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LangChain Model Inference (Python) · jeremylongshore | DecimalAI

ai mlby jeremylongshore

LangChain Model Inference (Python)

jeremylongshore/langchain-model-inference

Source jeremylongshore/claude-code-plugins-plus-skills ↗License MIT

Invoke Claude, GPT-4o, and Gemini through LangChain 1.0 without tripping on the content-block, token-accounting, and structured-output quirks that silently break production code.

SkillScore95Maintained

Automatic

AI Engineer packsaaslangchainlanggraph

Last verified 8/31/2026

What it changes

Passed 21 of 22 test cases with the skill, and 14 of 22 without it.

Without skill64%

With skill95%

Checks it passed that the model alone missed

Sets max_retries parameter to two
Passes method parameter equal to json_schema
Sets timeout parameter to thirty seconds on ChatOpenAI

and 4 more in the full report

7 fixed14 passed either way1 still failing0 broke

Pass-rate lift: +32 pp
Tokens: +95%
Agent turns: 0%
Response time: -15%

Model gemini-3.6-flashMeasured 8/31/2026v121 of 22 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/jeremylongshore-langchain-model-inference/SKILL.md https://app.decimal.ai/s/jeremylongshore-langchain-model-inference/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add jeremylongshore-langchain-model-inference, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/jeremylongshore-langchain-model-inference/ and pins it in .decimal/skills.lock

decimalai skills add jeremylongshore-langchain-model-inference

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/jeremylongshore-langchain-model-inference/SKILL.md https://app.decimal.ai/s/jeremylongshore-langchain-model-inference/SKILL.md

Raw file: /s/jeremylongshore-langchain-model-inference/SKILL.md ↗ · machine-readable summary at /s/jeremylongshore-langchain-model-inference.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 7

Prompt

I am configuring with_structured_output on ChatAnthropic using a Pydantic schema. Which output extraction method parameter should be passed for best reliability on Claude 3.5 and 4 models?

What was checked, without and with the skill
Checked	Without skill	With skill
Passes method parameter equal to json_schema	Missed	Passed

case-07 · gemini-3.6-flash · 8/31/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md216 lines6 files

LangChain Model Inference (Python)

Overview

AIMessage.content is a str on simple OpenAI calls and a list[dict] on Claude the instant any tool_use, thinking, or image block enters the response. Code that does message.content.lower() crashes with AttributeError: 'list' object has no attribute 'lower' — the #1 first-production-call LangChain 1.0 bug on Anthropic. And that is one of four separate "content shape" pitfalls in this skill:

P02 — AIMessage.content list-vs-string divergence
P03 — with_structured_output(method="function_calling") silently drops Optional[list[X]] fields on ~40% of real schemas
P05 — temperature=0 is not deterministic on Anthropic even though it is on OpenAI
P58 — Claude expects the system message at position 0; middleware that reorders messages makes it silently ignored

This skill walks through ChatAnthropic, ChatOpenAI, and ChatGoogleGenerativeAI initialization; model routing; token counting that is actually correct during streaming; content-block iteration; and a decision tree for with_structured_output methods that holds up on real schemas. Pin: langchain-core 1.0.x, langchain-anthropic 1.0.x, langchain-openai 1.0.x, langchain-google-genai 1.0.x. Pain-catalog anchors: P01, P02, P03, P04, P05, P53, P54, P58, P63, P64, P65.

Prerequisites

Python 3.10+
langchain-core >= 1.0, < 2.0
At least one provider package: pip install langchain-anthropic langchain-openai
Provider API key(s): ANTHROPIC_API_KEY, OPENAI_API_KEY, GOOGLE_API_KEY

Instructions

Step 1 — Initialize a chat model with explicit, version-safe defaults

from langchain_anthropic import ChatAnthropic
from langchain_openai import ChatOpenAI

Track record

Benchmark

21 / 22

test cases passed, vs 14 / 22 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/10/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

jeremylongshore / claude-code-plugins-plus-skills

skills/.curated/langchain-model-inference/SKILL.md

View on GitHub ↗

License MITImported 8/25/2026Version v1Bundled 5 files

More skills from the same source and nearby in the registry, with their headline benchmark lift.

Ready to supercharge your AI agents?

See it in action

What's inside

LangChain Model Inference (Python)

Overview

Prerequisites

Instructions

Step 1 — Initialize a chat model with explicit, version-safe defaults

Track record

Benchmark

Adoption

SkillSafety

Source

Related skills