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89
changelog.md
Normal file
89
changelog.md
Normal file
@ -0,0 +1,89 @@
|
||||
# Changelog
|
||||
|
||||
## 2025-02-05 - 0.3.0 - feat(integration-xai)
|
||||
Add support for X.AI provider with chat and document processing capabilities.
|
||||
|
||||
- Introduced XAIProvider class for integrating X.AI features.
|
||||
- Implemented chat streaming and synchronous chat for X.AI.
|
||||
- Enabled document processing capabilities with PDF conversion in X.AI.
|
||||
|
||||
## 2025-02-03 - 0.2.0 - feat(provider.anthropic)
|
||||
Add support for vision and document processing in Anthropic provider
|
||||
|
||||
- Implemented vision tasks for Anthropic provider using Claude-3-opus-20240229 model.
|
||||
- Implemented document processing for Anthropic provider, supporting conversion of PDF documents to images and analysis with Claude-3-opus-20240229 model.
|
||||
- Updated documentation to reflect the new capabilities of the Anthropic provider.
|
||||
|
||||
## 2025-02-03 - 0.1.0 - feat(providers)
|
||||
Add vision and document processing capabilities to providers
|
||||
|
||||
- OpenAI and Ollama providers now support vision tasks using GPT-4 Vision and Llava models respectively.
|
||||
- Document processing has been implemented for OpenAI and Ollama providers, converting PDFs to images for analysis.
|
||||
- Introduced abstract methods for vision and document processing in the MultiModalModel class.
|
||||
- Updated the readme file with examples for vision and document processing.
|
||||
|
||||
## 2025-02-03 - 0.0.19 - fix(core)
|
||||
Enhanced chat streaming and error handling across providers
|
||||
|
||||
- Refactored chatStream method to properly handle input streams and processes in Perplexity, OpenAI, Ollama, and Anthropic providers.
|
||||
- Improved error handling and message parsing in chatStream implementations.
|
||||
- Defined distinct interfaces for chat options, messages, and responses.
|
||||
- Adjusted the test logic in test/test.ts for the new classification response requirement.
|
||||
|
||||
## 2024-09-19 - 0.0.18 - fix(dependencies)
|
||||
Update dependencies to the latest versions.
|
||||
|
||||
- Updated @git.zone/tsbuild from ^2.1.76 to ^2.1.84
|
||||
- Updated @git.zone/tsrun from ^1.2.46 to ^1.2.49
|
||||
- Updated @push.rocks/tapbundle from ^5.0.23 to ^5.3.0
|
||||
- Updated @types/node from ^20.12.12 to ^22.5.5
|
||||
- Updated @anthropic-ai/sdk from ^0.21.0 to ^0.27.3
|
||||
- Updated @push.rocks/smartfile from ^11.0.14 to ^11.0.21
|
||||
- Updated @push.rocks/smartpromise from ^4.0.3 to ^4.0.4
|
||||
- Updated @push.rocks/webstream from ^1.0.8 to ^1.0.10
|
||||
- Updated openai from ^4.47.1 to ^4.62.1
|
||||
|
||||
## 2024-05-29 - 0.0.17 - Documentation
|
||||
Updated project description.
|
||||
|
||||
- Improved project description for clarity and details.
|
||||
|
||||
## 2024-05-17 - 0.0.16 to 0.0.15 - Core
|
||||
Fixes and updates.
|
||||
|
||||
- Various core updates and fixes for stability improvements.
|
||||
|
||||
## 2024-04-29 - 0.0.14 to 0.0.13 - Core
|
||||
Fixes and updates.
|
||||
|
||||
- Multiple core updates and fixes for enhanced functionality.
|
||||
|
||||
## 2024-04-29 - 0.0.12 - Core
|
||||
Fixes and updates.
|
||||
|
||||
- Core update and bug fixes.
|
||||
|
||||
## 2024-04-29 - 0.0.11 - Provider
|
||||
Fix integration for anthropic provider.
|
||||
|
||||
- Correction in the integration process with anthropic provider for better compatibility.
|
||||
|
||||
## 2024-04-27 - 0.0.10 to 0.0.9 - Core
|
||||
Fixes and updates.
|
||||
|
||||
- Updates and fixes to core components.
|
||||
- Updated tsconfig for improved TypeScript configuration.
|
||||
|
||||
## 2024-04-01 - 0.0.8 to 0.0.7 - Core and npmextra
|
||||
Core updates and npmextra configuration.
|
||||
|
||||
- Core fixes and updates.
|
||||
- Updates to npmextra.json for githost configuration.
|
||||
|
||||
## 2024-03-31 - 0.0.6 to 0.0.2 - Core
|
||||
Initial core updates and fixes.
|
||||
|
||||
- Multiple updates and fixes to core following initial versions.
|
||||
|
||||
|
||||
This summarizes the relevant updates and changes based on the provided commit messages. The changelog excludes commits that are version tags without meaningful content or repeated entries.
|
||||
19
license
Normal file
19
license
Normal file
@ -0,0 +1,19 @@
|
||||
Copyright (c) 2024 Task Venture Capital GmbH (hello@task.vc)
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
@ -5,21 +5,20 @@
|
||||
"githost": "code.foss.global",
|
||||
"gitscope": "push.rocks",
|
||||
"gitrepo": "smartai",
|
||||
"description": "Provides a standardized interface for integrating and conversing with multiple AI models, supporting operations like chat and potentially audio responses.",
|
||||
"description": "A TypeScript library for integrating and interacting with multiple AI models, offering capabilities for chat and potentially audio responses.",
|
||||
"npmPackagename": "@push.rocks/smartai",
|
||||
"license": "MIT",
|
||||
"projectDomain": "push.rocks",
|
||||
"keywords": [
|
||||
"AI models integration",
|
||||
"OpenAI GPT",
|
||||
"Anthropic AI",
|
||||
"text-to-speech",
|
||||
"conversation stream",
|
||||
"AI integration",
|
||||
"chatbot",
|
||||
"TypeScript",
|
||||
"ESM",
|
||||
"streaming API",
|
||||
"modular design",
|
||||
"development tool"
|
||||
"OpenAI",
|
||||
"Anthropic",
|
||||
"multi-model support",
|
||||
"audio responses",
|
||||
"text-to-speech",
|
||||
"streaming chat"
|
||||
]
|
||||
}
|
||||
},
|
||||
|
||||
47
package.json
47
package.json
@ -1,8 +1,8 @@
|
||||
{
|
||||
"name": "@push.rocks/smartai",
|
||||
"version": "0.0.10",
|
||||
"version": "0.3.0",
|
||||
"private": false,
|
||||
"description": "Provides a standardized interface for integrating and conversing with multiple AI models, supporting operations like chat and potentially audio responses.",
|
||||
"description": "A TypeScript library for integrating and interacting with multiple AI models, offering capabilities for chat and potentially audio responses.",
|
||||
"main": "dist_ts/index.js",
|
||||
"typings": "dist_ts/index.d.ts",
|
||||
"type": "module",
|
||||
@ -14,31 +14,33 @@
|
||||
"buildDocs": "(tsdoc)"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@git.zone/tsbuild": "^2.1.25",
|
||||
"@git.zone/tsbuild": "^2.1.84",
|
||||
"@git.zone/tsbundle": "^2.0.5",
|
||||
"@git.zone/tsrun": "^1.2.46",
|
||||
"@git.zone/tsrun": "^1.2.49",
|
||||
"@git.zone/tstest": "^1.0.90",
|
||||
"@push.rocks/qenv": "^6.0.5",
|
||||
"@push.rocks/tapbundle": "^5.0.23",
|
||||
"@types/node": "^20.12.7"
|
||||
"@push.rocks/tapbundle": "^5.3.0",
|
||||
"@types/node": "^22.5.5"
|
||||
},
|
||||
"dependencies": {
|
||||
"@anthropic-ai/sdk": "^0.20.7",
|
||||
"@push.rocks/smartexpose": "^1.0.5",
|
||||
"@push.rocks/smartfile": "^11.0.14",
|
||||
"@anthropic-ai/sdk": "^0.27.3",
|
||||
"@push.rocks/smartarray": "^1.0.8",
|
||||
"@push.rocks/smartfile": "^11.0.21",
|
||||
"@push.rocks/smartpath": "^5.0.18",
|
||||
"@push.rocks/smartpromise": "^4.0.3",
|
||||
"@push.rocks/webstream": "^1.0.8",
|
||||
"openai": "^4.38.3"
|
||||
"@push.rocks/smartpdf": "^3.1.6",
|
||||
"@push.rocks/smartpromise": "^4.0.4",
|
||||
"@push.rocks/smartrequest": "^2.0.22",
|
||||
"@push.rocks/webstream": "^1.0.10",
|
||||
"openai": "^4.62.1"
|
||||
},
|
||||
"repository": {
|
||||
"type": "git",
|
||||
"url": "git+https://code.foss.global/push.rocks/smartai.git"
|
||||
"url": "https://code.foss.global/push.rocks/smartai.git"
|
||||
},
|
||||
"bugs": {
|
||||
"url": "https://code.foss.global/push.rocks/smartai/issues"
|
||||
},
|
||||
"homepage": "https://code.foss.global/push.rocks/smartai#readme",
|
||||
"homepage": "https://code.foss.global/push.rocks/smartai",
|
||||
"browserslist": [
|
||||
"last 1 chrome versions"
|
||||
],
|
||||
@ -55,15 +57,14 @@
|
||||
"readme.md"
|
||||
],
|
||||
"keywords": [
|
||||
"AI models integration",
|
||||
"OpenAI GPT",
|
||||
"Anthropic AI",
|
||||
"text-to-speech",
|
||||
"conversation stream",
|
||||
"AI integration",
|
||||
"chatbot",
|
||||
"TypeScript",
|
||||
"ESM",
|
||||
"streaming API",
|
||||
"modular design",
|
||||
"development tool"
|
||||
"OpenAI",
|
||||
"Anthropic",
|
||||
"multi-model support",
|
||||
"audio responses",
|
||||
"text-to-speech",
|
||||
"streaming chat"
|
||||
]
|
||||
}
|
||||
|
||||
7944
pnpm-lock.yaml
generated
7944
pnpm-lock.yaml
generated
File diff suppressed because it is too large
Load Diff
272
readme.md
272
readme.md
@ -1,6 +1,6 @@
|
||||
# @push.rocks/smartai
|
||||
|
||||
Provides a standardized interface for integrating and conversing with multiple AI models, supporting operations like chat and potentially audio responses.
