feat: align response-synthesizers & chat-engine module (#1169)

This commit is contained in:
Alex Yang
2024-09-17 15:44:44 -07:00
committed by GitHub
parent 72440c101f
commit 2cd1383dc8
47 changed files with 692 additions and 1006 deletions
+13
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@@ -0,0 +1,13 @@
---
"@llamaindex/core": patch
"@llamaindex/experimental": patch
"llamaindex": patch
---
refactor: align `response-synthesizers` & `chat-engine` module
- builtin event system
- correct class extends
- aligin APIs, naming with llama-index python
- move stream out of first parameter to second parameter for the better tyep checking
- remove JSONQueryEngine in `@llamaindex/experimental`, as the code quality is not satisify and we will bring it back later
+6 -4
View File
@@ -27,10 +27,12 @@ async function main() {
// Query the index
const queryEngine = index.asQueryEngine();
const stream = await queryEngine.query({
query: "What did the author do in college?",
stream: true,
});
const stream = await queryEngine.query(
{
query: "What did the author do in college?",
},
true,
);
// Output response
for await (const chunk of stream) {
+6 -4
View File
@@ -37,10 +37,12 @@ async function main() {
// Query the index
const queryEngine = index.asQueryEngine();
const stream = await queryEngine.query({
query: "What did the author do in college?",
stream: true,
});
const stream = await queryEngine.query(
{
query: "What did the author do in college?",
},
true,
);
// Output response
for await (const chunk of stream) {
+3 -3
View File
@@ -1,7 +1,7 @@
import {
Document,
getResponseSynthesizer,
NodeWithScore,
ResponseSynthesizer,
SentenceSplitter,
TextNode,
} from "llamaindex";
@@ -14,7 +14,7 @@ import {
console.log(nodes);
const responseSynthesizer = new ResponseSynthesizer();
const responseSynthesizer = getResponseSynthesizer("compact");
const nodesWithScore: NodeWithScore[] = [
{
@@ -30,7 +30,7 @@ import {
const stream = await responseSynthesizer.synthesize(
{
query: "What age am I?",
nodesWithScore,
nodes: nodesWithScore,
},
true,
);
+8 -6
View File
@@ -1,5 +1,5 @@
import {
MultiModalResponseSynthesizer,
getResponseSynthesizer,
OpenAI,
Settings,
VectorStoreIndex,
@@ -27,13 +27,15 @@ async function main() {
});
const queryEngine = index.asQueryEngine({
responseSynthesizer: new MultiModalResponseSynthesizer(),
responseSynthesizer: getResponseSynthesizer("multi_modal"),
retriever: index.asRetriever({ topK: { TEXT: 3, IMAGE: 1 } }),
});
const stream = await queryEngine.query({
query: "Tell me more about Vincent van Gogh's famous paintings",
stream: true,
});
const stream = await queryEngine.query(
{
query: "Tell me more about Vincent van Gogh's famous paintings",
},
true,
);
for await (const chunk of stream) {
process.stdout.write(chunk.response);
}
+2 -5
View File
@@ -1,8 +1,7 @@
import {
Document,
getResponseSynthesizer,
PromptTemplate,
ResponseSynthesizer,
TreeSummarize,
TreeSummarizePrompt,
VectorStoreIndex,
} from "llamaindex";
@@ -27,9 +26,7 @@ async function main() {
const query = "The quick brown fox jumps over the lazy dog";
const responseSynthesizer = new ResponseSynthesizer({
responseBuilder: new TreeSummarize(),
});
const responseSynthesizer = getResponseSynthesizer("tree_summarize");
const queryEngine = index.asQueryEngine({
responseSynthesizer,
+3 -4
View File
@@ -1,8 +1,7 @@
import {
CompactAndRefine,
getResponseSynthesizer,
OpenAI,
PromptTemplate,
ResponseSynthesizer,
Settings,
VectorStoreIndex,
} from "llamaindex";
@@ -29,8 +28,8 @@ Given the CSV file, generate me Typescript code to answer the question: {query}.
`,
});
const responseSynthesizer = new ResponseSynthesizer({
responseBuilder: new CompactAndRefine(undefined, csvPrompt),
const responseSynthesizer = getResponseSynthesizer("compact", {
textQATemplate: csvPrompt,
});
const queryEngine = index.asQueryEngine({ responseSynthesizer });
+1 -1
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@@ -1,3 +1,4 @@
import { createMessageContent } from "@llamaindex/core/utils";
import {
Document,
ImageNode,
@@ -6,7 +7,6 @@ import {
PromptTemplate,
VectorStoreIndex,
} from "llamaindex";
import { createMessageContent } from "llamaindex/synthesizers/utils";
const reader = new LlamaParseReader();
async function main() {
+2 -6
View File
@@ -2,12 +2,10 @@ import fs from "node:fs/promises";
import {
Anthropic,
CompactAndRefine,
Document,
ResponseSynthesizer,
Settings,
VectorStoreIndex,
anthropicTextQaPrompt,
getResponseSynthesizer,
} from "llamaindex";
// Update llm to use Anthropic
@@ -23,9 +21,7 @@ async function main() {
const document = new Document({ text: essay, id_: path });
// Split text and create embeddings. Store them in a VectorStoreIndex
const responseSynthesizer = new ResponseSynthesizer({
responseBuilder: new CompactAndRefine(undefined, anthropicTextQaPrompt),
});
const responseSynthesizer = getResponseSynthesizer("compact");
const index = await VectorStoreIndex.fromDocuments([document]);
+2 -6
View File
@@ -1,11 +1,10 @@
import {
getResponseSynthesizer,
OpenAI,
OpenAIEmbedding,
ResponseSynthesizer,
RetrieverQueryEngine,
Settings,
TextNode,
TreeSummarize,
VectorIndexRetriever,
VectorStore,
VectorStoreIndex,
@@ -165,10 +164,7 @@ async function main() {
similarityTopK: 500,
});
const responseSynthesizer = new ResponseSynthesizer({
responseBuilder: new TreeSummarize(),
});
const responseSynthesizer = getResponseSynthesizer("tree_summarize");
return new RetrieverQueryEngine(retriever, responseSynthesizer, {
filter,
});
+15
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@@ -185,6 +185,20 @@
"types": "./dist/storage/chat-store/index.d.ts",
"default": "./dist/storage/chat-store/index.js"
}
},
"./response-synthesizers": {
"require": {
"types": "./dist/response-synthesizers/index.d.cts",
"default": "./dist/response-synthesizers/index.cjs"
},
"import": {
"types": "./dist/response-synthesizers/index.d.ts",
"default": "./dist/response-synthesizers/index.js"
},
"default": {
"types": "./dist/response-synthesizers/index.d.ts",
"default": "./dist/response-synthesizers/index.js"
}
}
},
"files": [
@@ -210,6 +224,7 @@
"dependencies": {
"@llamaindex/env": "workspace:*",
"@types/node": "^22.5.1",
"magic-bytes.js": "^1.10.0",
"zod": "^3.23.8"
}
}
@@ -6,8 +6,13 @@ import type {
ToolCall,
ToolOutput,
} from "../../llms";
import type { QueryEndEvent, QueryStartEvent } from "../../query-engine";
import type {
SynthesizeEndEvent,
SynthesizeStartEvent,
} from "../../response-synthesizers";
import { TextNode } from "../../schema";
import { EventCaller, getEventCaller } from "../../utils/event-caller";
import { EventCaller, getEventCaller } from "../../utils";
import type { UUID } from "../type";
export type LLMStartEvent = {
@@ -60,6 +65,10 @@ export interface LlamaIndexEventMaps {
"chunking-end": ChunkingEndEvent;
"node-parsing-start": NodeParsingStartEvent;
"node-parsing-end": NodeParsingEndEvent;
"query-start": QueryStartEvent;
"query-end": QueryEndEvent;
"synthesize-start": SynthesizeStartEvent;
"synthesize-end": SynthesizeEndEvent;
}
export class LlamaIndexCustomEvent<T = any> extends CustomEvent<T> {
@@ -1,10 +1,13 @@
import { type Tokenizer, tokenizers } from "@llamaindex/env";
import {
DEFAULT_CHUNK_OVERLAP_RATIO,
DEFAULT_CHUNK_SIZE,
DEFAULT_CONTEXT_WINDOW,
DEFAULT_NUM_OUTPUTS,
DEFAULT_PADDING,
Settings,
} from "../global";
import type { LLMMetadata } from "../llms";
import { SentenceSplitter } from "../node-parser";
import type { PromptTemplate } from "../prompts";
@@ -133,4 +136,29 @@ export class PromptHelper {
const combinedStr = textChunks.join("\n\n");
return textSplitter.splitText(combinedStr);
}
static fromLLMMetadata(
metadata: LLMMetadata,
options?: {
chunkOverlapRatio?: number;
chunkSizeLimit?: number;
tokenizer?: Tokenizer;
separator?: string;
},
) {
const {
chunkOverlapRatio = DEFAULT_CHUNK_OVERLAP_RATIO,
chunkSizeLimit = DEFAULT_CHUNK_SIZE,
tokenizer = Settings.tokenizer,
separator = " ",
} = options ?? {};
return new PromptHelper({
contextWindow: metadata.contextWindow,
numOutput: metadata.maxTokens ?? DEFAULT_NUM_OUTPUTS,
chunkOverlapRatio,
chunkSizeLimit,
tokenizer,
separator,
});
}
}
+32 -7
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@@ -1,5 +1,9 @@
import { randomUUID } from "@llamaindex/env";
import { Settings } from "../global";
import type { MessageContent } from "../llms";
import { EngineResponse, type NodeWithScore } from "../schema";
import { PromptMixin } from "../prompts";
import { EngineResponse } from "../schema";
import { wrapEventCaller } from "../utils";
/**
* @link https://docs.llamaindex.ai/en/stable/api_reference/schema/?h=querybundle#llama_index.core.schema.QueryBundle
@@ -14,16 +18,37 @@ export type QueryBundle = {
export type QueryType = string | QueryBundle;
export interface BaseQueryEngine {
export type QueryFn = (
strOrQueryBundle: QueryType,
stream?: boolean,
) => Promise<AsyncIterable<EngineResponse> | EngineResponse>;
export abstract class BaseQueryEngine extends PromptMixin {
protected constructor(protected readonly _query: QueryFn) {
super();
}
query(
strOrQueryBundle: QueryType,
stream: true,
): Promise<AsyncIterable<EngineResponse>>;
