"""Ailiance Playground — bench Phase 6 scoreboard.

Interactive viewer of ailiance/ailiance-bench Phase 6 results.
Source of truth: bench-results/compare_base_vs_lora.md (commit 46801af).
"""

from __future__ import annotations

import gradio as gr
import pandas as pd

# Phase 6 scoreboard (mirror of bench-results/compare_base_vs_lora.md).
# base model: gemma-e4b-eu-kiki-base
SCOREBOARD = pd.DataFrame(
    [
        ["P1", "kicad-dsl", 0.090, 0.640, 0.090, 0.090, 0.090],
        ["P1", "kicad-pcb", 0.010, 0.430, 0.010, 0.010, 0.015],
        ["P1", "spice-sim", 0.425, 0.676, 0.176, 0.189, 0.268],
        ["P2", "kicad-sch-gen", 0.420, 0.220, 0.400, 0.320, 0.180],
        ["P3", "kicad-sch-extract", 0.308, 0.690, 0.785, 0.350, 0.000],
        ["P4", "kicad-erc-abs", 0.060, 0.057, 0.060, 0.060, 0.033],
        ["P5", "kicad-erc-delta", 0.060, 0.057, 0.060, 0.060, 0.033],
    ],
    columns=["Phase", "Task", "base", "+eu-kiki", "+mascarade", "+aggro", "+kicad9plus"],
)

ADAPTERS = ["+eu-kiki", "+mascarade", "+aggro", "+kicad9plus"]

VERDICTS = """
### Verdicts

- 🥇 **eu-kiki** — generalist champion (4/7 tasks)
  - Peak: P1-DSL **+55 pts**, P1-PCB **+42 pts**
  - Hosted on `:8502` (macm1 Gemma-4 + curriculum LoRA)
- 🥇 **mascarade** — P3 extraction champion (**+48 pts**)
  - Wins narrow extraction tasks but loses generation
  - Hosted on Tower Ollama `:8004`
- ⚠️ **aggro** — neutral (sanity-check baseline)
- ❌ **kicad9plus** — catastrophic forgetting on SPICE/P2/P3
  - **Use only** in permissive-KiCad-only contexts
- 🚫 **kicad-sch from-scratch** — unresolved across all 4 adapters
  - Bottleneck: KiCad 6+ S-expr absent from pre-training corpus
"""

TASK_DESCRIPTIONS = {
    "kicad-dsl": "Generate KiCad design DSL from a natural language spec",
    "kicad-pcb": "Generate KiCad PCB layout description",
    "spice-sim": "Reason about SPICE circuit simulation behavior",
    "kicad-sch-gen": "Generate a full .kicad_sch file from scratch",
    "kicad-sch-extract": "Extract components/nets from existing .kicad_sch",
    "kicad-erc-abs": "Detect absolute ERC (electrical rule) violations",
    "kicad-erc-delta": "Compute ERC delta between schematic revisions",
}


def compute_delta(row: pd.Series, adapter: str) -> str:
    """Format adapter score with Δ vs base in pts."""
    base = row["base"]
    score = row[adapter]
    delta = (score - base) * 100
    sign = "+" if delta >= 0 else ""
    return f"{score:.3f} ({sign}{delta:.0f})"


def styled_scoreboard() -> pd.DataFrame:
    """Build the display dataframe with deltas in parens."""
    df = SCOREBOARD.copy()
    for adapter in ADAPTERS:
        df[adapter] = df.apply(lambda r: compute_delta(r, adapter), axis=1)
    df["base"] = df["base"].map(lambda v: f"{v:.3f}")
    return df


def task_detail(task: str) -> tuple[str, pd.DataFrame]:
    """Drill-down for one task."""
    if task is None or task not in SCOREBOARD["Task"].values:
        return "Pick a task above to see the per-adapter breakdown.", pd.DataFrame()
    row = SCOREBOARD[SCOREBOARD["Task"] == task].iloc[0]
    base = row["base"]
    rows = []
    for adapter in ADAPTERS:
        score = row[adapter]
        delta = (score - base) * 100
        rows.append([adapter.lstrip("+"), f"{score:.3f}", f"{delta:+.1f} pts"])
    df = pd.DataFrame(rows, columns=["Adapter", "Score", "Δ vs base"])
    description = TASK_DESCRIPTIONS.get(task, "")
    md = f"**{task}** — {description}\n\nBase score: `{base:.3f}` (Gemma-E4B)"
    return md, df


