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...

33 Commits

Author SHA1 Message Date
github-actions[bot] b6fb10eba8 Release 0.6.11 (#1267)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-27 13:19:52 -07:00
Alex Yang df441e28f4 chore: release for new env package 2024-09-27 12:54:14 -07:00
github-actions[bot] a4e05ec7ab Release 0.6.10 (#1263)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-27 01:51:07 -07:00
irevived1 96f72ad86e fix: openai streaming with token usage and finish_reason (#1265)
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-09-26 17:51:59 -07:00
Alex Yang f3556c011c chore: update changeset 2024-09-26 09:36:20 -07:00
Alex Yang ebc510582b feat: support @vercel/postgres (#1262) 2024-09-25 22:39:32 -07:00
Alex Yang f3bfdc29e3 chore: fix changeset 2024-09-25 20:09:37 -07:00
Alex Yang 6cce3b12ea feat: support npm:postgres (#1248) 2024-09-25 19:40:20 -07:00
Alex Yang 0273e9739a chore: fix docs build with turbo (#1260) 2024-09-25 07:32:37 -07:00
Alex Yang 7c8b883448 fix: turbo cache (#1259) 2024-09-25 04:47:01 -07:00
Alex Yang c2bb418542 chore: fix url in package.json (#1258) 2024-09-25 03:52:33 -07:00
Alex Yang ed6acbead0 fix(core): backward support for legacy typescript (#1257) 2024-09-25 03:19:41 -07:00
Alex Yang 976cce40d7 docs: update README.md (#1255) 2024-09-24 15:03:48 -07:00
Alex Yang e4fd4158bb feat: move agent into core (#1254) 2024-09-24 14:55:40 -07:00
Alex Yang 31d5dffcef refactor: move ollama standalone (#1253) 2024-09-24 12:15:50 -07:00
github-actions[bot] d12edee802 Release 0.6.9 (#1252)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-24 10:31:54 -07:00
Alex Yang ac41ed3aae chore: bump cloud sdk version (#1251) 2024-09-24 09:43:45 -07:00
github-actions[bot] d8c1159032 Release 0.6.8 (#1245)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-23 18:41:44 -07:00
Alex Yang c856c5becb revert: stream back to first parameter (#1247) 2024-09-23 18:35:36 -07:00
John Wick 50e6b57be0 feat: add Amazon Bedrock Retriever (#1219)
Co-authored-by: Arnaud JEAN <arnajean@amazon.com>
Co-authored-by: ajohn-wick <ajohnwick@mrwick.org>
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-09-23 15:11:53 -07:00
Alex Yang 8b7fdba544 refactor: move chat engine & retriever into core (#1242) 2024-09-23 13:26:26 -07:00
github-actions[bot] 22ae8d0166 Release 0.6.7 (#1244)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-23 13:25:02 -07:00
Goran 23bcc379a8 fix: add serializer in doc store (#1243)
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-09-23 13:11:51 -07:00
github-actions[bot] bdc4bfe7b0 Release 0.6.6 (#1241)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-23 11:54:33 -07:00
Goran 025ffe6b50 fix: update PostgresKVStore constructor params (#1240)
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-09-23 10:46:11 -07:00
Cahid Arda Öz a6595747fa feat: add Upstash Vector Store (#1218)
Co-authored-by: ogzhanolguncu <ogzhan11@gmail.com>
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-09-23 10:00:10 -07:00
Marcus Schiesser d902cc3e7e fix: context not working in contextchatengine (#1237) 2024-09-22 15:19:13 -07:00
github-actions[bot] 726eb41359 Release 0.6.5 (#1239)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-20 14:24:23 -07:00
André Mazayev e9714dbfcd feat: update PGVectorStore constructor parameters (#1225)
Co-authored-by: Alex Yang <himself65@outlook.com>
2024-09-20 01:34:51 -07:00
Alex Yang a3618e761e chore: fix cache for cloud package (#1236) 2024-09-19 17:48:39 -07:00
github-actions[bot] 24eabe7f35 Release 0.6.4 (#1234)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
2024-09-19 16:42:39 -07:00
Alex Yang ecfa939ea6 ci: enable remote cache (#1233) 2024-09-19 15:40:34 -07:00
Alex Yang b48bcc3add feat: support custom @xenova/transformers (#1232) 2024-09-19 14:55:23 -07:00
196 changed files with 13172 additions and 7464 deletions
+14 -7
View File
@@ -14,6 +14,9 @@ concurrency:
env:
POSTGRES_HOST_AUTH_METHOD: trust
TURBO_TOKEN: ${{ secrets.TURBO_TOKEN }}
TURBO_TEAM: ${{ vars.TURBO_TEAM }}
TURBO_REMOTE_ONLY: true
jobs:
e2e:
@@ -86,13 +89,7 @@ jobs:
- name: Run Type Check
run: pnpm run type-check
- name: Run Circular Dependency Check
run: pnpm dlx turbo run circular-check
- uses: actions/upload-artifact@v3
if: failure()
with:
name: typecheck-build-dist
path: ./packages/llamaindex/dist
if-no-files-found: error
run: pnpm run circular-check
e2e-llamaindex-examples:
strategy:
fail-fast: false
@@ -148,6 +145,9 @@ jobs:
- name: Pack @llamaindex/groq
run: pnpm pack --pack-destination ${{ runner.temp }}
working-directory: packages/llm/groq
- name: Pack @llamaindex/ollama
run: pnpm pack --pack-destination ${{ runner.temp }}
working-directory: packages/llm/ollama
- name: Pack @llamaindex/core
run: pnpm pack --pack-destination ${{ runner.temp }}
working-directory: packages/core
@@ -163,3 +163,10 @@ jobs:
- name: Run Type Check
run: npx tsc --project ./tsconfig.json
working-directory: ${{ runner.temp }}/examples
- uses: actions/upload-artifact@v4
if: failure()
with:
name: build-dist
path: |
${{ runner.temp }}/*.tgz
if-no-files-found: error
+102 -49
View File
@@ -7,7 +7,7 @@
LlamaIndex is a data framework for your LLM application.
Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in Typescript and Javascript.
Use your own data with large language models (LLMs, OpenAI ChatGPT and others) in JS runtime environments with TypeScript support.
Documentation: https://ts.llamaindex.ai/
@@ -19,17 +19,36 @@ Try examples online:
LlamaIndex.TS aims to be a lightweight, easy to use set of libraries to help you integrate large language models into your applications with your own data.
## Multiple JS Environment Support
## Compatibility
### Multiple JS Environment Support
LlamaIndex.TS supports multiple JS environments, including:
- Node.js (18, 20, 22) ✅
- Deno ✅
- Bun ✅
- React Server Components (Next.js)
- Nitro
- Vercel Edge Runtime ✅ (with some limitations)
- Cloudflare Workers ✅ (with some limitations)
For now, browser support is limited due to the lack of support for [AsyncLocalStorage-like APIs](https://github.com/tc39/proposal-async-context)
### Supported LLMs:
- OpenAI LLms
- Anthropic LLms
- Groq LLMs
- Llama2, Llama3, Llama3.1 LLMs
- MistralAI LLMs
- Fireworks LLMs
- DeepSeek LLMs
- ReplicateAI LLMs
- TogetherAI LLMs
- HuggingFace LLms
- DeepInfra LLMs
- Gemini LLMs
## Getting started
```shell
@@ -77,7 +96,7 @@ See more about [moduleResolution](https://www.typescriptlang.org/docs/handbook/m
### Node.js
```ts
import fs from "fs/promises";
import fs from "node:fs/promises";
import { Document, VectorStoreIndex } from "llamaindex";
async function main() {
@@ -111,9 +130,9 @@ main();
node --import tsx ./main.ts
```
### React Server Component (Next.js, Waku, Redwood.JS...)
### Next.js
First, you will need to add a llamaindex plugin to your Next.js project.
You will need to add a llamaindex plugin to your Next.js project.
```js
// next.config.js
@@ -124,20 +143,18 @@ module.exports = withLlamaIndex({
});
```
You can combine `ai` with `llamaindex` in Next.js with RSC (React Server Components).
### React Server Actions
You can combine `ai` with `llamaindex` in Next.js, Waku or Redwood.js with RSC (React Server Components).
```tsx
// src/apps/page.tsx
"use client";
import { chatWithAgent } from "@/actions";
import type { JSX } from "react";
import { useFormState } from "react-dom";
// You can use the Edge runtime in Next.js by adding this line:
// export const runtime = "edge";
import { useActionState } from "react";
export default function Home() {
const [ui, action] = useFormState<JSX.Element | null>(async () => {
const [ui, action] = useActionState<JSX.Element | null>(async () => {
return chatWithAgent("hello!", []);
}, null);
return (
@@ -167,11 +184,13 @@ export async function chatWithAgent(
// ... adding your tools here
],
});
const responseStream = await agent.chat({
stream: true,
message: question,
chatHistory: prevMessages,
});
const responseStream = await agent.chat(
{
message: question,
chatHistory: prevMessages,
},
true,
);
const uiStream = createStreamableUI(<div>loading...</div>);
responseStream
.pipeTo(
@@ -189,6 +208,48 @@ export async function chatWithAgent(
}
```
### Cloudflare Workers
> [!TIP]
> Some modules are not supported in Cloudflare Workers which require Node.js APIs.
```ts
// add `OPENAI_API_KEY` to the `.dev.vars` file
interface Env {
OPENAI_API_KEY: string;
}
export default {
async fetch(
request: Request,
env: Env,
ctx: ExecutionContext,
): Promise<Response> {
const { OpenAIAgent, OpenAI } = await import("@llamaindex/openai");
const text = await request.text();
const agent = new OpenAIAgent({
llm: new OpenAI({
apiKey: env.OPENAI_API_KEY,
}),
tools: [],
});
const responseStream = await agent.chat({
stream: true,
message: text,
});
const textEncoder = new TextEncoder();
const response = responseStream.pipeThrough<Uint8Array>(
new TransformStream({
transform: (chunk, controller) => {
controller.enqueue(textEncoder.encode(chunk.delta));
},
}),
);
return new Response(response);
},
};
```
### Vite
We have some wasm dependencies for better performance. You can use `vite-plugin-wasm` to load them.
@@ -204,29 +265,9 @@ export default {
};
```
## Playground
### Tips when using in non-Node.js environments
Check out our NextJS playground at https://llama-playground.vercel.app/. The source is available at https://github.com/run-llama/ts-playground
## Core concepts for getting started:
- [Document](/packages/llamaindex/src/Node.ts): A document represents a text file, PDF file or other contiguous piece of data.
- [Node](/packages/llamaindex/src/Node.ts): The basic data building block. Most commonly, these are parts of the document split into manageable pieces that are small enough to be fed into an embedding model and LLM.
- [Embedding](/packages/llamaindex/src/embeddings/OpenAIEmbedding.ts): Embeddings are sets of floating point numbers which represent the data in a Node. By comparing the similarity of embeddings, we can derive an understanding of the similarity of two pieces of data. One use case is to compare the embedding of a question with the embeddings of our Nodes to see which Nodes may contain the data needed to answer that question. Because the default service context is OpenAI, the default embedding is `OpenAIEmbedding`. If using different models, say through Ollama, use this [Embedding](/packages/llamaindex/src/embeddings/OllamaEmbedding.ts) (see all [here](/packages/llamaindex/src/embeddings)).
- [Indices](/packages/llamaindex/src/indices/): Indices store the Nodes and the embeddings of those nodes. QueryEngines retrieve Nodes from these Indices using embedding similarity.
- [QueryEngine](/packages/llamaindex/src/engines/query/RetrieverQueryEngine.ts): Query engines are what generate the query you put in and give you back the result. Query engines generally combine a pre-built prompt with selected Nodes from your Index to give the LLM the context it needs to answer your query. To build a query engine from your Index (recommended), use the [`asQueryEngine`](/packages/llamaindex/src/indices/BaseIndex.ts) method on your Index. See all query engines [here](/packages/llamaindex/src/engines/query).
- [ChatEngine](/packages/llamaindex/src/engines/chat/SimpleChatEngine.ts): A ChatEngine helps you build a chatbot that will interact with your Indices. See all chat engines [here](/packages/llamaindex/src/engines/chat).
