mirror of
https://github.com/run-llama/LlamaIndexTS.git
synced 2026-07-01 22:14:03 -04:00
Compare commits
37 Commits
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| 2bc6914784 |
@@ -1,5 +1,83 @@
|
||||
# @llamaindex/doc
|
||||
|
||||
## 0.2.31
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
- @llamaindex/core@0.6.12
|
||||
- @llamaindex/cloud@4.0.16
|
||||
- @llamaindex/node-parser@2.0.12
|
||||
- @llamaindex/openai@0.4.6
|
||||
- @llamaindex/readers@3.1.11
|
||||
- @llamaindex/workflow@1.1.12
|
||||
|
||||
## 0.2.30
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [f7ec293]
|
||||
- @llamaindex/workflow@1.1.11
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 0.2.29
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c5846bd]
|
||||
- @llamaindex/readers@3.1.10
|
||||
|
||||
## 0.2.28
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [a89e187]
|
||||
- Updated dependencies [62699b7]
|
||||
- Updated dependencies [c5b2691]
|
||||
- Updated dependencies [d8ac8d3]
|
||||
- @llamaindex/core@0.6.11
|
||||
- @llamaindex/openai@0.4.5
|
||||
- @llamaindex/cloud@4.0.15
|
||||
- llamaindex@0.11.9
|
||||
- @llamaindex/node-parser@2.0.11
|
||||
- @llamaindex/readers@3.1.9
|
||||
- @llamaindex/workflow@1.1.10
|
||||
|
||||
## 0.2.27
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 8a51c16: Add natural language agent page
|
||||
- Updated dependencies [8a51c16]
|
||||
- Updated dependencies [1b5af14]
|
||||
- @llamaindex/workflow@1.1.9
|
||||
- @llamaindex/core@0.6.10
|
||||
- llamaindex@0.11.8
|
||||
- @llamaindex/cloud@4.0.14
|
||||
- @llamaindex/node-parser@2.0.10
|
||||
- @llamaindex/openai@0.4.4
|
||||
- @llamaindex/readers@3.1.8
|
||||
|
||||
## 0.2.26
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- a4d394f: fix: correct SimpleDirectoryReader import path in documentation example
|
||||
- Updated dependencies [dbd857f]
|
||||
- Updated dependencies [3c857f4]
|
||||
- @llamaindex/workflow@1.1.8
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 0.2.25
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [40161fe]
|
||||
- @llamaindex/workflow@1.1.7
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 0.2.24
|
||||
|
||||
### Patch Changes
|
||||
|
||||
+1
-1
@@ -111,7 +111,7 @@ Key build process:
|
||||
**Content Sources:**
|
||||
|
||||
- Local MDX files in `src/content/docs/`
|
||||
- External docs from `@llama-flow/docs` package
|
||||
- External docs from `@llamaindex/workflow-docs` package
|
||||
- Generated API docs from TypeScript source
|
||||
|
||||
### Development Notes
|
||||
|
||||
@@ -15,6 +15,20 @@ const config = {
|
||||
"twoslash",
|
||||
"typescript",
|
||||
],
|
||||
async redirects() {
|
||||
return [
|
||||
{
|
||||
source: "/docs/chat-ui/:path*.mdx",
|
||||
destination: "/docs/chat-ui/:path*",
|
||||
permanent: true,
|
||||
},
|
||||
{
|
||||
source: "/docs/workflows/:path*.mdx",
|
||||
destination: "/docs/workflows/:path*",
|
||||
permanent: true,
|
||||
},
|
||||
];
|
||||
},
|
||||
turbopack: {
|
||||
resolveAlias: {
|
||||
fs: { browser: "./fallback.js" },
|
||||
|
||||
+10
-10
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/doc",
|
||||
"version": "0.2.24",
|
||||
"version": "0.2.31",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"postinstall": "fumadocs-mdx",
|
||||
@@ -15,8 +15,8 @@
|
||||
"dependencies": {
|
||||
"@huggingface/transformers": "^3.5.0",
|
||||
"@icons-pack/react-simple-icons": "^10.1.0",
|
||||
"@llama-flow/docs": "0.0.8",
|
||||
"@llamaindex/chat-ui-docs": "0.0.3",
|
||||
"@llamaindex/workflow-docs": "0.1.1",
|
||||
"@llamaindex/chat-ui-docs": "^0.0.5",
|
||||
"@llamaindex/cloud": "workspace:*",
|
||||
"@llamaindex/core": "workspace:*",
|
||||
"@llamaindex/node-parser": "workspace:*",
|
||||
@@ -39,13 +39,13 @@
|
||||
"clsx": "2.1.1",
|
||||
"foxact": "^0.2.41",
|
||||
"framer-motion": "^11.11.17",
|
||||
"fumadocs-core": "^15.2.7",
|
||||
"fumadocs-core": "^15.5.0",
|
||||
"fumadocs-docgen": "^2.0.0",
|
||||
"fumadocs-mdx": "^11.6.0",
|
||||
"fumadocs-openapi": "^8.0.1",
|
||||
"fumadocs-twoslash": "^3.1.1",
|
||||
"fumadocs-typescript": "^4.0.2",
|
||||
"fumadocs-ui": "^15.2.7",
|
||||
"fumadocs-mdx": "^11.6.6",
|
||||
"fumadocs-openapi": "^9.0.5",
|
||||
"fumadocs-twoslash": "^3.1.3",
|
||||
"fumadocs-typescript": "^4.0.5",
|
||||
"fumadocs-ui": "^15.5.0",
|
||||
"hast-util-to-jsx-runtime": "^2.3.2",
|
||||
"llamaindex": "workspace:*",
|
||||
"lucide-react": "^0.460.0",
|
||||
@@ -69,7 +69,7 @@
|
||||
"twoslash": "^0.3.1",
|
||||
"use-stick-to-bottom": "^1.0.42",
|
||||
"web-tree-sitter": "^0.24.4",
|
||||
"zod": "^3.23.8"
|
||||
"zod": "^3.25.67"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@next/env": "^15.3.0",
|
||||
|
||||
@@ -13,7 +13,7 @@ const INTERNAL_LINK_REGEX = /(?:(?:\]\(|\bhref=["'])\/docs\/([^")]+))/g;
|
||||
// This captures relative links like [text](./path) or 
|
||||
const RELATIVE_LINK_REGEX = /(?:\]\()(?:\s*)(?:\.\.?)\//g;
|
||||
|
||||
const ALLOWED_LINKS = ["/docs/llamaflow", "/docs/chat-ui"];
|
||||
const ALLOWED_LINKS = ["/docs/workflows", "/docs/chat-ui"];
|
||||
|
||||
interface LinkValidationResult {
|
||||
file: string;
|
||||
|
||||
@@ -11,8 +11,13 @@ import remarkMath from "remark-math";
|
||||
export const docs = defineDocs({
|
||||
dir: [
|
||||
"./src/content/docs",
|
||||
"./node_modules/@llama-flow/docs",
|
||||
"./node_modules/@llamaindex/workflow-docs",
|
||||
"./node_modules/@llamaindex/chat-ui-docs",
|
||||
// NOTE: When adding external docs (like chat-ui or workflow-docs above),
|
||||
// make sure to also update:
|
||||
// 1. scripts/validate-links.mts - add to ALLOWED_LINKS array
|
||||
// 2. next.config.mjs - add redirect for .mdx files
|
||||
// 3. src/content/docs/meta.json - add to pages array
|
||||
],
|
||||
docs: {
|
||||
async: true,
|
||||
|
||||
@@ -113,7 +113,8 @@ export default function HomePage() {
|
||||
description="Truly powerful retrieval-augmented generation applications use agentic techniques, and LlamaIndex.TS makes it easy to build them."
|
||||
>
|
||||
<CodeBlock
|
||||
code={`import { SimpleDirectoryReader, VectorStoreIndex } from "llamaindex";
|
||||
code={`import { VectorStoreIndex } from "llamaindex";
|
||||
import { SimpleDirectoryReader } from "@llamaindex/readers/directory";
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import { agent } from "@llamaindex/workflow";
|
||||
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
{
|
||||
"title": "Agents",
|
||||
"pages": ["tool", "agent_workflow", "workflows"]
|
||||
"pages": ["tool", "agent_workflow", "workflows", "natural_language_workflow"]
|
||||
}
|
||||
|
||||
@@ -0,0 +1,103 @@
|
||||
---
|
||||
title: Define workflows using natural language
|
||||
---
|
||||
|
||||
When working with Workflows, you have to write code to handle an event in the workflow.
|
||||
Often, the logic of the handler is not too complex so that it can be expressed using natural language and executed by an LLM.
|
||||
Besides the instructions, we just need the expected result event of the step, possible tool calls and optionally other events that can be emitted.
|
||||
|
||||
## Usage
|
||||
|
||||
Let's take an example of a workflow that generates a joke, gets a critique for it, and then improves it.
|
||||
|
||||
### Define the events
|
||||
|
||||
First, we define the events for our workflow. We need one for writing the joke, one for critiquing it, and one for the final result:
|
||||
|
||||
```typescript
|
||||
import { z } from "zod";
|
||||
import { zodEvent } from "@llamaindex/workflow";
|
||||
|
||||
const writeJokeSchema = z.object({
|
||||
description: z
|
||||
.string()
|
||||
.describe("The topic to write a joke or describe the joke to improve."),
|
||||
writtenJoke: z.optional(z.string()).describe("The written joke."),
|
||||
retriedTimes: z
|
||||
.number()
|
||||
.default(0)
|
||||
.describe(
|
||||
"The retried times for writing the joke. Always increase this from the input retriedTimes.",
|
||||
),
|
||||
});
|
||||
|
||||
const critiqueSchema = z.object({
|
||||
joke: z.string().describe("The joke to critique"),
|
||||
retriedTimes: z.number().describe("The retried times for writing the joke."),
|
||||
});
|
||||
|
||||
const finalResultSchema = z.object({
|
||||
joke: z.string().describe("The joke to critique"),
|
||||
critique: z.string().describe("The critique of the joke"),
|
||||
});
|
||||
|
||||
const writeJokeEvent = zodEvent(writeJokeSchema, {
|
||||
debugLabel: "writeJokeEvent",
|
||||
});
|
||||
const critiqueEvent = zodEvent(critiqueSchema, {
|
||||
debugLabel: "critiqueEvent",
|
||||
});
|
||||
const finalResultEvent = zodEvent(finalResultSchema, {
|
||||
debugLabel: "finalResultEvent",
|
||||
});
|
||||
```
|
||||
|
||||
Note that your natural language workflows the events need to be created by the `zodEvent` function passing the zod schema as an argument. The agent needs the schema of the event data to correctly generate events.
|
||||
Also, we need a `debugLabel` so the LLM can identify the event to emit in the workflow.
|
||||
|
||||
### Define the workflow
|
||||
|
||||
As usual you first create the workflow:
|
||||
|
||||
```typescript
|
||||
import { agentHandler, createWorkflow } from "@llamaindex/workflow";
|
||||
|
||||
const jokeFlow = createWorkflow();
|
||||
```
|
||||
|
||||
Then you need to handle the events. For the handlers, instead of code, you're now going to use natural language by calling the `agentHandler` function.
|
||||
|
||||
It only requires two parameters:
|
||||
- `instructions`: A prompt to guide the agent how to handle the steps.
|
||||
- `results`: The output events that the agent should return after handling the step.
|
||||
|
||||
Then you will have a simple code to handle the step:
|
||||
|
||||
```typescript
|
||||
jokeFlow.handle(
|
||||
[writeJokeEvent],
|
||||
agentHandler({
|
||||
instructions: `You are a joke writer. You are given a topic and you need to write a joke about it.`,
|
||||
results: [critiqueEvent],
|
||||
}),
|
||||
);
|
||||
|
||||
jokeFlow.handle(
|
||||
[critiqueEvent],
|
||||
agentHandler({
|
||||
instructions: `
|
||||
You are given a joke and you need to critique it. Follow the following guidelines:
|
||||
1. You have maximum 3 times to improve the joke.
|
||||
2. If the joke is not good, increase the retriedTimes, describe how to improve the joke and send a writeJokeEvent.
|
||||
3. If the joke is good, trigger the finalResultEvent event.
|
||||
`,
|
||||
results: [writeJokeEvent, finalResultEvent],
|
||||
}),
|
||||
);
|
||||
```
|
||||
|
||||
For advanced usage, you can add more functionality to `agentHandler` by using these parameters:
|
||||
- `events`: A list of additional events that the agent can emit to the workflow. E.g., your agent can emit a `uiEvent` to update the UI during the execution.
|
||||
- `tools`: A list of tools that the agent can use to handle the step. E.g., your agent can use a `search` tool to search the web.
|
||||
|
||||
You can find more code examples in the [examples](https://github.com/run-llama/LlamaIndexTS/tree/main/examples/agents/natural) folder.
|
||||
@@ -74,12 +74,21 @@ const server = mcp({
|
||||
args: ["-y", "@modelcontextprotocol/server-filesystem", "."],
|
||||
verbose: true,
|
||||
});
|
||||
// or by SSE
|
||||
// or by StreamableHTTP transport
|
||||
const server = mcp({
|
||||
url: "http://localhost:8000/mcp",
|
||||
verbose: true,
|
||||
});
|
||||
|
||||
// if your MCP server is not using StreamableHTTP transport, you can also use SSE transport
|
||||
// by setting useSSETransport to true.
|
||||
// See: https://modelcontextprotocol.io/docs/concepts/transports#server-sent-events-sse-deprecated
|
||||
const server = mcp({
|
||||
url: "http://localhost:8000/mcp",
|
||||
useSSETransport: true,
|
||||
verbose: true,
|
||||
});
|
||||
|
||||
// 3. Get tools from MCP server
|
||||
const tools = await server.tools();
|
||||
|
||||
|
||||
@@ -9,10 +9,13 @@ Workflows are designed to be flexible and can be used to build agents, RAG flows
|
||||
To use workflows install this package:
|
||||
|
||||
```package-install
|
||||
npm i @llamaindex/workflow
|
||||
npm i @llamaindex/workflow-core
|
||||
```
|
||||
|
||||
This package is a stable, production-ready version of our [llama-flow](/docs/llamaflow) project.
|
||||
This contains the core functionality for the workflow system. You can read more about the core concepts in the [workflow-core](/docs/workflows) section.
|
||||
|
||||
While you can still reference the llama-flow documentation for detailed information about the underlying concepts, we recommend using the `@llamaindex/workflow` package for all new projects to ensure stability and long-term availability.
|
||||
In contrast, the `@llamaindex/workflow` package contains more utiltities, such as prebuilt agents.
|
||||
|
||||
```package-install
|
||||
npm i @llamaindex/workflow
|
||||
```
|
||||
|
||||
+31
-2
@@ -28,11 +28,12 @@ embedding vector(1536)
|
||||
);
|
||||
```
|
||||
|
||||
-- Create a function for similarity search
|
||||
-- Create a function for similarity search with filtering support
|
||||
```sql
|
||||
create function match_documents (
|
||||
query_embedding vector(1536),
|
||||
match_count int
|
||||
match_count int,
|
||||
filter jsonb DEFAULT '{}'
|
||||
) returns table (
|
||||
id uuid,
|
||||
content text,
|
||||
@@ -52,6 +53,7 @@ metadata,
|
||||
embedding,
|
||||
1 - (embedding <=> query_embedding) as similarity
|
||||
from documents
|
||||
where metadata @> filter
|
||||
order by embedding <=> query_embedding
|
||||
limit match_count;
|
||||
end;
|
||||
@@ -96,6 +98,7 @@ const index = await VectorStoreIndex.fromDocuments(documents, {
|
||||
```ts
|
||||
const queryEngine = index.asQueryEngine();
|
||||
|
||||
// Basic query without filters
|
||||
const response = await queryEngine.query({
|
||||
query: "What is in the document?",
|
||||
});
|
||||
@@ -104,6 +107,32 @@ const response = await queryEngine.query({
|
||||
console.log(response.toString());
|
||||
```
|
||||
|
||||
## Query with filters
|
||||
|
||||
You can filter documents based on metadata when querying:
|
||||
|
||||
```ts
|
||||
import { FilterOperator, MetadataFilters } from "llamaindex";
|
||||
|
||||
// Create a filter for documents with author = "Jane Smith"
|
||||
const filters: MetadataFilters = {
|
||||
filters: [
|
||||
{
|
||||
key: "author",
|
||||
value: "Jane Smith",
|
||||
operator: FilterOperator.EQ,
|
||||
},
|
||||
],
|
||||
};
|
||||
|
||||
// Query with filters
|
||||
const filteredResponse = await vectorStore.query({
|
||||
queryEmbedding: embedModel.getQueryEmbedding("What is vector search?"),
|
||||
similarityTopK: 5,
|
||||
filters,
|
||||
});
|
||||
```
|
||||
|
||||
## Full code
|
||||
|
||||
```ts
|
||||
|
||||
@@ -11,58 +11,130 @@ npm i llamaindex @llamaindex/google
|
||||
## Usage
|
||||
|
||||
```ts
|
||||
import { Gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { Settings } from "llamaindex";
|
||||
|
||||
Settings.llm = new Gemini({
|
||||
model: GEMINI_MODEL.GEMINI_PRO,
|
||||
});
|
||||
```
|
||||
|
||||
## Usage with Proxy
|
||||
|
||||
```ts
|
||||
import { Gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { Settings } from "llamaindex";
|
||||
|
||||
Settings.llm = new Gemini({
|
||||
model: GEMINI_MODEL.GEMINI_PRO,
|
||||
requestOptions: {
|
||||
baseUrl: <YOUR_PROXY_URL> // optional, but useful for custom endpoints
|
||||
}
|
||||
Settings.llm = gemini({
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH,
|
||||
});
|
||||
```
|
||||
|
||||
### Usage with Vertex AI
|
||||
|
||||
To use Gemini via Vertex AI you can use `GeminiVertexSession`.
