id stringlengths 14 16 | text stringlengths 13 2.7k | source stringlengths 57 178 |
|---|---|---|
4e07f41e034f-0 | Source code for langchain.agents.agent_toolkits.office365.toolkit
from __future__ import annotations
from typing import TYPE_CHECKING, List
from langchain.agents.agent_toolkits.base import BaseToolkit
from langchain.pydantic_v1 import Field
from langchain.tools import BaseTool
from langchain.tools.office365.create_draf... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/office365/toolkit.html |
d51947dbd3f5-0 | Source code for langchain.agents.agent_toolkits.conversational_retrieval.openai_functions
from typing import Any, List, Optional
from langchain.agents.agent import AgentExecutor
from langchain.agents.openai_functions_agent.agent_token_buffer_memory import (
AgentTokenBufferMemory,
)
from langchain.agents.openai_fun... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/conversational_retrieval/openai_functions.html |
d51947dbd3f5-1 | steps or not. Intermediate steps refer to prior action/observation
pairs from previous questions. The benefit of remembering these is if
there is relevant information in there, the agent can use it to answer
follow up questions. The downside is it will take up more tokens.
me... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/conversational_retrieval/openai_functions.html |
d51947dbd3f5-2 | tools=tools,
memory=memory,
verbose=verbose,
return_intermediate_steps=remember_intermediate_steps,
**kwargs,
) | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/agent_toolkits/conversational_retrieval/openai_functions.html |
54d960f9c97d-0 | Source code for langchain.agents.chat.base
from typing import Any, List, Optional, Sequence, Tuple
from langchain.agents.agent import Agent, AgentOutputParser
from langchain.agents.chat.output_parser import ChatOutputParser
from langchain.agents.chat.prompt import (
FORMAT_INSTRUCTIONS,
HUMAN_MESSAGE,
SYSTE... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/chat/base.html |
54d960f9c97d-1 | return (
f"This was your previous work "
f"(but I haven't seen any of it! I only see what "
f"you return as final answer):\n{agent_scratchpad}"
)
else:
return agent_scratchpad
@classmethod
def _get_default_output_parser(cls, **kwarg... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/chat/base.html |
54d960f9c97d-2 | ]
if input_variables is None:
input_variables = ["input", "agent_scratchpad"]
return ChatPromptTemplate(input_variables=input_variables, messages=messages)
[docs] @classmethod
def from_llm_and_tools(
cls,
llm: BaseLanguageModel,
tools: Sequence[BaseTool],
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/chat/base.html |
75ec7ae6683a-0 | Source code for langchain.agents.chat.output_parser
import json
import re
from typing import Union
from langchain.agents.agent import AgentOutputParser
from langchain.agents.chat.prompt import FORMAT_INSTRUCTIONS
from langchain.schema import AgentAction, AgentFinish, OutputParserException
FINAL_ANSWER_ACTION = "Final A... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/chat/output_parser.html |
75ec7ae6683a-1 | return AgentFinish({"output": output}, text)
@property
def _type(self) -> str:
return "chat" | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/chat/output_parser.html |
fbec6f99dde1-0 | Source code for langchain.agents.mrkl.base
"""Attempt to implement MRKL systems as described in arxiv.org/pdf/2205.00445.pdf."""
from __future__ import annotations
from typing import Any, Callable, List, NamedTuple, Optional, Sequence
from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser
from langc... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
fbec6f99dde1-1 | return AgentType.ZERO_SHOT_REACT_DESCRIPTION
@property
def observation_prefix(self) -> str:
"""Prefix to append the observation with."""
return "Observation: "
@property
def llm_prefix(self) -> str:
"""Prefix to append the llm call with."""
return "Thought:"
[docs] @cl... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
fbec6f99dde1-2 | llm: BaseLanguageModel,
tools: Sequence[BaseTool],
callback_manager: Optional[BaseCallbackManager] = None,
output_parser: Optional[AgentOutputParser] = None,
prefix: str = PREFIX,
suffix: str = SUFFIX,
format_instructions: str = FORMAT_INSTRUCTIONS,
input_variable... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
fbec6f99dde1-3 | f"a description must always be provided."
