AISuite：统一 LLM Agent API 2026 版

pip install aisuite

from aisuite import UnifiedClient

client = UnifiedClient(
    providers={
        "openai": {"api_key": "sk-xxx"},
        "anthropic": {"api_key": "sk-xxx"},
        "ollama": {"base_url": "http://localhost:11434"}
    }
)

# 调用 OpenAI
response = client.chat.completions.create(
    model="gpt-4",
    messages=[{"role": "user", "content": "你好"}]
)

# 调用 Ollama
response = client.chat.completions.create(
    model="llama3:latest",
    messages=[{"role": "user", "content": "解释 AI"}]
)

from aisuite.agent import Agent

agent = Agent(
    llm="gpt-4",
    provider="openai",
    tools=[search, calculator]
)

response = agent.ask("查询今天的天气")

from aisuite.orchestrator import Orchestrator

orchestrator = Orchestrator()
result = orchestrator.route(
    query="解释量子计算",
    preferred_models=["gpt-4", "claude-3-opus"]
)

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "获取天气",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {"type": "string"}
                },
                "required": ["city"]
            }
        }
    }
]

response = client.chat.completions.create(
    model="gpt-4",
    messages=query,
    tools=tools
)

completion = client.completions.create(
    model="llama3",
    prompt="写一首诗：AI 时代"
)
print(completion.choices[0].text)

messages = [
    {"role": "system", "content": "你是个 helpful assistant"},
    {"role": "user", "content": "解释下面的代码："}
]

response = client.chat.completions.create(
    model="gpt-4",
    messages=messages
)

export OPENAI_API_KEY=sk-xxx
export ANTHROPIC_API_KEY=sk-xxx
export AISUITE_DEFAULT_PROVIDER=openai

# aisuite.yaml
providers:
  openai:
    api_key: ${OPENAI_API_KEY}
    base_url: https://api.openai.com/v1
  local:
    base_url: http://localhost:11434

defaults:
  model: gpt-4
  temperature: 0.7
  max_tokens: 2048

from concurrent.futures import ThreadPoolExecutor

models = ["gpt-4", "claude-3-opus", "gemini-pro"]
prompts = ["解释 AI", "下一个时代", "未来趋势"]

with ThreadPoolExecutor() as executor:
    futures = [
        executor.submit(client.chat.completions.create, 
                       model=m, messages=[{"role": "user", "content": p}])
        for m, p in zip(models, prompts)
    ]
    results = [f.result() for f in futures]

client.configure(
    retry=3,
    timeout=30,
    backoff="exponential"
)