query(strOrQueryBundle: QueryType, stream?: false): Promise<EngineResponse>;
synthesize?(
@wrapEventCaller
async query(
strOrQueryBundle: QueryType,
nodes: NodeWithScore[],
additionalSources?: Iterator<NodeWithScore>,
): Promise<EngineResponse>;
stream = false,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const id = randomUUID();
const callbackManager = Settings.callbackManager;
callbackManager.dispatchEvent("query-start", {
id,
query: strOrQueryBundle,
});
const response = await this._query(strOrQueryBundle, stream);
callbackManager.dispatchEvent("query-end", {
id,
response,
});
return response;
}
}
+2 -1
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@@ -1 +1,2 @@
export type { BaseQueryEngine, QueryBundle, QueryType } from "./base";
export { BaseQueryEngine, type QueryBundle, type QueryType } from "./base";
export type { QueryEndEvent, QueryStartEvent } from "./type";
+12
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@@ -0,0 +1,12 @@
import { EngineResponse } from "../schema";
import type { QueryType } from "./base";
export type QueryStartEvent = {
id: string;
query: QueryType;
};
export type QueryEndEvent = {
id: string;
response: EngineResponse | AsyncIterable<EngineResponse>;
};
@@ -0,0 +1,58 @@
import { randomUUID } from "@llamaindex/env";
import { Settings } from "../global";
import { PromptHelper } from "../indices";
import type { LLM, MessageContent } from "../llms";
import { PromptMixin } from "../prompts";
import { EngineResponse, type NodeWithScore } from "../schema";
import type { SynthesizeQuery } from "./type";
export type BaseSynthesizerOptions = {
llm?: LLM;
promptHelper?: PromptHelper;
};
export abstract class BaseSynthesizer extends PromptMixin {
llm: LLM;
promptHelper: PromptHelper;
protected constructor(options: Partial<BaseSynthesizerOptions>) {
super();
this.llm = options.llm ?? Settings.llm;
this.promptHelper =
options.promptHelper ?? PromptHelper.fromLLMMetadata(this.llm.metadata);
}
protected abstract getResponse(
query: MessageContent,
textChunks: NodeWithScore[],
stream: boolean,
): Promise<EngineResponse | AsyncIterable<EngineResponse>>;
synthesize(
query: SynthesizeQuery,
stream: true,
): Promise<AsyncIterable<EngineResponse>>;
synthesize(query: SynthesizeQuery, stream?: false): Promise<EngineResponse>;
async synthesize(
query: SynthesizeQuery,
stream = false,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const callbackManager = Settings.callbackManager;
const id = randomUUID();
callbackManager.dispatchEvent("synthesize-start", { id, query });
let response: EngineResponse | AsyncIterable<EngineResponse>;
if (query.nodes.length === 0) {
if (stream) {
response = EngineResponse.fromResponse("Empty Response", true);
} else {
response = EngineResponse.fromResponse("Empty Response", false);
}
} else {
const queryMessage: MessageContent =
typeof query.query === "string" ? query.query : query.query.query;
response = await this.getResponse(queryMessage, query.nodes, stream);
}
callbackManager.dispatchEvent("synthesize-end", { id, query, response });
return response;
}
}
@@ -1,108 +1,52 @@
import { getBiggestPrompt, type PromptHelper } from "@llamaindex/core/indices";
import type { LLM } from "@llamaindex/core/llms";
import { z } from "zod";
import { getBiggestPrompt } from "../indices";
import type { MessageContent } from "../llms";
import {
PromptMixin,
defaultRefinePrompt,
defaultTextQAPrompt,
defaultTreeSummarizePrompt,
type ModuleRecord,
type PromptsRecord,
type RefinePrompt,
type TextQAPrompt,
type TreeSummarizePrompt,
} from "@llamaindex/core/prompts";
import type { QueryType } from "@llamaindex/core/query-engine";
import { extractText, streamConverter } from "@llamaindex/core/utils";
import type { ServiceContext } from "../ServiceContext.js";
} from "../prompts";
import {
llmFromSettingsOrContext,
promptHelperFromSettingsOrContext,
} from "../Settings.js";
import type { ResponseBuilder, ResponseBuilderQuery } from "./types.js";
EngineResponse,
MetadataMode,
type NodeWithScore,
TextNode,
} from "../schema";
import { createMessageContent, extractText, streamConverter } from "../utils";
import {
BaseSynthesizer,
type BaseSynthesizerOptions,
} from "./base-synthesizer";
/**
* Response modes of the response synthesizer
*/
enum ResponseMode {
REFINE = "refine",
COMPACT = "compact",
TREE_SUMMARIZE = "tree_summarize",
SIMPLE = "simple",
}
const responseModeSchema = z.enum([
"refine",
"compact",
"tree_summarize",
"multi_modal",
]);
/**
* A response builder that just concatenates responses.
*/
export class SimpleResponseBuilder
extends PromptMixin
implements ResponseBuilder
{
llm: LLM;
textQATemplate: TextQAPrompt;
constructor(serviceContext?: ServiceContext, textQATemplate?: TextQAPrompt) {
super();
this.llm = llmFromSettingsOrContext(serviceContext);
this.textQATemplate = textQATemplate ?? defaultTextQAPrompt;
}
protected _getPrompts(): PromptsRecord {
return {
textQATemplate: this.textQATemplate,
};
}
protected _updatePrompts(prompts: { textQATemplate: TextQAPrompt }): void {
if (prompts.textQATemplate) {
this.textQATemplate = prompts.textQATemplate;
}
}
protected _getPromptModules(): ModuleRecord {
return {};
}
getResponse(
query: ResponseBuilderQuery,
stream: true,
): Promise<AsyncIterable<string>>;
getResponse(query: ResponseBuilderQuery, stream?: false): Promise<string>;
async getResponse(
{ query, textChunks }: ResponseBuilderQuery,
stream?: boolean,
): Promise<AsyncIterable<string> | string> {
const prompt = this.textQATemplate.format({
query: extractText(query),
context: textChunks.join("\n\n"),
});
if (stream) {
const response = await this.llm.complete({ prompt, stream: true });
return streamConverter(response, (chunk) => chunk.text);
} else {
const response = await this.llm.complete({ prompt, stream: false });
return response.text;
}
}
}
export type ResponseMode = z.infer<typeof responseModeSchema>;
/**
* A response builder that uses the query to ask the LLM generate a better response using multiple text chunks.
*/
export class Refine extends PromptMixin implements ResponseBuilder {
llm: LLM;
promptHelper: PromptHelper;
class Refine extends BaseSynthesizer {
textQATemplate: TextQAPrompt;
refineTemplate: RefinePrompt;
constructor(
serviceContext?: ServiceContext,
textQATemplate?: TextQAPrompt,
refineTemplate?: RefinePrompt,
options: BaseSynthesizerOptions & {
textQATemplate?: TextQAPrompt | undefined;
refineTemplate?: RefinePrompt | undefined;
},
) {
super();
this.llm = llmFromSettingsOrContext(serviceContext);
this.promptHelper = promptHelperFromSettingsOrContext(serviceContext);
this.textQATemplate = textQATemplate ?? defaultTextQAPrompt;
this.refineTemplate = refineTemplate ?? defaultRefinePrompt;
super(options);
this.textQATemplate = options.textQATemplate ?? defaultTextQAPrompt;
this.refineTemplate = options.refineTemplate ?? defaultRefinePrompt;
}
protected _getPromptModules(): ModuleRecord {
@@ -132,41 +76,47 @@ export class Refine extends PromptMixin implements ResponseBuilder {
}
}
getResponse(
query: ResponseBuilderQuery,
stream: true,
): Promise<AsyncIterable<string>>;
getResponse(query: ResponseBuilderQuery, stream?: false): Promise<string>;
async getResponse(
{ query, textChunks, prevResponse }: ResponseBuilderQuery,
stream?: boolean,
): Promise<AsyncIterable<string> | string> {
let response: AsyncIterable<string> | string | undefined = prevResponse;
query: MessageContent,
nodes: NodeWithScore[],
stream: boolean,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
let response: AsyncIterable<string> | string | undefined = undefined;
const textChunks = nodes.map(({ node }) =>
node.getContent(MetadataMode.LLM),
);
for (let i = 0; i < textChunks.length; i++) {
const chunk = textChunks[i]!;
const text = textChunks[i]!;
const lastChunk = i === textChunks.length - 1;
if (!response) {
response = await this.giveResponseSingle(
query,
chunk,
text,
!!stream && lastChunk,
);
} else {
response = await this.refineResponseSingle(
response as string,
query,
chunk,
text,
!!stream && lastChunk,
);
}
}
return response ?? "Empty Response";
// fixme: no source nodes provided, cannot fix right now due to lack of context
if (typeof response === "string") {
return EngineResponse.fromResponse(response, false);
} else {
return streamConverter(response!, (text) =>
EngineResponse.fromResponse(text, true),
);
}
}
private async giveResponseSingle(
query: QueryType,
query: MessageContent,
textChunk: string,
stream: boolean,
): Promise<AsyncIterable<string> | string> {
@@ -203,10 +153,10 @@ export class Refine extends PromptMixin implements ResponseBuilder {
// eslint-disable-next-line max-params
private async refineResponseSingle(
initialReponse: string,
query: QueryType,
query: MessageContent,
textChunk: string,
stream: boolean,
) {
): Promise<AsyncIterable<string> | string> {
const refineTemplate: RefinePrompt = this.refineTemplate.partialFormat({
query: extractText(query),
});
@@ -246,59 +196,54 @@ export class Refine extends PromptMixin implements ResponseBuilder {
/**
* CompactAndRefine is a slight variation of Refine that first compacts the text chunks into the smallest possible number of chunks.
