claude

langchain-pack

Legacy LangChain integration skill pack with 24 skills covering chains, agents, RAG pipelines, memory, and LLM application development. Deprecated — use langchain-py-pack or langchain-ts-pack.

2 on GitHubby Jeremy Longshorev1.0.0MITupdated 6 months agosaas-packs
/

Plugin langchain-pack from marketplace claude-code-plugins-plus in flight505/skill-forge. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (24)

  • langchain-ci-integration

    Configure CI/CD for LangChain with GitHub Actions, mocked unit tests,

  • langchain-common-errors

    Diagnose and fix common LangChain errors and exceptions.

  • langchain-core-workflow-a

    Build LangChain LCEL chains with prompts, parsers, and composition.

  • langchain-core-workflow-b

    Build LangChain agents with tool calling for autonomous task execution.

  • langchain-cost-tuning

    Optimize LangChain API costs with token tracking, model tiering,

  • langchain-data-handling

    Implement LangChain RAG pipelines with document loaders, text splitters,

  • langchain-debug-bundle

    Collect LangChain debug evidence for troubleshooting and bug reports.

  • langchain-deploy-integration

    Deploy LangChain applications to production with LangServe,

  • langchain-enterprise-rbac

    Implement role-based access control for LangChain applications

  • langchain-hello-world

    Create a minimal working LangChain example with LCEL chains.

  • langchain-incident-runbook

    Incident response procedures for LangChain production issues:

  • langchain-install-auth

    Install and configure LangChain SDK with provider authentication.

  • langchain-local-dev-loop

    Configure LangChain local development workflow with testing and mocks.

  • langchain-migration-deep-dive

    Migrate to LangChain from raw OpenAI SDK, LlamaIndex, or custom LLM

  • langchain-multi-env-setup

    Configure LangChain across dev/staging/production environments

  • langchain-observability

    Set up comprehensive observability for LangChain applications

  • langchain-performance-tuning

    Optimize LangChain application performance: latency, throughput,

  • langchain-prod-checklist

    Production readiness checklist for LangChain applications.

  • langchain-rate-limits

    Implement LangChain rate limiting, retry strategies, and backoff.

  • langchain-reference-architecture

    Implement LangChain reference architecture for production systems:

  • langchain-sdk-patterns

    Apply production-ready LangChain SDK patterns for structured output,

  • langchain-security-basics

    Apply LangChain security best practices for production LLM apps.

  • langchain-upgrade-migration

    Upgrade LangChain SDK versions safely with import path migration,

  • langchain-webhooks-events

    Implement LangChain callback handlers, streaming, webhooks,

View source on GitHub tonsofskills.com

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