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base.py — langchain Source File

Architecture documentation for base.py, a python file in the langchain codebase. 19 imports, 0 dependents.

File python CoreAbstractions RunnableInterface 19 imports 2 functions 2 classes

Entity Profile

Dependency Diagram

graph LR
  d38d05a1_8249_925c_6c83_6bec2124d52b["base.py"]
  2a7f66a7_8738_3d47_375b_70fcaa6ac169["logging"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 2a7f66a7_8738_3d47_375b_70fcaa6ac169
  67ec3255_645e_8b6e_1eff_1eb3c648ed95["re"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 67ec3255_645e_8b6e_1eff_1eb3c648ed95
  cfe2bde5_180e_e3b0_df2b_55b3ebaca8e7["collections.abc"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> cfe2bde5_180e_e3b0_df2b_55b3ebaca8e7
  8e2034b7_ceb8_963f_29fc_2ea6b50ef9b3["typing"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 8e2034b7_ceb8_963f_29fc_2ea6b50ef9b3
  f3bc7443_c889_119d_0744_aacc3620d8d2["langchain_core.callbacks"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> f3bc7443_c889_119d_0744_aacc3620d8d2
  ba43b74d_3099_7e1c_aac3_cf594720469e["langchain_core.language_models"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> ba43b74d_3099_7e1c_aac3_cf594720469e
  d758344f_537f_649e_f467_b9d7442e86df["langchain_core.messages"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> d758344f_537f_649e_f467_b9d7442e86df
  83d7c7fd_1989_762c_9cf3_cecb50ada22b["langchain_core.output_parsers"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 83d7c7fd_1989_762c_9cf3_cecb50ada22b
  e6b4f61e_7b98_6666_3641_26b069517d4a["langchain_core.prompts"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> e6b4f61e_7b98_6666_3641_26b069517d4a
  38bc5323_3713_7377_32f8_091293bea54b["langchain_core.retrievers"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 38bc5323_3713_7377_32f8_091293bea54b
  2ceb1686_0f8c_8ae0_36d1_7c0b702fda1c["langchain_core.runnables"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 2ceb1686_0f8c_8ae0_36d1_7c0b702fda1c
  6e58aaea_f08e_c099_3cc7_f9567bfb1ae7["pydantic"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 6e58aaea_f08e_c099_3cc7_f9567bfb1ae7
  91721f45_4909_e489_8c1f_084f8bd87145["typing_extensions"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 91721f45_4909_e489_8c1f_084f8bd87145
  01158a5b_b299_f45d_92e9_2a7433a1a91a["langchain_classic.chains.base"]
  d38d05a1_8249_925c_6c83_6bec2124d52b --> 01158a5b_b299_f45d_92e9_2a7433a1a91a
  style d38d05a1_8249_925c_6c83_6bec2124d52b fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

from __future__ import annotations

import logging
import re
from collections.abc import Sequence
from typing import Any

from langchain_core.callbacks import (
    CallbackManagerForChainRun,
)
from langchain_core.language_models import BaseLanguageModel
from langchain_core.messages import AIMessage
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import BasePromptTemplate
from langchain_core.retrievers import BaseRetriever
from langchain_core.runnables import Runnable
from pydantic import Field
from typing_extensions import override

from langchain_classic.chains.base import Chain
from langchain_classic.chains.flare.prompts import (
    PROMPT,
    QUESTION_GENERATOR_PROMPT,
    FinishedOutputParser,
)
from langchain_classic.chains.llm import LLMChain

logger = logging.getLogger(__name__)


def _extract_tokens_and_log_probs(response: AIMessage) -> tuple[list[str], list[float]]:
    """Extract tokens and log probabilities from chat model response."""
    tokens = []
    log_probs = []
    for token in response.response_metadata["logprobs"]["content"]:
        tokens.append(token["token"])
        log_probs.append(token["logprob"])
    return tokens, log_probs


class QuestionGeneratorChain(LLMChain):
    """Chain that generates questions from uncertain spans."""

    prompt: BasePromptTemplate = QUESTION_GENERATOR_PROMPT
    """Prompt template for the chain."""

    @classmethod
    @override
    def is_lc_serializable(cls) -> bool:
        return False

    @property
    def input_keys(self) -> list[str]:
        """Input keys for the chain."""
        return ["user_input", "context", "response"]


def _low_confidence_spans(
    tokens: Sequence[str],
    log_probs: Sequence[float],
// ... (252 more lines)

Domain

Subdomains

Functions

Classes

Dependencies

  • collections.abc
  • langchain_classic.chains.base
  • langchain_classic.chains.flare.prompts
  • langchain_classic.chains.llm
  • langchain_core.callbacks
  • langchain_core.language_models
  • langchain_core.messages
  • langchain_core.output_parsers
  • langchain_core.prompts
  • langchain_core.retrievers
  • langchain_core.runnables
  • langchain_openai
  • logging
  • math
  • numpy
  • pydantic
  • re
  • typing
  • typing_extensions

Source

Frequently Asked Questions

What does base.py do?
base.py is a source file in the langchain codebase, written in python. It belongs to the CoreAbstractions domain, RunnableInterface subdomain.
What functions are defined in base.py?
base.py defines 2 function(s): _extract_tokens_and_log_probs, _low_confidence_spans.
What does base.py depend on?
base.py imports 19 module(s): collections.abc, langchain_classic.chains.base, langchain_classic.chains.flare.prompts, langchain_classic.chains.llm, langchain_core.callbacks, langchain_core.language_models, langchain_core.messages, langchain_core.output_parsers, and 11 more.
Where is base.py in the architecture?
base.py is located at libs/langchain/langchain_classic/chains/flare/base.py (domain: CoreAbstractions, subdomain: RunnableInterface, directory: libs/langchain/langchain_classic/chains/flare).

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