| <svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" fill="none" version="1.1" width="128" height="128" viewBox="0 0 128 128"><g><g style="opacity:0;"><rect x="0" y="0" width="128" height="128" rx="0" fill="#FFFFFF" fill-opacity="1"/></g><g><path d="M100.74,12L93.2335,12C69.21260000000001,12,55.3672,27.3468,55.3672,50.8672L55.3672,54.8988C52.6011,54.1056,49.7377,53.7031,46.8601,53.7031C29.816499999999998,53.7031,16,67.5196,16,84.5632C16,101.6069,29.816499999999998,115.423,46.8601,115.423C63.9037,115.423,77.72030000000001,101.6069,77.72030000000001,84.5632C77.72030000000001,82.4902,77.51140000000001,80.4223,77.0967,78.3911L77.2197,78.3911L100.74,78.3911C106.9654,78.3681,112,73.3151,112,67.08959999999999C112,60.8642,106.9654,55.8111,100.74,55.7882L100.7362,55.7882L100.6985,55.7879L100.6606,55.7882L77.2197,55.7882L77.2195,49.8663C77.2195,40.8584,83.7252,34.352900000000005,93.2335,34.352900000000005L100.5653,34.352900000000005L100.5733,34.352900000000005L100.5812,34.352900000000005L100.74,34.352900000000005L100.74,34.352900000000005C106.8469,34.2605,111.7497,29.284,111.7497,23.1764C111.7497,17.06889,106.8469,12.0923454,100.74,12L100.74,12ZM56.0347,84.5632C56.0347,79.4962,51.9271,75.3885,46.8601,75.3885C41.793099999999995,75.3885,37.6854,79.4962,37.6854,84.5632C37.6854,89.6303,41.793099999999995,93.7378,46.8601,93.7378C51.9271,93.7378,56.0347,89.6303,56.0347,84.5632Z" fill-rule="evenodd" fill="#8358F6" fill-opacity="1"/></g></g></svg> | 
| import requests | |||||
| from core.tools.errors import ToolProviderCredentialValidationError | |||||
| from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController | |||||
| class SiliconflowProvider(BuiltinToolProviderController): | |||||
| def _validate_credentials(self, credentials: dict) -> None: | |||||
| url = "https://api.siliconflow.cn/v1/models" | |||||
| headers = { | |||||
| "accept": "application/json", | |||||
| "authorization": f"Bearer {credentials.get('siliconFlow_api_key')}", | |||||
| } | |||||
| response = requests.get(url, headers=headers) | |||||
| if response.status_code != 200: | |||||
| raise ToolProviderCredentialValidationError( | |||||
| "SiliconFlow API key is invalid" | |||||
| ) | 
| identity: | |||||
| author: hjlarry | |||||
| name: siliconflow | |||||
| label: | |||||
| en_US: SiliconFlow | |||||
| zh_CN: 硅基流动 | |||||
| description: | |||||
| en_US: The image generation API provided by SiliconFlow includes Flux and Stable Diffusion models. | |||||
| zh_CN: 硅基流动提供的图片生成 API,包含 Flux 和 Stable Diffusion 模型。 | |||||
| icon: icon.svg | |||||
| tags: | |||||
| - image | |||||
| credentials_for_provider: | |||||
| siliconFlow_api_key: | |||||
| type: secret-input | |||||
| required: true | |||||
| label: | |||||
| en_US: SiliconFlow API Key | |||||
| placeholder: | |||||
| en_US: Please input your SiliconFlow API key | |||||
| url: https://cloud.siliconflow.cn/account/ak | 
| from typing import Any, Union | |||||
| import requests | |||||
| from core.tools.entities.tool_entities import ToolInvokeMessage | |||||
| from core.tools.tool.builtin_tool import BuiltinTool | |||||
| FLUX_URL = ( | |||||
| "https://api.siliconflow.cn/v1/black-forest-labs/FLUX.1-schnell/text-to-image" | |||||
| ) | |||||
| class FluxTool(BuiltinTool): | |||||
| def _invoke( | |||||
| self, user_id: str, tool_parameters: dict[str, Any] | |||||
| ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: | |||||
| headers = { | |||||
| "accept": "application/json", | |||||
| "content-type": "application/json", | |||||
| "authorization": f"Bearer {self.runtime.credentials['siliconFlow_api_key']}", | |||||
| } | |||||
| payload = { | |||||
| "prompt": tool_parameters.get("prompt"), | |||||
| "image_size": tool_parameters.get("image_size", "1024x1024"), | |||||
| "seed": tool_parameters.get("seed"), | |||||
| "num_inference_steps": tool_parameters.get("num_inference_steps", 20), | |||||
| } | |||||
| response = requests.post(FLUX_URL, json=payload, headers=headers) | |||||
| if response.status_code != 200: | |||||
