Building LangChain/LangGraph Agent Endpoints via FastAPI

1. Deep Architecture

Agent reasoning loops can take seconds or minutes, which can tie up Django request threads. FastAPI uses non-blocking asynchronous loops to handle these requests, using internal APIs to communicate with Django.

2. The Feynman Gatekeeper

[KNOWLEDGE CHECK] Why should you run heavy AI agent loops in an isolated microservice instead of standard Django view threads?

3. The Code

# fastapi_app.py
from fastapi import FastAPI
from pydantic import BaseModel
import asyncio

app = FastAPI()

class ScriptPayload(BaseModel):
    text: str

@app.post("/analyze/")
async def analyze_script(payload: ScriptPayload):
    # Simulate agent step traversal loops
    await asyncio.sleep(2)
    return {"hook_evaluation": "Strong", "score": 88}

4. The Funnel

Stat Level-Up: Service Isolator (Lvl 1).
Sanjaya Integration: Route video script analysis requests to the FastAPI microservice.