*/
export class CompactAndRefine extends Refine {
getResponse(
query: ResponseBuilderQuery,
stream: true,
): Promise<AsyncIterable<string>>;
getResponse(query: ResponseBuilderQuery, stream?: false): Promise<string>;
class CompactAndRefine extends Refine {
async getResponse(
{ query, textChunks, prevResponse }: ResponseBuilderQuery,
stream?: boolean,
): Promise<AsyncIterable<string> | string> {
query: MessageContent,
nodes: NodeWithScore[],
stream: boolean,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const textQATemplate: TextQAPrompt = this.textQATemplate.partialFormat({
query: extractText(query),
});
const refineTemplate: RefinePrompt = this.refineTemplate.partialFormat({
query: extractText(query),
});
const textChunks = nodes.map(({ node }) =>
node.getContent(MetadataMode.LLM),
);
const maxPrompt = getBiggestPrompt([textQATemplate, refineTemplate]);
const newTexts = this.promptHelper.repack(maxPrompt, textChunks);
const params = {
query,
textChunks: newTexts,
prevResponse,
};
const newNodes = newTexts.map((text) => new TextNode({ text }));
if (stream) {
return super.getResponse(
{
...params,
},
query,
newNodes.map((node) => ({ node })),
true,
);
}
return super.getResponse(params);
return super.getResponse(
query,
newNodes.map((node) => ({ node })),
false,
);
}
}
/**
* TreeSummarize repacks the text chunks into the smallest possible number of chunks and then summarizes them, then recursively does so until there's one chunk left.
*/
export class TreeSummarize extends PromptMixin implements ResponseBuilder {
llm: LLM;
promptHelper: PromptHelper;
class TreeSummarize extends BaseSynthesizer {
summaryTemplate: TreeSummarizePrompt;
constructor(
serviceContext?: ServiceContext,
summaryTemplate?: TreeSummarizePrompt,
options: BaseSynthesizerOptions & {
summaryTemplate?: TreeSummarizePrompt;
},
) {
super();
this.llm = llmFromSettingsOrContext(serviceContext);
this.promptHelper = promptHelperFromSettingsOrContext(serviceContext);
this.summaryTemplate = summaryTemplate ?? defaultTreeSummarizePrompt;
super(options);
this.summaryTemplate =
options.summaryTemplate ?? defaultTreeSummarizePrompt;
}
protected _getPromptModules(): ModuleRecord {
@@ -319,15 +264,14 @@ export class TreeSummarize extends PromptMixin implements ResponseBuilder {
}
}
getResponse(
query: ResponseBuilderQuery,
stream: true,
): Promise<AsyncIterable<string>>;
getResponse(query: ResponseBuilderQuery, stream?: false): Promise<string>;
async getResponse(
{ query, textChunks }: ResponseBuilderQuery,
stream?: boolean,
): Promise<AsyncIterable<string> | string> {
query: MessageContent,
nodes: NodeWithScore[],
stream: boolean,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const textChunks = nodes.map(({ node }) =>
node.getContent(MetadataMode.LLM),
);
if (!textChunks || textChunks.length === 0) {
throw new Error("Must have at least one text chunk");
}
@@ -347,9 +291,14 @@ export class TreeSummarize extends PromptMixin implements ResponseBuilder {
};
if (stream) {
const response = await this.llm.complete({ ...params, stream });
return streamConverter(response, (chunk) => chunk.text);
return streamConverter(response, (chunk) =>
EngineResponse.fromResponse(chunk.text, true),
);
}
return (await this.llm.complete(params)).text;
return EngineResponse.fromResponse(
(await this.llm.complete(params)).text,
false,
);
} else {
const summaries = await Promise.all(
packedTextChunks.map((chunk) =>
@@ -362,40 +311,118 @@ export class TreeSummarize extends PromptMixin implements ResponseBuilder {
),
);
const params = {
query,
textChunks: summaries.map((s) => s.text),
};
if (stream) {
return this.getResponse(
{
...params,
},
query,
summaries.map((s) => ({
node: new TextNode({
text: s.text,
}),
})),
true,
);
}
return this.getResponse(params);
return this.getResponse(
query,
summaries.map((s) => ({
node: new TextNode({
text: s.text,
}),
})),
false,
);
}
}
}
export function getResponseBuilder(
serviceContext?: ServiceContext,
responseMode?: ResponseMode,
): ResponseBuilder {
switch (responseMode) {
case ResponseMode.SIMPLE:
return new SimpleResponseBuilder(serviceContext);
case ResponseMode.REFINE:
return new Refine(serviceContext);
case ResponseMode.TREE_SUMMARIZE:
return new TreeSummarize(serviceContext);
default:
return new CompactAndRefine(serviceContext);
class MultiModal extends BaseSynthesizer {
metadataMode: MetadataMode;
textQATemplate: TextQAPrompt;
constructor({
textQATemplate,
metadataMode,
...options
}: BaseSynthesizerOptions & {
textQATemplate?: TextQAPrompt;
metadataMode?: MetadataMode;
} = {}) {
super(options);
this.metadataMode = metadataMode ?? MetadataMode.NONE;
this.textQATemplate = textQATemplate ?? defaultTextQAPrompt;
}
protected _getPromptModules(): ModuleRecord {
return {};
}
protected _getPrompts(): { textQATemplate: TextQAPrompt } {
return {
textQATemplate: this.textQATemplate,
};
}
protected _updatePrompts(promptsDict: {
textQATemplate: TextQAPrompt;
}): void {
if (promptsDict.textQATemplate) {
this.textQATemplate = promptsDict.textQATemplate;
}
}
protected async getResponse(
query: MessageContent,
nodes: NodeWithScore[],
stream: boolean,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const prompt = await createMessageContent(
this.textQATemplate,
nodes.map(({ node }) => node),
// this might not be good as this remove the image information
{ query: extractText(query) },
this.metadataMode,
);
const llm = this.llm;
if (stream) {
const response = await llm.complete({
prompt,
stream,
});
return streamConverter(response, ({ text }) =>
EngineResponse.fromResponse(text, true),
);
}
const response = await llm.complete({
prompt,
});
return EngineResponse.fromResponse(response.text, false);
}
}
export type ResponseBuilderPrompts =
| TextQAPrompt
| TreeSummarizePrompt
| RefinePrompt;
export function getResponseSynthesizer(
mode: ResponseMode,
options: BaseSynthesizerOptions & {
textQATemplate?: TextQAPrompt;
refineTemplate?: RefinePrompt;
summaryTemplate?: TreeSummarizePrompt;
metadataMode?: MetadataMode;
} = {},
) {
switch (mode) {
case "compact": {
return new CompactAndRefine(options);
}
case "refine": {
return new Refine(options);
}
case "tree_summarize": {
return new TreeSummarize(options);
}
case "multi_modal": {
return new MultiModal(options);
}
}
}
@@ -0,0 +1,10 @@
export {
BaseSynthesizer,
type BaseSynthesizerOptions,
} from "./base-synthesizer";
export { getResponseSynthesizer, type ResponseMode } from "./factory";
export type {
SynthesizeEndEvent,
SynthesizeQuery,
SynthesizeStartEvent,
} from "./type";
@@ -0,0 +1,19 @@
import type { QueryType } from "../query-engine";
import { EngineResponse, type NodeWithScore } from "../schema";
export type SynthesizeQuery = {
query: QueryType;
nodes: NodeWithScore[];
additionalSourceNodes?: NodeWithScore[];
};
export type SynthesizeStartEvent = {
id: string;
query: SynthesizeQuery;
};
export type SynthesizeEndEvent = {
id: string;
query: SynthesizeQuery;
response: EngineResponse | AsyncIterable<EngineResponse>;
};
+3 -1
View File
@@ -1,4 +1,4 @@
export { wrapEventCaller } from "./event-caller";
export { EventCaller, getEventCaller, wrapEventCaller } from "./event-caller";
export async function* streamConverter<S, D>(
stream: AsyncIterable<S>,
@@ -47,10 +47,12 @@ export async function* streamReducer<S, D>(params: {
export { wrapLLMEvent } from "./wrap-llm-event";
export {
createMessageContent,
extractDataUrlComponents,
extractImage,
extractSingleText,
extractText,
imageToDataUrl,
messagesToHistory,
toToolDescriptions,
} from "./llms";
+106
View File
@@ -1,3 +1,5 @@
import { fs } from "@llamaindex/env";
import { filetypemime } from "magic-bytes.js";
import type {
ChatMessage,
MessageContent,
@@ -5,8 +7,16 @@ import type {
MessageContentTextDetail,
ToolMetadata,
} from "../llms";
import type { BasePromptTemplate } from "../prompts";
import type { QueryType } from "../query-engine";
import type { ImageType } from "../schema";
import {
type BaseNode,
ImageNode,
MetadataMode,
ModalityType,
splitNodesByType,
} from "../schema";
/**
* Extracts just the text whether from
@@ -107,3 +117,99 @@ export function toToolDescriptions(tools: ToolMetadata[]): string {
