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88
changelog.md
88
changelog.md
@ -1,5 +1,93 @@
|
||||
# Changelog
|
||||
|
||||
## 2025-04-03 - 0.5.3 - fix(package.json)
|
||||
Add explicit packageManager field to package.json
|
||||
|
||||
- Include the packageManager property to specify the pnpm version and checksum.
|
||||
- Align package metadata with current standards.
|
||||
|
||||
## 2025-04-03 - 0.5.2 - fix(readme)
|
||||
Remove redundant conclusion section from README to streamline documentation.
|
||||
|
||||
- Eliminated the conclusion block describing SmartAi's capabilities and documentation pointers.
|
||||
|
||||
## 2025-02-25 - 0.5.1 - fix(OpenAiProvider)
|
||||
Corrected audio model ID in OpenAiProvider
|
||||
|
||||
- Fixed audio model identifier from 'o3-mini' to 'tts-1-hd' in the OpenAiProvider's audio method.
|
||||
- Addressed minor code formatting issues in test suite for better readability.
|
||||
- Corrected spelling errors in test documentation and comments.
|
||||
|
||||
## 2025-02-25 - 0.5.0 - feat(documentation and configuration)
|
||||
Enhanced package and README documentation
|
||||
|
||||
- Expanded the package description to better reflect the library's capabilities.
|
||||
- Improved README with detailed usage examples for initialization, chat interactions, streaming chat, audio generation, document analysis, and vision processing.
|
||||
- Provided error handling strategies and advanced streaming customization examples.
|
||||
|
||||
## 2025-02-25 - 0.4.2 - fix(core)
|
||||
Fix OpenAI chat streaming and PDF document processing logic.
|
||||
|
||||
- Updated OpenAI chat streaming to handle new async iterable format.
|
||||
- Improved PDF document processing by filtering out empty image buffers.
|
||||
- Removed unsupported temperature options from OpenAI requests.
|
||||
|
||||
## 2025-02-25 - 0.4.1 - fix(provider)
|
||||
Fix provider modules for consistency
|
||||
|
||||
- Updated TypeScript interfaces and options in provider modules for better type safety.
|
||||
- Modified transform stream handlers in Exo, Groq, and Ollama providers for consistency.
|
||||
- Added optional model options to OpenAI provider for custom model usage.
|
||||
|
||||
## 2025-02-08 - 0.4.0 - feat(core)
|
||||
Added support for Exo AI provider
|
||||
|
||||
- Introduced ExoProvider with chat functionalities.
|
||||
- Updated SmartAi class to initialize ExoProvider.
|
||||
- Extended Conversation class to support ExoProvider.
|
||||
|
||||
## 2025-02-05 - 0.3.3 - fix(documentation)
|
||||
Update readme with detailed license and legal information.
|
||||
|
||||
- Added explicit section on License and Legal Information in the README.
|
||||
- Clarified the use of trademarks and company information.
|
||||
|
||||
## 2025-02-05 - 0.3.2 - fix(documentation)
|
||||
Remove redundant badges from readme
|
||||
|
||||
- Removed Build Status badge from the readme file.
|
||||
- Removed License badge from the readme file.
|
||||
|
||||
## 2025-02-05 - 0.3.1 - fix(documentation)
|
||||
Updated README structure and added detailed usage examples
|
||||
|
||||
- Introduced a Table of Contents
|
||||
- Included comprehensive sections for chat, streaming chat, audio generation, document processing, and vision processing
|
||||
- Added example code and detailed configuration steps for supported AI providers
|
||||
- Clarified the development setup with instructions for running tests and building the project
|
||||
|
||||
## 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
|
||||
|
||||
|
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.
