Create app.py

app.py

@@ -0,0 +1,35 @@
+from flask import Flask, request, jsonify
+from transformers import pipeline, AutoModelForSeq2SeqLM, AutoTokenizer
+
+app = Flask(__name__)
+
+# Load a lightweight model for structured output
+model_name = "google/flan-t5-small"  # You can replace this with another small instruct model
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+generator = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
+
+@app.route('/generate-json', methods=['POST'])
+def generate_json():
+    data = request.json
+    prompt = data.get("prompt")
+
+    if not prompt:
+        return jsonify({"error": "Prompt is required"}), 400
+
+    # Add instruction if needed
+    instruction = f"Generate a JSON object from the following description:\n{prompt}"
+    
+    response = generator(instruction, max_length=256, do_sample=False)
+    generated_text = response[0]["generated_text"]
+
+    try:
+        # Try to parse generated text as JSON
+        generated_json = eval(generated_text)  # Use json.loads if safe JSON string is expected
+        return jsonify({"json": generated_json})
+    except Exception as e:
+        return jsonify({"raw_output": generated_text, "error": str(e)}), 200
+
+if __name__ == '__main__':
+    app.run(debug=True)