LangChain Configuration and Error Classes |

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RunnableConfig Configuration Options

Field	Type	Description
configurable	dict	Runtime configuration. Most commonly used: thread_id for Checkpointer
recursion_limit	int	Maximum recursion depth (default: 9999)
metadata	dict	Additional metadata
tags	list	List of tags for filtering and grouping tracing
callbacks	list	Callback handlers

Example

config = {
    "configurable": {"thread_id": "user-001"},
    "metadata": {"source": "web"},
    "tags": ["production", "chat"],
}

result = agent.invoke(inputs, config=config)

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Checkpointer Implementation Classes

Class	Import Path	Persistence
InMemorySaver	langgraph.checkpoint.memory	No
SqliteSaver	langgraph.checkpoint.sqlite	Yes
PostgresSaver	langgraph.checkpoint.postgres	Yes

Examples

# In-memory
from langgraph.checkpoint.memory import InMemorySaver

checkpointer = InMemorySaver()

# SQLite
from langgraph.checkpoint.sqlite import SqliteSaver

checkpointer = SqliteSaver.from_conn_string("checkpoints.db")

# PostgreSQL
# from langgraph.checkpoint.postgres import PostgresSaver
# checkpointer = PostgresSaver.from_conn_string("postgresql://...")

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Store Implementation Classes

Class	Import Path	Persistence
InMemoryStore	langgraph.store.memory	No
PostgresStore	langgraph.store.postgres	Yes

Examples

from langgraph.store.memory import InMemoryStore

store = InMemoryStore()

store.put(("namespace",), "key", {"data": "value"})

item = store.get(("namespace",), "key")

items = store.search(("namespace",))

store.delete(("namespace",), "key")

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Common Exception Classes

Exception	Source	Description
ToolException	langchain.tools	Exception within a tool. Agent can catch and re-decide
ImportError	Python built-in	Missing dependency package. Error message will suggest installation command
ValueError	Python built-in	Parameter validation failure or configuration error
NotImplementedError	Python built-in	Middleware method not implemented (e.g., only synchronous defined but asynchronous called)
StructuredOutputError	langchain.agents.structured_output	Structured output-related errors (format mismatch, multiple outputs, etc.)
StructuredOutputValidationError	langchain.agents.structured_output	Structured output validation failure
MultipleStructuredOutputsError	langchain.agents.structured_output	Model returned multiple structured outputs
TimeoutError	Python built-in / various SDKs	Request timeout

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LaunchDarkly Configuration Checklist

Check Item	Command / Method
Python Version	python --version (requires 3.10+)
LangChain Version	python -c "import langchain; print(langchain.__version__)"
Dependency Installation	pip list | grep langchain
API Key Configuration	python -c "import os; from dotenv import load_dotenv; load_dotenv(); print(os.getenv('DEEPSEEK_API_KEY', 'NOT SET')[:10])"
Model Connectivity	Send a simple request using init_chat_model() for testing

This tutorial’s API reference is based on LangChain v1.3.0. As LangChain is still rapidly evolving, it is recommended to consult the latest official documentation when using it to obtain up-to-date API information.