173 lines
8.0 KiB
JavaScript
173 lines
8.0 KiB
JavaScript
import { ChatWrapper } from "../ChatWrapper.js";
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import { SpecialToken, LlamaText, SpecialTokensText } from "../utils/LlamaText.js";
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import { ChatModelFunctionsDocumentationGenerator } from "./utils/ChatModelFunctionsDocumentationGenerator.js";
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// source: https://github.com/meta-llama/llama-recipes/blob/79aa70442e97c3127e53c2d22c54438c32adcf5e/README.md
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// source: https://llama.meta.com/docs/model-cards-and-prompt-formats/meta-llama-3/
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export class Llama3ChatWrapper extends ChatWrapper {
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wrapperName = "Llama 3";
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settings;
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constructor({ parallelFunctionCalling = true } = {}) {
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super();
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if (parallelFunctionCalling)
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this.settings = {
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supportsSystemMessages: true,
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functions: {
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call: {
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optionalPrefixSpace: true,
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prefix: "||call: ",
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paramsPrefix: LlamaText(new SpecialTokensText("(")),
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suffix: LlamaText(new SpecialTokensText(")"))
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},
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result: {
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prefix: LlamaText(new SpecialTokensText("<|start_header_id|>function_call_result<|end_header_id|>\n\n")),
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suffix: LlamaText(new SpecialTokensText("<|eot_id|>"))
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},
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parallelism: {
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call: {
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sectionPrefix: "",
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betweenCalls: "\n",
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sectionSuffix: LlamaText(new SpecialTokensText("<|eot_id|>"))
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},
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result: {
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sectionPrefix: "",
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betweenResults: "",
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sectionSuffix: LlamaText(new SpecialTokensText("<|start_header_id|>assistant<|end_header_id|>\n\n"))
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}
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}
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}
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};
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else
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this.settings = {
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supportsSystemMessages: true,
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functions: {
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call: {
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optionalPrefixSpace: true,
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prefix: "||call: ",
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paramsPrefix: LlamaText(new SpecialTokensText("(")),
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suffix: LlamaText(new SpecialTokensText(")"))
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},
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result: {
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prefix: LlamaText([
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LlamaText(new SpecialTokensText("<|eot_id|>")),
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new SpecialTokensText("<|start_header_id|>function_call_result<|end_header_id|>\n\n")
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]),
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suffix: LlamaText([
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new SpecialTokensText("<|eot_id|>"),
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new SpecialTokensText("<|start_header_id|>assistant<|end_header_id|>\n\n")
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])
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}
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}
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};
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}
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generateContextState({ chatHistory, availableFunctions, documentFunctionParams }) {
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const historyWithFunctions = this.addAvailableFunctionsSystemMessageToHistory(chatHistory, availableFunctions, {
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documentParams: documentFunctionParams
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});
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const resultItems = [];
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let systemTexts = [];
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let userTexts = [];
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let modelTexts = [];
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let currentAggregateFocus = null;
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function flush() {
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if (systemTexts.length > 0 || userTexts.length > 0 || modelTexts.length > 0)
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resultItems.push({
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system: systemTexts.length === 0
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? null
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: LlamaText.joinValues("\n\n", systemTexts),
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user: userTexts.length === 0
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? null
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: LlamaText.joinValues("\n\n", userTexts),
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model: modelTexts.length === 0
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? null
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: LlamaText.joinValues("\n\n", modelTexts)
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});
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systemTexts = [];
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userTexts = [];
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modelTexts = [];
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}
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for (const item of historyWithFunctions) {
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if (item.type === "system") {
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if (currentAggregateFocus !== "system")
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flush();
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currentAggregateFocus = "system";
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systemTexts.push(LlamaText.fromJSON(item.text));
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}
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else if (item.type === "user") {
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if (currentAggregateFocus !== "user")
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flush();
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currentAggregateFocus = "user";
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userTexts.push(LlamaText(item.text));
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}
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else if (item.type === "model") {
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if (currentAggregateFocus !== "model")
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flush();
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currentAggregateFocus = "model";
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modelTexts.push(this.generateModelResponseText(item.response));
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}
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else
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void item;
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}
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flush();
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const contextText = LlamaText(new SpecialToken("BOS"), resultItems.map((item, index) => {
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const isLastItem = index === resultItems.length - 1;
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const res = [];
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if (item.system != null) {
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res.push(LlamaText([
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new SpecialTokensText("<|start_header_id|>system<|end_header_id|>\n\n"),
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item.system,
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new SpecialTokensText("<|eot_id|>")
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]));
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}
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if (item.user != null) {
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res.push(LlamaText([
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new SpecialTokensText("<|start_header_id|>user<|end_header_id|>\n\n"),
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item.user,
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new SpecialTokensText("<|eot_id|>")
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]));
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}
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if (item.model != null) {
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res.push(LlamaText([
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new SpecialTokensText("<|start_header_id|>assistant<|end_header_id|>\n\n"),
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item.model,
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isLastItem
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? LlamaText([])
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: new SpecialTokensText("<|eot_id|>")
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]));
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}
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return LlamaText(res);
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}));
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return {
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contextText,
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stopGenerationTriggers: [
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LlamaText(new SpecialToken("EOS")),
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LlamaText(new SpecialToken("EOT")),
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LlamaText(new SpecialTokensText("<|eot_id|>")),
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LlamaText(new SpecialTokensText("<|end_of_text|>")),
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LlamaText("<|eot_id|>"),
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LlamaText("<|end_of_text|>")
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]
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};
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}
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generateAvailableFunctionsSystemText(availableFunctions, { documentParams = true }) {
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const functionsDocumentationGenerator = new ChatModelFunctionsDocumentationGenerator(availableFunctions);
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if (!functionsDocumentationGenerator.hasAnyFunctions)
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return LlamaText([]);
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return LlamaText.joinValues("\n", [
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"The assistant calls the provided functions as needed to retrieve information instead of relying on existing knowledge.",
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"To fulfill a request, the assistant calls relevant functions in advance when needed before responding to the request, and does not tell the user prior to calling a function.",
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"Provided functions:",
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"```typescript",
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functionsDocumentationGenerator.getTypeScriptFunctionSignatures({ documentParams }),
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"```",
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"",
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"Calling any of the provided functions can be done like this:",
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this.generateFunctionCall("getSomeInfo", { someKey: "someValue" }),
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"",
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"Note that the || prefix is mandatory.",
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"The assistant does not inform the user about using functions and does not explain anything before calling a function.",
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"After calling a function, the raw result appears afterwards and is not part of the conversation.",
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"To make information be part of the conversation, the assistant paraphrases and repeats the information without the function syntax."
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]);
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}
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}
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//# sourceMappingURL=Llama3ChatWrapper.js.map
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