OctoAI¶

If you're opening this Notebook on colab, you will probably need to install LlamaIndex 🦙.

In [ ]:

%pip install llama-index-llms-octoai
%pip install llama-index
%pip install octoai-sdk

%pip install llama-index-llms-octoai %pip install llama-index %pip install octoai-sdk

Include your OctoAI API key below. You can get yours at OctoAI.

Here are some instructions in case you need more guidance.

In [ ]:

OCTOAI_API_KEY = ""

OCTOAI_API_KEY = ""

Initialize the Integration with the default model¶

In [ ]:

from llama_index.llms.octoai import OctoAI

octoai = OctoAI(token=OCTOAI_API_KEY)

from llama_index.llms.octoai import OctoAI octoai = OctoAI(token=OCTOAI_API_KEY)

Call complete with a prompt¶

In [ ]:

response = octoai.complete("Paul Graham is ")
print(response)

response = octoai.complete("Paul Graham is ") print(response)

Call chat with a list of messages¶

In [ ]:

from llama_index.core.llms import ChatMessage

messages = [
    ChatMessage(
        role="system",
        content="Below is an instruction that describes a task. Write a response that appropriately completes the request.",
    ),
    ChatMessage(role="user", content="Write a blog about Seattle"),
]
response = octoai.chat(messages)
print(response)

from llama_index.core.llms import ChatMessage messages = [ ChatMessage( role="system", content="Below is an instruction that describes a task. Write a response that appropriately completes the request.", ), ChatMessage(role="user", content="Write a blog about Seattle"), ] response = octoai.chat(messages) print(response)

Streaming¶

Using stream_complete endpoint

In [ ]:

response = octoai.stream_complete("Paul Graham is ")
for r in response:
    print(r.delta, end="")

response = octoai.stream_complete("Paul Graham is ") for r in response: print(r.delta, end="")

Using stream_chat with a list of messages

In [ ]:

from llama_index.core.llms import ChatMessage

messages = [
    ChatMessage(
        role="system",
        content="Below is an instruction that describes a task. Write a response that appropriately completes the request.",
    ),
    ChatMessage(role="user", content="Write a blog about Seattle"),
]
response = octoai.stream_chat(messages)
for r in response:
    print(r.delta, end="")

from llama_index.core.llms import ChatMessage messages = [ ChatMessage( role="system", content="Below is an instruction that describes a task. Write a response that appropriately completes the request.", ), ChatMessage(role="user", content="Write a blog about Seattle"), ] response = octoai.stream_chat(messages) for r in response: print(r.delta, end="")

Configure Model¶

In [ ]:

# To customize your API token, do this
# otherwise it will lookup OCTOAI_TOKEN from your env variable
octoai = OctoAI(
    model="mistral-7b-instruct", max_tokens=128, token=OCTOAI_API_KEY
)

response = octoai.complete("Paul Graham is ")
print(response)

# To customize your API token, do this # otherwise it will lookup OCTOAI_TOKEN from your env variable octoai = OctoAI( model="mistral-7b-instruct", max_tokens=128, token=OCTOAI_API_KEY ) response = octoai.complete("Paul Graham is ") print(response)