uusi projekti
This commit is contained in:
Jaakko Vanhala
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network-poc/frontend/public/templates/data-analytics.json
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33
network-poc/frontend/public/templates/data-analytics.json
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@@ -0,0 +1,33 @@
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{
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"name": "Data Analytics Pipeline",
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"description": "ETL, analysis, and visualization with Docker (MariaDB + Jupyter)",
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"keywords": ["data", "analytics", "csv", "etl", "visualization", "statistics", "dashboard", "jupyter", "pandas", "matplotlib"],
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"files": {
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"etl.py": {
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"description": "Data loading, cleaning, and transformation",
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"example": "import pandas as pd\nfrom pathlib import Path\nfrom sqlalchemy import create_engine\n\nDB_URL = \"mysql+pymysql://root:secret@localhost:3306/analytics\"\nengine = create_engine(DB_URL)\n\ndef load_csv(path: str) -> pd.DataFrame:\n df = pd.read_csv(path)\n print(f\"Loaded {len(df)} rows from {path}\")\n return df\n\ndef clean(df: pd.DataFrame) -> pd.DataFrame:\n df = df.dropna(subset=[\"x\", \"y\"])\n df = df[(df[\"x\"] >= 0) & (df[\"y\"] >= 0)] # Remove outliers\n df[\"timestamp\"] = pd.to_datetime(df[\"timestamp\"])\n return df.sort_values(\"timestamp\").reset_index(drop=True)\n\ndef to_database(df: pd.DataFrame, table: str):\n df.to_sql(table, engine, if_exists=\"replace\", index=False)\n print(f\"Wrote {len(df)} rows to {table}\")\n\nif __name__ == \"__main__\":\n for csv_file in sorted(Path(\"data\").glob(\"*.csv\")):\n df = load_csv(str(csv_file))\n df = clean(df)\n to_database(df, \"measurements\")",
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"instructions": "Write the ETL pipeline:\n- Load CSV files from data/ directory using pandas\n- Clean: remove nulls, filter outliers, parse timestamps\n- Transform: convert units, compute derived columns\n- Load into MariaDB via SQLAlchemy\n- Make it runnable as a standalone script"
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},
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"analysis.py": {
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"description": "Statistical analysis and metrics computation",
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"example": "import pandas as pd\nfrom sqlalchemy import create_engine\n\nDB_URL = \"mysql+pymysql://root:secret@localhost:3306/analytics\"\nengine = create_engine(DB_URL)\n\ndef load_data() -> pd.DataFrame:\n return pd.read_sql(\"SELECT * FROM measurements\", engine)\n\ndef summary_stats(df: pd.DataFrame) -> dict:\n return {\n \"total_rows\": len(df),\n \"date_range\": f\"{df['timestamp'].min()} to {df['timestamp'].max()}\",\n \"unique_entities\": df[\"entity_id\"].nunique(),\n }\n\ndef hourly_distribution(df: pd.DataFrame) -> pd.DataFrame:\n df[\"hour\"] = df[\"timestamp\"].dt.hour\n return df.groupby(\"hour\").size().reset_index(name=\"count\")\n\nif __name__ == \"__main__\":\n df = load_data()\n stats = summary_stats(df)\n for k, v in stats.items():\n print(f\"{k}: {v}\")",
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"instructions": "Write analysis functions:\n- Load cleaned data from MariaDB\n- Compute summary statistics (counts, date ranges, distributions)\n- Time-based analysis (hourly, daily, weekly patterns)\n- Group-level metrics (per entity, per zone)\n- Return DataFrames and dicts suitable for visualization"
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},
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"visualize.py": {
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"description": "Charts and visualizations with matplotlib",
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"example": "import matplotlib.pyplot as plt\nimport pandas as pd\nfrom analysis import load_data, hourly_distribution\n\ndef plot_heatmap(df: pd.DataFrame, title: str, output: str):\n fig, ax = plt.subplots(figsize=(12, 8))\n scatter = ax.scatter(df[\"x\"], df[\"y\"], c=df[\"density\"], cmap=\"hot\", alpha=0.5, s=2)\n ax.set_title(title)\n ax.set_xlabel(\"x\")\n ax.set_ylabel(\"y\")\n ax.invert_yaxis()\n plt.colorbar(scatter, label=\"Density\")\n plt.tight_layout()\n plt.savefig(output, dpi=150)\n print(f\"Saved {output}\")\n\ndef plot_bar(df: pd.DataFrame, x: str, y: str, title: str, output: str):\n fig, ax = plt.subplots(figsize=(10, 5))\n ax.bar(df[x], df[y], color=\"steelblue\")\n ax.set_title(title)\n ax.set_xlabel(x)\n ax.set_ylabel(y)\n plt.tight_layout()\n plt.savefig(output, dpi=150)\n\nif __name__ == \"__main__\":\n df = load_data()\n hourly = hourly_distribution(df)\n plot_bar(hourly, \"hour\", \"count\", \"Hourly Distribution\", \"output/hourly.png\")",
