Build the FastAPI Backend

Build the backend API that receives documents, calls Claude, and returns structured analysis. By the end, you'll have a working AI endpoint you can call with curl or Postman.

~1 hour Hands-on Precision AI Academy

Today's Objective

A complete FastAPI backend: document analysis endpoint that calls Claude, structured JSON response with summary, key points, and sentiment, and error handling for all failure modes.

code

from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import anthropic, json

app = FastAPI()
app.add_middleware(CORSMiddleware,
    allow_origins=["http://localhost:3000"],
    allow_methods=["*"], allow_headers=["*"])
client = anthropic.Anthropic()

class AnalyzeRequest(BaseModel):
    text: str

@app.post("/analyze")
def analyze(req: AnalyzeRequest):
    if not req.text.strip():
        raise HTTPException(400, "text is required")

    msg = client.messages.create(
        model="claude-sonnet-4-20250514",
        max_tokens=1024,
        system="Analyze the provided text. Return JSON only: {summary, key_points: [], sentiment, word_count, reading_time_minutes}",
        messages=[{"role": "user", "content": req.text}]
    )
    try:
        return json.loads(msg.content[0].text)
    except json.JSONDecodeError:
        return {"summary": msg.content[0].text, "key_points": []}

Test the Endpoint

bash

$ curl -X POST http://localhost:8000/analyze   -H "Content-Type: application/json"   -d '{"text": "Artificial intelligence is transforming industries worldwide. Companies that adopt AI early gain significant competitive advantages. However, implementation requires careful planning and expertise."}'

Also visit http://localhost:8000/docs and test from the interactive UI. Verify the JSON response has all the expected fields.

JSON parsing tip: Instruct Claude to start its response with an opening brace: add to the system prompt "Start your response with {" — this almost eliminates cases where Claude adds text before the JSON.

Add More Endpoints

backend/main.py (additions)

python

@app.post("/summarize")
def summarize(req: AnalyzeRequest):
    msg = client.messages.create(
        model="claude-sonnet-4-20250514",
        max_tokens=512,
        system="Summarize in 3 sentences or less. Output only the summary.",
        messages=[{"role": "user", "content": req.text}]
    )
    return {"summary": msg.content[0].text}

@app.post("/questions")
def generate_questions(req: AnalyzeRequest):
    msg = client.messages.create(
        model="claude-sonnet-4-20250514",
        max_tokens=512,
        system="Generate 5 thoughtful questions about this text. Return JSON: {questions: []}",
        messages=[{"role": "user", "content": req.text}]
    )
    return json.loads(msg.content[0].text)

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Day 2 Checkpoint

Before moving on, confirm understanding of these key concepts:

What is the core concept introduced in this lesson?
How does the main technique or tool work in practice?
What common mistakes should be avoided?
How would this apply in a real-world project?
What is the next logical step to build on this knowledge?

Build the FastAPI Backend

Today's Objective

Test the Endpoint

Add More Endpoints

Supporting References & Reading

Go deeper with these external resources.

Day 2 Checkpoint