id stringlengths 14 15 | text stringlengths 44 2.47k | source stringlengths 61 181 |
|---|---|---|
9c3ef4382793-10 | visualizations,
complexity_metrics,
custom_metrics,
)
def _log_stream(self, prompt: str, metadata: dict, step: int) -> None:
self.experiment.log_text(prompt, metadata=metadata, step=step)
def _log_model(self, langchain_asset: Any) -> None:
model_parame... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/comet_ml_callback.html |
9c3ef4382793-11 | exc_info=True,
extra={"show_traceback": True},
)
try:
metadata = {"langchain_version": str(langchain.__version__)}
# Log the langchain low-level records as a JSON file directly
self.experiment.log_asset_data(
self.action_records, "l... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/comet_ml_callback.html |
9c3ef4382793-12 | sentence_spans,
style=visualization,
options={"compact": True},
jupyter=False,
page=True,
)
self.experiment.log_asset_data(
html,
name=f... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/comet_ml_callback.html |
9c3ef4382793-13 | visualizations=_visualizations,
complexity_metrics=_complexity_metrics,
custom_metrics=_custom_metrics,
)
self.reset_callback_meta()
self.temp_dir = tempfile.TemporaryDirectory()
def _create_session_analysis_dataframe(self, langchain_asset: Any = None) -> dict:
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/comet_ml_callback.html |
9c3ef4382793-14 | else:
llm_parameters = langchain_asset.dict()
except Exception:
return {}
return llm_parameters | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/comet_ml_callback.html |
5b24fd510b65-0 | Source code for langchain.callbacks.utils
import hashlib
from pathlib import Path
from typing import Any, Dict, Iterable, Tuple, Union
[docs]def import_spacy() -> Any:
"""Import the spacy python package and raise an error if it is not installed."""
try:
import spacy
except ImportError:
raise... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
5b24fd510b65-1 | parent_key (str): The prefix to prepend to the keys of the flattened dict.
sep (str): The separator to use between the parent key and the key of the
flattened dictionary.
Yields:
(str, any): A key-value pair from the flattened dictionary.
"""
for key, value in nested_dict.items()... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
5b24fd510b65-2 | """Load json file to a string.
Parameters:
json_path (str): The path to the json file.
Returns:
(str): The string representation of the json file.
"""
with open(json_path, "r") as f:
data = f.read()
return data
[docs]class BaseMetadataCallbackHandler:
"""This class handle... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
5b24fd510b65-3 | tool_ends (int): The number of times the tool end method has been called.
agent_ends (int): The number of times the agent end method has been called.
on_llm_start_records (list): A list of records of the on_llm_start method.
on_llm_token_records (list): A list of records of the on_llm_token meth... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
5b24fd510b65-4 | self.on_llm_token_records: list = []
self.on_llm_end_records: list = []
self.on_chain_start_records: list = []
self.on_chain_end_records: list = []
self.on_tool_start_records: list = []
self.on_tool_end_records: list = []
self.on_text_records: list = []
self.on_ag... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
5b24fd510b65-5 | }
[docs] def reset_callback_meta(self) -> None:
"""Reset the callback metadata."""
self.step = 0
self.starts = 0
self.ends = 0
self.errors = 0
self.text_ctr = 0
self.ignore_llm_ = False
self.ignore_chain_ = False
self.ignore_agent_ = False
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
758409e2edec-0 | Source code for langchain.callbacks.stdout
"""Callback Handler that prints to std out."""
from typing import Any, Dict, List, Optional
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
from langchain.utils.input import print_text
[docs]class StdOut... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/stdout.html |
758409e2edec-1 | """Print out that we finished a chain."""
print("\n\033[1m> Finished chain.\033[0m")
[docs] def on_chain_error(self, error: BaseException, **kwargs: Any) -> None:
"""Do nothing."""
pass
[docs] def on_tool_start(
self,
serialized: Dict[str, Any],
input_str: str,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/stdout.html |
758409e2edec-2 | ) -> None:
"""Run when agent ends."""
print_text(text, color=color or self.color, end=end)
[docs] def on_agent_finish(
self, finish: AgentFinish, color: Optional[str] = None, **kwargs: Any
) -> None:
"""Run on agent end."""