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"instructions": "Write visualization functions:\n- Import analysis functions for data\n- Heatmaps, bar charts, line charts as appropriate\n- Save figures to output/ directory (PNG, 150 DPI)\n- Use matplotlib with clear titles, labels, colorbars\n- Make it runnable as standalone to generate all charts"
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},
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"docker-compose.yml": {
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"description": "Docker Compose stack for database and Jupyter",
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"example": "services:\n db:\n image: mariadb:11\n environment:\n MYSQL_ROOT_PASSWORD: secret\n MYSQL_DATABASE: analytics\n ports:\n - \"3306:3306\"\n volumes:\n - db_data:/var/lib/mysql\n\n jupyter:\n image: jupyter/scipy-notebook:latest\n ports:\n - \"8888:8888\"\n volumes:\n - .:/home/jovyan/work\n environment:\n JUPYTER_TOKEN: kipina\n depends_on:\n - db\n\nvolumes:\n db_data:",
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"instructions": "Write docker-compose.yml:\n- MariaDB service with persistent volume\n- JupyterLab service with project mounted\n- Correct environment variables\n- Port mappings for local development\n- Write ONLY the YAML, no explanations"
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},
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"pyproject.toml": {
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"description": "Project dependencies",
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"example": "[project]\nname = \"analytics\"\nversion = \"0.1.0\"\nrequires-python = \">=3.11\"\ndependencies = [\n \"pandas\",\n \"matplotlib\",\n \"sqlalchemy\",\n \"pymysql\",\n]\n\n[project.scripts]\netl = \"python etl.py\"\nanalyze = \"python analysis.py\"\nvisualize = \"python visualize.py\"",
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"instructions": "Use [project] format (PEP 621). List all data science dependencies. Add scripts for ETL, analysis, and visualization."
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}
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},
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"order": ["etl.py", "analysis.py", "visualize.py", "docker-compose.yml", "pyproject.toml"]
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}
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@@ -1,6 +1,7 @@
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{
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"name": "FastAPI CRUD",
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"description": "REST API with SQLite database",
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"keywords": ["api", "rest", "crud", "endpoint", "fastapi", "web", "backend", "server", "database", "sqlite"],
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"files": {
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"models.py": {
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"description": "SQLAlchemy models, engine, and session",
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@@ -501,10 +501,16 @@ OUTPUT FORMAT:
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// Wasm-autostart vain jos natiivisolmua ei löydy (tarkistetaan onopen:ssa)
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// === Pipeline-keskeytys ===
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let pipelineAbort = null; // AbortController tai null
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// === kpnRun: lähettää promptin mallille ===
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const activeStreams = {};
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async function kpnRun(model, prompt, silent, agentOpts) {
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// Tarkistetaan keskeytys
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if (pipelineAbort?.signal?.aborted) return null;
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const taskId = crypto.randomUUID();
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const statusDiv = document.createElement('div');
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statusDiv.className = 'terminal-line';
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@@ -514,10 +520,6 @@ OUTPUT FORMAT:
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termPanel.scrollTop = termPanel.scrollHeight;
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try {
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// Ei odotetaan Wasmia — lähetetään suoraan hubille.
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// Jos hub löytää natiivisolmun, vastaus tulee nopeasti.
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// Jos 503, käynnistetään Wasm-fallback.
