id stringlengths 14 16 | text stringlengths 31 2.41k | source stringlengths 53 121 |
|---|---|---|
a6076a070fdd-0 | Source code for langchain.callbacks.arize_callback
from datetime import datetime
from typing import Any, Dict, List, Optional, Union
from langchain.callbacks.base import BaseCallbackHandler
from langchain.callbacks.utils import import_pandas
from langchain.schema import AgentAction, AgentFinish, LLMResult
[docs]class A... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/arize_callback.html |
a6076a070fdd-1 | self.arize_client = Client(space_key=SPACE_KEY, api_key=API_KEY)
if SPACE_KEY == "SPACE_KEY" or API_KEY == "API_KEY":
raise ValueError("❌ CHANGE SPACE AND API KEYS")
else:
print("✅ Arize client setup done! Now you can start using Arize!")
[docs] def on_llm_start(
self,... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/arize_callback.html |
a6076a070fdd-2 | for generations in response.generations:
for generation in generations:
prompt = self.prompt_records[self.step]
self.step = self.step + 1
prompt_embedding = pd.Series(
self.generator.generate_embeddings(
text_col=pd.... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/arize_callback.html |
a6076a070fdd-3 | "completion_token",
"total_token",
],
prompt_column_names=prompt_columns,
response_column_names=response_columns,
)
response_from_arize = self.arize_client.log(
dataframe=df,
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/arize_callback.html |
a6076a070fdd-4 | pass
[docs] def on_tool_end(
self,
output: str,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,
) -> None:
pass
[docs] def on_tool_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
) -> ... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/arize_callback.html |
d819d7118f27-0 | 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, Union
from langchain.callbacks.base import BaseCallbackHandler
from langchain.callbacks.utils import (
BaseMetadataCallbackHandler,
flat... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-1 | 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.
"""
def __init__(
self,
task_type: Optional[str] = "inference",
project_name: Optional[str] = "langchain_callback_demo",
tags: Optional[Seq... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-2 | )
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/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-3 | 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/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-4 | chain_input = inputs["input"]
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... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-5 | self.step += 1
self.tool_starts += 1
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(res... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-6 | if self.stream_logs:
self.logger.report_text(resp)
[docs] def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> None:
"""Run when agent ends running."""
self.step += 1
self.agent_ends += 1
self.ends += 1
resp = self._init_resp()
resp.update(
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-7 | """
resp = {}
textstat = import_textstat()
spacy = import_spacy()
if self.complexity_metrics:
text_complexity_metrics = {
"flesch_reading_ease": textstat.flesch_reading_ease(text),
"flesch_kincaid_grade": textstat.flesch_kincaid_grade(text),
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-8 | dep_out = spacy.displacy.render( # type: ignore
doc, style="dep", jupyter=False, page=True
)
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)
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-9 | "flesch_kincaid_grade",
"smog_index",
"coleman_liau_index",
"automated_readability_index",
"dale_chall_readability_score",
"difficult_words",
"linsear_write_formula",
"gunning_fog",
"text_stan... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-10 | finish: bool = False,
) -> None:
"""Flush the tracker and setup the session.
Everything after this will be a new table.
Args:
name: Name of the preformed session so far so it is identifyable
langchain_asset: The langchain asset to save.
finish: Whether to ... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d819d7118f27-11 | )
output_model.update_weights(
weights_filename=str(langchain_asset_path),
auto_delete_file=False,
target_filename=name,
)
except NotImplementedError as e:
print("Could not save model.")
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/clearml_callback.html |
d46655feb9e6-0 | Source code for langchain.callbacks.mlflow_callback
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 (
Bas... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-1 | "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/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-2 | doc, style="ent", jupyter=False, page=True
)
text_visualizations = {
"dependency_tree": dep_out,
"entities": ent_out,
}
resp.update(text_visualizations)
return resp
def construct_html_from_prompt_and_generation(prompt: str, generation: str) -> Any:
"""Cons... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-3 | # User can set other env variables described here
# > https://www.mlflow.org/docs/latest/tracking.html#logging-to-a-tracking-server
experiment_name = get_from_dict_or_env(
kwargs, "experiment_name", "MLFLOW_EXPERIMENT_NAME"
)
self.mlf_exp = self.mlflow.get_experiment_by_name(... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-4 | ):
self.mlflow.log_metric(key, value)
def metrics(
self, data: Union[Dict[str, float], Dict[str, int]], step: Optional[int] = 0
) -> None:
"""To log all metrics in the input dict."""