|
||||
|
||||
GeminiVertexSession accepts the env variables: `GOOGLE_VERTEX_LOCATION` and `GOOGLE_VERTEX_PROJECT`
|
||||
To use Gemini via Vertex AI, you can specify the vertex configuration:
|
||||
|
||||
```ts
|
||||
import { Gemini, GEMINI_MODEL, GeminiVertexSession } from "@llamaindex/google";
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
|
||||
const gemini = new Gemini({
|
||||
model: GEMINI_MODEL.GEMINI_PRO,
|
||||
session: new GeminiVertexSession({
|
||||
location: "us-central1", // optional if provided by GOOGLE_VERTEX_LOCATION env variable
|
||||
project: "project1", // optional if provided by GOOGLE_VERTEX_PROJECT env variable
|
||||
googleAuthOptions: {...}, // optional, but useful for production. It accepts all values from `GoogleAuthOptions`
|
||||
}),
|
||||
const llm = gemini({
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH,
|
||||
vertex: {
|
||||
project: "your-cloud-project", // required for Vertex AI
|
||||
location: "us-central1", // required for Vertex AI
|
||||
},
|
||||
});
|
||||
```
|
||||
|
||||
[GoogleAuthOptions](https://github.com/googleapis/google-auth-library-nodejs/blob/main/src/auth/googleauth.ts)
|
||||
|
||||
To authenticate for local development:
|
||||
|
||||
```bash
|
||||
npm i @google-cloud/vertexai
|
||||
gcloud auth application-default login
|
||||
```
|
||||
|
||||
To authenticate for production you'll have to use a [service account](https://cloud.google.com/docs/authentication/). `googleAuthOptions` has `credentials` which might be useful for you.
|
||||
|
||||
## Multimodal Usage
|
||||
|
||||
Gemini supports multimodal inputs including text, images, audio, and video:
|
||||
|
||||
```ts
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import fs from "fs";
|
||||
|
||||
const llm = gemini({ model: GEMINI_MODEL.GEMINI_2_0_FLASH });
|
||||
|
||||
const result = await llm.chat({
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: "What's in this image?",
|
||||
},
|
||||
{
|
||||
type: "image",
|
||||
data: fs.readFileSync("./image.jpg").toString("base64"),
|
||||
mimeType: "image/jpeg",
|
||||
},
|
||||
],
|
||||
},
|
||||
],
|
||||
});
|
||||
```
|
||||
|
||||
## Tool Calling
|
||||
|
||||
Gemini supports function calling with tools:
|
||||
|
||||
```ts
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { tool } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
const llm = gemini({ model: GEMINI_MODEL.GEMINI_2_0_FLASH });
|
||||
|
||||
const result = await llm.chat({
|
||||
messages: [
|
||||
{
|
||||
content: "What's the weather in Tokyo?",
|
||||
role: "user",
|
||||
},
|
||||
],
|
||||
tools: [
|
||||
tool({
|
||||
name: "weather",
|
||||
description: "Get the weather",
|
||||
parameters: z.object({
|
||||
location: z.string().describe("The location to get the weather for"),
|
||||
}),
|
||||
execute: ({ location }) => {
|
||||
return `The weather in ${location} is sunny and hot`;
|
||||
},
|
||||
}),
|
||||
],
|
||||
});
|
||||
```
|
||||
|
||||
## Live API (Real-time Conversations)
|
||||
|
||||
For real-time audio/video conversations using [Gemini Live API](https://ai.google.dev/gemini-api/docs/live).
|
||||
|
||||
The Live API is running directly in the frontend. That's why you have to generate an ephemeral key first on the server side and pass it to the frontend.
|
||||
|
||||
To use the Live API, make sure to pass `apiVersion: "v1alpha"` to the `httpOptions`.
|
||||
|
||||
```ts
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
|
||||
// Server-side: Generate ephemeral key
|
||||
const serverLlm = gemini({
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH_LIVE,
|
||||
httpOptions: { apiVersion: "v1alpha" },
|
||||
});
|
||||
const ephemeralKey = await serverLlm.live.getEphemeralKey();
|
||||
|
||||
// Client-side: Use ephemeral key for Live API
|
||||
const llm = gemini({
|
||||
apiKey: ephemeralKey,
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH_LIVE,
|
||||
voiceName: "Zephyr",
|
||||
httpOptions: { apiVersion: "v1alpha" },
|
||||
});
|
||||
|
||||
const session = await llm.live.connect();
|
||||
```
|
||||
|
||||
## Load and index documents
|
||||
|
||||
For this example, we will use a single document. In a real-world scenario, you would have multiple documents to index.
|
||||
@@ -90,11 +162,11 @@ const results = await queryEngine.query({
|
||||
## Full Example
|
||||
|
||||
```ts
|
||||
import { Gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { Document, VectorStoreIndex, Settings } from "llamaindex";
|
||||
|
||||
Settings.llm = new Gemini({
|
||||
model: GEMINI_MODEL.GEMINI_PRO,
|
||||
Settings.llm = gemini({
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH,
|
||||
});
|
||||
|
||||
async function main() {
|
||||
@@ -104,9 +176,7 @@ async function main() {
|
||||
const index = await VectorStoreIndex.fromDocuments([document]);
|
||||
|
||||
// Create a query engine
|
||||
const queryEngine = index.asQueryEngine({
|
||||
retriever,
|
||||
});
|
||||
const queryEngine = index.asQueryEngine();
|
||||
|
||||
const query = "What is the meaning of life?";
|
||||
|
||||
|
||||
@@ -378,3 +378,186 @@ async function main() {
|
||||
## API Reference
|
||||
|
||||
- [OpenAI](/docs/api/classes/OpenAI)
|
||||
|
||||
|
||||
# OpenAI Live LLM
|
||||
|
||||
The OpenAI Live LLM integration in LlamaIndex provides real-time chat capabilities with support for audio streaming and tool calling.
|
||||
|
||||
## Basic Usage
|
||||
|
||||
```typescript
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import { tool, ModalityType } from "llamaindex";
|
||||
|
||||
// Get the ephimeral key on the server
|
||||
const serverllm = openai({
|
||||
apiKey: "your-api-key",
|
||||
model: "gpt-4o-realtime-preview-2025-06-03",
|
||||
});
|
||||
|
||||
// Get an ephemeral key
|
||||
// Usually this code is run on the server and the ephemeral key is passed to the
|
||||
// client - the ephemeral key can be securely used on the client side
|
||||
const ephemeralKey = await serverllm.live.getEphemeralKey();
|
||||
|
||||
// Create a client-side LLM instance with the ephemeral key
|
||||
const llm = openai({
|
||||
apiKey: ephemeralKey,
|
||||
model: "gpt-4o-realtime-preview-2025-06-03"
|
||||
});
|
||||
|
||||
// Create a live sessionimport { tool } from "llamaindex";
|
||||
const session = await llm.live.connect({
|
||||
systemInstruction: "You are a helpful assistant.",
|
||||
});
|
||||
|
||||
// Send a message
|
||||
session.sendMessage({
|
||||
content: "Hello!",
|
||||
role: "user",
|
||||
});
|
||||
```
|
||||
|
||||
## Tool Integration
|
||||
|
||||
Tools are handled server-side, making it simple to pass them to the live session:
|
||||
|
||||
```typescript
|
||||
// Define your tools
|
||||
const weatherTool = tool({
|
||||
name: "weather",
|
||||
description: "Get the weather for a location",
|
||||
parameters: z.object({
|
||||
location: z.string().describe("The location to get weather for"),
|
||||
}),
|
||||
execute: async ({ location }) => {
|
||||
return `The weather in ${location} is sunny`;
|
||||
},
|
||||
});
|
||||
|
||||
// Create session with tools
|
||||
const session = await llm.live.connect({
|
||||
systemInstruction: "You are a helpful assistant.",
|
||||
tools: [weatherTool],
|
||||
});
|
||||
```
|
||||
|
||||
## Audio Support
|
||||
|
||||
For audio capabilities:
|
||||
|
||||
```typescript
|
||||
// Get microphone access
|
||||
const userStream = await navigator.mediaDevices.getUserMedia({
|
||||
audio: true,
|
||||
});
|
||||
|
||||
// Create session with audio
|
||||
const session = await llm.live.connect({
|
||||
audioConfig: {
|
||||
stream: userStream,
|
||||
onTrack: (remoteStream) => {
|
||||
// Handle incoming audio
|
||||
audioElement.srcObject = remoteStream;
|
||||
},
|
||||
},
|
||||
});
|
||||
```
|
||||
|
||||
## Event Handling
|
||||
|
||||
Listen to events from the session:
|
||||
|
||||
```typescript
|
||||
for await (const event of session.streamEvents()) {
|
||||
if (liveEvents.open.include(event)) {
|
||||
// Connection established
|
||||
console.log("Connected!");
|
||||
} else if (liveEvents.text.include(event)) {
|
||||
// Received text response
|
||||
console.log("Assistant:", event.text);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Capabilities
|
||||
|
||||
The OpenAI Live LLM supports:
|
||||
|
||||
- Real-time text chat
|
||||
- Audio streaming (if configured)
|
||||
- Tool calling (server-side execution)
|
||||
- Ephemeral key generation for secure sessions
|
||||
|
||||
## API Reference
|
||||
|
||||
### LiveLLM Methods
|
||||
// Get an ephemeral key
|
||||
// Usually this code is run on the server and the ephemeral key is passed to the
|
||||
// client - the ephemeral key can be securely used on the client side
|
||||
|
||||
#### `connect(config?: LiveConnectConfig)`
|
||||
|
||||
Creates a new live session.
|
||||
|
||||
```typescript
|
||||
interface LiveConnectConfig {
|
||||
systemInstruction?: string;
|
||||
tools?: BaseTool[];
|
||||
audioConfig?: AudioConfig;
|
||||
responseModality?: ModalityType[];
|
||||
}
|
||||
```
|
||||
|
||||
#### `getEphemeralKey()`
|
||||
|
||||
Gets a temporary key for the session.
|
||||
|
||||
### LiveLLMSession Methods
|
||||
|
||||
#### `sendMessage(message: ChatMessage)`
|
||||
|
||||
Sends a message to the assistant.
|
||||
|
||||
```typescript
|
||||
interface ChatMessage {
|
||||
content: string | MessageContentDetail[];
|
||||
role: "user" | "assistant";
|
||||
}
|
||||
```
|
||||
|
||||
#### `disconnect()`
|
||||
|
||||
Closes the session and cleans up resources.
|
||||
|
||||
## Error Handling
|
||||
|
||||
```typescript
|
||||
try {
|
||||
const session = await llm.live.connect();
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
console.error("Connection failed:", error.message);
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
## Best Practices
|
||||
|
||||
1. **Tool Definition**
|
||||
|
||||
- Keep tool implementations server-side
|
||||
- Use clear descriptions for tools
|
||||
- Handle tool errors gracefully
|
||||
|
||||
2. **Session Management**
|
||||
|
||||
- Always disconnect sessions when done
|
||||
- Clean up audio resources
|
||||
- Handle reconnection scenarios
|
||||
|
||||
3. **Security**
|
||||
- Use ephemeral keys for sessions
|
||||
- Validate tool inputs
|
||||
- Secure API key handling
|
||||
|
||||
@@ -1,3 +1,3 @@
|
||||
{
|
||||
"pages": ["llamaindex", "api", "llamaflow", "chat-ui"]
|
||||
"pages": ["llamaindex", "api", "workflows", "chat-ui"]
|
||||
}
|
||||
|
||||
@@ -4,7 +4,7 @@
|
||||
"tasks": {
|
||||
"build": {
|
||||
"inputs": [
|
||||
"node_modules/@llama-flow/docs/**",
|
||||
"node_modules/@llamaindex/workflow-docs/**",
|
||||
"node_modules/@llamaindex/chat-ui-docs/**",
|
||||
"src/**/*.ts",
|
||||
"src/**/*.tsx",
|
||||
|
||||
@@ -1,5 +1,43 @@
|
||||
# @llamaindex/cloudflare-worker-agent-test
|
||||
|
||||
## 0.0.172
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
|
||||
## 0.0.171
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 0.0.170
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
|
||||
## 0.0.169
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
|
||||
## 0.0.168
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 0.0.167
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 0.0.166
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/cloudflare-worker-agent-test",
|
||||
"version": "0.0.166",
|
||||
"version": "0.0.172",
|
||||
"type": "module",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
|
||||
@@ -1,5 +1,23 @@
|
||||
# @llamaindex/llama-parse-browser-test
|
||||
|
||||
## 0.0.71
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@4.0.16
|
||||
|
||||
## 0.0.70
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@4.0.15
|
||||
|
||||
## 0.0.69
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/cloud@4.0.14
|
||||
|
||||
## 0.0.68
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "@llamaindex/llama-parse-browser-test",
|
||||
"private": true,
|
||||
"version": "0.0.68",
|
||||
"version": "0.0.71",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
|
||||
@@ -1,5 +1,43 @@
|
||||
# @llamaindex/next-agent-test
|
||||
|
||||
## 0.1.172
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
|
||||
## 0.1.171
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 0.1.170
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
|
||||
## 0.1.169
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
|
||||
## 0.1.168
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 0.1.167
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 0.1.166
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/next-agent-test",
|
||||
"version": "0.1.166",
|
||||
"version": "0.1.172",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
|
||||
@@ -1,5 +1,43 @@
|
||||
# test-edge-runtime
|
||||
|
||||
## 0.1.171
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
|
||||
## 0.1.170
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 0.1.169
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
|
||||
## 0.1.168
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
|
||||
## 0.1.167
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 0.1.166
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 0.1.165
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/nextjs-edge-runtime-test",
|
||||
"version": "0.1.165",
|
||||
"version": "0.1.171",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
|
||||
@@ -1,5 +1,56 @@
|
||||
# @llamaindex/next-node-runtime
|
||||
|
||||
## 0.1.40
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
- @llamaindex/huggingface@0.1.16
|
||||
- @llamaindex/readers@3.1.11
|
||||
|
||||
## 0.1.39
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 0.1.38
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [c5846bd]
|
||||
- @llamaindex/readers@3.1.10
|
||||
|
||||
## 0.1.37
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
- @llamaindex/huggingface@0.1.15
|
||||
- @llamaindex/readers@3.1.9
|
||||
|
||||
## 0.1.36
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
- @llamaindex/huggingface@0.1.14
|
||||
- @llamaindex/readers@3.1.8
|
||||
|
||||
## 0.1.35
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 0.1.34
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 0.1.33
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/next-node-runtime-test",
|
||||
"version": "0.1.33",
|
||||
"version": "0.1.40",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"dev": "next dev",
|
||||
|
||||
@@ -1,5 +1,43 @@
|
||||
# vite-import-llamaindex
|
||||
|
||||
## 0.0.38
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
|
||||
## 0.0.37
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 0.0.36
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
|
||||
## 0.0.35
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
|
||||
## 0.0.34
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 0.0.33
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 0.0.32
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "vite-import-llamaindex",
|
||||
"private": true,
|
||||
"version": "0.0.32",
|
||||
"version": "0.0.38",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"build": "vite build",
|
||||
|
||||
@@ -1 +1,9 @@
|
||||
{"root":["./src/main.ts","./vite.config.ts"],"version":"5.7.3"}
|
||||
{
|
||||
"root": [
|
||||
"./src/main.ts",
|
||||
"./vite.config.ts",
|
||||
"./tsconfig.json"
|
||||
],
|
||||
"errors": true,
|
||||
"version": "5.7.3"
|
||||
}
|
||||
|
||||
@@ -1,5 +1,43 @@
|
||||
# @llamaindex/waku-query-engine-test
|
||||
|
||||
## 0.0.172
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
|
||||
## 0.0.171
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 0.0.170
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
|
||||
## 0.0.169
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
|
||||
## 0.0.168
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 0.0.167
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 0.0.166
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/waku-query-engine-test",
|
||||
"version": "0.0.166",
|
||||
"version": "0.0.172",
|
||||
"type": "module",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
|
||||
@@ -7,7 +7,7 @@
|
||||
"dependencies": {
|
||||
"@llamaindex/workflow": "1.1.1",
|
||||
"llamaindex": "0.10.5",
|
||||
"zod": "^3.23.8"
|
||||
"zod": "^3.25.67"
|
||||
},
|
||||
"devDependencies": {
|
||||
"tsx": "^4.19.1",
|
||||
|
||||
+1
-1
@@ -27,6 +27,6 @@
|
||||
"pg": "^8.12.0",
|
||||
"pgvector": "0.2.0",
|
||||
"tsx": "^4.19.3",
|
||||
"zod": "^3.24.2"
|
||||
"zod": "^3.25.67"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,5 +1,189 @@
|
||||
# examples
|
||||
|
||||
## 0.3.25
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
- @llamaindex/core@0.6.12
|
||||
- @llamaindex/google@0.3.11
|
||||
- @llamaindex/cloud@4.0.16
|
||||
- @llamaindex/node-parser@2.0.12
|
||||
- @llamaindex/anthropic@0.3.14
|
||||
- @llamaindex/assemblyai@0.1.11
|
||||
- @llamaindex/clip@0.0.62
|
||||
- @llamaindex/cohere@0.0.26
|
||||
- @llamaindex/deepinfra@0.0.62
|
||||
- @llamaindex/discord@0.1.11
|
||||
- @llamaindex/huggingface@0.1.16
|
||||
- @llamaindex/jinaai@0.0.22
|
||||
- @llamaindex/mistral@0.1.12
|
||||
- @llamaindex/mixedbread@0.0.26
|
||||
- @llamaindex/notion@0.1.11
|
||||
- @llamaindex/ollama@0.1.12