- [SimplePrompt](/packages/llamaindex/src/Prompt.ts): A simple standardized function call definition that takes in inputs and formats them in a template literal. SimplePrompts can be specialized using currying and combined using other SimplePrompt functions.
## Tips when using in non-Node.js environments
When you are importing `llamaindex` in a non-Node.js environment(such as React Server Components, Cloudflare Workers, etc.)
When you are importing `llamaindex` in a non-Node.js environment(such as Vercel Edge, Cloudflare Workers, etc.)
Some classes are not exported from top-level entry file.
The reason is that some classes are only compatible with Node.js runtime,(e.g. `PDFReader`) which uses Node.js specific APIs(like `fs`, `child_process`, `crypto`).
@@ -262,19 +303,31 @@ export async function getDocuments() {
You'll find a complete example with LlamaIndexTS here: https://github.com/run-llama/create_llama_projects/tree/main/nextjs-edge-llamaparse
## Supported LLMs:
## Playground
- OpenAI GPT-3.5-turbo and GPT-4
- Anthropic Claude 3 (Opus, Sonnet, and Haiku) and the legacy models (Claude 2 and Instant)
- Groq LLMs
- Llama2/3 Chat LLMs (70B, 13B, and 7B parameters)
- MistralAI Chat LLMs
- Fireworks Chat LLMs
Check out our NextJS playground at https://llama-playground.vercel.app/. The source is available at https://github.com/run-llama/ts-playground
## Core concepts for getting started:
- [Document](/packages/llamaindex/src/Node.ts): A document represents a text file, PDF file or other contiguous piece of data.
- [Node](/packages/llamaindex/src/Node.ts): The basic data building block. Most commonly, these are parts of the document split into manageable pieces that are small enough to be fed into an embedding model and LLM.
- [Embedding](/packages/llamaindex/src/embeddings/OpenAIEmbedding.ts): Embeddings are sets of floating point numbers which represent the data in a Node. By comparing the similarity of embeddings, we can derive an understanding of the similarity of two pieces of data. One use case is to compare the embedding of a question with the embeddings of our Nodes to see which Nodes may contain the data needed to answer that question. Because the default service context is OpenAI, the default embedding is `OpenAIEmbedding`. If using different models, say through Ollama, use this [Embedding](/packages/llamaindex/src/embeddings/OllamaEmbedding.ts) (see all [here](/packages/llamaindex/src/embeddings)).
- [Indices](/packages/llamaindex/src/indices/): Indices store the Nodes and the embeddings of those nodes. QueryEngines retrieve Nodes from these Indices using embedding similarity.
- [QueryEngine](/packages/llamaindex/src/engines/query/RetrieverQueryEngine.ts): Query engines are what generate the query you put in and give you back the result. Query engines generally combine a pre-built prompt with selected Nodes from your Index to give the LLM the context it needs to answer your query. To build a query engine from your Index (recommended), use the [`asQueryEngine`](/packages/llamaindex/src/indices/BaseIndex.ts) method on your Index. See all query engines [here](/packages/llamaindex/src/engines/query).
- [ChatEngine](/packages/llamaindex/src/engines/chat/SimpleChatEngine.ts): A ChatEngine helps you build a chatbot that will interact with your Indices. See all chat engines [here](/packages/llamaindex/src/engines/chat).
- [SimplePrompt](/packages/llamaindex/src/Prompt.ts): A simple standardized function call definition that takes in inputs and formats them in a template literal. SimplePrompts can be specialized using currying and combined using other SimplePrompt functions.
## Contributing:
We are in the very early days of LlamaIndex.TS. If youre interested in hacking on it with us check out our [contributing guide](/CONTRIBUTING.md)
Please see our [contributing guide](CONTRIBUTING.md) for more information.
You are highly encouraged to contribute to LlamaIndex.TS!
## Bugs? Questions?
## Community
Please join our Discord! https://discord.com/invite/eN6D2HQ4aX
+58
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@@ -1,5 +1,63 @@
# docs
## 0.0.80
### Patch Changes
- Updated dependencies [df441e2]
- llamaindex@0.6.11
## 0.0.79
### Patch Changes
- Updated dependencies [ebc5105]
- Updated dependencies [6cce3b1]
- llamaindex@0.6.10
## 0.0.78
### Patch Changes
- llamaindex@0.6.9
## 0.0.77
### Patch Changes
- Updated dependencies [8b7fdba]
- llamaindex@0.6.8
## 0.0.76
### Patch Changes
- Updated dependencies [23bcc37]
- llamaindex@0.6.7
## 0.0.75
### Patch Changes
- Updated dependencies [d902cc3]
- Updated dependencies [025ffe6]
- Updated dependencies [a659574]
- llamaindex@0.6.6
## 0.0.74
### Patch Changes
- Updated dependencies [e9714db]
- llamaindex@0.6.5
## 0.0.73
### Patch Changes
- Updated dependencies [b48bcc3]
- llamaindex@0.6.4
## 0.0.72
### Patch Changes
+1 -1
View File
@@ -1,6 +1,6 @@
{
"name": "docs",
"version": "0.0.72",
"version": "0.0.80",
"private": true,
"scripts": {
"docusaurus": "docusaurus",
+8
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@@ -0,0 +1,8 @@
{
"extends": ["//"],
"tasks": {
"build": {
"outputs": ["build/**", ".docusaurus/**"]
}
}
}
+1 -1
View File
@@ -18,7 +18,7 @@ import readline from "node:readline/promises";
});
const chatEngine = new SimpleChatEngine({
llm,
chatHistory,
memory: chatHistory,
});
const rl = readline.createInterface({ input, output });
+4 -6
View File
@@ -27,12 +27,10 @@ async function main() {
// Query the index
const queryEngine = index.asQueryEngine();
const stream = await queryEngine.query(
{
query: "What did the author do in college?",
},
true,
);
const stream = await queryEngine.query({
query: "What did the author do in college?",
stream: true,
});
// Output response
for await (const chunk of stream) {
+4 -6
View File
@@ -37,12 +37,10 @@ async function main() {
// Query the index
const queryEngine = index.asQueryEngine();
const stream = await queryEngine.query(
{
query: "What did the author do in college?",
},
true,
);
const stream = await queryEngine.query({
query: "What did the author do in college?",
stream: true,
});
// Output response
for await (const chunk of stream) {
+3 -1
View File
@@ -1,4 +1,5 @@
// call pnpm tsx multimodal/load.ts first to init the storage
import { extractText } from "@llamaindex/core/utils";
import {
ContextChatEngine,
NodeWithScore,
@@ -25,8 +26,9 @@ Settings.callbackManager.on("retrieve-end", (event) => {
const textNodes = nodes.filter(
(node: NodeWithScore) => node.node.type === ObjectType.TEXT,
);
const text = extractText(query);
console.log(
`Retrieved ${textNodes.length} text nodes and ${imageNodes.length} image nodes for query: ${query}`,
`Retrieved ${textNodes.length} text nodes and ${imageNodes.length} image nodes for query: ${text}`,
);
});
+7 -7
View File
@@ -1,3 +1,4 @@
import { extractText } from "@llamaindex/core/utils";
import {
getResponseSynthesizer,
OpenAI,
@@ -16,7 +17,8 @@ Settings.llm = new OpenAI({ model: "gpt-4-turbo", maxTokens: 512 });
// Update callbackManager
Settings.callbackManager.on("retrieve-end", (event) => {
const { nodes, query } = event.detail;
console.log(`Retrieved ${nodes.length} nodes for query: ${query}`);
const text = extractText(query);
console.log(`Retrieved ${nodes.length} nodes for query: ${text}`);
});
async function main() {
@@ -30,12 +32,10 @@ async function main() {
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",
},
true,
);
const stream = await queryEngine.query({
query: "Tell me more about Vincent van Gogh's famous paintings",
stream: true,
});
for await (const chunk of stream) {
process.stdout.write(chunk.response);
}
+3 -1
View File
@@ -9,6 +9,7 @@
"@llamaindex/core": "^0.2.0",
"@notionhq/client": "^2.2.15",
"@pinecone-database/pinecone": "^3.0.2",
"@vercel/postgres": "^0.10.0",
"@zilliz/milvus2-sdk-node": "^2.4.6",
"chromadb": "^1.8.1",
"commander": "^12.1.0",
@@ -16,7 +17,8 @@
"js-tiktoken": "^1.0.14",
"llamaindex": "^0.6.0",
"mongodb": "^6.7.0",
"pathe": "^1.1.2"
"pathe": "^1.1.2",
"postgres": "^3.4.4"
},
"devDependencies": {
"@types/node": "^22.5.1",
+1 -1
View File
@@ -1,4 +1,4 @@
import { createMessageContent } from "@llamaindex/core/utils";
import { createMessageContent } from "@llamaindex/core/response-synthesizers";
import {
Document,
ImageNode,
+9
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@@ -0,0 +1,9 @@
# neon template
PGHOST=
PGDATABASE=
PGUSER=
PGPASSWORD=
ENDPOINT_ID=
# vercel template
POSTGRES_URL=
@@ -1,11 +1,11 @@
// load-docs.ts
import fs from "fs/promises";
import {
PGVectorStore,
SimpleDirectoryReader,
storageContextFromDefaults,
VectorStoreIndex,
} from "llamaindex";
import fs from "node:fs/promises";
async function getSourceFilenames(sourceDir: string) {
return await fs
@@ -40,7 +40,11 @@ async function main(args: any) {
const rdr = new SimpleDirectoryReader(callback);
const docs = await rdr.loadData({ directoryPath: sourceDir });
const pgvs = new PGVectorStore();
const pgvs = new PGVectorStore({
clientConfig: {
connectionString: process.env.PG_CONNECTION_STRING,
},
});
pgvs.setCollection(sourceDir);
await pgvs.clearCollection();
+45
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@@ -0,0 +1,45 @@
/* eslint-disable turbo/no-undeclared-env-vars */
import dotenv from "dotenv";
import { Document, PGVectorStore, VectorStoreQueryMode } from "llamaindex";
import postgres from "postgres";
dotenv.config();
const { PGHOST, PGDATABASE, PGUSER, ENDPOINT_ID } = process.env;
const PGPASSWORD = decodeURIComponent(process.env.PGPASSWORD!);
const sql = postgres({
host: PGHOST,
database: PGDATABASE,
username: PGUSER,
password: PGPASSWORD,
port: 5432,
ssl: "require",
connection: {
options: `project=${ENDPOINT_ID}`,
},
});
await sql`CREATE EXTENSION IF NOT EXISTS vector`;
const vectorStore = new PGVectorStore({
dimensions: 3,
client: sql,
});
await vectorStore.add([
new Document({
text: "hello, world",
embedding: [1, 2, 3],
}),
]);
const results = await vectorStore.query({
mode: VectorStoreQueryMode.DEFAULT,
similarityTopK: 1,
queryEmbedding: [1, 2, 3],
});
console.log("result", results);
await sql.end();
+5
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@@ -0,0 +1,5 @@
{
"name": "pg-vector-store",
"type": "module",
"private": true
}
@@ -7,7 +7,11 @@ async function main() {
});
try {
const pgvs = new PGVectorStore();
const pgvs = new PGVectorStore({
clientConfig: {
connectionString: process.env.PG_CONNECTION_STRING,
},
});
// Optional - set your collection name, default is no filter on this field.