with self.mlflow.start_run(
run_id=self.run.info.run_id, experiment_id=self.mlf_e... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-5 | def artifact(self, path: str) -> None:
"""To upload the file from given path as artifact."""
with self.mlflow.start_run(
run_id=self.run.info.run_id, experiment_id=self.mlf_expid
):
self.mlflow.log_artifact(path)
def langchain_artifact(self, chain: Any) -> None:
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-6 | super().__init__()
self.name = name
self.experiment = experiment
self.tags = tags
self.tracking_uri = tracking_uri
self.temp_dir = tempfile.TemporaryDirectory()
self.mlflg = MlflowLogger(
tracking_uri=self.tracking_uri,
experiment_name=self.experim... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-7 | self.metrics[k] = 0
for k, v in self.records.items():
self.records[k] = []
[docs] def on_llm_start(
self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any
) -> None:
"""Run when LLM starts."""
self.metrics["step"] += 1
self.metrics["llm_starts"] +=... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-8 | self.records["on_llm_token_records"].append(resp)
self.records["action_records"].append(resp)
self.mlflg.jsonf(resp, f"llm_new_tokens_{llm_streams}")
[docs] def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
"""Run when LLM ends running."""
self.metrics["step"] += 1
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-9 | dependency_tree = generation_resp["dependency_tree"]
entities = generation_resp["entities"]
self.mlflg.html(dependency_tree, "dep-" + hash_string(generation.text))
self.mlflg.html(entities, "ent-" + hash_string(generation.text))
[docs] def on_llm_error(
self, e... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-10 | """Run when chain ends running."""
self.metrics["step"] += 1
self.metrics["chain_ends"] += 1
self.metrics["ends"] += 1
chain_ends = self.metrics["chain_ends"]
resp: Dict[str, Any] = {}
chain_output = ",".join([f"{k}={v}" for k, v in outputs.items()])
resp.update({... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-11 | self.records["on_tool_start_records"].append(resp)
self.records["action_records"].append(resp)
self.mlflg.jsonf(resp, f"tool_start_{tool_starts}")
[docs] def on_tool_end(self, output: str, **kwargs: Any) -> None:
"""Run when tool ends running."""
self.metrics["step"] += 1
self... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-12 | self.records["on_text_records"].append(resp)
self.records["action_records"].append(resp)
self.mlflg.jsonf(resp, f"on_text_{text_ctr}")
[docs] def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> None:
"""Run when agent ends running."""
self.metrics["step"] += 1
sel... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-13 | self.mlflg.metrics(self.metrics, step=self.metrics["step"])
self.records["on_agent_action_records"].append(resp)
self.records["action_records"].append(resp)
self.mlflg.jsonf(resp, f"agent_action_{tool_starts}")
def _create_session_analysis_df(self) -> Any:
"""Create a dataframe with ... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-14 | [
"step",
"text",
"token_usage_total_tokens",
"token_usage_prompt_tokens",
"token_usage_completion_tokens",
]
+ complexity_metrics_columns
+ visualizations_columns
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
d46655feb9e6-15 | try:
langchain_asset.save(langchain_asset_path)
self.mlflg.artifact(langchain_asset_path)
except ValueError:
try:
langchain_asset.save_agent(langchain_asset_path)
self.mlflg.artifact(langchain_ass... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/mlflow_callback.html |
f49d93018420-0 | Source code for langchain.callbacks.infino_callback
import time
from typing import Any, Dict, List, Optional, Union
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
def import_infino() -> Any:
try:
from infinopy import InfinoClient
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/infino_callback.html |
f49d93018420-1 | "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
# append to Infino log... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/infino_callback.html |
f49d93018420-2 | # 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"]
if token_usage is not None:
promp... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/infino_callback.html |
f49d93018420-3 | 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/stable/_modules/langchain/callbacks/infino_callback.html |
0322921a2eaf-0 | Source code for langchain.callbacks.comet_ml_callback
import tempfile
from copy import deepcopy
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Sequence, Union
import langchain
from langchain.callbacks.base import BaseCallbackHandler
from langchain.callbacks.utils import (
BaseMetad... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-1 | "automated_readability_index": textstat.automated_readability_index(text),
"dale_chall_readability_score": textstat.dale_chall_readability_score(text),
"difficult_words": textstat.difficult_words(text),
"linsear_write_formula": textstat.linsear_write_formula(text),
"gunning_fog": textsta... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-2 | stream_logs (bool): Whether to stream callback actions to Comet
This handler will utilize the associated callback method and formats
the input of each callback function with metadata regarding the state of LLM run,
and adds the response to the list of records for both the {method}_records and
action. It... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-3 | "based on updates to `langchain`. Please report any issues to "
"https://github.com/comet-ml/issue-tracking/issues with the tag "
"`langchain`."
