app.py

"""
app.py — Gradio UI for BERTopic Agentic AI
Assignment: Text Analysis & Topic Modelling (Prof. Shailaja Jha)
Generated via: Anthropic Claude Sonnet 4.5
Architecture: LangGraph ReAct Agent + Gradio 5.x UI
"""

import os
import json
import pandas as pd
import gradio as gr

from agent import invoke_agent

OUTPUT_DIR = "./outputs"
os.makedirs(OUTPUT_DIR, exist_ok=True)

# Use a simple global for thread ID — avoids gr.State schema issues
_THREAD_ID = "main-session"


# ─── HELPERS ──────────────────────────────────────────────────────────────────

def _exists(name: str) -> bool:
    return os.path.exists(os.path.join(OUTPUT_DIR, name))


def _load(name: str):
    with open(os.path.join(OUTPUT_DIR, name), "r", encoding="utf-8") as f:
        return json.load(f)


def get_phase_html() -> str:
    phases = [
        ("① Load", _exists("corpus_config.json")),
        ("② Codes", _exists("abstract_labels.json")),
        ("③ Themes", _exists("abstract_themes.json")),
        ("④ Saturation", _exists("abstract_themes.json")),
        ("⑤ Names", _exists("abstract_themes.json")),
        ("⑤½ PAJAIS", _exists("taxonomy_map.json")),
        ("⑥ Report", _exists("comparison.csv") and _exists("narrative.txt")),
    ]
    items = "".join(
        f'<span style="padding:6px 14px;border-radius:20px;margin:3px;font-size:13px;'
        f'background:{"#22c55e" if done else "#374151"};color:white;font-weight:600;">'
        f'{"✅" if done else "⬜"} {name}</span>'
        for name, done in phases
    )
    return f'<div style="display:flex;flex-wrap:wrap;gap:4px;padding:8px;">{items}</div>'


def load_review_table():
    """Return table rows as list-of-lists."""
    if _exists("taxonomy_map.json"):
        tax = _load("taxonomy_map.json")
        mapping = tax.get("taxonomy_mapping", {})
        rows = [
            [i, theme,
             f"→ {v.get('pajais_match','?')} | {v.get('reasoning','')[:80]}",
             0, 0, "YES", theme, v.get("reasoning", "")]
            for i, (theme, v) in enumerate(mapping.items())
        ]
        return rows if rows else []

    for fname, key in [("abstract_themes.json", "theme_name"),
                       ("abstract_labels.json", "label")]:
        if _exists(fname):
            data = _load(fname)
            rows = [
                [i, d.get(key, str(i)),
                 (d.get("top_sentences", [""])[0] or "")[:120],
                 d.get("sentence_count", 0), d.get("paper_count", 0),
                 "YES", d.get(key, ""), d.get("reasoning", "")]
                for i, d in enumerate(data)
            ]
            return rows if rows else []
    return []


def get_download_files():
    targets = ["comparison.csv", "taxonomy_map.json", "narrative.txt",
               "abstract_labels.json", "abstract_themes.json",
               "title_labels.json", "title_themes.json"]
    paths = [os.path.join(OUTPUT_DIR, f) for f in targets if _exists(f)]
    return paths if paths else None


# ─── EVENT HANDLERS ───────────────────────────────────────────────────────────

def on_csv_upload(file_obj, history):
    if file_obj is None:
        return history, get_phase_html(), load_review_table(), get_download_files()
    filepath = file_obj if isinstance(file_obj, str) else file_obj.name
    message = f"Analyze my Scopus CSV at: {filepath}"
    try:
        response = invoke_agent(message, _THREAD_ID)
    except Exception as e:
        response = f"❌ Error: {e}"
    history = history + [{"role": "user", "content": message},
                         {"role": "assistant", "content": response}]
    return history, get_phase_html(), load_review_table(), get_download_files()


def on_send(message, history):
    if not message.strip():
        return history, ""
    try:
        response = invoke_agent(message, _THREAD_ID)
    except Exception as e:
        response = f"❌ Error: {e}"
    history = history + [{"role": "user", "content": message},
                         {"role": "assistant", "content": response}]
    return history, ""


def on_refresh(history):
    return history, get_phase_html(), load_review_table(), get_download_files()


def on_submit_review(table_data, history):
    # Handle both DataFrame (Gradio 5) and list formats
    if table_data is None:
        return history, get_phase_html(), load_review_table(), get_download_files()
    if isinstance(table_data, pd.DataFrame):
        if table_data.empty:
            return history, get_phase_html(), load_review_table(), get_download_files()
        rows_list = table_data.values.tolist()
    else:
        if not table_data:
            return history, get_phase_html(), load_review_table(), get_download_files()
        rows_list = table_data

