Langchain Common Errors

LangChain Common Errors (Python)

Overview

The same twelve-plus LangChain 1.0 / LangGraph 1.0 tracebacks show up every week in production: ImportError: cannot import name 'ChatOpenAI' from 'langchain.chat_models', AttributeError: 'list' object has no attribute 'lower', GraphRecursionError: Recursion limit of 25 reached, TypeError: Object of type datetime is not JSON serializable, KeyError: 'question' deep in LCEL internals. Stack traces are ambiguous, docs sprawl across 0.2 / 0.3 / 1.0 eras, and engineers lose 30–90 minutes per incident re-deriving the fix.

This skill is a paste-match catalog of 14 entries (E01–E14) grouped into 3 reference files by category, plus a triage decision tree. Every entry opens with the exact exception class and message string you see in your terminal, names the cause in one sentence with a pain-catalog code, and gives a one-line fix or a reference-file pointer. Pinned to langchain-core 1.0.x, langchain 1.0.x, langgraph 1.0.x, verified 2026-04-21.

Pain-catalog anchors: P02, P06, P09, P10, P16, P17, P38, P39, P40, P41, P42, P55, P56, P57, P66.

Prerequisites

• Python 3.10+
• A traceback or a reproducible bug — this skill is diagnostic, not preventive
• langchain-core >= 1.0, < 2.0, langgraph >= 1.0, < 2.0, and any provider integration packages pinned to 1.0.x
• anthropic >= 0.42 when using langchain-anthropic 1.0 (see E06)

Instructions

1. Triage first. Read the first line of the traceback. Look up the exception class in the catalog below or in Triage Decision Tree.
2. Match the message string, not the call site. Each catalog entry opens with the literal message pattern you see.
3. Apply the named fix. If the entry points to a reference file, read that file for the deep walk-through including codemods, before/after code, and adjacent traps. Otherwise use the one-line fix here.
4. Verify with a test. Every catalog entry names a test that will catch the error in CI next time.
5. If no match: check docs/pain-catalog.md for the exception class name or a message substring. Do not add speculative fixes here without catalog evidence.

Catalog

Each entry is indexed as E## — ClassName: "message pattern" with a one-line cause (pain-catalog code) and a one-line fix or reference pointer.

Category A — Import & migration errors (0.2 / 0.3 → 1.0)

Full detail, before/after code, codemod commands: import-migration.md.

E01 — ImportError: cannot import name 'ChatOpenAI' from 'langchain.chat_models'

• Cause: Top-level langchain.chat_models / langchain.llms re-exports removed in 1.0 (P38).
• Fix: from langchain_openai import ChatOpenAI. Run python -m langchain_cli migrate for automated rewrites. See E01 in import-migration.md.

E02 — AttributeError: module 'langchain' has no attribute 'LLMChain'

• Cause: Legacy chain classes (LLMChain, SequentialChain, TransformChain) removed in 1.0 in favor of LCEL (P39).
• Fix: chain = prompt | llm | StrOutputParser(); .run(x) becomes .invoke({"input": x}). See E02 in import-migration.md.

E03 — ImportError: cannot import name 'ConversationBufferMemory'

• Cause: All legacy memory classes removed in 1.0; LangGraph checkpointing is the replacement (P40).
• Fix: Use InMemorySaver / PostgresSaver + thread_id via LangGraph create_react_agent. See E03 in import-migration.md.

E04 — ImportError: cannot import name 'initialize_agent'

• Cause: Legacy agent factories (initialize_agent, AgentType, create_openai_functions_agent) removed in 1.0 (P41).
• Fix: from langgraph.prebuilt import create_react_agent; create_react_agent(model=llm, tools=tools, checkpointer=InMemorySaver()). See E04 in import-migration.md.

E05 — AttributeError: 'AgentAction' object has no attribute 'tool_name' (or inverse)

• Cause: Legacy AgentAction / AgentFinish shape replaced by ToolCall objects; fields renamed .tool → .tool_name, .tool_input → .args (P42).
• Fix: Access tool_call["name"] / tool_call["args"] on message .tool_calls, not result["intermediate_steps"]. See E05 in import-migration.md.

E06 — KeyError: 'input' inside tool_use block parsing

• Cause: langchain-anthropic >= 1.0 requires anthropic >= 0.40; SDK tool-use schema changed (P66).
• Fix: pip install "langchain-anthropic>=1.0,<2.0" "anthropic>=0.42,<1.0" in the same commit. See E06 in import-migration.md.

Category B — Content-shape & prompt-template errors

Full detail, block-iterator extractor, jinja2 escape pattern: content-shape.md.

E07 — AttributeError: 'list' object has no attribute 'lower' (or .strip, .split, .format)

• Cause: AIMessage.content is list[dict] on Claude with any non-text block and on OpenAI once tools are bound (P02).
• Fix: Use msg.text() (LangChain 1.0+) or iterate and filter block["type"] == "text". See E07 in content-shape.md.

E08 — KeyError: '<var>' inside runnables/passthrough.py or runnables/base.py

• Cause: LCEL dict-shape mismatch between runnable stages; error surfaces at the consumer, not the producer (P06).
• Fix: Insert RunnableLambda debug probes between stages and enable set_debug(True). See E08 in content-shape.md.

E09 — KeyError: '<var>' inside prompts/chat.py or prompts/prompt.py on user input

• Cause: ChatPromptTemplate.from_messages defaults to f-string parsing; user-provided { / } characters are parsed as template variables (P57).
• Fix: Use MessagesPlaceholder("history") for variable content, or template_format="jinja2" for free-text templates, or escape literals as {{ / }}. See E09 in content-shape.md.