return JSON.stringify(toolsObj, null, 4);
}
async function blobToDataUrl(input: Blob) {
const buffer = Buffer.from(await input.arrayBuffer());
const mimes = filetypemime(buffer);
if (mimes.length < 1) {
throw new Error("Unsupported image type");
}
return "data:" + mimes[0] + ";base64," + buffer.toString("base64");
}
export async function imageToDataUrl(
input: ImageType | Uint8Array,
): Promise<string> {
// first ensure, that the input is a Blob
if (
(input instanceof URL && input.protocol === "file:") ||
typeof input === "string"
) {
// string or file URL
const dataBuffer = await fs.readFile(
input instanceof URL ? input.pathname : input,
);
input = new Blob([dataBuffer]);
} else if (!(input instanceof Blob)) {
if (input instanceof URL) {
throw new Error(`Unsupported URL with protocol: ${input.protocol}`);
} else if (input instanceof Uint8Array) {
input = new Blob([input]); // convert Uint8Array to Blob
} else {
throw new Error(`Unsupported input type: ${typeof input}`);
}
}
return await blobToDataUrl(input);
}
// eslint-disable-next-line max-params
async function createContentPerModality(
prompt: BasePromptTemplate,
type: ModalityType,
nodes: BaseNode[],
extraParams: Record<string, string>,
metadataMode: MetadataMode,
): Promise<MessageContentDetail[]> {
switch (type) {
case ModalityType.TEXT:
return [
{
type: "text",
text: prompt.format({
...extraParams,
context: nodes.map((r) => r.getContent(metadataMode)).join("\n\n"),
}),
},
];
case ModalityType.IMAGE:
const images: MessageContentDetail[] = await Promise.all(
(nodes as ImageNode[]).map(async (node) => {
return {
type: "image_url",
image_url: {
url: await imageToDataUrl(node.image),
},
} satisfies MessageContentDetail;
}),
);
return images;
default:
return [];
}
}
export async function createMessageContent(
prompt: BasePromptTemplate,
nodes: BaseNode[],
extraParams: Record<string, string> = {},
metadataMode: MetadataMode = MetadataMode.NONE,
): Promise<MessageContentDetail[]> {
const content: MessageContentDetail[] = [];
const nodeMap = splitNodesByType(nodes);
for (const type in nodeMap) {
// for each retrieved modality type, create message content
const nodes = nodeMap[type as ModalityType];
if (nodes) {
content.push(
...(await createContentPerModality(
prompt,
type as ModalityType,
nodes,
extraParams,
metadataMode,
)),
);
}
}
return content;
}
@@ -1,211 +0,0 @@
import jsonpath from "jsonpath";
import { EngineResponse } from "llamaindex";
import { serviceContextFromDefaults, type ServiceContext } from "llamaindex";
import type {
QueryEngine,
QueryEngineParamsNonStreaming,
QueryEngineParamsStreaming,
} from "llamaindex";
import {
defaultJsonPathPrompt,
defaultResponseSynthesizePrompt,
type JSONPathPrompt,
type ResponseSynthesisPrompt,
} from "./prompt.js";
export type JSONSchemaType = Record<string, unknown>;
function removeExtraQuotes(expr: string) {
let startIndex = 0;
let endIndex = expr.length;
// Trim the leading backticks and single quotes
while (
startIndex < endIndex &&
(expr[startIndex] === "`" || expr[startIndex] === "'")
) {
startIndex++;
}
// Trim the trailing backticks and single quotes
while (
endIndex > startIndex &&
(expr[endIndex - 1] === "`" || expr[endIndex - 1] === "'")
) {
endIndex--;
}
// Return the trimmed substring
return expr.substring(startIndex, endIndex);
}
export const defaultOutputProcessor = async ({
llmOutput,
jsonValue,
}: {
llmOutput: string;
jsonValue: JSONSchemaType;
}): Promise<Record<string, unknown>[]> => {
const expressions = llmOutput
.split(",")
.map((expr) => removeExtraQuotes(expr.trim()));
const results: Record<string, unknown>[] = [];
for (const expression of expressions) {
// get the key for example content from $.content
const key = expression.split(".").pop();
try {
const datums = jsonpath.query(jsonValue, expression);
if (!key) throw new Error(`Invalid JSON Path: ${expression}`);
for (const datum of datums) {
// in case there is a filter like [?(@.username=='simon')] without a key ie: $..comments[?(@.username=='simon').content]
if (key.includes("==")) {
results.push(datum);
continue;
}
results.push({
[key]: datum,
});
}
} catch (err) {
throw new Error(`Invalid JSON Path: ${expression}`);
}
}
return results;
};
type OutputProcessor = typeof defaultOutputProcessor;
/**
* A JSON query engine that uses JSONPath to query a JSON object.
*/
export class JSONQueryEngine implements QueryEngine {
jsonValue: JSONSchemaType;
jsonSchema: JSONSchemaType;
serviceContext: ServiceContext;
outputProcessor: OutputProcessor;
verbose: boolean;
jsonPathPrompt: JSONPathPrompt;
synthesizeResponse: boolean;
responseSynthesisPrompt: ResponseSynthesisPrompt;
constructor(init: {
jsonValue: JSONSchemaType;
jsonSchema: JSONSchemaType;
serviceContext?: ServiceContext;
jsonPathPrompt?: JSONPathPrompt;
outputProcessor?: OutputProcessor;
synthesizeResponse?: boolean;
responseSynthesisPrompt?: ResponseSynthesisPrompt;
verbose?: boolean;
}) {
this.jsonValue = init.jsonValue;
this.jsonSchema = init.jsonSchema;
this.serviceContext = init.serviceContext ?? serviceContextFromDefaults({});
this.jsonPathPrompt = init.jsonPathPrompt ?? defaultJsonPathPrompt;
this.outputProcessor = init.outputProcessor ?? defaultOutputProcessor;
this.verbose = init.verbose ?? false;
this.synthesizeResponse = init.synthesizeResponse ?? true;
this.responseSynthesisPrompt =
init.responseSynthesisPrompt ?? defaultResponseSynthesizePrompt;
}
getPrompts(): Record<string, unknown> {
return {
jsonPathPrompt: this.jsonPathPrompt,
responseSynthesisPrompt: this.responseSynthesisPrompt,
};
}
updatePrompts(prompts: {
jsonPathPrompt?: JSONPathPrompt;
responseSynthesisPrompt?: ResponseSynthesisPrompt;
}): void {
if (prompts.jsonPathPrompt) {
this.jsonPathPrompt = prompts.jsonPathPrompt;
}
if (prompts.responseSynthesisPrompt) {
this.responseSynthesisPrompt = prompts.responseSynthesisPrompt;
}
}
getPromptModules(): Record<string, unknown> {
return {};
}
getSchemaContext(): string {
return JSON.stringify(this.jsonSchema);
}
query(
params: QueryEngineParamsStreaming,
): Promise<AsyncIterable<EngineResponse>>;
query(params: QueryEngineParamsNonStreaming): Promise<EngineResponse>;
async query(
params: QueryEngineParamsStreaming | QueryEngineParamsNonStreaming,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const { query, stream } = params;
if (stream) {
throw new Error("Streaming is not supported");
}
const schema = this.getSchemaContext();
const { text: jsonPathResponse } = await this.serviceContext.llm.complete({
prompt: this.jsonPathPrompt({ query, schema }),
});
if (this.verbose) {
console.log(
`> JSONPath Instructions:\n\`\`\`\n${jsonPathResponse}\n\`\`\`\n`,
);
}
const jsonPathOutput = await this.outputProcessor({
llmOutput: jsonPathResponse,
jsonValue: this.jsonValue,
});
if (this.verbose) {
console.log(`> JSONPath Output: ${jsonPathOutput}\n`);
}
let responseStr;
if (this.synthesizeResponse) {
responseStr = await this.serviceContext.llm.complete({
prompt: this.responseSynthesisPrompt({
query,
jsonSchema: schema,
jsonPath: jsonPathResponse,
jsonPathValue: JSON.stringify(jsonPathOutput),
}),
});
responseStr = responseStr.text;
} else {
responseStr = JSON.stringify(jsonPathOutput);
}
const responseMetadata = {
jsonPathResponse,
};
const response = EngineResponse.fromResponse(responseStr, false);
response.metadata = responseMetadata;
return response;
}
}
@@ -1 +0,0 @@
export * from "./JSONQueryEngine.js";
@@ -1,36 +0,0 @@
export const defaultJsonPathPrompt = ({
query,
schema,
}: {
query: string;
schema: string;
}) => `
We have provided a JSON schema below:
${schema}
Given a task, respond with a JSON Path query that can retrieve data from a JSON value that matches the schema.
Task: ${query}
JSONPath:
`;
export type JSONPathPrompt = typeof defaultJsonPathPrompt;
export const defaultResponseSynthesizePrompt = ({
query,
jsonSchema,
jsonPath,
jsonPathValue,
}: {
query: string;
jsonSchema: string;
jsonPath: string;
jsonPathValue: string;
}) => `
Given a query, synthesize a response to satisfy the query using the JSON results. Only include details that are relevant to the query. If you don't know the answer, then say that.