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if (!silent) {
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const streamDiv = document.createElement('div');
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streamDiv.className = 'terminal-line';
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@@ -535,18 +537,18 @@ OUTPUT FORMAT:
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model,
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prompt,
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task_id: taskId,
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system_prompt: opts.systemPrompt || settings.systemPrompt || undefined,
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system_prompt: opts.prompt || settings.systemPrompt || undefined,
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temperature: opts.temperature ?? settings.temperature ?? undefined,
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top_k: opts.topK ?? settings.topK ?? undefined,
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max_tokens: opts.maxTokens ?? settings.maxTokens ?? undefined,
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repeat_penalty: opts.repeatPenalty ?? settings.repeatPenalty ?? undefined,
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stop: settings.stopSequences ? settings.stopSequences.split('\\n').filter(Boolean) : undefined,
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};
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const res = await fetch('/api/v1/chat/completions', {
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method: 'POST',
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headers: { 'Content-Type': 'application/json' },
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body: JSON.stringify(payload),
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signal: pipelineAbort?.signal,
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});
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if (res.status === 503 && !wasmNodeStarted) {
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@@ -619,7 +621,7 @@ OUTPUT FORMAT:
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const kpnExamples = {
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'kpn run coder': ['"hello world in python"','"fibonacci in rust"','"quicksort in javascript"'],
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'kpn run coder-3b': ['"REST API with Flask"','"binary search tree"'],
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'kpn project': ['"FastAPI + SQLite REST API"','"CLI tool for CSV processing"'],
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'kpn project': ['"FastAPI + SQLite REST API"','"UWB indoor positioning analytics — CSV cart tracking data, heatmaps, statistics, Docker (MariaDB + Jupyter)"','"CLI tool for CSV processing"'],
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'kpn pipeline': ['"todo-sovellus"','"laskin pythonilla"'],
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};
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@@ -753,15 +755,30 @@ OUTPUT FORMAT:
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// === Template-pohjainen projektipipeline ===
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let templates = {};
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const TEMPLATE_FILES = ['fastapi-crud.json', 'data-analytics.json'];
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// Ladataan mallipohjat
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(async () => {
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try {
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const res = await fetch('/templates/fastapi-crud.json');
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if (res.ok) { const t = await res.json(); templates[t.name] = t; }
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} catch(e) {}
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for (const file of TEMPLATE_FILES) {
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try {
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const res = await fetch(`/templates/${file}`);
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if (res.ok) { const t = await res.json(); templates[t.name] = t; }
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} catch(e) {}
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}
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})();
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// Valitaan mallipohja Asiakkaan briefin perusteella (keywords-match)
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function selectTemplate(brief) {
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const lower = brief.toLowerCase();
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let best = null, bestScore = 0;
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for (const t of Object.values(templates)) {
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const keywords = t.keywords || [];
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const score = keywords.filter(k => lower.includes(k)).length;
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if (score > bestScore) { bestScore = score; best = t; }
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}
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return best; // null = vapaa tila
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}
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function explainStep(title, explanation) {
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termLog(`\n <span style="color:#a371f7;font-size:12px">💡 ${esc(title)}</span>`);
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termLog(` <span style="color:#8b949e;font-size:12px">${esc(explanation)}</span>`);
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@@ -769,18 +786,11 @@ OUTPUT FORMAT:
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async function kpnProject(task) {
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const cli = agents.client || Object.values(agents)[0];
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const mgr = agents.manager || Object.values(agents)[1];
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const cdr = agents.coder || Object.values(agents)[2];
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// Etsitään sopivin mallipohja
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const template = Object.values(templates)[0]; // Toistaiseksi vain FastAPI CRUD
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if (!template) {
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termLog(' ✗ Mallipohjia ei ladattu', '#f85149');
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return;
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}
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termLog(`<span style="color:var(--purple);font-weight:bold">━━━ ${esc(template.name)} — ${esc(task)} ━━━</span>`);
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// Asiakas: jalostaa vaatimukset
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termLog(`<span style="color:var(--purple);font-weight:bold">━━━ Projekti — ${esc(task)} ━━━</span>`);
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termLog(`\n<span style="color:#f0883e;font-weight:bold">[0] ${esc(cli.name)}</span> — vaatimusmäärittely`);
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highlightAgent('client');
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explainStep('Vaatimusmäärittely', `${cli.name} muotoilee idean selkeiksi vaatimuksiksi: ominaisuudet, datamallit, rajapinnat.`);
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@@ -788,37 +798,72 @@ OUTPUT FORMAT:
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if (!brief) { termLog(' ✗ Vaatimusmäärittely epäonnistui', '#f85149'); return; }
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termLog(` <span style="color:#8b949e">Vaatimukset valmiit → Manageri</span>`);
