from fastapi import FastAPI
from pydantic import BaseModel
from openai import OpenAI
import uvicorn

app = FastAPI()

# =========================
# OPENAI CLIENT
# =========================
client = OpenAI()  # uses OPENAI_API_KEY from environment / HF Secrets

# =========================
# REQUEST BODY
# =========================
class TextIn(BaseModel):
    text: str


# =========================
# CORE MODERATION FUNCTION
# =========================
def analyze_text(text: str):
    try:
        response = client.moderations.create(
            model="omni-moderation-latest",
            input=text
        )

        result = response.results[0]

        return {
            "input": text,
            "flagged": result.flagged,
            "categories": result.categories.model_dump(),
            "category_scores": result.category_scores.model_dump()
        }

    except Exception as e:
        return {
            "input": text,
            "error": str(e),
            "flagged": False
        }


# =========================
# GET ENDPOINT
# =========================
@app.get("/analyze")
def analyze_get(text: str):
    return analyze_text(text)


# =========================
# POST ENDPOINT
# =========================
@app.post("/analyze")
def analyze_post(body: TextIn):
    return analyze_text(body.text)


# =========================
# ROOT
# =========================
@app.get("/")
def root():
    return {
        "status": "ok",
        "usage": "/analyze?text=your_text_here"
    }


# =========================
# RUN (for local testing only)
# =========================
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=7860)