|
||||
- @llamaindex/openai@0.4.6
|
||||
- @llamaindex/perplexity@0.0.19
|
||||
- @llamaindex/portkey-ai@0.0.54
|
||||
- @llamaindex/replicate@0.0.54
|
||||
- @llamaindex/astra@0.0.26
|
||||
- @llamaindex/azure@0.1.23
|
||||
- @llamaindex/chroma@0.0.26
|
||||
- @llamaindex/elastic-search@0.1.12
|
||||
- @llamaindex/firestore@1.0.19
|
||||
- @llamaindex/milvus@0.1.21
|
||||
- @llamaindex/mongodb@0.0.27
|
||||
- @llamaindex/pinecone@0.1.12
|
||||
- @llamaindex/postgres@0.0.55
|
||||
- @llamaindex/qdrant@0.1.22
|
||||
- @llamaindex/supabase@0.1.12
|
||||
- @llamaindex/upstash@0.0.26
|
||||
- @llamaindex/weaviate@0.0.27
|
||||
- @llamaindex/vercel@0.1.12
|
||||
- @llamaindex/voyage-ai@1.0.18
|
||||
- @llamaindex/readers@3.1.11
|
||||
- @llamaindex/tools@0.1.1
|
||||
- @llamaindex/workflow@1.1.12
|
||||
- @llamaindex/deepseek@0.0.22
|
||||
- @llamaindex/fireworks@0.0.22
|
||||
- @llamaindex/groq@0.0.77
|
||||
- @llamaindex/together@0.0.22
|
||||
- @llamaindex/vllm@0.0.48
|
||||
- @llamaindex/xai@0.0.9
|
||||
|
||||
## 0.3.24
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [096bf2b]
|
||||
- Updated dependencies [c5846bd]
|
||||
- @llamaindex/tools@0.1.0
|
||||
- @llamaindex/readers@3.1.10
|
||||
|
||||
## 0.3.23
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [a89e187]
|
||||
- Updated dependencies [62699b7]
|
||||
- Updated dependencies [c5b2691]
|
||||
- Updated dependencies [d8ac8d3]
|
||||
- @llamaindex/core@0.6.11
|
||||
- @llamaindex/google@0.3.10
|
||||
- @llamaindex/openai@0.4.5
|
||||
- @llamaindex/cloud@4.0.15
|
||||
- llamaindex@0.11.9
|
||||
- @llamaindex/node-parser@2.0.11
|
||||
- @llamaindex/anthropic@0.3.13
|
||||
- @llamaindex/assemblyai@0.1.10
|
||||
- @llamaindex/clip@0.0.61
|
||||
- @llamaindex/cohere@0.0.25
|
||||
- @llamaindex/deepinfra@0.0.61
|
||||
- @llamaindex/discord@0.1.10
|
||||
- @llamaindex/huggingface@0.1.15
|
||||
- @llamaindex/jinaai@0.0.21
|
||||
- @llamaindex/mistral@0.1.11
|
||||
- @llamaindex/mixedbread@0.0.25
|
||||
- @llamaindex/notion@0.1.10
|
||||
- @llamaindex/ollama@0.1.11
|
||||
- @llamaindex/perplexity@0.0.18
|
||||
- @llamaindex/portkey-ai@0.0.53
|
||||
- @llamaindex/replicate@0.0.53
|
||||
- @llamaindex/astra@0.0.25
|
||||
- @llamaindex/azure@0.1.22
|
||||
- @llamaindex/chroma@0.0.25
|
||||
- @llamaindex/elastic-search@0.1.11
|
||||
- @llamaindex/firestore@1.0.18
|
||||
- @llamaindex/milvus@0.1.20
|
||||
- @llamaindex/mongodb@0.0.26
|
||||
- @llamaindex/pinecone@0.1.11
|
||||
- @llamaindex/postgres@0.0.54
|
||||
- @llamaindex/qdrant@0.1.21
|
||||
- @llamaindex/supabase@0.1.10
|
||||
- @llamaindex/upstash@0.0.25
|
||||
- @llamaindex/weaviate@0.0.26
|
||||
- @llamaindex/vercel@0.1.11
|
||||
- @llamaindex/voyage-ai@1.0.17
|
||||
- @llamaindex/readers@3.1.9
|
||||
- @llamaindex/tools@0.0.17
|
||||
- @llamaindex/workflow@1.1.10
|
||||
- @llamaindex/deepseek@0.0.21
|
||||
- @llamaindex/fireworks@0.0.21
|
||||
- @llamaindex/groq@0.0.76
|
||||
- @llamaindex/together@0.0.21
|
||||
- @llamaindex/vllm@0.0.47
|
||||
- @llamaindex/xai@0.0.8
|
||||
|
||||
## 0.3.22
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [8a51c16]
|
||||
- Updated dependencies [1b5af14]
|
||||
- @llamaindex/workflow@1.1.9
|
||||
- @llamaindex/core@0.6.10
|
||||
- llamaindex@0.11.8
|
||||
- @llamaindex/cloud@4.0.14
|
||||
- @llamaindex/node-parser@2.0.10
|
||||
- @llamaindex/anthropic@0.3.12
|
||||
- @llamaindex/assemblyai@0.1.9
|
||||
- @llamaindex/clip@0.0.60
|
||||
- @llamaindex/cohere@0.0.24
|
||||
- @llamaindex/deepinfra@0.0.60
|
||||
- @llamaindex/discord@0.1.9
|
||||
- @llamaindex/google@0.3.9
|
||||
- @llamaindex/huggingface@0.1.14
|
||||
- @llamaindex/jinaai@0.0.20
|
||||
- @llamaindex/mistral@0.1.10
|
||||
- @llamaindex/mixedbread@0.0.24
|
||||
- @llamaindex/notion@0.1.9
|
||||
- @llamaindex/ollama@0.1.10
|
||||
- @llamaindex/openai@0.4.4
|
||||
- @llamaindex/perplexity@0.0.17
|
||||
- @llamaindex/portkey-ai@0.0.52
|
||||
- @llamaindex/replicate@0.0.52
|
||||
- @llamaindex/astra@0.0.24
|
||||
- @llamaindex/azure@0.1.21
|
||||
- @llamaindex/chroma@0.0.24
|
||||
- @llamaindex/elastic-search@0.1.10
|
||||
- @llamaindex/firestore@1.0.17
|
||||
- @llamaindex/milvus@0.1.19
|
||||
- @llamaindex/mongodb@0.0.25
|
||||
- @llamaindex/pinecone@0.1.10
|
||||
- @llamaindex/postgres@0.0.53
|
||||
- @llamaindex/qdrant@0.1.20
|
||||
- @llamaindex/supabase@0.1.9
|
||||
- @llamaindex/upstash@0.0.24
|
||||
- @llamaindex/weaviate@0.0.25
|
||||
- @llamaindex/vercel@0.1.10
|
||||
- @llamaindex/voyage-ai@1.0.16
|
||||
- @llamaindex/readers@3.1.8
|
||||
- @llamaindex/tools@0.0.16
|
||||
- @llamaindex/deepseek@0.0.20
|
||||
- @llamaindex/fireworks@0.0.20
|
||||
- @llamaindex/groq@0.0.75
|
||||
- @llamaindex/together@0.0.20
|
||||
- @llamaindex/vllm@0.0.46
|
||||
- @llamaindex/xai@0.0.7
|
||||
|
||||
## 0.3.21
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [dbd857f]
|
||||
- Updated dependencies [3c857f4]
|
||||
- @llamaindex/workflow@1.1.8
|
||||
- llamaindex@0.11.7
|
||||
- @llamaindex/tools@0.0.15
|
||||
|
||||
## 0.3.20
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [e7484ef]
|
||||
- @llamaindex/weaviate@0.0.24
|
||||
|
||||
## 0.3.19
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,4 +1,3 @@
|
||||
import { tool } from "@llamaindex/core/tools";
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import {
|
||||
agent,
|
||||
@@ -7,6 +6,7 @@ import {
|
||||
multiAgent,
|
||||
} from "@llamaindex/workflow";
|
||||
import fs from "fs";
|
||||
import { tool } from "llamaindex";
|
||||
import os from "os";
|
||||
import { z } from "zod";
|
||||
|
||||
|
||||
@@ -6,15 +6,24 @@ async function main() {
|
||||
// Create an MCP server for filesystem tools
|
||||
const server = mcp({
|
||||
command: "npx",
|
||||
args: ["-y", "@modelcontextprotocol/server-filesystem", "."],
|
||||
args: ["-y", "@modelcontextprotocol/server-filesystem@latest", "."],
|
||||
verbose: true,
|
||||
});
|
||||
// You can also connect to the MCP server using SSE
|
||||
// See: https://modelcontextprotocol.io/docs/concepts/transports#server-sent-events-sse
|
||||
//
|
||||
// You can also connect to a remote MCP server using:
|
||||
// 1. StreamableHTTP transport (recommended)
|
||||
// See: https://modelcontextprotocol.io/docs/concepts/transports#streamable-http
|
||||
// const server = mcp({
|
||||
// url: "http://localhost:8000/mcp",
|
||||
// verbose: true,
|
||||
// });
|
||||
// 2.Or using SSE transport (will be deprecated soon)
|
||||
// See: https://modelcontextprotocol.io/docs/concepts/transports#server-sent-events-sse-deprecated
|
||||
// const server = mcp({
|
||||
// url: "http://localhost:8000/mcp",
|
||||
// useSSETransport: true,
|
||||
// verbose: true,
|
||||
// });
|
||||
|
||||
try {
|
||||
// Create an agent that uses the MCP tools
|
||||
|
||||
@@ -0,0 +1,130 @@
|
||||
import { ToolCallLLM } from "llamaindex";
|
||||
|
||||
import {
|
||||
agentHandler,
|
||||
createWorkflow,
|
||||
workflowEvent,
|
||||
zodEvent,
|
||||
} from "@llamaindex/workflow";
|
||||
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import { z } from "zod";
|
||||
|
||||
// ===== 1. Define events =====
|
||||
// An event to trigger the workflow
|
||||
const planEvent = workflowEvent<{ topic: string }>();
|
||||
|
||||
// Generate artifact event
|
||||
const ArtifactRequirementSchema = z.object({
|
||||
type: z.literal("markdown"),
|
||||
title: z.string().describe("The title of the artifact."),
|
||||
requirement: z
|
||||
.string()
|
||||
.describe("The requirement for the artifact generation."),
|
||||
});
|
||||
|
||||
const generateArtifactEvent = zodEvent(ArtifactRequirementSchema, {
|
||||
debugLabel: "generateArtifactEvent",
|
||||
});
|
||||
|
||||
// Artifact output event
|
||||
const ArtifactSchema = z.object({
|
||||
type: z.literal("artifact"),
|
||||
data: z.object({
|
||||
type: z.literal("document"),
|
||||
data: z.object({
|
||||
title: z.string().describe("The title of the data."),
|
||||
content: z.string().describe("The content of the data."),
|
||||
type: z.enum(["markdown", "html"]).describe("The type of the data."),
|
||||
}),
|
||||
}),
|
||||
});
|
||||
const outputArtifactEvent = zodEvent(ArtifactSchema, {
|
||||
debugLabel: "outputArtifactEvent",
|
||||
});
|
||||
|
||||
// Events for updating UI
|
||||
// assume that we have a UI that can render different states of the workflow
|
||||
// and update the UI based on the state and the requirement
|
||||
export const UIEventSchema = z.object({
|
||||
type: z.literal("ui_event"),
|
||||
data: z.object({
|
||||
state: z
|
||||
.enum(["plan", "generate", "completed"])
|
||||
.describe("The current state of the workflow."),
|
||||
requirement: z
|
||||
.string()
|
||||
.optional()
|
||||
.describe(
|
||||
"An optional requirement creating or updating a document, if applicable.",
|
||||
),
|
||||
}),
|
||||
});
|
||||
const uiEvent = zodEvent(UIEventSchema, { debugLabel: "uiEvent" });
|
||||
|
||||
// ===== 2. Define workflow with agents using natural language =====
|
||||
// We have a document artifact workflow that made up of 2 steps:
|
||||
// 1. Generate requirement for the document
|
||||
// 2. Generate document content based on the requirement
|
||||
export function createDocumentArtifactWorkflow(llm: ToolCallLLM) {
|
||||
const workflow = createWorkflow();
|
||||
|
||||
// Generate requirement for the document
|
||||
workflow.handle(
|
||||
[planEvent],
|
||||
agentHandler({
|
||||
instructions: `
|
||||
Your task is to analyze the request and provide requirements for document generation or update.
|
||||
1. Send an uiEvent with the \`plan\` to show UI what you are going to do.
|
||||
2. Analyze the conversation history and the user's request carefully to determine the completed tasks and the next steps.
|
||||
3. Return the generateArtifactEvent with the requirement for the next step of the document generation or update.
|
||||
`,
|
||||
results: [generateArtifactEvent],
|
||||
events: [uiEvent],
|
||||
llm,
|
||||
}),
|
||||
);
|
||||
|
||||
// Generate document content based on the requirement
|
||||
workflow.handle(
|
||||
[generateArtifactEvent],
|
||||
agentHandler({
|
||||
instructions: `
|
||||
You are a skilled technical writer who can assist users with documentation.
|
||||
Your task is to generate document content based on the requirement and update the UI state.
|
||||
|
||||
Here are the steps to handle this task:
|
||||
1. First, send an uiEvent with the \`generate\` state and the requirement you received from the input.
|
||||
2. Next, start generating the content based on the requirement then send an uiEvent with the \`completed\` state to update the state.
|
||||
3. Finally, return the outputArtifactEvent with the document values.
|
||||
`,
|
||||
results: [outputArtifactEvent],
|
||||
events: [uiEvent],
|
||||
llm,
|
||||
}),
|
||||
);
|
||||
|
||||
return workflow;
|
||||
}
|
||||
|
||||
async function main() {
|
||||
const llm = openai({ model: "gpt-4.1-mini" });
|
||||
const workflow = createDocumentArtifactWorkflow(llm);
|
||||
const { stream, sendEvent } = workflow.createContext();
|
||||
|
||||
// Ask the workflow to generate a document about `llama`
|
||||
sendEvent(planEvent.with({ topic: "llama" }));
|
||||
|
||||
await stream.until(outputArtifactEvent).forEach((event) => {
|
||||
if (planEvent.include(event)) {
|
||||
console.log("Starting workflow: ", event.data);
|
||||
}
|
||||
if (uiEvent.include(event)) {
|
||||
console.log("UI event: ", event.data);
|
||||
} else if (outputArtifactEvent.include(event)) {
|
||||
console.log("Output artifact event: ", event.data);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
main();
|
||||
@@ -0,0 +1,93 @@
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import { agentHandler, createWorkflow, zodEvent } from "@llamaindex/workflow";
|
||||
import { Settings } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
// Create LLM instance
|
||||
const llm = openai({ model: "gpt-4.1-mini" });
|
||||
Settings.llm = llm;
|
||||
|
||||
// Define our workflow events
|
||||
const writeJokeSchema = z.object({
|
||||
description: z
|
||||
.string()
|
||||
.describe("The topic to write a joke or describe the joke to improve."),
|
||||
writtenJoke: z.optional(z.string()).describe("The written joke."),
|
||||
retriedTimes: z
|
||||
.number()
|
||||
.default(0)
|
||||
.describe(
|
||||
"The retried times for writing the joke. Always increase this from the input retriedTimes.",
|
||||
),
|
||||
});
|
||||
|
||||
const critiqueSchema = z.object({
|
||||
joke: z.string().describe("The joke to critique"),
|
||||
retriedTimes: z.number().describe("The retried times for writing the joke."),
|
||||
});
|
||||
|
||||
const finalResultSchema = z.object({
|
||||
joke: z.string().describe("The joke to critique"),
|
||||
critique: z.string().describe("The critique of the joke"),
|
||||
});
|
||||
|
||||
const writeJokeEvent = zodEvent(writeJokeSchema, {
|
||||
debugLabel: "writeJokeEvent",
|
||||
}); // Input topic for writing a joke
|
||||
const critiqueEvent = zodEvent(critiqueSchema, {
|
||||
debugLabel: "critiqueEvent",
|
||||
}); // Ask for critique of the joke
|
||||
const finalResultEvent = zodEvent(finalResultSchema, {
|
||||
debugLabel: "finalResultEvent",
|
||||
}); // Final result
|
||||
|
||||
// Create our workflow
|
||||
const jokeFlow = createWorkflow();
|
||||
|
||||
// Define handlers for each step
|
||||
// This step always write a joke based on the description
|
||||
jokeFlow.handle(
|
||||
[writeJokeEvent],
|
||||
agentHandler({
|
||||
instructions: `You are a joke writer. You are given a topic and you need to write a joke about it.`,
|
||||
results: [critiqueEvent],
|
||||
}),
|
||||
);
|
||||
|
||||
// This step critiques the joke and asks the writer to improve the joke or send a final result event for stopping.
|
||||
jokeFlow.handle(
|
||||
[critiqueEvent],
|
||||
agentHandler({
|
||||
instructions: `
|
||||
You are given a joke and you need to critique it. Follow the following guidelines:
|
||||
1. You have maximum 3 times to improve the joke.
|
||||
2. If the joke is not good, increase the retriedTimes, describe how to improve the joke and send a writeJokeEvent.
|
||||
3. If the joke is good, trigger the finalResultEvent event.
|
||||
`,
|
||||
results: [writeJokeEvent, finalResultEvent],
|
||||
}),
|
||||
);
|
||||
|
||||
// Usage
|
||||
async function main() {
|
||||
const { stream, sendEvent } = jokeFlow.createContext();
|
||||
sendEvent(writeJokeEvent.with({ description: "write a joke about llama" }));
|
||||
|
||||
await stream.until(finalResultEvent).forEach((event) => {
|
||||
if (writeJokeEvent.include(event)) {
|
||||
console.log(
|
||||
"Triggering write joke: ",
|
||||
JSON.stringify(event.data, null, 2),
|
||||
);
|
||||
} else if (critiqueEvent.include(event)) {
|
||||
console.log("Written joke: ", JSON.stringify(event.data, null, 2));
|
||||
} else if (finalResultEvent.include(event)) {
|
||||
console.log("Output: ", JSON.stringify(event.data, null, 2));
|
||||
} else {
|
||||
console.log("Unknown event: ", JSON.stringify(event.data, null, 2));
|
||||
}
|
||||
});
|
||||
console.log("Done");
|
||||
}
|
||||
|
||||
main().catch(console.error);
|
||||
@@ -0,0 +1,72 @@
|
||||
<?xml version="1.0" encoding="UTF-8"?>
|
||||
<company name="MidSizeCorp" founded="2008">
|
||||
<division name="Engineering" head="Dana White">
|
||||
<department name="Frontend" lead="Alex Kim">
|
||||
<team name="Web">
|
||||
<employee id="E01">
|
||||
<name>Jordan Lee</name>
|
||||
<role>Lead Developer</role>
|
||||
<projects>
|
||||
<project code="PRJ101" status="active">
|
||||
<title>User Portal</title>
|
||||
<deadline>2025-08-01</deadline>
|
||||
<tasks>
|
||||
<task id="T1011">
|
||||
<description>Implement login page</description>
|
||||
<due>2025-05-10</due>
|
||||
</task>
|
||||
<task id="T1012">
|
||||
<description>Design dashboard</description>
|
||||
<due>2025-05-20</due>
|
||||
</task>
|
||||
</tasks>
|
||||
</project>
|
||||
</projects>
|
||||
</employee>
|
||||
<employee id="E02">
|
||||
<name>Riley Chen</name>
|
||||
<role>UI Designer</role>
|
||||
</employee>
|
||||
</team>
|
||||
<team name="Mobile">
|
||||
<employee id="E03">
|
||||
<name>Sam Patel</name>
|
||||
<role>iOS Developer</role>
|
||||
</employee>
|
||||
</team>
|
||||
</department>
|
||||
<department name="Backend" lead="Morgan Reed">
|
||||
<team name="API">
|
||||
<employee id="E04">
|
||||
<name>Taylor Jones</name>
|
||||
<role>API Engineer</role>
|
||||
</employee>
|
||||
</team>
|
||||
<team name="Database">
|
||||
<employee id="E05">
|
||||
<name>Casey Nguyen</name>
|
||||
<role>DB Administrator</role>
|
||||
</employee>
|
||||
</team>
|
||||
</department>
|
||||
</division>
|
||||
|
||||
<division name="Marketing" head="Pat Morgan">
|
||||
<department name="Digital" lead="Alex Rivera">
|
||||
<team name="Content">
|
||||
<employee id="M01">
|
||||
<name>Charlie Brooks</name>
|
||||
<role>Content Strategist</role>
|
||||
</employee>
|
||||
</team>
|
||||
</department>
|
||||
</division>
|
||||
|
||||
<headquarters location="Chicago, USA">
|
||||
<address>
|
||||
<street>789 Lake Shore Drive</street>
|
||||
<city>Chicago</city>
|
||||
<zip>60601</zip>
|
||||
</address>
|
||||
</headquarters>
|
||||
</company>
|
||||
Binary file not shown.
