CrewAI-yhteensopiva projektioutput: agents.yaml, tasks.yaml, crew.py, prompts/

Pipeline kerää promptLog-listan jokaisesta agenttikutsusta (system prompt +
syöte + tulos) ja generoi lopuksi CrewAI-rakenteen files-objektiin.
Korjattu myös template.order.length-kaatuminen vapaassa tilassa.

network-poc/frontend/src/pages/index.astro

@@ -793,8 +793,92 @@ OUTPUT FORMAT:
         termLog(`  <span style="color:#8b949e;font-size:12px">${esc(explanation)}</span>`);
     }
 
+    // --- CrewAI-yhteensopiva output ---
+    function generateCrewAIFiles(promptLog, task) {
+        const crewFiles = {};
+
+        // Kerätään uniikit agentit
+        const agentMap = {};
+        for (const entry of promptLog) {
+            if (!agentMap[entry.agentKey]) {
+                const firstSentence = (entry.systemPrompt || '').split(/\.\s/)[0].trim();
+                agentMap[entry.agentKey] = {
+                    name: entry.agentName,
+                    model: entry.model,
+                    systemPrompt: entry.systemPrompt || '',
+                    goal: firstSentence.replace(/^You are (a |an )?/i, '').trim() || entry.label,
+                };
+            }
+        }
+
+        // agents.yaml
+        let ay = '# Agents — Kipinä Agentic Studio → CrewAI\n';
+        for (const [key, a] of Object.entries(agentMap)) {
+            ay += `\n${key}:\n`;
+            ay += `  role: >-\n    ${a.name}\n`;
+            ay += `  goal: >-\n    ${a.goal}\n`;
+            ay += `  backstory: |\n`;
+            for (const line of a.systemPrompt.split('\n')) {
+                ay += `    ${line}\n`;
+            }
+            ay += `  llm: ${a.model}\n`;
+        }
+        crewFiles['agents.yaml'] = ay;
+
+        // tasks.yaml
+        let ty = '# Tasks — Kipinä Agentic Studio → CrewAI\n';
+        for (let i = 0; i < promptLog.length; i++) {
+            const e = promptLog[i];
+            const name = `step_${i}_${e.label.replace(/[^a-z0-9]/gi, '_').toLowerCase()}`;
+            ty += `\n${name}:\n`;
+            ty += `  description: |\n`;
+            const descLines = e.userPrompt.split('\n').slice(0, 20);
+            for (const line of descLines) {
+                ty += `    ${line}\n`;
+            }
+            if (e.userPrompt.split('\n').length > 20) ty += `    # ... (truncated)\n`;
+            ty += `  expected_output: >-\n    ${e.label}\n`;
+            ty += `  agent: ${e.agentKey}\n`;
+        }
+        crewFiles['tasks.yaml'] = ty;
+
+        // crew.py
+        const agentKeys = Object.keys(agentMap);
+        const taskNames = promptLog.map((e, i) => `step_${i}_${e.label.replace(/[^a-z0-9]/gi, '_').toLowerCase()}`);
+        let py = `"""${task}\n\nCrewAI crew — generated by Kipinä Agentic Studio.\nRun: crewai run\n"""\n\n`;
+        py += `from crewai import Agent, Crew, Process, Task\n`;
+        py += `from crewai.project import CrewBase, agent, crew, task\n\n\n`;
+        py += `@CrewBase\nclass ProjectCrew:\n    """${task}"""\n\n`;
+        py += `    agents_config = "agents.yaml"\n    tasks_config = "tasks.yaml"\n\n`;
+        for (const key of agentKeys) {
+            py += `    @agent\n    def ${key}(self) -> Agent:\n        return Agent(config=self.agents_config["${key}"])\n\n`;
+        }
+        for (const name of taskNames) {
+            py += `    @task\n    def ${name}(self) -> Task:\n        return Task(config=self.tasks_config["${name}"])\n\n`;
+        }
+        py += `    @crew\n    def crew(self) -> Crew:\n        return Crew(\n`;
+        py += `            agents=self.agents,\n            tasks=self.tasks,\n`;
+        py += `            process=Process.sequential,\n            verbose=True,\n        )\n`;
+        crewFiles['crew.py'] = py;
+
+        // prompts/*.md — jokaisen vaiheen system prompt + syöte + tulos
+        for (let i = 0; i < promptLog.length; i++) {
+            const e = promptLog[i];
+            let md = `# ${i} — ${e.agentName} (${e.agentKey}) — ${e.label}\n\n`;
+            md += `**Malli:** \`${e.model}\`\n\n`;
+            md += `## System Prompt\n\n\`\`\`\n${e.systemPrompt || '(ei system promptia)'}\n\`\`\`\n\n`;
+            md += `## Syöte\n\n\`\`\`\n${e.userPrompt}\n\`\`\`\n\n`;
+            md += `## Tulos\n\n\`\`\`\n${e.response || '(ei tulosta)'}\n\`\`\`\n`;
+            const safe = e.label.replace(/[^a-z0-9._-]/gi, '_').toLowerCase();
+            crewFiles[`prompts/${i}_${e.agentKey}_${safe}.md`] = md;
+        }
+
+        return crewFiles;
+    }
+
     async function kpnProject(task) {
         pipelineAbort = new AbortController();
+        const promptLog = [];
         const cli = agents.client || Object.values(agents)[0];
         const mgr = agents.manager || Object.values(agents)[1];
         const cdr = agents.coder || Object.values(agents)[2];
@@ -806,6 +890,7 @@ OUTPUT FORMAT:
         explainStep('Vaatimusmäärittely', `${cli.name} muotoilee idean selkeiksi vaatimuksiksi: ominaisuudet, datamallit, rajapinnat.`);
         const brief = await kpnRun(cli.model, `${task}`, false, cli);
         if (!brief) { termLog('  ✗ Vaatimusmäärittely epäonnistui', '#f85149'); return; }
+        promptLog.push({ step: 0, agentKey: 'client', agentName: cli.name, model: cli.model, label: 'vaatimusmäärittely', systemPrompt: cli.prompt || '', userPrompt: task, response: brief });
         termLog(`  <span style="color:#8b949e">Vaatimukset valmiit → Manageri</span>`);
 