def best_per_task() -> pd.DataFrame:
    """Which adapter wins each task?"""
    rows = []
    for _, row in SCOREBOARD.iterrows():
        scores = {a: row[a] for a in ADAPTERS}
        winner = max(scores, key=scores.get)
        delta = (scores[winner] - row["base"]) * 100
        rows.append(
            [
                row["Phase"],
                row["Task"],
                winner.lstrip("+"),
                f"{scores[winner]:.3f}",
                f"{delta:+.1f} pts",
            ]
        )
    return pd.DataFrame(rows, columns=["Phase", "Task", "Winner", "Score", "Δ"])


with gr.Blocks(
    title="Ailiance Playground — Bench Phase 6",
    theme=gr.themes.Soft(),
) as demo:
    gr.Markdown(
        """
# 📊 Ailiance Playground

**Phase 6 bench scoreboard** — 7-task hardware-design evaluation of
LoRA adapters against the base Gemma-E4B model.

Source: [`ailiance/ailiance-bench`](https://github.com/ailiance/ailiance-bench#scoreboard-lora-phase-6--2026-05-11) · commit `46801af`
"""
    )

    with gr.Tab("Scoreboard"):
        gr.Markdown(
            "Each cell shows the adapter score and Δ in points (× 100) vs base."
        )
        gr.Dataframe(
            styled_scoreboard(),
            interactive=False,
            wrap=True,
        )
        gr.Markdown(VERDICTS)

    with gr.Tab("Task drill-down"):
        gr.Markdown("Pick a task to see per-adapter performance and Δ.")
        task_dropdown = gr.Dropdown(
            choices=list(SCOREBOARD["Task"]),
            label="Task",
            value="kicad-dsl",
        )
        task_md = gr.Markdown()
        task_table = gr.Dataframe(interactive=False)
        task_dropdown.change(
            task_detail, inputs=task_dropdown, outputs=[task_md, task_table]
        )
        # Initial render
        demo.load(task_detail, inputs=task_dropdown, outputs=[task_md, task_table])

    with gr.Tab("Winners"):
        gr.Markdown("Best adapter per task and the gain over the base model.")
        gr.Dataframe(best_per_task(), interactive=False)

    with gr.Tab("About"):
        gr.Markdown(
            """
## About ailiance-bench Phase 6

The bench evaluates LoRA adapters fine-tuned on hardware-design tasks
against the base `gemma-e4b-eu-kiki-base` model. Phase 6 is the final
ship of the 2026-05-11 benchmark cycle.

**Adapters compared:**

- `eu-kiki` — generalist hardware adapter (curriculum LoRA on macm1)
- `mascarade` — domain-specialist family (Qwen3-4B base, per-domain LoRAs on Tower)
- `aggro` — adversarial-data baseline (sanity check)
- `kicad9plus` — corpus-only continual pretrain on KiCad 9+ schematics

**Methodology:** see [`ailiance/ailiance-bench`](https://github.com/ailiance/ailiance-bench) `bench-results/compare_base_vs_lora.{md,json}`.

**Production impact:** the ailiance gateway (`:9300`) routes `kicad-dsl` /
`kicad-pcb` to `eu-kiki` (PR #54) and 9 hardware domains to the
mascarade Tower Ollama (PR #49), after this bench validated each
adapter's strengths.

## Links

- 🌐 [ailiance.fr](https://ailiance.fr)
- 💻 [github.com/ailiance](https://github.com/ailiance)
- 📦 [huggingface.co/Ailiance-fr](https://huggingface.co/Ailiance-fr)
- 📊 [bench source](https://github.com/ailiance/ailiance-bench)
- 📜 EU AI Act tags: `art-52`, `art-53`, `gpai-fine-tune`
"""
        )

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