demo",
tags: Option... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-2 | )
self.logger.report_text(warning, level=30, print_console=True)
self.callback_columns: list = []
self.action_records: list = []
self.complexity_metrics = complexity_metrics
self.visualize = visualize
self.nlp = spacy.load("en_core_web_sm")
def _init_resp(self) -> Dic... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-3 | if self.stream_logs:
self.logger.report_text(resp)
[docs] def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
"""Run when LLM ends running."""
self.step += 1
self.llm_ends += 1
self.ends += 1
resp = self._init_resp()
resp.update({"action": "on... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-4 | if isinstance(chain_input, str):
input_resp = deepcopy(resp)
input_resp["input"] = chain_input
self.on_chain_start_records.append(input_resp)
self.action_records.append(input_resp)
if self.stream_logs:
self.logger.report_text(input_resp)
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-5 | self.starts += 1
resp = self._init_resp()
resp.update({"action": "on_tool_start", "input_str": input_str})
resp.update(flatten_dict(serialized))
resp.update(self.get_custom_callback_meta())
self.on_tool_start_records.append(resp)
self.action_records.append(resp)
i... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-6 | """Run when agent ends running."""
self.step += 1
self.agent_ends += 1
self.ends += 1
resp = self._init_resp()
resp.update(
{
"action": "on_agent_finish",
"output": finish.return_values["output"],
"log": finish.log,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-7 | if self.complexity_metrics:
text_complexity_metrics = {
"flesch_reading_ease": textstat.flesch_reading_ease(text),
"flesch_kincaid_grade": textstat.flesch_kincaid_grade(text),
"smog_index": textstat.smog_index(text),
"coleman_liau_index": texts... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-8 | )
dep_output_path = Path(
self.temp_dir.name, hash_string(f"dep-{text}") + ".html"
)
dep_output_path.open("w", encoding="utf-8").write(dep_out)
ent_out = spacy.displacy.render( # type: ignore
doc, style="ent", jupyter=False, page=True
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-9 | "automated_readability_index",
"dale_chall_readability_score",
"difficult_words",
"linsear_write_formula",
"gunning_fog",
"text_standard",
"fernandez_huerta",
"szigriszt_pazos",
"gutierrez_pol... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-10 | Everything after this will be a new table.
Args:
name: Name of the performed session so far so it is identifiable
langchain_asset: The langchain asset to save.
finish: Whether to finish the run.
Returns:
None
"""
pd = import_pandas(... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
093fcef40689-11 | target_filename=name,
)
except NotImplementedError as e:
print("Could not save model.")
print(repr(e))
pass
# Cleanup after adding everything to ClearML
self.task.flush(wait_for_uploads=True)
self.temp_dir.cleanup()
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/clearml_callback.html |
2c92cf29b825-0 | Source code for langchain.callbacks.sagemaker_callback
import json
import os
import shutil
import tempfile
from copy import deepcopy
from typing import Any, Dict, List, Optional
from langchain.callbacks.base import BaseCallbackHandler
from langchain.callbacks.utils import (
flatten_dict,
)
from langchain.schema imp... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/sagemaker_callback.html |
2c92cf29b825-1 | # Create a temporary directory
self.temp_dir = tempfile.mkdtemp()
def _reset(self) -> None:
for k, v in self.metrics.items():
self.metrics[k] = 0
[docs] def on_llm_start(
self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
) -> None:
"""Run when LLM... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/sagemaker_callback.html |
2c92cf29b825-2 | [docs] def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
"""Run when LLM ends running."""
self.metrics["step"] += 1
self.metrics["llm_ends"] += 1
self.metrics["ends"] += 1
llm_ends = self.metrics["llm_ends"]
resp: Dict[str, Any] = {}
resp.update... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/sagemaker_callback.html |
2c92cf29b825-3 | resp.update(flatten_dict(serialized))
resp.update(self.metrics)
chain_input = ",".join([f"{k}={v}" for k, v in inputs.items()])
input_resp = deepcopy(resp)
input_resp["inputs"] = chain_input
self.jsonf(input_resp, self.temp_dir, f"chain_start_{chain_starts}")
[docs] def on_cha... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/sagemaker_callback.html |
2c92cf29b825-4 | resp: Dict[str, Any] = {}
resp.update({"action": "on_tool_start", "input_str": input_str})
resp.update(flatten_dict(serialized))
resp.update(self.metrics)
self.jsonf(resp, self.temp_dir, f"tool_start_{tool_starts}")
[docs] def on_tool_end(self, output: str, **kwargs: Any) -> None:
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/sagemaker_callback.html |
2c92cf29b825-5 | """Run when agent ends running."""
self.metrics["step"] += 1
self.metrics["agent_ends"] += 1
self.metrics["ends"] += 1
agent_ends = self.metrics["agent_ends"]
resp: Dict[str, Any] = {}
resp.update(
{
"action": "on_agent_finish",
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/sagemaker_callback.html |
2c92cf29b825-6 | save_json(data, file_path)
self.run.log_file(file_path, name=filename, is_output=is_output)
[docs] def flush_tracker(self) -> None:
"""Reset the steps and delete the temporary local directory."""
self._reset()
shutil.rmtree(self.temp_dir) | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/sagemaker_callback.html |
ad1031a42eb5-0 | Source code for langchain.callbacks.human
from typing import Any, Callable, Dict, Optional
from uuid import UUID
from langchain.callbacks.base import BaseCallbackHandler
def _default_approve(_input: str) -> bool:
msg = (
"Do you approve of the following input? "
"Anything except 'Y'/'Yes' (case-inse... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/human.html |
1ea00e92df8f-0 | Source code for langchain.callbacks.tracers.log_stream
from __future__ import annotations
import math
import threading
from typing import (
Any,
AsyncIterator,
Dict,
List,
Optional,
Sequence,
TypedDict,
Union,
)
from uuid import UUID
import jsonpatch
from anyio import create_memory_objec... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/tracers/log_stream.html |
1ea00e92df8f-1 | """Final output of the run, usually the result of aggregating streamed_output.
Only available after the run has finished successfully."""
logs: list[LogEntry]
"""List of sub-runs contained in this run, if any, in the order they were started.
If filters were supplied, this list will contain only the runs... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/tracers/log_stream.html |
1ea00e92df8f-2 | [docs]class RunLog(RunLogPatch):
state: RunState
"""Current state of the log, obtained from applying all ops in sequence."""
[docs] def __init__(self, *ops: Dict[str, Any], state: RunState) -> None:
super().__init__(*ops)
self.state = state
def __add__(self, other: Union[RunLogPatch, Any]... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/tracers/log_stream.html |
1ea00e92df8f-3 | self.exclude_types = exclude_types
self.exclude_tags = exclude_tags
send_stream, receive_stream = create_memory_object_stream(
math.inf, item_type=RunLogPatch
)
self.lock = threading.Lock()
self.send_stream = send_stream
self.receive_stream = receive_stream
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/tracers/log_stream.html |
1ea00e92df8f-4 | # therefore not useful here
pass
def _on_run_create(self, run: Run) -> None:
"""Start a run."""
if run.parent_run_id is None:
self.send_stream.send_nowait(
RunLogPatch(
{
"op": "replace",
"path": ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/tracers/log_stream.html |
1ea00e92df8f-5 | RunLogPatch(
{
"op": "add",
"path": f"/logs/{index}/final_output",
"value": run.outputs,
},
{
"op": "add",
"path": f"/logs/{index}/end_time"... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/tracers/log_stream.html |
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