         // Valitaan mallipohja automaattisesti briefin perusteella
@@ -843,6 +928,7 @@ OUTPUT FORMAT:
                 return;
             }
             explainStep('Suunnitelma', `${fileOrder.length} tiedostoa: ${fileOrder.join(', ')}`);
+            promptLog.push({ step: 1, agentKey: 'manager', agentName: mgr.name, model: mgr.model, label: 'tiedostorakenne', systemPrompt: mgr.prompt || '', userPrompt: planPrompt, response: plan });
         }
 
         const files = {};
@@ -898,10 +984,11 @@ OUTPUT FORMAT:
                 return;
             }
             files[fileName] = code;
+            promptLog.push({ step: promptLog.length, agentKey: fileAgentKey, agentName: fileAgent.name, model: fileAgent.model, label: fileName, systemPrompt: fileAgent.prompt || '', userPrompt: prompt, response: code });
         }
 
         const allCode = Object.entries(files).map(([n,c]) => `--- ${n} ---\n${c}`).join('\n\n');
-        let stepN = template.order.length + 1;
+        let stepN = fileOrder.length + 1;
 
         // Review-korjausluuppi: max 2 kierrosta
         const tst = agents.tester || Object.values(agents)[5];
@@ -918,6 +1005,7 @@ OUTPUT FORMAT:
 
             const reviewPrompt = (tst.prompt ? tst.prompt+'\n\n' : '') + `Review this project:\n\n${currentCode}`;
             const review = await kpnRun(tst.model, reviewPrompt, false, tst);
+            promptLog.push({ step: promptLog.length, agentKey: 'tester', agentName: tst.name, model: tst.model, label: 'review' + (round > 0 ? '_r'+(round+1) : ''), systemPrompt: tst.prompt || '', userPrompt: reviewPrompt, response: review || '' });
             stepN++;
 