// pgvs.setCollection();
+9
View File
@@ -0,0 +1,9 @@
{
"extends": "../../tsconfig.json",
"compilerOptions": {
"outDir": "./dist",
"types": ["node"],
"skipLibCheck": true
},
"include": ["./**/*.ts"]
}
+30
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@@ -0,0 +1,30 @@
// https://vercel.com/docs/storage/vercel-postgres/sdk
import { sql } from "@vercel/postgres";
import dotenv from "dotenv";
import { Document, PGVectorStore, VectorStoreQueryMode } from "llamaindex";
dotenv.config();
await sql`CREATE EXTENSION IF NOT EXISTS vector`;
const vectorStore = new PGVectorStore({
dimensions: 3,
client: sql,
});
await vectorStore.add([
new Document({
text: "hello, world",
embedding: [1, 2, 3],
}),
]);
const results = await vectorStore.query({
mode: VectorStoreQueryMode.DEFAULT,
similarityTopK: 1,
queryEmbedding: [1, 2, 3],
});
console.log("result", results);
await sql.end();
+2 -1
View File
@@ -12,6 +12,7 @@
"e2e": "turbo run e2e",
"test": "turbo run test",
"type-check": "tsc -b --diagnostics",
"circular-check": "madge --circular ./packages/**/**/dist/index.js",
"release": "pnpm run build:release && changeset publish",
"release-snapshot": "pnpm run build:release && changeset publish --tag snapshot",
"new-version": "changeset version && pnpm format:write && pnpm run build:release",
@@ -30,7 +31,7 @@
"madge": "^8.0.0",
"prettier": "^3.3.3",
"prettier-plugin-organize-imports": "^4.0.0",
"turbo": "^2.1.0",
"turbo": "^2.1.2",
"typescript": "^5.6.2"
},
"packageManager": "pnpm@9.5.0",
+59
View File
@@ -1,5 +1,64 @@
# @llamaindex/autotool
## 3.0.11
### Patch Changes
- df441e2: fix: consoleLogger is missing from `@llamaindex/env`
- Updated dependencies [df441e2]
- llamaindex@0.6.11
## 3.0.10
### Patch Changes
- Updated dependencies [ebc5105]
- Updated dependencies [6cce3b1]
- llamaindex@0.6.10
## 3.0.9
### Patch Changes
- llamaindex@0.6.9
## 3.0.8
### Patch Changes
- Updated dependencies [8b7fdba]
- llamaindex@0.6.8
## 3.0.7
### Patch Changes
- Updated dependencies [23bcc37]
- llamaindex@0.6.7
## 3.0.6
### Patch Changes
- Updated dependencies [d902cc3]
- Updated dependencies [025ffe6]
- Updated dependencies [a659574]
- llamaindex@0.6.6
## 3.0.5
### Patch Changes
- Updated dependencies [e9714db]
- llamaindex@0.6.5
## 3.0.4
### Patch Changes
- Updated dependencies [b48bcc3]
- llamaindex@0.6.4
## 3.0.3
### Patch Changes
@@ -1,5 +1,71 @@
# @llamaindex/autotool-01-node-example
## 0.0.20
### Patch Changes
- Updated dependencies [df441e2]
- @llamaindex/autotool@3.0.11
- llamaindex@0.6.11
## 0.0.19
### Patch Changes
- Updated dependencies [ebc5105]
- Updated dependencies [6cce3b1]
- llamaindex@0.6.10
- @llamaindex/autotool@3.0.10
## 0.0.18
### Patch Changes
- llamaindex@0.6.9
- @llamaindex/autotool@3.0.9
## 0.0.17
### Patch Changes
- Updated dependencies [8b7fdba]
- llamaindex@0.6.8
- @llamaindex/autotool@3.0.8
## 0.0.16
### Patch Changes
- Updated dependencies [23bcc37]
- llamaindex@0.6.7
- @llamaindex/autotool@3.0.7
## 0.0.15
### Patch Changes
- Updated dependencies [d902cc3]
- Updated dependencies [025ffe6]
- Updated dependencies [a659574]
- llamaindex@0.6.6
- @llamaindex/autotool@3.0.6
## 0.0.14
### Patch Changes
- Updated dependencies [e9714db]
- llamaindex@0.6.5
- @llamaindex/autotool@3.0.5
## 0.0.13
### Patch Changes
- Updated dependencies [b48bcc3]
- llamaindex@0.6.4
- @llamaindex/autotool@3.0.4
## 0.0.12
### Patch Changes
@@ -13,5 +13,5 @@
"scripts": {
"start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
},
"version": "0.0.12"
"version": "0.0.20"
}
@@ -1,5 +1,71 @@
# @llamaindex/autotool-02-next-example
## 0.1.64
### Patch Changes
- Updated dependencies [df441e2]
- @llamaindex/autotool@3.0.11
- llamaindex@0.6.11
## 0.1.63
### Patch Changes
- Updated dependencies [ebc5105]
- Updated dependencies [6cce3b1]
- llamaindex@0.6.10
- @llamaindex/autotool@3.0.10
## 0.1.62
### Patch Changes
- llamaindex@0.6.9
- @llamaindex/autotool@3.0.9
## 0.1.61
### Patch Changes
- Updated dependencies [8b7fdba]
- llamaindex@0.6.8
- @llamaindex/autotool@3.0.8
## 0.1.60
### Patch Changes
- Updated dependencies [23bcc37]
- llamaindex@0.6.7
- @llamaindex/autotool@3.0.7
## 0.1.59
### Patch Changes
- Updated dependencies [d902cc3]
- Updated dependencies [025ffe6]
- Updated dependencies [a659574]
- llamaindex@0.6.6
- @llamaindex/autotool@3.0.6
## 0.1.58
### Patch Changes
- Updated dependencies [e9714db]
- llamaindex@0.6.5
- @llamaindex/autotool@3.0.5
## 0.1.57
### Patch Changes
- Updated dependencies [b48bcc3]
- llamaindex@0.6.4
- @llamaindex/autotool@3.0.4
## 0.1.56
### Patch Changes
@@ -1,7 +1,7 @@
{
"name": "@llamaindex/autotool-02-next-example",
"private": true,
"version": "0.1.56",
"version": "0.1.64",
"scripts": {
"dev": "next dev",
"build": "next build",
+1 -1
View File
@@ -1,7 +1,7 @@
{
"name": "@llamaindex/autotool",
"type": "module",
"version": "3.0.3",
"version": "3.0.11",
"description": "auto transpile your JS function to LLM Agent compatible",
"files": [
"dist",
+15
View File
@@ -1,5 +1,20 @@
# @llamaindex/cloud
## 0.2.9
### Patch Changes
- df441e2: fix: consoleLogger is missing from `@llamaindex/env`
- Updated dependencies [df441e2]
- @llamaindex/core@0.2.8
- @llamaindex/env@0.1.13
## 0.2.8
### Patch Changes
- ac41ed3: feat: bump cloud sdk version
## 0.2.7
### Patch Changes
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+7890 -4744
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File diff suppressed because it is too large Load Diff
+20 -19
View File
@@ -1,6 +1,6 @@
{
"name": "@llamaindex/cloud",
"version": "0.2.7",
"version": "0.2.9",
"type": "module",
"license": "MIT",
"scripts": {
@@ -9,54 +9,55 @@
},
"files": [
"openapi.json",
"dist"
"./api",
"./reader"
],
"exports": {
"./openapi.json": "./openapi.json",
"./api": {
"require": {
"types": "./dist/api.d.cts",
"default": "./dist/api.cjs"
"types": "./api/dist/index.d.cts",
"default": "./api/dist/index.cjs"
},
"import": {
"types": "./dist/api.d.ts",
"default": "./dist/api.js"
"types": "./api/dist/index.d.ts",
"default": "./api/dist/index.js"
},
"default": {
"types": "./dist/api.d.ts",
"default": "./dist/api.js"
"types": "./api/dist/index.d.ts",
"default": "./api/dist/index.js"
}
},
"./reader": {
"require": {
"types": "./dist/reader.d.cts",
"default": "./dist/reader.cjs"
"types": "./reader/dist/index.d.cts",
"default": "./reader/dist/index.cjs"
},
"import": {
"types": "./dist/reader.d.ts",
"default": "./dist/reader.js"
"types": "./reader/dist/index.d.ts",
"default": "./reader/dist/index.js"
},
"default": {
"types": "./dist/reader.d.ts",
"default": "./dist/reader.js"
"types": "./reader/dist/index.d.ts",
"default": "./reader/dist/index.js"
}
}
},
"repository": {
"type": "git",
"url": "https://github.com/himself65/LlamaIndexTS.git",
"url": "https://github.com/run-llama/LlamaIndexTS.git",
"directory": "packages/cloud"
},
"devDependencies": {
"@hey-api/client-fetch": "^0.2.4",
"@hey-api/openapi-ts": "^0.53.0",
"@llamaindex/core": "workspace:^0.2.3",
"@llamaindex/env": "workspace:^0.1.11",
"@llamaindex/core": "workspace:^0.2.8",
"@llamaindex/env": "workspace:^0.1.13",
"bunchee": "5.3.2"
},
"peerDependencies": {
"@llamaindex/core": "workspace:^0.2.3",
"@llamaindex/env": "workspace:^0.1.11"
"@llamaindex/core": "workspace:^0.2.8",
"@llamaindex/env": "workspace:^0.1.13"
},
"dependencies": {
"magic-bytes.js": "^1.10.0"
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+16 -7
View File
@@ -170,6 +170,15 @@ export class LlamaParseReader extends FileReader {
vendorMultimodalModelName?: string | undefined;
// The API key for the multimodal API. Can also be set as an env variable: LLAMA_CLOUD_VENDOR_MULTIMODAL_API_KEY
vendorMultimodalApiKey?: string | undefined;
webhookUrl?: string | undefined;
premiumMode?: boolean | undefined;
takeScreenshot?: boolean | undefined;
disableOcr?: boolean | undefined;
disableReconstruction?: boolean | undefined;
inputS3Path?: string | undefined;
outputS3PathPrefix?: string | undefined;
// numWorkers is implemented in SimpleDirectoryReader
stdout?: WriteStream | undefined;
@@ -258,13 +267,13 @@ export class LlamaParseReader extends FileReader {
use_vendor_multimodal_model: this.useVendorMultimodalModel,
vendor_multimodal_model_name: this.vendorMultimodalModelName,
vendor_multimodal_api_key: this.vendorMultimodalApiKey,
// fixme: does these fields need to be set?
webhook_url: undefined,
take_screenshot: undefined,
disable_ocr: undefined,
disable_reconstruction: undefined,
input_s3_path: undefined,
output_s3_path_prefix: undefined,
premium_mode: this.premiumMode,
webhook_url: this.webhookUrl,
take_screenshot: this.takeScreenshot,
disable_ocr: this.disableOcr,
disable_reconstruction: this.disableReconstruction,
input_s3_path: this.inputS3Path,
output_s3_path_prefix: this.outputS3PathPrefix,
} satisfies {
[Key in keyof Body_upload_file_api_v1_parsing_upload_post]-?:
| Body_upload_file_api_v1_parsing_upload_post[Key]
+8
View File
@@ -0,0 +1,8 @@
{
"extends": ["//"],
"tasks": {
"build": {
"outputs": ["**/dist/**", "src/client/**"]
}
}
}
+39
View File
@@ -1,5 +1,44 @@
# @llamaindex/community
## 0.0.42
### Patch Changes
- df441e2: fix: consoleLogger is missing from `@llamaindex/env`
- Updated dependencies [df441e2]
- @llamaindex/core@0.2.8
- @llamaindex/env@0.1.13
## 0.0.41
### Patch Changes
- Updated dependencies [6cce3b1]
- @llamaindex/core@0.2.7
## 0.0.40
### Patch Changes
- 50e6b57: feat: add Amazon Bedrock Retriever
- Updated dependencies [8b7fdba]
- @llamaindex/core@0.2.6
## 0.0.39
### Patch Changes
- Updated dependencies [d902cc3]
- @llamaindex/core@0.2.5
## 0.0.38
### Patch Changes
- Updated dependencies [b48bcc3]
- @llamaindex/core@0.2.4
- @llamaindex/env@0.1.12
## 0.0.37
### Patch Changes
+1
View File
@@ -7,6 +7,7 @@
- Bedrock support for the Anthropic Claude Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock)
- Bedrock support for the Meta LLama 2, 3 and 3.1 Models [usage](https://ts.llamaindex.ai/modules/llms/available_llms/bedrock)
- Meta LLama3.1 405b tool call support
- Bedrock support for querying Knowledge Base
## LICENSE
+2 -1
View File
@@ -1,7 +1,7 @@
{
"name": "@llamaindex/community",
"description": "Community package for LlamaIndexTS",
"version": "0.0.37",
"version": "0.0.42",
"type": "module",
"types": "dist/type/index.d.ts",
"main": "dist/cjs/index.js",
@@ -47,6 +47,7 @@
},
"dependencies": {
"@aws-sdk/client-bedrock-runtime": "^3.642.0",
"@aws-sdk/client-bedrock-agent-runtime": "^3.642.0",
"@llamaindex/core": "workspace:*",
"@llamaindex/env": "workspace:*"
}
+1
View File
@@ -3,3 +3,4 @@ export {
BEDROCK_MODEL_MAX_TOKENS,
Bedrock,
} from "./llm/bedrock/index.js";
export { AmazonKnowledgeBaseRetriever } from "./retrievers/bedrock.js";
+2 -1
View File
@@ -16,7 +16,7 @@ import {
ToolCallLLM,
type ToolCallLLMMessageOptions,
} from "@llamaindex/core/llms";
import { streamConverter, wrapLLMEvent } from "@llamaindex/core/utils";
import { streamConverter } from "@llamaindex/core/utils";
import {
type BedrockAdditionalChatOptions,
type BedrockChatStreamResponse,
@@ -24,6 +24,7 @@ import {
} from "./provider";
import { mapMessageContentToMessageContentDetails } from "./utils";
import { wrapLLMEvent } from "@llamaindex/core/decorator";
import { AnthropicProvider } from "./anthropic/provider";
import { MetaProvider } from "./meta/provider";
@@ -0,0 +1,165 @@
import type { KnowledgeBaseVectorSearchConfiguration } from "@aws-sdk/client-bedrock-agent-runtime";
import {
BedrockAgentRuntimeClient,
type BedrockAgentRuntimeClientConfig,
type RetrievalFilter,
RetrieveCommand,
type SearchType,
} from "@aws-sdk/client-bedrock-agent-runtime";
import type { QueryBundle } from "@llamaindex/core/query-engine";
import { BaseRetriever } from "@llamaindex/core/retriever";
import { Document, type NodeWithScore } from "@llamaindex/core/schema";
import { extractText } from "@llamaindex/core/utils";
/**
* Interface for the arguments required to initialize an
* AmazonKnowledgeBaseRetriever instance.