print_text(finish.log, color=color or self.color,... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/stdout.html |
63dd96d18a5b-0 | Source code for langchain.callbacks.file
"""Callback Handler that writes to a file."""
from typing import Any, Dict, Optional, TextIO, cast
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish
from langchain.utils.input import print_text
[docs]class FileCallback... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/file.html |
63dd96d18a5b-1 | ) -> Any:
"""Run on agent action."""
print_text(action.log, color=color or self.color, file=self.file)
[docs] def on_tool_end(
self,
output: str,
color: Optional[str] = None,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/file.html |
6d8028e4e39a-0 | Source code for langchain.callbacks.aim_callback
from copy import deepcopy
from typing import Any, Dict, List, Optional
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
[docs]def import_aim() -> Any:
"""Import the aim python package and raise ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-1 | llm_ends (int): The number of times the llm end method has been called.
llm_streams (int): The number of times the text method has been called.
tool_starts (int): The number of times the tool start method has been called.
tool_ends (int): The number of times the tool end method has been called.
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-2 | """Whether to ignore agent callbacks."""
return self.ignore_agent_
@property
def ignore_retriever(self) -> bool:
"""Whether to ignore retriever callbacks."""
return self.ignore_retriever_
[docs] def get_custom_callback_meta(self) -> Dict[str, Any]:
return {
"step":... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-3 | """Callback Handler that logs to Aim.
Parameters:
repo (:obj:`str`, optional): Aim repository path or Repo object to which
Run object is bound. If skipped, default Repo is used.
experiment_name (:obj:`str`, optional): Sets Run's `experiment` property.
'default' if not specifi... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-4 | self._run_hash = self._run.hash
self.action_records: list = []
[docs] def setup(self, **kwargs: Any) -> None:
aim = import_aim()
if not self._run:
if self._run_hash:
self._run = aim.Run(
self._run_hash,
repo=self.repo,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-5 | self.llm_ends += 1
self.ends += 1
resp = {"action": "on_llm_end"}
resp.update(self.get_custom_callback_meta())
response_res = deepcopy(response)
generated = [
aim.Text(generation.text)
for generations in response_res.generations
for generation ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-6 | aim = import_aim()
self.step += 1
self.chain_ends += 1
self.ends += 1
resp = {"action": "on_chain_end"}
resp.update(self.get_custom_callback_meta())
outputs_res = deepcopy(outputs)
self._run.track(
aim.Text(outputs_res["output"]), name="on_chain_end", ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-7 | """Run when tool errors."""
self.step += 1
self.errors += 1
[docs] def on_text(self, text: str, **kwargs: Any) -> None:
"""
Run when agent is ending.
"""
self.step += 1
self.text_ctr += 1
[docs] def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-8 | [docs] def flush_tracker(
self,
repo: Optional[str] = None,
experiment_name: Optional[str] = None,
system_tracking_interval: Optional[int] = 10,
log_system_params: bool = True,
langchain_asset: Any = None,
reset: bool = True,
finish: bool = False,
)... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
6d8028e4e39a-9 | repo=repo if repo else self.repo,
experiment_name=experiment_name
if experiment_name
else self.experiment_name,
system_tracking_interval=system_tracking_interval
if system_tracking_interval
else self.system_tracking_interval... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/aim_callback.html |
e58bdd542509-0 | Source code for langchain.callbacks.streaming_stdout_final_only
"""Callback Handler streams to stdout on new llm token."""
import sys
from typing import Any, Dict, List, Optional
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
DEFAULT_ANSWER_PREFIX_TOKENS = ["Final", "Answer", ":"]
[docs... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_stdout_final_only.html |
e58bdd542509-1 | reached)
stream_prefix: Should answer prefix itself also be streamed?