)
self.comet_ml.LOGGER.warning(warning)
self.callback_columns: list = []
self.action_records: list = []
self.co... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-4 | self.llm_streams += 1
resp = self._init_resp()
resp.update({"action": "on_llm_new_token", "token": token})
resp.update(self.get_custom_callback_meta())
self.action_records.append(resp)
[docs] def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
"""Run when LLM end... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-5 | [docs] def on_llm_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
) -> None:
"""Run when LLM errors."""
self.step += 1
self.errors += 1
[docs] def on_chain_start(
self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any
) -> Non... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-6 | if isinstance(chain_output_val, str):
output_resp = deepcopy(resp)
if self.stream_logs:
self._log_stream(chain_output_val, resp, self.step)
output_resp.update({chain_output_key: chain_output_val})
self.action_records.append(output_resp)... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-7 | resp.update(self.get_custom_callback_meta())
if self.stream_logs:
self._log_stream(output, resp, self.step)
resp.update({"output": output})
self.action_records.append(resp)
[docs] def on_tool_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
) -> N... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-8 | """Run on agent action."""
self.step += 1
self.tool_starts += 1
self.starts += 1
tool = action.tool
tool_input = str(action.tool_input)
log = action.log
resp = self._init_resp()
resp.update({"action": "on_agent_action", "log": log, "tool": tool})
r... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-9 | return resp
[docs] def flush_tracker(
self,
langchain_asset: Any = None,
task_type: Optional[str] = "inference",
workspace: Optional[str] = None,
project_name: Optional[str] = "comet-langchain-demo",
tags: Optional[Sequence] = None,
name: Optional[str] = None,
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-10 | self.experiment.log_text(prompt, metadata=metadata, step=step)
def _log_model(self, langchain_asset: Any) -> None:
model_parameters = self._get_llm_parameters(langchain_asset)
self.experiment.log_parameters(model_parameters, prefix="model")
langchain_asset_path = Path(self.temp_dir.name, "mo... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-11 | # Log the langchain low-level records as a JSON file directly
self.experiment.log_asset_data(
self.action_records, "langchain-action_records.json", metadata=metadata
)
except Exception:
self.comet_ml.LOGGER.warning(
"Failed to log session data ... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-12 | )
self.experiment.log_asset_data(
html,
name=f"langchain-viz-{visualization}-{idx}.html",
metadata={"prompt": prompt},
step=idx,
)
except Exception as e:
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
0322921a2eaf-13 | self.reset_callback_meta()
self.temp_dir = tempfile.TemporaryDirectory()
def _create_session_analysis_dataframe(self, langchain_asset: Any = None) -> dict:
pd = import_pandas()
llm_parameters = self._get_llm_parameters(langchain_asset)
num_generations_per_prompt = llm_parameters.get(... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/comet_ml_callback.html |
7e2dbe72a59d-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, Union
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
[docs]class StreamingStdOutCallba... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/streaming_stdout.html |
7e2dbe72a59d-1 | ) -> 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] def on_agent_action(self, action: AgentAction, **kwargs: Any) -> Any:
"""Run on agent action."... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/streaming_stdout.html |
c319f8d04476-0 | 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/stable/_modules/langchain/callbacks/human.html |
af1e87a33343-0 | Source code for langchain.callbacks.manager
from __future__ import annotations
import asyncio
import functools
import logging
import os
import warnings
from contextlib import asynccontextmanager, contextmanager
from contextvars import ContextVar
from typing import (
Any,
AsyncGenerator,
Dict,
Generator,... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-1 | wandb_tracing_callback_var: ContextVar[
Optional[WandbTracer]
] = ContextVar( # noqa: E501
"tracing_wandb_callback", default=None
)
tracing_v2_callback_var: ContextVar[
Optional[LangChainTracer]
] = ContextVar( # noqa: E501
"tracing_callback_v2", default=None
)
def _get_debug() -> bool:
return lan... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-2 | tracing_callback_var.set(cb)
yield session
tracing_callback_var.set(None)
[docs]@contextmanager
def wandb_tracing_enabled(
session_name: str = "default",
) -> Generator[None, None, None]:
"""Get the WandbTracer in a context manager.