*/
export interface AmazonKnowledgeBaseRetrieverArgs {
knowledgeBaseId: string;
topK: number;
region: string;
clientOptions?: BedrockAgentRuntimeClientConfig;
filter?: RetrievalFilter;
overrideSearchType?: SearchType;
}
/**
* Class for interacting with Amazon Bedrock Knowledge Bases, a RAG workflow oriented service
* Extends the BaseRetriever class.
* @example
* ```typescript
* const retriever = new AmazonKnowledgeBaseRetriever({
* topK: 10,
* knowledgeBaseId: "YOUR_KNOWLEDGE_BASE_ID",
* region: "us-east-2",
* clientOptions: {
* credentials: {
* accessKeyId: "YOUR_ACCESS_KEY_ID",
* secretAccessKey: "YOUR_SECRET_ACCESS_KEY",
* },
* },
* });
*
* const docs = await retriever.retrieve({query: "How are clouds formed?"});
* ```
*/
export class AmazonKnowledgeBaseRetriever extends BaseRetriever {
static lc_name() {
return "AmazonKnowledgeBaseRetriever";
}
lc_namespace = ["llamaindex", "retrievers", "amazon_bedrock_knowledge_base"];
knowledgeBaseId: string;
topK: number;
bedrockAgentRuntimeClient: BedrockAgentRuntimeClient;
filter: RetrievalFilter | undefined;
overrideSearchType: SearchType | undefined;
constructor({
knowledgeBaseId,
topK = 10,
clientOptions,
region,
filter,
overrideSearchType,
}: AmazonKnowledgeBaseRetrieverArgs) {
super();
this.topK = topK;
this.filter = filter;
this.overrideSearchType = overrideSearchType;
this.bedrockAgentRuntimeClient = new BedrockAgentRuntimeClient({
region,
...clientOptions,
});
this.knowledgeBaseId = knowledgeBaseId;
}
/**
* Cleans the result text by replacing sequences of whitespace with a
* single space and removing ellipses.
* @param resText The result text to clean.
* @returns The cleaned result text.
*/
cleanResult(resText: string) {
const res = resText.replace(/\s+/g, " ").replace(/\.\.\./g, "");
return res;
}
async queryKnowledgeBase(
query: QueryBundle,
topK: number,
filter?: RetrievalFilter,
overrideSearchType?: SearchType,
): Promise<NodeWithScore[]> {
const retrieveCommand = new RetrieveCommand({
knowledgeBaseId: this.knowledgeBaseId,
retrievalQuery: {
text: extractText(query),
},
retrievalConfiguration: {
vectorSearchConfiguration: {
numberOfResults: topK,
overrideSearchType,
filter,
} as KnowledgeBaseVectorSearchConfiguration,
},
});
const retrieveResponse =
await this.bedrockAgentRuntimeClient.send(retrieveCommand);
return (
retrieveResponse.retrievalResults?.map((result) => {
let source;
switch (result.location?.type) {
case "CONFLUENCE":
source = result.location?.confluenceLocation?.url;
break;
case "S3":
source = result.location?.s3Location?.uri;
break;
case "SALESFORCE":
source = result.location?.salesforceLocation?.url;
break;
case "SHAREPOINT":
source = result.location?.sharePointLocation?.url;
break;
case "WEB":
source = result.location?.webLocation?.url;
break;
default:
source = result.location?.s3Location?.uri;
break;
}
return {
node: new Document({
text: this.cleanResult(result.content?.text || ""),
metadata: {
source,
score: result.score,
...result.metadata,
},
}),
score: result.score ?? 1.0,
};
}) ?? []
);
}
async _retrieve(query: QueryBundle): Promise<NodeWithScore[]> {
return await this.queryKnowledgeBase(
query,
this.topK,
this.filter,
this.overrideSearchType,
);
}
}
+40
View File
@@ -1,5 +1,45 @@
# @llamaindex/core
## 0.2.8
### Patch Changes
- df441e2: fix: consoleLogger is missing from `@llamaindex/env`
- Updated dependencies [df441e2]
- @llamaindex/env@0.1.13
## 0.2.7
### Patch Changes
- 6cce3b1: feat: support `npm:postgres`
## 0.2.6
### Patch Changes
- 8b7fdba: refactor: move chat engine & retriever into core.
- `chatHistory` in BaseChatEngine now returns `ChatMessage[] | Promise<ChatMessage[]>`, instead of `BaseMemory`
- update `retrieve-end` type
## 0.2.5
### Patch Changes
- d902cc3: Fix context not being sent using ContextChatEngine
## 0.2.4
### Patch Changes
- b48bcc3: feat: add `load-transformers` event type when loading `@xenova/transformers` module
This would benefit user who want to customize the transformer env.
- Updated dependencies [b48bcc3]
- @llamaindex/env@0.1.12
## 0.2.3
### Patch Changes
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+175 -88
View File
@@ -1,208 +1,295 @@
{
"name": "@llamaindex/core",
"type": "module",
"version": "0.2.3",
"version": "0.2.8",
"description": "LlamaIndex Core Module",
"exports": {
"./node-parser": {
"./agent": {
"require": {
"types": "./dist/node-parser/index.d.cts",
"default": "./dist/node-parser/index.cjs"
"types": "./agent/dist/index.d.cts",
"default": "./agent/dist/index.cjs"
},
"import": {
"types": "./dist/node-parser/index.d.ts",
"default": "./dist/node-parser/index.js"
"types": "./agent/dist/index.d.ts",
"default": "./agent/dist/index.js"
},
"default": {
"types": "./dist/node-parser/index.d.ts",
"default": "./dist/node-parser/index.js"
"types": "./agent/dist/index.d.ts",
"default": "./agent/dist/index.js"
}
},
"./objects": {
"require": {
"types": "./objects/dist/index.d.cts",
"default": "./objects/dist/index.cjs"
},
"import": {
"types": "./objects/dist/index.d.ts",
"default": "./objects/dist/index.js"
},
"default": {
"types": "./objects/dist/index.d.ts",
"default": "./objects/dist/index.js"
}
},
"./node-parser": {
"require": {
"types": "./node-parser/dist/index.d.cts",
"default": "./node-parser/dist/index.cjs"
},
"import": {
"types": "./node-parser/dist/index.d.ts",
"default": "./node-parser/dist/index.js"
},
"default": {
"types": "./node-parser/dist/index.d.ts",
"default": "./node-parser/dist/index.js"
}
},
"./query-engine": {
"require": {
"types": "./dist/query-engine/index.d.cts",
"default": "./dist/query-engine/index.cjs"
"types": "./query-engine/dist/index.d.cts",
"default": "./query-engine/dist/index.cjs"
},
"import": {
"types": "./dist/query-engine/index.d.ts",
"default": "./dist/query-engine/index.js"
"types": "./query-engine/dist/index.d.ts",
"default": "./query-engine/dist/index.js"
},
"default": {
"types": "./dist/query-engine/index.d.ts",
"default": "./dist/query-engine/index.js"
"types": "./query-engine/dist/index.d.ts",
"default": "./query-engine/dist/index.js"
}
},
"./llms": {
"require": {
"types": "./dist/llms/index.d.cts",
"default": "./dist/llms/index.cjs"
"types": "./llms/dist/index.d.cts",
"default": "./llms/dist/index.cjs"
},
"import": {
"types": "./dist/llms/index.d.ts",
"default": "./dist/llms/index.js"
"types": "./llms/dist/index.d.ts",
"default": "./llms/dist/index.js"
},
"default": {
"types": "./dist/llms/index.d.ts",
"default": "./dist/llms/index.js"
"types": "./llms/dist/index.d.ts",
"default": "./llms/dist/index.js"
}
},
"./decorator": {
"require": {
"types": "./dist/decorator/index.d.cts",
"default": "./dist/decorator/index.cjs"
"types": "./decorator/dist/index.d.cts",
"default": "./decorator/dist/index.cjs"
},
"import": {
"types": "./dist/decorator/index.d.ts",
"default": "./dist/decorator/index.js"
"types": "./decorator/dist/index.d.ts",
"default": "./decorator/dist/index.js"
},
"default": {
"types": "./dist/decorator/index.d.ts",
"default": "./dist/decorator/index.js"
"types": "./decorator/dist/index.d.ts",
"default": "./decorator/dist/index.js"
}
},
"./embeddings": {
"require": {
"types": "./dist/embeddings/index.d.cts",
"default": "./dist/embeddings/index.cjs"
"types": "./embeddings/dist/index.d.cts",
"default": "./embeddings/dist/index.cjs"
},
"import": {
"types": "./dist/embeddings/index.d.ts",
"default": "./dist/embeddings/index.js"
"types": "./embeddings/dist/index.d.ts",
"default": "./embeddings/dist/index.js"
},
"default": {
"types": "./dist/embeddings/index.d.ts",
"default": "./dist/embeddings/index.js"
"types": "./embeddings/dist/index.d.ts",
"default": "./embeddings/dist/index.js"
}
},
"./global": {
"require": {
"types": "./dist/global/index.d.cts",
"default": "./dist/global/index.cjs"
"types": "./global/dist/index.d.cts",
"default": "./global/dist/index.cjs"
},
"import": {
"types": "./dist/global/index.d.ts",
"default": "./dist/global/index.js"
"types": "./global/dist/index.d.ts",
"default": "./global/dist/index.js"
},
"default": {
"types": "./dist/global/index.d.ts",
"default": "./dist/global/index.js"
"types": "./global/dist/index.d.ts",
"default": "./global/dist/index.js"
}
},
"./schema": {
"require": {
"types": "./dist/schema/index.d.cts",
"default": "./dist/schema/index.cjs"
"types": "./schema/dist/index.d.cts",
"default": "./schema/dist/index.cjs"
},
"import": {
"types": "./dist/schema/index.d.ts",
"default": "./dist/schema/index.js"
"types": "./schema/dist/index.d.ts",
"default": "./schema/dist/index.js"
},
"default": {
"types": "./dist/schema/index.d.ts",
"default": "./dist/schema/index.js"
"types": "./schema/dist/index.d.ts",
"default": "./schema/dist/index.js"
}
},
"./utils": {
"require": {
"types": "./dist/utils/index.d.cts",
"default": "./dist/utils/index.cjs"
"types": "./utils/dist/index.d.cts",
"default": "./utils/dist/index.cjs"
},
"import": {
"types": "./dist/utils/index.d.ts",
"default": "./dist/utils/index.js"
"types": "./utils/dist/index.d.ts",
"default": "./utils/dist/index.js"
},
"default": {
"types": "./dist/utils/index.d.ts",
"default": "./dist/utils/index.js"
"types": "./utils/dist/index.d.ts",
"default": "./utils/dist/index.js"
}
},
"./prompts": {
"require": {
"types": "./dist/prompts/index.d.cts",
"default": "./dist/prompts/index.cjs"
"types": "./prompts/dist/index.d.cts",
"default": "./prompts/dist/index.cjs"
},
"import": {
"types": "./dist/prompts/index.d.ts",
"default": "./dist/prompts/index.js"
"types": "./prompts/dist/index.d.ts",
"default": "./prompts/dist/index.js"
},
"default": {
"types": "./dist/prompts/index.d.ts",
"default": "./dist/prompts/index.js"
"types": "./prompts/dist/index.d.ts",
"default": "./prompts/dist/index.js"
}
},
"./indices": {
"require": {
"types": "./dist/indices/index.d.cts",
"default": "./dist/indices/index.cjs"
"types": "./indices/dist/index.d.cts",