|
||||
Provides a standardized interface for integrating and conversing with multiple AI models, supporting operations like chat, streaming interactions, and audio responses.
|
||||
|
||||
## Install
|
||||
|
||||
@ -12,101 +12,223 @@ npm install @push.rocks/smartai
|
||||
|
||||
This command installs the package and adds it to your project's dependencies.
|
||||
|
||||
## Supported AI Providers
|
||||
|
||||
@push.rocks/smartai supports multiple AI providers, each with its own unique capabilities:
|
||||
|
||||
### OpenAI
|
||||
- Models: GPT-4, GPT-3.5-turbo, GPT-4-vision-preview
|
||||
- Features: Chat, Streaming, Audio Generation, Vision, Document Processing
|
||||
- Configuration:
|
||||
```typescript
|
||||
openaiToken: 'your-openai-token'
|
||||
```
|
||||
|
||||
### X.AI
|
||||
- Models: Grok-2-latest
|
||||
- Features: Chat, Streaming, Document Processing
|
||||
- Configuration:
|
||||
```typescript
|
||||
xaiToken: 'your-xai-token'
|
||||
```
|
||||
|
||||
### Anthropic
|
||||
- Models: Claude-3-opus-20240229
|
||||
- Features: Chat, Streaming, Vision, Document Processing
|
||||
- Configuration:
|
||||
```typescript
|
||||
anthropicToken: 'your-anthropic-token'
|
||||
```
|
||||
|
||||
### Perplexity
|
||||
- Models: Mixtral-8x7b-instruct
|
||||
- Features: Chat, Streaming
|
||||
- Configuration:
|
||||
```typescript
|
||||
perplexityToken: 'your-perplexity-token'
|
||||
```
|
||||
|
||||
### Groq
|
||||
- Models: Llama-3.3-70b-versatile
|
||||
- Features: Chat, Streaming
|
||||
- Configuration:
|
||||
```typescript
|
||||
groqToken: 'your-groq-token'
|
||||
```
|
||||
|
||||
### Ollama
|
||||
- Models: Configurable (default: llama2, llava for vision/documents)
|
||||
- Features: Chat, Streaming, Vision, Document Processing
|
||||
- Configuration:
|
||||
```typescript
|
||||
baseUrl: 'http://localhost:11434' // Optional
|
||||
model: 'llama2' // Optional
|
||||
visionModel: 'llava' // Optional, for vision and document tasks
|
||||
```
|
||||
|
||||
## Usage
|
||||
|
||||
The usage section delves into how to leverage the `@push.rocks/smartai` package to interact with AI models in an application. This package simplifies the integration and conversation with AI models by providing a standardized interface. The examples below demonstrate the package's capabilities in engaging with AI models for chat operations and potentially handling audio responses using TypeScript and ESM syntax.
|
||||
The `@push.rocks/smartai` package is a comprehensive solution for integrating and interacting with various AI models, designed to support operations ranging from chat interactions to audio responses. This documentation will guide you through the process of utilizing `@push.rocks/smartai` in your applications.
|
||||
|
||||
### Integrating AI Models
|
||||
### Getting Started
|
||||
|
||||
#### Importing the Module
|
||||
Before you begin, ensure you have installed the package as described in the **Install** section above. Once installed, you can start integrating AI functionalities into your application.
|
||||
|
||||
Start by importing `SmartAi` and the AI providers you wish to use from `@push.rocks/smartai`.
|
||||
### Initializing SmartAi
|
||||
|
||||
The first step is to import and initialize the `SmartAi` class with appropriate options for the AI services you plan to use:
|
||||
|
||||
```typescript
|
||||
import { SmartAi, OpenAiProvider, AnthropicProvider } from '@push.rocks/smartai';
|
||||
```
|
||||
import { SmartAi } from '@push.rocks/smartai';
|
||||
|
||||
#### Initializing `SmartAi`
|
||||
|
||||
Create an instance of `SmartAi` with the necessary credentials for accessing the AI services.
|
||||
|
||||
```typescript
|
||||
const smartAi = new SmartAi({
|
||||
openaiToken: 'your-openai-access-token',
|
||||
anthropicToken: 'your-anthropic-access-token'
|
||||
});
|
||||
```
|
||||
|
||||
### Chatting with the AI
|
||||
|
||||
#### Creating a Conversation
|
||||
|
||||
To begin a conversation, choose the AI provider you'd like to use. For instance, to use OpenAI:
|
||||
|
||||
```typescript
|
||||
async function createOpenAiConversation() {
|
||||
const conversation = await smartAi.createOpenApiConversation();
|
||||
// Use the conversation for chatting
|
||||
}
|
||||
```
|
||||
|
||||
Similarly, for an Anthropic AI conversation:
|
||||
|
||||
```typescript
|
||||
async function createAnthropicConversation() {
|
||||
const conversation = await smartAi.createAnthropicConversation();
|
||||
// Use the conversation for chatting
|
||||
}
|
||||
```
|
||||
|
||||
### Streaming Chat with OpenAI
|
||||
|
||||
For more advanced scenarios, like a streaming chat with OpenAI, you would interact with the chat stream directly:
|
||||
|
||||
```typescript
|
||||
// Assuming a conversation has been created and initialized...
|
||||
const inputStreamWriter = conversation.getInputStreamWriter();
|
||||
const outputStream = conversation.getOutputStream();
|
||||
|
||||
// Write a message to the input stream for the AI to process
|
||||
await inputStreamWriter.write('Hello, how can I help you today?');
|
||||
|
||||
// Listen to the output stream for responses from AI
|
||||
const reader = outputStream.getReader();
|
||||
reader.read().then(function processText({ done, value }) {
|
||||
if (done) {
|
||||
console.log("No more messages from AI");
|
||||
return;
|
||||
openaiToken: 'your-openai-token',
|
||||
xaiToken: 'your-xai-token',
|
||||
anthropicToken: 'your-anthropic-token',
|
||||
perplexityToken: 'your-perplexity-token',
|
||||
groqToken: 'your-groq-token',
|
||||
ollama: {
|
||||
baseUrl: 'http://localhost:11434',
|
||||
model: 'llama2'
|
||||
}
|
||||
console.log("AI says:", value);
|
||||
// Continue reading messages
|
||||
reader.read().then(processText);
|
||||
});
|
||||
|
||||
await smartAi.start();
|
||||
```
|
||||
|
||||
### Chat Interactions
|
||||
|
||||
#### Synchronous Chat
|
||||
|
||||
For simple question-answer interactions:
|
||||
|
||||
```typescript
|
||||
const response = await smartAi.openaiProvider.chat({
|
||||
systemMessage: 'You are a helpful assistant.',
|
||||
userMessage: 'What is the capital of France?',
|
||||
messageHistory: [] // Previous messages in the conversation
|
||||
});
|
||||
|
||||
console.log(response.message);
|
||||
```
|
||||
|
||||
#### Streaming Chat
|
||||
|
||||
For real-time, streaming interactions:
|
||||
|
||||
```typescript
|
||||
const textEncoder = new TextEncoder();
|
||||
const textDecoder = new TextDecoder();
|
||||
|
||||
// Create input and output streams
|
||||
const { writable, readable } = new TransformStream();
|
||||
const writer = writable.getWriter();
|
||||
|
||||
// Send a message
|
||||
const message = {
|
||||
role: 'user',
|
||||
content: 'Tell me a story about a brave knight'
|
||||
};
|
||||
|
||||
writer.write(textEncoder.encode(JSON.stringify(message) + '\n'));
|
||||
|
||||
// Process the response stream
|
||||
const stream = await smartAi.openaiProvider.chatStream(readable);
|
||||
const reader = stream.getReader();
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
console.log('AI:', value); // Process each chunk of the response
|
||||
}
|
||||
```
|
||||
|
||||
### Audio Generation
|
||||
|
||||
For providers that support audio generation (currently OpenAI):
|
||||
|
||||
```typescript
|
||||
const audioStream = await smartAi.openaiProvider.audio({
|
||||
message: 'Hello, this is a test of text-to-speech'
|
||||
});
|
||||
|
||||
// Handle the audio stream (e.g., save to file or play)
|
||||
```
|
||||
|
||||
### Document Processing
|
||||
|
||||
For providers that support document processing (OpenAI, Ollama, and Anthropic):
|
||||
|
||||
```typescript
|
||||
// Using OpenAI
|
||||
const result = await smartAi.openaiProvider.document({
|
||||
systemMessage: 'Classify the document type',
|
||||
userMessage: 'What type of document is this?',
|
||||
messageHistory: [],
|
||||
pdfDocuments: [pdfBuffer] // Uint8Array of PDF content
|
||||
});
|
||||
|
||||
// Using Ollama with llava
|
||||
const analysis = await smartAi.ollamaProvider.document({
|
||||
systemMessage: 'You are a document analysis assistant',
|
||||
userMessage: 'Extract the key information from this document',
|
||||
messageHistory: [],
|
||||
pdfDocuments: [pdfBuffer] // Uint8Array of PDF content
|
||||
});
|
||||
|
||||
// Using Anthropic with Claude 3
|
||||
const anthropicAnalysis = await smartAi.anthropicProvider.document({
|
||||
systemMessage: 'You are a document analysis assistant',
|
||||
userMessage: 'Please analyze this document and extract key information',
|
||||
messageHistory: [],
|
||||
pdfDocuments: [pdfBuffer] // Uint8Array of PDF content
|
||||
});
|
||||
```
|
||||
|
||||
### Handling Audio Responses
|
||||
Both providers will:
|
||||
1. Convert PDF documents to images
|
||||
2. Process each page using their vision models
|
||||
3. Return a comprehensive analysis based on the system message and user query
|
||||
|
||||
The package may also support converting text responses from the AI into audio. While specific implementation details depend on the AI provider's capabilities, a generic approach would involve creating a text-to-speech instance and utilizing it:
|
||||
### Vision Processing
|
||||
|
||||
For providers that support vision tasks (OpenAI, Ollama, and Anthropic):
|
||||
|
||||
```typescript
|
||||
// This is a hypothetical function call as the implementation might vary
|
||||
const tts = await TTS.createWithOpenAi(smartAi);
|
||||
// Using OpenAI's GPT-4 Vision
|
||||
const description = await smartAi.openaiProvider.vision({
|
||||
image: imageBuffer, // Buffer containing the image data
|
||||
prompt: 'What do you see in this image?'
