docs/examples/llm/together.ipynb
<a href="https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/examples/llm/together.ipynb" target="_parent"></a>
This notebook shows how to use Together AI as an LLM. Together AI provides access to many state-of-the-art LLM models. Check out the full list of models here.
Visit https://together.ai and sign up to get an API key.
If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.
%pip install llama-index-llms-together
!pip install llama-index
from llama_index.llms.together import TogetherLLM
# set api key in env or in llm
# import os
# os.environ["TOGETHER_API_KEY"] = "your api key"
llm = TogetherLLM(
model="mistralai/Mixtral-8x7B-Instruct-v0.1", api_key="your_api_key"
)
resp = llm.complete("Who is Paul Graham?")
print(resp)
chat with a list of messagesfrom llama_index.core.llms import ChatMessage
messages = [
ChatMessage(
role="system", content="You are a pirate with a colorful personality"
),
ChatMessage(role="user", content="What is your name"),
]
resp = llm.chat(messages)
print(resp)
Using stream_complete endpoint
response = llm.stream_complete("Who is Paul Graham?")
for r in response:
print(r.delta, end="")
Using stream_chat endpoint
from llama_index.core.llms import ChatMessage
messages = [
ChatMessage(
role="system", content="You are a pirate with a colorful personality"
),
ChatMessage(role="user", content="What is your name"),
]
resp = llm.stream_chat(messages)
for r in resp:
print(r.delta, end="")