SDKs & Libraries

Official SDKs for TypeScript, Python, and Go. Drop-in compatible with the OpenAI SDK — just change the base URL.

OpenAI SDK compatible. If you already use the OpenAI SDK, you can use Aisays.ai without installing a new SDK. Just set baseURL to https://api.aisays.ai/v1.

TypeScript / JavaScript

Full-featured TypeScript SDK with streaming, auto-retry, and type-safe responses.

Setup

import { AisaysAI } from "aisaysai"

const client = new AisaysAI({
  apiKey: process.env.AISAYSAI_API_KEY,
  // Optional: base URL, timeout, retry config
})

Usage Examples

// Chat completion
const response = await client.chat.completions.create({
  model: "deepseek/deepseek-v4-flash",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Hello!" },
  ],
  max_tokens: 500,
})

console.log(response.choices[0].message.content)

// Streaming
const stream = await client.chat.completions.create({
  model: "moonshot/kimi-k2.5",
  messages: [{ role: "user", content: "Tell me a story" }],
  stream: true,
})

for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content || "")
}

// List models
const models = await client.models.list()
models.data.forEach((m) => console.log(m.id))

Python

Python SDK with async support, type hints, and OpenAI-compatible drop-in.

Setup

from aisaysai import AisaysAI

client = AisaysAI(
    api_key="sk-or-YOUR_API_KEY",
    # Optional: base_url, timeout, max_retries
)

Usage Examples

# Chat completion
response = client.chat.completions.create(
    model="deepseek/deepseek-v4-flash",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"},
    ],
    max_tokens=500,
)

print(response.choices[0].message.content)

# Streaming
stream = client.chat.completions.create(
    model="moonshot/kimi-k2.5",
    messages=[{"role": "user", "content": "Tell me a story"}],
    stream=True,
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

# Async
import asyncio
from aisaysai import AsyncAisaysAI

async_client = AsyncAisaysAI(api_key="sk-or-YOUR_API_KEY")

async def main():
    response = await async_client.chat.completions.create(
        model="deepseek/deepseek-v4-flash",
        messages=[{"role": "user", "content": "Hello!"}],
    )
    print(response.choices[0].message.content)

asyncio.run(main())

Go

Go SDK with context support, structured logging, and connection pooling.

Setup

package main

import (
    "context"
    "github.com/aisaysai/aisaysai-go"
)

func main() {
    client := aisaysai.NewClient(
        aisaysai.WithAPIKey("sk-or-YOUR_API_KEY"),
    )
    _ = client
}

Usage Examples

// Chat completion
ctx := context.Background()
resp, err := client.Chat.Completions.Create(ctx, aisaysai.ChatCompletionRequest{
    Model: "deepseek/deepseek-v4-flash",
    Messages: []aisaysai.Message{
        {Role: "system", Content: "You are a helpful assistant."},
        {Role: "user", Content: "Hello!"},
    },
    MaxTokens: 500,
})
if err != nil {
    log.Fatal(err)
}
fmt.Println(resp.Choices[0].Message.Content)

// Streaming
stream, err := client.Chat.Completions.CreateStreaming(ctx, aisaysai.ChatCompletionRequest{
    Model: "moonshot/kimi-k2.5",
    Messages: []aisaysai.Message{
        {Role: "user", Content: "Tell me a story"},
    },
})
if err != nil {
    log.Fatal(err)
}
defer stream.Close()

for stream.Next() {
    chunk := stream.Current()
    fmt.Print(chunk.Choices[0].Delta.Content)
}

REST API

Prefer raw HTTP? All endpoints are documented with OpenAPI specs.

// Chat completion const response = await client.chat.completions.create({ model: "deepseek/deepseek-v4-flash", messages: [ { role: "system", content: "You are a helpful assistant." }, { role: "user", content: "Hello!" }, ], max_tokens: 500, }) console.log(response.choices[0].message.content) // Streaming const stream = await client.chat.completions.create({ model: "moonshot/kimi-k2.5", messages: [{ role: "user", content: "Tell me a story" }], stream: true, }) for await (const chunk of stream) { process.stdout.write(chunk.choices[0]?.delta?.content || "") } // List models const models = await client.models.list() models.data.forEach((m) => console.log(m.id))

# Chat completion response = client.chat.completions.create( model="deepseek/deepseek-v4-flash", messages=[ {"role": "system", "content": "You are a helpful assistant."}, {"role": "user", "content": "Hello!"}, ], max_tokens=500, ) print(response.choices[0].message.content) # Streaming stream = client.chat.completions.create( model="moonshot/kimi-k2.5", messages=[{"role": "user", "content": "Tell me a story"}], stream=True, ) for chunk in stream: if chunk.choices[0].delta.content: print(chunk.choices[0].delta.content, end="", flush=True) # Async import asyncio from aisaysai import AsyncAisaysAI async_client = AsyncAisaysAI(api_key="sk-or-YOUR_API_KEY") async def main(): response = await async_client.chat.completions.create( model="deepseek/deepseek-v4-flash", messages=[{"role": "user", "content": "Hello!"}], ) print(response.choices[0].message.content) asyncio.run(main())

// Chat completion ctx := context.Background() resp, err := client.Chat.Completions.Create(ctx, aisaysai.ChatCompletionRequest{ Model: "deepseek/deepseek-v4-flash", Messages: []aisaysai.Message{ {Role: "system", Content: "You are a helpful assistant."}, {Role: "user", Content: "Hello!"}, }, MaxTokens: 500, }) if err != nil { log.Fatal(err) } fmt.Println(resp.Choices[0].Message.Content) // Streaming stream, err := client.Chat.Completions.CreateStreaming(ctx, aisaysai.ChatCompletionRequest{ Model: "moonshot/kimi-k2.5", Messages: []aisaysai.Message{ {Role: "user", Content: "Tell me a story"}, }, }) if err != nil { log.Fatal(err) } defer stream.Close() for stream.Next() { chunk := stream.Current() fmt.Print(chunk.Choices[0].Delta.Content) }