@@ -1,14 +1,16 @@
|
||||
import { Gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import fs from "fs";
|
||||
import { tool } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
(async () => {
|
||||
if (!process.env.GOOGLE_API_KEY) {
|
||||
throw new Error("Please set the GOOGLE_API_KEY environment variable.");
|
||||
}
|
||||
const gemini = new Gemini({
|
||||
model: GEMINI_MODEL.GEMINI_PRO_1_5,
|
||||
});
|
||||
const result = await gemini.chat({
|
||||
const llm = gemini({ model: GEMINI_MODEL.GEMINI_2_0_FLASH });
|
||||
|
||||
// normal chat
|
||||
const result = await llm.chat({
|
||||
messages: [
|
||||
{ content: "You want to talk in rhymes.", role: "system" },
|
||||
{
|
||||
@@ -18,10 +20,10 @@ import fs from "fs";
|
||||
},
|
||||
],
|
||||
});
|
||||
console.log(result);
|
||||
console.log("\n normal chat: \n", result);
|
||||
|
||||
// chat with file
|
||||
const resultWithFile = await gemini.chat({
|
||||
const resultWithFile = await llm.chat({
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
@@ -39,6 +41,52 @@ import fs from "fs";
|
||||
},
|
||||
],
|
||||
});
|
||||
console.log("\n chat with file: \n", resultWithFile);
|
||||
|
||||
console.log(resultWithFile);
|
||||
// chat with image base64
|
||||
const resultWithImageFile = await llm.chat({
|
||||
messages: [
|
||||
{
|
||||
role: "user",
|
||||
content: [
|
||||
{
|
||||
type: "text",
|
||||
text: "What's in this image?",
|
||||
},
|
||||
{
|
||||
type: "image",
|
||||
data: fs
|
||||
.readFileSync("./multimodal/data/60.jpg")
|
||||
.toString("base64"),
|
||||
mimeType: "image/png",
|
||||
},
|
||||
],
|
||||
},
|
||||
],
|
||||
});
|
||||
console.log("\n chat with image base64: \n", resultWithImageFile);
|
||||
|
||||
// chat with tool
|
||||
const resultWithTool = await llm.chat({
|
||||
messages: [
|
||||
{
|
||||
content: "What's the weather in Tokyo?",
|
||||
role: "user",
|
||||
},
|
||||
],
|
||||
tools: [
|
||||
tool({
|
||||
name: "weather",
|
||||
description: "Get the weather",
|
||||
parameters: z.object({
|
||||
location: z.string().describe("The location to get the weather for"),
|
||||
}),
|
||||
execute: ({ location }) => {
|
||||
console.log("weather", location);
|
||||
return `The weather in ${location} is sunny and hot`;
|
||||
},
|
||||
}),
|
||||
],
|
||||
});
|
||||
console.log("\n chat with tool: \n", resultWithTool.message.options); // should have toolCall
|
||||
})();
|
||||
|
||||
@@ -1,11 +1,14 @@
|
||||
import { Gemini, GEMINI_MODEL, GeminiVertexSession } from "@llamaindex/google";
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
|
||||
(async () => {
|
||||
const gemini = new Gemini({
|
||||
model: GEMINI_MODEL.GEMINI_PRO,
|
||||
session: new GeminiVertexSession(),
|
||||
const llm = gemini({
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH,
|
||||
vertex: {
|
||||
project: "your-cloud-project", // update to your cloud project
|
||||
location: "us-central1",
|
||||
},
|
||||
});
|
||||
const result = await gemini.chat({
|
||||
const result = await llm.chat({
|
||||
messages: [
|
||||
{ content: "You want to talk in rhymes.", role: "system" },
|
||||
{
|
||||
|
||||
@@ -16,9 +16,19 @@ async function main() {
|
||||
|
||||
console.log("🚀 Initializing Gemini Live API example...");
|
||||
|
||||
// Server-side (token creation):
|
||||
const serverllm = gemini({
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH_LIVE,
|
||||
httpOptions: { apiVersion: "v1alpha" }, // must use v1alpha to generate ephemeral key
|
||||
});
|
||||
const ephemeralKey = await serverllm.live.getEphemeralKey();
|
||||
|
||||
// Client-side (Live API connection):
|
||||
const llm = gemini({
|
||||
apiKey: ephemeralKey, // use ephemeral key for client-side
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH_LIVE,
|
||||
voiceName: "Zephyr",
|
||||
httpOptions: { apiVersion: "v1alpha" }, // must use v1alpha to init client with ephemeral key
|
||||
});
|
||||
|
||||
console.log("📡 Connecting to Gemini Live session...");
|
||||
|
||||
@@ -3,8 +3,18 @@ import { liveEvents } from "llamaindex";
|
||||
import { saveWavFile } from "./util";
|
||||
|
||||
async function main() {
|
||||
const llm = gemini({
|
||||
// Server-side (token creation):
|
||||
const serverllm = gemini({
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH_LIVE,
|
||||
httpOptions: { apiVersion: "v1alpha" }, // must use v1alpha to generate ephemeral key
|
||||
});
|
||||
const ephemeralKey = await serverllm.live.getEphemeralKey();
|
||||
|
||||
// Client-side (Live API connection):
|
||||
const llm = gemini({
|
||||
apiKey: ephemeralKey, // use ephemeral key for client-side
|
||||
model: GEMINI_MODEL.GEMINI_2_0_FLASH_LIVE,
|
||||
httpOptions: { apiVersion: "v1alpha" }, // must use v1alpha to init client with ephemeral key
|
||||
});
|
||||
|
||||
const session = await llm.live.connect();
|
||||
@@ -23,10 +33,7 @@ async function main() {
|
||||
content: "Say something about you for 10 seconds",
|
||||
role: "user",
|
||||
});
|
||||
} else if (
|
||||
liveEvents.audio.include(event) &&
|
||||
typeof event.data === "string"
|
||||
) {
|
||||
} else if (liveEvents.audio.include(event)) {
|
||||
const chunk = Buffer.from(event.data, "base64");
|
||||
audioChunks.push(chunk);
|
||||
console.log(`Received audio chunk: ${chunk.length} bytes`);
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
import { ModalityType } from "@llamaindex/core/schema";
|
||||
import { tool } from "@llamaindex/core/tools";
|
||||
import { gemini, GEMINI_MODEL } from "@llamaindex/google";
|
||||
import { ModalityType, tool } from "llamaindex";
|
||||
|
||||
import { liveEvents } from "llamaindex";
|
||||
import { z } from "zod";
|
||||
|
||||
@@ -0,0 +1,24 @@
|
||||
# Logs
|
||||
logs
|
||||
*.log
|
||||
npm-debug.log*
|
||||
yarn-debug.log*
|
||||
yarn-error.log*
|
||||
pnpm-debug.log*
|
||||
lerna-debug.log*
|
||||
|
||||
node_modules
|
||||
dist
|
||||
dist-ssr
|
||||
*.local
|
||||
|
||||
# Editor directories and files
|
||||
.vscode/*
|
||||
!.vscode/extensions.json
|
||||
.idea
|
||||
.DS_Store
|
||||
*.suo
|
||||
*.ntvs*
|
||||
*.njsproj
|
||||
*.sln
|
||||
*.sw?
|
||||
@@ -0,0 +1,54 @@
|
||||
# OpenAI Realtime Chat with LlamaIndex
|
||||
|
||||
This is a demo application showcasing real-time audio and text chat capabilities using OpenAI's GPT-4 with voice through LlamaIndex. The application demonstrates bidirectional audio communication and text chat with an AI assistant.
|
||||
|
||||
## Features
|
||||
|
||||
- Real-time voice communication with GPT-4
|
||||
- Text-based chat interface
|
||||
- WebRTC-based audio streaming
|
||||
- Bidirectional communication (both text and voice)
|
||||
- React + TypeScript implementation
|
||||
|
||||
## Prerequisites
|
||||
|
||||
- Node.js (v18 or higher)
|
||||
- OpenAI API key with access to GPT-4 voice models
|
||||
- Modern browser with WebRTC support
|
||||
|
||||
## Getting Started
|
||||
|
||||
1. Install dependencies:
|
||||
|
||||
```bash
|
||||
pnpm install
|
||||
```
|
||||
|
||||
2. Start the development server:
|
||||
|
||||
```bash
|
||||
pnpm run dev
|
||||
```
|
||||
|
||||
## Usage
|
||||
|
||||
The application provides a simple interface where you can:
|
||||
|
||||
- Start/Stop a chat session
|
||||
- Speak to the AI assistant through your microphone
|
||||
- Receive audio responses from the assistant
|
||||
- See text transcripts of the conversation
|
||||
|
||||
## Technical Details
|
||||
|
||||
This project uses:
|
||||
|
||||
- LlamaIndex for AI interaction management
|
||||
- WebRTC for real-time audio streaming
|
||||
- React for the UI
|
||||
- Vite for development and building
|
||||
- TypeScript for type safety
|
||||
|
||||
```
|
||||
|
||||
```
|
||||
@@ -0,0 +1,28 @@
|
||||
import js from "@eslint/js";
|
||||
import reactHooks from "eslint-plugin-react-hooks";
|
||||
import reactRefresh from "eslint-plugin-react-refresh";
|
||||
import globals from "globals";
|
||||
import tseslint from "typescript-eslint";
|
||||
|
||||
export default tseslint.config(
|
||||
{ ignores: ["dist"] },
|
||||
{
|
||||
extends: [js.configs.recommended, ...tseslint.configs.recommended],
|
||||
files: ["**/*.{ts,tsx}"],
|
||||
languageOptions: {
|
||||
ecmaVersion: 2020,
|
||||
globals: globals.browser,
|
||||
},
|
||||
plugins: {
|
||||
"react-hooks": reactHooks,
|
||||
"react-refresh": reactRefresh,
|
||||
},
|
||||
rules: {
|
||||
...reactHooks.configs.recommended.rules,
|
||||
"react-refresh/only-export-components": [
|
||||
"warn",
|
||||
{ allowConstantExport: true },
|
||||
],
|
||||
},
|
||||
},
|
||||
);
|
||||
@@ -0,0 +1,13 @@
|
||||
<!doctype html>
|
||||
<html lang="en">
|
||||
<head>
|
||||
<meta charset="UTF-8" />
|
||||
<link rel="icon" type="image/svg+xml" href="/vite.svg" />
|
||||
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
|
||||
<title>Vite + React + TS</title>
|
||||
</head>
|
||||
<body>
|
||||
<div id="root"></div>
|
||||
<script type="module" src="/src/main.tsx"></script>
|
||||
</body>
|
||||
</html>
|
||||
@@ -0,0 +1,29 @@
|
||||
{
|
||||
"name": "open-ai-realtime",
|
||||
"private": true,
|
||||
"version": "0.0.0",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"dev": "vite",
|
||||
"build": "tsc -b && vite build",
|
||||
"lint": "eslint .",
|
||||
"preview": "vite preview"
|
||||
},
|
||||
"dependencies": {
|
||||
"react": "^19.1.0",
|
||||
"react-dom": "^19.1.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@eslint/js": "^9.25.0",
|
||||
"@types/react": "^19.1.2",
|
||||
"@types/react-dom": "^19.1.2",
|
||||
"@vitejs/plugin-react": "^4.5.2",
|
||||
"eslint": "^9.25.0",
|
||||
"eslint-plugin-react-hooks": "^5.2.0",
|
||||
"eslint-plugin-react-refresh": "^0.4.19",
|
||||
"globals": "^16.0.0",
|
||||
"typescript": "~5.8.3",
|
||||
"typescript-eslint": "^8.30.1",
|
||||
"vite": "^6.3.5"
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1 @@
|
||||
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" class="iconify iconify--logos" width="31.88" height="32" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 257"><defs><linearGradient id="IconifyId1813088fe1fbc01fb466" x1="-.828%" x2="57.636%" y1="7.652%" y2="78.411%"><stop offset="0%" stop-color="#41D1FF"></stop><stop offset="100%" stop-color="#BD34FE"></stop></linearGradient><linearGradient id="IconifyId1813088fe1fbc01fb467" x1="43.376%" x2="50.316%" y1="2.242%" y2="89.03%"><stop offset="0%" stop-color="#FFEA83"></stop><stop offset="8.333%" stop-color="#FFDD35"></stop><stop offset="100%" stop-color="#FFA800"></stop></linearGradient></defs><path fill="url(#IconifyId1813088fe1fbc01fb466)" d="M255.153 37.938L134.897 252.976c-2.483 4.44-8.862 4.466-11.382.048L.875 37.958c-2.746-4.814 1.371-10.646 6.827-9.67l120.385 21.517a6.537 6.537 0 0 0 2.322-.004l117.867-21.483c5.438-.991 9.574 4.796 6.877 9.62Z"></path><path fill="url(#IconifyId1813088fe1fbc01fb467)" d="M185.432.063L96.44 17.501a3.268 3.268 0 0 0-2.634 3.014l-5.474 92.456a3.268 3.268 0 0 0 3.997 3.378l24.777-5.718c2.318-.535 4.413 1.507 3.936 3.838l-7.361 36.047c-.495 2.426 1.782 4.5 4.151 3.78l15.304-4.649c2.372-.72 4.652 1.36 4.15 3.788l-11.698 56.621c-.732 3.542 3.979 5.473 5.943 2.437l1.313-2.028l72.516-144.72c1.215-2.423-.88-5.186-3.54-4.672l-25.505 4.922c-2.396.462-4.435-1.77-3.759-4.114l16.646-57.705c.677-2.35-1.37-4.583-3.769-4.113Z"></path></svg>
|
||||
|
After Width: | Height: | Size: 1.5 KiB |
@@ -0,0 +1,183 @@
|
||||
import { openai } from "@llamaindex/openai";
|
||||
import { liveEvents, LiveLLMSession, ModalityType } from "llamaindex";
|
||||
import { useEffect, useRef, useState } from "react";
|
||||
|
||||
const MicIcon = ({ isConnected }: { isConnected: boolean }) => (
|
||||
<svg
|
||||
xmlns="http://www.w3.org/2000/svg"
|
||||
viewBox="0 0 24 24"
|
||||
fill="currentColor"
|
||||
strokeWidth="2"
|
||||
strokeLinecap="round"
|
||||
strokeLinejoin="round"
|
||||
>
|
||||
{isConnected ? (
|
||||
<>
|
||||
<path d="M12 1a3 3 0 0 0-3 3v8a3 3 0 0 0 6 0V4a3 3 0 0 0-3-3z" />
|
||||
<path d="M19 10v2a7 7 0 0 1-14 0v-2" />
|
||||
<line x1="12" y1="19" x2="12" y2="23" />
|
||||
<line x1="8" y1="23" x2="16" y2="23" />
|
||||
</>
|
||||
) : (
|
||||
<>
|
||||
<path d="M12 1a3 3 0 0 0-3 3v8a3 3 0 0 0 6 0V4a3 3 0 0 0-3-3z" />
|
||||
<path d="M19 10v2a7 7 0 0 1-14 0v-2" />
|
||||
</>
|
||||
)}
|
||||
</svg>
|
||||
);
|
||||
|
||||
const WaveAnimation = () => (
|
||||
<div className="wave-animation">
|
||||
{[...Array(3)].map((_, i) => (
|
||||
<div key={i} className="wave" style={{ animationDelay: `${i * 0.2}s` }} />
|
||||
))}
|
||||
</div>
|
||||
);
|
||||
|
||||
export const AudioChat = () => {
|
||||
const [isConnected, setIsConnected] = useState(false);
|
||||
const [messages, setMessages] = useState<
|
||||
Array<{ role: string; content: string }>
|
||||
>([]);
|
||||
const [status, setStatus] = useState<string>("");
|
||||
const audioRef = useRef<HTMLAudioElement>(null);
|
||||
const sessionRef = useRef<LiveLLMSession | null>(null);
|
||||
const [stream, setStream] = useState<MediaStream | null>(null);
|
||||
const messagesEndRef = useRef<HTMLDivElement>(null);
|
||||
|
||||
const scrollToBottom = () => {
|
||||
messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
scrollToBottom();
|
||||
}, [messages]);
|
||||
|
||||
useEffect(() => {
|
||||
return () => {
|
||||
if (stream) {
|
||||
stream.getTracks().forEach((track) => track.stop());
|
||||
}
|
||||
};
|
||||
}, [stream]);
|
||||
|
||||
const startChat = async () => {
|
||||
try {
|
||||
setStatus("Initializing microphone...");
|
||||
const userStream = await navigator.mediaDevices.getUserMedia({
|
||||
audio: true,
|
||||
});
|
||||
setStream(userStream);
|
||||
|
||||
setStatus("Connecting to AI...");
|
||||
const apiKey = prompt("Please enter your OpenAI API key:");
|
||||
if (!apiKey) {
|
||||
throw new Error("API key is required");
|
||||
}
|
||||
|
||||
// move this call to the server side for security reasons
|
||||
// Do not store the API key in the frontend!
