The ChatFriendliParams interface defines the input parameters for the ChatFriendli class.
interface ChatFriendliParamsBase endpoint url.
Whether to disable streaming.
If streaming is bypassed, then stream() will defer to
invoke().
Number between -2.0 and 2.0. Positive values penalizes tokens that have been sampled, taking into account their frequency in the preceding text. This penalization diminishes the model's tendency to reproduce identical lines verbatim.
Friendli team ID to run as.
Friendli personal access token to run as.
The maximum number of concurrent calls that can be made.
Defaults to Infinity, which means no limit.
The maximum number of retries that can be made for a single call, with an exponential backoff between each attempt. Defaults to 6.
Number between -2.0 and 2.0. Positive values penalizes tokens that have been
sampled at least once in the existing text.
presence_penalty: Optional[float] = None
The maximum number of tokens to generate. The length of your input tokens plus
max_tokens should not exceed the model's maximum length (e.g., 2048 for OpenAI
GPT-3)
Model name to use.
Custom handler to handle failed attempts. Takes the originally thrown error object as input, and should itself throw an error if the input error is not retryable.
Version of AIMessage output format to store in message content.
AIMessage.contentBlocks will lazily parse the contents of content into a
standard format. This flag can be used to additionally store the standard format
as the message content, e.g., for serialization purposes.
.contentBlocks).contentBlocks)You can also set LC_OUTPUT_VERSION as an environment variable to "v1" to
enable this by default.
When one of the stop phrases appears in the generation result, the API will stop generation. The phrase is included in the generated result. If you are using beam search, all of the active beams should contain the stop phrase to terminate generation. Before checking whether a stop phrase is included in the result, the phrase is converted into tokens.
Sampling temperature. Smaller temperature makes the generation result closer to
greedy, argmax (i.e., top_k = 1) sampling. If it is None, then 1.0 is used.
Tokens comprising the top top_p probability mass are kept for sampling. Numbers
between 0.0 (exclusive) and 1.0 (inclusive) are allowed. If it is None, then 1.0
is used by default.