Langchain Architecture
This is a comprehensive reference for building LLM applications with LangChain's core primitives: agents, chains, memory systems, and document processing pipelines. You get concrete patterns for RAG implementations, custom tool integration, and multi-step workflows, plus practical guidance on choosing between memory types like ConversationBufferMemory for short chats versus ConversationSummaryMemory for longer sessions. The callback system examples and testing strategies are genuinely useful. Most valuable when you're architecting production LLM apps and need to understand how these components fit together, though the code samples assume you already know Python basics. It won't teach you LangChain from scratch, but it's solid for reference when implementing specific patterns.
- skills.sh installs
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- last updated
- Jun 3, 2026
Install
$ npx -y skills add sickn33/antigravity-awesome-skills --skill langchain-architecture --agent claude-codeInstalls into .claude/skills of the current project.
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Supporting material availability
This catalog copy contains the inline guidance below, but does not include the following supporting paths. They are external prerequisites, not bundled files:
<support-root>/references/agents.md<support-root>/references/memory.md<support-root>/references/chains.md<support-root>/references/document-processing.md<support-root>/references/callbacks.md<support-root>/assets/agent-template.py<support-root>/assets/memory-config.yaml<support-root>/assets/chain-example.py
Ask for the original supporting material or an existing installation before using a step that depends on these paths; this catalog does not identify a verified download source for them. Resolve each path relative to that installation, inspect its contents, and verify any applicable license and execution prerequisites. Do not run a command or claim a referenced procedure was followed until its required file exists. Do not fabricate the missing scripts or treat an unrelated file with the same name as equivalent. Independent steps fully documented here can proceed within the user’s authorized scope; report any dependent step as unavailable.
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- github.com/sickn33/antigravity-awesome-skills
- Categories
- Code Review & Quality, AI & Agent Building
- First seen
- Jun 3, 2026
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