Category C — Agent & graph execution traps

Full detail, diagnostic callbacks, thread_id middleware, router asserts: graph-traps.md.

E10 — GraphRecursionError: Recursion limit of 25 reached without hitting a stop condition

• Cause: create_react_agent and StateGraph.compile() default recursion_limit=25 counts supersteps, not loop iterations; vague prompts never converge (P10, P55).
• Fix: Set recursion_limit=10 for interactive use; add terminal edge on repeated tool-call names. See E10 in graph-traps.md.

E11 — AgentExecutor returns "I couldn't find the answer" on every tool call, no exception

• Cause: handle_parsing_errors=True catches tool exceptions and passes str(exc) (often empty) as observation; loop continues without signal (P09).
• Fix: return_intermediate_steps=True, handle_parsing_errors=False or migrate to LangGraph create_react_agent. See E11 in graph-traps.md.

E12 — Multi-turn chat forgets everything between calls, no exception

• Cause: LangGraph checkpointers key state by config["configurable"]["thread_id"]; omitted thread_id means every invocation gets a fresh state with no warning (P16).
• Fix: Require thread_id at app boundary; wrap in middleware that raises on missing key. See E12 in graph-traps.md.

E13 — TypeError: Object of type <datetime / bytes / Decimal / set> is not JSON serializable

• Cause: InMemorySaver / PostgresSaver / SqliteSaver serialize state as JSON on every superstep; non-primitives break at interrupt or checkpoint boundary (P17).
• Fix: Keep state JSON-primitive only (str/int/float/bool/list/dict); serialize at node boundaries; or use JsonPlusSerializer for Pydantic v2. See E13 in graph-traps.md.

E14 — Graph halts without reaching END, no exception, no log

• Cause: add_conditional_edges(node, router, path_map) where router returns a string not in path_map causes silent termination on some 1.0 versions (P56).
• Fix: assert router_return in path_map; always include END explicitly; inspect graph.get_state(cfg).next. See E14 in graph-traps.md.

Output

• Named cause tied to a P## pain-catalog code for every traceback
• Named fix (one-line or a reference-file walk-through) tied to E## catalog entry
• A regression test pattern that catches the error in CI next time
• Triage path recorded for the incident retro (which entry matched, how long it took)

Error Handling

This skill is the error-handling reference for the pack. The triage workflow:

1. First line of traceback → pick category in the table below.
2. Exception class + message substring → pick E## entry above.
3. Reference file → read the deep walk-through for before/after code and tests.

For tracebacks that do not match: consult triage-decision-tree.md for the full routing flowchart, then docs/pain-catalog.md for any remaining pain codes. Escalate to the main thread before adding speculative fixes.

Examples

Example 1 — ImportError on a 0.3 → 1.0 upgrade

Incoming traceback:

Traceback (most recent call last):
  File "app.py", line 3, in <module>
    from langchain.chat_models import ChatOpenAI
ImportError: cannot import name 'ChatOpenAI' from 'langchain.chat_models'

Triage:

1. First line is ImportError from langchain.chat_models → Category A.
2. Matches E01 exactly.
3. Cause: top-level re-exports removed in 1.0 (P38).
4. Fix: rewrite imports and bump provider packages.

pip install "langchain-openai>=1.0,<2.0" "langchain-anthropic>=1.0,<2.0" "langchain-cli>=0.1"
python -m langchain_cli migrate src/

# Before
from langchain.chat_models import ChatOpenAI

# After
from langchain_openai import ChatOpenAI

Re-run tests. Next failure is almost always E07 (AIMessage.content shape) once the imports resolve — walk that one next from content-shape.md.

Example 2 — GraphRecursionError triage

Incoming traceback:

Traceback (most recent call last):
  File "worker.py", line 88, in run
    result = agent.invoke({"messages": [("user", q)]}, config=cfg)
  ...
langgraph.errors.GraphRecursionError: Recursion limit of 25 reached without hitting a stop condition. You can increase the limit by setting the `recursion_limit` config key.

Triage:

1. Exception class is GraphRecursionError → Category C.
2. Matches E10 exactly.
3. Cause: vague prompt or tool loop; default recursion_limit=25 (P10, P55).
4. Before raising the limit, diagnose first — attach a StepLogger callback (see graph-traps.md § E10) and count real steps. If the same two node names alternate, it is a convergence bug, not a budget bug.

Fix (budget only):

cfg = {"configurable": {"thread_id": tid}, "recursion_limit": 10}
agent.invoke(inp, config=cfg)

Fix (convergence + budget):

def _should_stop(state):
    recent = [m for m in state["messages"][-6:] if getattr(m, "tool_calls", None)]
    if len(recent) >= 3 and all(
        r.tool_calls[0]["name"] == recent[0].tool_calls[0]["name"] for r in recent
    ):
        return "end"
    return "continue"

graph.add_conditional_edges("agent", _should_stop, {"continue": "agent", "end": END})

Pair with a per-session token-budget middleware from langchain-cost-tuning.

Resources

• Pack pain catalog: docs/pain-catalog.md — canonical entries for P02, P06, P09, P10, P16, P17, P38, P39, P40, P41, P42, P55, P56, P57, P66
• Import & migration errors — E01–E06
• Content-shape & prompt errors — E07–E09
• Agent & graph execution traps — E10–E14
• Triage decision tree — ASCII flowchart + quick-match table
• LangChain 1.0 release notes
• LangChain migration guide
• LangGraph concepts
• langchain-cli migrate command
• create_react_agent reference