硅基流动：致力于为开发者提供更快、更全面、体验更丝滑的模型 API，助力开发者和企业聚焦产品创新，无须担心产品大规模推广所带来的高昂算力成本。提供免费的模型以及付费模型，按需使用。

注册获取apiKey：https://cloud.siliconflow.cn/account/ak

代码示例：(包括：文本对话、文生图、向量化、重排序等功能)

import requests
import json
import os
from dotenv import load_dotenv
load_dotenv()

# os.environ['SILICON_FLOW_API_KEY'] = 'your sk-xxxxxxxxxxxxxxx'

def chat_openai(prompt):
    url = "https://api.siliconflow.cn/v1/chat/completions"

    payload = {
        "messages": [
            {
                "content": prompt,
                "role": "user"
            }
        ],
        # THUDM/glm-4-9b-chat, deepseek-ai/DeepSeek-R1-Distill-Llama-8B
        "model": "THUDM/glm-4-9b-chat",
        "frequency_penalty": 0.5,
        "max_tokens": 509,
        "n": 0,
        "response_format": {"type": "text"},
        "temperature": 0.7,
        "top_k": 50,
        "top_p": 0.7,
        # "tools": [
        #     {
        #         "type": "function",
        #         "function": {
        #             "description": "<string>",
        #             "name": "<string>",
        #             "parameters": {},
        #             "strict": False
        #         }
        #     }
        # ]
    }
    headers = {
        "Authorization": "Bearer " + os.getenv('SILICON_FLOW_API_KEY'),
        "Content-Type": "application/json"
    }
    response = requests.request("POST", url, json=payload, headers=headers)
    res = json.loads(response.text).get('choices')[0].get('message').get('content')
    print(res)
    return res

def text_to_image(text):
    url = "https://api.siliconflow.cn/v1/images/generations"
    payload = {
        "batch_size": 1, # 输出图片个数 1-4
        "guidance_scale": 11, # 图文匹配程度 0-20，低则创造性，高则更匹配
        "image_size": "576x1024", # 1024x1024, 512x1024, 768x512, 768x1024, 1024x576, 576x1024 
        "model": "black-forest-labs/FLUX.1-schnell", # 模型名称
        "num_inference_steps": 40, # 推理步骤数 1-50
        "prompt": text,
        # "seed": 123, # 随机种子，seed+prompt一致时，下一次则可能生成一样的图
        "prompt_enhancement": True # 开启将提示优化为详细的、模型友好的版本
    }
    headers = {
        "Authorization": "Bearer " + os.getenv('SILICON_FLOW_API_KEY'),
        "Content-Type": "application/json"
    }

    response = requests.request("POST", url, json=payload, headers=headers)
    text = response.text
    print(text)
    text = text.replace('\\u0026', '&') # 替换 \u0026 为 &
    print(text)
    res = json.loads(text).get('data')[0].get('url')
    return res

import base64
def image_to_base64(image_path):
    with open(image_path, 'rb') as image_file:
        image_data = image_file.read()
        base64_data = base64.b64encode(image_data)
        return base64_data.decode('utf-8')

def image_to_image(image_path, prompt):
    url = "https://api.siliconflow.cn/v1/images/generations"

    payload = {
        "batch_size": 1,
        "guidance_scale": 9,
        "image_size": "1024x1024",
        # stabilityai/stable-diffusion-2-1.0, stabilityai/stable-diffusion-xl-base-1.0
        "model": "stabilityai/stable-diffusion-xl-base-1.0",
        "num_inference_steps": 39,
        "prompt": prompt,
        "image": image_to_base64(image_path),
    }
    headers = {
        "Authorization": "Bearer " + os.getenv('SILICON_FLOW_API_KEY'),
        "Content-Type": "application/json"
    }

    response = requests.request("POST", url, json=payload, headers=headers)
    text = response.text
    print(text)
    text = text.replace('\\u0026', '&') # 替换 \u0026 为 &
    print(text)

def embed_text(text):
    url = "https://api.siliconflow.cn/v1/embeddings"

    payload = {
        "model": "BAAI/bge-m3",
        "input": text,
        "encoding_format": "float"
    }
    headers = {
        "Authorization": "Bearer " + os.getenv('SILICON_FLOW_API_KEY'),
        "Content-Type": "application/json"
    }

    response = requests.request("POST", url, json=payload, headers=headers)

    print(response.text)

def rerank(query, docs):
    url = "https://api.siliconflow.cn/v1/rerank"

    payload = {
        "model": "BAAI/bge-reranker-v2-m3",
        "query": query,
        "documents": docs,
        "top_n": 4,
        "return_documents": False,
        "max_chunks_per_doc": 1024,
        "overlap_tokens": 80
    }
    headers = {
        "Authorization": "Bearer " + os.getenv('SILICON_FLOW_API_KEY'),
        "Content-Type": "application/json"
    }

    response = requests.request("POST", url, json=payload, headers=headers)

    print(response.text)

# rerank('Apple', ["苹果", "香蕉", "水果", "蔬菜"])

# image_to_image('./doc/2023.jpg', "背景改成白色")

res = chat_openai("""我打算生成一张图片，内容大概是：\n 
            夕阳下奔跑的少年
            \n 帮我写一段细节更详细一点的提示语，包括高清、高品质、细节精致、真实写真风格等等。""")

text_to_image(res)