)
super()._validate_tools(tools)
[docs]class MRKLChain(AgentExecutor):
"""[Deprecated] Chain that implements the MRKL system."""
[docs] @classmethod
def from_chains(
cls, llm: BaseLanguageModel, chains: List[ChainConfig], **kwargs: Any... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/mrkl/base.html |
cebfdb148fc0-0 | Source code for langchain.agents.mrkl.output_parser
import re
from typing import Union
from langchain.agents.agent import AgentOutputParser
from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
from langchain.schema import AgentAction, AgentFinish, OutputParserException
FINAL_ANSWER_ACTION = "Final Answer:"
MISS... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/mrkl/output_parser.html |
cebfdb148fc0-1 | end_index = text.find("\n\n", start_index)
return AgentFinish(
{"output": text[start_index:end_index].strip()}, text[:end_index]
)
else:
raise OutputParserException(
f"{FINAL_ANSWER_AND_PARSABLE_ACTION_ERROR_MESSAGE}: {t... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/mrkl/output_parser.html |
cebfdb148fc0-2 | raise OutputParserException(f"Could not parse LLM output: `{text}`")
@property
def _type(self) -> str:
return "mrkl" | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/mrkl/output_parser.html |
f80623bddd1b-0 | Source code for langchain.agents.react.base
"""Chain that implements the ReAct paper from https://arxiv.org/pdf/2210.03629.pdf."""
from typing import Any, List, Optional, Sequence
from langchain.agents.agent import Agent, AgentExecutor, AgentOutputParser
from langchain.agents.agent_types import AgentType
from langchain... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
f80623bddd1b-1 | super()._validate_tools(tools)
if len(tools) != 2:
raise ValueError(f"Exactly two tools must be specified, but got {tools}")
tool_names = {tool.name for tool in tools}
if tool_names != {"Lookup", "Search"}:
raise ValueError(
f"Tool names should be Lookup a... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
f80623bddd1b-2 | raise ValueError("Cannot lookup without a successful search first")
if term.lower() != self.lookup_str:
self.lookup_str = term.lower()
self.lookup_index = 0
else:
self.lookup_index += 1
lookups = [p for p in self._paragraphs if self.lookup_str in p.lower()]
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
f80623bddd1b-3 | if tool_names != {"Play"}:
raise ValueError(f"Tool name should be Play, got {tool_names}")
[docs]class ReActChain(AgentExecutor):
"""[Deprecated] Chain that implements the ReAct paper."""
def __init__(self, llm: BaseLanguageModel, docstore: Docstore, **kwargs: Any):
"""Initialize with the LL... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/react/base.html |
41bef2ccf4a5-0 | Source code for langchain.agents.react.output_parser
import re
from typing import Union
from langchain.agents.agent import AgentOutputParser
from langchain.schema import AgentAction, AgentFinish, OutputParserException
[docs]class ReActOutputParser(AgentOutputParser):
"""Output parser for the ReAct agent."""
[docs] ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/react/output_parser.html |
00890ac95c01-0 | Source code for langchain.agents.conversational_chat.base
"""An agent designed to hold a conversation in addition to using tools."""
from __future__ import annotations
from typing import Any, List, Optional, Sequence, Tuple
from langchain.agents.agent import Agent, AgentOutputParser
from langchain.agents.conversational... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
00890ac95c01-1 | @property
def llm_prefix(self) -> str:
"""Prefix to append the llm call with."""
return "Thought:"
@classmethod
def _validate_tools(cls, tools: Sequence[BaseTool]) -> None:
super()._validate_tools(tools)
validate_tools_single_input(cls.__name__, tools)
[docs] @classmethod
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
00890ac95c01-2 | ) -> List[BaseMessage]:
"""Construct the scratchpad that lets the agent continue its thought process."""
