Revert "New tabs and functions v4.5"

This reverts commit 978bdd6a

app.py

@@ -100,6 +100,16 @@ with gr.Blocks(css=base_css) as demo:
             # первичная инициализация при запуске
             demo.load(fn=update_visuals, inputs=None, outputs=[price_plot, vol_plot], _js="() => 'Bitcoin vs Ethereum'")
 
+<<<<<<< HEAD
+=======
+
+            # первичная инициализация при запуске (Gradio 5.x compatible)
+            def init_visuals():
+                return update_visuals("Bitcoin vs Ethereum")
+
+            demo.load(fn=init_visuals, inputs=None, outputs=[price_plot, vol_plot])
+
+>>>>>>> parent of 53d7057 (Change UI v1.0)
         # --- Crypto Intelligence Dashboard (Plotly Edition + KPI line) ---
         with gr.TabItem("Crypto Intelligence Dashboard"):
             gr.HTML(f"<style>{crypto_css}</style>")

core/crypto_dashboard.py

@@ -1,9 +1,8 @@
 """
-Crypto Dashboard — Plotly Edition + KPI line (auto-load ready)
-Источник данных: Coinlore (без ключей).
-Графики: Treemap (market cap), Top Movers (24h), Market Cap vs Volume (bubble).
-Встроенные title у фигур убраны, подписи colorbar скрыты.
-KPI-строка компактная: BTC, ETH, SOL, DOGE.
+Crypto Dashboard — Plotly Edition (clean layout)
+• убраны colorbar заголовки (percent_change_*)
+• уменьшены отступы KPI
+• без глобального Markdown-заголовка
 """
 import requests
 import pandas as pd
@@ -11,19 +10,18 @@ import plotly.express as px
 from services.llm_client import llm_service
 
 
-def _fetch_coinlore(limit=100) -> pd.DataFrame:
+def fetch_coinlore_data(limit=100):
     url = "https://api.coinlore.net/api/tickers/"
     data = requests.get(url).json()["data"]
     df = pd.DataFrame(data)
-    for col in [
-        "price_usd", "market_cap_usd", "volume24",
-        "percent_change_1h", "percent_change_24h", "percent_change_7d"
-    ]:
+    for col in ["price_usd", "market_cap_usd", "volume24",
+                "percent_change_1h", "percent_change_24h", "percent_change_7d"]:
         df[col] = pd.to_numeric(df[col], errors="coerce")
     return df.head(limit)
 
 
-def _kpi_line(df: pd.DataFrame) -> str:
+def _kpi_line(df) -> str:
+    """Формирует компактную KPI-строку без лишних пробелов"""
     tracked = ["BTC", "ETH", "SOL", "DOGE"]
     parts = []
     for sym in tracked:
@@ -35,34 +33,16 @@ def _kpi_line(df: pd.DataFrame) -> str:
         arrow = "↑" if ch > 0 else "↓"
         color = "#4ade80" if ch > 0 else "#f87171"
         parts.append(
-            f"<span class='kpi-item'><b>{sym}</b> ${price:,.0f} "
-            f"<span style='color:{color}'>{arrow} {abs(ch):.2f}%</span></span>"
+            f"<b>{sym}</b> ${price:,.0f} "
+            f"<span style='color:{color}'>{arrow} {abs(ch):.2f}%</span>"
         )
     return " , ".join(parts)
 
 
-def _ai_summary(df: pd.DataFrame) -> str:
-    leaders = df.sort_values("percent_change_24h", ascending=False).head(3)["symbol"].tolist()
-    laggards = df.sort_values("percent_change_24h").head(3)["symbol"].tolist()
-    prompt = f"""
-Summarize today's crypto market based on Coinlore data.
-Top gainers: {', '.join(leaders)}.
-Top losers: {', '.join(laggards)}.
-Include: overall sentiment, volatility/liquidity, short-term outlook.
-"""
-    text = ""
-    for delta in llm_service.stream_chat(
-        messages=[{"role": "user", "content": prompt}],
-        model="meta-llama/Meta-Llama-3.1-8B-Instruct",
-    ):
-        text += delta
-    return text
-
-
-def build_crypto_dashboard(top_n: int = 50):
-    df = _fetch_coinlore(top_n)
+def build_crypto_dashboard(top_n=50):
+    df = fetch_coinlore_data(top_n)
 