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explainStep('Mallipohja', `Käytetään "${template.name}" -mallipohjaa jossa ${template.order.length} tiedostoa: ${template.order.join(', ')}. Jokainen tiedosto generoidaan järjestyksessä, ja aiemmat tiedostot annetaan kontekstina seuraavalle.`);
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// Valitaan mallipohja automaattisesti briefin perusteella
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const template = selectTemplate(brief);
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// Tiedostolista: mallipohjasta tai managerin dynaamisesta suunnitelmasta
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let fileOrder = [];
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let fileDefs = {};
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if (template) {
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// Mallipohja löytyi — käytetään sen rakennetta
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fileOrder = template.order;
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fileDefs = template.files;
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explainStep('Mallipohja', `Tunnistettiin "${template.name}" — ${fileOrder.length} tiedostoa: ${fileOrder.join(', ')}.`);
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} else {
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// Vapaa tila — Manageri päättää tiedostorakenteen
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termLog(`\n<span style="color:#d29922;font-weight:bold">[1] ${esc(mgr.name)}</span> — tiedostorakenne`);
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highlightAgent('manager');
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explainStep('Vapaa tila', 'Sopivaa mallipohjaa ei löytynyt. Manageri suunnittelee tiedostorakenteen vaatimusten perusteella.');
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const planPrompt = `PROJECT REQUIREMENTS:\n${brief}\n\nPlan the file structure for this project. List each file on its own line:\nfilename.ext: one-line description\n\nMaximum 6 files. List dependency files first.`;
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const plan = await kpnRun(mgr.model, planPrompt, false, mgr);
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if (!plan) { termLog(' ✗ Suunnittelu epäonnistui', '#f85149'); return; }
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// Parsitaan managerin tuottama tiedostolista
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for (const line of plan.split('\n')) {
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const m = line.match(/^\s*[-*]?\s*(\S+\.\w+)\s*[:\-–]\s*(.+)/);
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if (m) {
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const fname = m[1].replace(/^`|`$/g, '');
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fileOrder.push(fname);
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fileDefs[fname] = { description: m[2].trim(), instructions: m[2].trim() };
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}
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}
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if (fileOrder.length === 0) {
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termLog(' ✗ Manageri ei tuottanut tiedostolistaa', '#f85149');
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return;
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}
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explainStep('Suunnitelma', `${fileOrder.length} tiedostoa: ${fileOrder.join(', ')}`);
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}
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const files = {};
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for (let i = 0; i < template.order.length; i++) {
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const fileName = template.order[i];
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const fileDef = template.files[fileName];
|
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for (let i = 0; i < fileOrder.length; i++) {
|
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const fileName = fileOrder[i];
|
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const fileDef = fileDefs[fileName];
|
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if (!fileDef) continue;
|
||||
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const step = i + 1;
|
||||
// Valitaan oikea agentti tiedostotyypin mukaan
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||||
const isDbFile = fileName === 'models.py' || fileName === 'database.py';
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const isDbFile = fileName === 'models.py' || fileName === 'database.py' || fileName === 'etl.py';
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const dataAgent = agents.data || Object.values(agents)[3];
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const fileAgent = isDbFile && dataAgent ? dataAgent : cdr;
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const fileAgentKey = isDbFile && dataAgent ? 'data' : 'coder';
|
||||
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termLog(`\n<span style="color:#3fb950;font-weight:bold">[${step}/${template.order.length}] ${esc(fileAgent.name)}</span> — ${esc(fileName)}`);
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||||
termLog(`\n<span style="color:#3fb950;font-weight:bold">[${step}/${fileOrder.length}] ${esc(fileAgent.name)}</span> — ${esc(fileName)}`);
|
||||
highlightAgent(fileAgentKey);
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||||
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||||
// Opettava selitys: miksi tämä tiedosto, mitä se sisältää
|
||||
explainStep(fileName, fileDef.instructions);
|
||||
explainStep(fileName, fileDef.instructions || fileDef.description);
|
||||
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||||
// Rakennetaan prompti: esimerkki + konteksti + ohje
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||||
// Rakennetaan prompti
|
||||
let prompt = '';
|
||||
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||||
// Agentin system prompt (data-agentti models.py:lle, koodari muille)
|
||||
if (fileAgent.prompt) prompt += fileAgent.prompt + '\n\n';
|
||||
|
||||
// Esimerkki (few-shot)
|
||||
prompt += `EXAMPLE of ${fileName} (for a different project, adapt to this one):\n`;
|
||||
prompt += '```\n' + fileDef.example + '\n```\n\n';
|
||||
// Esimerkki (vain mallipohjatilassa)
|
||||
if (fileDef.example) {
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||||
prompt += `EXAMPLE of ${fileName} (for a different project, adapt to this one):\n`;
|
||||
prompt += '```\n' + fileDef.example + '\n```\n\n';
|
||||
}
|
||||
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||||
// Aiemmin generoidut tiedostot (konteksti)
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||||
const prevFiles = Object.entries(files);
|
||||
@@ -834,8 +879,8 @@ OUTPUT FORMAT:
|
||||
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||||
// Tehtävä
|
||||
prompt += `NOW write "${fileName}" for THIS project: ${task}\n`;
|
||||
prompt += fileDef.instructions + '\n';
|
||||
prompt += 'Adapt the example to match the project description. Import from already written files. Write ONLY the code, no explanations.';
|
||||
if (fileDef.instructions) prompt += fileDef.instructions + '\n';
|
||||
prompt += 'Adapt to the project requirements. Import from already written files. Write ONLY the code, no explanations.';
|
||||
|
||||
const code = await kpnRun(fileAgent.model, prompt, false, fileAgent);
|
||||
if (!code) {
|
||||
|
||||
@@ -4,6 +4,13 @@ set -e
|
||||
SCRIPT_DIR="$(cd "$(dirname "$0")" && pwd)"
|
||||
echo "=== Kipinä Studio Local Development ==="
|
||||
|
||||
# Tapetaan vanhat prosessit portissa 3000
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||||
if lsof -ti:3000 >/dev/null 2>&1; then
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||||
echo "[0] Tapetaan vanhat prosessit portissa 3000..."