    headers = ["#", "Topic Label", "Top Evidence",
               "Sentences", "Papers", "Approve", "Rename To", "Reasoning"]
    rows_out = []
    for row in rows_list:
        if not row:
            continue
        if isinstance(row, dict):
            d = row
        else:
            d = dict(zip(headers, row))
        rows_out.append({
            "cluster_id": int(d.get("#", 0) or 0),
            "label": str(d.get("Topic Label", "")),
            "approve": str(d.get("Approve", "YES")).upper(),
            "rename_to": str(d.get("Rename To", "")),
            "reasoning": str(d.get("Reasoning", "")),
        })

    message = f"I have reviewed the table. Here are my decisions (JSON):\n{json.dumps(rows_out)}"
    try:
        response = invoke_agent(message, _THREAD_ID)
    except Exception as e:
        response = f"❌ Error: {e}"
    history = history + [{"role": "user", "content": "[Submit Review]"},
                         {"role": "assistant", "content": response}]
    return history, get_phase_html(), load_review_table(), get_download_files()


# ─── GRADIO 5.x UI ────────────────────────────────────────────────────────────

with gr.Blocks(title="BERTopic Agentic AI") as demo:

    gr.HTML("""
    <div style="text-align:center;padding:16px;background:linear-gradient(135deg,#1e1b4b,#312e81);border-radius:12px;margin-bottom:12px;">
      <h1 style="color:white;margin:0;font-size:1.8em;">🤖 BERTopic Agentic AI</h1>
      <p style="color:#a5b4fc;margin:4px 0 0;">RQ5–RQ7: Abstract vs Title Theme Comparison &amp; PAJAIS Taxonomy Mapping</p>
      <p style="color:#818cf8;font-size:0.85em;margin:4px 0 0;">LangGraph · Mistral Small · all-MiniLM-L6-v2 · Braun &amp; Clarke (2006) · PAJAIS 2019</p>
    </div>
    """)

    phase_bar = gr.HTML(value=get_phase_html())

    with gr.Group():
        gr.Markdown("### 📁 Step 1: Upload Your Scopus CSV")
        csv_file = gr.File(label="Upload Scopus CSV (.csv)", file_types=[".csv"])

    with gr.Group():
        gr.Markdown("### 💬 Step 2: Agent Conversation")
        chatbot = gr.Chatbot(
            height=380,
            show_label=False,
            type="messages",
            placeholder="Upload your CSV first, then type 'run abstract' or 'run title'...",
        )
        with gr.Row():
            msg_box = gr.Textbox(
                placeholder="Type 'run abstract', 'run title', or a question...",
                label="Your message",
                scale=5,
                show_label=False,
            )
            send_btn = gr.Button("Send ➤", variant="primary", scale=1)
        with gr.Row():
            submit_btn = gr.Button("📋 Submit Review", variant="secondary")
            refresh_btn = gr.Button("🔄 Refresh", variant="secondary")

    with gr.Group():
        gr.Markdown("### 📊 Step 3: Topic Review Table")
        gr.Markdown("_Edit **Approve** (YES/NO) and **Rename To** inline, then click Submit Review._")
        review_table = gr.Dataframe(
            headers=["#", "Topic Label", "Top Evidence",
                     "Sentences", "Papers", "Approve", "Rename To", "Reasoning"],
            value=load_review_table(),
            interactive=True,
        )

    with gr.Group():
        gr.Markdown("### 📥 Step 4: Download Deliverables")
        gr.Markdown("_Click Refresh after each phase to see new files._")
        download_box = gr.File(
            value=get_download_files(),
            label="Deliverable Files",
            interactive=False,
        )

    gr.Markdown("""
---
**Stack:** Mistral Small · all-MiniLM-L6-v2 · AgglomerativeClustering (cosine, 0.7) · LangGraph ReAct · MemorySaver · PAJAIS 2019
> ⚙️ Set `MISTRAL_API_KEY` in Space **Settings → Variables and secrets**
    """)

    # ── Event Wiring ──────────────────────────────────────────────────────────
    csv_file.upload(
        fn=on_csv_upload,
        inputs=[csv_file, chatbot],
        outputs=[chatbot, phase_bar, review_table, download_box],
    )
    send_btn.click(
        fn=on_send,
        inputs=[msg_box, chatbot],
        outputs=[chatbot, msg_box],
    )
    msg_box.submit(
        fn=on_send,
        inputs=[msg_box, chatbot],
        outputs=[chatbot, msg_box],
    )
    submit_btn.click(
        fn=on_submit_review,
        inputs=[review_table, chatbot],
        outputs=[chatbot, phase_bar, review_table, download_box],
    )
    refresh_btn.click(
        fn=on_refresh,
        inputs=[chatbot],
        outputs=[chatbot, phase_bar, review_table, download_box],
    )


if __name__ == "__main__":
    demo.launch(server_name="0.0.0.0", server_port=7860)