|
||||
const serverllm = openai({
|
||||
apiKey: apiKey,
|
||||
model: "gpt-4o-realtime-preview-2025-06-03",
|
||||
});
|
||||
|
||||
const tempKey = await serverllm.live.getEphemeralKey();
|
||||
|
||||
const llm = openai({
|
||||
apiKey: tempKey,
|
||||
model: "gpt-4o-realtime-preview-2025-06-03",
|
||||
});
|
||||
const session = await llm.live.connect({
|
||||
systemInstruction: "You are a helpful assistant who speaks naturally.",
|
||||
responseModality: [ModalityType.TEXT, ModalityType.AUDIO],
|
||||
audioConfig: {
|
||||
stream: userStream,
|
||||
onTrack: (remoteStream) => {
|
||||
if (audioRef.current && remoteStream) {
|
||||
audioRef.current.srcObject = remoteStream;
|
||||
audioRef.current.play().catch(console.error);
|
||||
}
|
||||
},
|
||||
},
|
||||
});
|
||||
|
||||
sessionRef.current = session;
|
||||
setIsConnected(true);
|
||||
setStatus("Connected! Listening...");
|
||||
|
||||
for await (const event of session.streamEvents()) {
|
||||
if (liveEvents.open.include(event)) {
|
||||
setMessages((prev) => [
|
||||
...prev,
|
||||
{
|
||||
role: "user",
|
||||
content: "Hello, I'm ready to chat!",
|
||||
},
|
||||
]);
|
||||
session.sendMessage({
|
||||
content: "Hello, I'm ready to chat!",
|
||||
role: "user",
|
||||
});
|
||||
} else if (liveEvents.text.include(event)) {
|
||||
setMessages((prev) => [
|
||||
...prev,
|
||||
{
|
||||
role: "assistant",
|
||||
content: event.text,
|
||||
},
|
||||
]);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error starting chat:", error);
|
||||
setStatus("Error connecting. Please try again.");
|
||||
setIsConnected(false);
|
||||
}
|
||||
};
|
||||
|
||||
const stopChat = async () => {
|
||||
setStatus("Disconnecting...");
|
||||
if (sessionRef.current) {
|
||||
await sessionRef.current.disconnect();
|
||||
sessionRef.current = null;
|
||||
}
|
||||
if (stream) {
|
||||
stream.getTracks().forEach((track) => track.stop());
|
||||
setStream(null);
|
||||
}
|
||||
if (audioRef.current) {
|
||||
audioRef.current.srcObject = null;
|
||||
}
|
||||
setIsConnected(false);
|
||||
setStatus("");
|
||||
};
|
||||
|
||||
return (
|
||||
<div className="audio-chat-container">
|
||||
<h1>AI Voice Chat</h1>
|
||||
<div className="messages-container">
|
||||
{messages.map((msg, idx) => (
|
||||
<div key={idx} className={`message ${msg.role}`}>
|
||||
{msg.content}
|
||||
</div>
|
||||
))}
|
||||
<div ref={messagesEndRef} />
|
||||
</div>
|
||||
|
||||
<div className="controls">
|
||||
{status && <div className="status-indicator">{status}</div>}
|
||||
<button
|
||||
className={`mic-button ${isConnected ? "connected" : ""}`}
|
||||
onClick={isConnected ? stopChat : startChat}
|
||||
title={isConnected ? "Stop Chat" : "Start Chat"}
|
||||
>
|
||||
<MicIcon isConnected={isConnected} />
|
||||
{isConnected && <WaveAnimation />}
|
||||
</button>
|
||||
<audio ref={audioRef} style={{ display: "none" }} />
|
||||
</div>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
@@ -0,0 +1,322 @@
|
||||
:root {
|
||||
--primary-color: #646cff;
|
||||
--secondary-color: #535bf2;
|
||||
--background-dark: #1a1a1a;
|
||||
--chat-bg: #242424;
|
||||
--text-primary: #ffffff;
|
||||
--text-secondary: #888888;
|
||||
--success-color: #4caf50;
|
||||
--error-color: #f44336;
|
||||
--gradient-start: #4776e6;
|
||||
--gradient-end: #8e54e9;
|
||||
}
|
||||
|
||||
body {
|
||||
background-color: var(--background-dark);
|
||||
color: var(--text-primary);
|
||||
margin: 0;
|
||||
min-height: 100vh;
|
||||
font-family:
|
||||
-apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Oxygen, Ubuntu,
|
||||
Cantarell, "Open Sans", "Helvetica Neue", sans-serif;
|
||||
}
|
||||
|
||||
#root {
|
||||
max-width: 1280px;
|
||||
height: 100vh;
|
||||
margin: 0 auto;
|
||||
padding: 2rem;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
}
|
||||
|
||||
.logo {
|
||||
height: 6em;
|
||||
padding: 1.5em;
|
||||
will-change: filter;
|
||||
transition: filter 300ms;
|
||||
}
|
||||
.logo:hover {
|
||||
filter: drop-shadow(0 0 2em #646cffaa);
|
||||
}
|
||||
.logo.react:hover {
|
||||
filter: drop-shadow(0 0 2em #61dafbaa);
|
||||
}
|
||||
|
||||
@keyframes logo-spin {
|
||||
from {
|
||||
transform: rotate(0deg);
|
||||
}
|
||||
to {
|
||||
transform: rotate(360deg);
|
||||
}
|
||||
}
|
||||
|
||||
@media (prefers-reduced-motion: no-preference) {
|
||||
a:nth-of-type(2) .logo {
|
||||
animation: logo-spin infinite 20s linear;
|
||||
}
|
||||
}
|
||||
|
||||
.card {
|
||||
padding: 2em;
|
||||
}
|
||||
|
||||
.read-the-docs {
|
||||
color: #888;
|
||||
}
|
||||
|
||||
.audio-chat-container {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 2rem;
|
||||
width: 100%;
|
||||
max-width: 800px;
|
||||
height: 80vh;
|
||||
margin: 0 auto;
|
||||
padding: 2rem;
|
||||
background: var(--chat-bg);
|
||||
border-radius: 24px;
|
||||
box-shadow: 0 8px 32px rgba(0, 0, 0, 0.2);
|
||||
position: relative;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.audio-chat-container::before {
|
||||
content: "";
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
right: 0;
|
||||
height: 4px;
|
||||
background: linear-gradient(
|
||||
to right,
|
||||
var(--gradient-start),
|
||||
var(--gradient-end)
|
||||
);
|
||||
}
|
||||
|
||||
.audio-chat-container h1 {
|
||||
font-size: 2.5rem;
|
||||
margin: 0;
|
||||
background: linear-gradient(
|
||||
to right,
|
||||
var(--gradient-start),
|
||||
var(--gradient-end)
|
||||
);
|
||||
-webkit-background-clip: text;
|
||||
background-clip: text;
|
||||
color: transparent;
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
.messages-container {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 1rem;
|
||||
flex: 1;
|
||||
overflow-y: auto;
|
||||
padding: 1rem;
|
||||
border-radius: 16px;
|
||||
background: rgba(255, 255, 255, 0.05);
|
||||
backdrop-filter: blur(10px);
|
||||
margin: 1rem 0;
|
||||
}
|
||||
|
||||
.message {
|
||||
padding: 1rem 1.5rem;
|
||||
border-radius: 16px;
|
||||
max-width: 80%;
|
||||
text-align: left;
|
||||
animation: messageSlide 0.3s ease-out;
|
||||
box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
|
||||
}
|
||||
|
||||
@keyframes messageSlide {
|
||||
from {
|
||||
opacity: 0;
|
||||
transform: translateY(20px);
|
||||
}
|
||||
to {
|
||||
opacity: 1;
|
||||
transform: translateY(0);
|
||||
}
|
||||
}
|
||||
|
||||
.message.user {
|
||||
background: linear-gradient(
|
||||
135deg,
|
||||
var(--gradient-start),
|
||||
var(--gradient-end)
|
||||
);
|
||||
align-self: flex-end;
|
||||
margin-left: 20%;
|
||||
color: white;
|
||||
}
|
||||
|
||||
.message.assistant {
|
||||
background: rgba(255, 255, 255, 0.1);
|
||||
align-self: flex-start;
|
||||
margin-right: 20%;
|
||||
border: 1px solid rgba(255, 255, 255, 0.1);
|
||||
}
|
||||
|
||||
.controls {
|
||||
display: flex;
|
||||
justify-content: center;
|
||||
align-items: center;
|
||||
padding: 2rem;
|
||||
position: relative;
|
||||
}
|
||||
|
||||
.mic-button {
|
||||
width: 80px;
|
||||
height: 80px;
|
||||
border-radius: 50%;
|
||||
border: none;
|
||||
background: linear-gradient(
|
||||
135deg,
|
||||
var(--gradient-start),
|
||||
var(--gradient-end)
|
||||
);
|
||||
color: white;
|
||||
cursor: pointer;
|
||||
transition: all 0.3s cubic-bezier(0.4, 0, 0.2, 1);
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
box-shadow: 0 4px 15px rgba(0, 0, 0, 0.2);
|
||||
position: relative;
|
||||
overflow: hidden;
|
||||
}
|
||||
|
||||
.mic-button::before {
|
||||
content: "";
|
||||
position: absolute;
|
||||
top: 0;
|
||||
left: 0;
|
||||
right: 0;
|
||||
bottom: 0;
|
||||
background: linear-gradient(
|
||||
135deg,
|
||||
rgba(255, 255, 255, 0.1),
|
||||
rgba(255, 255, 255, 0)
|
||||
);
|
||||
border-radius: 50%;
|
||||
transition: transform 0.3s ease;
|
||||
}
|
||||
|
||||
.mic-button:hover {
|
||||
transform: scale(1.05);
|
||||
box-shadow: 0 8px 25px rgba(0, 0, 0, 0.3);
|
||||
}
|
||||
|
||||
.mic-button:hover::before {
|
||||
transform: translateY(-100%);
|
||||
}
|
||||
|
||||
.mic-button.connected {
|
||||
background: var(--error-color);
|
||||
animation: pulseError 2s infinite;
|
||||
}
|
||||
|
||||
.mic-button svg {
|
||||
width: 32px;
|
||||
height: 32px;
|
||||
filter: drop-shadow(0 2px 4px rgba(0, 0, 0, 0.2));
|
||||
transition: transform 0.3s ease;
|
||||
}
|
||||
|
||||
.mic-button:hover svg {
|
||||
transform: scale(1.1);
|
||||
}
|
||||
|
||||
@keyframes pulseError {
|
||||
0% {
|
||||
box-shadow: 0 0 0 0 rgba(244, 67, 54, 0.4);
|
||||
}
|
||||
70% {
|
||||
box-shadow: 0 0 0 20px rgba(244, 67, 54, 0);
|
||||
}
|
||||
100% {
|
||||
box-shadow: 0 0 0 0 rgba(244, 67, 54, 0);
|
||||
}
|
||||
}
|
||||
|
||||
/* Status indicator */
|
||||
.status-indicator {
|
||||
position: absolute;
|
||||
top: -30px;
|
||||
left: 50%;
|
||||
transform: translateX(-50%);
|
||||
font-size: 0.9rem;
|
||||
color: var(--text-secondary);
|
||||
opacity: 0;
|
||||
transition: opacity 0.3s ease;
|
||||
}
|
||||
|
||||
.controls:hover .status-indicator {
|
||||
opacity: 1;
|
||||
}
|
||||
|
||||
/* Scrollbar styling */
|
||||
.messages-container::-webkit-scrollbar {
|
||||
width: 8px;
|
||||
}
|
||||
|
||||
.messages-container::-webkit-scrollbar-track {
|
||||
background: rgba(255, 255, 255, 0.05);
|
||||
border-radius: 4px;
|
||||
}
|
||||
|
||||
.messages-container::-webkit-scrollbar-thumb {
|
||||
background: linear-gradient(var(--gradient-start), var(--gradient-end));
|
||||
border-radius: 4px;
|
||||
}
|
||||
|
||||
.messages-container::-webkit-scrollbar-thumb:hover {
|
||||
background: linear-gradient(var(--gradient-end), var(--gradient-start));
|
||||
}
|
||||
|
||||
/* Wave Animation */
|
||||
.wave-animation {
|
||||
position: absolute;
|
||||
bottom: -15px;
|
||||
left: 50%;
|
||||
transform: translateX(-50%);
|
||||
display: flex;
|
||||
gap: 4px;
|
||||
}
|
||||
|
||||
.wave {
|
||||
width: 4px;
|
||||
height: 15px;
|
||||
background: currentColor;
|
||||
border-radius: 2px;
|
||||
animation: wave 0.5s ease-in-out infinite;
|
||||
}
|
||||
|
||||
@keyframes wave {
|
||||
0%,
|
||||
100% {
|
||||
transform: scaleY(0.5);
|
||||
}
|
||||
50% {
|
||||
transform: scaleY(1.5);
|
||||
}
|
||||
}
|
||||
|
||||
/* Loading state */
|
||||
.mic-button.loading {
|
||||
animation: rotate 1s linear infinite;
|
||||
}
|
||||
|
||||
@keyframes rotate {
|
||||
from {
|
||||
transform: rotate(0deg);
|
||||
}
|
||||
to {
|
||||
transform: rotate(360deg);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,10 @@
|
||||
import { StrictMode } from "react";
|
||||
import { createRoot } from "react-dom/client";
|
||||
import { AudioChat } from "./audio-chat.tsx";
|
||||
import "./index.css";
|
||||
|
||||
createRoot(document.getElementById("root")!).render(
|
||||
<StrictMode>
|
||||
<AudioChat />
|
||||
</StrictMode>,
|
||||
);
|
||||
@@ -0,0 +1 @@
|
||||
/// <reference types="vite/client" />
|
||||
@@ -0,0 +1,26 @@
|
||||
{
|
||||
"compilerOptions": {
|
||||
"tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
|
||||
"target": "ES2020",
|
||||
"useDefineForClassFields": true,
|
||||
"lib": ["ES2020", "DOM", "DOM.Iterable"],
|
||||
"module": "ESNext",
|
||||
"skipLibCheck": true,
|
||||
|
||||
/* Bundler mode */
|
||||
"moduleResolution": "bundler",
|
||||
"allowImportingTsExtensions": true,
|
||||
"verbatimModuleSyntax": true,
|
||||
"moduleDetection": "force",
|
||||
"noEmit": true,
|
||||
"jsx": "react-jsx",
|
||||
|
||||
/* Linting */
|
||||
"strict": true,
|
||||
"noUnusedLocals": true,
|
||||
"noUnusedParameters": true,
|
||||
"noFallthroughCasesInSwitch": true,
|
||||
"noUncheckedSideEffectImports": true
|
||||
},
|
||||
"include": ["src"]
|
||||
}
|
||||
@@ -0,0 +1,4 @@
|
||||
{
|
||||
"files": [],
|
||||
"references": [{ "path": "./tsconfig.app.json" }]
|
||||
}
|
||||
@@ -0,0 +1,7 @@
|
||||
import react from "@vitejs/plugin-react";
|
||||
import { defineConfig } from "vite";
|
||||
|
||||
// https://vite.dev/config/
|
||||
export default defineConfig({
|
||||
plugins: [react()],
|
||||
});
|
||||
+47
-47
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/examples",
|
||||
"version": "0.3.19",
|
||||
"version": "0.3.25",
|
||||
"private": true,
|
||||
"scripts": {
|
||||
"lint": "eslint .",
|
||||
@@ -11,51 +11,51 @@
|
||||
"@azure/cosmos": "^4.1.1",
|
||||
"@azure/identity": "^4.4.1",
|
||||
"@azure/search-documents": "^12.1.0",
|
||||
"@llamaindex/anthropic": "^0.3.11",
|
||||
"@llamaindex/assemblyai": "^0.1.8",
|
||||
"@llamaindex/astra": "^0.0.23",
|
||||
"@llamaindex/azure": "^0.1.20",
|
||||
"@llamaindex/chroma": "^0.0.23",
|
||||
"@llamaindex/clip": "^0.0.59",
|
||||
"@llamaindex/cloud": "^4.0.13",
|
||||
"@llamaindex/cohere": "^0.0.23",
|
||||
"@llamaindex/core": "^0.6.9",
|
||||
"@llamaindex/deepinfra": "^0.0.59",
|
||||
"@llamaindex/deepseek": "^0.0.19",
|
||||
"@llamaindex/discord": "^0.1.8",
|
||||
"@llamaindex/elastic-search": "^0.1.9",
|
||||
"@llamaindex/anthropic": "^0.3.14",
|
||||
"@llamaindex/assemblyai": "^0.1.11",
|
||||
"@llamaindex/astra": "^0.0.26",
|
||||
"@llamaindex/azure": "^0.1.23",
|
||||
"@llamaindex/chroma": "^0.0.26",
|
||||
"@llamaindex/clip": "^0.0.62",
|
||||
"@llamaindex/cloud": "^4.0.16",
|
||||
"@llamaindex/cohere": "^0.0.26",
|
||||
"@llamaindex/core": "^0.6.12",
|
||||
"@llamaindex/deepinfra": "^0.0.62",
|
||||
"@llamaindex/deepseek": "^0.0.22",
|
||||
"@llamaindex/discord": "^0.1.11",
|
||||
"@llamaindex/elastic-search": "^0.1.12",
|
||||
"@llamaindex/env": "^0.1.30",
|
||||
"@llamaindex/firestore": "^1.0.16",
|
||||
"@llamaindex/fireworks": "^0.0.19",
|
||||
"@llamaindex/google": "^0.3.6",
|
||||
"@llamaindex/groq": "^0.0.74",
|
||||
"@llamaindex/huggingface": "^0.1.13",
|
||||
"@llamaindex/jinaai": "^0.0.19",
|
||||
"@llamaindex/milvus": "^0.1.18",
|
||||
"@llamaindex/mistral": "^0.1.9",
|
||||
"@llamaindex/mixedbread": "^0.0.23",
|
||||
"@llamaindex/mongodb": "^0.0.24",
|
||||
"@llamaindex/node-parser": "^2.0.9",
|
||||
"@llamaindex/notion": "^0.1.8",
|
||||
"@llamaindex/ollama": "^0.1.9",
|
||||
"@llamaindex/openai": "^0.4.3",
|
||||
"@llamaindex/perplexity": "^0.0.16",
|
||||
"@llamaindex/pinecone": "^0.1.9",
|
||||
"@llamaindex/portkey-ai": "^0.0.51",
|
||||
"@llamaindex/postgres": "^0.0.52",
|
||||
"@llamaindex/qdrant": "^0.1.19",
|
||||
"@llamaindex/readers": "^3.1.7",
|
||||
"@llamaindex/replicate": "^0.0.51",
|
||||
"@llamaindex/supabase": "^0.1.8",
|
||||
"@llamaindex/together": "^0.0.19",
|
||||
"@llamaindex/tools": "^0.0.14",
|
||||
"@llamaindex/upstash": "^0.0.23",
|
||||
"@llamaindex/vercel": "^0.1.9",
|
||||
"@llamaindex/vllm": "^0.0.45",
|
||||
"@llamaindex/voyage-ai": "^1.0.15",
|
||||
"@llamaindex/weaviate": "^0.0.23",
|
||||
"@llamaindex/workflow": "^1.1.6",
|
||||
"@llamaindex/xai": "workspace:^0.0.6",
|
||||
"@llamaindex/firestore": "^1.0.19",
|
||||
"@llamaindex/fireworks": "^0.0.22",
|
||||
"@llamaindex/google": "^0.3.11",
|
||||
"@llamaindex/groq": "^0.0.77",
|
||||
"@llamaindex/huggingface": "^0.1.16",
|
||||
"@llamaindex/jinaai": "^0.0.22",
|
||||
