test

examples/prompts/promptMixin.ts

@@ -1,5 +1,6 @@
 import {
   Document,
+  Prompt,
   ResponseSynthesizer,
   TreeSummarize,
   TreeSummarizePrompt,
@@ -7,16 +8,15 @@ import {
   serviceContextFromDefaults,
 } from "llamaindex";
 
-const treeSummarizePrompt: TreeSummarizePrompt = ({ context, query }) => {
-  return `Context information from multiple sources is below.
+const treeSummarizePrompt: TreeSummarizePrompt =
+  new Prompt(`Context information from multiple sources is below.
 ---------------------
-${context}
+{{context}}
 ---------------------
 Given the information from multiple sources and not prior knowledge.
 Answer the query in the style of a Shakespeare play"
-Query: ${query}
-Answer:`;
-};
+Query: {{query}}
+Answer:`);
 
 async function main() {
   const documents = new Document({

examples/readers/src/csv.ts

@@ -1,9 +1,10 @@
 import {
   CompactAndRefine,
   OpenAI,
+  Prompt,
   ResponseSynthesizer,
-  serviceContextFromDefaults,
   VectorStoreIndex,
+  serviceContextFromDefaults,
 } from "llamaindex";
 import { PapaCSVReader } from "llamaindex/readers";
 
@@ -22,14 +23,12 @@ async function main() {
     serviceContext,
   });
 
-  const csvPrompt = ({ context = "", query = "" }) => {
-    return `The following CSV file is loaded from ${path}
+  const csvPrompt = new Prompt(`The following CSV file is loaded from {{path}}
 \`\`\`csv
-${context}
+{{context}}
 \`\`\`
-Given the CSV file, generate me Typescript code to answer the question: ${query}. You can use built in NodeJS functions but avoid using third party libraries.
-`;
-  };
+Given the CSV file, generate me Typescript code to answer the question: {{query}. You can use built in NodeJS functions but avoid using third party libraries.
+`);
 
   const responseSynthesizer = new ResponseSynthesizer({
     responseBuilder: new CompactAndRefine(serviceContext, csvPrompt),

examples/vectorIndexAnthropic.ts

@@ -2,14 +2,16 @@ import fs from "node:fs/promises";
 
 import {
   Anthropic,
-  anthropicTextQaPrompt,
   CompactAndRefine,
   Document,
   ResponseSynthesizer,
-  serviceContextFromDefaults,
+  Settings,
   VectorStoreIndex,
+  serviceContextFromDefaults,
 } from "llamaindex";
 
+Settings.prompt.llm = "claude";
+
 async function main() {
   // Load essay from abramov.txt in Node
   const path = "node_modules/llamaindex/examples/abramov.txt";
@@ -23,10 +25,7 @@ async function main() {
   const serviceContext = serviceContextFromDefaults({ llm: new Anthropic() });
 
   const responseSynthesizer = new ResponseSynthesizer({
-    responseBuilder: new CompactAndRefine(
-      serviceContext,
-      anthropicTextQaPrompt,
-    ),
+    responseBuilder: new CompactAndRefine(serviceContext),
   });
 
   const index = await VectorStoreIndex.fromDocuments([document], {

packages/core/package.json

@@ -30,6 +30,7 @@
     "mammoth": "^1.6.0",
     "md-utils-ts": "^2.0.0",
     "mongodb": "^6.3.0",
+    "mustache": "^4.2.0",
     "notion-md-crawler": "^0.0.2",
     "openai": "^4.26.1",
     "papaparse": "^5.4.1",
@@ -41,12 +42,14 @@
     "rake-modified": "^1.0.8",
     "replicate": "^0.25.2",
     "string-strip-html": "^13.4.6",
+    "wikipedia": "^2.1.2",
     "wink-nlp": "^1.14.3",
-    "wikipedia": "^2.1.2"
+    "yaml": "^2.4.1"
   },
   "devDependencies": {
     "@swc/cli": "^0.3.9",
     "@swc/core": "^1.4.2",
+    "@types/mustache": "^4.2.5",
     "concurrently": "^8.2.2",
     "glob": "^10.3.10",
     "madge": "^6.1.0",

packages/core/src/ChatHistory.ts

@@ -96,7 +96,7 @@ export class SummaryChatHistory extends ChatHistory {
     do {
       promptMessages = [
         {
-          content: this.summaryPrompt({
+          content: this.summaryPrompt.format({
             context: messagesToHistoryStr(messagesToSummarize),
           }),
           role: "user" as MessageType,

packages/core/src/Prompt.ts

@@ -1,5 +1,8 @@
 import type { SubQuestion } from "./engines/query/types.js";
 import type { ChatMessage } from "./llm/types.js";
+
+import { Prompt } from "./prompts/types.js";
+
 import type { ToolMetadata } from "./types.js";
 
 /**
@@ -24,67 +27,42 @@ DEFAULT_TEXT_QA_PROMPT_TMPL = (
 )
 */
 
-export const defaultTextQaPrompt = ({ context = "", query = "" }) => {
-  return `Context information is below.
----------------------
-${context}
----------------------
-Given the context information and not prior knowledge, answer the query.
-Query: ${query}
-Answer:`;
-};
+export const defaultTextQaPrompt = new Prompt(`
+default: >
+  Context information is below.
+  ---------------------
+  {{context}}
+  ---------------------
+  Given the context information and not prior knowledge, answer the query.
+  Query: {{query}}
+  Answer:
+llm-claude: >
+  Context information:
+  <context>
+  {{context}}
+  </context>
+  Given the context information and not prior knowledge, answer the query.
+  Query: {{query}};
+`);
 
-export type TextQaPrompt = typeof defaultTextQaPrompt;
+export const defaultSummaryPrompt = new Prompt(`
+default: >  
+  Write a summary of the following. Try to use only the information provided. Try to include as many key details as possible.
 
