Create app.py

app.py

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+import gradio as gr
+import requests
+import os
+import json
+
+# The model you want to use — you can swap this for another if needed
+MODEL_ID = "deepseek-ai/deepseek-coder-1.3b-instruct"
+
+# Hugging Face token (set in your Space's "Variables and secrets")
+HF_TOKEN = os.environ.get("HF_TOKEN")
+
+API_URL = f"https://api-inference.huggingface.co/models/{MODEL_ID}"
+HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"}
+
+def format_json(json_text):
+    """
+    Takes JSON text, sends it to the model, and returns formatted output.
+    """
+    try:
+        # Validate JSON first
+        parsed = json.loads(json_text)
+    except json.JSONDecodeError:
+        return "❌ That’s not valid JSON. Please check your brackets and quotes."
+
+    # Create the prompt for the AI
+    prompt = (
+        "You are a document formatter. "
+        "Take the following JSON data and turn it into a neat, human-readable layout "
+        "that could be pasted into Google Docs with headings, bullet points, or tables:\n\n"
+        f"{json_text}"
+    )
+
+    payload = {"inputs": prompt}
+
+    # Send to Hugging Face Inference API
+    response = requests.post(API_URL, headers=HEADERS, json=payload)
+    try:
+        data = response.json()
+        if isinstance(data, list) and "generated_text" in data[0]:
+            return data[0]["generated_text"]
+        else:
+            return str(data)
+    except Exception as e:
+        return f"Error parsing model response: {e}"
+
+# Gradio interface
+demo = gr.Interface(
+    fn=format_json,
+    inputs=gr.Textbox(lines=12, placeholder="Paste your JSON here..."),
+    outputs="text",
+    title="DeepSeek JSON → Docs Formatter",
+    description="Paste JSON, get back neatly formatted text for Google Docs."
+)
+
+if __name__ == "__main__":
+    demo.launch()