JSON Schema: ${jsonSchema}
JSON Path: ${jsonPath}
Value at path: ${jsonPathValue}
Query: ${query}
Response:
`;
export type ResponseSynthesisPrompt = typeof defaultResponseSynthesizePrompt;
-1
View File
@@ -1 +0,0 @@
export * from "./engines/query/index.js";
@@ -100,7 +100,8 @@
/* Completeness */
// "skipDefaultLibCheck": true, /* Skip type checking .d.ts files that are included with TypeScript. */
"skipLibCheck": true /* Skip type checking all .d.ts files. */
"skipLibCheck": true /* Skip type checking all .d.ts files. */,
"tsBuildInfoFile": "./dist/.tsbuildinfo"
},
"exclude": ["test"]
}
@@ -1,7 +1,7 @@
"use server";
import { Document, VectorStoreIndex, type QueryEngine } from "llamaindex";
import { BaseQueryEngine, Document, VectorStoreIndex } from "llamaindex";
import { readFile } from "node:fs/promises";
let _queryEngine: QueryEngine;
let _queryEngine: BaseQueryEngine;
async function lazyLoadQueryEngine() {
if (!_queryEngine) {
@@ -9,6 +9,8 @@ import { OpenAI, OpenAIEmbedding } from "@llamaindex/openai";
/**
* The ServiceContext is a collection of components that are used in different parts of the application.
*
* @deprecated This will no longer supported, please use `Settings` instead.
*/
export interface ServiceContext {
llm: LLM;
@@ -1,9 +1,9 @@
import type { BaseQueryEngine } from "@llamaindex/core/query-engine";
import type { BaseSynthesizer } from "@llamaindex/core/response-synthesizers";
import type { Document, TransformComponent } from "@llamaindex/core/schema";
import type { BaseRetriever } from "../Retriever.js";
import { RetrieverQueryEngine } from "../engines/query/RetrieverQueryEngine.js";
import type { BaseNodePostprocessor } from "../postprocessors/types.js";
import type { BaseSynthesizer } from "../synthesizers/types.js";
import type { QueryEngine } from "../types.js";
import type { CloudRetrieveParams } from "./LlamaCloudRetriever.js";
import { LlamaCloudRetriever } from "./LlamaCloudRetriever.js";
import { getPipelineCreate } from "./config.js";
@@ -300,7 +300,7 @@ export class LlamaCloudIndex {
preFilters?: unknown;
nodePostprocessors?: BaseNodePostprocessor[];
} & CloudRetrieveParams,
): QueryEngine {
): BaseQueryEngine {
const retriever = new LlamaCloudRetriever({
...this.params,
...params,
@@ -6,6 +6,7 @@ import {
type ModuleRecord,
PromptMixin,
} from "@llamaindex/core/prompts";
import type { BaseQueryEngine } from "@llamaindex/core/query-engine";
import type { EngineResponse } from "@llamaindex/core/schema";
import {
extractText,
@@ -15,7 +16,6 @@ import {
} from "@llamaindex/core/utils";
import type { ServiceContext } from "../../ServiceContext.js";
import { llmFromSettingsOrContext } from "../../Settings.js";
import type { QueryEngine } from "../../types.js";
import type {
ChatEngine,
ChatEngineParamsNonStreaming,
@@ -37,13 +37,13 @@ export class CondenseQuestionChatEngine
extends PromptMixin
implements ChatEngine
{
queryEngine: QueryEngine;
queryEngine: BaseQueryEngine;
chatHistory: BaseMemory;
llm: LLM;
condenseMessagePrompt: CondenseQuestionPrompt;
constructor(init: {
queryEngine: QueryEngine;
queryEngine: BaseQueryEngine;
chatHistory: ChatMessage[];
serviceContext?: ServiceContext;
condenseMessagePrompt?: CondenseQuestionPrompt;
@@ -114,10 +114,12 @@ export class CondenseQuestionChatEngine
chatHistory.put({ content: message, role: "user" });
if (stream) {
const stream = await this.queryEngine.query({
query: condensedQuestion,
stream: true,
});
const stream = await this.queryEngine.query(
{
query: condensedQuestion,
},
true,
);
return streamReducer({
stream,
initialValue: "",
@@ -6,9 +6,9 @@ import {
PromptMixin,
} from "@llamaindex/core/prompts";
import { MetadataMode, type NodeWithScore } from "@llamaindex/core/schema";
import { createMessageContent } from "@llamaindex/core/utils";
import type { BaseNodePostprocessor } from "../../postprocessors/index.js";
import type { BaseRetriever } from "../../Retriever.js";
import { createMessageContent } from "../../synthesizers/utils.js";
import type { Context, ContextGenerator } from "./types.js";
export class DefaultContextGenerator
@@ -1,20 +1,15 @@
import { PromptMixin } from "@llamaindex/core/prompts";
import { EngineResponse, type NodeWithScore } from "@llamaindex/core/schema";
import { wrapEventCaller } from "@llamaindex/core/utils";
import { BaseQueryEngine } from "@llamaindex/core/query-engine";
import type { BaseSynthesizer } from "@llamaindex/core/response-synthesizers";
import { getResponseSynthesizer } from "@llamaindex/core/response-synthesizers";
import { type NodeWithScore } from "@llamaindex/core/schema";
import { extractText } from "@llamaindex/core/utils";
import type { BaseNodePostprocessor } from "../../postprocessors/index.js";
import type { BaseRetriever } from "../../Retriever.js";
import type { BaseSynthesizer } from "../../synthesizers/index.js";
import { ResponseSynthesizer } from "../../synthesizers/index.js";
import type {
QueryEngine,
QueryEngineParamsNonStreaming,
QueryEngineParamsStreaming,
} from "../../types.js";
/**
* A query engine that uses a retriever to query an index and then synthesizes the response.
*/
export class RetrieverQueryEngine extends PromptMixin implements QueryEngine {
export class RetrieverQueryEngine extends BaseQueryEngine {
retriever: BaseRetriever;
responseSynthesizer: BaseSynthesizer;
nodePostprocessors: BaseNodePostprocessor[];
@@ -26,14 +21,36 @@ export class RetrieverQueryEngine extends PromptMixin implements QueryEngine {
preFilters?: unknown,
nodePostprocessors?: BaseNodePostprocessor[],
) {
super();
super(async (strOrQueryBundle, stream) => {
const nodesWithScore = await this.retrieve(
typeof strOrQueryBundle === "string"
? strOrQueryBundle
: extractText(strOrQueryBundle),
);
if (stream) {
return this.responseSynthesizer.synthesize(
{
query:
typeof strOrQueryBundle === "string"
? { query: strOrQueryBundle }
: strOrQueryBundle,
nodes: nodesWithScore,
},
true,
);
}
return this.responseSynthesizer.synthesize({
query:
typeof strOrQueryBundle === "string"
? { query: strOrQueryBundle }
: strOrQueryBundle,
nodes: nodesWithScore,
});
});
this.retriever = retriever;
this.responseSynthesizer =
responseSynthesizer ||
new ResponseSynthesizer({
serviceContext: retriever.serviceContext,
});
responseSynthesizer || getResponseSynthesizer("compact");
this.preFilters = preFilters;
this.nodePostprocessors = nodePostprocessors || [];
}
@@ -71,29 +88,4 @@ export class RetrieverQueryEngine extends PromptMixin implements QueryEngine {
return await this.applyNodePostprocessors(nodes, query);
}
query(
params: QueryEngineParamsStreaming,
): Promise<AsyncIterable<EngineResponse>>;
query(params: QueryEngineParamsNonStreaming): Promise<EngineResponse>;
@wrapEventCaller
async query(
params: QueryEngineParamsStreaming | QueryEngineParamsNonStreaming,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const { query, stream } = params;
const nodesWithScore = await this.retrieve(query);
if (stream) {
return this.responseSynthesizer.synthesize(
{
query,
nodesWithScore,
},
true,
);
}
return this.responseSynthesizer.synthesize({
query,
nodesWithScore,
});
}
}
@@ -1,20 +1,20 @@
import { PromptMixin } from "@llamaindex/core/prompts";
import type { QueryType } from "@llamaindex/core/query-engine";
import {
BaseQueryEngine,
type QueryBundle,
} from "@llamaindex/core/query-engine";
import {
BaseSynthesizer,
getResponseSynthesizer,
} from "@llamaindex/core/response-synthesizers";
import { EngineResponse, type NodeWithScore } from "@llamaindex/core/schema";
import { extractText } from "@llamaindex/core/utils";
import type { ServiceContext } from "../../ServiceContext.js";
import { llmFromSettingsOrContext } from "../../Settings.js";
import type { BaseSelector } from "../../selectors/index.js";
import { LLMSingleSelector } from "../../selectors/index.js";
import { TreeSummarize } from "../../synthesizers/index.js";
import type {
QueryEngine,
QueryEngineParamsNonStreaming,
QueryEngineParamsStreaming,
} from "../../types.js";
type RouterQueryEngineTool = {
queryEngine: QueryEngine;
queryEngine: BaseQueryEngine;
description: string;
};
@@ -23,59 +23,67 @@ type RouterQueryEngineMetadata = {
};
async function combineResponses(
summarizer: TreeSummarize,
summarizer: BaseSynthesizer,
responses: EngineResponse[],
queryType: QueryType,
queryBundle: QueryBundle,
verbose: boolean = false,
): Promise<EngineResponse> {
if (verbose) {
console.log("Combining responses from multiple query engines.");
}
const responseStrs: string[] = [];
const sourceNodes: NodeWithScore[] = [];
for (const response of responses) {
if (response?.sourceNodes) {
sourceNodes.push(...response.sourceNodes);
}
responseStrs.push(extractText(response.message.content));
}
const summary = await summarizer.getResponse({
query: extractText(queryType),
textChunks: responseStrs,
return await summarizer.synthesize({
query: queryBundle,
nodes: sourceNodes,
});
return EngineResponse.fromResponse(summary, false, sourceNodes);
}
/**
* A query engine that uses multiple query engines and selects the best one.
