refactor: modularize imageGeneration.ts into focused modules (#3594)

Author: oyi77

open-sse/handlers/imageGeneration.ts

@@ -0,0 +1,221 @@
+
+/**
+ * Image Generation Handler
+ *
+ * Handles POST /v1/images/generations requests.
+ * Proxies to upstream image generation providers using OpenAI-compatible format.
+ *
+ * Request format (OpenAI-compatible):
+ * {
+ *   "model": "openai/gpt-image-2",
+ *   "prompt": "a beautiful sunset over mountains",
+ *   "n": 1,
+ *   "size": "1024x1024",
+ *   "quality": "standard",       // optional: "standard" | "hd"
+ *   "response_format": "url"     // optional: "url" | "b64_json"
+ * }
+ */
+
+import { getImageProvider, parseImageModel } from "../../config/imageRegistry.ts";
+
+import { mapImageSize } from "../../translator/image/sizeMapper.ts";
+
+import { sleep } from "../../utils/sleep.ts";
+
+import { sanitizeErrorMessage, sanitizeUpstreamDetails } from "../../utils/error.ts";
+
+import { extractImageInputs, normalizeRequestedImageFormat, resolveImageSource, isHttpUrl, parseSizeToDimensions, normalizeProviderImagePayload, normalizePositiveNumber } from "./utils.ts";
+import { saveImageErrorResult, saveImageSuccessResult } from "./logging.ts";
+
+
+
+const BFL_MODEL_ENDPOINTS = {
+  "flux-2-max": "/v1/flux-2-max",
+  "flux-2-pro": "/v1/flux-2-pro",
+  "flux-2-flex": "/v1/flux-2-flex",
+  "flux-2-klein-9b": "/v1/flux-2-klein-9b",
+  "flux-2-klein-4b": "/v1/flux-2-klein-4b",
+  "flux-kontext-pro": "/v1/flux-kontext-pro",
+  "flux-kontext-max": "/v1/flux-kontext-max",
+  "flux-pro-1.1": "/v1/flux-pro-1.1",
+  "flux-pro-1.1-ultra": "/v1/flux-pro-1.1-ultra",
+  "flux-dev": "/v1/flux-dev",
+  "flux-pro": "/v1/flux-pro",
+};
+
+
+
+const BFL_EDIT_MODELS = new Set([
+  "flux-2-max",
+  "flux-2-pro",
+  "flux-2-flex",
+  "flux-kontext-pro",
+  "flux-kontext-max",
+]);
+
+
+
+const BFL_FAILURE_STATUSES = new Set(["Error", "Failed", "Content Moderated", "Request Moderated"]);
+
+
+
+export async function handleBlackForestLabsImageGeneration({
+  model,
+  provider,
+  providerConfig,
+  body,
+  credentials,
+  log,
+}) {
+  const startTime = Date.now();
+  const token = credentials?.apiKey || credentials?.accessToken;
+  const endpoint = BFL_MODEL_ENDPOINTS[model];
+
+  if (!endpoint) {
+    return {
+      success: false,
+      status: 400,
+      error: `Unsupported Black Forest Labs image model: ${model}`,
+    };
+  }
+
+  const { imageUrl, maskUrl } = extractImageInputs(body);
+  const upstreamBody: Record<string, unknown> = {
+    prompt: body.prompt,
+    output_format: normalizeRequestedImageFormat(body, "png"),
+  };
+
+  try {
+    if (BFL_EDIT_MODELS.has(model) && imageUrl) {
+      upstreamBody.input_image = (await resolveImageSource(imageUrl)).base64;
+    } else if (imageUrl && isHttpUrl(imageUrl)) {
+      upstreamBody.image_url = imageUrl;
+    }
+
+    if (maskUrl && (model === "flux-pro-1.0-fill" || model === "flux-kontext-pro")) {
+      upstreamBody.mask = (await resolveImageSource(maskUrl)).base64;
+    }
+
+    if (model === "flux-kontext-pro" || model === "flux-kontext-max") {
+      upstreamBody.aspect_ratio = body.aspect_ratio || mapImageSize(body.size);
+    } else if (typeof body.size === "string" && body.size.includes("x")) {
+      const { width, height } = parseSizeToDimensions(body.size, 1024);
+      upstreamBody.width = width;
+      upstreamBody.height = height;
+    }
+
+    if (body.seed !== undefined) upstreamBody.seed = body.seed;
+    if (body.n !== undefined && model.includes("ultra"))
+      upstreamBody.num_images = Number(body.n) || 1;