"""
super().__init__()
if answer_prefix_tokens is None:
self.answer_prefix_tokens = DEFAULT_ANSWER_PREFIX_TOKENS
else:
self.answer_prefix_tokens = answer_prefix_tokens
if str... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_stdout_final_only.html |
a6fe3dc4c768-0 | Source code for langchain.callbacks.mlflow_callback
import os
import random
import string
import tempfile
import traceback
from copy import deepcopy
from pathlib import Path
from typing import Any, Dict, List, Optional, Union
from langchain.callbacks.base import BaseCallbackHandler
from langchain.callbacks.utils import... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-1 | "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": textstat.coleman_liau_index(text),
"automated_readability_index": textstat.automated_readability_index(te... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-2 | doc, style="ent", jupyter=False, page=True
)
text_visualizations = {
"dependency_tree": dep_out,
"entities": ent_out,
}
resp.update(text_visualizations)
return resp
[docs]def construct_html_from_prompt_and_generation(prompt: str, generation: str) -> Any:
"... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-3 | self.mlf_expid = self.mlflow.tracking.fluent._get_experiment_id()
self.mlf_exp = self.mlflow.get_experiment(self.mlf_expid)
else:
tracking_uri = get_from_dict_or_env(
kwargs, "tracking_uri", "MLFLOW_TRACKING_URI", ""
)
self.mlflow.set_tracking_uri(... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-4 | ):
self.mlflow.end_run()
[docs] def metric(self, key: str, value: float) -> None:
"""To log metric to mlflow server."""
with self.mlflow.start_run(
run_id=self.run.info.run_id, experiment_id=self.mlf_expid
):
self.mlflow.log_metric(key, value)
[docs] def... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-5 | ):
self.mlflow.log_text(html, f"{filename}.html")
[docs] def text(self, text: str, filename: str) -> None:
"""To log the input text as text file artifact."""
with self.mlflow.start_run(
run_id=self.run.info.run_id, experiment_id=self.mlf_expid
):
self.mlflo... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-6 | """
[docs] def __init__(
self,
name: Optional[str] = "langchainrun-%",
experiment: Optional[str] = "langchain",
tags: Optional[Dict] = None,
tracking_uri: Optional[str] = None,
) -> None:
"""Initialize callback handler."""
import_pandas()
import_tex... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-7 | "on_llm_end_records": [],
"on_chain_start_records": [],
"on_chain_end_records": [],
"on_tool_start_records": [],
"on_tool_end_records": [],
"on_text_records": [],
"on_agent_finish_records": [],
"on_agent_action_records": [],
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-8 | """Run when LLM generates a new token."""
self.metrics["step"] += 1
self.metrics["llm_streams"] += 1
llm_streams = self.metrics["llm_streams"]
resp: Dict[str, Any] = {}
resp.update({"action": "on_llm_new_token", "token": token})
resp.update(self.metrics)
self.mlfl... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-9 | self.mlflg.metrics(
complexity_metrics,
step=self.metrics["step"],
)
self.records["on_llm_end_records"].append(generation_resp)
self.records["action_records"].append(generation_resp)
self.mlflg.jsonf(resp, f"llm_end_... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-10 | self.records["on_chain_start_records"].append(input_resp)
self.records["action_records"].append(input_resp)
self.mlflg.jsonf(input_resp, f"chain_start_{chain_starts}")
[docs] def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
"""Run when chain ends running."""
sel... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-11 | resp: Dict[str, Any] = {}
resp.update({"action": "on_tool_start", "input_str": input_str})
resp.update(flatten_dict(serialized))
resp.update(self.metrics)
self.mlflg.metrics(self.metrics, step=self.metrics["step"])
self.records["on_tool_start_records"].append(resp)
self.r... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-12 | text_ctr = self.metrics["text_ctr"]
resp: Dict[str, Any] = {}
resp.update({"action": "on_text", "text": text})
resp.update(self.metrics)
self.mlflg.metrics(self.metrics, step=self.metrics["step"])
self.records["on_text_records"].append(resp)
self.records["action_records"]... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-13 | resp.update(
{
"action": "on_agent_action",
"tool": action.tool,
"tool_input": action.tool_input,
"log": action.log,
}
)
resp.update(self.metrics)
self.mlflg.metrics(self.metrics, step=self.metrics["step"])
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-14 | visualizations_columns = []
complexity_metrics_columns = [
"flesch_reading_ease",
"flesch_kincaid_grade",
"smog_index",
"coleman_liau_index",
"automated_readability_index",
"dale_chall_readability_score",
"difficult_words",
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
a6fe3dc4c768-15 | pd = import_pandas()
self.mlflg.table("action_records", pd.DataFrame(self.records["action_records"]))
session_analysis_df = self._create_session_analysis_df()
chat_html = session_analysis_df.pop("chat_html")
chat_html = chat_html.replace("\n", "", regex=True)
self.mlflg.table("se... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/mlflow_callback.html |
0ff95f41506c-0 | Source code for langchain.callbacks.streaming_stdout
"""Callback Handler streams to stdout on new llm token."""