-export const anthropicTextQaPrompt: TextQaPrompt = ({
-  context = "",
-  query = "",
-}) => {
-  return `Context information:
-<context>
-${context}
-</context>
-Given the context information and not prior knowledge, answer the query.
-Query: ${query}`;
-};
+  {{context}}
 
-/*
-DEFAULT_SUMMARY_PROMPT_TMPL = (
-    "Write a summary of the following. Try to use only the "
-    "information provided. "
-    "Try to include as many key details as possible.\n"
-    "\n"
-    "\n"
-    "{context_str}\n"
-    "\n"
-    "\n"
-    'SUMMARY:"""\n'
-)
-*/
+  SUMMARY:"""
+llm-claude: >
+  Summarize the following text. Try to use only the information provided. Try to include as many key details as possible.
+  <original-text>
+  {{context}}
+  </original-text>
 
-export const defaultSummaryPrompt = ({ context = "" }) => {
-  return `Write a summary of the following. Try to use only the information provided. Try to include as many key details as possible.
-
-
-${context}
-
-
-SUMMARY:"""
-`;
-};
+  SUMMARY:
+`);
 
 export type SummaryPrompt = typeof defaultSummaryPrompt;
 
-export const anthropicSummaryPrompt: SummaryPrompt = ({ context = "" }) => {
-  return `Summarize the following text. Try to use only the information provided. Try to include as many key details as possible.
-<original-text>
-${context}
-</original-text>
-
-SUMMARY:
-`;
-};
-
 /*
 DEFAULT_REFINE_PROMPT_TMPL = (
     "The original query is as follows: {query_str}\n"
@@ -101,20 +79,17 @@ DEFAULT_REFINE_PROMPT_TMPL = (
 )
 */
 
-export const defaultRefinePrompt = ({
-  query = "",
-  existingAnswer = "",
-  context = "",
-}) => {
-  return `The original query is as follows: ${query}
-We have provided an existing answer: ${existingAnswer}
-We have the opportunity to refine the existing answer (only if needed) with some more context below.
-------------
-${context}
-------------
-Given the new context, refine the original answer to better answer the query. If the context isn't useful, return the original answer.
-Refined Answer:`;
-};
+export const defaultRefinePrompt = new Prompt(`
+default: >
+  The original query is as follows: {{query}}
+  We have provided an existing answer: {{existingAnswer}}
+  We have the opportunity to refine the existing answer (only if needed) with some more context below.
+  ------------
+  {{context}}
+  ------------
+  Given the new context, refine the original answer to better answer the query. If the context isn't useful, return the original answer.
+  Refined Answer:
+`);
 
 export type RefinePrompt = typeof defaultRefinePrompt;
 
@@ -131,49 +106,51 @@ DEFAULT_TREE_SUMMARIZE_TMPL = (
 )
 */
 
-export const defaultTreeSummarizePrompt = ({ context = "", query = "" }) => {
-  return `Context information from multiple sources is below.
----------------------
-${context}
----------------------
-Given the information from multiple sources and not prior knowledge, answer the query.
-Query: ${query}
-Answer:`;
-};
+export const defaultTreeSummarizePrompt = new Prompt(`
+default: >
+  Context information from multiple sources is below.
+  ---------------------
+  {{context}}
+  ---------------------
+  Given the information from multiple sources and not prior knowledge, answer the query.
+  Query: {{query}}
+  Answer:
+`);
 
 export type TreeSummarizePrompt = typeof defaultTreeSummarizePrompt;
 
-export const defaultChoiceSelectPrompt = ({ context = "", query = "" }) => {
-  return `A list of documents is shown below. Each document has a number next to it along 
-with a summary of the document. A question is also provided.
-Respond with the numbers of the documents
-you should consult to answer the question, in order of relevance, as well
-as the relevance score. The relevance score is a number from 1-10 based on
-how relevant you think the document is to the question.
-Do not include any documents that are not relevant to the question.
-Example format:
-Document 1:
-<summary of document 1>
+export const defaultChoiceSelectPrompt = new Prompt(`
+default: >
+  A list of documents is shown below. Each document has a number next to it along 
+  with a summary of the document. A question is also provided.
+  Respond with the numbers of the documents
+  you should consult to answer the question, in order of relevance, as well
+  as the relevance score. The relevance score is a number from 1-10 based on
+  how relevant you think the document is to the question.
+  Do not include any documents that are not relevant to the question.
+  Example format:
+  Document 1:
+  <summary of document 1>
 
-Document 2:
-<summary of document 2>
+  Document 2:
+  <summary of document 2>
 
-...
+  ...
 
-Document 10:\n<summary of document 10>
+  Document 10:\n<summary of document 10>
 
-Question: <question>
-Answer:
-Doc: 9, Relevance: 7
-Doc: 3, Relevance: 4
-Doc: 7, Relevance: 3
+  Question: <question>
+  Answer:
+  Doc: 9, Relevance: 7
+  Doc: 3, Relevance: 4
+  Doc: 7, Relevance: 3
 
-Let's try this now:
+  Let's try this now:
 
-${context}
-Question: ${query}
-Answer:`;
-};
+  {{context}}
+  Question: {{query}}
+  Answer:
+`);
 
 export type ChoiceSelectPrompt = typeof defaultChoiceSelectPrompt;
 

packages/core/src/PromptHelper.ts

@@ -1,5 +1,4 @@
 import { globalsHelper } from "./GlobalsHelper.js";
-import type { SimplePrompt } from "./Prompt.js";
 import { SentenceSplitter } from "./TextSplitter.js";
 import {
   DEFAULT_CHUNK_OVERLAP_RATIO,
@@ -8,8 +7,18 @@ import {
   DEFAULT_PADDING,
 } from "./constants.js";
 
-export function getEmptyPromptTxt(prompt: SimplePrompt) {
-  return prompt({});
+import { Prompt } from "./prompts/types.js";
+
+import { messagesToPrompt } from "./prompts/utils.js";
+
+export function getEmptyPromptTxt(prompt: Prompt) {
+  const emptyPrompt = prompt.format({});
+
+  if (Array.isArray(emptyPrompt)) {
+    return messagesToPrompt(emptyPrompt);
+  }
+
+  return emptyPrompt;
 }
 
 /**
@@ -18,7 +27,7 @@ export function getEmptyPromptTxt(prompt: SimplePrompt) {
  * @param prompts
  * @returns
  */
-export function getBiggestPrompt(prompts: SimplePrompt[]) {
+export function getBiggestPrompt(prompts: Prompt[]) {
   const emptyPromptTexts = prompts.map(getEmptyPromptTxt);
   const emptyPromptLengths = emptyPromptTexts.map((text) => text.length);
   const maxEmptyPromptLength = Math.max(...emptyPromptLengths);
@@ -59,7 +68,7 @@ export class PromptHelper {
    * @param prompt
    * @returns
    */
-  private getAvailableContextSize(prompt: SimplePrompt) {
+  private getAvailableContextSize(prompt: Prompt) {
     const emptyPromptText = getEmptyPromptTxt(prompt);
     const promptTokens = this.tokenizer(emptyPromptText);
     const numPromptTokens = promptTokens.length;
@@ -74,11 +83,7 @@ export class PromptHelper {
    * @param padding
    * @returns
    */
-  private getAvailableChunkSize(
-    prompt: SimplePrompt,
-    numChunks = 1,
-    padding = 5,
-  ) {
+  private getAvailableChunkSize(prompt: Prompt, numChunks = 1, padding = 5) {
     const availableContextSize = this.getAvailableContextSize(prompt);
 