| return self.create_text_message(f"Got Error Response:{response.text}") | |||||
| res = response.json() | |||||
| result = [self.create_json_message(res)] | |||||
| for image in res.get("images", []): | |||||
| result.append( | |||||
| self.create_image_message( | |||||
| image=image.get("url"), save_as=self.VARIABLE_KEY.IMAGE.value | |||||
| ) | |||||
| ) | |||||
| return result | 
| identity: | |||||
| name: flux | |||||
| author: hjlarry | |||||
| label: | |||||
| en_US: Flux | |||||
| icon: icon.svg | |||||
| description: | |||||
| human: | |||||
| en_US: Generate image via SiliconFlow's flux schnell. | |||||
| llm: This tool is used to generate image from prompt via SiliconFlow's flux schnell model. | |||||
| parameters: | |||||
| - name: prompt | |||||
| type: string | |||||
| required: true | |||||
| label: | |||||
| en_US: prompt | |||||
| zh_Hans: 提示词 | |||||
| human_description: | |||||
| en_US: The text prompt used to generate the image. | |||||
| zh_Hans: 用于生成图片的文字提示词 | |||||
| llm_description: this prompt text will be used to generate image. | |||||
| form: llm | |||||
| - name: image_size | |||||
| type: select | |||||
| required: true | |||||
| options: | |||||
| - value: 1024x1024 | |||||
| label: | |||||
| en_US: 1024x1024 | |||||
| - value: 768x1024 | |||||
| label: | |||||
| en_US: 768x1024 | |||||
| - value: 576x1024 | |||||
| label: | |||||
| en_US: 576x1024 | |||||
| - value: 512x1024 | |||||
| label: | |||||
| en_US: 512x1024 | |||||
| - value: 1024x576 | |||||
| label: | |||||
| en_US: 1024x576 | |||||
| - value: 768x512 | |||||
| label: | |||||
| en_US: 768x512 | |||||
| default: 1024x1024 | |||||
| label: | |||||
| en_US: Choose Image Size | |||||
| zh_Hans: 选择生成的图片大小 | |||||
| form: form | |||||
| - name: num_inference_steps | |||||
| type: number | |||||
| required: true | |||||
| default: 20 | |||||
| min: 1 | |||||
| max: 100 | |||||
| label: | |||||
| en_US: Num Inference Steps | |||||
| zh_Hans: 生成图片的步数 | |||||
| form: form | |||||
| human_description: | |||||
| en_US: The number of inference steps to perform. More steps produce higher quality but take longer. | |||||
| zh_Hans: 执行的推理步骤数量。更多的步骤可以产生更高质量的结果,但需要更长的时间。 | |||||
| - name: seed | |||||
| type: number | |||||
| min: 0 | |||||
| max: 9999999999 | |||||
| label: | |||||
| en_US: Seed | |||||
| zh_Hans: 种子 | |||||
| human_description: | |||||
| en_US: The same seed and prompt can produce similar images. | |||||
| zh_Hans: 相同的种子和提示可以产生相似的图像。 | |||||
| form: form | 
| from typing import Any, Union | |||||
| import requests | |||||
| from core.tools.entities.tool_entities import ToolInvokeMessage | |||||
| from core.tools.tool.builtin_tool import BuiltinTool | |||||
| SDURL = { | |||||
| "sd_3": "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-3-medium/text-to-image", | |||||
| "sd_xl": "https://api.siliconflow.cn/v1/stabilityai/stable-diffusion-xl-base-1.0/text-to-image", | |||||
| } | |||||
| class StableDiffusionTool(BuiltinTool): | |||||
| def _invoke( | |||||
| self, user_id: str, tool_parameters: dict[str, Any] | |||||
| ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]: | |||||
| headers = { | |||||
| "accept": "application/json", | |||||
| "content-type": "application/json", | |||||
| "authorization": f"Bearer {self.runtime.credentials['siliconFlow_api_key']}", | |||||
| } | |||||
| model = tool_parameters.get("model", "sd_3") | |||||
| url = SDURL.get(model) | |||||
| payload = { | |||||
| "prompt": tool_parameters.get("prompt"), | |||||
| "negative_prompt": tool_parameters.get("negative_prompt", ""), | |||||
| "image_size": tool_parameters.get("image_size", "1024x1024"), | |||||
| "batch_size": tool_parameters.get("batch_size", 1), | |||||
| "seed": tool_parameters.get("seed"), | |||||
| "guidance_scale": tool_parameters.get("guidance_scale", 7.5), | |||||
| "num_inference_steps": tool_parameters.get("num_inference_steps", 20), | |||||
| } | |||||
| response = requests.post(url, json=payload, headers=headers) | |||||
