llm-integration-patterns

name	LLM Integration Patterns
description	How to identify and analyze LLM integration points across popular frameworks — OpenAI SDK, Anthropic SDK, LangChain, LlamaIndex, Vercel AI SDK
version	1.0.0

LLM Integration Patterns

Purpose

Teaches the recon-agent how to find system prompts, tool definitions, guardrails, and data flows in codebases using different LLM frameworks.

When to Use

• During code reconnaissance (recon-agent)
• When the user asks "where are the LLM integration points?"
• When analyzing a new codebase for the first time

Framework Detection

Framework	Detection Patterns
OpenAI	import openai, from openai, ChatCompletion, chat.completions.create
Anthropic	import Anthropic, from anthropic, messages.create, @anthropic-ai/sdk
LangChain	from langchain, ChatOpenAI, ConversationChain, AgentExecutor, @langchain
LlamaIndex	from llama_index, VectorStoreIndex, QueryEngine, ServiceContext
Vercel AI	import { streamText }, import { generateText }, useChat, from 'ai'

Methodology

1. Detect framework — Search for import patterns
2. Find system prompts — Framework-specific locations (see reference files)
3. Find tool definitions — Framework-specific registration patterns
4. Find guardrails — Content filters, validators, middleware
5. Trace data flows — User input → prompt → LLM → output

Reference Files

• OpenAI SDK Patterns
• Anthropic SDK Patterns
• LangChain Patterns
• LlamaIndex Patterns
• Vercel AI SDK Patterns