"@llamaindex/milvus": "^0.1.21",
|
||||
"@llamaindex/mistral": "^0.1.12",
|
||||
"@llamaindex/mixedbread": "^0.0.26",
|
||||
"@llamaindex/mongodb": "^0.0.27",
|
||||
"@llamaindex/node-parser": "^2.0.12",
|
||||
"@llamaindex/notion": "^0.1.11",
|
||||
"@llamaindex/ollama": "^0.1.12",
|
||||
"@llamaindex/openai": "^0.4.6",
|
||||
"@llamaindex/perplexity": "^0.0.19",
|
||||
"@llamaindex/pinecone": "^0.1.12",
|
||||
"@llamaindex/portkey-ai": "^0.0.54",
|
||||
"@llamaindex/postgres": "^0.0.55",
|
||||
"@llamaindex/qdrant": "^0.1.22",
|
||||
"@llamaindex/readers": "^3.1.11",
|
||||
"@llamaindex/replicate": "^0.0.54",
|
||||
"@llamaindex/supabase": "^0.1.12",
|
||||
"@llamaindex/together": "^0.0.22",
|
||||
"@llamaindex/tools": "^0.1.1",
|
||||
"@llamaindex/upstash": "^0.0.26",
|
||||
"@llamaindex/vercel": "^0.1.12",
|
||||
"@llamaindex/vllm": "^0.0.48",
|
||||
"@llamaindex/voyage-ai": "^1.0.18",
|
||||
"@llamaindex/weaviate": "^0.0.27",
|
||||
"@llamaindex/workflow": "^1.1.12",
|
||||
"@llamaindex/xai": "workspace:^0.0.9",
|
||||
"@notionhq/client": "^2.2.15",
|
||||
"@pinecone-database/pinecone": "^4.0.0",
|
||||
"@vercel/postgres": "^0.10.0",
|
||||
@@ -64,11 +64,11 @@
|
||||
"commander": "^12.1.0",
|
||||
"dotenv": "^16.4.5",
|
||||
"js-tiktoken": "^1.0.14",
|
||||
"llamaindex": "^0.11.5",
|
||||
"llamaindex": "^0.11.11",
|
||||
"mongodb": "6.7.0",
|
||||
"postgres": "^3.4.4",
|
||||
"wikipedia": "^2.1.2",
|
||||
"zod": "^3.23.8"
|
||||
"zod": "^3.25.67"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@types/node": "^22.9.0",
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import { OpenAIEmbedding } from "@llamaindex/openai";
|
||||
import {
|
||||
Document,
|
||||
SentenceSplitter,
|
||||
@@ -7,6 +8,10 @@ import {
|
||||
import { OldSentenceSplitter } from "./old-sentence-splitter";
|
||||
export const STORAGE_DIR = "./data";
|
||||
|
||||
Settings.embedModel = new OpenAIEmbedding({
|
||||
model: "text-embedding-3-small",
|
||||
});
|
||||
|
||||
// Update node parser
|
||||
(async () => {
|
||||
// generate a document with a very long sentence (9000 words long)
|
||||
|
||||
@@ -15,11 +15,14 @@
|
||||
"start:llamaparse-json": "node --import tsx ./src/llamaparse-json.ts",
|
||||
"start:discord": "node --import tsx ./src/discord.ts",
|
||||
"start:json": "node --import tsx ./src/json.ts",
|
||||
"start:obsidian": "node --import tsx ./src/obsidian.ts"
|
||||
"start:obsidian": "node --import tsx ./src/obsidian.ts",
|
||||
"start:xml": "node --import tsx ./src/xml.ts",
|
||||
"start:excel": "node --import tsx ./src/excel.ts"
|
||||
},
|
||||
"dependencies": {
|
||||
"@llamaindex/cloud": "workspace:* || ^2.0.24",
|
||||
"@llamaindex/readers": "workspace:* || ^1.0.25",
|
||||
"@llamaindex/excel": "workspace:*",
|
||||
"llamaindex": "workspace:* || ^0.8.37"
|
||||
},
|
||||
"devDependencies": {
|
||||
|
||||
@@ -0,0 +1,20 @@
|
||||
import { ExcelReader } from "@llamaindex/excel";
|
||||
|
||||
async function main() {
|
||||
// Load PDF
|
||||
const reader = new ExcelReader({
|
||||
sheetSpecifier: 0,
|
||||
concatRows: true,
|
||||
fieldSeparator: ",",
|
||||
keyValueSeparator: ":",
|
||||
});
|
||||
|
||||
const documents = await reader.loadData("../data/sample_excel_sheet.xls");
|
||||
|
||||
for (const doc of documents) {
|
||||
console.log(doc.text);
|
||||
console.log("----");
|
||||
}
|
||||
}
|
||||
|
||||
main().catch(console.error);
|
||||
@@ -0,0 +1,16 @@
|
||||
import { XMLReader } from "@llamaindex/readers/xml";
|
||||
|
||||
async function main() {
|
||||
// Load PDF
|
||||
const reader = new XMLReader({
|
||||
splitLevel: 2,
|
||||
});
|
||||
const documents = await reader.loadData("../data/company.xml");
|
||||
|
||||
for (const doc of documents) {
|
||||
console.log(doc.text);
|
||||
console.log("----");
|
||||
}
|
||||
}
|
||||
|
||||
main().catch(console.error);
|
||||
@@ -1,8 +1,4 @@
|
||||
import {
|
||||
GEMINI_EMBEDDING_MODEL,
|
||||
GeminiEmbedding,
|
||||
GeminiSession,
|
||||
} from "@llamaindex/google";
|
||||
import { GEMINI_EMBEDDING_MODEL, GeminiEmbedding } from "@llamaindex/google";
|
||||
import { QdrantVectorStore } from "@llamaindex/qdrant";
|
||||
import {
|
||||
Document,
|
||||
@@ -12,9 +8,6 @@ import {
|
||||
|
||||
const embedding = new GeminiEmbedding({
|
||||
model: GEMINI_EMBEDDING_MODEL.EMBEDDING_001,
|
||||
session: new GeminiSession({
|
||||
apiKey: process.env.GEMINI_API_KEY,
|
||||
}),
|
||||
});
|
||||
|
||||
async function main() {
|
||||
|
||||
@@ -18,5 +18,11 @@
|
||||
"module": "commonjs"
|
||||
}
|
||||
},
|
||||
"include": ["./**/*.ts"]
|
||||
"include": ["./**/*.ts"],
|
||||
"exclude": [
|
||||
"node_modules",
|
||||
"dist",
|
||||
"models/openai/live/browser/open-ai-realtime",
|
||||
"**/browser/**"
|
||||
]
|
||||
}
|
||||
|
||||
@@ -1,5 +1,43 @@
|
||||
# @llamaindex/autotool
|
||||
|
||||
## 8.0.11
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
|
||||
## 8.0.10
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 8.0.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
|
||||
## 8.0.8
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
|
||||
## 8.0.7
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 8.0.6
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 8.0.5
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,5 +1,49 @@
|
||||
# @llamaindex/autotool-01-node-example
|
||||
|
||||
## 0.0.119
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
- @llamaindex/autotool@8.0.11
|
||||
|
||||
## 0.0.118
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
- @llamaindex/autotool@8.0.10
|
||||
|
||||
## 0.0.117
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
- @llamaindex/autotool@8.0.9
|
||||
|
||||
## 0.0.116
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
- @llamaindex/autotool@8.0.8
|
||||
|
||||
## 0.0.115
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
- @llamaindex/autotool@8.0.7
|
||||
|
||||
## 0.0.114
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
- @llamaindex/autotool@8.0.6
|
||||
|
||||
## 0.0.113
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -13,5 +13,5 @@
|
||||
"scripts": {
|
||||
"start": "node --import tsx --import @llamaindex/autotool/node ./src/index.ts"
|
||||
},
|
||||
"version": "0.0.113"
|
||||
"version": "0.0.119"
|
||||
}
|
||||
|
||||
@@ -6,7 +6,7 @@
|
||||
"url": "git+https://github.com/run-llama/LlamaIndexTS.git",
|
||||
"directory": "packages/autotool"
|
||||
},
|
||||
"version": "8.0.5",
|
||||
"version": "8.0.11",
|
||||
"description": "auto transpile your JS function to LLM Agent compatible",
|
||||
"files": [
|
||||
"dist",
|
||||
|
||||
@@ -1,5 +1,30 @@
|
||||
# @llamaindex/cloud
|
||||
|
||||
## 4.0.16
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- Updated dependencies [7039e1a]
|
||||
- @llamaindex/core@0.6.12
|
||||
|
||||
## 4.0.15
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [a89e187]
|
||||
- Updated dependencies [62699b7]
|
||||
- Updated dependencies [c5b2691]
|
||||
- Updated dependencies [d8ac8d3]
|
||||
- @llamaindex/core@0.6.11
|
||||
|
||||
## 4.0.14
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [1b5af14]
|
||||
- @llamaindex/core@0.6.10
|
||||
|
||||
## 4.0.13
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@llamaindex/cloud",
|
||||
"version": "4.0.13",
|
||||
"version": "4.0.16",
|
||||
"type": "module",
|
||||
"license": "MIT",
|
||||
"scripts": {
|
||||
@@ -79,6 +79,6 @@
|
||||
},
|
||||
"dependencies": {
|
||||
"p-retry": "^6.2.1",
|
||||
"zod": "^3.25.7"
|
||||
"zod": "^3.25.67"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,5 +1,27 @@
|
||||
# @llamaindex/core
|
||||
|
||||
## 0.6.12
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 7039e1a: Internal cleanup of base64 encoding
|
||||
- 7039e1a: chore: migrate to @google/genai SDK
|
||||
|
||||
## 0.6.11
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- a89e187: Feat: added custom abbreviations to sentence splitter
|
||||
- 62699b7: Improve performance of sentence splitter
|
||||
- c5b2691: Add more Acronyms on SentenceSplitter
|
||||
- d8ac8d3: Feat: add support for openai realtime API
|
||||
|
||||
## 0.6.10
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 1b5af14: fix: jsonToNode for image nodes
|
||||
|
||||
## 0.6.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "@llamaindex/core",
|
||||
"type": "module",
|
||||
"version": "0.6.9",
|
||||
"version": "0.6.12",
|
||||
"description": "LlamaIndex Core Module",
|
||||
"exports": {
|
||||
"./agent": {
|
||||
@@ -312,7 +312,7 @@
|
||||
"@llamaindex/env": "workspace:*",
|
||||
"@types/node": "^22.9.0",
|
||||
"magic-bytes.js": "^1.10.0",
|
||||
"zod": "^3.23.8",
|
||||
"zod-to-json-schema": "^3.23.3"
|
||||
"zod": "^3.25.67",
|
||||
"zod-to-json-schema": "^3.24.6"
|
||||
}
|
||||
}
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
import { extractText, streamConverter } from "../utils";
|
||||
import { extractText } from "../utils/llms";
|
||||
import { streamConverter } from "../utils/stream";
|
||||
import type {
|
||||
ChatResponse,
|
||||
ChatResponseChunk,
|
||||
|
||||
@@ -1,6 +1,9 @@
|
||||
export { BaseLLM, ToolCallLLM } from "./base";
|
||||
export { LiveLLM, LiveLLMSession, liveEvents, type LiveEvent } from "./live";
|
||||
export { LiveLLM, LiveLLMCapability, LiveLLMSession } from "./live/live";
|
||||
export { liveEvents, type LiveEvent } from "./live/live-types";
|
||||
export type { MessageSender } from "./live/sender";
|
||||
export type {
|
||||
AudioConfig,
|
||||
BaseTool,
|
||||
BaseToolWithCall,
|
||||
ChatMessage,
|
||||
|
||||
@@ -1,9 +1,7 @@
|
||||
import type {
|
||||
ChatMessage,
|
||||
LiveConnectConfig,
|
||||
MessageContentAudioDetail,
|
||||
MessageContentTextDetail,
|
||||
} from "./type";
|
||||
} from "../type";
|
||||
|
||||
export type OpenEvent = { type: "open" };
|
||||
|
||||
@@ -63,45 +61,3 @@ export const liveEvents = {
|
||||
e.type === "turnComplete",
|
||||
},
|
||||
};
|
||||
export abstract class LiveLLMSession {
|
||||
protected eventQueue: LiveEvent[] = [];
|
||||
protected eventResolvers: ((value: LiveEvent) => void)[] = [];
|
||||
protected closed = false;
|
||||
abstract sendMessage(message: ChatMessage): void;
|
||||
async *streamEvents(): AsyncIterable<LiveEvent> {
|
||||
while (true) {
|
||||
const event = await this.nextEvent();
|
||||
if (event === undefined) {
|
||||
break;
|
||||
}
|
||||
yield event;
|
||||
}
|
||||
}
|
||||
abstract disconnect(): Promise<void>;
|
||||
|
||||
protected async nextEvent(): Promise<LiveEvent | undefined> {
|
||||
if (this.eventQueue.length) {
|
||||
return Promise.resolve(this.eventQueue.shift());
|
||||
}
|
||||
|
||||
return new Promise((resolve) => {
|
||||
this.eventResolvers.push(resolve);
|
||||
});
|
||||
}
|
||||
|
||||
//Uses an async queue to send events to the client
|
||||
// if the consumer is waiting for an event, it will be resolved immediately
|
||||
// otherwise, the event will be queued up and sent when the consumer is ready
|
||||
pushEventToQueue(event: LiveEvent) {
|
||||
if (this.eventResolvers.length) {
|
||||
//resolving the promise with the event
|
||||
this.eventResolvers.shift()!(event);
|
||||
} else {
|
||||
this.eventQueue.push(event);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export abstract class LiveLLM {
|
||||
abstract connect(config?: LiveConnectConfig): Promise<LiveLLMSession>;
|
||||
}
|
||||
@@ -0,0 +1,124 @@
|
||||
import type {
|
||||
ChatMessage,
|
||||
LiveConnectConfig,
|
||||
MessageContentAudioDetail,
|
||||
MessageContentDetail,
|
||||
MessageContentImageDataDetail,
|
||||
MessageContentVideoDetail,
|
||||
} from "../type";
|
||||
import type { LiveEvent } from "./live-types";
|
||||
import type { MessageSender } from "./sender";
|
||||
|
||||
export enum LiveLLMCapability {
|
||||
EPHEMERAL_KEY = "ephemeral_key",
|
||||
AUDIO_CONFIG = "audio_config",
|
||||
}
|
||||
|
||||
export abstract class LiveLLMSession {
|
||||
protected eventQueue: LiveEvent[] = [];
|
||||
protected eventResolvers: ((value: LiveEvent) => void)[] = [];
|
||||
closed = false;
|
||||
abstract get messageSender(): MessageSender;
|
||||
|
||||
private isTextMessage(content: MessageContentDetail) {
|
||||
return content.type === "text";
|
||||
}
|
||||
|
||||
private isAudioMessage(
|
||||
content: MessageContentDetail,
|
||||
): content is MessageContentAudioDetail {
|
||||
return content.type === "audio";
|
||||
}
|
||||
|
||||
private isImageMessage(
|
||||
content: MessageContentDetail,
|
||||
): content is MessageContentImageDataDetail {
|
||||
return content.type === "image";
|
||||
}
|
||||
|
||||
private isVideoMessage(
|
||||
content: MessageContentDetail,
|
||||
): content is MessageContentVideoDetail {
|
||||
return content.type === "video";
|
||||
}
|
||||
|
||||
sendMessage(message: ChatMessage) {
|
||||
const { content, role } = message;
|
||||
if (!Array.isArray(content)) {
|
||||
this.messageSender.sendTextMessage(content, role);
|
||||
} else {
|
||||
for (const item of content) {
|
||||
this.processMessage(item, role);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private processMessage(message: MessageContentDetail, role?: string) {
|
||||
if (this.isTextMessage(message)) {
|
||||
this.messageSender.sendTextMessage(message.text, role);
|
||||
} else if (
|
||||
this.isAudioMessage(message) &&
|
||||
this.messageSender.sendAudioMessage
|
||||
) {
|
||||
this.messageSender.sendAudioMessage(message, role);
|
||||
} else if (
|
||||
this.isImageMessage(message) &&
|
||||
this.messageSender.sendImageMessage
|
||||
) {
|
||||
this.messageSender.sendImageMessage(message, role);
|
||||
} else if (
|
||||
this.isVideoMessage(message) &&
|
||||
this.messageSender.sendVideoMessage
|
||||
) {
|
||||
this.messageSender.sendVideoMessage(message, role);
|
||||
}
|
||||
}
|
||||
|
||||
async *streamEvents(): AsyncIterable<LiveEvent> {
|
||||
while (true) {
|
||||
const event = await this.nextEvent();
|
||||
if (event === undefined) {
|
||||
break;
|
||||
}
|
||||
yield event;
|
||||
}
|
||||
}
|
||||
abstract disconnect(): Promise<void>;
|
||||
|
||||
protected async nextEvent(): Promise<LiveEvent | undefined> {
|
||||
if (this.eventQueue.length) {
|
||||
return Promise.resolve(this.eventQueue.shift());
|
||||
}
|
||||
|
||||
return new Promise((resolve) => {
|
||||
this.eventResolvers.push(resolve);
|
||||
});
|
||||
}
|
||||
|
||||
//Uses an async queue to send events to the client
|
||||
// if the consumer is waiting for an event, it will be resolved immediately
|
||||
// otherwise, the event will be queued up and sent when the consumer is ready
|
||||
pushEventToQueue(event: LiveEvent) {
|
||||
if (this.eventResolvers.length) {
|
||||
//resolving the promise with the event
|
||||
this.eventResolvers.shift()!(event);
|
||||
} else {
|
||||
this.eventQueue.push(event);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
export abstract class LiveLLM {
|
||||
/**
|
||||
* Set of capabilities supported by this implementation.