| if response.status_code != 200: | |||||
| return self.create_text_message(f"Got Error Response:{response.text}") | |||||
| res = response.json() | |||||
| result = [self.create_json_message(res)] | |||||
| for image in res.get("images", []): | |||||
| result.append( | |||||
| self.create_image_message( | |||||
| image=image.get("url"), save_as=self.VARIABLE_KEY.IMAGE.value | |||||
| ) | |||||
| ) | |||||
| return result | 
| identity: | |||||
| name: stable_diffusion | |||||
| author: hjlarry | |||||
| label: | |||||
| en_US: Stable Diffusion | |||||
| icon: icon.svg | |||||
| description: | |||||
| human: | |||||
| en_US: Generate image via SiliconFlow's stable diffusion model. | |||||
| llm: This tool is used to generate image from prompt via SiliconFlow's stable diffusion model. | |||||
| parameters: | |||||
| - name: prompt | |||||
| type: string | |||||
| required: true | |||||
| label: | |||||
| en_US: prompt | |||||
| zh_Hans: 提示词 | |||||
| human_description: | |||||
| en_US: The text prompt used to generate the image. | |||||
| zh_Hans: 用于生成图片的文字提示词 | |||||
| llm_description: this prompt text will be used to generate image. | |||||
| form: llm | |||||
| - name: negative_prompt | |||||
| type: string | |||||
| label: | |||||
| en_US: negative prompt | |||||
| zh_Hans: 负面提示词 | |||||
| human_description: | |||||
| en_US: Describe what you don't want included in the image. | |||||
| zh_Hans: 描述您不希望包含在图片中的内容。 | |||||
| llm_description: Describe what you don't want included in the image. | |||||
| form: llm | |||||
| - name: model | |||||
| type: select | |||||
| required: true | |||||
| options: | |||||
| - value: sd_3 | |||||
| label: | |||||
| en_US: Stable Diffusion 3 | |||||
| - value: sd_xl | |||||
| label: | |||||
| en_US: Stable Diffusion XL | |||||
| default: sd_3 | |||||
| label: | |||||
| en_US: Choose Image Model | |||||
| zh_Hans: 选择生成图片的模型 | |||||
| form: form | |||||
| - name: image_size | |||||
| type: select | |||||
| required: true | |||||
| options: | |||||
| - value: 1024x1024 | |||||
| label: | |||||
| en_US: 1024x1024 | |||||
| - value: 1024x2048 | |||||
| label: | |||||
| en_US: 1024x2048 | |||||
| - value: 1152x2048 | |||||
| label: | |||||
| en_US: 1152x2048 | |||||
| - value: 1536x1024 | |||||
| label: | |||||
| en_US: 1536x1024 | |||||
| - value: 1536x2048 | |||||
| label: | |||||
| en_US: 1536x2048 | |||||
| - value: 2048x1152 | |||||
| label: | |||||
| en_US: 2048x1152 | |||||
| default: 1024x1024 | |||||
| label: | |||||
| en_US: Choose Image Size | |||||
| zh_Hans: 选择生成图片的大小 | |||||
| form: form | |||||
| - name: batch_size | |||||
| type: number | |||||
| required: true | |||||
| default: 1 | |||||
| min: 1 | |||||
| max: 4 | |||||
| label: | |||||
| en_US: Number Images | |||||
| zh_Hans: 生成图片的数量 | |||||
| form: form | |||||
| - name: guidance_scale | |||||
| type: number | |||||
| required: true | |||||
| default: 7 | |||||
| min: 0 | |||||
| max: 100 | |||||
| label: | |||||
| en_US: Guidance Scale | |||||
| zh_Hans: 与提示词紧密性 | |||||
| human_description: | |||||
| en_US: Classifier Free Guidance. How close you want the model to stick to your prompt when looking for a related image to show you. | |||||
| zh_Hans: 无分类器引导。您希望模型在寻找相关图片向您展示时,与您的提示保持多紧密的关联度。 | |||||
| form: form | |||||
| - name: num_inference_steps | |||||
| type: number | |||||
| required: true | |||||
| default: 20 | |||||
| min: 1 | |||||
| max: 100 | |||||
| label: | |||||
| en_US: Num Inference Steps | |||||
| zh_Hans: 生成图片的步数 | |||||
| human_description: | |||||
| en_US: The number of inference steps to perform. More steps produce higher quality but take longer. | |||||
| zh_Hans: 执行的推理步骤数量。更多的步骤可以产生更高质量的结果,但需要更长的时间。 | |||||
| form: form | |||||
| - name: seed | |||||
| type: number | |||||
| min: 0 | |||||
| max: 9999999999 | |||||
| label: | |||||
| en_US: Seed | |||||
| zh_Hans: 种子 | |||||
| human_description: | |||||
| en_US: The same seed and prompt can produce similar images. | |||||
| zh_Hans: 相同的种子和提示可以产生相似的图像。 | |||||
| form: form |