     const result = Math.floor(availableContextSize / numChunks) - padding;
@@ -98,7 +103,7 @@ export class PromptHelper {
    * @returns
    */
   getTextSplitterGivenPrompt(
-    prompt: SimplePrompt,
+    prompt: Prompt,
     numChunks = 1,
     padding = DEFAULT_PADDING,
   ) {
@@ -118,11 +123,7 @@ export class PromptHelper {
    * @param padding
    * @returns
    */
-  repack(
-    prompt: SimplePrompt,
-    textChunks: string[],
-    padding = DEFAULT_PADDING,
-  ) {
+  repack(prompt: Prompt, textChunks: string[], padding = DEFAULT_PADDING) {
     const textSplitter = this.getTextSplitterGivenPrompt(prompt, 1, padding);
     const combinedStr = textChunks.join("\n\n");
     return textSplitter.splitText(combinedStr);

packages/core/src/Settings.ts

@@ -0,0 +1,27 @@
+type PromptConfig = {
+  llm?: string;
+  lang?: string;
+};
+
+interface Config {
+  prompt: PromptConfig;
+}
+
+// Determine the global object based on the environment
+const globalObject: any =
+  typeof window !== "undefined"
+    ? window
+    : typeof global !== "undefined"
+      ? global
+      : {};
+
+// Initialize or access a global config object
+const globalConfigKey = "__GLOBAL_LITS__";
+
+if (!globalObject[globalConfigKey]) {
+  globalObject[globalConfigKey] = {
+    prompt: {},
+  } satisfies Config;
+}
+
+export const Settings: Config = globalObject[globalConfigKey];

packages/core/src/evaluation/Correctness.ts

@@ -68,11 +68,11 @@ export class CorrectnessEvaluator extends PromptMixin implements BaseEvaluator {
     const messages: ChatMessage[] = [
       {
         role: "system",
-        content: this.correctnessPrompt(),
+        content: this.correctnessPrompt.format({}),
       },
       {
         role: "user",
-        content: defaultUserPrompt({
+        content: defaultUserPrompt.format({
           query,
           generatedAnswer: response,
           referenceAnswer: reference || "(NO REFERENCE ANSWER SUPPLIED)",

packages/core/src/evaluation/prompts.ts

@@ -1,155 +1,130 @@
-export const defaultUserPrompt = ({
-  query,
-  referenceAnswer,
-  generatedAnswer,
-}: {
-  query: string;
-  referenceAnswer: string;
-  generatedAnswer: string;
-}) => `
-## User Query
-${query}
+import { Prompt } from "./../prompts/types.js";
 
-## Reference Answer
-${referenceAnswer}
+export const defaultUserPrompt = new Prompt(`
+default: >
+  ## User Query
+  {{query}}
 
-## Generated Answer
-${generatedAnswer}
-`;
+  ## Reference Answer
+  {{referenceAnswer}}
+
+  ## Generated Answer
+  {{generatedAnswer}}
+`);
 
 export type UserPrompt = typeof defaultUserPrompt;
 
-export const defaultCorrectnessSystemPrompt =
-  () => `You are an expert evaluation system for a question answering chatbot.
+export const defaultCorrectnessSystemPrompt = new Prompt(`
+default: >  
+  You are an expert evaluation system for a question answering chatbot.
 
-You are given the following information:
-- a user query, and
-- a generated answer
+  You are given the following information:
+  - a user query, and
+  - a generated answer
 
-You may also be given a reference answer to use for reference in your evaluation.
+  You may also be given a reference answer to use for reference in your evaluation.
 
-Your job is to judge the relevance and correctness of the generated answer.
-Output a single score that represents a holistic evaluation.
-You must return your response in a line with only the score.
-Do not return answers in any other format.
-On a separate line provide your reasoning for the score as well.
+  Your job is to judge the relevance and correctness of the generated answer.
+  Output a single score that represents a holistic evaluation.
+  You must return your response in a line with only the score.
+  Do not return answers in any other format.
+  On a separate line provide your reasoning for the score as well.
 
-Follow these guidelines for scoring:
-- Your score has to be between 1 and 5, where 1 is the worst and 5 is the best.
-- If the generated answer is not relevant to the user query,
-you should give a score of 1.
-- If the generated answer is relevant but contains mistakes,
-you should give a score between 2 and 3.
-- If the generated answer is relevant and fully correct,
-you should give a score between 4 and 5.
+  Follow these guidelines for scoring:
+  - Your score has to be between 1 and 5, where 1 is the worst and 5 is the best.
+  - If the generated answer is not relevant to the user query,
+  you should give a score of 1.
+  - If the generated answer is relevant but contains mistakes,
+  you should give a score between 2 and 3.
+  - If the generated answer is relevant and fully correct,
+  you should give a score between 4 and 5.
 
-Example Response:
-4.0
-The generated answer has the exact same metrics as the reference answer
-but it is not as concise.
-`;
+  Example Response:
+  4.0
+  The generated answer has the exact same metrics as the reference answer
+  but it is not as concise.
+`);
 
 export type CorrectnessSystemPrompt = typeof defaultCorrectnessSystemPrompt;
 
-export const defaultFaithfulnessRefinePrompt = ({
-  query,
-  context,
-  existingAnswer,
-}: {
-  query: string;
-  context: string;
-  existingAnswer: string;
-}) => `
-We want to understand if the following information is present
-in the context information: ${query}
-We have provided an existing YES/NO answer: ${existingAnswer}
-We have the opportunity to refine the existing answer
-(only if needed) with some more context below.
-------------
-${context}
-------------
-If the existing answer was already YES, still answer YES.
-If the information is present in the new context, answer YES.
-Otherwise answer NO.
-`;
+export const defaultFaithfulnessRefinePrompt = new Prompt(`
+default: >
+  We want to understand if the following information is present
+  in the context information: {{query}}
+  We have provided an existing YES/NO answer: {{existingAnswer}}
+  We have the opportunity to refine the existing answer
+  (only if needed) with some more context below.
+  ------------
+  {{context}}
+  ------------
+  If the existing answer was already YES, still answer YES.
+  If the information is present in the new context, answer YES.
+  Otherwise answer NO.
+`);
 
 export type FaithfulnessRefinePrompt = typeof defaultFaithfulnessRefinePrompt;
 
-export const defaultFaithfulnessTextQaPrompt = ({
-  query,
-  context,
-}: {
-  query: string;
-  context: string;
-}) => `
-Please tell if a given piece of information
-is supported by the context.
-You need to answer with either YES or NO.
-Answer YES if any of the context supports the information, even
-if most of the context is unrelated.
-Some examples are provided below.
+export const defaultFaithfulnessTextQaPrompt = new Prompt(`
+default: >
+  Please tell if a given piece of information
+  is supported by the context.
+  You need to answer with either YES or NO.
+  Answer YES if any of the context supports the information, even
+  if most of the context is unrelated.
+  Some examples are provided below.
 