|
@ -5,20 +5,33 @@
|
||||
"githost": "code.foss.global",
|
||||
"gitscope": "push.rocks",
|
||||
"gitrepo": "smartai",
|
||||
"description": "A TypeScript library for integrating and interacting with multiple AI models, offering capabilities for chat and potentially audio responses.",
|
||||
"description": "SmartAi is a versatile TypeScript library designed to facilitate integration and interaction with various AI models, offering functionalities for chat, audio generation, document processing, and vision tasks.",
|
||||
"npmPackagename": "@push.rocks/smartai",
|
||||
"license": "MIT",
|
||||
"projectDomain": "push.rocks",
|
||||
"keywords": [
|
||||
"AI integration",
|
||||
"chatbot",
|
||||
"TypeScript",
|
||||
"chatbot",
|
||||
"OpenAI",
|
||||
"Anthropic",
|
||||
"multi-model support",
|
||||
"audio responses",
|
||||
"multi-model",
|
||||
"audio generation",
|
||||
"text-to-speech",
|
||||
"streaming chat"
|
||||
"document processing",
|
||||
"vision processing",
|
||||
"streaming chat",
|
||||
"API",
|
||||
"multiple providers",
|
||||
"AI models",
|
||||
"synchronous chat",
|
||||
"asynchronous chat",
|
||||
"real-time interaction",
|
||||
"content analysis",
|
||||
"image description",
|
||||
"document classification",
|
||||
"AI toolkit",
|
||||
"provider switching"
|
||||
]
|
||||
}
|
||||
},
|
||||
|
61
package.json
61
package.json
@ -1,8 +1,8 @@
|
||||
{
|
||||
"name": "@push.rocks/smartai",
|
||||
"version": "0.0.19",
|
||||
"version": "0.5.3",
|
||||
"private": false,
|
||||
"description": "A TypeScript library for integrating and interacting with multiple AI models, offering capabilities for chat and potentially audio responses.",
|
||||
"description": "SmartAi is a versatile TypeScript library designed to facilitate integration and interaction with various AI models, offering functionalities for chat, audio generation, document processing, and vision tasks.",
|
||||
"main": "dist_ts/index.js",
|
||||
"typings": "dist_ts/index.d.ts",
|
||||
"type": "module",
|
||||
@ -14,24 +14,24 @@
|
||||
"buildDocs": "(tsdoc)"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@git.zone/tsbuild": "^2.1.84",
|
||||
"@git.zone/tsbundle": "^2.0.5",
|
||||
"@git.zone/tsrun": "^1.2.49",
|
||||
"@git.zone/tstest": "^1.0.90",
|
||||
"@push.rocks/qenv": "^6.0.5",
|
||||
"@push.rocks/tapbundle": "^5.3.0",
|
||||
"@types/node": "^22.5.5"
|
||||
"@git.zone/tsbuild": "^2.2.1",
|
||||
"@git.zone/tsbundle": "^2.2.5",
|
||||
"@git.zone/tsrun": "^1.3.3",
|
||||
"@git.zone/tstest": "^1.0.96",
|
||||
"@push.rocks/qenv": "^6.1.0",
|
||||
"@push.rocks/tapbundle": "^5.5.6",
|
||||
"@types/node": "^22.13.5"
|
||||
},
|
||||
"dependencies": {
|
||||
"@anthropic-ai/sdk": "^0.27.3",
|
||||
"@push.rocks/smartarray": "^1.0.8",
|
||||
"@push.rocks/smartfile": "^11.0.21",
|
||||
"@anthropic-ai/sdk": "^0.37.0",
|
||||
"@push.rocks/smartarray": "^1.1.0",
|
||||
"@push.rocks/smartfile": "^11.2.0",
|
||||
"@push.rocks/smartpath": "^5.0.18",
|
||||
"@push.rocks/smartpdf": "^3.1.6",
|
||||
"@push.rocks/smartpromise": "^4.0.4",
|
||||
"@push.rocks/smartrequest": "^2.0.22",
|
||||
"@push.rocks/smartpdf": "^3.2.2",
|
||||
"@push.rocks/smartpromise": "^4.2.3",
|
||||
"@push.rocks/smartrequest": "^2.0.23",
|
||||
"@push.rocks/webstream": "^1.0.10",
|
||||
"openai": "^4.62.1"
|
||||
"openai": "^4.85.4"
|
||||
},
|
||||
"repository": {
|
||||
"type": "git",
|
||||
@ -58,13 +58,32 @@
|
||||
],
|
||||
"keywords": [
|
||||
