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

Author: himself65

.changeset/ten-bottles-learn.md

@@ -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

examples/huggingface/embedding.ts

@@ -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) {

examples/huggingface/embeddingApi.ts

@@ -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) {

examples/lowlevel.ts

@@ -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,
   );

examples/multimodal/rag.ts

@@ -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);
   }

examples/prompts/promptMixin.ts

@@ -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,

examples/readers/src/csv.ts

@@ -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 });

examples/readers/src/llamaparse-json.ts

@@ -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() {

examples/vectorIndexAnthropic.ts

@@ -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]);
 

examples/vectorIndexFromVectorStore.ts

@@ -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,
     });