update

banana_pro_image.py

@@ -10,69 +10,58 @@ from image_api_utils import (
     prepare_reference_images,
 )
 
-MODEL_NAME = "gemini-3-pro-image-preview"
+MODEL_NAME = "nano-banana-pro"
 
 
-def generate_image(images=None, prompt="", aspect_ratio="1:1", image_size="2K", notify_url=None):
+def generate_image(images=None, prompt="", aspect_ratio="1:1", image_size="2K"):
     """
-    Triggers the image generation task using the Nano Banana Pro (gemini-3-pro-image-preview) model.
-    
+    Triggers an async image generation task via the Grsai nano-banana API.
+
     :param images: Up to 14 local image paths, HTTP(S) URLs, or base64 data URLs.
     :param prompt: Text prompt describing the desired image content.
     :param aspect_ratio: Image aspect ratio. Allowed: "1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"
     :param image_size: Image resolution/quality. Allowed: "1K", "2K", "4K"
-    :param notify_url: Optional webhook URL for async callback.
-    :return: task_id string/int
+    :return: task_id string
     """
-    url = f"{IMAGE_API_BASE_URL}/v1/media/generate"
-    
-    params = {
-        "aspectRatio": aspect_ratio,
-        "imageSize": image_size
-    }
-    
+    url = f"{IMAGE_API_BASE_URL}/v1/api/generate"
+
     reference_images = prepare_reference_images(images)
-    if reference_images:
-        params["images"] = reference_images
 
     payload = {
         "model": MODEL_NAME,
-        "params": params,
-        "prompt": prompt
+        "prompt": prompt,
+        "aspectRatio": aspect_ratio,
+        "imageSize": image_size,
+        "replyType": "async",
     }
-    
-    if notify_url:
-        payload["notify_url"] = notify_url
+
+    if reference_images:
+        payload["images"] = reference_images
 
     payload_body = encode_json_request(payload)
-    
+
     headers = get_auth_headers(api_key=API_KEY)
-    print(f"[*] Sending Banana Pro ({MODEL_NAME}) generation request to: {url}")
+    print(f"[*] Sending Banana Pro ({MODEL_NAME}) async generation request to: {url}")
     response = requests.post(url, data=payload_body, headers=headers)
     response.raise_for_status()
     res_json = response.json()
-    
-    # Try parsing task_id from root or nested "data" dictionary
-    task_id = res_json.get("task_id")
-    if not task_id and "data" in res_json and isinstance(res_json["data"], dict):
-        task_id = res_json["data"].get("task_id")
-        
+
+    task_id = res_json.get("id")
     if not task_id:
-        raise ValueError(f"Failed to obtain task_id from response: {res_json}")
+        raise ValueError(f"Failed to obtain task id from response: {res_json}")
     print(f"[+] Task created successfully. Task ID: {task_id}")
     return task_id
 
 
-def generate_txt2img(prompt, output_path=None, aspect_ratio="1:1", image_size="2K", notify_url=None):
+def generate_txt2img(prompt, output_path=None, aspect_ratio="1:1", image_size="2K"):
     """
-    Text-to-image API for Nano Banana Pro (gemini-3-pro-image-preview).
+    Text-to-image API for Nano Banana Pro (nano-banana-pro).
     """
     task_id = generate_image(
         images=None,
         prompt=prompt,
         aspect_ratio=aspect_ratio,
         image_size=image_size,
-        notify_url=notify_url,
     )
     return poll_and_download_result(
         task_id=task_id,
@@ -81,7 +70,7 @@ def generate_txt2img(prompt, output_path=None, aspect_ratio="1:1", image_size="2
     )
 
 
-def generate_img2img(local_image_paths, prompt, output_path=None, aspect_ratio="1:1", image_size="2K", notify_url=None):
+def generate_img2img(local_image_paths, prompt, output_path=None, aspect_ratio="1:1", image_size="2K"):
     """
     Image-to-image API accepting local paths, HTTP(S) URLs, or base64 data URLs.
     """
@@ -90,7 +79,6 @@ def generate_img2img(local_image_paths, prompt, output_path=None, aspect_ratio="
         prompt=prompt,
         aspect_ratio=aspect_ratio,
         image_size=image_size,
-        notify_url=notify_url,
     )
     return poll_and_download_result(
         task_id=task_id,
@@ -100,7 +88,7 @@ def generate_img2img(local_image_paths, prompt, output_path=None, aspect_ratio="
 
 
 if __name__ == '__main__':
-    parser = argparse.ArgumentParser(description="Generate image using Gemini 3 Pro (Nano Banana Pro) model.")
+    parser = argparse.ArgumentParser(description="Generate image using Nano Banana Pro model via Grsai API.")
     parser.add_argument("prompt", help="Text prompt for image generation.")
     parser.add_argument(
         "-i",

gpt_image.py

@@ -1,5 +1,3 @@
-import os
-
 import requests
 from image_api_utils import (
     IMAGE_API_BASE_URL,
@@ -10,61 +8,53 @@ from image_api_utils import (
     prepare_reference_images,
 )
 
-GPT_IMAGE_API_BASE_URL = (
-    os.getenv("IMAGE_API_BASE_URL")
-    or os.getenv("GPT_IMAGE_API_BASE_URL")
-    or IMAGE_API_BASE_URL
-)
 MODEL_NAME = "gpt-image-2"
 
