V 2.0.0 - Universal api #15 - Imagen
This commit is contained in:
DESKTOP-TVBJISQ\Primere
+37
-27
@@ -134,8 +134,8 @@ class PrimereApiProcessor:
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"seed": ("INT", {"default": 1, "min": 0, "max": (2 ** 32) - 1, "forceInput": True})
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}
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for key, values in cls._parameter_options().items():
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required_inputs[key] = (values,)
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# for key, values in cls._parameter_options().items():
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# required_inputs[key] = (values,)
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return {"required": required_inputs, "optional": optional_inputs}
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@@ -335,34 +335,44 @@ class PrimereApiProcessor:
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raise RuntimeError(f"API call failed for {api_provider}/{selected_service}: {api_error}")
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if api_error is None:
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if api_result.candidates[0].content is not None and api_result.candidates[0].content.parts is not None:
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image_parts = [
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part.inline_data.data
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for part in api_result.candidates[0].content.parts
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if part.inline_data
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]
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if image_parts:
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result_image = Image.open(BytesIO(image_parts[0]))
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if api_provider == "Gemini" and (selected_service or api_service) == "Nanobanana":
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if api_result.candidates[0].content is not None and api_result.candidates[0].content.parts is not None:
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image_parts = [
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part.inline_data.data
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for part in api_result.candidates[0].content.parts
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if part.inline_data
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]
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if image_parts:
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result_image = Image.open(BytesIO(image_parts[0]))
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if result_image is not None:
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result_image = result_image.convert("RGB")
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result_image = np.array(result_image).astype(np.float32) / 255.0
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result_image = torch.from_numpy(result_image)[None,]
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final_batch_img.append(result_image)
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if type(final_batch_img).__name__ == "list" and len(final_batch_img) > 1:
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image_list = final_batch_img
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single_image_start = final_batch_img[0]
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batch_count = 0
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s = None
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for single_image in final_batch_img:
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if (batch_count + 1) < len(final_batch_img):
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current_single_image = final_batch_img[batch_count + 1]
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if single_image_start.shape[1:] != current_single_image.shape[1:]:
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current_single_image = comfy.utils.common_upscale(current_single_image.movedim(-1, 1), single_image_start.shape[2], single_image_start.shape[1], "bilinear", "center").movedim(1, -1)
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batch_count = batch_count + 1
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if s is not None:
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single_image = s
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s = torch.cat((current_single_image, single_image), dim=0)
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result_image = s
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if api_provider == "Gemini" and (selected_service or api_service) == "Imagen":
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if api_result.generated_images[0].image is not None and api_result.generated_images[0].image.image_bytes is not None:
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generated_image = api_result.generated_images[0].image.image_bytes
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result_image = Image.open(BytesIO(generated_image))
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if result_image is not None:
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result_image = result_image.convert("RGB")
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result_image = np.array(result_image).astype(np.float32) / 255.0
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result_image = torch.from_numpy(result_image)[None,]
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final_batch_img.append(result_image)
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if type(final_batch_img).__name__ == "list" and len(final_batch_img) > 1:
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image_list = final_batch_img
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single_image_start = final_batch_img[0]
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batch_count = 0
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s = None
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for single_image in final_batch_img:
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if (batch_count + 1) < len(final_batch_img):
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current_single_image = final_batch_img[batch_count + 1]
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if single_image_start.shape[1:] != current_single_image.shape[1:]:
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current_single_image = comfy.utils.common_upscale(current_single_image.movedim(-1, 1), single_image_start.shape[2], single_image_start.shape[1], "bilinear", "center").movedim(1, -1)
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batch_count = batch_count + 1
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if s is not None:
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single_image = s
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s = torch.cat((current_single_image, single_image), dim=0)
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result_image = s
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return (client, api_provider, schema, rendered_payload, api_schemas, api_result, result_image)
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@@ -98,6 +98,41 @@
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}
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}
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}
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},
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"Imagen": {
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"provider": "Gemini",
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"service": "Imagen",
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"possible_parameters": {
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"resolution": [
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"1K",
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"2K"
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],
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"model": [
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"imagen-4.0-generate-001",
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"imagen-4.0-ultra-generate-001",
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"imagen-4.0-fast-generate-001"
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]
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},
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"request": {
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"method": "SDK",
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"endpoint": "client.models.generate_images",
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"sdk_call": {
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"args": [],
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"kwargs": {
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"model": "{{model}}",
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"prompt": "{{prompt}}",
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"config": {
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"$call": "types.GenerateImagesConfig",
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"$args": [],
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"$kwargs": {
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"number_of_images": "{{config_number_of_images}}",
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"aspect_ratio": "{{config_aspect_ratio}}",
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"image_size": "{{config_image_size}}"
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}
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}
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}
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}
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}
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}
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}
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}
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@@ -1,4 +1,6 @@
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"""Convert `snippet.py` into grouped provider->service API schema JSON."""