+    if (body.quality === "hd" && model.includes("ultra")) upstreamBody.raw = true;
+    if (body.left !== undefined) upstreamBody.left = body.left;
+    if (body.right !== undefined) upstreamBody.right = body.right;
+    if (body.top !== undefined) upstreamBody.top = body.top;
+    if (body.bottom !== undefined) upstreamBody.bottom = body.bottom;
+    if (body.steps !== undefined) upstreamBody.steps = body.steps;
+    if (body.guidance !== undefined) upstreamBody.guidance = body.guidance;
+    if (body.grow_mask !== undefined) upstreamBody.grow_mask = body.grow_mask;
+    if (body.safety_tolerance !== undefined) upstreamBody.safety_tolerance = body.safety_tolerance;
+
+    if (log) {
+      const promptPreview = String(body.prompt ?? "").slice(0, 60);
+      log.info("IMAGE", `${provider}/${model} (black-forest-labs) | prompt: "${promptPreview}..."`);
+    }
+
+    const response = await fetch(`${providerConfig.baseUrl.replace(/\/$/, "")}${endpoint}`, {
+      method: "POST",
+      headers: {
+        "Content-Type": "application/json",
+        Accept: "application/json",
+        "x-key": token,
+      },
+      body: JSON.stringify(upstreamBody),
+    });
+
+    if (!response.ok) {
+      const errorText = await response.text();
+      if (log)
+        log.error("IMAGE", `${provider} error ${response.status}: ${errorText.slice(0, 200)}`);
+      return saveImageErrorResult({
+        provider,
+        model,
+        status: response.status,
+        startTime,
+        error: errorText,
+        requestBody: upstreamBody,
+      });
+    }
+
+    const initialPayload = await response.json();
+    const finalPayload = initialPayload?.polling_url
+      ? await pollBlackForestLabsResult({
+          pollingUrl: initialPayload?.polling_url,
+          token,
+          body,
+          log,
+        })
+      : initialPayload;
+
+    const images = await normalizeProviderImagePayload(finalPayload, body, log);
+    return saveImageSuccessResult({
+      provider,
+      model,
+      startTime,
+      requestBody: upstreamBody,
+      responseBody: { images_count: images.length },
+      created: finalPayload.created,
+      images,
+    });
+  } catch (err) {
+    if (log) log.error("IMAGE", `${provider} fetch error: ${err.message}`);
+    return saveImageErrorResult({
+      provider,
+      model,
+      status: 502,
+      startTime,
+      error: `Image provider error: ${sanitizeErrorMessage((err as Error).message || err)}`,
+    });
+  }
+}
+
+
+
+async function pollBlackForestLabsResult({ pollingUrl, token, body, log }) {
+  const timeoutMs = normalizePositiveNumber(body.timeout_ms, 300000);
+  const pollIntervalMs = normalizePositiveNumber(body.poll_interval_ms, 1500);
+  const deadline = Date.now() + timeoutMs;
+
+  while (Date.now() < deadline) {
+    const response = await fetch(pollingUrl, {
+      method: "GET",
+      headers: {
+        "x-key": token,
+      },
+    });
+
+    if (!response.ok) {
+      const errorText = await response.text();
+      throw new Error(`BFL polling failed (${response.status}): ${errorText}`);
+    }
+
+    const payload = await response.json();
+    const status = payload?.status;
+
+    if (status === "Ready") {
+      return payload;
+    }
+
+    if (BFL_FAILURE_STATUSES.has(status)) {
+      throw new Error(`BFL image generation failed: ${status}`);
+    }
+
+    if (log) {
+      log.info("IMAGE", `black-forest-labs polling status: ${String(status || "Pending")}`);
+    }
+
+    await sleep(pollIntervalMs);
+  }
+
+  throw new Error(`BFL polling timed out after ${timeoutMs}ms`);
+}
+