app.py

import gradio as gr
import pandas as pd
import plotly.express as px
import plotly.graph_objects as go
from datasets import load_dataset

# ---------------------------------------------------------------------------
# Data loading
# ---------------------------------------------------------------------------

DATASETS = {
    "EN": "AYI-NEDJIMI/ai-code-multimodal-en",
    "FR": "AYI-NEDJIMI/ai-code-multimodal-fr",
}

_cache: dict[str, pd.DataFrame] = {}


def get_df(lang: str = "EN") -> pd.DataFrame:
    if lang not in _cache:
        ds = load_dataset(DATASETS[lang], split="train")
        _cache[lang] = ds.to_pandas()
    return _cache[lang]


# Pre-load both
for _l in DATASETS:
    get_df(_l)

COLS_TABLE = ["name", "vendor", "category", "subcategory", "pricing"]
DETAIL_FIELDS = [
    "name", "vendor", "category", "subcategory", "description",
    "features", "strengths", "weaknesses", "ide_support",
    "privacy_model", "supported_languages", "pricing", "source_url",
]

LABELS = {
    "EN": {
        "title": "AI Code & Multimodal Explorer",
        "tab_explorer": "Tools Explorer",
        "tab_details": "Details",
        "tab_compare": "Comparison",
        "tab_stats": "Statistics",
        "search": "Search by name or vendor...",
        "category": "Category",
        "all_categories": "All categories",
        "select_tool": "Select a tool",
        "select_tool_a": "Tool A",
        "select_tool_b": "Tool B",
        "compare_btn": "Compare",
        "no_tool": "No tool selected.",
        "chart_cat": "Tools by Category",
        "chart_vendor": "Top 15 Vendors by Number of Tools",
        "chart_pricing": "Pricing Distribution",
        "chart_cat_vendor": "Category × Vendor Heatmap",
    },
    "FR": {
        "title": "AI Code & Multimodal Explorer",
        "tab_explorer": "Explorateur",
        "tab_details": "Détails",
        "tab_compare": "Comparaison",
        "tab_stats": "Statistiques",
        "search": "Rechercher par nom ou éditeur...",
        "category": "Catégorie",
        "all_categories": "Toutes les catégories",
        "select_tool": "Sélectionner un outil",
        "select_tool_a": "Outil A",
        "select_tool_b": "Outil B",
        "compare_btn": "Comparer",
        "no_tool": "Aucun outil sélectionné.",
        "chart_cat": "Outils par catégorie",
        "chart_vendor": "Top 15 éditeurs par nombre d'outils",
        "chart_pricing": "Répartition des tarifs",
        "chart_cat_vendor": "Carte thermique Catégorie × Éditeur",
    },
}

# ---------------------------------------------------------------------------
# Helper functions
# ---------------------------------------------------------------------------

def filter_table(search: str, category: str, lang: str) -> pd.DataFrame:
    df = get_df(lang)
    if category and category != LABELS[lang]["all_categories"]:
        df = df[df["category"] == category]
    if search:
        mask = (
            df["name"].str.contains(search, case=False, na=False)
            | df["vendor"].str.contains(search, case=False, na=False)
        )
        df = df[mask]
    return df[COLS_TABLE].reset_index(drop=True)


def get_tool_names(lang: str) -> list[str]:
    return sorted(get_df(lang)["name"].dropna().unique().tolist())


def get_categories(lang: str) -> list[str]:
    cats = sorted(get_df(lang)["category"].dropna().unique().tolist())
    return [LABELS[lang]["all_categories"]] + cats


def tool_detail_md(name: str | None, lang: str) -> str:
    if not name:
        return LABELS[lang]["no_tool"]
    df = get_df(lang)
    rows = df[df["name"] == name]
    if rows.empty:
        return LABELS[lang]["no_tool"]
    r = rows.iloc[0]
    lines = []
    for f in DETAIL_FIELDS:
        val = r.get(f, "")
        if pd.isna(val) or val == "":
            val = "—"
        label = f.replace("_", " ").title()
        if f == "source_url" and val != "—":
            lines.append(f"**{label}:** [{val}]({val})")
        else:
            lines.append(f"**{label}:** {val}")
    return "\n\n".join(lines)