|
||||
lsof -ti:3000 | xargs kill -9 2>/dev/null || true
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||||
sleep 1
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||||
fi
|
||||
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||||
# Frontend
|
||||
echo "[1/3] Rakennetaan frontend..."
|
||||
cd "$SCRIPT_DIR/frontend"
|
||||
@@ -12,18 +19,32 @@ npm run build --silent 2>&1 | tail -1
|
||||
|
||||
# Hub
|
||||
echo "[2/3] Käynnistetään hub..."
|
||||
cd "$SCRIPT_DIR/hub"
|
||||
cargo run &
|
||||
cd "$SCRIPT_DIR"
|
||||
STATIC_DIR="$SCRIPT_DIR/frontend/dist" cargo run -p hub &
|
||||
HUB_PID=$!
|
||||
sleep 3
|
||||
sleep 2
|
||||
|
||||
# Native-node (jos Ollama on käynnissä)
|
||||
if curl -s http://localhost:11434/api/tags >/dev/null 2>&1; then
|
||||
echo "[3/3] Ollama löytyi — käynnistetään native-node..."
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||||
cd "$SCRIPT_DIR/native-node"
|
||||
HUB_URL=ws://localhost:3000/ws cargo run --no-default-features &
|
||||
NODE_PID=$!
|
||||
echo " Native-node PID: $NODE_PID"
|
||||
# Valitaan automaattisesti ensimmäinen qwen-coder -malli
|
||||
MODEL=$(curl -s http://localhost:11434/api/tags | python3 -c "
|
||||
import sys, json
|
||||
models = json.load(sys.stdin).get('models', [])
|
||||
for m in models:
|
||||
if 'coder' in m['name']:
|
||||
print(m['name']); break
|
||||
else:
|
||||
if models: print(models[0]['name'])
|
||||
" 2>/dev/null)
|
||||
|
||||
if [ -n "$MODEL" ]; then
|
||||
echo "[3/3] Ollama löytyi — käynnistetään native-node (malli: $MODEL)..."
|
||||
HUB_URL=ws://localhost:3000/ws OLLAMA_MODEL="$MODEL" cargo run -p native-node --no-default-features &
|
||||
NODE_PID=$!
|
||||
echo " Native-node PID: $NODE_PID"
|
||||
else
|
||||
echo "[3/3] Ollama käynnissä mutta ei malleja — asenna: ollama pull qwen2.5-coder:7b"
|
||||
fi
|
||||
else
|
||||
echo "[3/3] Ollama ei käynnissä — käytetään selaimen Wasm-laskentaa"
|
||||
echo " Nopeampi: ollama serve & ollama pull qwen2.5-coder:7b && ./local.sh"
|
||||
@@ -33,5 +54,11 @@ echo ""
|
||||
echo "=== http://localhost:3000 ==="
|
||||
echo " Ctrl+C pysäyttää"
|
||||
|
||||
# Avataan selain
|
||||
open http://localhost:3000 2>/dev/null || xdg-open http://localhost:3000 2>/dev/null || true
|
||||
|
||||
# Siivotaan lapset Ctrl+C:llä
|
||||
trap 'echo ""; echo "Pysäytetään..."; kill $HUB_PID $NODE_PID 2>/dev/null; exit 0' INT TERM
|
||||
|
||||
# Odotetaan hub-prosessia
|
||||
wait $HUB_PID
|
||||
|
||||
@@ -109,14 +109,21 @@ impl LlmEngine {
|
||||
let model = self.model.borrow().clone();
|
||||
|
||||
let default_stop: Vec<String> = vec![
|
||||
"<|im_end|>".into(), "\n###".into(), "\nExplanation".into(),
|
||||
"\nNote:".into(), "\nPlease note".into(), "\nThis is".into(),
|
||||
"\n```\n\n".into(), "\n// Example".into(), "\n# Example".into(),
|
||||
"<|im_end|>".into(),
|
||||
];
|
||||
|
||||
let mut body = serde_json::json!({
|
||||
// Rakennetaan messages-lista (chat API)
|
||||
let mut messages = Vec::new();
|
||||
if let Some(ref sp) = opts.system_prompt {
|
||||
if !sp.is_empty() {
|
||||
messages.push(serde_json::json!({"role": "system", "content": sp}));
|
||||
}
|
||||
}
|
||||
messages.push(serde_json::json!({"role": "user", "content": prompt}));
|
||||
|
||||
let body = serde_json::json!({
|
||||
"model": model,
|
||||
"prompt": prompt,
|
||||
"messages": messages,
|
||||
"stream": false,
|
||||
"options": {
|
||||
"num_predict": opts.max_tokens,
|
||||
