Wrapper around Ali Tongyi large language models that use the Chat endpoint.
To use you should have the ALIBABA_API_KEY
environment variable set.
AWS Bedrock chat model integration.
Setup:
Install @langchain/community and set the following environment variables:
npm install @langchain/openai
export AWS_REGION="your-aws-region"
expor
AWS Bedrock chat model integration.
Setup:
Install @langchain/community and set the following environment variables:
npm install @langchain/openai
export AWS_REGION="your-aws-region"
expor
Wrapper around Fireworks API for large language models fine-tuned for chat
Fireworks API is compatible to the OpenAI API with some limitations described in https://readme.fireworks.ai/docs/openai-com
The ChatFriendli class is used to interact with Friendli inference Endpoint models. This requires your Friendli Token and Friendli Team which is autoloaded if not specified.
To use this model you need to have the node-llama-cpp module installed.
This can be installed using npm install -S node-llama-cpp and the minimum
version supported in version 2.0.0.
This also r
Wrapper around Minimax large language models that use the Chat endpoint.
To use you should have the MINIMAX_GROUP_ID and MINIMAX_API_KEY
environment variable set.
Interface defining the input to the MoonshotChatInput class.
Novita chat model implementation
Wrapper around Perplexity large language models that use the Chat endpoint.
Integration with a chat model.
Wrapper around Tencent Hunyuan large language models that use the Chat endpoint.
To use you should have the TENCENT_SECRET_ID and TENCENT_SECRET_KEY
environment variable set.
Wrapper around Tencent Hunyuan large language models that use the Chat endpoint.
To use you should have the TENCENT_SECRET_ID and TENCENT_SECRET_KEY
environment variable set.
TogetherAI chat model integration.
The TogetherAI API is compatible to the OpenAI API with some limitations. View the full API ref at:
To use this model you need to have the @mlc-ai/web-llm module installed.
This can be installed using npm install -S @mlc-ai/web-llm.
You can see a list of available model records here: https://gi
Interface defining the input to the ZhipuAIChatInput class.
Function that converts an array of messages into a single string prompt that can be used as input for a chat model. It delegates the conversion logic to the appropriate provider-specific function.
Function that converts an array of messages into a single string prompt that can be used as input for a chat model. It delegates the conversion logic to the appropriate provider-specific function.
The ChatFriendliParams interface defines the input parameters for the ChatFriendli class.
Deployed params
Project/space params
Project/space params
Deployed params
Project/space params
Deployed params
Gateway params
Project/space params
Note that the modelPath is the only required parameter. For testing you
can set this in the environment variable LLAMA_PATH.
The name and arguments of a function that should be called, as generated by the model.
Interface defining the input to the MoonshotChatInput class.
Interface defining the parameters for the Perplexity chat model.
Input to chat model class.
Interface defining the input to the ChatTencentHunyuan class.
Interface defining the input to the ChatTencentHunyuan class.
Interface defining the input to the ZhipuAIChatInput class.