"AI integration",
|
||||
"chatbot",
|
||||
"TypeScript",
|
||||
"chatbot",
|
||||
"OpenAI",
|
||||
"Anthropic",
|
||||
"multi-model support",
|
||||
"audio responses",
|
||||
"multi-model",
|
||||
"audio generation",
|
||||
"text-to-speech",
|
||||
"streaming chat"
|
||||
]
|
||||
"document processing",
|
||||
"vision processing",
|
||||
"streaming chat",
|
||||
"API",
|
||||
"multiple providers",
|
||||
"AI models",
|
||||
"synchronous chat",
|
||||
"asynchronous chat",
|
||||
"real-time interaction",
|
||||
"content analysis",
|
||||
"image description",
|
||||
"document classification",
|
||||
"AI toolkit",
|
||||
"provider switching"
|
||||
],
|
||||
"pnpm": {
|
||||
"onlyBuiltDependencies": [
|
||||
"puppeteer"
|
||||
]
|
||||
},
|
||||
"packageManager": "pnpm@10.7.0+sha512.6b865ad4b62a1d9842b61d674a393903b871d9244954f652b8842c2b553c72176b278f64c463e52d40fff8aba385c235c8c9ecf5cc7de4fd78b8bb6d49633ab6"
|
||||
}
|
||||
|
6084
pnpm-lock.yaml
generated
6084
pnpm-lock.yaml
generated
File diff suppressed because it is too large
Load Diff
210
readme.md
210
readme.md
@ -1,73 +1,24 @@
|
||||
# @push.rocks/smartai
|
||||
|
||||
Provides a standardized interface for integrating and conversing with multiple AI models, supporting operations like chat, streaming interactions, and audio responses.
|
||||
SmartAi is a TypeScript library providing a unified interface for integrating and interacting with multiple AI models, supporting chat interactions, audio and document processing, and vision tasks.
|
||||
|
||||
## Install
|
||||
|
||||
To add @push.rocks/smartai to your project, run the following command in your terminal:
|
||||
To install SmartAi into your project, you need to run the following command in your terminal:
|
||||
|
||||
```bash
|
||||
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
|
||||
- Features: Chat, Streaming, Audio Generation
|
||||
- Configuration:
|
||||
```typescript
|
||||
openaiToken: 'your-openai-token'
|
||||
```
|
||||
|
||||
### Anthropic
|
||||
- Models: Claude-3-opus-20240229
|
||||
- Features: Chat, Streaming
|
||||
- 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)
|
||||
- Features: Chat, Streaming
|
||||
- Configuration:
|
||||
```typescript
|
||||
baseUrl: 'http://localhost:11434' // Optional
|
||||
model: 'llama2' // Optional
|
||||
```
|
||||
This command will add the SmartAi library to your project's dependencies, making it available for use in your TypeScript application.
|
||||
|
||||
## Usage
|
||||
|
||||
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.
|
||||
SmartAi is designed to provide a comprehensive and unified API for working seamlessly with multiple AI providers like OpenAI, Anthropic, Perplexity, and others. Below we will delve into how to make the most out of this library, illustrating the setup and functionality with in-depth examples. Our scenarios will explore synchronous and streaming interactions, audio generation, document handling, and vision tasks with different AI providers.
|
||||
|
||||
### Getting Started
|
||||
### Initialization
|
||||
|
||||
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.
|
||||
|
||||
### Initializing SmartAi
|
||||
|
||||
The first step is to import and initialize the `SmartAi` class with appropriate options for the AI services you plan to use:
|
||||
Initialization is the first step before using any AI functionalities. You should provide API tokens for each provider you plan to utilize.
