> ## Documentation Index
> Fetch the complete documentation index at: https://together-ai-preview.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.
# OpenAI Compatibility
> Together's API is compatible with OpenAI's client libraries, making it easy to try out our open-source models on existing applications.
Together's API endpoints for chat, language and code, images, and embeddings are fully compatible with OpenAI's API.
If you have an application that uses one of OpenAI's client libraries, you can easily configure it to point to Together's API servers, and start running your existing applications using our open-source models.
## [Configuring OpenAI to use Together's API](#configuring-openai-to-use-togethers-api)
To start using Together with OpenAI's client libraries, pass in your Together API key to the api\_key option, and change the base\_url to [https://api.together.xyz/v1](https://api.together.xyz/v1):
```
import os
import openai
client = openai.OpenAI(
api_key=os.environ.get("TOGETHER_API_KEY"),
base_url="https://api.together.xyz/v1",
)
```
```
import OpenAI from "openai";
const client = new OpenAI({
apiKey: process.env.TOGETHER_API_KEY,
baseURL: "https://api.together.xyz/v1",
});
```
You can find your API key in [your settings page](https://api.together.xyz/settings/api-keys). If you don't have an account, you can [register for free](https://api.together.ai/). New accounts come with \$5 to get started.
## [Querying an Inference model](#querying-an-inference-model)
Now that your OpenAI client is configured to point to Together, you can start using one of our open-source models for your inference queries.
For example, you can query one of our [chat models](/docs/chat-models), like Meta Llama 3:
```
import os
import openai
client = openai.OpenAI(
api_key=os.environ.get("TOGETHER_API_KEY"),
base_url="https://api.together.xyz/v1",
)
response = client.chat.completions.create(
model="meta-llama/Llama-3-8b-chat-hf",
messages=[
{"role": "system", "content": "You are a travel agent. Be descriptive and helpful."},
{"role": "user", "content": "Tell me about San Francisco"},
]
)
print(response.choices[0].message.content)
```
```
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.TOGETHER_API_KEY,
baseURL: 'https://api.together.xyz/v1',
});
const response = await client.chat.completions.create({
model: 'meta-llama/Llama-3-8b-chat-hf',
messages: [
{ role: 'user', content: 'What are some fun things to do in New York?' },
],
});
console.log(response.choices[0].message.content);
```
Or you can use a [language model](/docs/language-and-code-models) to generate a code completion:
```
import os
import openai
client = openai.OpenAI(
api_key=os.environ.get("TOGETHER_API_KEY"),
base_url="https://api.together.xyz/v1",
)
response = client.completions.create(
model="codellama/CodeLlama-34b-Python-hf",
prompt="def bubbleSort(): ",
max_tokens=175
)
print(response.choices[0].text)
```
```
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.TOGETHER_API_KEY,
baseURL: 'https://api.together.xyz/v1',
});
const response = await client.completions.create({
model: 'codellama/CodeLlama-34b-Python-hf',
prompt: 'def bubbleSort(): ',
max_tokens: 175,
});
console.log(response.choices[0].text);
```
## Streaming with OpenAI
You can also use OpenAI's streaming capabilities to stream back your response:
```
import os
import openai
system_content = "You are a travel agent. Be descriptive and helpful."
user_content = "Tell me about San Francisco"
client = openai.OpenAI(
api_key=os.environ.get("TOGETHER_API_KEY"),
base_url="https://api.together.xyz/v1",
)
stream = client.chat.completions.create(
model="mistralai/Mixtral-8x7B-Instruct-v0.1",
messages=[
{"role": "system", "content": system_content},
{"role": "user", "content": user_content},
],
stream=True,
)
for chunk in stream:
print(chunk.choices[0].delta.content or "", end="", flush=True)
```
```
import OpenAI from 'openai';
const client = new OpenAI({
apiKey: process.env.TOGETHER_API_KEY,
baseURL: 'https://api.together.xyz/v1',
});
async function run() {
const stream = await client.chat.completions.create({
model: 'mistralai/Mixtral-8x7B-Instruct-v0.1',
messages: [
{ role: 'system', content: 'You are an AI assistant' },
{ role: 'user', content: 'Who won the world series in 2020?' },
],
stream: true,
});
for await (const chunk of stream) {
// use process.stdout.write instead of console.log to avoid newlines
process.stdout.write(chunk.choices[0]?.delta?.content || '');
}
}
run();
```
## [Community libraries](#community-libraries)
The Together API is also supported by most [OpenAI libraries built by the community](https://platform.openai.com/docs/libraries/community-libraries).
Feel free to [reach out to support](https://www.together.ai/contact) if you come across some unexpected behavior when using our API.
Updated 28 days ago