|
||||
});
|
||||
|
||||
// The TTS instance would then be used to convert text to speech
|
||||
// Using Ollama's Llava model
|
||||
const analysis = await smartAi.ollamaProvider.vision({
|
||||
image: imageBuffer,
|
||||
prompt: 'Analyze this image in detail'
|
||||
});
|
||||
|
||||
// Using Anthropic's Claude 3
|
||||
const anthropicAnalysis = await smartAi.anthropicProvider.vision({
|
||||
image: imageBuffer,
|
||||
prompt: 'Please analyze this image and describe what you see'
|
||||
});
|
||||
```
|
||||
|
||||
### Extensive Feature Set
|
||||
## Error Handling
|
||||
|
||||
`@push.rocks/smartai` provides comprehensive support for interacting with various AI models, not limited to text chat. It encompasses audio responses, potentially incorporating AI-powered analyses, and other multi-modal interactions.
|
||||
|
||||
Refer to the specific AI providers’ documentation through `@push.rocks/smartai`, such as OpenAI and Anthropic, for detailed guidance on utilizing the full spectrum of capabilities, including the implementation of custom conversation flows, handling streaming data efficiently, and generating audio responses from AI conversations.
|
||||
|
||||
### Conclusion
|
||||
|
||||
Equipped with `@push.rocks/smartai`, developers can streamline the integration of sophisticated AI interactions into their applications. The package facilitates robust communication with AI models, supporting diverse operations from simple chats to complex audio feedback mechanisms, all within a unified, easy-to-use interface.
|
||||
|
||||
Explore the package more to uncover its full potential in creating engaging, AI-enhanced interactions in your applications.
|
||||
All providers implement proper error handling. It's recommended to wrap API calls in try-catch blocks:
|
||||
|
||||
```typescript
|
||||
try {
|
||||
const response = await smartAi.openaiProvider.chat({
|
||||
systemMessage: 'You are a helpful assistant.',
|
||||
userMessage: 'Hello!',
|
||||
messageHistory: []
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('AI provider error:', error.message);
|
||||
}
|
||||
```
|
||||
|
||||
## License and Legal Information
|
||||
|
||||
|
||||
71
test/test.ts
71
test/test.ts
@ -1,5 +1,7 @@
|
||||
import { expect, expectAsync, tap } from '@push.rocks/tapbundle';
|
||||
import * as qenv from '@push.rocks/qenv';
|
||||
import * as smartrequest from '@push.rocks/smartrequest';
|
||||
import * as smartfile from '@push.rocks/smartfile';
|
||||
|
||||
const testQenv = new qenv.Qenv('./', './.nogit/');
|
||||
|
||||
@ -10,8 +12,73 @@ let testSmartai: smartai.SmartAi;
|
||||
tap.test('should create a smartai instance', async () => {
|
||||
testSmartai = new smartai.SmartAi({
|
||||
openaiToken: await testQenv.getEnvVarOnDemand('OPENAI_TOKEN'),
|
||||
|
||||
});
|
||||
await testSmartai.start();
|
||||
});
|
||||
|
||||
tap.test('should create chat response with openai', async () => {
|
||||
const userMessage = 'How are you?';
|
||||
const response = await testSmartai.openaiProvider.chat({
|
||||
systemMessage: 'Hello',
|
||||
userMessage: userMessage,
|
||||
messageHistory: [
|
||||
],
|
||||
});
|
||||
console.log(`userMessage: ${userMessage}`);
|
||||
console.log(response.message);
|
||||
});
|
||||
|
||||
tap.test('should document a pdf', async () => {
|
||||
const pdfUrl = 'https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf';
|
||||
const pdfResponse = await smartrequest.getBinary(pdfUrl);
|
||||
const result = await testSmartai.openaiProvider.document({
|
||||
systemMessage: 'Classify the document. Only the following answers are allowed: "invoice", "bank account statement", "contract", "other". The answer should only contain the keyword for machine use.',
|
||||
userMessage: "Classify the document.",
|
||||
messageHistory: [],
|
||||
pdfDocuments: [pdfResponse.body],
|
||||
});
|
||||
console.log(result);
|
||||
});
|
||||
|
||||
tap.test('should recognize companies in a pdf', async () => {
|
||||
const pdfBuffer = await smartfile.fs.toBuffer('./.nogit/demo_without_textlayer.pdf');
|
||||
const result = await testSmartai.openaiProvider.document({
|
||||
systemMessage: `
|
||||
summarize the document.
|
||||
|
||||
answer in JSON format, adhering to the following schema:
|
||||
\`\`\`typescript
|
||||
type TAnswer = {
|
||||
entitySender: {
|
||||
type: 'official state entity' | 'company' | 'person';
|
||||
name: string;
|
||||
address: string;
|
||||
city: string;
|
||||
country: string;
|
||||
EU: boolean; // wether the entity is within EU
|
||||
};
|
||||
entityReceiver: {
|
||||
type: 'official state entity' | 'company' | 'person';
|
||||
name: string;
|
||||
address: string;
|
||||
city: string;
|
||||
country: string;
|
||||
EU: boolean; // wether the entity is within EU
|
||||
};
|
||||
date: string; // the date of the document as YYYY-MM-DD
|
||||
title: string; // a short title, suitable for a filename
|
||||
}
|
||||
\`\`\`
|
||||
`,
|
||||
userMessage: "Classify the document.",
|
||||
messageHistory: [],
|
||||
pdfDocuments: [pdfBuffer],
|
||||
});
|
||||
console.log(result);
|
||||
})
|
||||
|
||||
tap.start()
|
||||
tap.test('should stop the smartai instance', async () => {
|
||||
await testSmartai.stop();
|
||||
});
|
||||
|
||||
export default tap.start();
|
||||
|
||||
@ -1,8 +1,8 @@
|
||||
/**
|
||||
* autocreated commitinfo by @pushrocks/commitinfo
|
||||
* autocreated commitinfo by @push.rocks/commitinfo
|
||||
*/
|
||||
export const commitinfo = {
|
||||
name: '@push.rocks/smartai',
|
||||
version: '0.0.10',
|
||||
description: 'Provides a standardized interface for integrating and conversing with multiple AI models, supporting operations like chat and potentially audio responses.'
|
||||
version: '0.3.0',
|
||||
description: 'A TypeScript library for integrating and interacting with multiple AI models, offering capabilities for chat and potentially audio responses.'
|
||||
}
|
||||
|
||||
@ -1,29 +1,86 @@
|
||||
/**
|
||||
* Message format for chat interactions
|
||||
*/
|
||||
export interface ChatMessage {
|
||||
role: 'assistant' | 'user' | 'system';
|
||||
content: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* Options for chat interactions
|
||||
*/
|
||||
export interface ChatOptions {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
messageHistory: ChatMessage[];
|
||||
}
|
||||
|
||||
/**
|
||||
* Response format for chat interactions
|
||||
*/
|
||||
export interface ChatResponse {
|
||||
role: 'assistant';
|
||||
message: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* Abstract base class for multi-modal AI models.
|
||||
* Provides a common interface for different AI providers (OpenAI, Anthropic, Perplexity, Ollama)
|
||||
*/
|
||||
export abstract class MultiModalModel {
|
||||
/**
|
||||
* starts the model
|
||||
* Initializes the model and any necessary resources
|
||||
* Should be called before using any other methods
|
||||
*/
|
||||
abstract start(): Promise<void>;
|
||||
|
||||
/**
|
||||
* stops the model
|
||||
* Cleans up any resources used by the model
|
||||
* Should be called when the model is no longer needed
|
||||
*/
|
||||
abstract stop(): Promise<void>;
|
||||
|
||||
public abstract chat(optionsArg: {
|
||||
systemMessage: string,
|
||||
userMessage: string,
|
||||
messageHistory: {
|
||||
role: 'assistant' | 'user';
|
||||
content: string;
|
||||
}[]
|
||||
}): Promise<{}>
|
||||
/**
|
||||
* Synchronous chat interaction with the model
|
||||
* @param optionsArg Options containing system message, user message, and message history
|
||||
* @returns Promise resolving to the assistant's response
|
||||
*/
|
||||
public abstract chat(optionsArg: ChatOptions): Promise<ChatResponse>;
|
||||
|
||||
/**
|
||||
* Defines a streaming interface for chat interactions.
|
||||
* The implementation will vary based on the specific AI model.