|
||||
|
||||
```typescript
|
||||
import { SmartAi } from '@push.rocks/smartai';
|
||||
@ -76,10 +27,16 @@ const smartAi = new SmartAi({
|
||||
openaiToken: 'your-openai-token',
|
||||
anthropicToken: 'your-anthropic-token',
|
||||
perplexityToken: 'your-perplexity-token',
|
||||
xaiToken: 'your-xai-token',
|
||||
groqToken: 'your-groq-token',
|
||||
ollama: {
|
||||
baseUrl: 'http://localhost:11434',
|
||||
model: 'llama2'
|
||||
model: 'llama2',
|
||||
visionModel: 'llava'
|
||||
},
|
||||
exo: {
|
||||
baseUrl: 'http://localhost:8080/v1',
|
||||
apiKey: 'your-api-key'
|
||||
}
|
||||
});
|
||||
|
||||
@ -88,33 +45,34 @@ await smartAi.start();
|
||||
|
||||
### Chat Interactions
|
||||
|
||||
#### Synchronous Chat
|
||||
Interaction through chat is a key feature. SmartAi caters to both synchronous and asynchronous (streaming) chats across several AI models.
|
||||
|
||||
For simple question-answer interactions:
|
||||
#### Regular Synchronous Chat
|
||||
|
||||
Connect with AI models via straightforward request-response interactions.
|
||||
|
||||
```typescript
|
||||
const response = await smartAi.openaiProvider.chat({
|
||||
const syncResponse = await smartAi.openaiProvider.chat({
|
||||
systemMessage: 'You are a helpful assistant.',
|
||||
userMessage: 'What is the capital of France?',
|
||||
messageHistory: [] // Previous messages in the conversation
|
||||
messageHistory: [] // Could include context or preceding messages
|
||||
});
|
||||
|
||||
console.log(response.message);
|
||||
console.log(syncResponse.message); // Outputs: "The capital of France is Paris."
|
||||
```
|
||||
|
||||
#### Streaming Chat
|
||||
#### Real-Time Streaming Chat
|
||||
|
||||
For real-time, streaming interactions:
|
||||
For continuous interaction and lower latency, engage in streaming chat.
|
||||
|
||||
```typescript
|
||||
const textEncoder = new TextEncoder();
|
||||
const textDecoder = new TextDecoder();
|
||||
|
||||
// Create input and output streams
|
||||
// Establish a transform stream
|
||||
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'
|
||||
@ -122,58 +80,144 @@ const message = {
|
||||
|
||||
writer.write(textEncoder.encode(JSON.stringify(message) + '\n'));
|
||||
|
||||
// Process the response stream
|
||||
// Initiate streaming
|
||||
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
|
||||
console.log('AI:', value);
|
||||
}
|
||||
```
|
||||
|
||||
### Audio Generation
|
||||
|
||||
For providers that support audio generation (currently OpenAI):
|
||||
Audio generation from textual input is possible using providers like OpenAI.
|
||||
|
||||
```typescript
|
||||
const audioStream = await smartAi.openaiProvider.audio({
|
||||
message: 'Hello, this is a test of text-to-speech'
|
||||
message: 'This is a test message for generating speech.'
|
||||
});
|
||||
|
||||
// Handle the audio stream (e.g., save to file or play)
|
||||
// Use the audioStream e.g., playing or saving it.
|
||||
```
|
||||
|
||||
### Document Processing
|
||||
### Document Analysis
|
||||
|
||||
For providers that support document processing (currently OpenAI):
|
||||
SmartAi can ingest and process documents, extracting meaningful information or performing classifications.