@@ -126,16 +133,13 @@ impl LlmEngine {
|
||||
"stop": opts.stop.as_ref().unwrap_or(&default_stop),
|
||||
}
|
||||
});
|
||||
if let Some(ref sp) = opts.system_prompt {
|
||||
body.as_object_mut().unwrap().insert("system".to_string(), serde_json::json!(sp));
|
||||
}
|
||||
|
||||
let start = Instant::now();
|
||||
let resp = self.client.post(format!("{}/api/generate", self.ollama_url))
|
||||
let resp = self.client.post(format!("{}/api/chat", self.ollama_url))
|
||||
.json(&body)
|
||||
.send()
|
||||
.await
|
||||
.map_err(|e| format!("Ollama generate: {}", e))?;
|
||||
.map_err(|e| format!("Ollama chat: {}", e))?;
|
||||
|
||||
if !resp.status().is_success() {
|
||||
return Err(format!("Ollama HTTP {}", resp.status()));
|
||||
@@ -144,7 +148,7 @@ impl LlmEngine {
|
||||
let body: serde_json::Value = resp.json().await
|
||||
.map_err(|e| format!("Ollama JSON: {}", e))?;
|
||||
|
||||
let text = body["response"].as_str().unwrap_or("").to_string();
|
||||
let text = body["message"]["content"].as_str().unwrap_or("").to_string();
|
||||
let _total_duration_ns = body["total_duration"].as_u64().unwrap_or(0);
|
||||
let eval_count = body["eval_count"].as_u64().unwrap_or(0) as usize;
|
||||
let eval_duration_ns = body["eval_duration"].as_u64().unwrap_or(1);
|
||||
@@ -163,40 +167,15 @@ impl LlmEngine {
|
||||
}
|
||||
}
|
||||
|
||||
/// Siivoa markdown-koodiblokki-merkit ja selitystekstit
|
||||
/// Siivoa markdown-koodiblokki-merkit vastauksesta
|
||||
fn strip_code_fences(text: &str) -> String {
|
||||
// Poistetaan kaikki ```-rivit ja kielitunnisteet (```python, ```rust jne.)
|
||||
let lines: Vec<&str> = text.lines().collect();
|
||||
let filtered: Vec<&str> = lines.into_iter().filter(|line| {
|
||||
let trimmed = line.trim();
|
||||
// Poista rivit jotka ovat pelkkiä ``` tai ```kielitunniste
|
||||
if trimmed.starts_with("```") {
|
||||
return false;
|
||||
}
|
||||
true
|
||||
trimmed != "```" && !(trimmed.starts_with("```") && !trimmed[3..].contains('`'))
|
||||
}).collect();
|
||||
let mut result = filtered.join("\n").trim().to_string();
|
||||
|
||||
// Poista selitysteksti lopusta (kaikki rivin "\nPlease note" jälkeen jne.)
|
||||
let lower = result.to_lowercase();
|
||||
for stop in &["\nplease note", "\nthis is a basic", "\nthis code", "\nnote that", "\nremember to", "\nyou can", "\nto run"] {
|
||||
if let Some(pos) = lower.find(stop) {
|
||||
result = result[..pos].trim_end().to_string();
|
||||
}
|
||||
}
|
||||
|
||||
// Poista johdantolauseet alusta
|
||||
let lower = result.to_lowercase();
|
||||
for prefix in &["sure!", "here is", "here's", "certainly!", "below is"] {
|
||||
if lower.starts_with(prefix) {
|
||||
if let Some(nl) = result.find('\n') {
|
||||
result = result[nl + 1..].to_string();
|
||||
}
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
result.trim().to_string()
|
||||
filtered.join("\n").trim().to_string()
|
||||
}
|
||||
|
||||
pub struct GenerateResult {
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
use futures_util::{SinkExt, StreamExt};
|
||||
use serde_json::json;
|
||||
use std::io::IsTerminal;
|
||||
use sysinfo::System;
|
||||
use tokio_tungstenite::connect_async;
|
||||
use tokio_tungstenite::tungstenite::Message;
|
||||
@@ -362,13 +363,17 @@ async fn main() {
|
||||
st.push_log("System", format!("Malli valmis: {}", active_model), None);
|
||||
}
|
||||
|
||||
// Käynnistetään graafinen TUI vasta kun TUI:n Prompt (LlmEngine::load) on ohitettu!