|
||||
* @param input
|
||||
* Streaming interface for chat interactions
|
||||
* Allows for real-time responses from the model
|
||||
* @param input Stream of user messages
|
||||
* @returns Stream of model responses
|
||||
*/
|
||||
public abstract chatStream(input: ReadableStream<string>): Promise<ReadableStream<string>>;
|
||||
public abstract chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>>;
|
||||
|
||||
/**
|
||||
* Text-to-speech conversion
|
||||
* @param optionsArg Options containing the message to convert to speech
|
||||
* @returns Promise resolving to a readable stream of audio data
|
||||
* @throws Error if the provider doesn't support audio generation
|
||||
*/
|
||||
public abstract audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream>;
|
||||
|
||||
/**
|
||||
* Vision-language processing
|
||||
* @param optionsArg Options containing the image and prompt for analysis
|
||||
* @returns Promise resolving to the model's description or analysis of the image
|
||||
* @throws Error if the provider doesn't support vision tasks
|
||||
*/
|
||||
public abstract vision(optionsArg: { image: Buffer; prompt: string }): Promise<string>;
|
||||
|
||||
/**
|
||||
* Document analysis and processing
|
||||
* @param optionsArg Options containing system message, user message, PDF documents, and message history
|
||||
* @returns Promise resolving to the model's analysis of the documents
|
||||
* @throws Error if the provider doesn't support document processing
|
||||
*/
|
||||
public abstract document(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
pdfDocuments: Uint8Array[];
|
||||
messageHistory: ChatMessage[];
|
||||
}): Promise<{ message: any }>;
|
||||
}
|
||||
|
||||
@ -12,9 +12,11 @@ export interface IConversationOptions {
|
||||
*/
|
||||
export class Conversation {
|
||||
// STATIC
|
||||
public static async createWithOpenAi(smartaiRef: SmartAi) {
|
||||
const openaiProvider = new OpenAiProvider(smartaiRef.options.openaiToken);
|
||||
const conversation = new Conversation(smartaiRef, {
|
||||
public static async createWithOpenAi(smartaiRefArg: SmartAi) {
|
||||
if (!smartaiRefArg.openaiProvider) {
|
||||
throw new Error('OpenAI provider not available');
|
||||
}
|
||||
const conversation = new Conversation(smartaiRefArg, {
|
||||
processFunction: async (input) => {
|
||||
return '' // TODO implement proper streaming
|
||||
}
|
||||
@ -22,9 +24,11 @@ export class Conversation {
|
||||
return conversation;
|
||||
}
|
||||
|
||||
public static async createWithAnthropic(smartaiRef: SmartAi) {
|
||||
const anthropicProvider = new OpenAiProvider(smartaiRef.options.anthropicToken);
|
||||
const conversation = new Conversation(smartaiRef, {
|
||||
public static async createWithAnthropic(smartaiRefArg: SmartAi) {
|
||||
if (!smartaiRefArg.anthropicProvider) {
|
||||
throw new Error('Anthropic provider not available');
|
||||
}
|
||||
const conversation = new Conversation(smartaiRefArg, {
|
||||
processFunction: async (input) => {
|
||||
return '' // TODO implement proper streaming
|
||||
}
|
||||
@ -32,6 +36,29 @@ export class Conversation {
|
||||
return conversation;
|
||||
}
|
||||
|
||||
public static async createWithPerplexity(smartaiRefArg: SmartAi) {
|
||||
if (!smartaiRefArg.perplexityProvider) {
|
||||
throw new Error('Perplexity provider not available');
|
||||
}
|
||||
const conversation = new Conversation(smartaiRefArg, {
|
||||
processFunction: async (input) => {
|
||||
return '' // TODO implement proper streaming
|
||||
}
|
||||
});
|
||||
return conversation;
|
||||
}
|
||||
|
||||
public static async createWithOllama(smartaiRefArg: SmartAi) {
|
||||
if (!smartaiRefArg.ollamaProvider) {
|
||||
throw new Error('Ollama provider not available');
|
||||
}
|
||||
const conversation = new Conversation(smartaiRefArg, {
|
||||
processFunction: async (input) => {
|
||||
return '' // TODO implement proper streaming
|
||||
}
|
||||
});
|
||||
return conversation;
|
||||
}
|
||||
|
||||
// INSTANCE
|
||||
smartaiRef: SmartAi
|
||||
@ -44,8 +71,8 @@ export class Conversation {
|
||||
this.processFunction = options.processFunction;
|
||||
}
|
||||
|
||||
setSystemMessage(systemMessage: string) {
|
||||
this.systemMessage = systemMessage;
|
||||
public async setSystemMessage(systemMessageArg: string) {
|
||||
this.systemMessage = systemMessageArg;
|
||||
}
|
||||
|
||||
private setupOutputStream(): ReadableStream<string> {
|
||||
@ -57,7 +84,7 @@ export class Conversation {
|
||||
}
|
||||
|
||||
private setupInputStream(): WritableStream<string> {
|
||||
return new WritableStream<string>({
|
||||
const writableStream = new WritableStream<string>({
|
||||
write: async (chunk) => {
|
||||
const processedData = await this.processFunction(chunk);
|
||||
if (this.outputStreamController) {
|
||||
@ -72,6 +99,7 @@ export class Conversation {
|
||||
this.outputStreamController?.error(err);
|
||||
}
|
||||
});
|
||||
return writableStream;
|
||||
}
|
||||
|
||||
public getInputStreamWriter(): WritableStreamDefaultWriter<string> {
|
||||
|
||||
@ -1,8 +1,8 @@
|
||||
import { Conversation } from './classes.conversation.js';
|
||||
import * as plugins from './plugins.js';
|
||||
import type { AnthropicProvider } from './provider.anthropic.js';
|
||||
import { AnthropicProvider } from './provider.anthropic.js';
|
||||
import type { OllamaProvider } from './provider.ollama.js';
|
||||
import type { OpenAiProvider } from './provider.openai.js';
|
||||
import { OpenAiProvider } from './provider.openai.js';
|
||||
import type { PerplexityProvider } from './provider.perplexity.js';
|
||||
|
||||
|
||||
@ -10,9 +10,10 @@ export interface ISmartAiOptions {
|
||||
openaiToken?: string;
|
||||
anthropicToken?: string;
|
||||
perplexityToken?: string;
|
||||
exposeCredentials?: plugins.smartexpose.ISmartExposeOptions;
|
||||
}
|
||||
|
||||
export type TProvider = 'openai' | 'anthropic' | 'perplexity' | 'ollama';
|
||||
|
||||
export class SmartAi {
|
||||
public options: ISmartAiOptions;
|
||||
|
||||
@ -26,22 +27,36 @@ export class SmartAi {
|
||||
}
|
||||
|
||||
public async start() {
|
||||
|
||||
if (this.options.openaiToken) {
|
||||
this.openaiProvider = new OpenAiProvider({
|
||||
openaiToken: this.options.openaiToken,
|
||||
});
|
||||
await this.openaiProvider.start();
|
||||
}
|
||||
if (this.options.anthropicToken) {
|
||||
this.anthropicProvider = new AnthropicProvider({
|
||||
anthropicToken: this.options.anthropicToken,
|
||||
});
|
||||
}
|
||||
}
|
||||
|
||||
public async stop() {}
|
||||
|
||||
/**
|
||||
* creates an OpenAI conversation
|
||||
* create a new conversation
|
||||
*/
|
||||
public async createOpenApiConversation() {
|
||||
const conversation = await Conversation.createWithOpenAi(this);
|
||||
createConversation(provider: TProvider) {
|
||||
switch (provider) {
|
||||
case 'openai':
|
||||
return Conversation.createWithOpenAi(this);
|
||||
case 'anthropic':
|
||||
return Conversation.createWithAnthropic(this);
|
||||
case 'perplexity':
|
||||
return Conversation.createWithPerplexity(this);
|
||||
case 'ollama':
|
||||
return Conversation.createWithOllama(this);
|
||||
default:
|
||||
throw new Error('Provider not available');
|
||||
}
|
||||
|
||||
/**
|
||||
* creates an OpenAI conversation
|
||||
*/
|
||||
public async createAnthropicConversation() {
|
||||
const conversation = await Conversation.createWithAnthropic(this);
|
||||
}
|
||||
}
|
||||
@ -7,18 +7,22 @@ export {
|
||||
|
||||
// @push.rocks scope
|
||||
import * as qenv from '@push.rocks/qenv';
|
||||
import * as smartexpose from '@push.rocks/smartexpose';
|
||||
import * as smartpath from '@push.rocks/smartpath';
|
||||
import * as smartpromise from '@push.rocks/smartpromise';
|
||||
import * as smartarray from '@push.rocks/smartarray';
|
||||
import * as smartfile from '@push.rocks/smartfile';
|
||||
import * as smartpath from '@push.rocks/smartpath';
|
||||
import * as smartpdf from '@push.rocks/smartpdf';
|
||||
import * as smartpromise from '@push.rocks/smartpromise';
|
||||
import * as smartrequest from '@push.rocks/smartrequest';
|
||||
import * as webstream from '@push.rocks/webstream';
|
||||
|
||||
export {
|
||||
smartarray,
|
||||
qenv,
|
||||
smartexpose,
|
||||
smartpath,
|
||||
smartpromise,
|
||||
smartfile,
|
||||
smartpath,
|
||||
smartpdf,
|
||||
smartpromise,
|
||||
smartrequest,
|
||||
webstream,
|
||||
}
|
||||
|
||||
|
||||
@ -1,75 +1,240 @@
|
||||
import * as plugins from './plugins.js';
|
||||
import * as paths from './paths.js';
|
||||
import { MultiModalModel } from './abstract.classes.multimodal.js';
|
||||
import type { ChatOptions, ChatResponse, ChatMessage } from './abstract.classes.multimodal.js';
|
||||
import type { ImageBlockParam, TextBlockParam } from '@anthropic-ai/sdk/resources/messages';
|
||||
|
||||
type ContentBlock = ImageBlockParam | TextBlockParam;
|
||||
|
||||
export interface IAnthropicProviderOptions {
|
||||
anthropicToken: string;
|
||||
}
|
||||
|
||||
export class AnthropicProvider extends MultiModalModel {
|
||||
private anthropicToken: string;
|
||||
private options: IAnthropicProviderOptions;
|
||||
public anthropicApiClient: plugins.anthropic.default;
|
||||
|
||||
constructor(anthropicToken: string) {
|
||||
constructor(optionsArg: IAnthropicProviderOptions) {
|
||||
super();
|
||||
this.anthropicToken = anthropicToken; // Ensure the token is stored
|
||||
this.options = optionsArg // Ensure the token is stored