"default": "./indices/dist/index.cjs"
},
"import": {
"types": "./dist/indices/index.d.ts",
"default": "./dist/indices/index.js"
"types": "./indices/dist/index.d.ts",
"default": "./indices/dist/index.js"
},
"default": {
"types": "./dist/indices/index.d.ts",
"default": "./dist/indices/index.js"
"types": "./indices/dist/index.d.ts",
"default": "./indices/dist/index.js"
}
},
"./workflow": {
"require": {
"types": "./dist/workflow/index.d.cts",
"default": "./dist/workflow/index.cjs"
"types": "./workflow/dist/index.d.cts",
"default": "./workflow/dist/index.cjs"
},
"import": {
"types": "./dist/workflow/index.d.ts",
"default": "./dist/workflow/index.js"
"types": "./workflow/dist/index.d.ts",
"default": "./workflow/dist/index.js"
},
"default": {
"types": "./dist/workflow/index.d.ts",
"default": "./dist/workflow/index.js"
"types": "./workflow/dist/index.d.ts",
"default": "./workflow/dist/index.js"
}
},
"./memory": {
"require": {
"types": "./dist/memory/index.d.cts",
"default": "./dist/memory/index.cjs"
"types": "./memory/dist/index.d.cts",
"default": "./memory/dist/index.cjs"
},
"import": {
"types": "./dist/memory/index.d.ts",
"default": "./dist/memory/index.js"
"types": "./memory/dist/index.d.ts",
"default": "./memory/dist/index.js"
},
"default": {
"types": "./dist/memory/index.d.ts",
"default": "./dist/memory/index.js"
"types": "./memory/dist/index.d.ts",
"default": "./memory/dist/index.js"
}
},
"./storage/chat-store": {
"require": {
"types": "./dist/storage/chat-store/index.d.cts",
"default": "./dist/storage/chat-store/index.cjs"
"types": "./storage/chat-store/dist/index.d.cts",
"default": "./storage/chat-store/dist/index.cjs"
},
"import": {
"types": "./dist/storage/chat-store/index.d.ts",
"default": "./dist/storage/chat-store/index.js"
"types": "./storage/chat-store/dist/index.d.ts",
"default": "./storage/chat-store/dist/index.js"
},
"default": {
"types": "./dist/storage/chat-store/index.d.ts",
"default": "./dist/storage/chat-store/index.js"
"types": "./storage/chat-store/dist/index.d.ts",
"default": "./storage/chat-store/dist/index.js"
}
},
"./response-synthesizers": {
"require": {
"types": "./dist/response-synthesizers/index.d.cts",
"default": "./dist/response-synthesizers/index.cjs"
"types": "./response-synthesizers/dist/index.d.cts",
"default": "./response-synthesizers/dist/index.cjs"
},
"import": {
"types": "./dist/response-synthesizers/index.d.ts",
"default": "./dist/response-synthesizers/index.js"
"types": "./response-synthesizers/dist/index.d.ts",
"default": "./response-synthesizers/dist/index.js"
},
"default": {
"types": "./dist/response-synthesizers/index.d.ts",
"default": "./dist/response-synthesizers/index.js"
"types": "./response-synthesizers/dist/index.d.ts",
"default": "./response-synthesizers/dist/index.js"
}
},
"./chat-engine": {
"require": {
"types": "./chat-engine/dist/index.d.cts",
"default": "./chat-engine/dist/index.cjs"
},
"import": {
"types": "./chat-engine/dist/index.d.ts",
"default": "./chat-engine/dist/index.js"
},
"default": {
"types": "./chat-engine/dist/index.d.ts",
"default": "./chat-engine/dist/index.js"
}
},
"./retriever": {
"require": {
"types": "./retriever/dist/index.d.cts",
"default": "./retriever/dist/index.cjs"
},
"import": {
"types": "./retriever/dist/index.d.ts",
"default": "./retriever/dist/index.js"
},
"default": {
"types": "./retriever/dist/index.d.ts",
"default": "./retriever/dist/index.js"
}
},
"./vector-store": {
"require": {
"types": "./dist/vector-store/index.d.cts",
"default": "./dist/vector-store/index.cjs"
},
"import": {
"types": "./dist/vector-store/index.d.ts",
"default": "./dist/vector-store/index.js"
},
"default": {
"types": "./dist/vector-store/index.d.ts",
"default": "./dist/vector-store/index.js"
}
}
},
"files": [
"dist"
"./agent",
"./objects",
"./node-parser",
"./query-engine",
"./llms",
"./decorator",
"./embeddings",
"./global",
"./schema",
"./utils",
"./prompts",
"./indices",
"./workflow",
"./memory",
"./storage",
"./response-synthesizers",
"./chat-engine",
"./retriever"
],
"scripts": {
"dev": "bunchee --watch",
@@ -211,7 +298,7 @@
"repository": {
"type": "git",
"directory": "packages/core",
"url": "https://github.com/himself65/LlamaIndexTS.git"
"url": "https://github.com/run-llama/LlamaIndexTS.git"
},
"devDependencies": {
"@edge-runtime/vm": "^4.0.3",
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
@@ -1,23 +1,21 @@
import { consoleLogger, emptyLogger, randomUUID } from "@llamaindex/env";
import {
BaseChatEngine,
type NonStreamingChatEngineParams,
type StreamingChatEngineParams,
} from "../chat-engine";
import { wrapEventCaller } from "../decorator";
import { Settings } from "../global";
import type {
BaseToolWithCall,
ChatMessage,
LLM,
MessageContent,
ToolOutput,
} from "@llamaindex/core/llms";
import { BaseMemory } from "@llamaindex/core/memory";
import { EngineResponse } from "@llamaindex/core/schema";
import { wrapEventCaller } from "@llamaindex/core/utils";
import { randomUUID } from "@llamaindex/env";
import { Settings } from "../Settings.js";
import {
type ChatEngine,
type ChatEngineParamsNonStreaming,
type ChatEngineParamsStreaming,
} from "../engines/chat/index.js";
import { consoleLogger, emptyLogger } from "../internal/logger.js";
import { isReadableStream } from "../internal/utils.js";
import { ObjectRetriever } from "../objects/index.js";
} from "../llms";
import { BaseMemory } from "../memory";
import type { ObjectRetriever } from "../objects";
import { EngineResponse } from "../schema";
import type {
AgentTaskContext,
TaskHandler,
@@ -207,8 +205,7 @@ export abstract class AgentRunner<
>
? AdditionalMessageOptions
: never,
> implements ChatEngine
{
> extends BaseChatEngine {
readonly #llm: AI;
readonly #tools:
| BaseToolWithCall[]
@@ -259,6 +256,7 @@ export abstract class AgentRunner<
protected constructor(
params: AgentRunnerParams<AI, Store, AdditionalMessageOptions>,
) {
super();
const { llm, chatHistory, systemPrompt, runner, tools, verbose } = params;
this.#llm = llm;
this.#chatHistory = chatHistory;
@@ -345,20 +343,19 @@ export abstract class AgentRunner<
});
}
async chat(params: ChatEngineParamsNonStreaming): Promise<EngineResponse>;
async chat(params: NonStreamingChatEngineParams): Promise<EngineResponse>;
async chat(
params: ChatEngineParamsStreaming,
params: StreamingChatEngineParams,
): Promise<ReadableStream<EngineResponse>>;
@wrapEventCaller
async chat(
params: ChatEngineParamsNonStreaming | ChatEngineParamsStreaming,
params: NonStreamingChatEngineParams | StreamingChatEngineParams,
): Promise<EngineResponse | ReadableStream<EngineResponse>> {
let chatHistory: ChatMessage<AdditionalMessageOptions>[] = [];
if (params.chatHistory instanceof BaseMemory) {
chatHistory = (await params.chatHistory.getMessages(
params.message,
)) as ChatMessage<AdditionalMessageOptions>[];
chatHistory =
(await params.chatHistory.getMessages()) as ChatMessage<AdditionalMessageOptions>[];
} else {
chatHistory =
params.chatHistory as ChatMessage<AdditionalMessageOptions>[];
@@ -375,7 +372,7 @@ export abstract class AgentRunner<
this.#chatHistory = [...stepOutput.taskStep.context.store.messages];
if (stepOutput.isLast) {
const { output } = stepOutput;
if (isReadableStream(output)) {
if (output instanceof ReadableStream) {
return output.pipeThrough<EngineResponse>(
new TransformStream({
transform(chunk, controller) {
+11
View File
@@ -0,0 +1,11 @@
export { AgentRunner, AgentWorker, type AgentParamsBase } from "./base.js";
export { LLMAgent, LLMAgentWorker, type LLMAgentParams } from "./llm.js";
export type { AgentEndEvent, AgentStartEvent, TaskHandler } from "./types.js";
export {
callTool,
consumeAsyncIterable,
createReadableStream,
stepTools,
stepToolsStreaming,
validateAgentParams,
} from "./utils.js";
@@ -1,6 +1,6 @@
import type { BaseToolWithCall, LLM } from "@llamaindex/core/llms";
import { ObjectRetriever } from "../objects/index.js";
import { Settings } from "../Settings.js";
import { Settings } from "../global";
import type { BaseToolWithCall, LLM } from "../llms";
import { ObjectRetriever } from "../objects";
import { AgentRunner, AgentWorker, type AgentParamsBase } from "./base.js";
import { validateAgentParams } from "./utils.js";
@@ -1,3 +1,5 @@
import type { Logger } from "@llamaindex/env";
import type { UUID } from "../global";
import type {
BaseToolWithCall,
ChatMessage,
@@ -6,9 +8,7 @@ import type {
LLM,
MessageContent,
ToolOutput,
} from "@llamaindex/core/llms";
import type { Logger } from "../internal/logger.js";
import type { UUID } from "../types.js";
} from "../llms";
export type AgentTaskContext<
Model extends LLM,
@@ -1,8 +1,6 @@
import {
type JSONObject,
type JSONValue,
Settings,
} from "@llamaindex/core/global";
import type { Logger } from "@llamaindex/env";
import { z } from "zod";
import { type JSONObject, type JSONValue, Settings } from "../global";
import type {
BaseTool,
ChatMessage,
@@ -14,15 +12,13 @@ import type {
ToolCall,
ToolCallLLMMessageOptions,
ToolOutput,
} from "@llamaindex/core/llms";
import { baseToolWithCallSchema } from "@llamaindex/core/schema";
import { z } from "zod";
import type { Logger } from "../internal/logger.js";
} from "../llms";
import { baseToolWithCallSchema } from "../schema";
import {
isAsyncIterable,
prettifyError,
stringifyJSONToMessageContent,
} from "../internal/utils.js";
} from "../utils";
import type { AgentParamsBase } from "./base.js";
import type { TaskHandler } from "./types.js";
+36
View File
@@ -0,0 +1,36 @@
import type { ChatMessage, MessageContent } from "../llms";
import type { BaseMemory } from "../memory";
import { EngineResponse } from "../schema";
export interface BaseChatEngineParams<
AdditionalMessageOptions extends object = object,
> {
message: MessageContent;
/**
* Optional chat history if you want to customize the chat history.
