Skip to main content
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

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:
  • python
  • Typescript
import os
import openai

client = openai.OpenAI(
api_key=os.environ.get("TOGETHER_API_KEY"),
base_url="https://api.together.xyz/v1",
)
You can find your API key in your settings page. If you don’t have an account, you can register for free. New accounts come with $5 to get started.

​
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, like Meta Llama 3:
  • python
  • Typescript
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)
Or you can use a language model to generate a code completion:
  • python
  • Typescript
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)

​
Streaming with OpenAI

You can also use OpenAI’s streaming capabilities to stream back your response:
  • python
  • TypeScript
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)

​
Community libraries

The Together API is also supported by most OpenAI libraries built by the community. Feel free to reach out to support if you come across some unexpected behavior when using our API. Updated 28 days ago