import sys
from typing import Any, Dict, List
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
from langchain.schema.messages import Ba... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_stdout.html |
0ff95f41506c-1 | """Run when chain ends running."""
[docs] def on_chain_error(self, error: BaseException, **kwargs: Any) -> None:
"""Run when chain errors."""
[docs] def on_tool_start(
self, serialized: Dict[str, Any], input_str: str, **kwargs: Any
) -> None:
"""Run when tool starts running."""
[docs] ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_stdout.html |
c76d6bcd25f1-0 | Source code for langchain.callbacks.base
"""Base callback handler that can be used to handle callbacks in langchain."""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, TypeVar, Union
from uuid import UUID
from tenacity import RetryCallState
if TYPE_CHECKING:
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-1 | Args:
token (str): The new token.
chunk (GenerationChunk | ChatGenerationChunk): The new generated chunk,
containing content and other information.
"""
[docs] def on_llm_end(
self,
response: LLMResult,
*,
run_id: UUID,
parent_run_id:... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-2 | ) -> Any:
"""Run on agent action."""
[docs] def on_agent_finish(
self,
finish: AgentFinish,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
**kwargs: Any,
) -> Any:
"""Run on agent end."""
[docs]class ToolManagerMixin:
"""Mixin for tool c... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-3 | messages: List[List[BaseMessage]],
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
metadata: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Any:
"""Run when a chat model starts running."""
raise NotImpleme... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-4 | metadata: Optional[Dict[str, Any]] = None,
**kwargs: Any,
) -> Any:
"""Run when tool starts running."""
[docs]class RunManagerMixin:
"""Mixin for run manager."""
[docs] def on_text(
self,
text: str,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-5 | return False
@property
def ignore_retriever(self) -> bool:
"""Whether to ignore retriever callbacks."""
return False
@property
def ignore_chat_model(self) -> bool:
"""Whether to ignore chat model callbacks."""
return False
[docs]class AsyncCallbackHandler(BaseCallbackHand... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-6 | run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
**kwargs: Any,
) -> None:
"""Run on new LLM token. Only available when streaming is enabled."""
[docs] async def on_llm_end(
self,
response: LLMResult,
*,
run_id: ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-7 | **kwargs: Any,
) -> None:
"""Run when chain ends running."""
[docs] async def on_chain_error(
self,
error: BaseException,
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
**kwargs: Any,
) -> None:
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-8 | run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
**kwargs: Any,
) -> None:
"""Run on arbitrary text."""
[docs] async def on_retry(
self,
retry_state: RetryCallState,
*,
run_id: UUID,
parent_run_id: Option... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-9 | [docs] async def on_retriever_end(
self,
documents: Sequence[Document],
*,
run_id: UUID,
parent_run_id: Optional[UUID] = None,
tags: Optional[List[str]] = None,
**kwargs: Any,
) -> None:
"""Run on retriever end."""