*/
export class RouterQueryEngine extends PromptMixin implements QueryEngine {
export class RouterQueryEngine extends BaseQueryEngine {
private selector: BaseSelector;
private queryEngines: QueryEngine[];
private queryEngines: BaseQueryEngine[];
private metadatas: RouterQueryEngineMetadata[];
private summarizer: TreeSummarize;
private summarizer: BaseSynthesizer;
private verbose: boolean;
constructor(init: {
selector: BaseSelector;
queryEngineTools: RouterQueryEngineTool[];
serviceContext?: ServiceContext | undefined;
summarizer?: TreeSummarize | undefined;
summarizer?: BaseSynthesizer | undefined;
verbose?: boolean | undefined;
}) {
super();
super(async (strOrQueryBundle, stream) => {
const response = await this.queryRoute(
typeof strOrQueryBundle === "string"
? { query: strOrQueryBundle }
: strOrQueryBundle,
);
if (stream) {
throw new Error("Streaming is not supported yet.");
}
return response;
});
this.selector = init.selector;
this.queryEngines = init.queryEngineTools.map((tool) => tool.queryEngine);
this.metadatas = init.queryEngineTools.map((tool) => ({
description: tool.description,
}));
this.summarizer = init.summarizer || new TreeSummarize(init.serviceContext);
this.summarizer =
init.summarizer || getResponseSynthesizer("tree_summarize");
this.verbose = init.verbose ?? false;
}
@@ -96,7 +104,7 @@ export class RouterQueryEngine extends PromptMixin implements QueryEngine {
queryEngineTools: RouterQueryEngineTool[];
selector?: BaseSelector;
serviceContext?: ServiceContext;
summarizer?: TreeSummarize;
summarizer?: BaseSynthesizer;
verbose?: boolean;
}) {
const serviceContext = init.serviceContext;
@@ -114,25 +122,7 @@ export class RouterQueryEngine extends PromptMixin implements QueryEngine {
});
}
query(
params: QueryEngineParamsStreaming,
): Promise<AsyncIterable<EngineResponse>>;
query(params: QueryEngineParamsNonStreaming): Promise<EngineResponse>;
async query(
params: QueryEngineParamsStreaming | QueryEngineParamsNonStreaming,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const { query, stream } = params;
const response = await this.queryRoute(query);
if (stream) {
throw new Error("Streaming is not supported yet.");
}
return response;
}
private async queryRoute(query: QueryType): Promise<EngineResponse> {
private async queryRoute(query: QueryBundle): Promise<EngineResponse> {
const result = await this.selector.select(this.metadatas, query);
if (result.selections.length > 1) {
@@ -146,11 +136,7 @@ export class RouterQueryEngine extends PromptMixin implements QueryEngine {
}
const selectedQueryEngine = this.queryEngines[engineInd.index]!;
responses.push(
await selectedQueryEngine.query({
query: extractText(query),
}),
);
responses.push(await selectedQueryEngine.query(query));
}
if (responses.length > 1) {
@@ -1,29 +1,21 @@
import {
EngineResponse,
TextNode,
type NodeWithScore,
} from "@llamaindex/core/schema";
import type { BaseSynthesizer } from "@llamaindex/core/response-synthesizers";
import { getResponseSynthesizer } from "@llamaindex/core/response-synthesizers";
import { TextNode, type NodeWithScore } from "@llamaindex/core/schema";
import { LLMQuestionGenerator } from "../../QuestionGenerator.js";
import type { ServiceContext } from "../../ServiceContext.js";
import type { BaseSynthesizer } from "../../synthesizers/index.js";
import {
CompactAndRefine,
ResponseSynthesizer,
} from "../../synthesizers/index.js";
import type { BaseTool, ToolMetadata } from "@llamaindex/core/llms";
import { PromptMixin, type PromptsRecord } from "@llamaindex/core/prompts";
import type { BaseQueryEngine, QueryType } from "@llamaindex/core/query-engine";
import { wrapEventCaller } from "@llamaindex/core/utils";
import type { PromptsRecord } from "@llamaindex/core/prompts";
import {
BaseQueryEngine,
type QueryBundle,
} from "@llamaindex/core/query-engine";
import type { BaseQuestionGenerator, SubQuestion } from "./types.js";
/**
* SubQuestionQueryEngine decomposes a question into subquestions and then
*/
export class SubQuestionQueryEngine
extends PromptMixin
implements BaseQueryEngine
{
export class SubQuestionQueryEngine extends BaseQueryEngine {
responseSynthesizer: BaseSynthesizer;
questionGen: BaseQuestionGenerator;
queryEngines: BaseTool[];
@@ -34,11 +26,48 @@ export class SubQuestionQueryEngine
responseSynthesizer: BaseSynthesizer;
queryEngineTools: BaseTool[];
}) {
super();
super(async (strOrQueryBundle, stream) => {
let query: QueryBundle;
if (typeof strOrQueryBundle === "string") {
query = {
query: strOrQueryBundle,
};
} else {
query = strOrQueryBundle;
}
const subQuestions = await this.questionGen.generate(
this.metadatas,
strOrQueryBundle,
);
const subQNodes = await Promise.all(
subQuestions.map((subQ) => this.querySubQ(subQ)),
);
const nodesWithScore: NodeWithScore[] = subQNodes.filter(
(node) => node !== null,
);
if (stream) {
return this.responseSynthesizer.synthesize(
{
query,
nodes: nodesWithScore,
},
true,
);
}
return this.responseSynthesizer.synthesize(
{
query,
nodes: nodesWithScore,
},
false,
);
});
this.questionGen = init.questionGen;
this.responseSynthesizer =
init.responseSynthesizer ?? new ResponseSynthesizer();
init.responseSynthesizer ?? getResponseSynthesizer("compact");
this.queryEngines = init.queryEngineTools;
this.metadatas = init.queryEngineTools.map((tool) => tool.metadata);
}
@@ -62,15 +91,9 @@ export class SubQuestionQueryEngine
responseSynthesizer?: BaseSynthesizer;
serviceContext?: ServiceContext;
}) {
const serviceContext = init.serviceContext;
const questionGen = init.questionGen ?? new LLMQuestionGenerator();
const responseSynthesizer =
init.responseSynthesizer ??
new ResponseSynthesizer({
responseBuilder: new CompactAndRefine(serviceContext),
serviceContext,
});
init.responseSynthesizer ?? getResponseSynthesizer("compact");
return new SubQuestionQueryEngine({
questionGen,
@@ -79,40 +102,6 @@ export class SubQuestionQueryEngine
});
}
query(query: QueryType, stream: true): Promise<AsyncIterable<EngineResponse>>;
query(query: QueryType, stream?: false): Promise<EngineResponse>;
@wrapEventCaller
async query(
query: QueryType,
stream?: boolean,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const subQuestions = await this.questionGen.generate(this.metadatas, query);
const subQNodes = await Promise.all(
subQuestions.map((subQ) => this.querySubQ(subQ)),
);
const nodesWithScore = subQNodes
.filter((node) => node !== null)
.map((node) => node as NodeWithScore);
if (stream) {
return this.responseSynthesizer.synthesize(
{
query,
nodesWithScore,
},
true,
);
}
return this.responseSynthesizer.synthesize(
{
query,
nodesWithScore,
},
false,
);
}
private async querySubQ(subQ: SubQuestion): Promise<NodeWithScore | null> {
try {
const question = subQ.subQuestion;
+2 -1
View File
@@ -33,6 +33,8 @@ export type {
export * from "@llamaindex/core/indices";
export * from "@llamaindex/core/llms";
export * from "@llamaindex/core/prompts";
export * from "@llamaindex/core/query-engine";
export * from "@llamaindex/core/response-synthesizers";
export * from "@llamaindex/core/schema";
declare module "@llamaindex/core/global" {
@@ -69,6 +71,5 @@ export * from "./selectors/index.js";
export * from "./ServiceContext.js";
export { Settings } from "./Settings.js";
export * from "./storage/StorageContext.js";
export * from "./synthesizers/index.js";
export * from "./tools/index.js";
export * from "./types.js";
+3 -3
View File
@@ -1,3 +1,5 @@
import type { BaseQueryEngine } from "@llamaindex/core/query-engine";
import type { BaseSynthesizer } from "@llamaindex/core/response-synthesizers";
import type { BaseNode, Document } from "@llamaindex/core/schema";
import type { BaseRetriever } from "../Retriever.js";
import type { ServiceContext } from "../ServiceContext.js";
@@ -6,8 +8,6 @@ import { runTransformations } from "../ingestion/IngestionPipeline.js";
import type { StorageContext } from "../storage/StorageContext.js";
import type { BaseDocumentStore } from "../storage/docStore/types.js";
import type { BaseIndexStore } from "../storage/indexStore/types.js";
import type { BaseSynthesizer } from "../synthesizers/types.js";
import type { QueryEngine } from "../types.js";
import { IndexStruct } from "./IndexStruct.js";
import { IndexStructType } from "./json-to-index-struct.js";
@@ -83,7 +83,7 @@ export abstract class BaseIndex<T> {
abstract asQueryEngine(options?: {
retriever?: BaseRetriever;
responseSynthesizer?: BaseSynthesizer;
}): QueryEngine;
}): BaseQueryEngine;
/**
* Insert a document into the index.
