OPENAI_API_KEY
environment variable. You can obtain the OpenAI API key from the OpenAI Platform.
Once you have obtained the key, you can use it like this:
OpenAILlm
class as an array of functions. Here are several ways in which you can achieve that:
Examples:
Using Pydantic Models
Using OpenAI JSON schema
Using actual python functions
GOOGLE_API_KEY
environment variable. You can obtain the Google API key from the Google Maker Suite
ANTHROPIC_API_KEY
which you find on their Account Settings Page.
COHERE_API_KEY
as environment variable which you can find on their Account settings page.
Once you have the API key, you are all set to use it with Embedchain.
TOGETHER_API_KEY
as environment variable which you can find on their Account settings page.
Once you have the API key, you are all set to use it with Embedchain.
JINACHAT_API_KEY
in environment variable which you can obtain from their platform.
Once you have the key, load the app using the config yaml file:
HUGGINGFACE_ACCESS_TOKEN
in environment variable which you can obtain from their platform.
Once you have the token, load the app using the config yaml file:
HUGGINGFACE_ACCESS_TOKEN
as above.
Then, load the app using the config yaml file:
model_kwargs
field:
text-generation
and text2text-generation
for now [ref].
See langchain’s hugging face endpoint for more information.
REPLICATE_API_TOKEN
in environment variable which you can obtain from their platform.
Once you have the token, load the app using the config yaml file:
boto3
client by using a method in the AWS documentationAWS_REGION