Args:
session_name (str, optional): The name of the session... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-3 | example_id = UUID(example_id)
cb = LangChainTracer(
example_id=example_id,
project_name=project_name,
)
tracing_v2_callback_var.set(cb)
yield
tracing_v2_callback_var.set(None)
@contextmanager
def trace_as_chain_group(
group_name: str,
*,
project_name: Optional[str] = None... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-4 | )
run_manager = cm.on_chain_start({"name": group_name}, {})
yield run_manager.get_child()
run_manager.on_chain_end({})
@asynccontextmanager
async def atrace_as_chain_group(
group_name: str,
*,
project_name: Optional[str] = None,
example_id: Optional[Union[str, UUID]] = None,
tags: Option... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-5 | try:
yield run_manager.get_child()
finally:
await run_manager.on_chain_end({})
def _handle_event(
handlers: List[BaseCallbackHandler],
event_name: str,
ignore_condition_name: Optional[str],
*args: Any,
**kwargs: Any,
) -> None:
"""Generic event handler for CallbackManager."""... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-6 | if ignore_condition_name is None or not getattr(handler, ignore_condition_name):
event = getattr(handler, event_name)
if asyncio.iscoroutinefunction(event):
await event(*args, **kwargs)
else:
if handler.run_inline:
event(*args, **kw... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-7 | )
await asyncio.gather(
*(
_ahandle_event_for_handler(
handler, event_name, ignore_condition_name, *args, **kwargs
)
for handler in handlers
if not handler.run_inline
)
)
BRM = TypeVar("BRM", bound="BaseRunManager")
class BaseRunMan... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-8 | Returns:
BaseRunManager: The noop manager.
"""
return cls(
run_id=uuid4(),
handlers=[],
inheritable_handlers=[],
tags=[],
inheritable_tags=[],
)
class RunManager(BaseRunManager):
"""Sync Run Manager."""
def on_text(
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-9 | ) -> None:
"""Run when LLM generates a new token.
Args:
token (str): The new token.
"""
_handle_event(
self.handlers,
"on_llm_new_token",
"ignore_llm",
token=token,
run_id=self.run_id,
parent_run_id=self.... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-10 | """Run when LLM generates a new token.
Args:
token (str): The new token.
"""
await _ahandle_event(
self.handlers,
"on_llm_new_token",
"ignore_llm",
token,
run_id=self.run_id,
parent_run_id=self.parent_run_id,
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-11 | Defaults to None.
Returns:
CallbackManager: The child callback manager.
"""
manager = CallbackManager(handlers=[], parent_run_id=self.run_id)
manager.set_handlers(self.inheritable_handlers)
manager.add_tags(self.inheritable_tags)
if tag is not None:
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-12 | "on_agent_action",
"ignore_agent",
action,
run_id=self.run_id,
parent_run_id=self.parent_run_id,
**kwargs,
)
def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> Any:
"""Run when agent finish is received.
Args:
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-13 | self.handlers,
"on_chain_end",
"ignore_chain",
outputs,
run_id=self.run_id,
parent_run_id=self.parent_run_id,
**kwargs,
)
async def on_chain_error(
self,
error: Union[Exception, KeyboardInterrupt],
**kwargs: Any,... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-14 | run_id=self.run_id,
parent_run_id=self.parent_run_id,
**kwargs,
)
class CallbackManagerForToolRun(RunManager, ToolManagerMixin):
"""Callback manager for tool run."""
def get_child(self, tag: Optional[str] = None) -> CallbackManager:
"""Get a child callback manager.