*/
chatHistory?:
| ChatMessage<AdditionalMessageOptions>[]
| BaseMemory<AdditionalMessageOptions>;
}
export interface StreamingChatEngineParams<
AdditionalMessageOptions extends object = object,
> extends BaseChatEngineParams<AdditionalMessageOptions> {
stream: true;
}
export interface NonStreamingChatEngineParams<
AdditionalMessageOptions extends object = object,
> extends BaseChatEngineParams<AdditionalMessageOptions> {
stream?: false;
}
export abstract class BaseChatEngine {
abstract chat(params: NonStreamingChatEngineParams): Promise<EngineResponse>;
abstract chat(
params: StreamingChatEngineParams,
): Promise<AsyncIterable<EngineResponse>>;
abstract chatHistory: ChatMessage[] | Promise<ChatMessage[]>;
}
@@ -0,0 +1,48 @@
import { AsyncLocalStorage } from "@llamaindex/env";
import { withEventCaller } from "../global";
import { isAsyncIterable, isIterable } from "../utils";
export function wrapEventCaller<This, Result, Args extends unknown[]>(
originalMethod: (this: This, ...args: Args) => Result,
context: ClassMethodDecoratorContext<object>,
) {
const name = context.name;
context.addInitializer(function () {
// @ts-expect-error
const fn = this[name].bind(this);
// @ts-expect-error
this[name] = (...args: unknown[]) => {
return withEventCaller(this, () => fn(...args));
};
});
return function (this: This, ...args: Args): Result {
const result = originalMethod.call(this, ...args);
// patch for iterators because AsyncLocalStorage doesn't work with them
if (isAsyncIterable(result)) {
const iter = result[Symbol.asyncIterator]();
const snapshot = AsyncLocalStorage.snapshot();
return (async function* asyncGeneratorWrapper() {
while (true) {
const { value, done } = await snapshot(() => iter.next());
if (done) {
break;
}
yield value;
}
})() as Result;
} else if (isIterable(result)) {
const iter = result[Symbol.iterator]();
const snapshot = AsyncLocalStorage.snapshot();
return (function* generatorWrapper() {
while (true) {
const { value, done } = snapshot(() => iter.next());
if (done) {
break;
}
yield value;
}
})() as Result;
}
return result;
};
}
+3 -67
View File
@@ -1,67 +1,3 @@
import { getEnv } from "@llamaindex/env";
import { Settings } from "../global";
import type { BaseNode } from "../schema/node";
const emitOnce = false;
export function chunkSizeCheck<
This extends { id_: string },
Args extends any[],
Return,
>(
contentGetter: (this: This, ...args: Args) => string,
_context: ClassMethodDecoratorContext<
This,
(this: This, ...args: Args) => Return
>,
) {
return function (this: This, ...args: Args) {
const content = contentGetter.call(this, ...args);
const chunkSize = Settings.chunkSize;
const enableChunkSizeCheck = getEnv("ENABLE_CHUNK_SIZE_CHECK") === "true";
if (
enableChunkSizeCheck &&
chunkSize !== undefined &&
content.length > chunkSize
) {
console.warn(
`Node (${this.id_}) is larger than chunk size: ${content.length} > ${chunkSize}`,
);
if (!emitOnce) {
console.warn(
"Will truncate the content if it is larger than chunk size",
);
console.warn("If you want to disable this behavior:");
console.warn(" 1. Set Settings.chunkSize = undefined");
console.warn(" 2. Set Settings.chunkSize to a larger value");
console.warn(
" 3. Change the way of splitting content into smaller chunks",
);
}
return content.slice(0, chunkSize);
}
return content;
};
}
export function lazyInitHash(
value: ClassAccessorDecoratorTarget<BaseNode, string>,
_context: ClassAccessorDecoratorContext,
): ClassAccessorDecoratorResult<BaseNode, string> {
return {
get() {
const oldValue = value.get.call(this);
if (oldValue === "") {
const hash = this.generateHash();
value.set.call(this, hash);
}
return value.get.call(this);
},
set(newValue: string) {
value.set.call(this, newValue);
},
init(value: string): string {
return value;
},
};
}
export { wrapEventCaller } from "./event-caller";
export { lazyInitHash } from "./lazy-init-hash";
export { wrapLLMEvent } from "./wrap-llm-event";
@@ -0,0 +1,23 @@
import type { BaseNode } from "../schema";
export function lazyInitHash(
value: ClassAccessorDecoratorTarget<BaseNode, string>,
_context: ClassAccessorDecoratorContext,
): ClassAccessorDecoratorResult<BaseNode, string> {
return {
get() {
const oldValue = value.get.call(this);
if (oldValue === "") {
const hash = this.generateHash();
value.set.call(this, hash);
}
return value.get.call(this);
},
set(newValue: string) {
value.set.call(this, newValue);
},
init(value: string): string {
return value;
},
};
}
+6 -1
View File
@@ -9,4 +9,9 @@ export type {
LLMToolResultEvent,
LlamaIndexEventMaps,
} from "./settings/callback-manager";
export type { JSONArray, JSONObject, JSONValue } from "./type";
export {
EventCaller,
getEventCaller,
withEventCaller,
} from "./settings/event-caller";
export type { JSONArray, JSONObject, JSONValue, UUID } from "./type";
+13 -1
View File
@@ -1,4 +1,4 @@
import type { Tokenizer } from "@llamaindex/env";
import { getEnv, type Tokenizer } from "@llamaindex/env";
import type { LLM } from "../llms";
import {
type CallbackManager,
@@ -61,4 +61,16 @@ export const Settings = {
): Result {
return withCallbackManager(callbackManager, fn);
},
get debug() {
let debug = getEnv("DEBUG");
if (typeof window !== "undefined") {
debug ||= window.localStorage.debug;
}
return (
(Boolean(debug) && debug?.includes("llamaindex")) ||
debug === "*" ||
debug === "true"
);
},
};
@@ -1,4 +1,5 @@
import { AsyncLocalStorage, CustomEvent } from "@llamaindex/env";
import type { AgentEndEvent, AgentStartEvent } from "../../agent";
import type {
ChatMessage,
ChatResponse,
@@ -11,9 +12,10 @@ import type {
SynthesizeEndEvent,
SynthesizeStartEvent,
} from "../../response-synthesizers";
import type { RetrieveEndEvent, RetrieveStartEvent } from "../../retriever";
import { TextNode } from "../../schema";
import { EventCaller, getEventCaller } from "../../utils";
import type { UUID } from "../type";
import { EventCaller, getEventCaller } from "./event-caller";
export type LLMStartEvent = {
id: UUID;
@@ -69,6 +71,10 @@ export interface LlamaIndexEventMaps {
"query-end": QueryEndEvent;
"synthesize-start": SynthesizeStartEvent;
"synthesize-end": SynthesizeEndEvent;
"retrieve-start": RetrieveStartEvent;
"retrieve-end": RetrieveEndEvent;
"agent-start": AgentStartEvent;
"agent-end": AgentEndEvent;
}
export class LlamaIndexCustomEvent<T = any> extends CustomEvent<T> {
@@ -128,16 +134,29 @@ export class CallbackManager {
dispatchEvent<K extends keyof LlamaIndexEventMaps>(
event: K,
detail: LlamaIndexEventMaps[K],
sync = false,
) {
const cbs = this.#handlers.get(event);
if (!cbs) {
return;
}
queueMicrotask(() => {
if (typeof queueMicrotask === "undefined") {
console.warn(
"queueMicrotask is not available, dispatching synchronously",
);
sync = true;
}
if (sync) {
cbs.forEach((handler) =>
handler(LlamaIndexCustomEvent.fromEvent(event, { ...detail })),
);
});
} else {
queueMicrotask(() => {
cbs.forEach((handler) =>
handler(LlamaIndexCustomEvent.fromEvent(event, { ...detail })),
);
});
}
}
}
@@ -0,0 +1,55 @@
import { AsyncLocalStorage, randomUUID } from "@llamaindex/env";
const eventReasonAsyncLocalStorage = new AsyncLocalStorage<EventCaller>();
/**
* EventCaller is used to track the caller of an event.
*/
export class EventCaller {
public readonly id = randomUUID();
private constructor(
public readonly caller: unknown,
public readonly parent: EventCaller | null,
) {}
#computedCallers: unknown[] | null = null;
public get computedCallers(): unknown[] {
if (this.#computedCallers != null) {
return this.#computedCallers;
}
const callers = [this.caller];
let parent = this.parent;
while (parent != null) {
callers.push(parent.caller);
parent = parent.parent;
}
this.#computedCallers = callers;
return callers;
}
public static create(
caller: unknown,
parent: EventCaller | null,
): EventCaller {
return new EventCaller(caller, parent);
}
}
export function getEventCaller(): EventCaller | null {
return eventReasonAsyncLocalStorage.getStore() ?? null;
}
/**
* @param caller who is calling this function, pass in `this` if it's a class method
* @param fn
*/
export function withEventCaller<T>(caller: unknown, fn: () => T) {
// create a chain of event callers
const parentCaller = getEventCaller();
return eventReasonAsyncLocalStorage.run(
EventCaller.create(caller, parentCaller),
fn,
);
}
+23 -2
View File
@@ -1,5 +1,5 @@
import { Settings } from "../global";
import type { ChatMessage, MessageContent } from "../llms";
import type { ChatMessage } from "../llms";
import { type BaseChatStore, SimpleChatStore } from "../storage/chat-store";
import { extractText } from "../utils";
@@ -12,15 +12,36 @@ export const DEFAULT_CHAT_STORE_KEY = "chat_history";
export abstract class BaseMemory<
AdditionalMessageOptions extends object = object,
> {
/**
* Retrieves messages from the memory, optionally including transient messages.
* Compared to getAllMessages, this method a) allows for transient messages to be included in the retrieval and b) may return a subset of the total messages by applying a token limit.
* @param transientMessages Optional array of temporary messages to be included in the retrieval.
* These messages are not stored in the memory but are considered for the current interaction.
* @returns An array of chat messages, either synchronously or as a Promise.
*/
abstract getMessages(
input?: MessageContent | undefined,
transientMessages?: ChatMessage<AdditionalMessageOptions>[] | undefined,
):
| ChatMessage<AdditionalMessageOptions>[]
| Promise<ChatMessage<AdditionalMessageOptions>[]>;
/**
* Retrieves all messages stored in the memory.
* @returns An array of all chat messages, either synchronously or as a Promise.
*/
abstract getAllMessages():
| ChatMessage<AdditionalMessageOptions>[]
| Promise<ChatMessage<AdditionalMessageOptions>[]>;
/**
* Adds a new message to the memory.
* @param messages The chat message to be added to the memory.
*/
abstract put(messages: ChatMessage<AdditionalMessageOptions>): void;
/**
* Clears all messages from the memory.