 
-def generate_image(images, prompt):
+def generate_image(images, prompt, aspect_ratio="1:1"):
     """
-    Trigger a gpt-image-2 task using local paths, URLs, or base64 data URLs.
+    Trigger an async gpt-image-2 task via the Grsai API.
+
+    :param images: Up to 14 local image paths, HTTP(S) URLs, or base64 data URLs.
+    :param prompt: Text prompt describing the desired image content.
+    :param aspect_ratio: Image aspect ratio (e.g. "1:1", "16:9") or pixel
+                         dimensions (e.g. "1024x1024").
+    :return: task_id string
     """
-    url = f"{GPT_IMAGE_API_BASE_URL}/v1/media/generate"
+    url = f"{IMAGE_API_BASE_URL}/v1/api/generate"
     reference_images = prepare_reference_images(images)
+
     payload = {
         "model": MODEL_NAME,
-        "params": {
-            "aspect_ratio": "1:1",
-            "images": reference_images,
-            "n": 1,
-            "quality": "high",
-            "resolution": "1K",
-            "response_format": "url",
-            "size": "1024x1024",
-        },
         "prompt": prompt,
+        "aspectRatio": aspect_ratio,
+        "replyType": "async",
     }
 
+    if reference_images:
+        payload["images"] = reference_images
+
     payload_body = encode_json_request(payload)
     headers = get_auth_headers(api_key=API_KEY)
-    print(f"[*] Sending image generation request to: {url}")
+    print(f"[*] Sending gpt-image-2 async generation request to: {url}")
     response = requests.post(url, data=payload_body, headers=headers)
     response.raise_for_status()
     res_json = response.json()
 
-    # Try parsing task_id from root or nested "data" dictionary
-    task_id = res_json.get("task_id")
-    if not task_id and "data" in res_json and isinstance(res_json["data"], dict):
-        task_id = res_json["data"].get("task_id")
-
+    task_id = res_json.get("id")
     if not task_id:
-        raise ValueError(f"Failed to obtain task_id from response: {res_json}")
+        raise ValueError(f"Failed to obtain task id from response: {res_json}")
     print(f"[+] Task created successfully. Task ID: {task_id}")
     return task_id
 
 
-def generate_img2img(local_image_paths, prompt, output_path=None):
+def generate_img2img(local_image_paths, prompt, output_path=None, aspect_ratio="1:1"):
     """
     Generate an image using up to 14 local paths, URLs, or base64 data URLs.
     """
-    task_id = generate_image(local_image_paths, prompt)
+    task_id = generate_image(local_image_paths, prompt, aspect_ratio=aspect_ratio)
     return poll_and_download_result(
         task_id=task_id,
         output_path=output_path,
-        default_prefix="result",
-        api_base_url=GPT_IMAGE_API_BASE_URL,
-        api_key=API_KEY,
+        default_prefix="gpt_image_result",
     )

image_api_utils.py

@@ -139,50 +139,49 @@ def encode_json_request(payload):
 
 def poll_task_status(task_id, api_base_url=None, api_key=None, timeout_seconds=320, poll_interval=10):
     """
-    Polls the task status with a timeout.
+    Polls the async task result from the Grsai nano-banana API.
+
+    Queries GET {base_url}/v1/api/result?id={task_id} until the task reaches
+    a terminal state (succeeded / failed / violation).
     """
     base_url = api_base_url or IMAGE_API_BASE_URL
-    status_url = f"{base_url}/v1/media/status"
+    status_url = f"{base_url}/v1/api/result"
     start_time = time.time()
     print(f"[*] Polling task status (timeout={timeout_seconds}s, interval={poll_interval}s)...")
-    
+
     headers = get_auth_headers(api_key=api_key, content_type=None)
-    
+
     while True:
         elapsed = time.time() - start_time
         if elapsed > timeout_seconds:
             raise TimeoutError(f"Task {task_id} timed out after {timeout_seconds} seconds.")
-            
+
         try:
-            response = requests.get(status_url, params={"task_id": task_id}, headers=headers)
+            response = requests.get(status_url, params={"id": task_id}, headers=headers)
             response.raise_for_status()
-            res_json = response.json()
-            
-            # Support both flat and nested responses for task status
-            data = res_json
-            if "data" in res_json and isinstance(res_json["data"], dict):
-                if any(k in res_json["data"] for k in ["state", "is_final", "result_url"]):
-                    data = res_json["data"]
-            
-            state = data.get("state")
-            is_final = data.get("is_final", False)
-            progress = data.get("progress", "0%")
-            status_text = data.get("status", "")
-            print(f"[*] [Elapsed: {int(elapsed)}s] State: {state} ({status_text}), Progress: {progress}")
-            
-            if is_final:
-                if state == "success":
-                    result_url = data.get("result_url")
-                    if not result_url:
-                        raise ValueError("Task finished with success state, but result_url is empty.")
-                    return result_url
-                else:
-                    error_msg = data.get("error", "Unknown error")
-                    raise RuntimeError(f"Task failed with state '{state}': {error_msg}")
-                    
+            data = response.json()
+
+            status = data.get("status")
+            progress = data.get("progress", 0)
+            task_id_resp = data.get("id", task_id)
+            print(f"[*] [Elapsed: {int(elapsed)}s] Task: {task_id_resp}, Status: {status}, Progress: {progress}%")
+
+            if status == "succeeded":
+                results = data.get("results", [])
+                if not results or not results[0].get("url"):
+                    raise ValueError("Task succeeded but no result URL found in response.")
+                return results[0]["url"]
+
+            if status in ("failed", "violation"):
+                error_msg = data.get("error", "Unknown error")
+                raise RuntimeError(f"Task {status}: {error_msg}")
+
+            # status == "running" → keep polling
+        except (requests.RequestException, ValueError, RuntimeError, TimeoutError):
+            raise
         except Exception as e:
             print(f"[!] Error querying task status: {e}")
-            
+
         time.sleep(poll_interval)