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# python api_snippet_to_json.py --provider Gemini --service Imagen
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from __future__ import annotations
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@@ -0,0 +1,44 @@
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{
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"Gemini": {
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"Imagen": {
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"provider": "Gemini",
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"service": "Imagen",
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"possible_parameters": {
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"resolution": [
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"1K",
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"2K",
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"4K"
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],
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"config_number_of_images": [
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"fake_config_number_of_images_value_1",
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"fake_config_number_of_images_value_2"
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],
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"model": [
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"gemini-3-pro-image-preview",
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"gemini-2.5-flash-image"
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]
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},
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"request": {
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"method": "SDK",
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"endpoint": "client.models.generate_images",
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"sdk_call": {
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"args": [],
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"kwargs": {
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"model": "{{model}}",
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"prompt": "{{prompt}}",
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"config": {
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"$call": "types.GenerateImagesConfig",
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"$args": [],
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"$kwargs": {
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"number_of_images": "{{config_number_of_images}}",
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"aspect_ratio": "{{config_aspect_ratio}}",
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"image_size": "{{config_image_size}}",
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"person_generation": "{{config_person_generation}}"
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}
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}
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}
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}
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}
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}
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}
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}
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@@ -0,0 +1,50 @@
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{
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"Gemini": {
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"Nanobanana": {
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"provider": "Gemini",
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"service": "Nanobanana",
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"possible_parameters": {
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"resolution": [
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"1K",
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"2K",
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"4K"
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],
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"model": [
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"gemini-3-pro-image-preview",
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"gemini-2.5-flash-image"
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]
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},
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"request": {
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"method": "SDK",
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"endpoint": "client.models.generate_content",
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"sdk_call": {
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"args": [],
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"kwargs": {
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"model": "{{model}}",
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"contents": [
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"{{prompt}}",
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"{{reference_images}}"
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],
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"config": {
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"$call": "types.GenerateContentConfig",
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"$args": [],
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"$kwargs": {
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"response_modalities": [
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"{{config_response_modalities_0}}"
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],
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"image_config": {
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"$call": "types.ImageConfig",
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"$args": [],
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"$kwargs": {
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"aspect_ratio": "{{config_image_config_aspect_ratio}}",
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"image_size": "{{config_image_config_image_size}}"
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}
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}
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}
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}
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}
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}
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}
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}
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}
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}
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@@ -0,0 +1,144 @@
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{
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"Gemini": {
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"Nanobanana": {
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"provider": "Gemini",
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"service": "Nanobanana",
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"possible_parameters": {
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"resolution": [
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"1K",
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"2K",
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"4K"
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],
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"model": [
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"gemini-3-pro-image-preview",
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"gemini-2.5-flash-image"
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]
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},
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"request": {
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"method": "SDK",
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"endpoint": "client.models.generate_content",
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"sdk_call": {
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"args": [],
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"kwargs": {
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"model": "{{model}}",
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"contents": [
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"{{prompt}}",
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"{{reference_images}}"
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],
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"config": {
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"$call": "types.GenerateContentConfig",
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"$args": [],
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"$kwargs": {
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"response_modalities": [
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"{{config_response_modalities_0}}"
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],
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"image_config": {
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"$call": "types.ImageConfig",
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"$args": [],
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"$kwargs": {
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"aspect_ratio": "{{config_image_config_aspect_ratio}}",
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"image_size": "{{config_image_config_image_size}}"