*/
abstract reset(): void;
protected _tokenCountForMessages(messages: ChatMessage[]): number {
+14 -8
View File
@@ -1,5 +1,5 @@
import { Settings } from "../global";
import type { ChatMessage, LLM, MessageContent } from "../llms";
import type { ChatMessage, LLM } from "../llms";
import { type BaseChatStore } from "../storage/chat-store";
import { BaseChatStoreMemory, DEFAULT_TOKEN_LIMIT_RATIO } from "./base";
@@ -34,7 +34,7 @@ export class ChatMemoryBuffer<
}
getMessages(
input?: MessageContent | undefined,
transientMessages?: ChatMessage<AdditionalMessageOptions>[] | undefined,
initialTokenCount: number = 0,
) {
const messages = this.getAllMessages();
@@ -43,16 +43,22 @@ export class ChatMemoryBuffer<
throw new Error("Initial token count exceeds token limit");
}
let messageCount = messages.length;
let currentMessages = messages.slice(-messageCount);
let tokenCount = this._tokenCountForMessages(messages) + initialTokenCount;
// Add input messages as transient messages
const messagesWithInput = transientMessages
? [...transientMessages, ...messages]
: messages;
let messageCount = messagesWithInput.length;
let currentMessages = messagesWithInput.slice(-messageCount);
let tokenCount =
this._tokenCountForMessages(messagesWithInput) + initialTokenCount;
while (tokenCount > this.tokenLimit && messageCount > 1) {
messageCount -= 1;
if (messages.at(-messageCount)!.role === "assistant") {
if (messagesWithInput.at(-messageCount)!.role === "assistant") {
messageCount -= 1;
}
currentMessages = messages.slice(-messageCount);
currentMessages = messagesWithInput.slice(-messageCount);
tokenCount =
this._tokenCountForMessages(currentMessages) + initialTokenCount;
}
@@ -60,6 +66,6 @@ export class ChatMemoryBuffer<
if (tokenCount > this.tokenLimit && messageCount <= 0) {
return [];
}
return messages.slice(-messageCount);
return messagesWithInput.slice(-messageCount);
}
}
+10 -6
View File
@@ -114,18 +114,22 @@ export class ChatSummaryMemoryBuffer extends BaseMemory {
}
}
private calcCurrentRequestMessages() {
// TODO: check order: currently, we're sending:
private calcCurrentRequestMessages(transientMessages?: ChatMessage[]) {
// currently, we're sending:
// system messages first, then transient messages and then the messages that describe the conversation so far
return [...this.systemMessages, ...this.calcConversationMessages(true)];
return [
...this.systemMessages,
...(transientMessages ? transientMessages : []),
...this.calcConversationMessages(true),
];
}
reset() {
this.messages = [];
}
async getMessages(): Promise<ChatMessage[]> {
const requestMessages = this.calcCurrentRequestMessages();
async getMessages(transientMessages?: ChatMessage[]): Promise<ChatMessage[]> {
const requestMessages = this.calcCurrentRequestMessages(transientMessages);
// get tokens of current request messages and the transient messages
const tokens = requestMessages.reduce(
@@ -149,7 +153,7 @@ export class ChatSummaryMemoryBuffer extends BaseMemory {
// TODO: we still might have too many tokens
// e.g. too large system messages or transient messages
// how should we deal with that?
return this.calcCurrentRequestMessages();
return this.calcCurrentRequestMessages(transientMessages);
}
return requestMessages;
}
+78
View File
@@ -0,0 +1,78 @@
/**
* @todo refactor this module, most of the part is broken
* reference
* - https://github.com/run-llama/LlamaIndexTS/pull/531
* - https://github.com/run-llama/LlamaIndexTS/pull/416
*/
import type { MessageContent } from "../llms";
import { BaseRetriever } from "../retriever";
import { BaseNode, TextNode } from "../schema";
import { extractText } from "../utils";
// Assuming that necessary interfaces and classes (like OT, TextNode, BaseNode, etc.) are defined elsewhere
// Import statements (e.g., for TextNode, BaseNode) should be added based on your project's structure
export abstract class BaseObjectNodeMapping {
// TypeScript doesn't support Python's classmethod directly, but we can use static methods as an alternative
abstract fromObjects<OT>(objs: OT[], ...args: any[]): BaseObjectNodeMapping;
// Abstract methods in TypeScript
abstract objNodeMapping(): Record<any, any>;
abstract toNode(obj: any): TextNode;
// Concrete methods can be defined as usual
validateObject(obj: any): void {}
// Implementing the add object logic
addObj(obj: any): void {
this.validateObject(obj);
this._addObj(obj);
}
// Abstract method for internal add object logic
abstract _addObj(obj: any): void;
// Implementing toNodes method
toNodes(objs: any[]): TextNode[] {
return objs.map((obj) => this.toNode(obj));
}
// Abstract method for internal from node logic
abstract _fromNode(node: BaseNode): any;
// Implementing fromNode method
fromNode(node: BaseNode): any {
const obj = this._fromNode(node);
this.validateObject(obj);
return obj;
}
// Abstract methods for persistence
abstract persist(persistDir: string, objNodeMappingFilename: string): void;
}
export class ObjectRetriever<T = unknown> {
_retriever: BaseRetriever;
_objectNodeMapping: BaseObjectNodeMapping;
constructor(
retriever: BaseRetriever,
objectNodeMapping: BaseObjectNodeMapping,
) {
this._retriever = retriever;
this._objectNodeMapping = objectNodeMapping;
}
// In TypeScript, getters are defined like this.
get retriever(): BaseRetriever {
return this._retriever;
}
// Translating the retrieve method
async retrieve(strOrQueryBundle: MessageContent): Promise<T[]> {
const nodes = await this.retriever.retrieve({
query: extractText(strOrQueryBundle),
});
const objs = nodes.map((n) => this._objectNodeMapping.fromNode(n.node));
return objs;
}
}
+26 -11
View File
@@ -1,9 +1,9 @@
import { randomUUID } from "@llamaindex/env";
import { wrapEventCaller } from "../decorator";
import { Settings } from "../global";
import type { MessageContent } from "../llms";
import { PromptMixin } from "../prompts";
import { EngineResponse } from "../schema";
import { wrapEventCaller } from "../utils";
import { EngineResponse, type NodeWithScore } from "../schema";
/**
* @link https://docs.llamaindex.ai/en/stable/api_reference/schema/?h=querybundle#llama_index.core.schema.QueryBundle
@@ -18,6 +18,18 @@ export type QueryBundle = {
export type QueryType = string | QueryBundle;
export type BaseQueryParams = {
query: QueryType;
};
export interface StreamingQueryParams extends BaseQueryParams {
stream: true;
}
export interface NonStreamingQueryParams extends BaseQueryParams {
stream?: false;
}
export type QueryFn = (
strOrQueryBundle: QueryType,
stream?: boolean,
@@ -28,23 +40,26 @@ export abstract class BaseQueryEngine extends PromptMixin {
super();
}
query(
strOrQueryBundle: QueryType,
stream: true,
): Promise<AsyncIterable<EngineResponse>>;
query(strOrQueryBundle: QueryType, stream?: false): Promise<EngineResponse>;
async retrieve(params: QueryType): Promise<NodeWithScore[]> {
throw new Error(
"This query engine does not support retrieve, use query directly",
);
}
query(params: StreamingQueryParams): Promise<AsyncIterable<EngineResponse>>;
query(params: NonStreamingQueryParams): Promise<EngineResponse>;
@wrapEventCaller
async query(
strOrQueryBundle: QueryType,
stream = false,
params: StreamingQueryParams | NonStreamingQueryParams,
): Promise<EngineResponse | AsyncIterable<EngineResponse>> {
const { stream, query } = params;
const id = randomUUID();
const callbackManager = Settings.callbackManager;
callbackManager.dispatchEvent("query-start", {
id,
query: strOrQueryBundle,
query,
});
const response = await this._query(strOrQueryBundle, stream);
const response = await this._query(query, stream);
callbackManager.dispatchEvent("query-end", {
id,
response,
@@ -16,11 +16,12 @@ import {
type NodeWithScore,
TextNode,
} from "../schema";
import { createMessageContent, extractText, streamConverter } from "../utils";
import { extractText, streamConverter } from "../utils";
import {
BaseSynthesizer,
type BaseSynthesizerOptions,
} from "./base-synthesizer";
import { createMessageContent } from "./utils";
const responseModeSchema = z.enum([
"refine",
@@ -8,3 +8,4 @@ export type {
SynthesizeQuery,
SynthesizeStartEvent,
} from "./type";
export { createMessageContent } from "./utils";
@@ -0,0 +1,72 @@
// eslint-disable-next-line max-params
import type { MessageContentDetail } from "../llms";
import type { BasePromptTemplate } from "../prompts";
import {
type BaseNode,
ImageNode,
MetadataMode,
ModalityType,
splitNodesByType,
} from "../schema";
import { imageToDataUrl } from "../utils";
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;
}
+112
View File
@@ -0,0 +1,112 @@
import { randomUUID } from "@llamaindex/env";
import { Settings } from "../global";
import type { MessageContent } from "../llms";
import { PromptMixin } from "../prompts";
import type { QueryBundle, QueryType } from "../query-engine";
import { BaseNode, IndexNode, type NodeWithScore, ObjectType } from "../schema";
export type RetrieveParams = {
query: MessageContent;
preFilters?: unknown;
};
export type RetrieveStartEvent = {
id: string;
query: QueryBundle;
};
export type RetrieveEndEvent = {
id: string;
query: QueryBundle;
nodes: NodeWithScore[];
};
export abstract class BaseRetriever extends PromptMixin {
objectMap: Map<string, unknown> = new Map();
protected _updatePrompts() {}
protected _getPrompts() {
return {};
}
protected _getPromptModules() {
return {};
}
protected constructor() {
super();
}
public async retrieve(params: QueryType): Promise<NodeWithScore[]> {
const cb = Settings.callbackManager;
const queryBundle = typeof params === "string" ? { query: params } : params;
const id = randomUUID();
cb.dispatchEvent("retrieve-start", { id, query: queryBundle });
let response = await this._retrieve(queryBundle);
response = await this._handleRecursiveRetrieval(queryBundle, response);
cb.dispatchEvent("retrieve-end", {
id,
query: queryBundle,
nodes: response,
});
return response;
}
abstract _retrieve(params: QueryBundle): Promise<NodeWithScore[]>;
async _handleRecursiveRetrieval(
params: QueryBundle,
nodes: NodeWithScore[],
): Promise<NodeWithScore[]> {
const retrievedNodes = [];
for (const { node, score = 1.0 } of nodes) {
if (node.type === ObjectType.INDEX) {
const indexNode = node as IndexNode;
const object = this.objectMap.get(indexNode.indexId);
if (object !== undefined) {
retrievedNodes.push(
...this._retrieveFromObject(object, params, score),
);
} else {
retrievedNodes.push({ node, score });
}
} else {
retrievedNodes.push({ node, score });
}
}
return nodes;
}
_retrieveFromObject(
object: unknown,
queryBundle: QueryBundle,
score: number,
): NodeWithScore[] {
if (object == null) {
throw new TypeError("Object is not retrievable");
}
if (typeof object !== "object") {
throw new TypeError("Object is not retrievable");
}
if ("node" in object && object.node instanceof BaseNode) {
return [
{
node: object.node,
score:
"score" in object && typeof object.score === "number"
? object.score
: score,
},
];
}
if (object instanceof BaseNode) {
return [{ node: object, score }];
} else {
// todo: support other types
// BaseQueryEngine
// BaseRetriever
// QueryComponent
throw new TypeError("Object is not retrievable");
}
}
}
+2 -1
View File
@@ -1,5 +1,6 @@
import { createSHA256, path, randomUUID } from "@llamaindex/env";
import { chunkSizeCheck, lazyInitHash } from "../decorator";
import { lazyInitHash } from "../decorator";
import { chunkSizeCheck } from "./utils/chunk-size-check";
export enum NodeRelationship {
SOURCE = "SOURCE",
@@ -0,0 +1,44 @@
import { getEnv } from "@llamaindex/env";
import { Settings } from "../../global";
const emitOnce = false;
export function chunkSizeCheck<
This extends { id_: string },
Args extends any[],
Return,
>(
contentGetter: (this: This, ...args: Args) => string,
_context: ClassMethodDecoratorContext<
This,
(this: This, ...args: Args) => Return
>,
) {
return function (this: This, ...args: Args) {
const content = contentGetter.call(this, ...args);
const chunkSize = Settings.chunkSize;
const enableChunkSizeCheck = getEnv("ENABLE_CHUNK_SIZE_CHECK") === "true";
if (
enableChunkSizeCheck &&
chunkSize !== undefined &&
content.length > chunkSize
) {
console.warn(
`Node (${this.id_}) is larger than chunk size: ${content.length} > ${chunkSize}`,
);
if (!emitOnce) {
console.warn(
"Will truncate the content if it is larger than chunk size",
);
console.warn("If you want to disable this behavior:");
console.warn(" 1. Set Settings.chunkSize = undefined");
console.warn(" 2. Set Settings.chunkSize to a larger value");
console.warn(
" 3. Change the way of splitting content into smaller chunks",
);
}
return content.slice(0, chunkSize);
}
return content;
};
}
-110
View File
@@ -1,110 +0,0 @@
import { AsyncLocalStorage, randomUUID } from "@llamaindex/env";
export const isAsyncIterable = (
obj: unknown,
): obj is AsyncIterable<unknown> => {
return obj != null && typeof obj === "object" && Symbol.asyncIterator in obj;
};
export const isIterable = (obj: unknown): obj is Iterable<unknown> => {
return obj != null && typeof obj === "object" && Symbol.iterator in obj;
};
const eventReasonAsyncLocalStorage = new AsyncLocalStorage<EventCaller>();
/**
* EventCaller is used to track the caller of an event.