-Information: Apple pie is generally double-crusted.
-Context: An apple pie is a fruit pie in which the principal filling
-ingredient is apples.
-Apple pie is often served with whipped cream, ice cream
-('apple pie à la mode'), custard or cheddar cheese.
-It is generally double-crusted, with pastry both above
-and below the filling; the upper crust may be solid or
-latticed (woven of crosswise strips).
-Answer: YES
-Information: Apple pies tastes bad.
-Context: An apple pie is a fruit pie in which the principal filling
-ingredient is apples.
-Apple pie is often served with whipped cream, ice cream
-('apple pie à la mode'), custard or cheddar cheese.
-It is generally double-crusted, with pastry both above
-and below the filling; the upper crust may be solid or
-latticed (woven of crosswise strips).
-Answer: NO
-Information: ${query}
-Context: ${context}
-Answer:
-`;
+  Information: Apple pie is generally double-crusted.
+  Context: An apple pie is a fruit pie in which the principal filling
+  ingredient is apples.
+  Apple pie is often served with whipped cream, ice cream
+  ('apple pie à la mode'), custard or cheddar cheese.
+  It is generally double-crusted, with pastry both above
+  and below the filling; the upper crust may be solid or
+  latticed (woven of crosswise strips).
+  Answer: YES
+  Information: Apple pies tastes bad.
+  Context: An apple pie is a fruit pie in which the principal filling
+  ingredient is apples.
+  Apple pie is often served with whipped cream, ice cream
+  ('apple pie à la mode'), custard or cheddar cheese.
+  It is generally double-crusted, with pastry both above
+  and below the filling; the upper crust may be solid or
+  latticed (woven of crosswise strips).
+  Answer: NO
+  Information: {{query}}
+  Context: {{context}}
+  Answer:
+`);
 
 export type FaithfulnessTextQAPrompt = typeof defaultFaithfulnessTextQaPrompt;
 
-export const defaultRelevancyEvalPrompt = ({
-  query,
-  context,
-}: {
-  query: string;
-  context: string;
-}) => `Your task is to evaluate if the response for the query is in line with the context information provided.
-You have two options to answer. Either YES/ NO.
-Answer - YES, if the response for the query is in line with context information otherwise NO.
-Query and Response: ${query}
-Context: ${context}
-Answer: `;
+export const defaultRelevancyEvalPrompt = new Prompt(`
+default: >
+  Your task is to evaluate if the response for the query is in line with the context information provided.
+  You have two options to answer. Either YES/ NO.
+  Answer - YES, if the response for the query is in line with context information otherwise NO.
+  Query and Response: {{query}}
+  Context: {{context}}
+  Answer: 
+`);
 
 export type RelevancyEvalPrompt = typeof defaultRelevancyEvalPrompt;
 
-export const defaultRelevancyRefinePrompt = ({
-  query,
-  existingAnswer,
-  contextMsg,
-}: {
-  query: string;
-  existingAnswer: string;
-  contextMsg: string;
-}) => `We want to understand if the following query and response is
-in line with the context information: 
-${query}
-We have provided an existing YES/NO answer: 
-${existingAnswer}
-We have the opportunity to refine the existing answer
-(only if needed) with some more context below.
-------------
-${contextMsg}
-------------
-If the existing answer was already YES, still answer YES.
-If the information is present in the new context, answer YES.
-Otherwise answer NO.
-`;
+export const defaultRelevancyRefinePrompt = new Prompt(`
+default: >  
+  We want to understand if the following query and response is
+  in line with the context information: 
+  {{query}}
+  We have provided an existing YES/NO answer: 
+  {{existingAnswer}}
+  We have the opportunity to refine the existing answer
+  (only if needed) with some more context below.
+  ------------
+  {{contextMsg}}
+  ------------
+  If the existing answer was already YES, still answer YES.
+  If the information is present in the new context, answer YES.
+  Otherwise answer NO.
+`);
 
 export type RelevancyRefinePrompt = typeof defaultRelevancyRefinePrompt;

packages/core/src/index.edge.ts

@@ -8,6 +8,7 @@ export * from "./QuestionGenerator.js";
 export * from "./Response.js";
 export * from "./Retriever.js";
 export * from "./ServiceContext.js";
+export * from "./Settings.js";
 export * from "./TextSplitter.js";
 export * from "./agent/index.js";
 export * from "./callbacks/CallbackManager.js";

packages/core/src/indices/summary/index.ts

@@ -354,7 +354,7 @@ export class SummaryIndexLLMRetriever implements BaseRetriever {
       const input = { context: fmtBatchStr, query: query };
       const rawResponse = (
         await this.serviceContext.llm.complete({
-          prompt: this.choiceSelectPrompt(input),
+          prompt: this.choiceSelectPrompt.format(input),
         })
       ).text;
 

packages/core/src/llm/base.ts

@@ -10,11 +10,75 @@ import type {
   LLMCompletionParamsStreaming,
   LLMMetadata,
 } from "./types.js";
+
 import { streamConverter } from "./utils.js";
 
 export abstract class BaseLLM implements LLM {
   abstract metadata: LLMMetadata;
 
+  predict(
+    params: LLMCompletionParamsStreaming,
+  ): Promise<AsyncIterable<CompletionResponse>>;
+  predict(params: LLMCompletionParamsNonStreaming): Promise<CompletionResponse>;
+  async predict(
+    params: LLMCompletionParamsStreaming | LLMCompletionParamsNonStreaming,
+  ): Promise<CompletionResponse | AsyncIterable<CompletionResponse>> {
+    const { prompt, parentEvent, stream } = params;
+
+    if (Array.isArray(prompt)) {
+      if (stream) {
+        const stream = await this.chat({
+          messages: prompt,
+          parentEvent,
+          stream: true,
+        });
+        return streamConverter(stream, (chunk) => {
+          return {
+            text: chunk.delta,
+          };
+        });
+      }
+
+      const chatResponse = await this.chat({
+        messages: prompt,
+        parentEvent,
+      });
+      return { text: chatResponse.message.content as string };
+    }
+
+    if (typeof prompt === "string") {
+      if (stream) {
+        const stream = await this.complete({
+          prompt,
+          parentEvent,
+          stream: true,
+        });
+
+        return stream;
+      }
+
+      return this.complete({
+        prompt,
+        parentEvent,
+      });
+    }
+
+    if (stream) {
+      const stream = await this.complete({
+        prompt,
+        parentEvent,
+        stream: true,
+      });
+
+      return stream;
+    }
+
+    return this.complete({
+      prompt,
+      parentEvent,
+    });
+  }
+
   complete(
     params: LLMCompletionParamsStreaming,
   ): Promise<AsyncIterable<CompletionResponse>>;

packages/core/src/llm/ollama.ts

@@ -64,6 +64,16 @@ export class Ollama extends BaseEmbedding implements LLM {
     };
   }
 
