# agentic-ai-dev

> This skill provides patterns and templates for building production AI agents with Python 3.13, LangChain v1.2.8, LangGraph v1.0.7, and FastAPI 0.128.x. Use when creating AI agents, RAG systems, graph workflows, tools, memory systems, or agent tests.

- Author: kumaran Iyyasamy srinivasan
- Repository: kumaran-is/claude-code-onboarding
- Version: 20260204170321
- Stars: 0
- Forks: 0
- Last Updated: 2026-02-06
- Source: https://github.com/kumaran-is/claude-code-onboarding
- Web: https://mule.run/skillshub/@@kumaran-is/claude-code-onboarding~agentic-ai-dev:20260204170321

---

---
name: agentic-ai-dev
description: "This skill provides patterns and templates for building production AI agents with Python 3.13, LangChain v1.2.8, LangGraph v1.0.7, and FastAPI 0.128.x. Use when creating AI agents, RAG systems, graph workflows, tools, memory systems, or agent tests."
allowed-tools: Bash, Read, Write, Edit
---

# Agentic AI Development Skill — Python 3.13 + LangChain + LangGraph + FastAPI

## Quick Scaffold

```bash
uv init my-agent-service && cd my-agent-service
uv add "langchain-core>=1.2.8" "langchain-anthropic>=1.3.0" "langchain-openai>=1.1.0" "langgraph>=1.0.7" \
  "fastapi>=0.128.0" "uvicorn[standard]" pydantic pydantic-settings \
  langsmith prometheus-client structlog httpx asyncpg \
  "langgraph-checkpoint-postgres>=3.0.0"
uv add --dev pytest pytest-asyncio httpx ruff mypy
```

## Process

1. **Scaffold** — `uv init` + install dependencies
2. **Configure** — `core/config.py` with pydantic-settings, `.env`, structured logging
3. **Define State** — `TypedDict` with `Annotated[list, add_messages]` for each agent
4. **Build Graph** — `StateGraph` with typed nodes, conditional edges, checkpointing
5. **Define Tools** — `@tool` with docstrings, Pydantic input schemas, error handling
6. **Add Memory** — Checkpointing (PostgresSaver), semantic memory (vector store)
7. **Add Guardrails** — Input validation, prompt injection detection, output validation
8. **Expose API** — FastAPI routes for invoke/stream with `thread_id` propagation
9. **Write Tests** — Basic invoke, tool usage, iteration limit, error recovery, RAG quality
10. **Deploy** — Docker multi-stage, gunicorn + uvicorn, health checks, Prometheus

## Key Patterns

| Pattern | Implementation | Reference |
|---------|---------------|-----------|
| Agent Graphs | `StateGraph` + typed nodes + conditional edges | `agentic-templates-agents.md` |
| Tools | `@tool` + docstring + Pydantic input + try/except | `agentic-templates-tools.md` |
| LLM Binding | Factory function per provider, `.bind_tools()` | `agentic-llm-routing.md` |
| Routing | `Command(goto=...)` pattern (LangGraph) | `agentic-templates-agents.md` |
| Checkpointing | `PostgresSaver` (prod) / `MemorySaver` (test) | `agentic-memory-systems.md` |
| Streaming | `astream()` + `stream_mode` + FastAPI SSE | `agentic-streaming-hitl.md` |
| Human-in-the-Loop | `interrupt_before` + approval node | `agentic-streaming-hitl.md` |
| RAG | Embeddings → Vector Store → Retriever → Reranker | `agentic-templates-rag.md` |
| Guardrails | 12-layer pipeline: input → process → output | `agentic-guardrails-security.md` |
| Structured Output | `.with_structured_output(PydanticModel)` | `agentic-prompt-engineering.md` |
| Error Recovery | Retry node + fallback model + graceful degradation | `agentic-templates-agents.md` |
| Config | pydantic-settings + fail-fast validators | `agentic-config-project.md` |

## Conventions & Rules

> For package layout, LangGraph rules, and FastAPI integration rules, read `reference/agentic-conventions.md`

## Documentation Sources

Before generating code, consult these sources for current syntax and APIs:

| Source | URL / Tool | Purpose |
|--------|-----------|---------|
| LangGraph | `https://langchain-ai.github.io/langgraph/llms-full.txt` | StateGraph, nodes, edges, checkpointing APIs |
| Pydantic v2 | `https://docs.pydantic.dev/latest/llms-full.txt` | Model validation, settings, Field constraints |
| FastAPI / LangChain | `Context7` MCP | Latest LangChain tools, FastAPI patterns |

## Reference Files

| File | Content | When to Use |
|------|---------|-------------|
| `agentic-config-project.md` | pyproject.toml, .env, config, Docker, ruff/mypy | Project setup |
| `agentic-templates-core.md` | FastAPI app, main.py, routes, middleware, base state | Creating API layer |
| `agentic-templates-agents.md` | 6 LangGraph agent patterns (ReAct, Multi-Agent, Supervisor, Command, Sub-Graph, Error Recovery) | Building any agent |
| `agentic-templates-rag.md` | 6 RAG architectures + document ingestion pipeline | Building RAG systems |
| `agentic-templates-tools.md` | @tool patterns, MCP integration, retry/timeout | Defining agent tools |
| `agentic-guardrails-security.md` | 12-layer security framework | Adding safety layers |
| `agentic-memory-systems.md` | 7-layer memory hierarchy, practical implementations | Adding memory to agents |
| `agentic-streaming-hitl.md` | Streaming + Human-in-the-Loop patterns | Real-time responses, approval flows |
| `agentic-llm-routing.md` | Multi-provider routing, cost calculation, fallback chains | Multi-model setups |
| `agentic-observability.md` | LangSmith, Prometheus, structured logging | Monitoring and debugging |
| `agentic-testing.md` | Agent testing patterns, mocks, fixtures | Writing agent tests |
| `agentic-deployment.md` | Docker, docker-compose, production config | Deploying agents |
| `agentic-debugging.md` | Debugging playbook, common issues | Troubleshooting agents |
| `agentic-cost-optimization.md` | Cost management, budget caps, prompt optimization | Reducing LLM costs |
| `agentic-prompt-engineering.md` | Advanced prompting, structured output, templates | Writing better prompts |
| `agentic-error-handling.md` | Agent, tool, LLM provider, and API error handling patterns | Error handling in agents |

## Error Handling

> For error handling patterns and code examples, read `reference/agentic-error-handling.md`

**LLM provider errors**: Use retry with exponential backoff + fallback model chain. Never let provider errors crash the graph.

**Tool execution errors**: Wrap all `@tool` functions in try/except. Return structured error messages the LLM can reason about.

**Graph infinite loops**: Always include `iteration_count` in state and check it in the routing function.