*/
export class EventCaller {
public readonly id = randomUUID();
private constructor(
public readonly caller: unknown,
public readonly parent: EventCaller | null,
) {}
#computedCallers: unknown[] | null = null;
public get computedCallers(): unknown[] {
if (this.#computedCallers != null) {
return this.#computedCallers;
}
const callers = [this.caller];
let parent = this.parent;
while (parent != null) {
callers.push(parent.caller);
parent = parent.parent;
}
this.#computedCallers = callers;
return callers;
}
public static create(
caller: unknown,
parent: EventCaller | null,
): EventCaller {
return new EventCaller(caller, parent);
}
}
export function getEventCaller(): EventCaller | null {
return eventReasonAsyncLocalStorage.getStore() ?? null;
}
/**
* @param caller who is calling this function, pass in `this` if it's a class method
* @param fn
*/
function withEventCaller<T>(caller: unknown, fn: () => T) {
// create a chain of event callers
const parentCaller = getEventCaller();
return eventReasonAsyncLocalStorage.run(
EventCaller.create(caller, parentCaller),
fn,
);
}
export function wrapEventCaller<This, Result, Args extends unknown[]>(
originalMethod: (this: This, ...args: Args) => Result,
context: ClassMethodDecoratorContext<object>,
) {
const name = context.name;
context.addInitializer(function () {
// @ts-expect-error
const fn = this[name].bind(this);
// @ts-expect-error
this[name] = (...args: unknown[]) => {
return withEventCaller(this, () => fn(...args));
};
});
return function (this: This, ...args: Args): Result {
const result = originalMethod.call(this, ...args);
// patch for iterators because AsyncLocalStorage doesn't work with them
if (isAsyncIterable(result)) {
const iter = result[Symbol.asyncIterator]();
const snapshot = AsyncLocalStorage.snapshot();
return (async function* asyncGeneratorWrapper() {
while (true) {
const { value, done } = await snapshot(() => iter.next());
if (done) {
break;
}
yield value;
}
})() as Result;
} else if (isIterable(result)) {
const iter = result[Symbol.iterator]();
const snapshot = AsyncLocalStorage.snapshot();
return (function* generatorWrapper() {
while (true) {
const { value, done } = snapshot(() => iter.next());
if (done) {
break;
}
yield value;
}
})() as Result;
}
return result;
};
}
+25 -3
View File
@@ -1,4 +1,14 @@
export { EventCaller, getEventCaller, wrapEventCaller } from "./event-caller";
import type { JSONValue } from "../global";
export const isAsyncIterable = (
obj: unknown,
): obj is AsyncIterable<unknown> => {
return obj != null && typeof obj === "object" && Symbol.asyncIterator in obj;
};
export const isIterable = (obj: unknown): obj is Iterable<unknown> => {
return obj != null && typeof obj === "object" && Symbol.iterator in obj;
};
export async function* streamConverter<S, D>(
stream: AsyncIterable<S>,
@@ -44,10 +54,22 @@ export async function* streamReducer<S, D>(params: {
}
}
export { wrapLLMEvent } from "./wrap-llm-event";
/**
* Prettify an error for AI to read
*/
export function prettifyError(error: unknown): string {
if (error instanceof Error) {
return `Error(${error.name}): ${error.message}`;
} else {
return `${error}`;
}
}
export function stringifyJSONToMessageContent(value: JSONValue): string {
return JSON.stringify(value, null, 2).replace(/"([^"]*)"/g, "$1");
}
export {
createMessageContent,
extractDataUrlComponents,
extractImage,
extractSingleText,
-70
View File
@@ -7,16 +7,8 @@ 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
@@ -151,65 +143,3 @@ export async function imageToDataUrl(
}
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;
}
+13
View File
@@ -0,0 +1,13 @@
/**
* should compatible with npm:pg and npm:postgres
*/
export interface IsomorphicDB {
query: (sql: string, params?: any[]) => Promise<any[]>;
// begin will wrap the multiple queries in a transaction
begin: <T>(fn: (query: IsomorphicDB["query"]) => Promise<T>) => Promise<T>;
// event handler
connect: () => Promise<void>;
close: () => Promise<void>;
onCloseEvent: (listener: () => void) => void;
}
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
@@ -1,4 +1,4 @@
import { validateAgentParams } from "llamaindex/agent/utils";
import { validateAgentParams } from "@llamaindex/core/agent";
import { expect, test } from "vitest";
import { ZodError } from "zod";
@@ -0,0 +1,74 @@
import { Settings } from "@llamaindex/core/global";
import type { ChatMessage } from "@llamaindex/core/llms";
import { ChatMemoryBuffer } from "@llamaindex/core/memory";
import { beforeEach, describe, expect, test } from "vitest";
describe("ChatMemoryBuffer", () => {
beforeEach(() => {
// Mock the Settings.llm
(Settings.llm as any) = {
metadata: {
contextWindow: 1000,
},
};
});
test("constructor initializes with custom token limit", () => {
const buffer = new ChatMemoryBuffer({ tokenLimit: 500 });
expect(buffer.tokenLimit).toBe(500);
});
test("getMessages returns all messages when under token limit", () => {
const messages: ChatMessage[] = [
{ role: "user", content: "Hello" },
{ role: "assistant", content: "Hi there!" },
{ role: "user", content: "How are you?" },
];
const buffer = new ChatMemoryBuffer({
tokenLimit: 1000,
chatHistory: messages,
});
const result = buffer.getMessages();
expect(result).toEqual(messages);
});
test("getMessages truncates messages when over token limit", () => {
const messages: ChatMessage[] = [
{ role: "user", content: "This is a long message" },
{ role: "assistant", content: "This is also a long reply" },
{ role: "user", content: "Short" },
];
const buffer = new ChatMemoryBuffer({
tokenLimit: 5, // limit to only allow the last message
chatHistory: messages,
});
const result = buffer.getMessages();
expect(result).toEqual([{ role: "user", content: "Short" }]);
});
test("getMessages handles input messages", () => {
const storedMessages: ChatMessage[] = [
{ role: "user", content: "Hello" },
{ role: "assistant", content: "Hi there!" },
];
const buffer = new ChatMemoryBuffer({
tokenLimit: 50,
chatHistory: storedMessages,
});
const inputMessages: ChatMessage[] = [
{ role: "user", content: "New message" },
];
const result = buffer.getMessages(inputMessages);
expect(result).toEqual([...inputMessages, ...storedMessages]);
});
test("getMessages throws error when initial token count exceeds limit", () => {
const buffer = new ChatMemoryBuffer({ tokenLimit: 10 });
expect(() => buffer.getMessages(undefined, 20)).toThrow(
"Initial token count exceeds token limit",
);
});
});
+1 -1
View File
@@ -8,7 +8,7 @@
"moduleResolution": "Bundler",
"skipLibCheck": true,
"strict": true,
"lib": ["ESNext", "DOM"],
"lib": ["ESNext", "DOM", "DOM.AsyncIterable"],
"types": ["node"]
},
"include": ["./src"],
+8
View File
@@ -0,0 +1,8 @@
{
"extends": ["//"],
"tasks": {
"build": {
"outputs": ["**/dist/**"]
}
}
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
+8
View File
@@ -0,0 +1,8 @@
{
"type": "module",
"main": "./dist/index.cjs",
"module": "./dist/index.js",
"types": "./dist/index.d.ts",
"exports": "./dist/index.js",
"private": true
}
-7
View File
@@ -1,7 +0,0 @@
{
"detectiveOptions": {
"ts": {
"skipTypeImports": true
}
}
}
+14
View File
@@ -1,5 +1,19 @@
# @llamaindex/env
## 0.1.13
### Patch Changes
- df441e2: fix: consoleLogger is missing from `@llamaindex/env`
## 0.1.12
### Patch Changes
- b48bcc3: feat: add `load-transformers` event type when loading `@xenova/transformers` module
This would benefit user who want to customize the transformer env.
## 0.1.11
### Patch Changes
+14 -4
View File
@@ -1,7 +1,7 @@
{
"name": "@llamaindex/env",
"description": "environment wrapper, supports all JS environment including node, deno, bun, edge runtime, and cloudflare worker",
"version": "0.1.11",
"version": "0.1.13",
"type": "module",
"types": "dist/type/index.d.ts",
"main": "dist/cjs/index.js",
@@ -57,7 +57,7 @@
],
"repository": {
"type": "git",
"url": "https://github.com/himself65/LlamaIndexTS.git",
"url": "https://github.com/run-llama/LlamaIndexTS.git",
"directory": "packages/env"
},
"scripts": {
@@ -67,23 +67,24 @@
"build:type": "tsc -p tsconfig.json",
"postbuild": "node -e \"require('fs').writeFileSync('./dist/cjs/package.json', JSON.stringify({ type: 'commonjs' }))\"",
"dev": "concurrently \"pnpm run build:esm --watch\" \"pnpm run build:cjs --watch\" \"pnpm run build:type --watch\"",
"circular-check": "madge -c ./src/index.ts",
"test": "vitest"
},
"devDependencies": {
"@aws-crypto/sha256-js": "^5.2.0",
"@swc/cli": "^0.4.0",
"@swc/core": "^1.7.22",
"@xenova/transformers": "^2.17.2",
"concurrently": "^8.2.2",
"pathe": "^1.1.2",
"tiktoken": "^1.0.16",
"vitest": "^2.0.5"
},
"dependencies": {
"@types/lodash": "^4.17.7",
"@types/node": "^22.5.1"
},
"peerDependencies": {
"@aws-crypto/sha256-js": "^5.2.0",
"@xenova/transformers": "^2.17.2",
"js-tiktoken": "^1.0.12",
"pathe": "^1.1.2",
"tiktoken": "^1.0.15"
@@ -92,8 +93,17 @@
"@aws-crypto/sha256-js": {
"optional": true
},
"@xenova/transformers": {
"optional": true
},
"pathe": {
"optional": true
},
"tiktoken": {
"optional": true
},
"js-tiktoken": {
"optional": true
}
}
}
+7
View File
@@ -6,6 +6,13 @@
import "./global-check.js";
export * from "./web-polyfill.js";
export { consoleLogger, emptyLogger, type Logger } from "./logger/index.js";
export {
loadTransformers,
setTransformers,
type LoadTransformerEvent,
type OnLoad,
} from "./multi-model/index.browser.js";
export { Tokenizers, tokenizers, type Tokenizer } from "./tokenizers/js.js";
// @ts-expect-error
+7
View File
@@ -6,4 +6,11 @@
import "./global-check.js";
export * from "./node-polyfill.js";
export { consoleLogger, emptyLogger, type Logger } from "./logger/index.js";
export {
loadTransformers,
setTransformers,
type LoadTransformerEvent,
type OnLoad,
} from "./multi-model/index.non-nodejs.js";
export { Tokenizers, tokenizers, type Tokenizer } from "./tokenizers/js.js";
+7
View File
@@ -33,6 +33,13 @@ export function createSHA256(): SHA256 {
};
}
export { consoleLogger, emptyLogger, type Logger } from "./logger/index.js";
export {
loadTransformers,
setTransformers,
type LoadTransformerEvent,
type OnLoad,
} from "./multi-model/index.js";
export { Tokenizers, tokenizers, type Tokenizer } from "./tokenizers/node.js";
export {
AsyncLocalStorage,
+7
View File
@@ -13,4 +13,11 @@ export function getEnv(name: string): string | undefined {
return INTERNAL_ENV[name];
}
export { consoleLogger, emptyLogger, type Logger } from "./logger/index.js";
export {
loadTransformers,
setTransformers,
type LoadTransformerEvent,
type OnLoad,
} from "./multi-model/index.non-nodejs.js";
export { Tokenizers, tokenizers, type Tokenizer } from "./tokenizers/js.js";

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