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-15 | run_id=self.run_id,
parent_run_id=self.parent_run_id,
**kwargs,
)
class AsyncCallbackManagerForToolRun(AsyncRunManager, ToolManagerMixin):
"""Async callback manager for tool run."""
def get_child(self, tag: Optional[str] = None) -> AsyncCallbackManager:
"""Get a child cal... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-16 | run_id=self.run_id,
parent_run_id=self.parent_run_id,
**kwargs,
)
class CallbackManager(BaseCallbackManager):
"""Callback manager that can be used to handle callbacks from langchain."""
def on_llm_start(
self,
serialized: Dict[str, Any],
prompts: List[str]... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-17 | messages: List[List[BaseMessage]],
**kwargs: Any,
) -> List[CallbackManagerForLLMRun]:
"""Run when LLM starts running.
Args:
serialized (Dict[str, Any]): The serialized LLM.
messages (List[List[BaseMessage]]): The list of messages.
run_id (UUID, optional):... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-18 | inputs (Dict[str, 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 = uuid4()
_handle_event(
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-19 | run_id = uuid4()
_handle_event(
self.handlers,
"on_tool_start",
"ignore_agent",
serialized,
input_str,
run_id=run_id,
parent_run_id=self.parent_run_id,
tags=self.tags,
**kwargs,
)
return C... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-20 | local_tags,
)
class AsyncCallbackManager(BaseCallbackManager):
"""Async callback manager that can be used to handle callbacks from LangChain."""
@property
def is_async(self) -> bool:
"""Return whether the handler is async."""
return True
async def on_llm_start(
self,
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-21 | )
)
await asyncio.gather(*tasks)
return managers
async def on_chat_model_start(
self,
serialized: Dict[str, Any],
messages: List[List[BaseMessage]],
**kwargs: Any,
) -> Any:
"""Run when LLM starts running.
Args:
serialized (... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-22 | serialized: Dict[str, Any],
inputs: Dict[str, Any],
run_id: Optional[UUID] = None,
**kwargs: Any,
) -> AsyncCallbackManagerForChainRun:
"""Run when chain starts running.
Args:
serialized (Dict[str, Any]): The serialized chain.
inputs (Dict[str, Any]): ... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-23 | input_str (str): The input to the tool.
run_id (UUID, optional): The ID of the run. Defaults to None.
parent_run_id (UUID, optional): The ID of the parent run.
Defaults to None.
Returns:
AsyncCallbackManagerForToolRun: The async callback manager
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-24 | Defaults to None.
local_tags (Optional[List[str]], optional): The local tags.
Defaults to None.
Returns:
AsyncCallbackManager: The configured async callback manager.
"""
return _configure(
cls,
inheritable_callbacks,
loc... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-25 | Defaults to None.
local_tags (Optional[List[str]], optional): The local tags. Defaults to None.
Returns:
T: The configured callback manager.
"""
callback_manager = callback_manager_cls(handlers=[])
if inheritable_callbacks or local_callbacks:
if isinstance(inheritable_callbacks, ... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-26 | )
tracer_v2 = tracing_v2_callback_var.get()
tracing_v2_enabled_ = (
env_var_is_set("LANGCHAIN_TRACING_V2") or tracer_v2 is not None
)
tracer_project = os.environ.get(
"LANGCHAIN_PROJECT", os.environ.get("LANGCHAIN_SESSION", "default")
)
debug = _get_debug()
if (
verbo... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
af1e87a33343-27 | if tracing_v2_enabled_ and not any(
isinstance(handler, LangChainTracer)
for handler in callback_manager.handlers
):
if tracer_v2:
callback_manager.add_handler(tracer_v2, True)
else:
try:
handler = LangChainTrace... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/manager.html |
c630145c3a58-0 | Source code for langchain.callbacks.argilla_callback
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 ArgillaCallbackHandler(BaseCallbackHandler):
"""Cal... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
c630145c3a58-1 | >>> argilla_callback = ArgillaCallbackHandler(
... dataset_name="my-dataset",
... workspace_name="my-workspace",
... api_url="http://localhost:6900",
... api_key="argilla.apikey",
... )
>>> llm = OpenAI(
... temperature=0,
... callb... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
c630145c3a58-2 | `FeedbackDataset` lives in. Defaults to `None`, which means that either
`ARGILLA_API_URL` environment variable or the default
http://localhost:6900 will be used.
api_key: API Key to connect to the Argilla Server. Defaults to `None`, which
means that either `AR... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
c630145c3a58-3 | " set, it will default to `argilla.apikey`."