+  predict(
+    params: LLMCompletionParamsStreaming,
+  ): Promise<AsyncIterable<CompletionResponse>>;
+  predict(params: LLMCompletionParamsNonStreaming): Promise<CompletionResponse>;
+  predict(
+    params: unknown,
+  ): Promise<AsyncIterable<CompletionResponse>> | Promise<CompletionResponse> {
+    throw new Error("Method not implemented.");
+  }
+
   chat(
     params: LLMChatParamsStreaming,
   ): Promise<AsyncIterable<ChatResponseChunk>>;

packages/core/src/llm/types.ts

@@ -6,6 +6,15 @@ import type { Event } from "../callbacks/CallbackManager.js";
  */
 export interface LLM {
   metadata: LLMMetadata;
+  /**
+   * Predict the next completion from the LLM
+   * *
+   * @param params
+   */
+  predict(
+    params: LLMCompletionParamsStreaming,
+  ): Promise<AsyncIterable<CompletionResponse>>;
+  predict(params: LLMCompletionParamsNonStreaming): Promise<CompletionResponse>;
   /**
    * Get a chat response from the LLM
    *

packages/core/src/prompts/index.ts

@@ -1 +1,3 @@
 export * from "./Mixin.js";
+export * from "./types.js";
+export * from "./utils.js";

packages/core/src/prompts/types.ts

@@ -0,0 +1,104 @@
+import type { ChatMessage } from "../llm/types.js";
+
+import { Settings } from "../Settings.js";
+
+import mustache from "mustache";
+
+import * as yaml from "yaml";
+
+interface Env {
+  llm?: string;
+  lang?: string;
+}
+
+type Inputs = Record<string, string>;
+
+type FunctionResult = string | ChatMessage[];
+
+interface ParsedTemplate {
+  [key: string]: any;
+}
+
+export class Prompt {
+  template: string;
+
+  constructor(template: string) {
+    this.template = template;
+  }
+
+  format(inputs: Inputs, env?: Env): FunctionResult {
+    const parsedTemplate: ParsedTemplate = yaml.parse(this.template);
+
+    let templateSection = null;
+    let defaultSection = null;
+
+    // Determine the language and LLM settings to use, either from the environment or the global settings.
+    const envLang = env?.lang || Settings?.prompt?.lang;
+    const envLlm = env?.llm || Settings?.prompt?.llm;
+
+    // Regular expressions for matching language and LLM keys, including defaults.
+    const langRegex = new RegExp(`^lang-(${envLang}|default)$`, "i");
+    const llmRegex = new RegExp(`^llm-(${envLlm}|default)$`, "i");
+
+    // First, look for language matches or language defaults.
+    Object.entries(parsedTemplate).forEach(([key, value]) => {
+      if (langRegex.test(key)) {
+        templateSection = value; // Select the matching language section or a default language section.
+
+        // Then, within the selected language section, look for LLM matches or LLM defaults.
+        if (templateSection && typeof templateSection === "object") {
+          Object.entries(templateSection).forEach(
+            ([nestedKey, nestedValue]) => {
+              if (llmRegex.test(nestedKey)) {
+                templateSection = nestedValue; // Further refine to LLM section if available, including defaults.
+              } else if (/^default$/.test(nestedKey)) {
+                templateSection = nestedValue;
+              }
+            },
+          );
+        }
+      } else if (llmRegex.test(key)) {
+        templateSection = value;
+      } else if (/^default$/.test(key)) {
+        // Keep track of a root-level default to use if no other matches are found.
+        defaultSection = value;
+      }
+    });
+
+    // If no specific matches were found, use the root-level default section if available.
+    if (!templateSection && defaultSection) {
+      templateSection = defaultSection;
+    } else if (!templateSection && !defaultSection) {
+      // If no matches were found, set a single prompt
+      templateSection = parsedTemplate;
+    }
+
+    // Process the selected template section for message rendering or other logic.
+    if (templateSection && templateSection["messages"]) {
+      const result: ChatMessage[] = [];
+      for (const message of templateSection["messages"] as ChatMessage[]) {
+        result.push({
+          content: mustache.render(message.content, inputs),
+          role: message.role,
+        });
+      }
+      return result;
+    } else if (typeof templateSection === "string") {
+      const renderedResult = mustache.render(templateSection, inputs);
+      return renderedResult;
+    } else {
+      throw new Error("Invalid template section");
+    }
+  }
+
+  partial(inputs: Record<string, string>): Prompt {
+    const template = mustache.render(this.template, inputs);
+    return new Prompt(template);
+  }
+
+  toJSON(): Record<string, any> {
+    return {
+      template: this.template,
+    };
+  }
+}

packages/core/src/prompts/utils.ts

@@ -0,0 +1,19 @@
+import type { ChatMessage } from "../llm/types.js";
+
+export const messagesToPrompt = (messages: ChatMessage[]): string => {
+  const stringMessages = [];
+  for (const message of messages) {
+    const role = message.role;
+    const content = message.content;
+    let stringMessage = `${role}: ${content}`;
+
+    const additionalKwargs = message.additionalKwargs;
+    if (additionalKwargs) {
+      stringMessage += `\n${additionalKwargs}`;
+    }
+    stringMessages.push(stringMessage);
+  }
+
+  stringMessages.push(`assistant: `);
+  return stringMessages.join("\n");
+};

packages/core/src/synthesizers/MultiModalResponseSynthesizer.ts

@@ -6,8 +6,11 @@ import { serviceContextFromDefaults } from "../ServiceContext.js";
 import { imageToDataUrl } from "../embeddings/index.js";
 import type { MessageContentDetail } from "../llm/types.js";
 import { PromptMixin } from "../prompts/Mixin.js";
-import type { TextQaPrompt } from "./../Prompt.js";
+
 import { defaultTextQaPrompt } from "./../Prompt.js";
+
+import { Prompt } from "./../prompts/types.js";
+
 import type {
   BaseSynthesizer,
   SynthesizeParamsNonStreaming,
@@ -20,7 +23,7 @@ export class MultiModalResponseSynthesizer
 {
   serviceContext: ServiceContext;
   metadataMode: MetadataMode;
-  textQATemplate: TextQaPrompt;
+  textQATemplate: Prompt;
 
   constructor({
     serviceContext,
@@ -34,15 +37,13 @@ export class MultiModalResponseSynthesizer
     this.textQATemplate = textQATemplate ?? defaultTextQaPrompt;
   }
 
-  protected _getPrompts(): { textQATemplate: TextQaPrompt } {
+  protected _getPrompts(): { textQATemplate: Prompt } {
     return {
       textQATemplate: this.textQATemplate,
     };
   }
 
