> ## Documentation Index
> Fetch the complete documentation index at: https://aisa.one/docs/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> - Base URLs: models `https://api.aisa.one/v1` (Gemini GenerateContent: `https://api.aisa.one/v1beta`); data APIs `https://api.aisa.one/apis/v1`. The `servers` of each operation in https://aisa.one/openapi.yaml is authoritative.
> - Auth: `Authorization: Bearer $AISA_API_KEY`. Never print, log, or commit the key.
> - MCP (preferred for agents): `https://mcp.aisa.one/mcp`, signed in with OAuth, so there is no key to paste.
> - Agent Skill: `npx skills add AIsa-team/agent-skills --skill aisa`. Fallback with the AIsa CLI: `aisa skills install aisa`.
> - Spending: docs, https://aisa.one/models, https://aisa.one/api, `/v1/models`, and MCP `search`, `list_categories`, `get_details`, `batch_quote`, and the `account` operation are free. Quote the exact calls before running them (MCP `batch_quote`, CLI `aisa quote --json`). If the quote reports `auto_execute_eligible: true`, run it unless the user set a tighter limit or asked only for a quote. Otherwise, tell the user in one message the planned calls, the quoted price, and a total USD budget for the task, then wait for approval. Direct HTTP calls follow the stricter rule at https://aisa.one/docs/get-started/cli.md#direct-http-fallback. Do not make paid calls to test availability. Full rule: https://aisa.one/llms.txt

# 混元 API - 通过 AIsa 访问腾讯混元模型

> 腾讯混元模型 ID 和端点指南：通过 OpenAI 兼容路由调用。

AIsa 用一个 API Key 接入腾讯的混元模型。混元模型使用 `POST /v1/chat/completions` 和 `POST /v1/responses`。

## 支持的混元模型

| 模型 ID | 类型 | 端点 | 适合 |
| - | - | - | - |
| `hy3` | 文本 | `/v1/chat/completions`、`/v1/responses` | 腾讯混元文本路由 |
| `hy4-preview` | 文本 | `/v1/chat/completions`、`/v1/responses` | 下一代混元的预览版本 |

这些模型的当前价格见 [aisa.one/models](https://aisa.one/models)。

## 快速开始

```python theme={null}
import os
from openai import OpenAI

client = OpenAI(api_key=os.environ["AISA_API_KEY"], base_url="https://api.aisa.one/v1")

response = client.chat.completions.create(
    model="hy3",
    messages=[{"role": "user", "content": "Summarize this product review in one sentence."}],
)
print(response.choices[0].message.content)
```

## 下一步

* [模型目录](https://aisa.one/docs/zh/guides/models.md)
* [AI 模型价格](https://aisa.one/docs/zh/guides/pricing.md#模型)


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.