@@ -1,3 +1,4 @@
import type { BaseSynthesizer } from "@llamaindex/core/response-synthesizers";
import type {
BaseNode,
Document,
@@ -12,8 +13,6 @@ import type { BaseNodePostprocessor } from "../../postprocessors/index.js";
import type { StorageContext } from "../../storage/StorageContext.js";
import { storageContextFromDefaults } from "../../storage/StorageContext.js";
import type { BaseDocumentStore } from "../../storage/docStore/types.js";
import type { BaseSynthesizer } from "../../synthesizers/index.js";
import type { QueryEngine } from "../../types.js";
import type { BaseIndexInit } from "../BaseIndex.js";
import { BaseIndex, KeywordTable } from "../BaseIndex.js";
import { IndexStructType } from "../json-to-index-struct.js";
@@ -30,6 +29,7 @@ import {
type KeywordExtractPrompt,
type QueryKeywordExtractPrompt,
} from "@llamaindex/core/prompts";
import type { BaseQueryEngine } from "@llamaindex/core/query-engine";
import { extractText } from "@llamaindex/core/utils";
import { llmFromSettingsOrContext } from "../../Settings.js";
@@ -237,7 +237,7 @@ export class KeywordTableIndex extends BaseIndex<KeywordTable> {
responseSynthesizer?: BaseSynthesizer;
preFilters?: unknown;
nodePostprocessors?: BaseNodePostprocessor[];
}): QueryEngine {
}): BaseQueryEngine {
const { retriever, responseSynthesizer } = options ?? {};
return new RetrieverQueryEngine(
retriever ?? this.asRetriever(),
@@ -2,6 +2,8 @@ import {
type ChoiceSelectPrompt,
defaultChoiceSelectPrompt,
} from "@llamaindex/core/prompts";
import type { BaseSynthesizer } from "@llamaindex/core/response-synthesizers";
import { getResponseSynthesizer } from "@llamaindex/core/response-synthesizers";
import type {
BaseNode,
Document,
@@ -23,12 +25,6 @@ import type {
BaseDocumentStore,
RefDocInfo,
} from "../../storage/docStore/types.js";
import type { BaseSynthesizer } from "../../synthesizers/index.js";
import {
CompactAndRefine,
ResponseSynthesizer,
} from "../../synthesizers/index.js";
import type { QueryEngine } from "../../types.js";
import type { BaseIndexInit } from "../BaseIndex.js";
import { BaseIndex } from "../BaseIndex.js";
import { IndexList, IndexStructType } from "../json-to-index-struct.js";
@@ -178,7 +174,7 @@ export class SummaryIndex extends BaseIndex<IndexList> {
responseSynthesizer?: BaseSynthesizer;
preFilters?: unknown;
nodePostprocessors?: BaseNodePostprocessor[];
}): QueryEngine & RetrieverQueryEngine {
}): RetrieverQueryEngine {
let { retriever, responseSynthesizer } = options ?? {};
if (!retriever) {
@@ -186,11 +182,7 @@ export class SummaryIndex extends BaseIndex<IndexList> {
}
if (!responseSynthesizer) {
const responseBuilder = new CompactAndRefine(this.serviceContext);
responseSynthesizer = new ResponseSynthesizer({
serviceContext: this.serviceContext,
responseBuilder,
});
responseSynthesizer = getResponseSynthesizer("compact");
}
return new RetrieverQueryEngine(
@@ -4,6 +4,7 @@ import {
} from "@llamaindex/core/embeddings";
import { Settings } from "@llamaindex/core/global";
import type { MessageContent } from "@llamaindex/core/llms";
import type { BaseSynthesizer } from "@llamaindex/core/response-synthesizers";
import {
ImageNode,
ModalityType,
@@ -30,8 +31,6 @@ import type { BaseNodePostprocessor } from "../../postprocessors/types.js";
import type { StorageContext } from "../../storage/StorageContext.js";
import { storageContextFromDefaults } from "../../storage/StorageContext.js";
import type { BaseIndexStore } from "../../storage/indexStore/types.js";
import type { BaseSynthesizer } from "../../synthesizers/types.js";
import type { QueryEngine } from "../../types.js";
import type {
MetadataFilters,
VectorStore,
@@ -288,7 +287,7 @@ export class VectorStoreIndex extends BaseIndex<IndexDict> {
preFilters?: MetadataFilters;
nodePostprocessors?: BaseNodePostprocessor[];
similarityTopK?: number;
}): QueryEngine & RetrieverQueryEngine {
}): RetrieverQueryEngine {
const {
retriever,
responseSynthesizer,
@@ -1,88 +0,0 @@
import {
defaultTextQAPrompt,
PromptMixin,
type ModuleRecord,
type TextQAPrompt,
} from "@llamaindex/core/prompts";
import { EngineResponse, MetadataMode } from "@llamaindex/core/schema";
import { streamConverter } from "@llamaindex/core/utils";
import type { ServiceContext } from "../ServiceContext.js";
import { llmFromSettingsOrContext } from "../Settings.js";
import type { BaseSynthesizer, SynthesizeQuery } from "./types.js";
import { createMessageContent } from "./utils.js";
export class MultiModalResponseSynthesizer
extends PromptMixin
implements BaseSynthesizer
{
serviceContext?: ServiceContext | undefined;
metadataMode: MetadataMode;
textQATemplate: TextQAPrompt;
constructor({
serviceContext,
textQATemplate,
metadataMode,
}: Partial<MultiModalResponseSynthesizer> = {}) {
super();
this.serviceContext = serviceContext;
this.metadataMode = metadataMode ?? MetadataMode.NONE;
this.textQATemplate = textQATemplate ?? defaultTextQAPrompt;
}
protected _getPromptModules(): ModuleRecord {
return {};
}
protected _getPrompts(): { textQATemplate: TextQAPrompt } {
return {
textQATemplate: this.textQATemplate,
};
}
protected _updatePrompts(promptsDict: {
textQATemplate: TextQAPrompt;
}): void {
if (promptsDict.textQATemplate) {
this.textQATemplate = promptsDict.textQATemplate;
}
}
synthesize(
query: SynthesizeQuery,
stream: true,
): Promise<AsyncIterable<EngineResponse>>;
synthesize(query: SynthesizeQuery, stream?: false): Promise<EngineResponse>;
async synthesize(
query: SynthesizeQuery,
stream?: boolean,
): Promise<AsyncIterable<EngineResponse> | EngineResponse> {
const { nodesWithScore } = query;
const nodes = nodesWithScore.map(({ node }) => node);
const prompt = await createMessageContent(
this.textQATemplate,
nodes,
// fixme: wtf type is this?
// { query },
{},
this.metadataMode,
);
const llm = llmFromSettingsOrContext(this.serviceContext);
if (stream) {
const response = await llm.complete({
prompt,
stream,
});
return streamConverter(response, ({ text }) =>
EngineResponse.fromResponse(text, true, nodesWithScore),
);
}
const response = await llm.complete({
prompt,
});
return EngineResponse.fromResponse(response.text, false, nodesWithScore);
}
}
@@ -1,87 +0,0 @@
import { PromptMixin, type PromptsRecord } from "@llamaindex/core/prompts";
import { EngineResponse, MetadataMode } from "@llamaindex/core/schema";
import { streamConverter } from "@llamaindex/core/utils";
import type { ServiceContext } from "../ServiceContext.js";
import { getResponseBuilder } from "./builders.js";
import type {
BaseSynthesizer,
ResponseBuilder,
SynthesizeQuery,
} from "./types.js";
/**
* A ResponseSynthesizer is used to generate a response from a query and a list of nodes.
*/
export class ResponseSynthesizer
extends PromptMixin
implements BaseSynthesizer
{
responseBuilder: ResponseBuilder;
metadataMode: MetadataMode;
constructor({
responseBuilder,
serviceContext,
metadataMode = MetadataMode.NONE,
}: {
responseBuilder?: ResponseBuilder | undefined;
serviceContext?: ServiceContext | undefined;
metadataMode?: MetadataMode | undefined;
} = {}) {
super();
this.responseBuilder =
responseBuilder ?? getResponseBuilder(serviceContext);
this.metadataMode = metadataMode;
}
_getPromptModules() {
return {};
}
protected _getPrompts() {
const prompts = this.responseBuilder.getPrompts?.();
return {
...prompts,
};
}
protected _updatePrompts(promptsRecord: PromptsRecord): void {
this.responseBuilder.updatePrompts?.(promptsRecord);
}
synthesize(
query: SynthesizeQuery,
stream: true,
): Promise<AsyncIterable<EngineResponse>>;
synthesize(query: SynthesizeQuery, stream?: false): Promise<EngineResponse>;
async synthesize(
query: SynthesizeQuery,
stream?: boolean,
): Promise<AsyncIterable<EngineResponse> | EngineResponse> {
const { nodesWithScore } = query;
const textChunks: string[] = nodesWithScore.map(({ node }) =>
node.getContent(this.metadataMode),
);
if (stream) {
const response = await this.responseBuilder.getResponse(
{
...query,
textChunks,
},
true,
);
return streamConverter(response, (chunk) =>
EngineResponse.fromResponse(chunk, true, nodesWithScore),
);
}
const response = await this.responseBuilder.getResponse(
{
...query,
textChunks,
},
false,
);
return EngineResponse.fromResponse(response, false, nodesWithScore);
}
}
@@ -1,4 +0,0 @@
export * from "./builders.js";
export * from "./MultiModalResponseSynthesizer.js";
export * from "./ResponseSynthesizer.js";
export * from "./types.js";
@@ -1,40 +0,0 @@
import type { PromptMixin } from "@llamaindex/core/prompts";
import type { QueryType } from "@llamaindex/core/query-engine";
import { EngineResponse, type NodeWithScore } from "@llamaindex/core/schema";
export interface SynthesizeQuery {
query: QueryType;
nodesWithScore: NodeWithScore[];
}
// todo(himself65): Move this to @llamaindex/core/schema
/**
* A BaseSynthesizer is used to generate a response from a query and a list of nodes.
