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LangChain

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LangChain

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Glossary

langchain-ai/langchain

Glossary

Vocabulary used throughout the codebase, with pointers to the source.

Term Meaning
Runnable The universal invocation protocol for everything that takes an input and returns an output: models, parsers, prompts, retrievers, agents, even functions wrapped in RunnableLambda. Defined in libs/core/langchain_core/runnables/base.py.
LCEL LangChain Expression Language — the | operator and helpers that compose Runnable objects into pipelines. prompt | model | parser produces a RunnableSequence.
BaseChatModel The interface every chat-style model implements. The legacy class is BaseChatModel in libs/core/langchain_core/language_models/chat_models.py; the new streaming-first contract is BaseChatModelV1 in chat_model_stream.py. Partners typically subclass one of these via the _compat_bridge.py shim.
BaseLLM The older completion-style model interface, in libs/core/langchain_core/language_models/llms.py. New integrations prefer BaseChatModel.
Message A turn in a conversation: HumanMessage, AIMessage, SystemMessage, ToolMessage, FunctionMessage, ChatMessage, plus their *Chunk streaming counterparts. See libs/core/langchain_core/messages/.
Content block A typed piece of message content introduced in v1: TextContentBlock, ImageContentBlock, AudioContentBlock, VideoContentBlock, ReasoningContentBlock, ToolCall, ServerToolCall, Citation, Annotation. The taxonomy lives in libs/core/langchain_core/messages/content.py.
Tool A callable wrapped with input/output schemas the model can invoke. BaseTool and the @tool decorator are in libs/core/langchain_core/tools/.
Tool call The model's request to execute a tool. Represented as ToolCall in libs/core/langchain_core/messages/tool.py; appears as part of an AIMessage's content.
ToolNode The langgraph node that actually runs tools. langchain.agents constructs a ToolNode from the tools passed to create_agent.
Prompt template A parameterized prompt: PromptTemplate (string), ChatPromptTemplate (messages), few-shot variants. See libs/core/langchain_core/prompts/.
Output parser A Runnable that turns model output into a typed value. Includes JsonOutputParser, PydanticOutputParser, StrOutputParser, OutputFixingParser. See libs/core/langchain_core/output_parsers/.
Callback The observability protocol — CallbackHandler methods receive events for every LLM/tool/chain start, end, and error. Manager classes (CallbackManager) propagate config through nested runs. See libs/core/langchain_core/callbacks/.
Tracer A specialized callback handler that builds a tree of runs for LangSmith. See libs/core/langchain_core/tracers/.
LangSmith The hosted observability/eval platform. langchain-core depends on the langsmith SDK directly so that traces flow without extra setup.
LangGraph A separate library for low-level agent orchestration via StateGraph. langchain.agents.create_agent builds on top of it.
Agent In v1, the result of langchain.agents.create_agent(...) — a compiled langgraph graph that wraps a model + tools + middleware loop. In langchain-classic, Agent referred to legacy MRKL/ReAct/OpenAI-functions agents.
Middleware A v1 concept implementing AgentMiddleware. Hooks include before_agent, before_model, wrap_model_call, wrap_tool_call, after_model, after_agent. Built-ins live in libs/langchain_v1/langchain/agents/middleware/.
Structured output Constraining a model's reply to a schema. ToolStrategy, ProviderStrategy, AutoStrategy in libs/langchain_v1/langchain/agents/structured_output.py implement different strategies.
Provider A model vendor (OpenAI, Anthropic, …). The _BUILTIN_PROVIDERS registry in libs/langchain_v1/langchain/chat_models/base.py maps a provider key to a (module, class, ctor) tuple used by init_chat_model.
Partner package A LangChain-maintained integration package, e.g. langchain-openai, langchain-anthropic. Source under libs/partners/<provider>/.
Community The langchain-community package (separate repository) collecting third-party-contributed integrations. langchain-classic re-exports many of them.
Model profile A capability descriptor (context window, supports vision, supports tools, pricing) shipped as JSON in each partner's data/ directory and refreshed by the langchain-profiles CLI. Accessed at runtime via BaseChatModel.profile.
Standard tests The shared test base classes in libs/standard-tests/langchain_tests/. Every partner package inherits from them.
Indexing API The deduplicating vector-store loader in libs/langchain/langchain_classic/indexes/ (legacy) and libs/core/langchain_core/indexing/ (new).
Self-query retriever A retriever that uses an LLM to translate natural language into a structured filter against a vector store. See libs/langchain/langchain_classic/retrievers/self_query/.
Hub The LangSmith Hub of shared prompts. Loaded via langchain_classic.hub.pull (libs/langchain/langchain_classic/hub.py).
Serializable A subclass of langchain_core.load.serializable.Serializable whose instances can be JSON-encoded and re-hydrated. Used for chains, prompts, and many runnables.
VCR test A test that records and replays HTTP interactions via vcrpy. The _test_vcr.yml workflow runs them.
Snapshot test A test using syrupy that asserts an output matches a pre-recorded snapshot.
Conventional commits The PR/commit title format the repo enforces (feat(scope): ..., fix(scope): ...). See .github/workflows/pr_lint.yml for allowed types and scopes.

Acronyms

Acronym Expansion
LLM Large language model
LCEL LangChain Expression Language
RAG Retrieval-augmented generation
HITL Human-in-the-loop
PII Personally identifiable information
MRKL Modular Reasoning, Knowledge and Language (the original LangChain agent pattern)
ReAct Reason + Act prompting pattern

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