Analyze the following product listing and return a JSON object with these fields:- "category": the product category (e.g., Electronics, Clothing, Home & Garden)- "sentiment": overall sentiment of the description (positive, neutral, negative)- "summary": a one-sentence summary of the product- "key_features": an array of up to 5 key featuresProduct Name: {{product_name}}Price: {{price}}Description: {{description}}

import jsonfrom flask import Flask, request, jsonifyfrom anthropic import Anthropicapp = Flask(__name__)client = Anthropic(api_key="your-anthropic-api-key")ENRICHMENT_PROMPT = """Analyze the following scraped data and return a JSON object with:- "summary": a one-sentence summary- "category": the most appropriate category- "sentiment": positive, neutral, or negative- "tags": an array of up to 5 relevant tags- "quality_score": a score from 1-10 rating the data quality/completenessRespond with valid JSON only, no other text.Data:{data}"""@app.route("/webhook/browse-ai", methods=["POST"])def handle_webhook():    event = request.json    event_type = event.get("event")    # Only process successful task completions    if event_type != "taskFinishedSuccessfully":        return jsonify({"status": "ignored"}), 200    task = event.get("task", {})    captured_data = task.get("capturedTexts", {})    # Enrich each record with Claude    enriched = enrich_with_claude(captured_data)    # Store enriched data (replace with your storage logic)    save_enriched_data(task.get("id"), captured_data, enriched)    return jsonify({"status": "enriched"}), 200def enrich_with_claude(data):    message = client.messages.create(        model="claude-sonnet-4-6",        max_tokens=1024,        messages=[{            "role": "user",            "content": ENRICHMENT_PROMPT.format(data=json.dumps(data, indent=2))        }]    )    return json.loads(message.content[0].text)def save_enriched_data(task_id, original, enriched):    # Replace this with your preferred storage    # Examples: database insert, Google Sheets append, S3 upload    print(f"Task {task_id}: {json.dumps(enriched, indent=2)}")if __name__ == "__main__":    app.run(port=5000)

@app.route("/webhook/browse-ai/list", methods=["POST"])def handle_list_webhook():    event = request.json    if event.get("event") != "taskFinishedSuccessfully":        return jsonify({"status": "ignored"}), 200    task = event.get("task", {})    rows = task.get("capturedLists", {}).get("items", [])    enriched_rows = []    for row in rows:        enriched = enrich_with_claude(row)        enriched_rows.append({**row, **enriched})    save_enriched_data(task.get("id"), enriched_rows)    return jsonify({"status": "enriched", "rows": len(enriched_rows)}), 200

def enrich_with_structured_output(data):    message = client.messages.create(        model="claude-sonnet-4-6",        max_tokens=1024,        system="""You are a data enrichment engine. You ONLY respond with valid JSON.Never include explanations, markdown, or text outside the JSON object.If a field cannot be determined, use null.""",        messages=[{            "role": "user",            "content": f"""Enrich this scraped data. Return a JSON object with exactly these fields:{{  "summary": "one sentence summary",  "category": "primary category",  "subcategory": "more specific category",  "sentiment": "positive|neutral|negative",  "confidence": 0.0 to 1.0,  "tags": ["tag1", "tag2"],  "language": "detected language code"}}Data: {json.dumps(data)}"""        }]    )    return json.loads(message.content[0].text)

import requestsfrom anthropic import AnthropicBROWSE_AI_API_KEY = "your-browse-ai-api-key"ANTHROPIC_API_KEY = "your-anthropic-api-key"ROBOT_ID = "your-robot-id"client = Anthropic(api_key=ANTHROPIC_API_KEY)def get_recent_tasks(robot_id, page=1):    """Fetch recent successful tasks from Browse AI."""    response = requests.get(        f"https://api.browse.ai/v2/robots/{robot_id}/tasks",        headers={"Authorization": f"Bearer {BROWSE_AI_API_KEY}"},        params={"page": page}    )    return response.json().get("result", {}).get("robotTasks", {}).get("items", [])

def batch_enrich(tasks):    """Enrich a batch of Browse AI tasks with Claude."""    enriched_results = []    for task in tasks:        if task.get("status") != "successful":            continue        captured = task.get("capturedTexts", {})        if not captured:            continue        message = client.messages.create(            model="claude-sonnet-4-6",            max_tokens=1024,            messages=[{                "role": "user",                "content": f"""Analyze this scraped data and return a JSON object with:- "summary": one-sentence summary- "category": primary category- "sentiment": positive, neutral, or negative- "tags": up to 5 relevant tagsRespond with valid JSON only.Data: {json.dumps(captured)}"""            }]        )        enrichment = json.loads(message.content[0].text)        enriched_results.append({            "task_id": task["id"],            "original": captured,            "enrichment": enrichment        })    return enriched_results# Run the enrichmenttasks = get_recent_tasks(ROBOT_ID)results = batch_enrich(tasks)# Save resultsfor r in results:    print(f"Task {r['task_id']}: {r['enrichment']}")

0 * * * * cd /path/to/project && python3 enrich.py >> enrich.log 2>&1