),
)
# Connect to Argilla with the provided credentials, if applicable
try:
rg.init(
api_key=api_key,
api_url=api_url,
)
except Exception as e:
raise Conne... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
c630145c3a58-4 | " If the problem persists please report it to"
" https://github.com/argilla-io/argilla/issues with the label"
" `langchain`."
) from e
supported_fields = ["prompt", "response"]
if supported_fields != [field.name for field in self.dataset.fields]:
r... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
c630145c3a58-5 | [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 Argilla when an LLM ends."""
# Do nothing if there's a parent_run_id... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
c630145c3a58-6 | we don't log the same input prompt twice, once when the LLM starts and once
when the chain starts.
"""
if "input" in inputs:
self.prompts.update(
{
str(kwargs["parent_run_id"] or kwargs["run_id"]): (
inputs["input"]
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
c630145c3a58-7 | self.dataset.add_records(
records=[
{
"fields": {
"prompt": " ".join(prompts), # type: ignore
"response": chain_output_val.strip(),
},
... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
c630145c3a58-8 | ) -> None:
"""Do nothing when tool outputs an error."""
pass
[docs] def on_text(self, text: str, **kwargs: Any) -> None:
"""Do nothing"""
pass
[docs] def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> None:
"""Do nothing"""
pass | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/argilla_callback.html |
aa6f172b81d3-0 | Source code for langchain.callbacks.aim_callback
from copy import deepcopy
from typing import Any, Dict, List, Optional, Union
from langchain.callbacks.base import BaseCallbackHandler
from langchain.schema import AgentAction, AgentFinish, LLMResult
def import_aim() -> Any:
"""Import the aim python package and raise... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
aa6f172b81d3-1 | 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.
agent_ends (int): The number of times the agent end method has been call... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
aa6f172b81d3-2 | "step": self.step,
"starts": self.starts,
"ends": self.ends,
"errors": self.errors,
"text_ctr": self.text_ctr,
"chain_starts": self.chain_starts,
"chain_ends": self.chain_ends,
"llm_starts": self.llm_starts,
"llm_ends": self... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
aa6f172b81d3-3 | 'default' if not specified. Can be used later to query runs/sequences.
system_tracking_interval (:obj:`int`, optional): Sets the tracking interval
in seconds for system usage metrics (CPU, Memory, etc.). Set to `None`
to disable system metrics tracking.
log_system_params (:obj:`... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
aa6f172b81d3-4 | repo=self.repo,
system_tracking_interval=self.system_tracking_interval,
)
else:
self._run = aim.Run(
repo=self.repo,
experiment=self.experiment_name,
system_tracking_interval=self.system_tracking_... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
aa6f172b81d3-5 | for generation in generations
]
self._run.track(
generated,
name="on_llm_end",
context=resp,
)
[docs] def on_llm_new_token(self, token: str, **kwargs: Any) -> None:
"""Run when LLM generates a new token."""
self.step += 1
self.llm_st... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
aa6f172b81d3-6 | outputs_res = deepcopy(outputs)
self._run.track(
aim.Text(outputs_res["output"]), name="on_chain_end", context=resp
)
[docs] def on_chain_error(
self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any
) -> None:
"""Run when chain errors."""
self.step +=... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
aa6f172b81d3-7 | """
Run when agent is ending.
"""
self.step += 1
self.text_ctr += 1
[docs] def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> None:
"""Run when agent ends running."""
aim = import_aim()
self.step += 1
self.agent_ends += 1
self.ends... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
aa6f172b81d3-8 | log_system_params: bool = True,
langchain_asset: Any = None,
reset: bool = True,
finish: bool = False,
) -> None:
"""Flush the tracker and reset the session.
Args:
repo (:obj:`str`, optional): Aim repository path or Repo object to which
Run object ... | https://api.python.langchain.com/en/stable/_modules/langchain/callbacks/aim_callback.html |
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