# shopmate/reviews/monthly_report.py -- 200 reviews in, 3-minute report out
import anthropic, json
client = anthropic.Anthropic()

def generate_review_report(reviews: list[dict]) -> dict:
    """Analyse all ThreadCo reviews for the month and extract actionable insights."""
    reviews_text = "
".join(
        f"[{r['rating']}/5] {r['product']}: {r['text']}"
        for r in reviews
    )
    resp = client.messages.create(
        model="claude-sonnet-4-6", max_tokens=1500,
        system="""You are analysing customer reviews for ThreadCo, a T-shirt brand.
Produce an actionable monthly report for the founder.
Focus on patterns, not individual reviews.
Return ONLY valid JSON.""",
        messages=[{"role":"user","content":
            f"Analyse these {len(reviews)} reviews:

{reviews_text}

"
            'Return JSON: {"top_complaints":["..."],"top_praises":["..."],'
            '"sizing_issues":["..."],"product_suggestions":["..."],'
            '"average_rating":0.0,"summary":"2-3 sentences for the founder"}'
        }]
    )
    return json.loads(resp.content[0].text)

# Sample reviews
sample_reviews = [
    {"rating":5,"product":"Sunset Gradient Tee","text":"Softest tee I own, the colour is exactly as shown"},
    {"rating":2,"product":"Midnight Pocket Tee","text":"Runs small, ordered my usual size and it was tight"},
    {"rating":4,"product":"Wave Print Crop Tee","text":"Love the print but shipping took 2 weeks"},
    {"rating":3,"product":"Midnight Pocket Tee","text":"Nice quality but definitely size up"},
]
report = generate_review_report(sample_reviews)
print(json.dumps(report, indent=2))