first pass

app.py

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+import gradio as gr
+from huggingface_hub import HfApi
+from datasets import load_dataset, Dataset
+import os
+import uuid
+import json
+
+# Set your HF credentials
+HF_TOKEN = os.getenv("HF_TOKEN")  # In Space, add as a secret variable
+DATASET_REPO = "your-username/submitted-papers"  # Replace with your dataset repo
+
+# Load dataset (or create dummy if doesn't exist)
+def append_to_dataset(entry):
+    try:
+        # Load current dataset
+        dataset = load_dataset(DATASET_REPO, split="train", token=HF_TOKEN)
+        data = dataset.to_list()
+    except Exception:
+        data = []
+
+    # Append new entry
+    data.append(entry)
+
+    # Save locally and push
+    new_dataset = Dataset.from_list(data)
+    new_dataset.push_to_hub(DATASET_REPO, token=HF_TOKEN)
+
+def submit_paper(title, authors, abstract, category, paper_url, originality):
+    if not originality:
+        return "You must confirm that this is your own submission."
+
+    entry = {
+        "id": str(uuid.uuid4()),
+        "title": title,
+        "authors": authors,
+        "abstract": abstract,
+        "category": category,
+        "url": paper_url
+    }
+
+    append_to_dataset(entry)
+    return "✅ Submission successful!"
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("## 📄 Submit Your Paper")
+
+    with gr.Row():
+        title = gr.Textbox(label="Title", placeholder="Enter paper title")
+        authors = gr.Textbox(label="Authors", placeholder="Jane Doe, John Smith")
+
+    abstract = gr.Textbox(label="Abstract", lines=6)
+    category = gr.Dropdown(
+        label="Category",
+        choices=["NLP", "CV", "Audio", "Theory", "Robotics", "Other"],
+        value="NLP"
+    )
+    paper_url = gr.Textbox(label="Paper URL (arXiv or PDF)", placeholder="https://...")
+
+    originality = gr.Checkbox(label="I confirm this is my own work")
+
+    submit_btn = gr.Button("Submit")
+    output = gr.Textbox(label="Status", interactive=False)
+
+    submit_btn.click(
+        fn=submit_paper,
+        inputs=[title, authors, abstract, category, paper_url, originality],
+        outputs=output
+    )
+
+demo.launch()

requirements.txt

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+gradio
+datasets
+huggingface_hub