thoughts: List[BaseMessage] = []
for action, observation in intermediate_steps:
thoughts.append(AIMessage(content=action.log))
human_message = HumanMessage(
... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/base.html |
daab0c5388fc-0 | Source code for langchain.agents.conversational_chat.output_parser
from __future__ import annotations
from typing import Union
from langchain.agents import AgentOutputParser
from langchain.agents.conversational_chat.prompt import FORMAT_INSTRUCTIONS
from langchain.output_parsers.json import parse_json_markdown
from lan... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/output_parser.html |
daab0c5388fc-1 | # exception
raise OutputParserException(
f"Missing 'action' or 'action_input' in LLM output: {text}"
)
except Exception as e:
# If any other exception is raised during parsing, also raise an
# OutputParserException
raise Out... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/conversational_chat/output_parser.html |
18837e6fbfc6-0 | Source code for langchain.agents.format_scratchpad.log
from typing import List, Tuple
from langchain.schema.agent import AgentAction
[docs]def format_log_to_str(
intermediate_steps: List[Tuple[AgentAction, str]],
observation_prefix: str = "Observation: ",
llm_prefix: str = "Thought: ",
) -> str:
"""Cons... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/format_scratchpad/log.html |
7c3fc31a2cbf-0 | Source code for langchain.agents.format_scratchpad.openai_tools
import json
from typing import List, Sequence, Tuple
from langchain.agents.output_parsers.openai_tools import OpenAIToolAgentAction
from langchain.schema.agent import AgentAction
from langchain.schema.messages import (
AIMessage,
BaseMessage,
T... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/format_scratchpad/openai_tools.html |
7c3fc31a2cbf-1 | _create_tool_message(agent_action, observation)
]
messages.extend([new for new in new_messages if new not in messages])
else:
messages.append(AIMessage(content=agent_action.log))
return messages | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/format_scratchpad/openai_tools.html |
5bd7fa33ef89-0 | Source code for langchain.agents.format_scratchpad.xml
from typing import List, Tuple
from langchain.schema.agent import AgentAction
[docs]def format_xml(
intermediate_steps: List[Tuple[AgentAction, str]],
) -> str:
"""Format the intermediate steps as XML.
Args:
intermediate_steps: The intermediate ... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/format_scratchpad/xml.html |
53ccb0231581-0 | Source code for langchain.agents.format_scratchpad.log_to_messages
from typing import List, Tuple
from langchain.schema.agent import AgentAction
from langchain.schema.messages import AIMessage, BaseMessage, HumanMessage
[docs]def format_log_to_messages(
intermediate_steps: List[Tuple[AgentAction, str]],
templat... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/format_scratchpad/log_to_messages.html |
8295adf2a12d-0 | Source code for langchain.agents.format_scratchpad.openai_functions
import json
from typing import List, Sequence, Tuple
from langchain.schema.agent import AgentAction, AgentActionMessageLog
from langchain.schema.messages import AIMessage, BaseMessage, FunctionMessage
def _convert_agent_action_to_messages(
agent_ac... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/format_scratchpad/openai_functions.html |
8295adf2a12d-1 | """Convert (AgentAction, tool output) tuples into FunctionMessages.
Args:
intermediate_steps: Steps the LLM has taken to date, along with observations
Returns:
list of messages to send to the LLM for the next prediction
"""
messages = []
for agent_action, observation in intermediate_... | lang/api.python.langchain.com/en/latest/_modules/langchain/agents/format_scratchpad/openai_functions.html |
9924af10309d-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_aiter.html |
9924af10309d-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()),
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_aiter.html |
6e56302c2344-0 | Source code for langchain.callbacks.manager
from __future__ import annotations
import logging
from contextlib import contextmanager
from contextvars import ContextVar
from typing import (
Generator,
Optional,
)
from langchain.callbacks.openai_info import OpenAICallbackHandler
from langchain.callbacks.tracers.wa... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
6e56302c2344-1 | )
[docs]@contextmanager
def get_openai_callback() -> Generator[OpenAICallbackHandler, None, None]:
"""Get the OpenAI callback handler in a context manager.
which conveniently exposes token and cost information.
