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fix(blender): switch from Ollama to Gemini Flash for script generation 

Ollama runs CPU-only on Netcup — 7B models take minutes, exceeding
Cloudflare's 100s timeout (524). Gemini 2.0 Flash responds in seconds.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Jeff Emmett 2026-03-25 16:51:35 -07:00
parent 4a75c64a18
commit c046acf9ce
1 changed files with 22 additions and 30 deletions
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52
server/index.ts
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@ -1556,52 +1556,44 @@ const RUNPOD_API_KEY = process.env.RUNPOD_API_KEY || "";
app.get("/api/blender-gen/health", async (c) => {
const issues: string[] = [];
const warnings: string[] = [];
const OLLAMA_URL = process.env.OLLAMA_URL || "http://localhost:11434";
try {
const res = await fetch(`${OLLAMA_URL}/api/tags`, { signal: AbortSignal.timeout(3000) });
if (!res.ok) issues.push("Ollama not responding");
} catch {
issues.push("Ollama unreachable");
}
if (!GEMINI_API_KEY) issues.push("GEMINI_API_KEY not configured");
if (!RUNPOD_API_KEY) warnings.push("RunPod not configured — script-only mode");
return c.json({ available: issues.length === 0, issues, warnings });
});
app.post("/api/blender-gen", async (c) => {
if (!GEMINI_API_KEY) return c.json({ error: "GEMINI_API_KEY not configured" }, 503);
const { prompt } = await c.req.json();
if (!prompt) return c.json({ error: "prompt required" }, 400);
// Step 1: Generate Blender Python script via LLM
const OLLAMA_URL = process.env.OLLAMA_URL || "http://localhost:11434";
// Step 1: Generate Blender Python script via Gemini Flash
let script = "";
try {
const llmRes = await fetch(`${OLLAMA_URL}/api/generate`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({
model: process.env.OLLAMA_MODEL || "qwen2.5-coder:7b",
prompt: `Generate a Blender Python script that creates: ${prompt}\n\nThe script should:\n- Import bpy\n- Clear the default scene\n- Create the described objects with materials\n- Set up basic lighting and camera\n- Render to /tmp/render.png at 1024x1024\n\nOnly output the Python code, no explanations.`,
stream: false,
}),
});
const { GoogleGenerativeAI } = await import("@google/generative-ai");
const genAI = new GoogleGenerativeAI(GEMINI_API_KEY);
const model = genAI.getGenerativeModel({ model: "gemini-2.0-flash" });
const result = await model.generateContent(`Generate a Blender Python script that creates: ${prompt}
if (llmRes.ok) {
const llmData = await llmRes.json();
script = llmData.response || "";
// Extract code block if wrapped in markdown
const codeMatch = script.match(/```(?:python)?\n([\s\S]*?)```/);
if (codeMatch) script = codeMatch[1].trim();
} else {
const errText = await llmRes.text().catch(() => "");
console.error(`[blender-gen] Ollama ${llmRes.status}: ${errText}`);
}
The script should:
- Import bpy
- Clear the default scene (delete all default objects)
- Create the described objects with materials and colors
- Set up basic lighting (sun + area light) and camera positioned to frame the scene
- Render to /tmp/render.png at 1024x1024
Output ONLY the Python code, no explanations or comments outside the code.`);
const text = result.response.text();
const codeMatch = text.match(/```(?:python)?\n([\s\S]*?)```/);
script = codeMatch ? codeMatch[1].trim() : text.trim();
} catch (e) {
console.error("[blender-gen] LLM error:", e);
console.error("[blender-gen] Gemini error:", e);
}
if (!script) {
return c.json({ error: "Failed to generate Blender script — is Ollama running?" }, 502);
return c.json({ error: "Failed to generate Blender script" }, 502);
}
// Step 2: Execute on RunPod (headless Blender) — optional