-    # --- Treemap (Market Composition) ---
+    # === Treemap ===
     fig_treemap = px.treemap(
         df,
         path=["symbol"],
@@ -74,14 +54,13 @@ def build_crypto_dashboard(top_n: int = 50):
     fig_treemap.update_layout(
         title=None,
         template="plotly_dark",
-        coloraxis_colorbar=dict(title=None),
-        autosize=True,
+        coloraxis_colorbar=dict(title=None),  # 🔹 убираем надпись percent_change_24h
         margin=dict(l=5, r=5, t=5, b=5),
         paper_bgcolor="rgba(0,0,0,0)",
         plot_bgcolor="rgba(0,0,0,0)",
     )
 
-    # --- Top Movers (24h) ---
+    # === Bar chart (Top gainers) ===
     top = df.sort_values("percent_change_24h", ascending=False).head(12)
     fig_bar = px.bar(
         top,
@@ -95,14 +74,13 @@ def build_crypto_dashboard(top_n: int = 50):
     fig_bar.update_layout(
         title=None,
         template="plotly_dark",
-        coloraxis_colorbar=dict(title=None),
-        autosize=True,
+        coloraxis_colorbar=dict(title=None),  # 🔹 убираем надпись percent_change_24h
         margin=dict(l=40, r=10, t=5, b=18),
         paper_bgcolor="rgba(0,0,0,0)",
         plot_bgcolor="rgba(0,0,0,0)",
     )
 
-    # --- Market Cap vs Volume (bubble, log-log) ---
+    # === Scatter (Market Cap vs Volume) ===
     fig_bubble = px.scatter(
         df.head(60),
         x="market_cap_usd",
@@ -118,11 +96,31 @@ def build_crypto_dashboard(top_n: int = 50):
     fig_bubble.update_layout(
         title=None,
         template="plotly_dark",
-        coloraxis_colorbar=dict(title=None),
-        autosize=True,
+        coloraxis_colorbar=dict(title=None),  # 🔹 убираем надпись percent_change_7d
         margin=dict(l=36, r=10, t=5, b=18),
         paper_bgcolor="rgba(0,0,0,0)",
         plot_bgcolor="rgba(0,0,0,0)",
     )
 
-    return fig_treemap, fig_bar, fig_bubble, _ai_summary(df), _kpi_line(df)
+    # === LLM summary ===
+    summary = _ai_summary(df)
+    kpi_text = _kpi_line(df)
+    return fig_treemap, fig_bar, fig_bubble, summary, kpi_text
+
+
+def _ai_summary(df):
+    leaders = df.sort_values("percent_change_24h", ascending=False).head(3)["symbol"].tolist()
+    laggards = df.sort_values("percent_change_24h").head(3)["symbol"].tolist()
+    prompt = f"""
+Summarize today's crypto market based on Coinlore data.
+Top gainers: {', '.join(leaders)}.
+Top losers: {', '.join(laggards)}.
+Include: overall sentiment, volatility/liquidity, short-term outlook.
+"""
+    text = ""
+    for delta in llm_service.stream_chat(
+        messages=[{"role": "user", "content": prompt}],
+        model="meta-llama/Meta-Llama-3.1-8B-Instruct",
+    ):
+        text += delta
+    return text

