from litellm import completion# OpenAI调用response = completion(
model="openai/gpt-4", 
messages=[{"role": "user", "content": "写一个python快速排序"}]
)

# 换成Anthropicresponse = completion(
model="anthropic/claude-3-sonnet",
messages=[{"role": "user", "content": "写一个python快速排序"}]
)# 换成Googleresponse = completion(
model="google/gemini-pro",
messages=[{"role": "user", "content": "写一个python快速排序"}]
)

from litellm import Router# 配置模型列表model_list = [
{"model_name": "gpt-4","litellm_params": {"model": "openai/gpt-4"},
},
{"model_name": "gpt-4","litellm_params": {"model": "anthropic/claude-3-sonnet"},
}
]# 创建路由器router = Router(model_list=model_list)# 自动选择可用模型response = router.completion(
model="gpt-4",
messages=[{"role": "user", "content": "你好"}]
)

from litellm import completionimport os# 设置回调os.environ["HELICONE_API_KEY"] = "your-key"litellm.success_callback = ["helicone"]# 调用时会自动记录用量response = completion(
model="openai/gpt-4",
messages=[{"role": "user", "content": "Hi"}],
metadata={"project": "chatbot", "user": "user_123"}
)

response = completion(
model="openai/gpt-4",
messages=[{"role": "user", "content": "讲个故事"}],
stream=True)for chunk in response:print(chunk.choices[0].delta.content or "", end="")

litellm --model huggingface/bigcode/starcoder

import openai
client = openai.OpenAI(
api_key="anything",
base_url="http://localhost:4000")

response = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[{"role": "user", "content": "你好"}]
)