[docs] async def on_retriever_e... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-10 | self.inheritable_tags = inheritable_tags or []
self.metadata = metadata or {}
self.inheritable_metadata = inheritable_metadata or {}
[docs] def copy(self: T) -> T:
"""Copy the callback manager."""
return self.__class__(
handlers=self.handlers,
inheritable_handl... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c76d6bcd25f1-11 | """Set handler as the only handler on the callback manager."""
self.set_handlers([handler], inherit=inherit)
[docs] def add_tags(self, tags: List[str], inherit: bool = True) -> None:
for tag in tags:
if tag in self.tags:
self.remove_tags([tag])
self.tags.extend(tag... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/base.html |
c410b1c0d1fb-0 | Source code for langchain.callbacks.llmonitor_callback
import os
import traceback
from contextvars import ContextVar
from datetime import datetime
from typing import Any, Dict, List, Literal, Union
from uuid import UUID
import requests
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema.agent... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-1 | if not raw_input:
return None
if not isinstance(raw_input, dict):
return _serialize(raw_input)
input_value = raw_input.get("input")
inputs_value = raw_input.get("inputs")
question_value = raw_input.get("question")
query_value = raw_input.get("query")
if input_value:
retur... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-2 | return None
def _get_user_id(metadata: Any) -> Any:
if user_ctx.get() is not None:
return user_ctx.get()
metadata = metadata or {}
user_id = metadata.get("user_id")
if user_id is None:
user_id = metadata.get("userId") # legacy, to delete in the future
return user_id
def _get_user_pr... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-3 | - `ValueError`: if `app_id` is not provided either as an
argument or as an environment variable.
- `ConnectionError`: if the connection to the API fails.
#### Example:
```python
from langchain.llms import OpenAI
from langchain.callbacks import LLMonitorCallbackHandler
llmonitor_callb... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-4 | ) from e
def __send_event(self, event: Dict[str, Any]) -> None:
headers = {"Content-Type": "application/json"}
event = {**event, "app": self.__app_id, "timestamp": str(datetime.utcnow())}
if self.__verbose:
print("llmonitor_callback", event)
data = {"events": event}
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-5 | messages: List[List[BaseMessage]],
*,
run_id: UUID,
parent_run_id: Union[UUID, None] = None,
tags: Union[List[str], None] = None,
metadata: Union[Dict[str, Any], None] = None,
**kwargs: Any,
) -> Any:
user_id = _get_user_id(metadata)
user_props = _get_... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-6 | and "function_call" in generation.message.additional_kwargs
else {}
),
}
for generation in response.generations[0]
]
event = {
"event": "end",
"type": "llm",
"runId": str(run_id),
"parent_run_id":... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-7 | self,
output: str,
*,
run_id: UUID,
parent_run_id: Union[UUID, None] = None,
tags: Union[List[str], None] = None,
**kwargs: Any,
) -> None:
event = {
"event": "end",
"type": "tool",
"runId": str(run_id),
"parent_... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-8 | event = {
"event": "start",
"type": type,
"userId": user_id,
"runId": str(run_id),
"parentRunId": str(parent_run_id) if parent_run_id else None,
"input": _parse_input(inputs),
"tags": tags,
"metadata": metadata,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-9 | finish: AgentFinish,
*,
run_id: UUID,
parent_run_id: Union[UUID, None] = None,
**kwargs: Any,
) -> Any:
event = {
"event": "end",
"type": "agent",
"runId": str(run_id),
"parentRunId": str(parent_run_id) if parent_run_id else Non... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
c410b1c0d1fb-10 | }
self.__send_event(event)
[docs] def on_llm_error(
self,
error: BaseException,
*,
run_id: UUID,
parent_run_id: Union[UUID, None] = None,
**kwargs: Any,
) -> Any:
event = {
"event": "error",
"type": "llm",
"runId"... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
1bf8c31c416a-0 | Source code for langchain.callbacks.wandb_callback
import json
import tempfile
from copy import deepcopy
from pathlib import Path
from typing import Any, Dict, List, Optional, Sequence, Union
from langchain.callbacks.base import BaseCallbackHandler
from langchain.callbacks.utils import (
BaseMetadataCallbackHandler... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-1 | Parameters:
text (str): The text to analyze.
complexity_metrics (bool): Whether to compute complexity metrics.
visualize (bool): Whether to visualize the text.
nlp (spacy.lang): The spacy language model to use for visualization.