|
||||
* Override in subclasses as needed.
|
||||
*/
|
||||
capabilities: Set<LiveLLMCapability> = new Set();
|
||||
|
||||
abstract connect(config?: LiveConnectConfig): Promise<LiveLLMSession>;
|
||||
abstract getEphemeralKey(): Promise<string | undefined>;
|
||||
|
||||
hasCapability(capability: LiveLLMCapability): boolean {
|
||||
return this.capabilities.has(capability);
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,15 @@
|
||||
import type {
|
||||
MessageContentAudioDetail,
|
||||
MessageContentImageDataDetail,
|
||||
MessageContentVideoDetail,
|
||||
} from "../type";
|
||||
|
||||
export interface MessageSender {
|
||||
sendTextMessage(message: string, role?: string): void;
|
||||
sendAudioMessage?(content: MessageContentAudioDetail, role?: string): void;
|
||||
sendImageMessage?(
|
||||
content: MessageContentImageDataDetail,
|
||||
role?: string,
|
||||
): void;
|
||||
sendVideoMessage?(content: MessageContentVideoDetail, role?: string): void;
|
||||
}
|
||||
@@ -290,8 +290,14 @@ export type ToolOutput = {
|
||||
isError: boolean;
|
||||
};
|
||||
|
||||
export interface AudioConfig {
|
||||
stream?: MediaStream;
|
||||
onTrack?: (track: MediaStream | null) => void;
|
||||
}
|
||||
|
||||
export interface LiveConnectConfig {
|
||||
tools?: BaseTool[];
|
||||
responseModality?: ModalityType[];
|
||||
systemInstruction?: string;
|
||||
audioConfig?: AudioConfig;
|
||||
}
|
||||
|
||||
@@ -0,0 +1,42 @@
|
||||
export const abbreviations = {
|
||||
english: [
|
||||
"i.e.",
|
||||
"etc.",
|
||||
"vs.",
|
||||
"Inc.",
|
||||
"A.S.A.P.",
|
||||
"Mr.",
|
||||
"Mrs.",
|
||||
"Ms.",
|
||||
"Dr.",
|
||||
"Prof.",
|
||||
"Sr.",
|
||||
"Jr.",
|
||||
"Tel.",
|
||||
"a.m.",
|
||||
"p.m.",
|
||||
"Art.",
|
||||
],
|
||||
spanish: [
|
||||
"Sr.",
|
||||
"Sres.",
|
||||
"Srs.",
|
||||
"Sra.",
|
||||
"Sras.",
|
||||
"Srta.",
|
||||
"Srtas.",
|
||||
"Dr.",
|
||||
"Drs.",
|
||||
"Dra.",
|
||||
"Dras.",
|
||||
"Prof.",
|
||||
"Profs.",
|
||||
"Profa.",
|
||||
"Profas.",
|
||||
"Ing.",
|
||||
"Lic.",
|
||||
"Arq.",
|
||||
"Ab.",
|
||||
"Abs.",
|
||||
],
|
||||
};
|
||||
@@ -12,11 +12,7 @@ import {
|
||||
type TextSplitterFn,
|
||||
} from "./utils";
|
||||
|
||||
type _Split = {
|
||||
text: string;
|
||||
isSentence: boolean;
|
||||
tokenSize: number;
|
||||
};
|
||||
type _Split = [string, boolean, number]; // [text, isSentence, tokenSize]
|
||||
|
||||
/**
|
||||
* Parse text with a preference for complete sentences.
|
||||
@@ -42,6 +38,11 @@ export class SentenceSplitter extends MetadataAwareTextSplitter {
|
||||
* Backup regex for splitting into sentences.
|
||||
*/
|
||||
secondaryChunkingRegex: string = "[^,.;。?!]+[,.;。?!]?";
|
||||
/**
|
||||
* Extra abbreviations to consider while splitting into sentences.
|
||||
* For example, for contracts, you may want to consider "LLC." as an important abbreviation
|
||||
*/
|
||||
extraAbbreviations: string[] | undefined = [];
|
||||
|
||||
#chunkingTokenizerFn = splitBySentenceTokenizer();
|
||||
#splitFns: Set<TextSplitterFn> = new Set();
|
||||
@@ -59,7 +60,11 @@ export class SentenceSplitter extends MetadataAwareTextSplitter {
|
||||
this.separator = parsedParams.separator;
|
||||
this.paragraphSeparator = parsedParams.paragraphSeparator;
|
||||
this.secondaryChunkingRegex = parsedParams.secondaryChunkingRegex;
|
||||
this.extraAbbreviations = parsedParams.extraAbbreviations;
|
||||
}
|
||||
this.#chunkingTokenizerFn = splitBySentenceTokenizer(
|
||||
this.extraAbbreviations,
|
||||
);
|
||||
this.#tokenizer = params?.tokenizer ?? Settings.tokenizer;
|
||||
this.#splitFns.add(splitBySep(this.paragraphSeparator));
|
||||
this.#splitFns.add(this.#chunkingTokenizerFn);
|
||||
@@ -105,34 +110,26 @@ export class SentenceSplitter extends MetadataAwareTextSplitter {
|
||||
return chunks;
|
||||
}
|
||||
|
||||
#split(text: string, chunkSize: number): _Split[] {
|
||||
const tokenSize = this.tokenSize(text);
|
||||
if (tokenSize <= chunkSize) {
|
||||
return [
|
||||
{
|
||||
text,
|
||||
isSentence: true,
|
||||
tokenSize,
|
||||
},
|
||||
];
|
||||
*#split(
|
||||
text: string,
|
||||
chunkSize: number,
|
||||
tokenSize?: number,
|
||||
): Generator<_Split> {
|
||||
const _tokenSize = tokenSize ?? this.tokenSize(text);
|
||||
if (_tokenSize <= chunkSize) {
|
||||
yield [text, true, _tokenSize];
|
||||
return;
|
||||
}
|
||||
const [textSplitsByFns, isSentence] = this.#getSplitsByFns(text);
|
||||
const textSplits: _Split[] = [];
|
||||
|
||||
for (const textSplit of textSplitsByFns) {
|
||||
const tokenSize = this.tokenSize(textSplit);
|
||||
if (tokenSize <= chunkSize) {
|
||||
textSplits.push({
|
||||
text: textSplit,
|
||||
isSentence,
|
||||
tokenSize,
|
||||
});
|
||||
const textSplitTokenSize = this.tokenSize(textSplit);
|
||||
if (textSplitTokenSize <= chunkSize) {
|
||||
yield [textSplit, isSentence, textSplitTokenSize];
|
||||
} else {
|
||||
const recursiveTextSplits = this.#split(textSplit, chunkSize);
|
||||
textSplits.push(...recursiveTextSplits);
|
||||
yield* this.#split(textSplit, chunkSize, textSplitTokenSize);
|
||||
}
|
||||
}
|
||||
return textSplits;
|
||||
}
|
||||
|
||||
#getSplitsByFns(text: string): [splits: string[], isSentence: boolean] {
|
||||
@@ -151,7 +148,7 @@ export class SentenceSplitter extends MetadataAwareTextSplitter {
|
||||
return [[text], true];
|
||||
}
|
||||
|
||||
#merge(splits: _Split[], chunkSize: number): string[] {
|
||||
#merge(splits: Iterable<_Split>, chunkSize: number): string[] {
|
||||
const chunks: string[] = [];
|
||||
let currentChunk: [string, number][] = [];
|
||||
let lastChunk: [string, number][] = [];
|
||||
@@ -177,23 +174,26 @@ export class SentenceSplitter extends MetadataAwareTextSplitter {
|
||||
}
|
||||
};
|
||||
|
||||
while (splits.length > 0) {
|
||||
const curSplit = splits[0]!;
|
||||
if (curSplit.tokenSize > chunkSize) {
|
||||
const splitsIterator = splits[Symbol.iterator]();
|
||||
let currentSplitResult = splitsIterator.next();
|
||||
|
||||
while (!currentSplitResult.done) {
|
||||
const [text, isSentence, tokenSize] = currentSplitResult.value;
|
||||
if (tokenSize > chunkSize) {
|
||||
throw new Error("Single token exceeded chunk size");
|
||||
}
|
||||
if (currentChunkLength + curSplit.tokenSize > chunkSize && !newChunk) {
|
||||
if (currentChunkLength + tokenSize > chunkSize && !newChunk) {
|
||||
closeChunk();
|
||||
} else {
|
||||
if (
|
||||
curSplit.isSentence ||
|
||||
currentChunkLength + curSplit.tokenSize <= chunkSize ||
|
||||
isSentence ||
|
||||
currentChunkLength + tokenSize <= chunkSize ||
|
||||
newChunk
|
||||
) {
|
||||
currentChunkLength += curSplit.tokenSize;
|
||||
currentChunk.push([curSplit.text, curSplit.tokenSize]);
|
||||
splits.shift();
|
||||
currentChunkLength += tokenSize;
|
||||
currentChunk.push([text, tokenSize]);
|
||||
newChunk = false;
|
||||
currentSplitResult = splitsIterator.next();
|
||||
} else {
|
||||
closeChunk();
|
||||
}
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
import { abbreviations } from "./abbreviations";
|
||||
import type { TextSplitter } from "./base";
|
||||
import SentenceTokenizer from "./sentence_tokenizer";
|
||||
|
||||
@@ -34,19 +35,15 @@ export const splitByChar = (): TextSplitterFn => {
|
||||
return (text: string) => text.split("");
|
||||
};
|
||||
|
||||
let sentenceTokenizer: SentenceTokenizer | null = null;
|
||||
|
||||
export const splitBySentenceTokenizer = (): TextSplitterFn => {
|
||||
if (!sentenceTokenizer) {
|
||||
sentenceTokenizer = new SentenceTokenizer([
|
||||
"i.e.",
|
||||
"etc.",
|
||||
"vs.",
|
||||
"Inc.",
|
||||
"A.S.A.P.",
|
||||
]);
|
||||
}
|
||||
const tokenizer = sentenceTokenizer;
|
||||
export const splitBySentenceTokenizer = (
|
||||
extraAbbreviations: string[] | undefined = [],
|
||||
): TextSplitterFn => {
|
||||
const tokenizer = new SentenceTokenizer([
|
||||
...abbreviations.english,
|
||||
...abbreviations.spanish,
|
||||
// Add the extra abbreviations provided by the user, e.g. for business-specific context
|
||||
...extraAbbreviations,
|
||||
]);
|
||||
return (text: string) => {
|
||||
try {
|
||||
return tokenizer.tokenize(text);
|
||||
|
||||
@@ -347,6 +347,8 @@ export function jsonToNode(json: any, type?: ObjectType) {
|
||||
return new Document(json);
|
||||
case ObjectType.IMAGE_DOCUMENT:
|
||||
return new ImageDocument(json);
|
||||
case ObjectType.IMAGE:
|
||||
return new ImageNode(json);
|
||||
default:
|
||||
throw new Error(`Invalid node type: ${nodeType}`);
|
||||
}
|
||||
|
||||
@@ -51,6 +51,13 @@ export const sentenceSplitterSchema = z
|
||||
})
|
||||
.optional()
|
||||
.default("[^,.;。?!]+[,.;。?!]?"),
|
||||
extraAbbreviations: z
|
||||
.array(z.string(), {
|
||||
description:
|
||||
"Extra abbreviations to consider while splitting into sentences. For example, for contracts, you may want to consider 'LLC.' as an important abbreviation",
|
||||
})
|
||||
.optional()
|
||||
.default([]),
|
||||
})
|
||||
.refine(
|
||||
(data) => data.chunkOverlap < data.chunkSize,
|
||||
|
||||
@@ -0,0 +1,103 @@
|
||||
import { filetypemime } from "magic-bytes.js";
|
||||
|
||||
/**
|
||||
* Converts a base64 string (without data: prefix) to a Uint8Array
|
||||
* @param base64 - The base64 string without data: prefix
|
||||
* @returns The Uint8Array
|
||||
*/
|
||||
export function base64ToUint8Array(base64: string): Uint8Array {
|
||||
// Decode Base64 string
|
||||
const binaryString = atob(base64);
|
||||
|
||||
// Convert binary string to Uint8Array
|
||||
const bytes = new Uint8Array(binaryString.length);
|
||||
for (let i = 0; i < binaryString.length; i++) {
|
||||
bytes[i] = binaryString.charCodeAt(i);
|
||||
}
|
||||
|
||||
return bytes;
|
||||
}
|
||||
|
||||
/**
|
||||
* Converts a Uint8Array to a base64 string.
|
||||
* @param uint8Array The Uint8Array to convert.
|
||||
* @returns The base64-encoded string.
|
||||
*/
|
||||
export function uint8ArrayToBase64(uint8Array: Uint8Array): string {
|
||||
let binary = "";
|
||||
for (let i = 0; i < uint8Array.byteLength; i++) {
|
||||
// Asserts that the value is not undefined, for `noUncheckedIndexedAccess`
|
||||
binary += String.fromCharCode(uint8Array[i]!);
|
||||
}
|
||||
return btoa(binary);
|
||||
}
|
||||
|
||||
/**
|
||||
* Extracts the MIME type from a data URL.
|
||||
* @param dataUrl The data URL string.
|
||||
* @returns The MIME type from the data URL.
|
||||
* @throws An error if the data URL is malformed.