             // LGTM → ei korjauksia tarvita
@@ -936,6 +1024,7 @@ OUTPUT FORMAT:
 
             // Parsitaan korjatut tiedostot takaisin files-objektiin
             if (fixedCode) {
+                promptLog.push({ step: promptLog.length, agentKey: 'coder', agentName: cdr.name, model: cdr.model, label: 'korjaus' + (round > 0 ? '_r'+(round+1) : ''), systemPrompt: cdr.prompt || '', userPrompt: fixPrompt, response: fixedCode });
                 const fixedParts = fixedCode.split(/^---\s*(\S+)\s*---$/m);
                 for (let j = 1; j < fixedParts.length; j += 2) {
                     const fname = fixedParts[j].trim();
@@ -959,7 +1048,10 @@ OUTPUT FORMAT:
             explainStep('Testit', `${qaAgent.name} kirjoittaa pytest-testit korjatulle koodille.`);
             const qaPrompt = (qaAgent.prompt ? qaAgent.prompt+'\n\n' : '') + `Write pytest tests for this project:\n\n${updatedCode}\n\nWrite a complete test_main.py file with TestClient.`;
             const tests = await kpnRun(qaAgent.model, qaPrompt, false, qaAgent);
-            if (tests) files['test_main.py'] = tests;
+            if (tests) {
+                files['test_main.py'] = tests;
+                promptLog.push({ step: promptLog.length, agentKey: 'qa', agentName: qaAgent.name, model: qaAgent.model, label: 'test_main.py', systemPrompt: qaAgent.prompt || '', userPrompt: qaPrompt, response: tests });
+            }
             stepN++;
         }
 
@@ -979,7 +1071,10 @@ OUTPUT FORMAT:
             `- CMD: uv run uvicorn main:app --host 0.0.0.0 --port 8000\n` +
             `\nWrite ONLY the Dockerfile, no explanations.`;
         const dockerfile = await kpnRun(tst.model, dockerPrompt, false, tst);
-        if (dockerfile) files['Dockerfile'] = dockerfile;
+        if (dockerfile) {
+            files['Dockerfile'] = dockerfile;
+            promptLog.push({ step: promptLog.length, agentKey: 'tester', agentName: tst.name, model: tst.model, label: 'Dockerfile', systemPrompt: tst.prompt || '', userPrompt: dockerPrompt, response: dockerfile });
+        }
         stepN++;
 
         // Tarkkailija: yhteenveto + raportti + arvosana
@@ -1018,6 +1113,7 @@ OUTPUT FORMAT:
                 files['README.md'] = readme;
                 // Tallennetaan raportti globaalisti jotta tarkkailija-klikkaus avaa sen
                 window._lastReport = readme;
+                promptLog.push({ step: promptLog.length, agentKey: 'observer', agentName: obs.name, model: obs.model, label: 'README.md', systemPrompt: obs.prompt || '', userPrompt: obsPrompt, response: readme });
                 // Parsitaan arvosana → tarkkailijan kehäväri
                 const firstLine = readme.split('\n')[0].toUpperCase();
                 let verdictColor = '#3fb950'; // oletus: vihreä
@@ -1040,6 +1136,10 @@ OUTPUT FORMAT:
 
         termLog(`\n<span style="color:var(--purple);font-weight:bold">━━━ Valmis (${Object.keys(files).length} tiedostoa) ━━━</span>`);
         explainStep('Tulos', `Projekti "${task}" generoitu ${Object.keys(files).length} tiedostoon. Klikkaa "Avaa editorissa" tutkiaksesi koodia ja README:tä.`);
+        // CrewAI-yhteensopiva output
+        const crewFiles = generateCrewAIFiles(promptLog, task);
+        Object.assign(files, crewFiles);
+
         renderProjectCard(files, task);
     }