|
||||
|
||||
```typescript
|
||||
const result = await smartAi.openaiProvider.document({
|
||||
systemMessage: 'Classify the document type',
|
||||
userMessage: 'What type of document is this?',
|
||||
const pdfBuffer = await fetchPdf('https://example.com/document.pdf');
|
||||
const documentRes = await smartAi.openaiProvider.document({
|
||||
systemMessage: 'Determine the nature of the document.',
|
||||
userMessage: 'Classify this document.',
|
||||
messageHistory: [],
|
||||
pdfDocuments: [pdfBuffer] // Uint8Array of PDF content
|
||||
pdfDocuments: [pdfBuffer]
|
||||
});
|
||||
|
||||
console.log(documentRes.message); // Outputs: classified document type
|
||||
```
|
||||
|
||||
## Error Handling
|
||||
SmartAi allows easy switching between providers, thus giving developers flexibility:
|
||||
|
||||
All providers implement proper error handling. It's recommended to wrap API calls in try-catch blocks:
|
||||
```typescript
|
||||
const anthopicRes = await smartAi.anthropicProvider.document({
|
||||
systemMessage: 'Analyze this document.',
|
||||
userMessage: 'Extract core points.',
|
||||
messageHistory: [],
|
||||
pdfDocuments: [pdfBuffer]
|
||||
});
|
||||
|
||||
console.log(anthopicRes.message); // Outputs: summarized core points
|
||||
```
|
||||
|
||||
### Vision Processing
|
||||
|
||||
Engage AI models in analyzing and describing images:
|
||||
|
||||
```typescript
|
||||
const imageBuffer = await fetchImage('path/to/image.jpg');
|
||||
|
||||
// Using OpenAI's vision capabilities
|
||||
const visionOutput = await smartAi.openaiProvider.vision({
|
||||
image: imageBuffer,
|
||||
prompt: 'Describe the image.'
|
||||
});
|
||||
|
||||
console.log(visionOutput); // Outputs: image description
|
||||
```
|
||||
|
||||
Use other providers for more varied analysis:
|
||||
|
||||
```typescript
|
||||
const ollamaOutput = await smartAi.ollamaProvider.vision({
|
||||
image: imageBuffer,
|
||||
prompt: 'Detailed analysis required.'
|
||||
});
|
||||
|
||||
console.log(ollamaOutput); // Outputs: detailed analysis results
|
||||
```
|
||||
|
||||
### Error Handling
|
||||
|
||||
Due to the nature of external integrations, ensure to wrap AI calls within try-catch blocks.
|
||||
|
||||
```typescript
|
||||
try {
|
||||
const response = await smartAi.openaiProvider.chat({
|
||||
systemMessage: 'You are a helpful assistant.',
|
||||
userMessage: 'Hello!',
|
||||
const response = await smartAi.anthropicProvider.chat({
|
||||
systemMessage: 'Hello!',
|
||||
userMessage: 'Help me out.',
|
||||
messageHistory: []
|
||||
});
|
||||
} catch (error) {
|
||||
console.error('AI provider error:', error.message);
|
||||
console.log(response.message);
|
||||
} catch (error: any) {
|
||||
console.error('Encountered an error:', error.message);
|
||||
}
|
||||
```
|
||||
|
||||
### Providers and Customization
|
||||
|
||||
The library supports provider-specific customization, enabling tailored interactions:
|
||||
|
||||
```typescript
|
||||
const smartAi = new SmartAi({
|
||||
openaiToken: 'your-openai-token',
|
||||
anthropicToken: 'your-anthropic-token',
|
||||
ollama: {
|
||||
baseUrl: 'http://localhost:11434',
|
||||
model: 'llama2',
|
||||
visionModel: 'llava'
|
||||
}
|
||||
});
|
||||
|
||||
await smartAi.start();
|
||||
```
|
||||
|
||||
### Advanced Streaming Customization
|
||||
|
||||
Developers can implement real-time processing pipelines with custom transformations:
|
||||
|
||||
```typescript
|
||||
const customProcessingStream = new TransformStream({
|
||||
transform(chunk, controller) {
|
||||
const processed = chunk.toUpperCase(); // Example transformation
|
||||
controller.enqueue(processed);
|
||||
}
|
||||
});
|
||||
|
||||
const processedStream = stream.pipeThrough(customProcessingStream);
|
||||
const processedReader = processedStream.getReader();
|
||||
|
||||
while (true) {
|
||||
const { done, value } = await processedReader.read();
|
||||
if (done) break;
|
||||
console.log('Processed Output:', value);
|
||||
}
|
||||
```
|
||||
|
||||
This approach can facilitate adaptive content processing workflows.