def compare_tools(name_a: str | None, name_b: str | None, lang: str) -> str:
    if not name_a or not name_b:
        return LABELS[lang]["no_tool"]
    md_a = tool_detail_md(name_a, lang)
    md_b = tool_detail_md(name_b, lang)
    sep = "\n\n---\n\n"
    return f"## {name_a}\n\n{md_a}{sep}## {name_b}\n\n{md_b}"


# ---------------------------------------------------------------------------
# Charts
# ---------------------------------------------------------------------------

def chart_category(lang: str):
    df = get_df(lang)
    counts = df["category"].value_counts().reset_index()
    counts.columns = ["category", "count"]
    fig = px.bar(
        counts, x="category", y="count", color="category",
        title=LABELS[lang]["chart_cat"],
        color_discrete_sequence=px.colors.qualitative.Set2,
    )
    fig.update_layout(showlegend=False, template="plotly_white")
    return fig


def chart_vendor(lang: str):
    df = get_df(lang)
    counts = df["vendor"].value_counts().head(15).reset_index()
    counts.columns = ["vendor", "count"]
    fig = px.bar(
        counts, x="count", y="vendor", orientation="h",
        title=LABELS[lang]["chart_vendor"],
        color="count", color_continuous_scale="Viridis",
    )
    fig.update_layout(yaxis=dict(autorange="reversed"), template="plotly_white")
    return fig


def chart_pricing(lang: str):
    df = get_df(lang)
    counts = df["pricing"].value_counts().reset_index()
    counts.columns = ["pricing", "count"]
    fig = px.pie(
        counts, names="pricing", values="count",
        title=LABELS[lang]["chart_pricing"],
        color_discrete_sequence=px.colors.qualitative.Pastel,
    )
    fig.update_layout(template="plotly_white")
    return fig


def chart_heatmap(lang: str):
    df = get_df(lang)
    ct = pd.crosstab(df["category"], df["vendor"])
    top_vendors = df["vendor"].value_counts().head(12).index.tolist()
    ct = ct[[v for v in top_vendors if v in ct.columns]]
    fig = go.Figure(data=go.Heatmap(
        z=ct.values, x=ct.columns.tolist(), y=ct.index.tolist(),
        colorscale="YlOrRd",
    ))
    fig.update_layout(
        title=LABELS[lang]["chart_cat_vendor"],
        template="plotly_white", height=400,
    )
    return fig


# ---------------------------------------------------------------------------
# Footer
# ---------------------------------------------------------------------------

FOOTER_HTML = """
<div style="text-align:center; padding:20px 0 10px 0; margin-top:30px;
            border-top:1px solid #444; font-size:0.9em; color:#aaa;">
  <p>Built by <strong>AYI-NEDJIMI Consultants</strong></p>
  <p>
    <a href="https://ayinedjimi-consultants.fr" target="_blank" style="margin:0 8px;">🌐 Website</a> |
    <a href="https://www.linkedin.com/company/ayi-nedjimi" target="_blank" style="margin:0 8px;">LinkedIn</a> |
    <a href="https://github.com/AYI-NEDJIMI" target="_blank" style="margin:0 8px;">GitHub</a> |
    <a href="https://x.com/AyiNedjimi" target="_blank" style="margin:0 8px;">X / Twitter</a>
  </p>
</div>
"""