output_dir (str): The directory to save the visuali... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-2 | "gutierrez_polini": textstat.gutierrez_polini(text),
"crawford": textstat.crawford(text),
"gulpease_index": textstat.gulpease_index(text),
"osman": textstat.osman(text),
}
resp.update(text_complexity_metrics)
if visualize and nlp and output_dir is not None:
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-3 | formatted_prompt = prompt.replace("\n", "<br>")
formatted_generation = generation.replace("\n", "<br>")
return wandb.Html(
f"""
<p style="color:black;">{formatted_prompt}:</p>
<blockquote>
<p style="color:green;">
{formatted_generation}
</p>
</blockquote>
""",
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-4 | group: Optional[str] = None,
name: Optional[str] = None,
notes: Optional[str] = None,
visualize: bool = False,
complexity_metrics: bool = False,
stream_logs: bool = False,
) -> None:
"""Initialize callback handler."""
wandb = import_wandb()
import_pand... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-5 | def _init_resp(self) -> Dict:
return {k: None for k in self.callback_columns}
[docs] def on_llm_start(
self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
) -> None:
"""Run when LLM starts."""
self.step += 1
self.llm_starts += 1
self.starts += 1
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-6 | self.ends += 1
resp = self._init_resp()
resp.update({"action": "on_llm_end"})
resp.update(flatten_dict(response.llm_output or {}))
resp.update(self.get_custom_callback_meta())
for generations in response.generations:
for generation in generations:
gene... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-7 | self.on_chain_start_records.append(input_resp)
self.action_records.append(input_resp)
if self.stream_logs:
self.run.log(input_resp)
elif isinstance(chain_input, list):
for inp in chain_input:
input_resp = deepcopy(resp)
input_re... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-8 | resp.update(flatten_dict(serialized))
resp.update(self.get_custom_callback_meta())
self.on_tool_start_records.append(resp)
self.action_records.append(resp)
if self.stream_logs:
self.run.log(resp)
[docs] def on_tool_end(self, output: str, **kwargs: Any) -> None:
"""... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-9 | 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,
}
)
resp.update(self.get_custom_callback_m... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-10 | )
complexity_metrics_columns = []
visualizations_columns = []
if self.complexity_metrics:
complexity_metrics_columns = [
"flesch_reading_ease",
"flesch_kincaid_grade",
"smog_index",
"coleman_liau_index",
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-11 | ),
axis=1,
)
return session_analysis_df
[docs] def flush_tracker(
self,
langchain_asset: Any = None,
reset: bool = True,
finish: bool = False,
job_type: Optional[str] = None,
project: Optional[str] = None,
entity: Optional[str] = Non... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1bf8c31c416a-12 | }
)
if langchain_asset:
langchain_asset_path = Path(self.temp_dir.name, "model.json")
model_artifact = wandb.Artifact(name="model", type="model")
model_artifact.add(action_records_table, name="action_records")
model_artifact.add(session_analysis_table, nam... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
77d8ca46d9fa-0 | Source code for langchain.callbacks.trubrics_callback
import os
from typing import Any, Dict, List, Optional
from uuid import UUID
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import LLMResult
from langchain.schema.messages import (
AIMessage,
BaseMessage,
ChatMessage,
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/trubrics_callback.html |
77d8ca46d9fa-1 | """
Callback handler for Trubrics.
Args:
project: a trubrics project, default project is "default"
email: a trubrics account email, can equally be set in env variables
password: a trubrics account password, can equally be set in env variables
**kwargs: all other kwargs are parsed... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/trubrics_callback.html |
77d8ca46d9fa-2 | serialized: Dict[str, Any],
messages: List[List[BaseMessage]],
**kwargs: Any,
) -> None:
self.messages = [_convert_message_to_dict(message) for message in messages[0]]
self.prompt = self.messages[-1]["content"]
[docs] def on_llm_end(self, response: LLMResult, run_id: UUID, **kwarg... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/trubrics_callback.html |
52c41d5d3587-0 | Source code for langchain.callbacks.context_callback
"""Callback handler for Context AI"""
import os
from typing import Any, Dict, List
from uuid import UUID
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import (
BaseMessage,
LLMResult,
)
[docs]def import_context() -> Any:
"... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/context_callback.html |
52c41d5d3587-1 | >>> chat = ChatOpenAI(
... temperature=0,
... headers={"user_id": "123"},
... callbacks=[context_callback],
... openai_api_key="API_KEY_HERE",
... )
>>> messages = [
... SystemMessage(content="You translate English to French."),
... ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/context_callback.html |
52c41d5d3587-2 | (
self.context,
self.credential,
self.conversation_model,
self.message_model,
self.message_role_model,
self.rating_model,
) = import_context()
token = token or os.environ.get("CONTEXT_TOKEN") or ""
self.client = self.context... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/context_callback.html |
52c41d5d3587-3 | """Run when LLM ends."""