core/multi_charts.py

@@ -0,0 +1,56 @@
+"""
+Multi Visualization Demo — ECharts + Highcharts (pure HTML/JS)
+Никаких внешних питон-зависимостей, всё через CDN-скрипты.
+"""
+import json
+import numpy as np
+
+def build_echarts_html():
+    # сгенерируем 90 точек псевдо-цены
+    prices = (np.cumsum(np.random.randn(90)) * 100 + 42000).tolist()
+    xcats = list(range(1, 91))
+    return f"""
+    <div id="echarts_btc" style="height:360px;"></div>
+    <script src="https://cdn.jsdelivr.net/npm/echarts@5/dist/echarts.min.js"></script>
+    <script>
+      var chart = echarts.init(document.getElementById('echarts_btc'), null, {{renderer:'canvas'}});
+      var option = {{
+        backgroundColor: '#0d1117',
+        title: {{ text: 'ECharts: BTC/USD (Simulated)', textStyle: {{ color:'#f0f6fc' }} }},
+        tooltip: {{ trigger: 'axis' }},
+        grid: {{ left: 30, right: 20, top: 40, bottom: 20 }},
+        xAxis: {{ type: 'category', data: {json.dumps(xcats)}, axisLine: {{ lineStyle: {{ color:'#30363d' }} }} }},
+        yAxis: {{ type: 'value', axisLine: {{ lineStyle: {{ color:'#30363d' }} }} }},
+        series: [{{
+          name: 'BTC/USD',
+          type: 'line',
+          smooth: true,
+          data: {json.dumps(prices)},
+          lineStyle: {{ width: 2, color: '#4f46e5' }},
+          areaStyle: {{ color: 'rgba(99,102,241,0.15)' }},
+          showSymbol: false
+        }}]
+      }};
+      chart.setOption(option);
+      window.addEventListener('resize', () => chart.resize());
+    </script>
+    """
+
+def build_highcharts_html():
+    prices = (np.cumsum(np.random.randn(90)) * 10 + 2300).tolist()
+    xcats = list(range(1, 91))
+    return f"""
+    <div id="highcharts_eth" style="height:360px;"></div>
+    <script src="https://code.highcharts.com/highcharts.js"></script>
+    <script>
+      Highcharts.chart('highcharts_eth', {{
+        chart: {{ backgroundColor: '#0d1117', style: {{ fontFamily: 'Inter' }} }},
+        title: {{ text: 'Highcharts: ETH/USD (Simulated)', style: {{ color: '#f0f6fc' }} }},
+        xAxis: {{ categories: {json.dumps(xcats)}, labels: {{ style: {{ color: '#9da5b4' }} }} }},
+        yAxis: {{ title: {{ text: 'Price (USD)', style: {{ color: '#9da5b4' }} }} }},
+        tooltip: {{ backgroundColor:'#161b22', borderColor:'#30363d', style: {{ color:'#f0f6fc' }} }},
+        credits: {{ enabled: false }},
+        series: [{{ name: 'ETH/USD', data: {json.dumps(prices)}, color: '#10b981' }}]
+      }});
+    </script>
+    """

core/styles/crypto_dashboard.css

@@ -6,49 +6,43 @@
 
 /* === KPI fixed line (строка с метриками) === */
 #kpi_row {
-  margin: 0 !important;
+  margin-top: 0 !important;
+  margin-bottom: 0 !important;
   padding: 0 !important;
-  height: auto !important;
 }
 #kpi_line {
   width: 100%;
   margin: 0 !important;
-  padding: 1px 6px !important;
+  padding: 2px 6px !important;
   background: transparent;
   color: #f0f6fc;
   font-family: 'JetBrains Mono', monospace;
   font-size: 14px;
-  line-height: 1.1;
+  line-height: 1.2;
   white-space: nowrap;
   overflow: hidden;
   text-overflow: ellipsis;
   display: flex;
   align-items: center;
   justify-content: flex-start;
+  min-height: 24px;
   border-bottom: 1px solid #30363d;
   transition: all 0.2s ease-in-out;
-  min-height: unset !important;
-  height: auto !important;
 }
+
+/* KPI items */
 .kpi-item {
   margin-right: 14px;
   letter-spacing: 0.2px;
   transition: opacity 0.2s ease;
 }
-.kpi-item:hover { opacity: 0.85; }
-
-/* === Убираем избыточные поля вокруг KPI и контролов === */
-#kpi_row + .gr-row,
-#controls_row {
-  margin-top: 0 !important;
-  padding-top: 0 !important;
-  margin-bottom: 0 !important;
-  padding-bottom: 0 !important;
+.kpi-item:hover {
+  opacity: 0.85;
 }
 
-/* === Controls (slider) — минимальные отступы === */
+/* === Controls (slider + button) — минимальные отступы === */
 #controls_row {
-  margin-top: 0 !important;
+  margin-top: 2px !important;
   margin-bottom: 2px !important;
   padding: 0 !important;
 }
@@ -72,9 +66,11 @@
   background: transparent !important;
   box-shadow: none !important;
 }
-[data-testid="plot-container"] svg { display: none !important; }
+[data-testid="plot-container"] svg {
+  display: none !important;
+}
 
-/* === Скрываем только заголовки Plotly и подписи colorbar (оси, тики, легенды — оставить) === */
+/* === Скрываем только встроенные заголовки Plotly и подписи colorbar === */
 .js-plotly-plot .plotly .gtitle,
 .js-plotly-plot .plotly .g-xtitle,
 .js-plotly-plot .plotly .g-ytitle,
@@ -84,6 +80,8 @@
   display: none !important;
   visibility: hidden !important;
 }
+
+/* === Явно оставляем видимыми подписи осей, тики, легенду и аннотации === */
 .js-plotly-plot .legend text,
 .js-plotly-plot .xtick text,
 .js-plotly-plot .ytick text,