-  protected _updatePrompts(promptsDict: {
-    textQATemplate: TextQaPrompt;
-  }): void {
+  protected _updatePrompts(promptsDict: { textQATemplate: Prompt }): void {
     if (promptsDict.textQATemplate) {
       this.textQATemplate = promptsDict.textQATemplate;
     }
@@ -70,7 +71,9 @@ export class MultiModalResponseSynthesizer
     );
     // TODO: use builders to generate context
     const context = textChunks.join("\n\n");
-    const textPrompt = this.textQATemplate({ context, query });
+
+    const textQaPrompt = this.textQATemplate.format({ context, query });
+
     const images = await Promise.all(
       imageNodes.map(async (node: ImageNode) => {
         return {
@@ -81,11 +84,17 @@ export class MultiModalResponseSynthesizer
         } as MessageContentDetail;
       }),
     );
+
+    // TODO: handle chat message prompt
+    if (Array.isArray(textQaPrompt)) {
+      throw new Error("textQaPrompt must be a string");
+    }
+
     const prompt: MessageContentDetail[] = [
-      { type: "text", text: textPrompt },
+      { type: "text", text: textQaPrompt },
       ...images,
     ];
-    const response = await this.serviceContext.llm.complete({
+    const response = await this.serviceContext.llm.predict({
       prompt,
       parentEvent,
     });

packages/core/src/synthesizers/builders.ts

@@ -1,12 +1,6 @@
 import type { Event } from "../callbacks/CallbackManager.js";
-import type { LLM } from "../llm/index.js";
+import type { ChatMessage, LLM } from "../llm/index.js";
 import { streamConverter } from "../llm/utils.js";
-import type {
-  RefinePrompt,
-  SimplePrompt,
-  TextQaPrompt,
-  TreeSummarizePrompt,
-} from "../Prompt.js";
 import {
   defaultRefinePrompt,
   defaultTextQaPrompt,
@@ -22,6 +16,8 @@ import type {
   ResponseBuilderParamsStreaming,
 } from "./types.js";
 
+import { Prompt } from "../prompts/types.js";
+
 /**
  * Response modes of the response synthesizer
  */
@@ -37,9 +33,9 @@ enum ResponseMode {
  */
 export class SimpleResponseBuilder implements ResponseBuilder {
   llm: LLM;
-  textQATemplate: TextQaPrompt;
+  textQATemplate: Prompt;
 
-  constructor(serviceContext: ServiceContext, textQATemplate?: TextQaPrompt) {
+  constructor(serviceContext: ServiceContext, textQATemplate?: Prompt) {
     this.llm = serviceContext.llm;
     this.textQATemplate = textQATemplate ?? defaultTextQaPrompt;
   }
@@ -63,7 +59,8 @@ export class SimpleResponseBuilder implements ResponseBuilder {
       context: textChunks.join("\n\n"),
     };
 
-    const prompt = this.textQATemplate(input);
+    const prompt = this.textQATemplate.format(input);
+
     if (stream) {
       const response = await this.llm.complete({ prompt, parentEvent, stream });
       return streamConverter(response, (chunk) => chunk.text);
@@ -80,13 +77,13 @@ export class SimpleResponseBuilder implements ResponseBuilder {
 export class Refine extends PromptMixin implements ResponseBuilder {
   llm: LLM;
   promptHelper: PromptHelper;
-  textQATemplate: TextQaPrompt;
-  refineTemplate: RefinePrompt;
+  textQATemplate: Prompt;
+  refineTemplate: Prompt;
 
   constructor(
     serviceContext: ServiceContext,
-    textQATemplate?: TextQaPrompt,
-    refineTemplate?: RefinePrompt,
+    textQATemplate?: Prompt,
+    refineTemplate?: Prompt,
   ) {
     super();
 
@@ -97,8 +94,8 @@ export class Refine extends PromptMixin implements ResponseBuilder {
   }
 
   protected _getPrompts(): {
-    textQATemplate: RefinePrompt;
-    refineTemplate: RefinePrompt;
+    textQATemplate: Prompt;
+    refineTemplate: Prompt;
   } {
     return {
       textQATemplate: this.textQATemplate,
@@ -107,8 +104,8 @@ export class Refine extends PromptMixin implements ResponseBuilder {
   }
 
   protected _updatePrompts(prompts: {
-    textQATemplate: RefinePrompt;
-    refineTemplate: RefinePrompt;
+    textQATemplate: Prompt;
+    refineTemplate: Prompt;
   }): void {
     if (prompts.textQATemplate) {
       this.textQATemplate = prompts.textQATemplate;
@@ -166,19 +163,21 @@ export class Refine extends PromptMixin implements ResponseBuilder {
     stream: boolean,
     parentEvent?: Event,
   ) {
-    const textQATemplate: SimplePrompt = (input) =>
-      this.textQATemplate({ ...input, query: queryStr });
-    const textChunks = this.promptHelper.repack(textQATemplate, [textChunk]);
+    const textChunks = this.promptHelper.repack(this.textQATemplate, [
+      textChunk,
+    ]);
 
     let response: AsyncIterable<string> | string | undefined = undefined;
 
     for (let i = 0; i < textChunks.length; i++) {
       const chunk = textChunks[i];
       const lastChunk = i === textChunks.length - 1;
+
       if (!response) {
         response = await this.complete({
-          prompt: textQATemplate({
+          prompt: this.textQATemplate.format({
             context: chunk,
+            query: queryStr,
           }),
           parentEvent,
           stream: stream && lastChunk,
@@ -205,20 +204,21 @@ export class Refine extends PromptMixin implements ResponseBuilder {
     stream: boolean,
     parentEvent?: Event,
   ) {
-    const refineTemplate: SimplePrompt = (input) =>
-      this.refineTemplate({ ...input, query: queryStr });
-
-    const textChunks = this.promptHelper.repack(refineTemplate, [textChunk]);
+    const textChunks = this.promptHelper.repack(this.refineTemplate, [
+      textChunk,
+    ]);
 
     let response: AsyncIterable<string> | string = initialReponse;
 
     for (let i = 0; i < textChunks.length; i++) {
       const chunk = textChunks[i];
       const lastChunk = i === textChunks.length - 1;
+
       response = await this.complete({
-        prompt: refineTemplate({
+        prompt: this.refineTemplate.format({
           context: chunk,
           existingAnswer: response as string,
+          query: queryStr,
         }),
         parentEvent,
         stream: stream && lastChunk,
@@ -228,15 +228,15 @@ export class Refine extends PromptMixin implements ResponseBuilder {
   }
 
