Using Official OpenAI Libraries
GravitexAI is fully compatible with OpenAI API format. You can use official OpenAI SDKs with just a simple configuration change.Supported SDKs
- Python (
openai) - Node.js (
openai) - .NET (
OpenAI) - Go (
go-openai) - Java (third-party)
- PHP (third-party)
- Ruby (third-party)
Python SDK
Installation
pip install openai
Basic Configuration
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.gravitex.ai/v1"
)
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{"role": "user", "content": "Hello!"}
]
)
print(response.choices[0].message.content)
Environment Variables
import os
from openai import OpenAI
os.environ["OPENAI_API_KEY"] = "YOUR_API_KEY"
os.environ["OPENAI_BASE_URL"] = "https://api.gravitex.ai/v1"
client = OpenAI()
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Explain quantum computing"}]
)
Async Usage
import asyncio
from openai import AsyncOpenAI
async def main():
client = AsyncOpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.gravitex.ai/v1"
)
response = await client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello!"}]
)
print(response.choices[0].message.content)
asyncio.run(main())
Streaming
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.gravitex.ai/v1"
)
stream = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Write a short story"}],
stream=True
)
for chunk in stream:
if chunk.choices[0].delta.content is not None:
print(chunk.choices[0].delta.content, end="")
Node.js SDK
Installation
npm install openai
Basic Configuration
import OpenAI from 'openai';
const openai = new OpenAI({
apiKey: 'YOUR_API_KEY',
baseURL: 'https://api.gravitex.ai/v1'
});
const response = await openai.chat.completions.create({
model: 'gpt-4o',
messages: [{ role: 'user', content: 'Hello!' }]
});
console.log(response.choices[0].message.content);
Streaming
const stream = await openai.chat.completions.create({
model: 'gpt-4o',
messages: [{ role: 'user', content: 'Tell me a joke' }],
stream: true
});
for await (const chunk of stream) {
if (chunk.choices[0]?.delta?.content) {
process.stdout.write(chunk.choices[0].delta.content);
}
}
TypeScript
import OpenAI from 'openai';
import type { ChatCompletionCreateParamsNonStreaming } from 'openai/resources/chat/completions';
const openai = new OpenAI({
apiKey: process.env.OPENAI_API_KEY!,
baseURL: 'https://api.gravitex.ai/v1'
});
const params: ChatCompletionCreateParamsNonStreaming = {
model: 'gpt-4o',
messages: [{ role: 'user', content: 'Hello TypeScript!' }],
temperature: 0.7
};
const response = await openai.chat.completions.create(params);
.NET SDK
Installation
dotnet add package OpenAI
Basic Configuration
using OpenAI;
using OpenAI.Chat;
var client = new OpenAIClient("YOUR_API_KEY", new OpenAIClientOptions
{
Endpoint = new Uri("https://api.gravitex.ai/v1")
});
var chatClient = client.GetChatClient("gpt-4o");
var response = await chatClient.CompleteChatAsync("Hello!");
Console.WriteLine(response.Value.Content[0].Text);
Go SDK
Installation
go get github.com/sashabaranov/go-openai
Basic Configuration
package main
import (
"context"
"fmt"
openai "github.com/sashabaranov/go-openai"
)
func main() {
config := openai.DefaultConfig("YOUR_API_KEY")
config.BaseURL = "https://api.gravitex.ai/v1"
client := openai.NewClientWithConfig(config)
resp, err := client.CreateChatCompletion(
context.Background(),
openai.ChatCompletionRequest{
Model: "gpt-4o",
Messages: []openai.ChatCompletionMessage{
{Role: openai.ChatMessageRoleUser, Content: "Hello!"},
},
},
)
if err != nil {
fmt.Printf("Error: %v\n", err)
return
}
fmt.Println(resp.Choices[0].Message.Content)
}
Model Switching
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://api.gravitex.ai/v1"
)
# GPT model
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello"}]
)
# Claude model
response = client.chat.completions.create(
model="claude-sonnet-4-20250514",
messages=[{"role": "user", "content": "Hello"}]
)
# Gemini model
response = client.chat.completions.create(
model="gemini-2.5-pro",
messages=[{"role": "user", "content": "Hello"}]
)
Advanced Features
Function Calling
tools = [
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get weather info for a city",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string", "description": "City name"}
},
"required": ["location"]
}
}
}
]
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "What's the weather in Beijing?"}],
tools=tools,
tool_choice="auto"
)
Image Input
response = client.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "user",
"content": [
{"type": "text", "text": "What's in this image?"},
{
"type": "image_url",
"image_url": {"url": "https://example.com/image.jpg"}
}
]
}
]
)
Embeddings
response = client.embeddings.create(
model="text-embedding-3-small",
input="Text to embed"
)
embedding = response.data[0].embedding
print(f"Dimensions: {len(embedding)}")
Error Handling
from openai import (
OpenAI,
APIError,
APIConnectionError,
RateLimitError,
InternalServerError
)
try:
response = client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": "Hello"}]
)
except RateLimitError:
print("Rate limited, please retry later")
except APIConnectionError:
print("Network connection error")
except InternalServerError:
print("Server internal error")
except APIError as e:
print(f"API error: {e}")
Migration Guide
From OpenAI
# Original config
client = OpenAI(api_key="sk-...")
# Change to GravitexAI
client = OpenAI(
api_key="YOUR_GRAVITEX_KEY",
base_url="https://api.gravitex.ai/v1"
)
No code changes needed. All other code stays the same including method calls, parameter formats, and response handling.