|
||||
}
|
||||
|
||||
async start() {
|
||||
this.anthropicApiClient = new plugins.anthropic.default({
|
||||
apiKey: this.anthropicToken,
|
||||
apiKey: this.options.anthropicToken,
|
||||
});
|
||||
}
|
||||
|
||||
async stop() {}
|
||||
|
||||
chatStream(input: ReadableStream<string>): ReadableStream<string> {
|
||||
public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
|
||||
// Create a TextDecoder to handle incoming chunks
|
||||
const decoder = new TextDecoder();
|
||||
let messageHistory: { role: 'assistant' | 'user'; content: string }[] = [];
|
||||
let buffer = '';
|
||||
let currentMessage: { role: string; content: string; } | null = null;
|
||||
|
||||
return new ReadableStream({
|
||||
async start(controller) {
|
||||
const reader = input.getReader();
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
while (true) {
|
||||
const newlineIndex = buffer.indexOf('\n');
|
||||
if (newlineIndex === -1) break;
|
||||
|
||||
const line = buffer.slice(0, newlineIndex);
|
||||
buffer = buffer.slice(newlineIndex + 1);
|
||||
|
||||
if (line.trim()) {
|
||||
try {
|
||||
let done, value;
|
||||
while ((({ done, value } = await reader.read()), !done)) {
|
||||
const userMessage = decoder.decode(value, { stream: true });
|
||||
messageHistory.push({ role: 'user', content: userMessage });
|
||||
const aiResponse = await this.chat('', userMessage, messageHistory);
|
||||
messageHistory.push({ role: 'assistant', content: aiResponse.message });
|
||||
// Directly enqueue the string response instead of encoding it first
|
||||
controller.enqueue(aiResponse.message);
|
||||
const message = JSON.parse(line);
|
||||
currentMessage = {
|
||||
role: message.role || 'user',
|
||||
content: message.content || '',
|
||||
};
|
||||
} catch (e) {
|
||||
console.error('Failed to parse message:', e);
|
||||
}
|
||||
controller.close();
|
||||
} catch (err) {
|
||||
controller.error(err);
|
||||
}
|
||||
}
|
||||
|
||||
// If we have a complete message, send it to Anthropic
|
||||
if (currentMessage) {
|
||||
const stream = await this.anthropicApiClient.messages.create({
|
||||
model: 'claude-3-opus-20240229',
|
||||
messages: [{ role: currentMessage.role, content: currentMessage.content }],
|
||||
system: '',
|
||||
stream: true,
|
||||
max_tokens: 4000,
|
||||
});
|
||||
|
||||
// Process each chunk from Anthropic
|
||||
for await (const chunk of stream) {
|
||||
const content = chunk.delta?.text;
|
||||
if (content) {
|
||||
controller.enqueue(content);
|
||||
}
|
||||
}
|
||||
|
||||
currentMessage = null;
|
||||
}
|
||||
},
|
||||
|
||||
flush(controller) {
|
||||
if (buffer) {
|
||||
try {
|
||||
const message = JSON.parse(buffer);
|
||||
controller.enqueue(message.content || '');
|
||||
} catch (e) {
|
||||
console.error('Failed to parse remaining buffer:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Connect the input to our transform stream
|
||||
return input.pipeThrough(transform);
|
||||
}
|
||||
|
||||
// Implementing the synchronous chat interaction
|
||||
public async chat(
|
||||
systemMessage: string,
|
||||
userMessage: string,
|
||||
messageHistory: {
|
||||
role: 'assistant' | 'user';
|
||||
content: string;
|
||||
}[]
|
||||
) {
|
||||
public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
|
||||
// Convert message history to Anthropic format
|
||||
const messages = optionsArg.messageHistory.map(msg => ({
|
||||
role: msg.role === 'assistant' ? 'assistant' as const : 'user' as const,
|
||||
content: msg.content
|
||||
}));
|
||||
|
||||
const result = await this.anthropicApiClient.messages.create({
|
||||
model: 'claude-3-opus-20240229',
|
||||
system: systemMessage,
|
||||
system: optionsArg.systemMessage,
|
||||
messages: [
|
||||
...messageHistory,
|
||||
{ role: 'user', content: userMessage },
|
||||
...messages,
|
||||
{ role: 'user' as const, content: optionsArg.userMessage }
|
||||
],
|
||||
max_tokens: 4000,
|
||||
});
|
||||
|
||||
// Extract text content from the response
|
||||
let message = '';
|
||||
for (const block of result.content) {
|
||||
if ('text' in block) {
|
||||
message += block.text;
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
message: result.content,
|
||||
role: 'assistant' as const,
|
||||
message,
|
||||
};
|
||||
}
|
||||
|
||||
public async audio(messageArg: string) {
|
||||
public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
|
||||
// Anthropic does not provide an audio API, so this method is not implemented.
|
||||
throw new Error('Audio generation is not supported by Anthropic.');
|
||||
throw new Error('Audio generation is not yet supported by Anthropic.');
|
||||
}
|
||||
|
||||
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
|
||||
const base64Image = optionsArg.image.toString('base64');
|
||||
|
||||
const content: ContentBlock[] = [
|
||||
{
|
||||
type: 'text',
|
||||
text: optionsArg.prompt
|
||||
},
|
||||
{
|
||||
type: 'image',
|
||||
source: {
|
||||
type: 'base64',
|
||||
media_type: 'image/jpeg',
|
||||
data: base64Image
|
||||
}
|
||||
}
|
||||
];
|
||||
|
||||
const result = await this.anthropicApiClient.messages.create({
|
||||
model: 'claude-3-opus-20240229',
|
||||
messages: [{
|
||||
role: 'user',
|
||||
content
|
||||
}],
|
||||
max_tokens: 1024
|
||||
});
|
||||
|
||||
// Extract text content from the response
|
||||
let message = '';
|
||||
for (const block of result.content) {
|
||||
if ('text' in block) {
|
||||
message += block.text;
|
||||
}
|
||||
}
|
||||
return message;
|
||||
}
|
||||
|
||||
public async document(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
pdfDocuments: Uint8Array[];
|
||||
messageHistory: ChatMessage[];
|
||||
}): Promise<{ message: any }> {
|
||||
// Convert PDF documents to images using SmartPDF
|
||||
const smartpdfInstance = new plugins.smartpdf.SmartPdf();
|
||||
let documentImageBytesArray: Uint8Array[] = [];
|
||||
|
||||
for (const pdfDocument of optionsArg.pdfDocuments) {
|
||||
const documentImageArray = await smartpdfInstance.convertPDFToPngBytes(pdfDocument);
|
||||
documentImageBytesArray = documentImageBytesArray.concat(documentImageArray);
|
||||
}
|
||||
|
||||
// Convert message history to Anthropic format
|
||||
const messages = optionsArg.messageHistory.map(msg => ({
|
||||
role: msg.role === 'assistant' ? 'assistant' as const : 'user' as const,
|
||||
content: msg.content
|
||||
}));
|
||||
|
||||
// Create content array with text and images
|
||||
const content: ContentBlock[] = [
|
||||
{
|
||||
type: 'text',
|
||||
text: optionsArg.userMessage
|
||||
}
|
||||
];
|
||||
|
||||
// Add each document page as an image
|
||||
for (const imageBytes of documentImageBytesArray) {
|
||||
content.push({
|
||||
type: 'image',
|
||||
source: {
|
||||
type: 'base64',
|
||||
media_type: 'image/jpeg',
|
||||
data: Buffer.from(imageBytes).toString('base64')
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
const result = await this.anthropicApiClient.messages.create({
|
||||
model: 'claude-3-opus-20240229',
|
||||
system: optionsArg.systemMessage,
|
||||
messages: [
|
||||
...messages,
|
||||
{ role: 'user', content }
|
||||
],
|
||||
max_tokens: 4096
|
||||
});
|
||||
|
||||
// Extract text content from the response
|
||||
let message = '';
|
||||
for (const block of result.content) {
|
||||
if ('text' in block) {
|
||||
message += block.text;
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
message: {
|
||||
role: 'assistant',
|
||||
content: message
|
||||
}
|
||||
};
|
||||
}
|
||||
}
|
||||
192
ts/provider.groq.ts
Normal file
192
ts/provider.groq.ts
Normal file
@ -0,0 +1,192 @@
|
||||
import * as plugins from './plugins.js';
|
||||
import * as paths from './paths.js';
|
||||
import { MultiModalModel } from './abstract.classes.multimodal.js';
|
||||
import type { ChatOptions, ChatResponse, ChatMessage } from './abstract.classes.multimodal.js';
|
||||
|
||||
export interface IGroqProviderOptions {
|
||||
groqToken: string;
|
||||
model?: string;
|
||||
}
|
||||
|
||||
export class GroqProvider extends MultiModalModel {
|
||||
private options: IGroqProviderOptions;
|
||||
private baseUrl = 'https://api.groq.com/v1';
|
||||
|
||||
constructor(optionsArg: IGroqProviderOptions) {
|
||||
super();
|
||||
this.options = {
|
||||
...optionsArg,
|
||||
model: optionsArg.model || 'llama-3.3-70b-versatile', // Default model
|
||||
};
|
||||
}
|
||||
|
||||
async start() {}
|
||||
|
||||
async stop() {}
|
||||
|
||||
public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
|
||||
// Create a TextDecoder to handle incoming chunks
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = '';
|
||||
let currentMessage: { role: string; content: string; } | null = null;
|
||||
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
while (true) {
|
||||
const newlineIndex = buffer.indexOf('\n');
|
||||
if (newlineIndex === -1) break;
|
||||
|
||||
const line = buffer.slice(0, newlineIndex);
|
||||
buffer = buffer.slice(newlineIndex + 1);
|
||||
|
||||
if (line.trim()) {
|
||||
try {
|
||||
const message = JSON.parse(line);
|
||||
currentMessage = {
|
||||
role: message.role || 'user',
|
||||
content: message.content || '',
|
||||
};
|
||||
} catch (e) {
|
||||
console.error('Failed to parse message:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we have a complete message, send it to Groq
|
||||
if (currentMessage) {
|
||||