|
||||
|
||||
## License and Legal Information
|
||||
|
||||
This repository contains open-source code that is licensed under the MIT License. A copy of the MIT License can be found in the [license](license) file within this repository.
|
||||
|
26
test/test.ts
26
test/test.ts
@ -21,8 +21,7 @@ tap.test('should create chat response with openai', async () => {
|
||||
const response = await testSmartai.openaiProvider.chat({
|
||||
systemMessage: 'Hello',
|
||||
userMessage: userMessage,
|
||||
messageHistory: [
|
||||
],
|
||||
messageHistory: [],
|
||||
});
|
||||
console.log(`userMessage: ${userMessage}`);
|
||||
console.log(response.message);
|
||||
@ -55,7 +54,7 @@ tap.test('should recognize companies in a pdf', async () => {
|
||||
address: string;
|
||||
city: string;
|
||||
country: string;
|
||||
EU: boolean; // wether the entity is within EU
|
||||
EU: boolean; // whether the entity is within EU
|
||||
};
|
||||
entityReceiver: {
|
||||
type: 'official state entity' | 'company' | 'person';
|
||||
@ -63,7 +62,7 @@ tap.test('should recognize companies in a pdf', async () => {
|
||||
address: string;
|
||||
city: string;
|
||||
country: string;
|
||||
EU: boolean; // wether the entity is within EU
|
||||
EU: boolean; // whether 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
|
||||
@ -75,7 +74,24 @@ tap.test('should recognize companies in a pdf', async () => {
|
||||
pdfDocuments: [pdfBuffer],
|
||||
});
|
||||
console.log(result);
|
||||
})
|
||||
});
|
||||
|
||||
tap.test('should create audio response with openai', async () => {
|
||||
// Call the audio method with a sample message.
|
||||
const audioStream = await testSmartai.openaiProvider.audio({
|
||||
message: 'This is a test of audio generation.',
|
||||
});
|
||||
// Read all chunks from the stream.
|
||||
const chunks: Uint8Array[] = [];
|
||||
for await (const chunk of audioStream) {
|
||||
chunks.push(chunk as Uint8Array);
|
||||
}
|
||||
const audioBuffer = Buffer.concat(chunks);
|
||||
await smartfile.fs.toFs(audioBuffer, './.nogit/testoutput.mp3');
|
||||
console.log(`Audio Buffer length: ${audioBuffer.length}`);
|
||||
// Assert that the resulting buffer is not empty.
|
||||
expect(audioBuffer.length).toBeGreaterThan(0);
|
||||
});
|
||||
|
||||
tap.test('should stop the smartai instance', async () => {
|
||||
await testSmartai.stop();
|
||||
|
@ -3,6 +3,6 @@
|
||||
*/
|
||||
export const commitinfo = {
|
||||
name: '@push.rocks/smartai',
|
||||
version: '0.0.19',
|
||||
description: 'A TypeScript library for integrating and interacting with multiple AI models, offering capabilities for chat and potentially audio responses.'
|
||||
version: '0.5.3',
|
||||
description: 'SmartAi is a versatile TypeScript library designed to facilitate integration and interaction with various AI models, offering functionalities for chat, audio generation, document processing, and vision tasks.'