Returns:
OpenAICallbackHandler: The OpenAI callback handler.
Example:
>>> wit... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
6e56302c2344-2 | "CallbackManagerForRetrieverRun",
"AsyncCallbackManagerForRetrieverRun",
"CallbackManager",
"CallbackManagerForChainGroup",
"AsyncCallbackManager",
"AsyncCallbackManagerForChainGroup",
"tracing_enabled",
"tracing_v2_enabled",
"collect_runs",
"atrace_as_chain_group",
"trace_as_cha... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/manager.html |
2377302227fb-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_stdout_final_only.html |
2377302227fb-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_stdout_final_only.html |
93aee58072b0-0 | 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,
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
93aee58072b0-1 | "gpt-3.5-turbo": 0.0015,
"gpt-3.5-turbo-0301": 0.0015,
"gpt-3.5-turbo-0613": 0.0015,
"gpt-3.5-turbo-1106": 0.001,
"gpt-3.5-turbo-instruct": 0.0015,
"gpt-3.5-turbo-16k": 0.003,
"gpt-3.5-turbo-16k-0613": 0.003,
# GPT-3.5 output
"gpt-3.5-turbo-completion": 0.002,
"gpt-3.5-turbo-0301-com... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
93aee58072b0-2 | "gpt-35-turbo-0613": 0.0015,
"gpt-35-turbo-instruct": 0.0015,
"gpt-35-turbo-16k": 0.003,
"gpt-35-turbo-16k-0613": 0.003,
# Azure GPT-35 output
"gpt-35-turbo-completion": 0.002, # Azure OpenAI version of ChatGPT
"gpt-35-turbo-0301-completion": 0.002, # Azure OpenAI version of ChatGPT
"gpt-3... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
93aee58072b0-3 | "babbage-002-finetuned": 0.0016,
"davinci-002-finetuned": 0.012,
"gpt-3.5-turbo-0613-finetuned": 0.012,
# Fine Tuned output
"babbage-002-finetuned-completion": 0.0016,
"davinci-002-finetuned-completion": 0.012,
"gpt-3.5-turbo-0613-finetuned-completion": 0.016,
# Azure Fine Tuned input
"b... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
93aee58072b0-4 | is_completion: bool = False,
) -> str:
"""
Standardize the model name to a format that can be used in the OpenAI API.
Args:
model_name: Model name to standardize.
is_completion: Whether the model is used for completion or not.
Defaults to False.
Returns:
Standardized ... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
93aee58072b0-5 | """
model_name = standardize_model_name(model_name, is_completion=is_completion)
if model_name not in MODEL_COST_PER_1K_TOKENS:
raise ValueError(
f"Unknown model: {model_name}. Please provide a valid OpenAI model name."
"Known models are: " + ", ".join(MODEL_COST_PER_1K_TOKENS.ke... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
93aee58072b0-6 | """Print out the token."""
pass
[docs] def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:
"""Collect token usage."""
if response.llm_output is None:
return None
self.successful_requests += 1
if "token_usage" not in response.llm_output:
re... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/openai_info.html |
169f5caba2fc-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/confident_callback.html |
169f5caba2fc-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/confident_callback.html |
169f5caba2fc-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/confident_callback.html |
169f5caba2fc-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/confident_callback.html |
218e22867f05-0 | Source code for langchain.callbacks.llmonitor_callback
import importlib.metadata
import logging
import os
import traceback
import warnings
from contextvars import ContextVar
from typing import Any, Dict, List, Union, cast
from uuid import UUID
import requests
from packaging.version import parse
from langchain.callbacks... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-1 | """Builds an LLMonitor UserContextManager
Parameters:
- `user_id`: The user id.