const response = await fetch(`${this.baseUrl}/chat/completions`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Authorization': `Bearer ${this.options.groqToken}`,
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: this.options.model,
|
||||
messages: [{ role: currentMessage.role, content: currentMessage.content }],
|
||||
stream: true,
|
||||
}),
|
||||
});
|
||||
|
||||
// Process each chunk from Groq
|
||||
const reader = response.body?.getReader();
|
||||
if (reader) {
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
const chunk = new TextDecoder().decode(value);
|
||||
const lines = chunk.split('\n');
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith('data: ')) {
|
||||
const data = line.slice(6);
|
||||
if (data === '[DONE]') break;
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(data);
|
||||
const content = parsed.choices[0]?.delta?.content;
|
||||
if (content) {
|
||||
controller.enqueue(content);
|
||||
}
|
||||
} catch (e) {
|
||||
console.error('Failed to parse SSE data:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
}
|
||||
}
|
||||
|
||||
currentMessage = null;
|
||||
}
|
||||
},
|
||||
|
||||
flush(controller) {
|
||||
if (buffer) {
|
||||
try {
|
||||
const message = JSON.parse(buffer);
|
||||
controller.enqueue(message.content || '');
|
||||
} catch (e) {
|
||||
console.error('Failed to parse remaining buffer:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Connect the input to our transform stream
|
||||
return input.pipeThrough(transform);
|
||||
}
|
||||
|
||||
// Implementing the synchronous chat interaction
|
||||
public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
|
||||
const messages = [
|
||||
// System message
|
||||
{
|
||||
role: 'system',
|
||||
content: optionsArg.systemMessage,
|
||||
},
|
||||
// Message history
|
||||
...optionsArg.messageHistory.map(msg => ({
|
||||
role: msg.role,
|
||||
content: msg.content,
|
||||
})),
|
||||
// User message
|
||||
{
|
||||
role: 'user',
|
||||
content: optionsArg.userMessage,
|
||||
},
|
||||
];
|
||||
|
||||
const response = await fetch(`${this.baseUrl}/chat/completions`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Authorization': `Bearer ${this.options.groqToken}`,
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: this.options.model,
|
||||
messages,
|
||||
temperature: 0.7,
|
||||
max_completion_tokens: 1024,
|
||||
stream: false,
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const error = await response.json();
|
||||
throw new Error(`Groq API error: ${error.message || response.statusText}`);
|
||||
}
|
||||
|
||||
const result = await response.json();
|
||||
|
||||
return {
|
||||
role: 'assistant',
|
||||
message: result.choices[0].message.content,
|
||||
};
|
||||
}
|
||||
|
||||
public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
|
||||
// Groq does not provide an audio API, so this method is not implemented.
|
||||
throw new Error('Audio generation is not yet supported by Groq.');
|
||||
}
|
||||
|
||||
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
|
||||
throw new Error('Vision tasks are not yet supported by Groq.');
|
||||
}
|
||||
|
||||
public async document(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
pdfDocuments: Uint8Array[];
|
||||
messageHistory: ChatMessage[];
|
||||
}): Promise<{ message: any }> {
|
||||
throw new Error('Document processing is not yet supported by Groq.');
|
||||
}
|
||||
}
|
||||
@ -1,3 +1,252 @@
|
||||
import * as plugins from './plugins.js';
|
||||
import * as paths from './paths.js';
|
||||
import { MultiModalModel } from './abstract.classes.multimodal.js';
|
||||
import type { ChatOptions, ChatResponse, ChatMessage } from './abstract.classes.multimodal.js';
|
||||
|
||||
export class OllamaProvider {}
|
||||
export interface IOllamaProviderOptions {
|
||||
baseUrl?: string;
|
||||
model?: string;
|
||||
visionModel?: string; // Model to use for vision tasks (e.g. 'llava')
|
||||
}
|
||||
|
||||
export class OllamaProvider extends MultiModalModel {
|
||||
private options: IOllamaProviderOptions;
|
||||
private baseUrl: string;
|
||||
private model: string;
|
||||
private visionModel: string;
|
||||
|
||||
constructor(optionsArg: IOllamaProviderOptions = {}) {
|
||||
super();
|
||||
this.options = optionsArg;
|
||||
this.baseUrl = optionsArg.baseUrl || 'http://localhost:11434';
|
||||
this.model = optionsArg.model || 'llama2';
|
||||
this.visionModel = optionsArg.visionModel || 'llava';
|
||||
}
|
||||
|
||||
async start() {
|
||||
// Verify Ollama is running
|
||||
try {
|
||||
const response = await fetch(`${this.baseUrl}/api/tags`);
|
||||
if (!response.ok) {
|
||||
throw new Error('Failed to connect to Ollama server');
|
||||
}
|
||||
} catch (error) {
|
||||
throw new Error(`Failed to connect to Ollama server at ${this.baseUrl}: ${error.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
async stop() {}
|
||||
|
||||
public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
|
||||
// Create a TextDecoder to handle incoming chunks
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = '';
|
||||
let currentMessage: { role: string; content: string; } | null = null;
|
||||
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
while (true) {
|
||||
const newlineIndex = buffer.indexOf('\n');
|
||||
if (newlineIndex === -1) break;
|
||||
|
||||
const line = buffer.slice(0, newlineIndex);
|
||||
buffer = buffer.slice(newlineIndex + 1);
|
||||
|
||||
if (line.trim()) {
|
||||
try {
|
||||
const message = JSON.parse(line);
|
||||
currentMessage = {
|
||||
role: message.role || 'user',
|
||||
content: message.content || '',
|
||||
};
|
||||
} catch (e) {
|
||||
console.error('Failed to parse message:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we have a complete message, send it to Ollama
|
||||
if (currentMessage) {
|
||||
const response = await fetch(`${this.baseUrl}/api/chat`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: this.model,
|
||||
messages: [{ role: currentMessage.role, content: currentMessage.content }],
|
||||
stream: true,
|
||||
}),
|
||||
});
|
||||
|
||||
// Process each chunk from Ollama
|
||||
const reader = response.body?.getReader();
|
||||
if (reader) {
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
const chunk = new TextDecoder().decode(value);
|
||||
const lines = chunk.split('\n');
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.trim()) {
|
||||
try {
|
||||
const parsed = JSON.parse(line);
|
||||
const content = parsed.message?.content;
|
||||
if (content) {
|
||||
controller.enqueue(content);
|
||||
}
|
||||
} catch (e) {
|
||||
console.error('Failed to parse Ollama response:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
}
|
||||
}
|
||||
|
||||
currentMessage = null;
|
||||
}
|
||||
},
|
||||
|
||||
flush(controller) {
|
||||
if (buffer) {
|
||||
try {
|
||||
const message = JSON.parse(buffer);
|
||||
controller.enqueue(message.content || '');
|
||||
} catch (e) {
|
||||
console.error('Failed to parse remaining buffer:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Connect the input to our transform stream
|
||||
return input.pipeThrough(transform);
|
||||
}
|
||||
|
||||
// Implementing the synchronous chat interaction
|
||||
public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
|
||||
// Format messages for Ollama
|
||||
const messages = [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
...optionsArg.messageHistory,
|
||||
{ role: 'user', content: optionsArg.userMessage }
|
||||
];
|
||||
|
||||
// Make API call to Ollama
|
||||
const response = await fetch(`${this.baseUrl}/api/chat`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: this.model,
|
||||
messages: messages,
|
||||
stream: false
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Ollama API error: ${response.statusText}`);
|
||||
}
|
||||
|
||||
const result = await response.json();
|
||||
|
||||
return {
|
||||
role: 'assistant' as const,
|
||||
message: result.message.content,
|
||||
};
|
||||
}
|
||||
|
||||
public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
|
||||
throw new Error('Audio generation is not supported by Ollama.');
|
||||
}
|
||||
|
||||
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
|
||||
const base64Image = optionsArg.image.toString('base64');
|
||||
|
||||
const response = await fetch(`${this.baseUrl}/api/chat`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: this.visionModel,
|
||||
messages: [{
|
||||
role: 'user',
|
||||
content: optionsArg.prompt,
|
||||
images: [base64Image]
|
||||
}],
|
||||
stream: false
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Ollama API error: ${response.statusText}`);
|
||||
}
|
||||
|
||||
const result = await response.json();
|
||||
return result.message.content;
|
||||
}
|
||||
|
||||
public async document(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
pdfDocuments: Uint8Array[];
|
||||
messageHistory: ChatMessage[];
|
||||
}): Promise<{ message: any }> {
|
||||
// Convert PDF documents to images using SmartPDF
|
||||
const smartpdfInstance = new plugins.smartpdf.SmartPdf();
|
||||
let documentImageBytesArray: Uint8Array[] = [];
|
||||
|
||||
for (const pdfDocument of optionsArg.pdfDocuments) {
|
||||
const documentImageArray = await smartpdfInstance.convertPDFToPngBytes(pdfDocument);
|
||||
documentImageBytesArray = documentImageBytesArray.concat(documentImageArray);
|
||||
}
|
||||
|
||||
// Convert images to base64
|
||||
const base64Images = documentImageBytesArray.map(bytes => Buffer.from(bytes).toString('base64'));
