Merge branch 'main' of github.com:run-llama/LlamaIndexTS

31c99baf · Yi Ding · b2810777 · 805d6fb8 · 31c99baf · 31c99baf
Commit 31c99baf authored 1 year ago by Yi Ding
--- a/README.md
+++ b/README.md
 # LlamaIndex.TS

+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.

+Documentation: https://ts.llamaindex.ai/
+
 ## What is LlamaIndex.TS?

 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.

--- a/apps/docs/docs/introduction.md
+++ b/apps/docs/docs/introduction.md
@@ -37,15 +37,14 @@ For more complex applications, our lower-level APIs allow advanced users to cust

 Our documentation includes [Installation Instructions](./installation.md) and a [Starter Tutorial](./starter.md) to build your first application.

-Once you're up and running, [High-Level Concepts](./concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our [End-to-End Tutorials](LINK TO EXAMPLES FOLDER).
+Once you're up and running, [High-Level Concepts](./concepts.md) has an overview of LlamaIndex's modular architecture. For more hands-on practical examples, look through our [End-to-End Tutorials](./end_to_end.md).

 ## 🗺️ Ecosystem

 To download or contribute, find LlamaIndex on:

- Github: https://github.com/jerryjliu/llama_index
- LlamaIndex (NPM): LINK TO NPM PACKAGE
- LlamaIndex (Python): https://pypi.org/project/llama-index/.
+- Github: https://github.com/run-llama/LlamaIndexTS
+- NPM: https://www.npmjs.com/package/llamaindex

 ## Community


--- a/apps/docs/docs/modules/index.md
+++ b/apps/docs/docs/modules/index.md
@@ -12,7 +12,7 @@ LlamaIndex.TS offers several core modules, seperated into high-level modules for

 - [**Indexes**](./high_level/data_index.md): indexes store the Nodes and the embeddings of those nodes.

-[**QueryEngine**](./high_level/query_engine.md): 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.
+- [**QueryEngine**](./high_level/query_engine.md): 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.

 - [**ChatEngine**](./high_level/chat_engine.md): A ChatEngine helps you build a chatbot that will interact with your Indexes.


--- a/apps/docs/docs/starter.md
+++ b/apps/docs/docs/starter.md
@@ -11,7 +11,7 @@ In a new folder:
 ```bash npm2yarn
 npm install typescript
 npm install @types/node
-npx tsc –-init # if needed
+npx tsc --init # if needed
 ```

 Create the file `example.ts`. This code will load some example data, create a document, index it (which creates embeddings using OpenAI), and then creates query engine to answer questions about the data.

--- a/apps/docs/src/pages/index.tsx
+++ b/apps/docs/src/pages/index.tsx
@@ -24,8 +24,8 @@ export default function Home(): JSX.Element {
  const { siteConfig } = useDocusaurusContext();
  return (
    <Layout
-      title={`Hello from ${siteConfig.title}`}
-      description="Description will go into a meta tag in <head />"
+      title={`${siteConfig.title}`}
+      description="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."
    >
      <HomepageHeader />
      <main>

--- a/apps/simple/README.md
+++ b/apps/simple/README.md
 # Simple Examples

-Due to packaging, you will need to run `pnpm --filter llamaindex build` before running these examples.
+Due to packaging, you will need to run these commands to get started.
+```bash
+pnpm --filter llamaindex build
+pnpm install
+```

-Run them with ts-node, for example `npx ts-node vectorIndex.ts`
+Then run the examples with `ts-node`, for example `npx ts-node vectorIndex.ts`
--- a/apps/simple/llamadeuce.ts
+++ b/apps/simple/llamadeuce.ts
-import { LlamaDeuce } from "llamaindex/src/llm/LLM";
+import { LlamaDeuce } from "llamaindex";

 (async () => {
  const deuce = new LlamaDeuce();