- `user_props`: The user properties.
Returns:
A context manager that sets the user context.
"""
return UserContextManager(user_id, user_props)
def _serialize(obj: Any) -> Union[Dict[str, Any], List[An... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-2 | return _serialize(raw_output)
text_value = raw_output.get("text")
output_value = raw_output.get("output")
output_text_value = raw_output.get("output_text")
answer_value = raw_output.get("answer")
result_value = raw_output.get("result")
if text_value:
return text_value
if answer_value... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-3 | for key in keys
if message.additional_kwargs.get(key) is not None
}
)
return parsed
def _parse_lc_messages(messages: Union[List[BaseMessage], Any]) -> List[Dict[str, Any]]:
return [_parse_lc_message(message) for message in messages]
[docs]class LLMonitorCallbackHandler(BaseCallbackHandle... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-4 | api_url: Union[str, None] = None,
verbose: bool = False,
) -> None:
super().__init__()
self.__has_valid_config = True
try:
import llmonitor
self.__llmonitor_version = importlib.metadata.version("llmonitor")
self.__track_event = llmonitor.track_even... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-5 | if self.__has_valid_config is False:
return None
try:
res = requests.get(f"{self.__api_url}/api/app/{self.__app_id}")
if not res.ok:
raise ConnectionError()
except Exception:
logger.warning(
f"""[LLMonitor] Could not connect... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-6 | self.__track_event(
"llm",
"start",
user_id=user_id,
run_id=str(run_id),
parent_run_id=str(parent_run_id) if parent_run_id else None,
name=name,
input=input,
tags=tags,
extra=e... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-7 | param: params.get(param)
for param in PARAMS_TO_CAPTURE
if params.get(param) is not None
}
input = _parse_lc_messages(messages[0])
self.__track_event(
"llm",
"start",
user_id=user_id,
run_... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-8 | output=parsed_output,
token_usage={
"prompt": token_usage.get("prompt_tokens"),
"completion": token_usage.get("completion_tokens"),
},
app_id=self.__app_id,
)
except Exception as e:
logger.error(f"[LL... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-9 | parent_run_id: Union[UUID, None] = None,
tags: Union[List[str], None] = None,
**kwargs: Any,
) -> None:
if self.__has_valid_config is False:
return
try:
self.__track_event(
"tool",
"end",
run_id=str(run_id),
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-10 | type = "chain"
user_id = _get_user_id(metadata)
user_props = _get_user_props(metadata)
input = _parse_input(inputs)
self.__track_event(
type,
"start",
user_id=user_id,
run_id=str(run_id),
pare... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-11 | ) -> Any:
if self.__has_valid_config is False:
return
try:
name = action.tool
input = _parse_input(action.tool_input)
self.__track_event(
"tool",
"start",
run_id=str(run_id),
parent_run_id=str... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-12 | return
try:
self.__track_event(
"chain",
"error",
run_id=str(run_id),
parent_run_id=str(parent_run_id) if parent_run_id else None,
error={"message": str(error), "stack": traceback.format_exc()},
app_id=se... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
218e22867f05-13 | parent_run_id=str(parent_run_id) if parent_run_id else None,
error={"message": str(error), "stack": traceback.format_exc()},
app_id=self.__app_id,
)
except Exception as e:
logger.error(f"[LLMonitor] An error occurred in on_llm_error: {e}")
__all__ = ["LLMo... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/llmonitor_callback.html |
d08eb55b07a7-0 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/file.html |
d08eb55b07a7-1 | ) -> 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,
**... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/file.html |
a2751fd82df9-0 | Source code for langchain.callbacks.arize_callback
from datetime import datetime
from typing import Any, Dict, List, Optional
from langchain.callbacks.base import BaseCallbackHandler
from langchain.callbacks.utils import import_pandas
from langchain.schema import AgentAction, AgentFinish, LLMResult
[docs]class ArizeCal... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/arize_callback.html |
a2751fd82df9-1 | 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,... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/arize_callback.html |
a2751fd82df9-2 | 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.... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/arize_callback.html |
a2751fd82df9-3 | "completion_token",
"total_token",
],
prompt_column_names=prompt_columns,
response_column_names=response_columns,
)
response_from_arize = self.arize_client.log(
dataframe=df,
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/arize_callback.html |
a2751fd82df9-4 | output: str,
observation_prefix: Optional[str] = None,
llm_prefix: Optional[str] = None,
**kwargs: Any,
) -> None:
pass
[docs] def on_tool_error(self, error: BaseException, **kwargs: Any) -> None:
pass
[docs] def on_text(self, text: str, **kwargs: Any) -> None:
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/arize_callback.html |
ec5a81de6def-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_stdout.html |
ec5a81de6def-1 | ) -> None:
"""Run when chain starts running."""