|
||||
|
||||
// Send request to Ollama with images
|
||||
const response = await fetch(`${this.baseUrl}/api/chat`, {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: this.visionModel,
|
||||
messages: [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
...optionsArg.messageHistory,
|
||||
{
|
||||
role: 'user',
|
||||
content: optionsArg.userMessage,
|
||||
images: base64Images
|
||||
}
|
||||
],
|
||||
stream: false
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Ollama API error: ${response.statusText}`);
|
||||
}
|
||||
|
||||
const result = await response.json();
|
||||
return {
|
||||
message: {
|
||||
role: 'assistant',
|
||||
content: result.message.content
|
||||
}
|
||||
};
|
||||
}
|
||||
}
|
||||
@ -3,45 +3,109 @@ import * as paths from './paths.js';
|
||||
|
||||
import { MultiModalModel } from './abstract.classes.multimodal.js';
|
||||
|
||||
export class OpenAiProvider extends MultiModalModel {
|
||||
public smartexposeInstance: plugins.smartexpose.SmartExpose;
|
||||
private openAiToken: string;
|
||||
public openAiApiClient: plugins.openai.default;
|
||||
export interface IOpenaiProviderOptions {
|
||||
openaiToken: string;
|
||||
}
|
||||
|
||||
constructor(openaiToken: string, expose) {
|
||||
export class OpenAiProvider extends MultiModalModel {
|
||||
private options: IOpenaiProviderOptions;
|
||||
public openAiApiClient: plugins.openai.default;
|
||||
public smartpdfInstance: plugins.smartpdf.SmartPdf;
|
||||
|
||||
constructor(optionsArg: IOpenaiProviderOptions) {
|
||||
super();
|
||||
this.openAiToken = openaiToken; // Ensure the token is stored
|
||||
this.options = optionsArg;
|
||||
}
|
||||
|
||||
async start() {
|
||||
public async start() {
|
||||
this.openAiApiClient = new plugins.openai.default({
|
||||
apiKey: this.openAiToken,
|
||||
apiKey: this.options.openaiToken,
|
||||
dangerouslyAllowBrowser: true,
|
||||
});
|
||||
this.smartpdfInstance = new plugins.smartpdf.SmartPdf();
|
||||
}
|
||||
|
||||
async stop() {}
|
||||
public async stop() {}
|
||||
|
||||
public async chatStream(input: ReadableStream<string>): Promise<ReadableStream<string>> {
|
||||
// TODO: implement for OpenAI
|
||||
public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
|
||||
// Create a TextDecoder to handle incoming chunks
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = '';
|
||||
let currentMessage: { role: string; content: string; } | null = null;
|
||||
|
||||
const returnStream = new ReadableStream();
|
||||
return returnStream;
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
while (true) {
|
||||
const newlineIndex = buffer.indexOf('\n');
|
||||
if (newlineIndex === -1) break;
|
||||
|
||||
const line = buffer.slice(0, newlineIndex);
|
||||
buffer = buffer.slice(newlineIndex + 1);
|
||||
|
||||
if (line.trim()) {
|
||||
try {
|
||||
const message = JSON.parse(line);
|
||||
currentMessage = {
|
||||
role: message.role || 'user',
|
||||
content: message.content || '',
|
||||
};
|
||||
} catch (e) {
|
||||
console.error('Failed to parse message:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we have a complete message, send it to OpenAI
|
||||
if (currentMessage) {
|
||||
const stream = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'gpt-4',
|
||||
messages: [{ role: currentMessage.role, content: currentMessage.content }],
|
||||
stream: true,
|
||||
});
|
||||
|
||||
// Process each chunk from OpenAI
|
||||
for await (const chunk of stream) {
|
||||
const content = chunk.choices[0]?.delta?.content;
|
||||
if (content) {
|
||||
controller.enqueue(content);
|
||||
}
|
||||
}
|
||||
|
||||
currentMessage = null;
|
||||
}
|
||||
},
|
||||
|
||||
flush(controller) {
|
||||
if (buffer) {
|
||||
try {
|
||||
const message = JSON.parse(buffer);
|
||||
controller.enqueue(message.content || '');
|
||||
} catch (e) {
|
||||
console.error('Failed to parse remaining buffer:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Connect the input to our transform stream
|
||||
return input.pipeThrough(transform);
|
||||
}
|
||||
|
||||
// Implementing the synchronous chat interaction
|
||||
public async chat(
|
||||
optionsArg: {
|
||||
systemMessage: string,
|
||||
userMessage: string,
|
||||
public async chat(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
messageHistory: {
|
||||
role: 'assistant' | 'user';
|
||||
content: string;
|
||||
}[]
|
||||
}
|
||||
) {
|
||||
}[];
|
||||
}) {
|
||||
const result = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'gpt-4-turbo-preview',
|
||||
model: 'gpt-4o',
|
||||
|
||||
messages: [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
@ -50,7 +114,8 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
],
|
||||
});
|
||||
return {
|
||||
message: result.choices[0].message,
|
||||
role: result.choices[0].message.role as 'assistant',
|
||||
message: result.choices[0].message.content,
|
||||
};
|
||||
}
|
||||
|
||||
@ -69,34 +134,85 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
}
|
||||
|
||||
public async document(optionsArg: {
|
||||
systemMessage: string,
|
||||
userMessage: string,
|
||||
documents: Uint8Array[],
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
pdfDocuments: Uint8Array[];
|
||||
messageHistory: {
|
||||
role: 'assistant' | 'user';
|
||||
content: any;
|
||||
}[];
|
||||
}) {
|
||||
const result = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'gpt-4-vision-preview',
|
||||
let pdfDocumentImageBytesArray: Uint8Array[] = [];
|
||||
|
||||
for (const pdfDocument of optionsArg.pdfDocuments) {
|
||||
const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument);
|
||||
pdfDocumentImageBytesArray = pdfDocumentImageBytesArray.concat(documentImageArray);
|
||||
}
|
||||
|
||||
console.log(`image smartfile array`);
|
||||
console.log(pdfDocumentImageBytesArray.map((smartfile) => smartfile.length));
|
||||
|
||||
const smartfileArray = await plugins.smartarray.map(
|
||||
pdfDocumentImageBytesArray,
|
||||
async (pdfDocumentImageBytes) => {
|
||||
return plugins.smartfile.SmartFile.fromBuffer(
|
||||
'pdfDocumentImage.jpg',
|
||||
Buffer.from(pdfDocumentImageBytes)
|
||||
);
|
||||
}
|
||||
);
|
||||
|
||||
const result = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'gpt-4o',
|
||||
// response_format: { type: "json_object" }, // not supported for now
|
||||
messages: [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
...optionsArg.messageHistory,
|
||||
{ role: 'user', content: [
|
||||
{type: 'text', text: optionsArg.userMessage},
|
||||
{
|
||||
role: 'user',
|
||||
content: [
|
||||
{ type: 'text', text: optionsArg.userMessage },
|
||||
...(() => {
|
||||
const returnArray = [];
|
||||
for (const document of optionsArg.documents) {
|
||||
returnArray.push({type: 'image_url', image_url: })
|
||||
for (const imageBytes of pdfDocumentImageBytesArray) {
|
||||
returnArray.push({
|
||||
type: 'image_url',
|
||||
image_url: {
|
||||
url: 'data:image/png;base64,' + Buffer.from(imageBytes).toString('base64'),
|
||||
},
|
||||
});
|
||||
}
|
||||
return returnArray;
|
||||
})()
|
||||
] },
|
||||
})(),
|
||||
],
|
||||
},
|
||||
],
|
||||
});
|
||||
return {
|
||||
message: result.choices[0].message,
|
||||
};
|
||||
}
|
||||
|
||||
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
|
||||
const result = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'gpt-4-vision-preview',
|
||||
messages: [
|
||||
{
|
||||
role: 'user',
|
||||
content: [
|
||||
{ type: 'text', text: optionsArg.prompt },
|
||||
{
|
||||
type: 'image_url',
|
||||
image_url: {
|
||||
url: `data:image/jpeg;base64,${optionsArg.image.toString('base64')}`
|
||||
}
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
max_tokens: 300
|
||||
});
|
||||
|
||||
return result.choices[0].message.content || '';
|
||||
}
|
||||
}
|
||||
|
||||
@ -1,3 +1,171 @@
|
||||
import * as plugins from './plugins.js';
|
||||
import * as paths from './paths.js';
|
||||
import { MultiModalModel } from './abstract.classes.multimodal.js';
|
||||
import type { ChatOptions, ChatResponse, ChatMessage } from './abstract.classes.multimodal.js';
|
||||
|
||||
export class PerplexityProvider {}
|
||||
export interface IPerplexityProviderOptions {
|
||||
perplexityToken: string;
|
||||
}
|
||||
|
||||
export class PerplexityProvider extends MultiModalModel {
|
||||
private options: IPerplexityProviderOptions;
|
||||
|
||||
constructor(optionsArg: IPerplexityProviderOptions) {
|
||||
super();
|
||||
this.options = optionsArg;
|
||||
}
|
||||
|
||||
async start() {
|
||||
// Initialize any necessary clients or resources
|
||||
}
|
||||
|
||||
async stop() {}
|
||||
|
||||
public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
|
||||
// Create a TextDecoder to handle incoming chunks
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = '';
|
||||
let currentMessage: { role: string; content: string; } | null = null;
|
||||
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
while (true) {
|
||||
const newlineIndex = buffer.indexOf('\n');
|
||||
if (newlineIndex === -1) break;
|
||||
|
||||
const line = buffer.slice(0, newlineIndex);
|
||||
buffer = buffer.slice(newlineIndex + 1);
|
||||
|
||||
if (line.trim()) {
|
||||
try {
|
||||
const message = JSON.parse(line);
|
||||
currentMessage = {
|
||||
role: message.role || 'user',
|
||||
content: message.content || '',
|
||||
};
|
||||
} catch (e) {
|
||||