*/
export interface BaseSynthesizer extends PromptMixin {
synthesize(
query: SynthesizeQuery,
stream: true,
): Promise<AsyncIterable<EngineResponse>>;
synthesize(query: SynthesizeQuery, stream?: false): Promise<EngineResponse>;
}
export interface ResponseBuilderQuery {
query: QueryType;
textChunks: string[];
prevResponse?: string | undefined;
}
/**
* A ResponseBuilder is used in a response synthesizer to generate a response from multiple response chunks.
*/
export interface ResponseBuilder extends PromptMixin {
/**
* Get the response from a query and a list of text chunks.
*/
getResponse(
query: ResponseBuilderQuery,
stream: true,
): Promise<AsyncIterable<string>>;
getResponse(query: ResponseBuilderQuery, stream?: false): Promise<string>;
}
@@ -1,72 +0,0 @@
import type { MessageContentDetail } from "@llamaindex/core/llms";
import type { BasePromptTemplate } from "@llamaindex/core/prompts";
import {
ImageNode,
MetadataMode,
ModalityType,
splitNodesByType,
type BaseNode,
} from "@llamaindex/core/schema";
import { imageToDataUrl } from "../internal/utils.js";
export async function createMessageContent(
prompt: BasePromptTemplate,
nodes: BaseNode[],
extraParams: Record<string, string | undefined> = {},
metadataMode: MetadataMode = MetadataMode.NONE,
): Promise<MessageContentDetail[]> {
const content: MessageContentDetail[] = [];
const nodeMap = splitNodesByType(nodes);
for (const type in nodeMap) {
// for each retrieved modality type, create message content
const nodes = nodeMap[type as ModalityType];
if (nodes) {
content.push(
...(await createContentPerModality(
prompt,
type as ModalityType,
nodes,
extraParams,
metadataMode,
)),
);
}
}
return content;
}
// eslint-disable-next-line max-params
async function createContentPerModality(
prompt: BasePromptTemplate,
type: ModalityType,
nodes: BaseNode[],
extraParams: Record<string, string | undefined>,
metadataMode: MetadataMode,
): Promise<MessageContentDetail[]> {
switch (type) {
case ModalityType.TEXT:
return [
{
type: "text",
text: prompt.format({
...extraParams,
context: nodes.map((r) => r.getContent(metadataMode)).join("\n\n"),
}),
},
];
case ModalityType.IMAGE:
const images: MessageContentDetail[] = await Promise.all(
(nodes as ImageNode[]).map(async (node) => {
return {
type: "image_url",
image_url: {
url: await imageToDataUrl(node.image),
},
} satisfies MessageContentDetail;
}),
);
return images;
default:
return [];
}
}
-30
View File
@@ -2,36 +2,6 @@
* Top level types to avoid circular dependencies
*/
import type { ToolMetadata } from "@llamaindex/core/llms";
import type { EngineResponse } from "@llamaindex/core/schema";
/**
* Parameters for sending a query.
*/
export interface QueryEngineParamsBase {
query: string;
}
export interface QueryEngineParamsStreaming extends QueryEngineParamsBase {
stream: true;
}
export interface QueryEngineParamsNonStreaming extends QueryEngineParamsBase {
stream?: false | null;
}
/**
* A query engine is a question answerer that can use one or more steps.
*/
export interface QueryEngine {
/**
* Query the query engine and get a response.
* @param params
*/
query(
params: QueryEngineParamsStreaming,
): Promise<AsyncIterable<EngineResponse>>;
query(params: QueryEngineParamsNonStreaming): Promise<EngineResponse>;
}
/**
* StructuredOutput is just a combo of the raw output and the parsed output.
+9 -36
View File
@@ -167,7 +167,7 @@ importers:
version: link:../packages/llamaindex
mongodb:
specifier: ^6.7.0
version: 6.8.0(@aws-sdk/credential-providers@3.650.0(@aws-sdk/client-sso-oidc@3.650.0(@aws-sdk/client-sts@3.650.0)))
version: 6.8.0(@aws-sdk/credential-providers@3.650.0)
pathe:
specifier: ^1.1.2
version: 1.1.2
@@ -388,6 +388,9 @@ importers:
'@types/node':
specifier: ^22.5.1
version: 22.5.4
magic-bytes.js:
specifier: ^1.10.0
version: 1.10.0
zod:
specifier: ^3.23.8
version: 3.23.8
@@ -603,7 +606,7 @@ importers:
version: 2.0.0
mongodb:
specifier: ^6.7.0
version: 6.8.0(@aws-sdk/credential-providers@3.650.0(@aws-sdk/client-sso-oidc@3.650.0(@aws-sdk/client-sts@3.650.0)))
version: 6.8.0(@aws-sdk/credential-providers@3.650.0)
notion-md-crawler:
specifier: ^1.0.0
version: 1.0.0(encoding@0.1.13)
@@ -18297,7 +18300,7 @@ snapshots:
'@typescript-eslint/parser': 7.2.0(eslint@8.57.0)(typescript@5.6.2)
eslint: 8.57.0
eslint-import-resolver-node: 0.3.9
eslint-import-resolver-typescript: 3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint@8.57.0))(eslint@8.57.0)
eslint-import-resolver-typescript: 3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1)(eslint@8.57.0)
eslint-plugin-import: 2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-typescript@3.6.3)(eslint@8.57.0)
eslint-plugin-jsx-a11y: 6.9.0(eslint@8.57.0)
eslint-plugin-react: 7.35.0(eslint@8.57.0)
@@ -18345,25 +18348,6 @@ snapshots:
transitivePeerDependencies:
- supports-color
eslint-import-resolver-typescript@3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint@8.57.0))(eslint@8.57.0):
dependencies:
'@nolyfill/is-core-module': 1.0.39
debug: 4.3.7
enhanced-resolve: 5.17.1
eslint: 8.57.0
eslint-module-utils: 2.8.2(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-import-resolver-typescript@3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint@8.57.0))(eslint@8.57.0))(eslint@8.57.0)
fast-glob: 3.3.2
get-tsconfig: 4.8.0
is-bun-module: 1.1.0
is-glob: 4.0.3
optionalDependencies:
eslint-plugin-import: 2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-typescript@3.6.3)(eslint@8.57.0)
transitivePeerDependencies:
- '@typescript-eslint/parser'
- eslint-import-resolver-node
- eslint-import-resolver-webpack
- supports-color
eslint-import-resolver-typescript@3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1)(eslint@8.57.0):
dependencies:
'@nolyfill/is-core-module': 1.0.39
@@ -18376,24 +18360,13 @@ snapshots:
is-bun-module: 1.1.0
is-glob: 4.0.3
optionalDependencies:
eslint-plugin-import: 2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-typescript@3.6.3)(eslint@8.57.0)
eslint-plugin-import: 2.29.1(@typescript-eslint/parser@8.5.0(eslint@8.57.0)(typescript@5.6.2))(eslint@8.57.0)
transitivePeerDependencies:
- '@typescript-eslint/parser'
- eslint-import-resolver-node
- eslint-import-resolver-webpack
- supports-color
eslint-module-utils@2.8.2(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-import-resolver-typescript@3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint@8.57.0))(eslint@8.57.0))(eslint@8.57.0):
dependencies:
debug: 3.2.7
optionalDependencies:
'@typescript-eslint/parser': 7.2.0(eslint@8.57.0)(typescript@5.6.2)
eslint: 8.57.0
eslint-import-resolver-node: 0.3.9
eslint-import-resolver-typescript: 3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint@8.57.0))(eslint@8.57.0)
transitivePeerDependencies:
- supports-color
eslint-module-utils@2.8.2(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-import-resolver-typescript@3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1)(eslint@8.57.0))(eslint@8.57.0):
dependencies:
debug: 3.2.7
@@ -18415,7 +18388,7 @@ snapshots:
doctrine: 2.1.0
eslint: 8.57.0
eslint-import-resolver-node: 0.3.9
eslint-module-utils: 2.8.2(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-import-resolver-typescript@3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint@8.57.0))(eslint@8.57.0))(eslint@8.57.0)
eslint-module-utils: 2.8.2(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-import-resolver-typescript@3.6.3(@typescript-eslint/parser@7.2.0(eslint@8.57.0)(typescript@5.6.2))(eslint-import-resolver-node@0.3.9)(eslint-plugin-import@2.29.1)(eslint@8.57.0))(eslint@8.57.0)
hasown: 2.0.2
is-core-module: 2.15.1
is-glob: 4.0.3
@@ -21144,7 +21117,7 @@ snapshots:
optionalDependencies:
'@aws-sdk/credential-providers': 3.650.0(@aws-sdk/client-sso-oidc@3.650.0(@aws-sdk/client-sts@3.650.0))
mongodb@6.8.0(@aws-sdk/credential-providers@3.650.0(@aws-sdk/client-sso-oidc@3.650.0(@aws-sdk/client-sts@3.650.0))):
mongodb@6.8.0(@aws-sdk/credential-providers@3.650.0):
dependencies:
'@mongodb-js/saslprep': 1.1.7
bson: 6.8.0