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togetherai.ts
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import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
import {
LLM,
type BaseLLMCallOptions,
type BaseLLMParams,
} from "@langchain/core/language_models/llms";
import { GenerationChunk } from "@langchain/core/outputs";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { convertEventStreamToIterableReadableDataStream } from "../utils/event_source_parse.js";
interface TogetherAIInferenceResult {
object: string;
status: string;
prompt: Array<string>;
model: string;
model_owner: string;
tags: object;
num_returns: number;
args: {
model: string;
prompt: string;
temperature: number;
top_p: number;
top_k: number;
max_tokens: number;
stop: string[];
};
// eslint-disable-next-line @typescript-eslint/no-explicit-any
subjobs: Array<any>;
output: {
choices: Array<{
finish_reason: string;
index: number;
text: string;
}>;
raw_compute_time: number;
result_type: string;
};
}
/**
* Note that the modelPath is the only required parameter. For testing you
* can set this in the environment variable `LLAMA_PATH`.
*/
export interface TogetherAIInputs extends BaseLLMParams {
/**
* The API key to use for the TogetherAI API.
* @default {process.env.TOGETHER_AI_API_KEY}
*/
apiKey?: string;
/**
* The name of the model to query.
*/
modelName: string;
/**
* A decimal number that determines the degree of randomness in the response.
* A value of 1 will always yield the same output.
* A temperature less than 1 favors more correctness and is appropriate for question answering or summarization.
* A value greater than 1 introduces more randomness in the output.
* @default {0.7}
*/
temperature?: number;
/**
* Whether or not to stream tokens as they are generated.
* @default {false}
*/
streaming?: boolean;
/**
* The `topP` (nucleus) parameter is used to dynamically adjust the number of choices for each predicted token based on the cumulative probabilities.
* It specifies a probability threshold, below which all less likely tokens are filtered out.
* This technique helps to maintain diversity and generate more fluent and natural-sounding text.
* @default {0.7}
*/
topP?: number;
/**
* The `topK` parameter is used to limit the number of choices for the next predicted word or token.
* It specifies the maximum number of tokens to consider at each step, based on their probability of occurrence.
* This technique helps to speed up the generation process and can improve the quality of the generated text by focusing on the most likely options.
* @default {50}
*/
topK?: number;
/**
* A number that controls the diversity of generated text by reducing the likelihood of repeated sequences.
* Higher values decrease repetition.
* @default {1}
*/
repetitionPenalty?: number;
/**
* An integer that specifies how many top token log probabilities are included in the response for each token generation step.
*/
logprobs?: number;
/**
* Run an LLM-based input-output safeguard model on top of any model.
*/
safetyModel?: string;
/**
* Limit the number of tokens generated.
*/
maxTokens?: number;
/**
* A list of tokens at which the generation should stop.
*/
stop?: string[];
}
export interface TogetherAICallOptions
extends BaseLLMCallOptions,
Pick<
TogetherAIInputs,
| "modelName"
| "temperature"
| "topP"
| "topK"
| "repetitionPenalty"
| "logprobs"
| "safetyModel"
| "maxTokens"
| "stop"
> {}
export class TogetherAI extends LLM<TogetherAICallOptions> {
lc_serializable = true;
static inputs: TogetherAIInputs;
temperature = 0.7;
topP = 0.7;
topK = 50;
modelName: string;
streaming = false;
repetitionPenalty = 1;
logprobs?: number;
maxTokens?: number;
safetyModel?: string;
stop?: string[];
private apiKey: string;
private inferenceAPIUrl = "https://api.together.xyz/inference";
static lc_name() {
return "TogetherAI";
}
constructor(inputs: TogetherAIInputs) {
super(inputs);
const apiKey =
inputs.apiKey ?? getEnvironmentVariable("TOGETHER_AI_API_KEY");
if (!apiKey) {
throw new Error("TOGETHER_AI_API_KEY not found.");
}
this.apiKey = apiKey;
this.temperature = inputs?.temperature ?? this.temperature;
this.topK = inputs?.topK ?? this.topK;
this.topP = inputs?.topP ?? this.topP;
this.modelName = inputs.modelName;
this.streaming = inputs.streaming ?? this.streaming;
this.repetitionPenalty = inputs.repetitionPenalty ?? this.repetitionPenalty;
this.logprobs = inputs.logprobs;
this.safetyModel = inputs.safetyModel;
this.maxTokens = inputs.maxTokens;
this.stop = inputs.stop;
}
_llmType() {
return "together_ai";
}
private constructHeaders() {
return {
accept: "application/json",
"content-type": "application/json",
Authorization: `Bearer ${this.apiKey}`,
};
}
private constructBody(prompt: string, options?: this["ParsedCallOptions"]) {
const body = {
model: options?.modelName ?? this?.modelName,
prompt,
temperature: this?.temperature ?? options?.temperature,
top_k: this?.topK ?? options?.topK,
top_p: this?.topP ?? options?.topP,
repetition_penalty: this?.repetitionPenalty ?? options?.repetitionPenalty,
logprobs: this?.logprobs ?? options?.logprobs,
stream_tokens: this?.streaming,
safety_model: this?.safetyModel ?? options?.safetyModel,
max_tokens: this?.maxTokens ?? options?.maxTokens,
stop: this?.stop ?? options?.stop,
};
return body;
}
async completionWithRetry(
prompt: string,
options?: this["ParsedCallOptions"]
) {
return this.caller.call(async () => {
const fetchResponse = await fetch(this.inferenceAPIUrl, {
method: "POST",
headers: {
...this.constructHeaders(),
},
body: JSON.stringify(this.constructBody(prompt, options)),
});
if (fetchResponse.status === 200) {
return fetchResponse.json();
}
const errorResponse = await fetchResponse.json();
throw new Error(
`Error getting prompt completion from Together AI. ${JSON.stringify(
errorResponse,
null,
2
)}`
);
});
}
/** @ignore */
async _call(
prompt: string,
options?: this["ParsedCallOptions"]
): Promise<string> {
const response: TogetherAIInferenceResult = await this.completionWithRetry(
prompt,
options
);
const outputText = response.output.choices[0].text;
return outputText ?? "";
}
async *_streamResponseChunks(
prompt: string,
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): AsyncGenerator<GenerationChunk> {
const fetchResponse = await fetch(this.inferenceAPIUrl, {
method: "POST",
headers: {
...this.constructHeaders(),
},
body: JSON.stringify(this.constructBody(prompt, options)),
});
if (fetchResponse.status !== 200 ?? !fetchResponse.body) {
const errorResponse = await fetchResponse.json();
throw new Error(
`Error getting prompt completion from Together AI. ${JSON.stringify(
errorResponse,
null,
2
)}`
);
}
const stream = convertEventStreamToIterableReadableDataStream(
fetchResponse.body
);
for await (const chunk of stream) {
if (chunk !== "[DONE]") {
const parsedChunk = JSON.parse(chunk);
const generationChunk = new GenerationChunk({
text: parsedChunk.choices[0].text ?? "",
});
yield generationChunk;
// eslint-disable-next-line no-void
void runManager?.handleLLMNewToken(generationChunk.text ?? "");
}
}
}
}