|
||||
// Käynnistetään graafinen TUI vain jos stdin on terminaali (ei taustaprosessina)
|
||||
let ui_state = tui_state.clone();
|
||||
tokio::spawn(async move {
|
||||
if let Err(e) = tui_dashboard::run_dashboard(ui_state, cmd_tx).await {
|
||||
tracing::error!("Pääluupin TUI kaatui: {}", e);
|
||||
}
|
||||
});
|
||||
if std::io::stdin().is_terminal() {
|
||||
tokio::spawn(async move {
|
||||
if let Err(e) = tui_dashboard::run_dashboard(ui_state, cmd_tx).await {
|
||||
tracing::error!("Pääluupin TUI kaatui: {}", e);
|
||||
}
|
||||
});
|
||||
} else {
|
||||
tracing::info!("Ei terminaalia — TUI ohitettu, lokitetaan stdoutiin");
|
||||
};
|
||||
|
||||
// Haetaan paikalliset mallit hubille lähetettäväksi
|
||||
let mut available_models = None;
|
||||
@@ -418,6 +423,48 @@ async fn main() {
|
||||
st.status = "ACTIVE".to_string();
|
||||
st.push_log("System", "Suoritus jatkuu...".to_string(), None);
|
||||
}
|
||||
} else if cmd_str == "fetch_models" {
|
||||
// Haetaan mallit Ollamasta ja avataan valikkö
|
||||
if let Some(ref engine) = llm {
|
||||
match engine.fetch_models().await {
|
||||
Ok(tags) => {
|
||||
let models: Vec<String> = tags.get("models")
|
||||
.and_then(|v| v.as_array())
|
||||
.map(|arr| arr.iter()
|
||||
.filter_map(|m| m.get("name").and_then(|n| n.as_str()).map(|s| s.to_string()))
|
||||
.collect())
|
||||
.unwrap_or_default();
|
||||
let mut st = tui_state.write().await;
|
||||
st.model_picker_items = models;
|
||||
st.model_picker_idx = 0;
|
||||
st.model_picker_open = true;
|
||||
}
|
||||
Err(e) => {
|
||||
let mut st = tui_state.write().await;
|
||||
st.push_log("System", format!("Mallilistan haku epäonnistui: {}", e), None);
|
||||
}
|
||||
}
|
||||
}
|
||||
} else if let Some(model) = cmd_str.strip_prefix("change_model:") {
|
||||
// TUI:sta valittu malli — vaihdetaan
|
||||
if let Some(ref engine) = llm {
|
||||
engine.set_model(model.to_string());
|
||||
match engine.ensure_model().await {
|
||||
Ok(()) => {
|
||||
tracing::info!("Malli vaihdettu: {}", model);
|
||||
let mut st = tui_state.write().await;
|
||||
st.model_name = model.to_string();
|
||||
st.push_log("System", format!("Malli vaihdettu: {}", model), None);
|
||||
// Ilmoitetaan hubille
|
||||
let auth = build_auth_message(allocated_gb, model, available_models.clone());
|
||||
let _ = write.send(Message::Text(auth)).await;
|
||||
}
|
||||
Err(e) => {
|
||||
let mut st = tui_state.write().await;
|
||||
st.push_log("System", format!("Mallin vaihto epäonnistui: {}", e), None);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -35,6 +35,10 @@ pub struct DashboardState {
|
||||
pub last_tokens_sec: f64,
|
||||
pub network_active_nodes: usize,
|
||||
pub network_total_tasks: u64,
|
||||
// Mallivalikko
|
||||
pub model_picker_open: bool,
|
||||
pub model_picker_items: Vec<String>,
|
||||
pub model_picker_idx: usize,
|
||||
}
|
||||
|
||||
impl DashboardState {
|
||||
@@ -51,6 +55,9 @@ impl DashboardState {
|
||||
last_tokens_sec: 0.0,
|
||||
network_active_nodes: 1, // oletetaan itsemme
|
||||
network_total_tasks: 0,
|
||||
model_picker_open: false,
|
||||
model_picker_items: Vec::new(),
|
||||
model_picker_idx: 0,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -88,20 +95,53 @@ pub async fn run_dashboard(
|
||||
}
|
||||
ev = reader.next() => {
|
||||
if let Some(Ok(Event::Key(key))) = ev {
|
||||
match key.code {
|
||||
KeyCode::Char('q') | KeyCode::Esc => {
|
||||
// Palautetaan näyttö ja suljetaan ohjelma
|
||||
disable_raw_mode()?;
|
||||
execute!(terminal.backend_mut(), LeaveAlternateScreen)?;
|
||||
std::process::exit(0);
|
||||
let picker_open = state.read().await.model_picker_open;
|
||||
|
||||
if picker_open {
|
||||
// Mallivalikko auki — navigointi
|
||||
match key.code {
|
||||
KeyCode::Up | KeyCode::Char('k') => {