[docs] def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> None:
"""Run when chain ends running."""
[docs] def on_chain_error(self, error: BaseException, **kwargs: Any) -> None:
"""Run when chain errors."""
[docs] def on_tool... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/streaming_stdout.html |
75d95966b7cf-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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:
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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>
""",
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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:
"""... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-10 | )
complexity_metrics_columns = []
visualizations_columns = []
if self.complexity_metrics:
complexity_metrics_columns = [
"flesch_reading_ease",
"flesch_kincaid_grade",
"smog_index",
"coleman_liau_index",
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
75d95966b7cf-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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/wandb_callback.html |
1b6ba24f9219-0 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
1b6ba24f9219-1 | 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()... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
1b6ba24f9219-2 | """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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
1b6ba24f9219-3 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
1b6ba24f9219-4 | 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... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
1b6ba24f9219-5 | }
[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
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/utils.html |
c4d7491a702e-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,... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
c4d7491a702e-1 | <Rating name="rating" toName="prompt"/>
</View>""",
LabelStudioMode.CHAT.value: """
<View>
<View className="root">
<Paragraphs name="dialogue"
value="$prompt"
layout="dialogue"
textKey="content"
nameKey="role"
granularity="sentence"... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
c4d7491a702e-2 | ... )
>>> llm = OpenAI(callbacks=[handler])
>>> llm.predict('Tell me a story about a dog.')
"""
DEFAULT_PROJECT_NAME: str = "LangChain-%Y-%m-%d"
[docs] def __init__(
self,
api_key: Optional[str] = None,
url: Optional[str] = None,
project_id: Optional[int] = Non... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
c4d7491a702e-3 | f"Use the key as a parameter for the callback: "
f"{self.__class__.__name__}"
f"(label_studio_api_key='<your_key_here>', ...) or "
f"set the environment variable LABEL_STUDIO_API_KEY=<your_key_here>"
)
self.api_key = api_key
if ... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
c4d7491a702e-4 | if existing_projects:
self.ls_project = existing_projects[0]
self.project_id = self.ls_project.id
else:
self.ls_project = self.ls_client.create_project(
title=project_title, label_config=self.project_config
)
... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
c4d7491a702e-5 | "Labeling Interface -> Browse Templates"
" and check available templates under "
'"Generative AI" section.'
)
raise ValueError(error_message)
[docs] def add_prompts_generations(
self, run_id: str, generations: List[List[Generation]]
) ->... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
c4d7491a702e-6 | f'To make it work with the mode="chat", '
f"the input type should be <Text>.\n"
f"Read more here https://labelstud.io/tags/text"
)
run_id = str(kwargs["run_id"])
self.payload[run_id] = {"prompts": prompts, "kwargs": kwargs}
def _get_message_role(self, mess... | lang/api.python.langchain.com/en/latest/_modules/langchain/callbacks/labelstudio_callback.html |
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