Blueprint Canvas

\n \n

\n \n\n\n\n`;\n}\n\n// --- HONO APPLICATION SETUP (MODIFIED FOR BLUEPRINT CANVAS) ---\nconst app = new Hono();\n\napp.get(\"/\", (c: Context) => c.html(generateHtml(c.req.url)));\n\n// New endpoint to provide the list of available nodes to the frontend.\napp.get(\"/api/nodes/palette\", (c: Context) => {\n return c.json(NODE_PALETTE);\n});\n\n// The new core execution engine for the Blueprint Canvas.\napp.post(\"/api/blueprint/execute\", async (c: Context) => {\n const { blueprint, company_context } = await c.req.json<\n BlueprintExecuteBody\n >();\n if (!blueprint || !company_context) {\n return c.json({ error: \"Blueprint and context are required\" }, 400);\n }\n\n // --- Topological Sort to process nodes in dependency order ---\n // This is the key to \"chaining\". We process nodes that have no inputs first.\n const sortedNodes: Node[] = [];\n const nodeMap = new Map(blueprint.nodes.map((node) => [node.id, node]));\n const inDegree = new Map(blueprint.nodes.map((node) => [node.id, 0]));\n const adjList = new Map(blueprint.nodes.map((node) => [node.id, []]));\n\n for (const conn of blueprint.connections) {\n adjList.get(conn.from)?.push(conn.to);\n inDegree.set(conn.to, (inDegree.get(conn.to) || 0) + 1);\n }\n\n const queue = blueprint.nodes.filter((node) => inDegree.get(node.id) === 0);\n\n while (queue.length > 0) {\n const nodeId = queue.shift()!.id;\n sortedNodes.push(nodeMap.get(nodeId)!);\n\n for (const neighborId of adjList.get(nodeId) || []) {\n inDegree.set(neighborId, inDegree.get(neighborId)! - 1);\n if (inDegree.get(neighborId) === 0) {\n queue.push(nodeMap.get(neighborId)!);\n }\n }\n }\n // --- End of Sort ---\n\n // Build the user content that will be sent to the AI compiler.\n // Each node's data becomes a step in the final prompt.\n const compilerSteps = sortedNodes.map((node, index) => {\n // In a real app, the output of a previous node could be injected as input to the next.\n return {\n step: index + 1,\n node_type: node.type,\n data: node.data,\n };\n });\n\n const systemPrompt = `# YOUR CONTEXT\n- Company: ${company_context.company_name} (${company_context.company_description})\n- Goal: ${company_context.use_case}\n- Language: ${company_context.language}\n---\n${BLUEPRINT_COMPILER_SYSTEM_PROMPT}`;\n\n const userPrompt =\n `Here is the project blueprint data, sorted in execution order. Please compile it into a project brief.\\n\\n${\n JSON.stringify(compilerSteps, null, 2)\n }`;\n\n try {\n const openai = new OpenAI();\n const stream = await openai.chat.completions.create({\n model: \"gpt-4o\",\n messages: [\n { role: \"system\", content: systemPrompt },\n { role: \"user\", content: userPrompt },\n ],\n stream: true,\n });\n return streamText(c, async (s) => {\n for await (const part of stream) {\n await s.write(part.choices[0]?.delta?.content || \"\");\n }\n });\n } catch (e) {\n return c.body(`AI execution failed: ${e.message}`, 500);\n }\n});\n\n// Export the Hono app\nexport default app.fetch;","deleted","label",[98],"permalink","https://www.val.town/x/real/Blueprint/code/main.tsx","extension","actionData","errors"]

Compiled Project Brief