   async complete(params: {
-    prompt: string;
+    prompt: string | ChatMessage[];
     stream: boolean;
     parentEvent?: Event;
   }): Promise<AsyncIterable<string> | string> {
     if (params.stream) {
-      const response = await this.llm.complete({ ...params, stream: true });
+      const response = await this.llm.predict({ ...params, stream: true });
       return streamConverter(response, (chunk) => chunk.text);
     } else {
-      const response = await this.llm.complete({ ...params, stream: false });
+      const response = await this.llm.predict({ ...params, stream: false });
       return response.text;
     }
   }
@@ -261,12 +261,10 @@ export class CompactAndRefine extends Refine {
     | ResponseBuilderParamsNonStreaming): Promise<
     AsyncIterable<string> | string
   > {
-    const textQATemplate: SimplePrompt = (input) =>
-      this.textQATemplate({ ...input, query: query });
-    const refineTemplate: SimplePrompt = (input) =>
-      this.refineTemplate({ ...input, query: query });
-
-    const maxPrompt = getBiggestPrompt([textQATemplate, refineTemplate]);
+    const maxPrompt = getBiggestPrompt([
+      this.textQATemplate,
+      this.refineTemplate,
+    ]);
     const newTexts = this.promptHelper.repack(maxPrompt, textChunks);
     const params = {
       query,
@@ -290,12 +288,9 @@ export class CompactAndRefine extends Refine {
 export class TreeSummarize extends PromptMixin implements ResponseBuilder {
   llm: LLM;
   promptHelper: PromptHelper;
-  summaryTemplate: TreeSummarizePrompt;
+  summaryTemplate: Prompt;
 
-  constructor(
-    serviceContext: ServiceContext,
-    summaryTemplate?: TreeSummarizePrompt,
-  ) {
+  constructor(serviceContext: ServiceContext, summaryTemplate?: Prompt) {
     super();
 
     this.llm = serviceContext.llm;
@@ -303,15 +298,13 @@ export class TreeSummarize extends PromptMixin implements ResponseBuilder {
     this.summaryTemplate = summaryTemplate ?? defaultTreeSummarizePrompt;
   }
 
-  protected _getPrompts(): { summaryTemplate: TreeSummarizePrompt } {
+  protected _getPrompts(): { summaryTemplate: Prompt } {
     return {
       summaryTemplate: this.summaryTemplate,
     };
   }
 
-  protected _updatePrompts(prompts: {
-    summaryTemplate: TreeSummarizePrompt;
-  }): void {
+  protected _updatePrompts(prompts: { summaryTemplate: Prompt }): void {
     if (prompts.summaryTemplate) {
       this.summaryTemplate = prompts.summaryTemplate;
     }
@@ -342,11 +335,13 @@ export class TreeSummarize extends PromptMixin implements ResponseBuilder {
     );
 
     if (packedTextChunks.length === 1) {
+      const prompt = this.summaryTemplate.partial({
+        context: packedTextChunks[0],
+        query,
+      });
+
       const params = {
-        prompt: this.summaryTemplate({
-          context: packedTextChunks[0],
-          query,
-        }),
+        prompt,
         parentEvent,
       };
       if (stream) {
@@ -356,21 +351,20 @@ export class TreeSummarize extends PromptMixin implements ResponseBuilder {
       return (await this.llm.complete(params)).text;
     } else {
       const summaries = await Promise.all(
-        packedTextChunks.map((chunk) =>
-          this.llm.complete({
-            prompt: this.summaryTemplate({
-              context: chunk,
-              query,
-            }),
-            parentEvent,
-          }),
-        ),
+        packedTextChunks.map((chunk) => {
+          const prompt = this.summaryTemplate.partial({
+            context: chunk,
+            query,
+          });
+          return this.llm.complete({ prompt, parentEvent });
+        }),
       );
 
       const params = {
         query,
         textChunks: summaries.map((s) => s.text),
       };
+
       if (stream) {
         return this.getResponse({
           ...params,
@@ -398,7 +392,4 @@ export function getResponseBuilder(
   }
 }
 
-export type ResponseBuilderPrompts =
-  | TextQaPrompt
-  | TreeSummarizePrompt
-  | RefinePrompt;
+export type ResponseBuilderPrompts = Prompt | Prompt;

packages/core/src/test.ts

@@ -0,0 +1,36 @@
+import { Settings, SimpleDirectoryReader, VectorStoreIndex } from "./index.js";
+
+// Update llm and prompt
+Settings.prompt.llm = "claude";
+
+// Update lang
+Settings.prompt.lang = "en";
+
+async function main() {
+  const documents = await new SimpleDirectoryReader().loadData({
+    directoryPath: "../examples",
+  });
+
+  const index = await VectorStoreIndex.fromDocuments(documents);
+
+  const retriever = await index.asRetriever({});
+
+  retriever.similarityTopK = 10;
+
+  const queryEngine = index.asQueryEngine({
+    retriever,
+  });
+
+  // Query the engine
+  const query = "Tell me about abramov";
+
+  const response = await queryEngine.query({
+    query,
+  });
+
+  console.log({
+    response,
+  });
+}
+
+main();

packages/core/tests/package.json

@@ -4,7 +4,7 @@
   "version": "0.0.2",
   "type": "module",
   "scripts": {
-    "test": "vitest run"
+    "test": "vitest run --silent=false"
   },
   "devDependencies": {
     "llamaindex": "workspace:*",

packages/core/tests/prompts/Prompt.test.ts

@@ -0,0 +1,77 @@
+import { describe, expect, it } from "vitest";
+
+import { Prompt } from "llamaindex/prompts/types";
+
+describe("Prompt", () => {
+  it("should format messages prompt", () => {
+    const prompt = new Prompt(`
+      messages:
+        - content:  hello, {{name}}
+          role: user
+    `);
+    const result = prompt.format({ name: "world" });
+    expect(result).toEqual([{ content: "hello, world", role: "user" }]);
+  });
+
+  it("should format single prompt", () => {
+    const prompt = new Prompt("hello, {{name}}");
+    const result = prompt.format({ name: "world" });
+    expect(result).toEqual("hello, world");
+  });
+
+  it("should format a prompt with a language section", () => {
+    const prompt = new Prompt(
+      "lang-en:\n  messages:\n    - content: 'hello, {{name}}'\n      role: user",
+    );
+    const result = prompt.format({ name: "world" }, { lang: "en" });
+    expect(result).toEqual([{ content: "hello, world", role: "user" }]);
+  });
+
+  it("should format a prompt with a language section and LLM section", () => {
+    const prompt = new Prompt(`
+      lang-en:
+        llm-gpt3:
+          messages:
+            - content: 'hello, {{name}}'
+              role: user
+    `);
+    const result = prompt.format(
+      { name: "world" },
+      { lang: "en", llm: "gpt3" },
+    );
+    expect(result).toEqual([{ content: "hello, world", role: "user" }]);
+  });
+
+  it("should format a prompt with a default language section and LLM section", () => {
+    const prompt = new Prompt(`
+      lang-default:
+        llm-gpt3:
+          messages:
+            - content: hello, {{name}}
+              role: user
+    `);
+    const result = prompt.format({ name: "world" }, { llm: "gpt3" });
+    expect(result).toEqual([{ content: "hello, world", role: "user" }]);
+  });
+
+  it("should format a prompt with a default language section and default LLM section", () => {
+    const prompt = new Prompt(`
+      lang-default:
+        llm-default:
+          messages:
+            - content: hello, {{name}}
+              role: user
+    `);
+    const result = prompt.format({ name: "world" });
+    expect(result).toEqual([{ content: "hello, world", role: "user" }]);
+  });
+
+  it("should format a default prompt", () => {
+    const prompt = new Prompt(`
+      default:
+        hello, {{name}}
+    `);
+    const result = prompt.format({ name: "world" });
+    expect(result).toEqual("hello, world");
+  });
+});

