langflow中添加Siliconflow组件

组件代码：

import requests from pydantic.v1 import SecretStr from typing_extensions import override from langflow.base.models.model import LCModelComponent from langflow.field_typing import LanguageModel from langflow.field_typing.range_spec import RangeSpec from langflow.inputs import BoolInput, DictInput, DropdownInput, IntInput, SecretStrInput, SliderInput, StrInput # 定义 SiliconFlow 提供的模型列表 SILICONFLOW_MODELS = [ "Pro/deepseek-ai/DeepSeek-R1", "Pro/deepseek-ai/DeepSeek-V3", "deepseek-ai/DeepSeek-R1", "deepseek-ai/DeepSeek-V3", "deepseek-ai/DeepSeek-R1-Distill-Llama-70B", "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B", "deepseek-ai/DeepSeek-R1-Distill-Qwen-14B", "deepseek-ai/DeepSeek-R1-Distill-Llama-8B", "deepseek-ai/DeepSeek-R1-Distill-Qwen-7B", "deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B", "SeedLLM/Seed-Rice-7B", "Qwen/QVQ-72B-Preview", "deepseek-ai/DeepSeek-V2.5", "meta-llama/Llama-3.3-70B-Instruct", "Qwen/QwQ-32B-Preview", "Qwen/Qwen2.5-Coder-32B-Instruct", "Qwen/Qwen2-VL-72B-Instruct", "OpenGVLab/InternVL2-26B", "Qwen/Qwen2.5-72B-Instruct-128K", "deepseek-ai/deepseek-vl2", "Qwen/Qwen2.5-72B-Instruct", "Qwen/Qwen2.5-32B-Instruct", "Qwen/Qwen2.5-14B-Instruct", "Qwen/Qwen2.5-7B-Instruct", "Qwen/Qwen2.5-Coder-7B-Instruct", "Qwen/Qwen2-VL-7B-Instruct", "OpenGVLab/InternVL2-8B", "Qwen/Qwen2-7B-Instruct", "Qwen/Qwen2-1.5B-Instruct", "THUDM/glm-4-9b-chat", "THUDM/chatglm3-6b", "01-ai/Yi-1.5-9B-Chat-16K", "01-ai/Yi-1.5-6B-Chat", "01-ai/Yi-1.5-34B-Chat-16K", "google/gemma-2-27b-it", "google/gemma-2-9b-it", "AIDC-AI/Marco-o1", "LoRA/meta-llama/Meta-Llama-3.1-8B-Instruct", "LoRA/Qwen/Qwen2.5-32B-Instruct", "LoRA/Qwen/Qwen2.5-14B-Instruct", "Vendor-A/Qwen/Qwen2.5-72B-Instruct", "Pro/deepseek-ai/DeepSeek-R1-Distill-Llama-8B", "Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-7B", "Pro/deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B", "Pro/Qwen/Qwen2.5-Coder-7B-Instruct", "Pro/Qwen/Qwen2-VL-7B-Instruct", "Pro/OpenGVLab/InternVL2-8B", "Pro/Qwen/Qwen2.5-7B-Instruct", "Pro/meta-llama/Meta-Llama-3.1-8B-Instruct", "LoRA/Qwen/Qwen2.5-72B-Instruct", "Pro/Qwen/Qwen2-7B-Instruct", "Pro/Qwen/Qwen2-1.5B-Instruct", "LoRA/Qwen/Qwen2.5-7B-Instruct", "Pro/THUDM/glm-4-9b-chat", "Pro/google/gemma-2-9b-it" ] class SiliconFlowModelComponent(LCModelComponent): display_name = "SiliconFlow" description = "Generate text using SiliconFlow LLMs." icon = "google" inputs = [ *LCModelComponent._base_inputs, IntInput( name="max_tokens", display_name="Max Tokens", advanced=True, info="Maximum number of tokens to generate. Set to 0 for unlimited.", range_spec=RangeSpec(min=0, max=128000), ), DictInput( name="model_kwargs", display_name="Model Kwargs", advanced=True, info="Additional keyword arguments to pass to the model.", ), BoolInput( name="json_mode", display_name="JSON Mode", advanced=True, info="If True, it will output JSON regardless of passing a schema.", ), DropdownInput( name="model_name", display_name="Model Name", info="SiliconFlow model to use", options=SILICONFLOW_MODELS, value="deepseek-ai/DeepSeek-R1", refresh_button=True, ), StrInput( name="api_base", display_name="SiliconFlow API Base", advanced=True, info="Base URL for API requests. Defaults to api.siliconflow ", value=" api.siliconflow ", ), SecretStrInput( name="api_key", display_name="SiliconFlow API Key", info="The SiliconFlow API Key", advanced=False, required=True, ), SliderInput( name="temperature", display_name="Temperature", info="Controls randomness in responses", value=1.0, range_spec=RangeSpec(min=0, max=2, step=0.01), ), IntInput( name="seed", display_name="Seed", info="The seed controls the reproducibility of the job.", advanced=True, value=1, ), ] def get_models(self) -> list[str]: if not self.api_key: return SILICONFLOW_MODELS url = f"{self.api_base}/models" headers = {"Authorization": f"Bearer {self.api_key}", "Accept": "application/json"} try: response = requests.get(url, headers=headers, timeout=10) response.raise_for_status() model_list = response.json() return [model["id"] for model in model_list.get("data", [])] except requests.RequestException as e: self.status = f"Error fetching models: {e}" return SILICONFLOW_MODELS @override def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None): if field_name in {"api_key", "api_base", "model_name"}: models = self.get_models() build_config["model_name"]["options"] = models return build_config def build_model(self) -> LanguageModel: try: from langchain_openai import ChatOpenAI except ImportError as e: msg = "langchain-openai not installed. Please install with `pip install langchain-openai`" raise ImportError(msg) from e api_key = SecretStr(self.api_key).get_secret_value() if self.api_key else None output = ChatOpenAI( model=self.model_name, temperature=self.temperature if self.temperature is not None else 0.1, max_tokens=self.max_tokens or None, model_kwargs=self.model_kwargs or {}, base_url=self.api_base, api_key=api_key, streaming=self.stream if hasattr(self, "stream") else False, seed=self.seed, ) if self.json_mode: output = output.bind(response_format={"type": "json_object"}) return output def _get_exception_message(self, e: Exception): """Get message from SiliconFlow API exception.""" try: from openai import BadRequestError if isinstance(e, BadRequestError): message = e.body.get("message") if message: return message except ImportError: pass return None