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}
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}
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}
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}
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}
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}
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}
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},
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"VEO": {
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"provider": "Gemini",
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"service": "VEO",
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"possible_parameters": {
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"durationSeconds": [
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"4",
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"6",
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"8"
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],
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"personGeneration": [
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"allow_all",
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"allow_adult",
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"dont_allow"
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],
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"resolution": [
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"720p",
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"1080p",
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"4K"
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],
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"model": [
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"veo-3.0-generate",
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"veo-3.0-fast-generate",
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"veo-3.1-generate-preview",
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"veo-3.1-generate",
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"veo-3.1-fast-generate-preview",
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"veo-3.1-fast-generate"
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]
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},
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"request": {
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"method": "SDK",
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"endpoint": "client.models.generate_videos",
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"sdk_call": {
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"args": [],
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"kwargs": {
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"model": "{{model}}",
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"prompt": "{{prompt}}",
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"image": "{{first_image}}",
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"config": {
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"$call": "types.GenerateVideosConfig",
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"$args": [],
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"$kwargs": {
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"aspectRatio": "{{config_aspectRatio}}",
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"resolution": "{{config_resolution}}",
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"durationSeconds": "{{config_durationSeconds}}",
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"personGeneration": "{{config_personGeneration}}",
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"reference_images": "{{reference_images}}",
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"last_frame": "{{last_image}}"
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}
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}
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}
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}
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}
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},
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"Imagen": {
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"provider": "Gemini",
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"service": "Imagen",
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"possible_parameters": {
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"resolution": [
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"1K",
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"2K"
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],
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"model": [
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"imagen-4.0-generate-001",
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"imagen-4.0-ultra-generate-001",
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"imagen-4.0-fast-generate-001"
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],
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"person_generation": [
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"allow_all",
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"allow_adult",
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"dont_allow"
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]
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},
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"request": {
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"method": "SDK",
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"endpoint": "client.models.generate_images",
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"sdk_call": {
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"args": [],
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"kwargs": {
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"model": "{{model}}",
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"prompt": "{{prompt}}",
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"config": {
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"$call": "types.GenerateImagesConfig",
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"$args": [],
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"$kwargs": {
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"number_of_images": "{{config_number_of_images}}",
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"aspect_ratio": "{{config_aspect_ratio}}",
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"image_size": "{{config_image_size}}",
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"person_generation": "{{config_person_generation}}"
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}
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}
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}
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}
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}
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}
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}
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}
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@@ -0,0 +1,10 @@
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response = client.models.generate_images(
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model='imagen-4.0-generate-001',
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prompt=prompt,
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config=types.GenerateImagesConfig(
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number_of_images=4,
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aspect_ratio="16:9",
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image_size="1K",
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person_generation="allow_all",
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)
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)
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@@ -1,13 +1,10 @@
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response = client.models.generate_videos(
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model="veo-3.1-generate-preview",
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response = client.models.generate_images(
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model='imagen-4.0-generate-001',
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prompt=prompt,
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image=first_image,
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config=types.GenerateVideosConfig(
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aspectRatio="9:16",
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resolution="720p",
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durationSeconds="8s",
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personGeneration="allow_all",
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reference_images=reference_images,
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last_frame=last_image
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),
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config=types.GenerateImagesConfig(
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number_of_images=4,
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aspect_ratio="16:9",
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image_size="1K",
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person_generation="allow_all",
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)
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)
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