# ---------------------------------------------------------------------------
# Gradio UI
# ---------------------------------------------------------------------------

theme = gr.themes.Soft(
    primary_hue="indigo",
    secondary_hue="purple",
    font=gr.themes.GoogleFont("Inter"),
)

with gr.Blocks(theme=theme, title="AI Code & Multimodal Explorer") as demo:

    lang_state = gr.State("EN")

    gr.Markdown("# AI Code & Multimodal Explorer")

    with gr.Row():
        lang_toggle = gr.Radio(
            choices=["EN", "FR"], value="EN", label="Language / Langue",
            interactive=True,
        )

    # ---- Tab: Explorer ----
    with gr.Tabs() as tabs:
        with gr.TabItem("Tools Explorer", id="explorer"):
            with gr.Row():
                search_box = gr.Textbox(
                    label="Search", placeholder="Search by name or vendor...",
                    scale=3,
                )
                cat_filter = gr.Dropdown(
                    choices=get_categories("EN"),
                    value=LABELS["EN"]["all_categories"],
                    label="Category", scale=1,
                )
            explorer_table = gr.Dataframe(
                value=filter_table("", LABELS["EN"]["all_categories"], "EN"),
                headers=COLS_TABLE,
                interactive=False,
                wrap=True,
            )

        # ---- Tab: Details ----
        with gr.TabItem("Details", id="details"):
            tool_select = gr.Dropdown(
                choices=get_tool_names("EN"),
                label="Select a tool",
                interactive=True,
            )
            detail_output = gr.Markdown(LABELS["EN"]["no_tool"])

        # ---- Tab: Comparison ----
        with gr.TabItem("Comparison", id="compare"):
            with gr.Row():
                tool_a = gr.Dropdown(
                    choices=get_tool_names("EN"), label="Tool A", scale=1,
                )
                tool_b = gr.Dropdown(
                    choices=get_tool_names("EN"), label="Tool B", scale=1,
                )
            compare_btn = gr.Button("Compare", variant="primary")
            compare_output = gr.Markdown(LABELS["EN"]["no_tool"])

        # ---- Tab: Statistics ----
        with gr.TabItem("Statistics", id="stats"):
            with gr.Row():
                plot_cat = gr.Plot(value=chart_category("EN"))
                plot_vendor = gr.Plot(value=chart_vendor("EN"))
            with gr.Row():
                plot_pricing = gr.Plot(value=chart_pricing("EN"))
                plot_heatmap = gr.Plot(value=chart_heatmap("EN"))

    gr.HTML(FOOTER_HTML)

    # ---- Callbacks ----

    def on_lang_change(lang):
        cats = get_categories(lang)
        names = get_tool_names(lang)
        default_cat = cats[0]
        table = filter_table("", default_cat, lang)
        return (
            lang,                                              # lang_state
            gr.update(choices=cats, value=default_cat),        # cat_filter
            table,                                             # explorer_table
            gr.update(choices=names, value=None),              # tool_select
            LABELS[lang]["no_tool"],                           # detail_output
            gr.update(choices=names, value=None),              # tool_a
            gr.update(choices=names, value=None),              # tool_b
            LABELS[lang]["no_tool"],                           # compare_output
            chart_category(lang),
            chart_vendor(lang),
            chart_pricing(lang),
            chart_heatmap(lang),
        )

    lang_toggle.change(
        on_lang_change, inputs=[lang_toggle],
        outputs=[
            lang_state, cat_filter, explorer_table,
            tool_select, detail_output,
            tool_a, tool_b, compare_output,
            plot_cat, plot_vendor, plot_pricing, plot_heatmap,
        ],
    )

    def on_filter(search, category, lang):
        return filter_table(search, category, lang)

    search_box.change(on_filter, [search_box, cat_filter, lang_state], explorer_table)
    cat_filter.change(on_filter, [search_box, cat_filter, lang_state], explorer_table)

    tool_select.change(
        lambda name, lang: tool_detail_md(name, lang),
        [tool_select, lang_state], detail_output,
    )

    compare_btn.click(
        lambda a, b, lang: compare_tools(a, b, lang),
        [tool_a, tool_b, lang_state], compare_output,
    )

demo.launch()