if len(response.generations) == 0 or len(response.generations[0]) == 0:
return
if not self.chain_run_id:
generation = response.generations[0][0]
self.messages.append(
self.message_model(
message=generation.t... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/context_callback.html |
f1f6764a2557-0 | Source code for langchain.callbacks.streaming_aiter_final_only
from __future__ import annotations
from typing import Any, Dict, List, Optional
from langchain.callbacks.streaming_aiter import AsyncIteratorCallbackHandler
from langchain.schema import LLMResult
DEFAULT_ANSWER_PREFIX_TOKENS = ["Final", "Answer", ":"]
[docs... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_aiter_final_only.html |
f1f6764a2557-1 | """
super().__init__()
if answer_prefix_tokens is None:
self.answer_prefix_tokens = DEFAULT_ANSWER_PREFIX_TOKENS
else:
self.answer_prefix_tokens = answer_prefix_tokens
if strip_tokens:
self.answer_prefix_tokens_stripped = [
token.strip(... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_aiter_final_only.html |
f1f6764a2557-2 | # If yes, then put tokens from now on
if self.answer_reached:
self.queue.put_nowait(token) | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_aiter_final_only.html |
6b4f7496e6cd-0 | Source code for langchain.callbacks.streaming_aiter
from __future__ import annotations
import asyncio
from typing import Any, AsyncIterator, Dict, List, Literal, Union, cast
from langchain.callbacks.base import AsyncCallbackHandler
from langchain.schema.output import LLMResult
# TODO If used by two LLM runs in parallel... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_aiter.html |
6b4f7496e6cd-1 | # but stop waiting if the done event is set
done, other = await asyncio.wait(
[
# NOTE: If you add other tasks here, update the code below,
# which assumes each set has exactly one task each
asyncio.ensure_future(self.queue.get()),
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_aiter.html |
076e04903e55-0 | Source code for langchain.callbacks.labelstudio_callback
import os
import warnings
from datetime import datetime
from enum import Enum
from typing import Any, Dict, List, Optional, Tuple, Union
from uuid import UUID
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import (
AgentAction,... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
076e04903e55-1 | textKey="content"
nameKey="role"
granularity="sentence"/>
<Header value="Final response:"/>
<TextArea name="response" toName="dialogue"
maxSubmissions="1" editable="true"
required="true"/>
</View>
<Header value="Rate the response:"/>
<Rating name="rating" ... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
076e04903e55-2 | self,
api_key: Optional[str] = None,
url: Optional[str] = None,
project_id: Optional[int] = None,
project_name: str = DEFAULT_PROJECT_NAME,
project_config: Optional[str] = None,
mode: Union[str, LabelStudioMode] = LabelStudioMode.PROMPT,
):
super().__init__()
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
076e04903e55-3 | )
self.api_key = api_key
if not url:
if os.getenv("LABEL_STUDIO_URL"):
url = os.getenv("LABEL_STUDIO_URL")
else:
warnings.warn(
f"Label Studio URL is not provided, "
f"using default URL: {ls.LABEL_STUDIO_DEFA... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
076e04903e55-4 | )
self.project_id = self.ls_project.id
self.parsed_label_config = self.ls_project.parsed_label_config
# Find the first TextArea tag
# "from_name", "to_name", "value" will be used to create predictions
self.from_name, self.to_name, self.value, self.input_type = (
... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
076e04903e55-5 | ) -> None:
# Create tasks in Label Studio
tasks = []
prompts = self.payload[run_id]["prompts"]
model_version = (
self.payload[run_id]["kwargs"]
.get("invocation_params", {})
.get("model_name")
)
for prompt, generation in zip(prompts, ge... | https://api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
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