|
||||
let mut st = state.write().await;
|
||||
if st.model_picker_idx > 0 { st.model_picker_idx -= 1; }
|
||||
}
|
||||
KeyCode::Down | KeyCode::Char('j') => {
|
||||
let mut st = state.write().await;
|
||||
let max = st.model_picker_items.len().saturating_sub(1);
|
||||
if st.model_picker_idx < max { st.model_picker_idx += 1; }
|
||||
}
|
||||
KeyCode::Enter => {
|
||||
let mut st = state.write().await;
|
||||
let idx = st.model_picker_idx;
|
||||
if let Some(model) = st.model_picker_items.get(idx).cloned() {
|
||||
st.model_picker_open = false;
|
||||
st.push_log("System", format!("Vaihdetaan malliin: {}...", model), None);
|
||||
let _ = cmd_tx.send(format!("change_model:{}", model));
|
||||
}
|
||||
}
|
||||
KeyCode::Esc | KeyCode::Char('m') | KeyCode::Char('M') => {
|
||||
state.write().await.model_picker_open = false;
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
KeyCode::Char('p') | KeyCode::Char('P') => {
|
||||
let _ = cmd_tx.send("pause".to_string());
|
||||
} else {
|
||||
// Normaali tila
|
||||
match key.code {
|
||||
KeyCode::Char('q') | KeyCode::Esc => {
|
||||
disable_raw_mode()?;
|
||||
execute!(terminal.backend_mut(), LeaveAlternateScreen)?;
|
||||
std::process::exit(0);
|
||||
}
|
||||
KeyCode::Char('p') | KeyCode::Char('P') => {
|
||||
let _ = cmd_tx.send("pause".to_string());
|
||||
}
|
||||
KeyCode::Char('r') | KeyCode::Char('R') | KeyCode::Char('s') => {
|
||||
let _ = cmd_tx.send("resume".to_string());
|
||||
}
|
||||
KeyCode::Char('m') | KeyCode::Char('M') => {
|
||||
let _ = cmd_tx.send("fetch_models".to_string());
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
KeyCode::Char('r') | KeyCode::Char('R') | KeyCode::Char('s') => {
|
||||
let _ = cmd_tx.send("resume".to_string());
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -214,10 +254,43 @@ fn ui(f: &mut ratatui::Frame, st: &DashboardState) {
|
||||
|
||||
// --- Footer / Status ---
|
||||
let status_color = if st.status == "ACTIVE" { Color::Green } else { Color::Yellow };
|
||||
let status_text = format!(" Tila: {} | Komennot: [P] Pause / [R] Työhön / [Q] Sulje ", st.status);
|
||||
let status_text = format!(" Tila: {} | [P] Pause [R] Työhön [M] Malli [Q] Sulje ", st.status);
|
||||
let footer = Paragraph::new(status_text)
|
||||
.style(Style::default().fg(status_color).add_modifier(Modifier::BOLD))
|
||||
.alignment(Alignment::Center)
|
||||
.block(Block::default().borders(Borders::ALL));
|
||||
f.render_widget(footer, chunks[2]);
|
||||
|
||||
// --- Mallivalikko-overlay ---
|
||||
if st.model_picker_open && !st.model_picker_items.is_empty() {
|
||||
let area = f.area();
|
||||
let popup_h = (st.model_picker_items.len() as u16 + 4).min(area.height - 4);
|
||||
let popup_w = 50.min(area.width - 4);
|
||||
let popup = ratatui::layout::Rect::new(
|
||||
(area.width - popup_w) / 2,
|
||||
(area.height - popup_h) / 2,
|
||||
popup_w,
|
||||
popup_h,
|
||||
);
|
||||
|
||||
// Tausta
|
||||
f.render_widget(ratatui::widgets::Clear, popup);
|
||||
|
||||
let items: Vec<ratatui::text::Line> = st.model_picker_items.iter().enumerate().map(|(i, name)| {
|
||||
if i == st.model_picker_idx {
|
||||
ratatui::text::Line::from(format!(" ▸ {} ", name))
|
||||
.style(Style::default().fg(Color::Cyan).add_modifier(Modifier::BOLD))
|
||||
} else {
|
||||
ratatui::text::Line::from(format!(" {} ", name))
|
||||
.style(Style::default().fg(Color::White))
|
||||
}
|
||||
}).collect();
|
||||
|
||||
let picker = Paragraph::new(items)
|
||||
.block(Block::default()
|
||||
.title(" Vaihda malli [↑↓] Enter=valitse Esc=peruuta ")
|
||||
.borders(Borders::ALL)
|
||||
.style(Style::default().fg(Color::Cyan)));
|
||||
f.render_widget(picker, popup);
|
||||
}
|
||||
}
|
||||
|
||||
Binary file not shown.
Reference in New Issue
Block a user