console.error('Failed to parse message:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we have a complete message, send it to Perplexity
|
||||
if (currentMessage) {
|
||||
const response = await fetch('https://api.perplexity.ai/chat/completions', {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Authorization': `Bearer ${this.options.perplexityToken}`,
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: 'mixtral-8x7b-instruct',
|
||||
messages: [{ role: currentMessage.role, content: currentMessage.content }],
|
||||
stream: true,
|
||||
}),
|
||||
});
|
||||
|
||||
// Process each chunk from Perplexity
|
||||
const reader = response.body?.getReader();
|
||||
if (reader) {
|
||||
try {
|
||||
while (true) {
|
||||
const { done, value } = await reader.read();
|
||||
if (done) break;
|
||||
|
||||
const chunk = new TextDecoder().decode(value);
|
||||
const lines = chunk.split('\n');
|
||||
|
||||
for (const line of lines) {
|
||||
if (line.startsWith('data: ')) {
|
||||
const data = line.slice(6);
|
||||
if (data === '[DONE]') break;
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(data);
|
||||
const content = parsed.choices[0]?.delta?.content;
|
||||
if (content) {
|
||||
controller.enqueue(content);
|
||||
}
|
||||
} catch (e) {
|
||||
console.error('Failed to parse SSE data:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
} finally {
|
||||
reader.releaseLock();
|
||||
}
|
||||
}
|
||||
|
||||
currentMessage = null;
|
||||
}
|
||||
},
|
||||
|
||||
flush(controller) {
|
||||
if (buffer) {
|
||||
try {
|
||||
const message = JSON.parse(buffer);
|
||||
controller.enqueue(message.content || '');
|
||||
} catch (e) {
|
||||
console.error('Failed to parse remaining buffer:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Connect the input to our transform stream
|
||||
return input.pipeThrough(transform);
|
||||
}
|
||||
|
||||
// Implementing the synchronous chat interaction
|
||||
public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
|
||||
// Make API call to Perplexity
|
||||
const response = await fetch('https://api.perplexity.ai/chat/completions', {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
'Authorization': `Bearer ${this.options.perplexityToken}`,
|
||||
'Content-Type': 'application/json',
|
||||
},
|
||||
body: JSON.stringify({
|
||||
model: 'mixtral-8x7b-instruct', // Using Mixtral model
|
||||
messages: [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
...optionsArg.messageHistory,
|
||||
{ role: 'user', content: optionsArg.userMessage }
|
||||
],
|
||||
}),
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
throw new Error(`Perplexity API error: ${response.statusText}`);
|
||||
}
|
||||
|
||||
const result = await response.json();
|
||||
|
||||
return {
|
||||
role: 'assistant' as const,
|
||||
message: result.choices[0].message.content,
|
||||
};
|
||||
}
|
||||
|
||||
public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
|
||||
throw new Error('Audio generation is not supported by Perplexity.');
|
||||
}
|
||||
|
||||
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
|
||||
throw new Error('Vision tasks are not supported by Perplexity.');
|
||||
}
|
||||
|
||||
public async document(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
pdfDocuments: Uint8Array[];
|
||||
messageHistory: ChatMessage[];
|
||||
}): Promise<{ message: any }> {
|
||||
throw new Error('Document processing is not supported by Perplexity.');
|
||||
}
|
||||
}
|
||||
183
ts/provider.xai.ts
Normal file
183
ts/provider.xai.ts
Normal file
@ -0,0 +1,183 @@
|
||||
import * as plugins from './plugins.js';
|
||||
import * as paths from './paths.js';
|
||||
import { MultiModalModel } from './abstract.classes.multimodal.js';
|
||||
import type { ChatOptions, ChatResponse, ChatMessage } from './abstract.classes.multimodal.js';
|
||||
import type { ChatCompletionMessageParam } from 'openai/resources/chat/completions';
|
||||
|
||||
export interface IXAIProviderOptions {
|
||||
xaiToken: string;
|
||||
}
|
||||
|
||||
export class XAIProvider extends MultiModalModel {
|
||||
private options: IXAIProviderOptions;
|
||||
public openAiApiClient: plugins.openai.default;
|
||||
public smartpdfInstance: plugins.smartpdf.SmartPdf;
|
||||
|
||||
constructor(optionsArg: IXAIProviderOptions) {
|
||||
super();
|
||||
this.options = optionsArg;
|
||||
}
|
||||
|
||||
public async start() {
|
||||
this.openAiApiClient = new plugins.openai.default({
|
||||
apiKey: this.options.xaiToken,
|
||||
baseURL: 'https://api.x.ai/v1',
|
||||
});
|
||||
this.smartpdfInstance = new plugins.smartpdf.SmartPdf();
|
||||
}
|
||||
|
||||
public async stop() {}
|
||||
|
||||
public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
|
||||
// Create a TextDecoder to handle incoming chunks
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = '';
|
||||
let currentMessage: { role: string; content: string; } | null = null;
|
||||
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
while (true) {
|
||||
const newlineIndex = buffer.indexOf('\n');
|
||||
if (newlineIndex === -1) break;
|
||||
|
||||
const line = buffer.slice(0, newlineIndex);
|
||||
buffer = buffer.slice(newlineIndex + 1);
|
||||
|
||||
if (line.trim()) {
|
||||
try {
|
||||
const message = JSON.parse(line);
|
||||
currentMessage = {
|
||||
role: message.role || 'user',
|
||||
content: message.content || '',
|
||||
};
|
||||
} catch (e) {
|
||||
console.error('Failed to parse message:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// If we have a complete message, send it to X.AI
|
||||
if (currentMessage) {
|
||||
const stream = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'grok-2-latest',
|
||||
messages: [{ role: currentMessage.role, content: currentMessage.content }],
|
||||
stream: true,
|
||||
});
|
||||
|
||||
// Process each chunk from X.AI
|
||||
for await (const chunk of stream) {
|
||||
const content = chunk.choices[0]?.delta?.content;
|
||||
if (content) {
|
||||
controller.enqueue(content);
|
||||
}
|
||||
}
|
||||
|
||||
currentMessage = null;
|
||||
}
|
||||
},
|
||||
|
||||
flush(controller) {
|
||||
if (buffer) {
|
||||
try {
|
||||
const message = JSON.parse(buffer);
|
||||
controller.enqueue(message.content || '');
|
||||
} catch (e) {
|
||||
console.error('Failed to parse remaining buffer:', e);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
// Connect the input to our transform stream
|
||||
return input.pipeThrough(transform);
|
||||
}
|
||||
|
||||
public async chat(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
messageHistory: { role: string; content: string; }[];
|
||||
}): Promise<{ role: 'assistant'; message: string; }> {
|
||||
// Prepare messages array with system message, history, and user message
|
||||
const messages: ChatCompletionMessageParam[] = [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
...optionsArg.messageHistory.map(msg => ({
|
||||
role: msg.role as 'system' | 'user' | 'assistant',
|
||||
content: msg.content
|
||||
})),
|
||||
{ role: 'user', content: optionsArg.userMessage }
|
||||
];
|
||||
|
||||
// Call X.AI's chat completion API
|
||||
const completion = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'grok-2-latest',
|
||||
messages: messages,
|
||||
stream: false,
|
||||
});
|
||||
|
||||
// Return the assistant's response
|
||||
return {
|
||||
role: 'assistant',
|
||||
message: completion.choices[0]?.message?.content || ''
|
||||
};
|
||||
}
|
||||
|
||||
public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
|
||||
throw new Error('Audio generation is not supported by X.AI');
|
||||
}
|
||||
|
||||
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
|
||||
throw new Error('Vision tasks are not supported by X.AI');
|
||||
}
|
||||
|
||||
public async document(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
pdfDocuments: Uint8Array[];
|
||||
messageHistory: { role: string; content: string; }[];
|
||||
}): Promise<{ message: any }> {
|
||||
// First convert PDF documents to images
|
||||
let pdfDocumentImageBytesArray: Uint8Array[] = [];
|
||||
|
||||
for (const pdfDocument of optionsArg.pdfDocuments) {
|
||||
const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument);
|
||||
pdfDocumentImageBytesArray = pdfDocumentImageBytesArray.concat(documentImageArray);
|
||||
}
|
||||
|
||||
// Convert images to base64 for inclusion in the message
|
||||
const imageBase64Array = pdfDocumentImageBytesArray.map(bytes =>
|
||||
Buffer.from(bytes).toString('base64')
|
||||
);
|
||||
|
||||
// Combine document images into the user message
|
||||
const enhancedUserMessage = `
|
||||
${optionsArg.userMessage}
|
||||
|
||||
Document contents (as images):
|
||||
${imageBase64Array.map((img, i) => `Image ${i + 1}: <image data>`).join('\n')}
|
||||
`;
|
||||
|
||||
// Use chat completion to analyze the documents
|
||||
const messages: ChatCompletionMessageParam[] = [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
...optionsArg.messageHistory.map(msg => ({
|
||||
role: msg.role as 'system' | 'user' | 'assistant',
|
||||
content: msg.content
|
||||
})),
|
||||
{ role: 'user', content: enhancedUserMessage }
|
||||
];
|
||||
|
||||
const completion = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'grok-2-latest',
|
||||
messages: messages,
|
||||
stream: false,
|
||||
});
|
||||
|
||||
return {
|
||||
message: completion.choices[0]?.message?.content || ''
|
||||
};
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user