packages/edge/package.json

@@ -29,6 +29,7 @@
     "mammoth": "^1.6.0",
     "md-utils-ts": "^2.0.0",
     "mongodb": "^6.3.0",
+    "mustache": "^4.2.0",
     "notion-md-crawler": "^0.0.2",
     "openai": "^4.26.1",
     "papaparse": "^5.4.1",
@@ -40,8 +41,9 @@
     "rake-modified": "^1.0.8",
     "replicate": "^0.25.2",
     "string-strip-html": "^13.4.6",
+    "wikipedia": "^2.1.2",
     "wink-nlp": "^1.14.3",
-    "wikipedia": "^2.1.2"
+    "yaml": "^2.4.1"
   },
   "engines": {
     "node": ">=18.0.0"

pnpm-lock.yaml

@@ -243,6 +243,9 @@ importers:
       mongodb:
         specifier: ^6.3.0
         version: 6.3.0
+      mustache:
+        specifier: ^4.2.0
+        version: 4.2.0
       notion-md-crawler:
         specifier: ^0.0.2
         version: 0.0.2
@@ -282,6 +285,9 @@ importers:
       wink-nlp:
         specifier: ^1.14.3
         version: 1.14.3
+      yaml:
+        specifier: ^2.4.1
+        version: 2.4.1
     devDependencies:
       '@swc/cli':
         specifier: ^0.3.9
@@ -289,6 +295,9 @@ importers:
       '@swc/core':
         specifier: ^1.4.2
         version: 1.4.2
+      '@types/mustache':
+        specifier: ^4.2.5
+        version: 4.2.5
       concurrently:
         specifier: ^8.2.2
         version: 8.2.2
@@ -388,6 +397,9 @@ importers:
       mongodb:
         specifier: ^6.3.0
         version: 6.3.0
+      mustache:
+        specifier: ^4.2.0
+        version: 4.2.0
       notion-md-crawler:
         specifier: ^0.0.2
         version: 0.0.2
@@ -427,6 +439,9 @@ importers:
       wink-nlp:
         specifier: ^1.14.3
         version: 1.14.3
+      yaml:
+        specifier: ^2.4.1
+        version: 2.4.1
 
   packages/edge/e2e/test-edge-runtime:
     dependencies:
@@ -2419,7 +2434,7 @@ packages:
       '@docusaurus/react-loadable': 5.5.2(react@18.2.0)
       '@docusaurus/types': 3.1.1(react-dom@18.2.0)(react@18.2.0)
       '@types/history': 4.7.11
-      '@types/react': 18.2.65
+      '@types/react': 18.2.66
       '@types/react-router-config': 5.0.11
       '@types/react-router-dom': 5.3.3
       react: 18.2.0
@@ -4574,6 +4589,10 @@ packages:
   /@types/ms@0.7.34:
     resolution: {integrity: sha512-nG96G3Wp6acyAgJqGasjODb+acrI7KltPiRxzHPXnP3NgI28bpQDRv53olbqGXbfcgF5aiiHmO3xpwEpS5Ld9g==}
 
+  /@types/mustache@4.2.5:
+    resolution: {integrity: sha512-PLwiVvTBg59tGFL/8VpcGvqOu3L4OuveNvPi0EYbWchRdEVP++yRUXJPFl+CApKEq13017/4Nf7aQ5lTtHUNsA==}
+    dev: true
+
   /@types/node-fetch@2.6.11:
     resolution: {integrity: sha512-24xFj9R5+rfQJLRyM56qh+wnVSYhyXC2tkoBndtY0U+vubqNsYXGjufB2nn8Q6gt0LrARwL6UBtMCSVCwl4B1g==}
     dependencies:
@@ -4668,7 +4687,7 @@ packages:
     resolution: {integrity: sha512-WmSAg7WgqW7m4x8Mt4N6ZyKz0BubSj/2tVUMsAHp+Yd2AMwcSbeFq9WympT19p5heCFmF97R9eD5uUR/t4HEqw==}
     dependencies:
       '@types/history': 4.7.11
-      '@types/react': 18.2.65
+      '@types/react': 18.2.66
       '@types/react-router': 5.1.20
     dev: true
 
@@ -4692,7 +4711,7 @@ packages:
     resolution: {integrity: sha512-jGjmu/ZqS7FjSH6owMcD5qpq19+1RS9DeVRqfl1FeBMxTDQAGwlMWOcs52NDoXaNKyG3d1cYQFMs9rCrb88o9Q==}
     dependencies:
       '@types/history': 4.7.11
-      '@types/react': 18.2.65
+      '@types/react': 18.2.66
     dev: true
 
   /@types/react@18.2.48:
@@ -11080,6 +11099,11 @@ packages:
       dns-packet: 5.6.1
       thunky: 1.1.0
 
+  /mustache@4.2.0:
+    resolution: {integrity: sha512-71ippSywq5Yb7/tVYyGbkBggbU8H3u5Rz56fH60jGFgr8uHwxs+aSKeqmluIVzM0m0kB7xQjKS6qPfd0b2ZoqQ==}
+    hasBin: true
+    dev: false
+
   /mz@2.7.0:
     resolution: {integrity: sha512-z81GNO7nnYMEhrGh9LeymoE4+Yr0Wn5McHIZMK5cfQCl+NDX08sCZgUc9/6MHni9IWuFLm1Z3HTCXu2z9fN62Q==}
     dependencies:
@@ -15836,6 +15860,12 @@ packages:
     engines: {node: '>= 14'}
     dev: true
 
+  /yaml@2.4.1:
+    resolution: {integrity: sha512-pIXzoImaqmfOrL7teGUBt/T7ZDnyeGBWyXQBvOVhLkWLN37GXv8NMLK406UY6dS51JfcQHsmcW5cJ441bHg6Lg==}
+    engines: {node: '>= 14'}
+    hasBin: true
+    dev: false
+
   /yargs-parser@18.1.3:
     resolution: {integrity: sha512-o50j0JeToy/4K6OZcaQmW6lyXXKhq7csREXcDwk2omFPJEwUNOVtJKvmDr9EI1fAJZUyZcRF7kxGBWmRXudrCQ==}
     engines: {node: '>=6'}