|
||||
*/
|
||||
export function getMimeTypeFromDataUrl(dataUrl: string): string {
|
||||
if (!dataUrl.startsWith("data:")) {
|
||||
throw new Error("Not a data URL");
|
||||
}
|
||||
const commaIndex = dataUrl.indexOf(",");
|
||||
if (commaIndex === -1) {
|
||||
throw new Error("Invalid data URL format");
|
||||
}
|
||||
|
||||
const header = dataUrl.slice(0, commaIndex);
|
||||
const semicolonIndex = header.indexOf(";base64");
|
||||
if (semicolonIndex === -1) {
|
||||
throw new Error("Invalid data URL format: missing base64 encoding");
|
||||
}
|
||||
|
||||
return header.slice(5, semicolonIndex);
|
||||
}
|
||||
|
||||
/**
|
||||
* Convert base64 data to Blob
|
||||
* @param base64 - The base64 string
|
||||
* @param mimeType - The MIME type of the file
|
||||
* @returns The Blob
|
||||
*/
|
||||
export function base64ToBlob(base64: string, mimeType?: string): Blob {
|
||||
let extractedMimeType = mimeType;
|
||||
let base64Data = base64;
|
||||
|
||||
// Extract mimeType from data URL if not provided
|
||||
if (!mimeType && base64.startsWith("data:")) {
|
||||
extractedMimeType = getMimeTypeFromDataUrl(base64);
|
||||
base64Data = base64.slice(base64.indexOf(",") + 1);
|
||||
} else if (!mimeType) {
|
||||
throw new Error(
|
||||
"No MIME type provided and base64 is not in data URL format",
|
||||
);
|
||||
} else {
|
||||
// Extract base64 data from data URL if present
|
||||
const commaIndex = base64.indexOf(",");
|
||||
base64Data = commaIndex !== -1 ? base64.slice(commaIndex + 1) : base64;
|
||||
}
|
||||
|
||||
if (!extractedMimeType) {
|
||||
throw new Error("No MIME type found in base64 data");
|
||||
}
|
||||
|
||||
// convert base64 to Uint8Array
|
||||
const bytes = base64ToUint8Array(base64Data);
|
||||
|
||||
// Create Blob
|
||||
return new Blob([bytes], { type: extractedMimeType });
|
||||
}
|
||||
|
||||
export async function blobToDataUrl(input: Blob) {
|
||||
const arrayBuffer = await input.arrayBuffer();
|
||||
const uint8Array = new Uint8Array(arrayBuffer);
|
||||
const mimes = filetypemime(uint8Array);
|
||||
if (mimes.length < 1) {
|
||||
throw new Error("Unsupported image type");
|
||||
}
|
||||
const base64 = uint8ArrayToBase64(uint8Array);
|
||||
return `data:${mimes[0]};base64,${base64}`;
|
||||
}
|
||||
@@ -14,19 +14,6 @@ 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>,
|
||||
converter: (s: S) => D | null,
|
||||
): AsyncIterable<D> {
|
||||
for await (const data of stream) {
|
||||
const newData = converter(data);
|
||||
if (newData === null) {
|
||||
return;
|
||||
}
|
||||
yield newData;
|
||||
}
|
||||
}
|
||||
|
||||
export async function* streamCallbacks<S>(
|
||||
stream: AsyncIterable<S>,
|
||||
callbacks: {
|
||||
@@ -85,4 +72,6 @@ export {
|
||||
|
||||
export { MockLLM } from "./mock";
|
||||
|
||||
export * from "./encoding";
|
||||
export { objectEntries } from "./object-entries";
|
||||
export * from "./stream";
|
||||
|
||||
@@ -1,5 +1,4 @@
|
||||
import { fs } from "@llamaindex/env";
|
||||
import { filetypemime } from "magic-bytes.js";
|
||||
import type {
|
||||
ChatMessage,
|
||||
MessageContent,
|
||||
@@ -9,6 +8,7 @@ import type {
|
||||
} from "../llms";
|
||||
import type { QueryType } from "../query-engine";
|
||||
import type { ImageType } from "../schema";
|
||||
import { blobToDataUrl } from "./encoding";
|
||||
|
||||
/**
|
||||
* Extracts just the text whether from
|
||||
@@ -110,15 +110,6 @@ export function toToolDescriptions(tools: ToolMetadata[]): string {
|
||||
return JSON.stringify(toolsObj, null, 4);
|
||||
}
|
||||
|
||||
async function blobToDataUrl(input: Blob) {
|
||||
const buffer = Buffer.from(await input.arrayBuffer());
|
||||
const mimes = filetypemime(buffer);
|
||||
if (mimes.length < 1) {
|
||||
throw new Error("Unsupported image type");
|
||||
}
|
||||
return "data:" + mimes[0] + ";base64," + buffer.toString("base64");
|
||||
}
|
||||
|
||||
export async function imageToDataUrl(
|
||||
input: ImageType | Uint8Array,
|
||||
): Promise<string> {
|
||||
|
||||
@@ -0,0 +1,12 @@
|
||||
export async function* streamConverter<S, D>(
|
||||
stream: AsyncIterable<S>,
|
||||
converter: (s: S) => D | null,
|
||||
): AsyncIterable<D> {
|
||||
for await (const data of stream) {
|
||||
const newData = converter(data);
|
||||
if (newData === null) {
|
||||
return;
|
||||
}
|
||||
yield newData;
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,99 @@
|
||||
import {
|
||||
base64ToBlob,
|
||||
base64ToUint8Array,
|
||||
blobToDataUrl,
|
||||
getMimeTypeFromDataUrl,
|
||||
uint8ArrayToBase64,
|
||||
} from "@llamaindex/core/utils";
|
||||
import { describe, expect, it } from "vitest";
|
||||
|
||||
const testString = "LlamaIndex";
|
||||
const testBase64 = "TGxhbWFJbmRleA=="; // btoa('LlamaIndex')
|
||||
const testUint8Array = new TextEncoder().encode(testString);
|
||||
|
||||
const pngB64 =
|
||||
"iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAQAAAC1HAwCAAAAC0lEQVR42mNkYAAAAAYAAjCB0C8AAAAASUVORK5CYII=";
|
||||
const pngMime = "image/png";
|
||||
const pngDataUrl = `data:${pngMime};base64,${pngB64}`;
|
||||
const pngBinaryString = atob(pngB64);
|
||||
const pngBytes = new Uint8Array(pngBinaryString.length);
|
||||
for (let i = 0; i < pngBinaryString.length; i++) {
|
||||
pngBytes[i] = pngBinaryString.charCodeAt(i);
|
||||
}
|
||||
|
||||
describe("Encoding utils", () => {
|
||||
describe("base64ToUint8Array", () => {
|
||||
it("should correctly convert a base64 string to a Uint8Array", () => {
|
||||
const result = base64ToUint8Array(testBase64);
|
||||
expect(result).toBeInstanceOf(Uint8Array);
|
||||
expect(result).toEqual(testUint8Array);
|
||||
});
|
||||
});
|
||||
|
||||
describe("uint8ArrayToBase64", () => {
|
||||
it("should correctly convert a Uint8Array to a base64 string", () => {
|
||||
const result = uint8ArrayToBase64(testUint8Array);
|
||||
expect(result).toBe(testBase64);
|
||||
});
|
||||
});
|
||||
|
||||
describe("getMimeTypeFromDataUrl", () => {
|
||||
it("should extract the correct MIME type from a data URL", () => {
|
||||
const result = getMimeTypeFromDataUrl(pngDataUrl);
|
||||
expect(result).toBe(pngMime);
|
||||
});
|
||||
|
||||
it("should throw an error for non-data URLs", () => {
|
||||
expect(() => getMimeTypeFromDataUrl("not a data url")).toThrow(
|
||||
"Not a data URL",
|
||||
);
|
||||
});
|
||||
|
||||
it("should throw an error for malformed data URLs", () => {
|
||||
expect(() => getMimeTypeFromDataUrl("data:image/pngbase64,abc")).toThrow(
|
||||
"Invalid data URL format: missing base64 encoding",
|
||||
);
|
||||
expect(() => getMimeTypeFromDataUrl("data:image/png;base64")).toThrow(
|
||||
"Invalid data URL format",
|
||||
);
|
||||
});
|
||||
});
|
||||
|
||||
describe("base64ToBlob", () => {
|
||||
it("should convert from a data URL string", async () => {
|
||||
const blob = base64ToBlob(pngDataUrl);
|
||||
expect(blob).toBeInstanceOf(Blob);
|
||||
expect(blob.type).toBe(pngMime);
|
||||
const arrayBuffer = await blob.arrayBuffer();
|
||||
expect(new Uint8Array(arrayBuffer)).toEqual(pngBytes);
|
||||
});
|
||||
|
||||
it("should convert from a base64 string with an explicit MIME type", async () => {
|
||||
const blob = base64ToBlob(pngB64, pngMime);
|
||||
expect(blob).toBeInstanceOf(Blob);
|
||||
expect(blob.type).toBe(pngMime);
|
||||
const arrayBuffer = await blob.arrayBuffer();
|
||||
expect(new Uint8Array(arrayBuffer)).toEqual(pngBytes);
|
||||
});
|
||||
|
||||
it("should prioritize the explicit MIME type if a data URL is provided", async () => {
|
||||
const differentMime = "image/jpeg";
|
||||
const blob = base64ToBlob(pngDataUrl, differentMime);
|
||||
expect(blob.type).toBe(differentMime);
|
||||
});
|
||||
|
||||
it("should throw an error if no MIME type can be determined", () => {
|
||||
expect(() => base64ToBlob(pngB64)).toThrow(
|
||||
"No MIME type provided and base64 is not in data URL format",
|
||||
);
|
||||
});
|
||||
});
|
||||
|
||||
describe("blobToDataUrl", () => {
|
||||
it("should correctly convert a blob to a data URL", async () => {
|
||||
const blob = new Blob([pngBytes], { type: "image/png" });
|
||||
const result = await blobToDataUrl(blob);
|
||||
expect(result).toBe(pngDataUrl);
|
||||
});
|
||||
});
|
||||
});
|
||||
@@ -75,6 +75,22 @@ describe("sentence splitter", () => {
|
||||
expect(splits).toEqual(["This is a sentence. This is another sentence."]);
|
||||
});
|
||||
|
||||
test("overall split long text", () => {
|
||||
const sentenceSplitter = new SentenceSplitter({
|
||||
chunkSize: 10,
|
||||
chunkOverlap: 0,
|
||||
});
|
||||
const splits = sentenceSplitter.splitText(
|
||||
"The first short sentence. The first long long long sentence. The second short sentence. The second long long long sentence.",
|
||||
);
|
||||
expect(splits).toEqual([
|
||||
"The first short sentence.",
|
||||
"The first long long long sentence.",
|
||||
"The second short sentence.",
|
||||
"The second long long long sentence.",
|
||||
]);
|
||||
});
|
||||
|
||||
test("doesn't split decimals", () => {
|
||||
const sentenceSplitter = new SentenceSplitter({
|
||||
chunkSize: 5,
|
||||
@@ -91,6 +107,39 @@ describe("sentence splitter", () => {
|
||||
]);
|
||||
});
|
||||
|
||||
test("doesn't split basic abbreviations", () => {
|
||||
const sentenceSplitter = new SentenceSplitter({
|
||||
chunkSize: 15,
|
||||
chunkOverlap: 0,
|
||||
});
|
||||
const splits = sentenceSplitter.splitText(
|
||||
"This is a sentence of Broda Noel. This is the sentence of Sr. Broda Noel. This is a sentence of somebody else",
|
||||
);
|
||||
|
||||
expect(splits).toEqual([
|
||||
"This is a sentence of Broda Noel.",
|
||||
"This is the sentence of Sr. Broda Noel.",
|
||||
"This is a sentence of somebody else",
|
||||
]);
|
||||
});
|
||||
|
||||
test("doesn't split extra abbreviations", () => {
|
||||
const sentenceSplitter = new SentenceSplitter({
|
||||
chunkSize: 10,
|
||||
chunkOverlap: 0,
|
||||
extraAbbreviations: ["S.A."],
|
||||
});
|
||||
const splits = sentenceSplitter.splitText(
|
||||
"This is a sentence. The S.A. Broda Company. This is another sentence",
|
||||
);
|
||||
|
||||
expect(splits).toEqual([
|
||||
"This is a sentence.",
|
||||
"The S.A. Broda Company.",
|
||||
"This is another sentence",
|
||||
]);
|
||||
});
|
||||
|
||||
test("splits cjk", () => {
|
||||
const sentenceSplitter = new SentenceSplitter({
|
||||
chunkSize: 30,
|
||||
|
||||
@@ -1,5 +1,43 @@
|
||||
# @llamaindex/experimental
|
||||
|
||||
## 0.0.188
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- llamaindex@0.11.11
|
||||
|
||||
## 0.0.187
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.10
|
||||
|
||||
## 0.0.186
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.9
|
||||
|
||||
## 0.0.185
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.8
|
||||
|
||||
## 0.0.184
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [3c857f4]
|
||||
- llamaindex@0.11.7
|
||||
|
||||
## 0.0.183
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- llamaindex@0.11.6
|
||||
|
||||
## 0.0.182
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "@llamaindex/experimental",
|
||||
"description": "Experimental package for LlamaIndexTS",
|
||||
"version": "0.0.182",
|
||||
"version": "0.0.188",
|
||||
"type": "module",
|
||||
"types": "dist/type/index.d.ts",
|
||||
"main": "dist/cjs/index.js",
|
||||
|
||||
@@ -1,5 +1,63 @@
|
||||
# llamaindex
|
||||
|
||||
## 0.11.11
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 7039e1a: Internal cleanup of base64 encoding
|
||||
- Updated dependencies [7039e1a]
|
||||
- Updated dependencies [7039e1a]
|
||||
- @llamaindex/core@0.6.12
|
||||
- @llamaindex/cloud@4.0.16
|
||||
- @llamaindex/node-parser@2.0.12
|
||||
- @llamaindex/workflow@1.1.12
|
||||
|
||||
## 0.11.10
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [f7ec293]
|
||||
- @llamaindex/workflow@1.1.11
|
||||
|
||||
## 0.11.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [a89e187]
|
||||
- Updated dependencies [62699b7]
|
||||
- Updated dependencies [c5b2691]
|
||||
- Updated dependencies [d8ac8d3]
|
||||
- @llamaindex/core@0.6.11
|
||||
- @llamaindex/cloud@4.0.15
|
||||
- @llamaindex/node-parser@2.0.11
|
||||
- @llamaindex/workflow@1.1.10
|
||||
|
||||
## 0.11.8
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [8a51c16]
|
||||
- Updated dependencies [1b5af14]
|
||||
- @llamaindex/workflow@1.1.9
|
||||
- @llamaindex/core@0.6.10
|
||||
- @llamaindex/cloud@4.0.14
|
||||
- @llamaindex/node-parser@2.0.10
|
||||
|
||||
## 0.11.7
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 3c857f4: chore: move ajv to dev deps
|
||||
- Updated dependencies [dbd857f]
|
||||
- @llamaindex/workflow@1.1.8
|
||||
|
||||
## 0.11.6
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [40161fe]
|
||||
- @llamaindex/workflow@1.1.7
|
||||
|
||||
## 0.11.5
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "llamaindex",
|
||||
"version": "0.11.5",
|
||||
"version": "0.11.11",
|
||||
"license": "MIT",
|
||||
"type": "module",
|
||||
"keywords": [
|
||||
@@ -24,14 +24,14 @@
|
||||
"@llamaindex/core": "workspace:*",
|
||||
"@llamaindex/env": "workspace:*",
|
||||
"@llamaindex/node-parser": "workspace:*",
|
||||
"@llamaindex/workflow": "1.1.6",
|
||||
"@llamaindex/workflow": "workspace:*",
|
||||
"@types/lodash": "^4.17.7",
|
||||
"@types/node": "^22.9.0",
|
||||
"ajv": "^8.17.1",
|
||||
"lodash": "^4.17.21",
|
||||
"magic-bytes.js": "^1.10.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"ajv": "^8.17.1",
|
||||
"@types/node": "^22.9.0"
|
||||
},
|
||||
"engines": {
|
||||
|
||||
@@ -18,11 +18,11 @@ import type {
|
||||
} from "@llamaindex/core/llms";
|
||||
import {
|
||||
extractText,
|
||||
isAsyncIterable,
|
||||
stringifyJSONToMessageContent,
|
||||
} from "@llamaindex/core/utils";
|
||||
import { randomUUID } from "@llamaindex/env";
|
||||
import { getReACTAgentSystemHeader } from "../internal/prompt/react.js";
|
||||
import { isAsyncIterable } from "../internal/utils.js";
|
||||
import { Settings } from "../Settings.js";
|
||||
|
||||
export type ReACTAgentParams = AgentParamsBase<LLM>;
|
||||
|
||||
@@ -63,7 +63,6 @@ export * from "./evaluation/index.js";
|
||||
export * from "./extractors/index.js";
|
||||
export * from "./indices/index.js";
|
||||
export * from "./ingestion/index.js";
|
||||
export { imageToDataUrl } from "./internal/utils.js";
|
||||
export * from "./node-parser.js";
|
||||
export * from "./objects/index.js";
|
||||
export * from "./OutputParser.js";
|
||||
|
||||
@@ -1,77 +0,0 @@
|
||||
import type { ImageType } from "@llamaindex/core/schema";
|
||||
import { fs } from "@llamaindex/env";
|
||||
import { filetypemime } from "magic-bytes.js";
|
||||
|
||||
export const isAsyncIterable = (
|
||||
obj: unknown,
|
||||
): obj is AsyncIterable<unknown> => {
|
||||
return obj != null && typeof obj === "object" && Symbol.asyncIterator in obj;
|
||||
};
|
||||
|
||||
export const isReadableStream = (obj: unknown): obj is ReadableStream => {
|
||||
return obj instanceof ReadableStream;
|
||||
};
|
||||
|
||||
export const isIterable = (obj: unknown): obj is Iterable<unknown> => {
|
||||
return obj != null && typeof obj === "object" && Symbol.iterator in obj;
|
||||
};
|
||||
|
||||
async function blobToDataUrl(input: Blob) {
|
||||
const buffer = Buffer.from(await input.arrayBuffer());
|
||||
const mimes = filetypemime(buffer);
|
||||
if (mimes.length < 1) {
|
||||
throw new Error("Unsupported image type");
|
||||
}
|
||||
return "data:" + mimes[0] + ";base64," + buffer.toString("base64");
|
||||
}
|
||||
|
||||
export async function imageToString(input: ImageType): Promise<string> {
|
||||
if (input instanceof Blob) {
|
||||
// if the image is a Blob, convert it to a base64 data URL
|
||||
return await blobToDataUrl(input);
|
||||
} else if (typeof input === "string") {
|
||||
return input;
|
||||
} else if (input instanceof URL) {
|
||||
return input.toString();
|
||||
} else {
|
||||
throw new Error(`Unsupported input type: ${typeof input}`);
|
||||
}
|
||||
}
|
||||
|
||||
export function stringToImage(input: string): ImageType {
|
||||
if (input.startsWith("data:")) {
|
||||
// if the input is a base64 data URL, convert it back to a Blob
|
||||
const base64Data = input.split(",")[1]!;
|
||||
const byteArray = Buffer.from(base64Data, "base64");
|
||||
return new Blob([byteArray]);
|
||||
} else if (input.startsWith("http://") || input.startsWith("https://")) {
|
||||
return new URL(input);
|
||||
} else {
|
||||
return input;
|
||||
}
|
||||
}
|
||||
|
||||
export async function imageToDataUrl(
|
||||
input: ImageType | Uint8Array,
|
||||
): Promise<string> {
|
||||
// first ensure, that the input is a Blob
|
||||
if (
|
||||
(input instanceof URL && input.protocol === "file:") ||
|
||||
typeof input === "string"
|
||||
) {
|
||||
// string or file URL
|
||||
const dataBuffer = await fs.readFile(
|
||||
input instanceof URL ? input.pathname : input,
|
||||
);
|
||||
input = new Blob([dataBuffer]);
|
||||
} else if (!(input instanceof Blob)) {
|
||||
if (input instanceof URL) {
|
||||
throw new Error(`Unsupported URL with protocol: ${input.protocol}`);
|
||||
} else if (input instanceof Uint8Array) {
|
||||
input = new Blob([input]); // convert Uint8Array to Blob
|
||||
} else {
|
||||
throw new Error(`Unsupported input type: ${typeof input}`);
|
||||
}
|
||||
}
|
||||
return await blobToDataUrl(input);
|
||||
}
|
||||
@@ -1,5 +1,24 @@
|
||||
# @llamaindex/core-test
|
||||
|
||||
## 0.1.7
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/openai@0.4.6
|
||||
|
||||
## 0.1.6
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [d8ac8d3]
|
||||
- @llamaindex/openai@0.4.5
|
||||
|
||||
## 0.1.5
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- @llamaindex/openai@0.4.4
|
||||
|
||||
## 0.1.4
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
{
|
||||
"name": "@llamaindex/llamaindex-test",
|
||||
"private": true,
|
||||
"version": "0.1.4",
|
||||
"version": "0.1.7",
|
||||
"type": "module",
|
||||
"scripts": {
|
||||
"test": "vitest run"
|
||||
|
||||
@@ -1,5 +1,30 @@
|
||||
# @llamaindex/node-parser
|
||||
|
||||
## 2.0.12
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [7039e1a]
|
||||
- Updated dependencies [7039e1a]
|
||||
- @llamaindex/core@0.6.12
|
||||
|
||||
## 2.0.11
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [a89e187]
|
||||
- Updated dependencies [62699b7]
|
||||
- Updated dependencies [c5b2691]
|
||||
- Updated dependencies [d8ac8d3]
|
||||
- @llamaindex/core@0.6.11
|
||||
|
||||
## 2.0.10
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [1b5af14]
|
||||
- @llamaindex/core@0.6.10
|
||||
|
||||
## 2.0.9
|
||||
|
||||
### Patch Changes
|
||||
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user