Together AI

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You are currently on a page documenting the use of Together AI models as text completion models. Many popular Together AI models are chat completion models.

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Together AI offers an API to query 50+ leading open-source models in a couple lines of code.

This example goes over how to use LangChain to interact with Together AI models.

Installation

%pip install --upgrade langchain-together

Environment

To use Together AI, you'll need an API key which you can find here: https://api.together.ai/settings/api-keys. This can be passed in as an init param together_api_key or set as environment variable TOGETHER_API_KEY.

Example

# Querying chat models with Together AI

from langchain_together import ChatTogether

# choose from our 50+ models here: https://docs.together.ai/docs/inference-models
chat = ChatTogether(
    # together_api_key="YOUR_API_KEY",
    model="meta-llama/Llama-3-70b-chat-hf",
)

# stream the response back from the model
for m in chat.stream("Tell me fun things to do in NYC"):
    print(m.content, end="", flush=True)

# if you don't want to do streaming, you can use the invoke method
# chat.invoke("Tell me fun things to do in NYC")

API Reference:ChatTogether

# Querying code and language models with Together AI

from langchain_together import Together

llm = Together(
    model="codellama/CodeLlama-70b-Python-hf",
    # together_api_key="..."
)

print(llm.invoke("def bubble_sort(): "))

API Reference:Together

Related

• LLM conceptual guide
• LLM how-to guides