|
||||
}
|
||||
|
@ -62,4 +62,25 @@ export abstract class MultiModalModel {
|
||||
* @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 }>;
|
||||
}
|
||||
|
@ -48,6 +48,18 @@ export class Conversation {
|
||||
return conversation;
|
||||
}
|
||||
|
||||
public static async createWithExo(smartaiRefArg: SmartAi) {
|
||||
if (!smartaiRefArg.exoProvider) {
|
||||
throw new Error('Exo 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');
|
||||
@ -60,6 +72,30 @@ export class Conversation {
|
||||
return conversation;
|
||||
}
|
||||
|
||||
public static async createWithGroq(smartaiRefArg: SmartAi) {
|
||||
if (!smartaiRefArg.groqProvider) {
|
||||
throw new Error('Groq provider not available');
|
||||
}
|
||||
const conversation = new Conversation(smartaiRefArg, {
|
||||
processFunction: async (input) => {
|
||||
return '' // TODO implement proper streaming
|
||||
}
|
||||
});
|
||||
return conversation;
|
||||
}
|
||||
|
||||
public static async createWithXai(smartaiRefArg: SmartAi) {
|
||||
if (!smartaiRefArg.xaiProvider) {
|
||||
throw new Error('XAI provider not available');
|
||||
}
|
||||
const conversation = new Conversation(smartaiRefArg, {
|
||||
processFunction: async (input) => {
|
||||
return '' // TODO implement proper streaming
|
||||
}
|
||||
});
|
||||
return conversation;
|
||||
}
|
||||
|
||||
// INSTANCE
|
||||
smartaiRef: SmartAi
|
||||
private systemMessage: string;
|
||||
|
@ -1,18 +1,32 @@
|
||||
import { Conversation } from './classes.conversation.js';
|
||||
import * as plugins from './plugins.js';
|
||||
import { AnthropicProvider } from './provider.anthropic.js';
|
||||
import type { OllamaProvider } from './provider.ollama.js';
|
||||
import { OllamaProvider } from './provider.ollama.js';
|
||||
import { OpenAiProvider } from './provider.openai.js';
|
||||
import type { PerplexityProvider } from './provider.perplexity.js';
|
||||
import { PerplexityProvider } from './provider.perplexity.js';
|
||||
import { ExoProvider } from './provider.exo.js';
|
||||
import { GroqProvider } from './provider.groq.js';
|
||||
import { XAIProvider } from './provider.xai.js';
|
||||
|
||||
|
||||
export interface ISmartAiOptions {
|
||||
openaiToken?: string;
|
||||
anthropicToken?: string;
|
||||
perplexityToken?: string;
|
||||
groqToken?: string;
|
||||
xaiToken?: string;
|
||||
exo?: {
|
||||
baseUrl?: string;
|
||||
apiKey?: string;
|
||||
};
|
||||
ollama?: {
|
||||
baseUrl?: string;
|
||||
model?: string;
|
||||
visionModel?: string;
|
||||
};
|
||||
}
|
||||
|
||||
export type TProvider = 'openai' | 'anthropic' | 'perplexity' | 'ollama';
|
||||
export type TProvider = 'openai' | 'anthropic' | 'perplexity' | 'ollama' | 'exo' | 'groq' | 'xai';
|
||||
|
||||
export class SmartAi {
|
||||
public options: ISmartAiOptions;
|
||||
@ -21,6 +35,9 @@ export class SmartAi {
|
||||
public anthropicProvider: AnthropicProvider;
|
||||
public perplexityProvider: PerplexityProvider;
|
||||
public ollamaProvider: OllamaProvider;
|
||||
public exoProvider: ExoProvider;
|
||||
public groqProvider: GroqProvider;
|
||||
public xaiProvider: XAIProvider;
|
||||
|
||||
constructor(optionsArg: ISmartAiOptions) {
|
||||
this.options = optionsArg;
|
||||
@ -37,6 +54,40 @@ export class SmartAi {
|
||||
this.anthropicProvider = new AnthropicProvider({
|
||||
anthropicToken: this.options.anthropicToken,
|
||||
});
|
||||
await this.anthropicProvider.start();
|
||||
}
|
||||
if (this.options.perplexityToken) {
|
||||
this.perplexityProvider = new PerplexityProvider({
|
||||
perplexityToken: this.options.perplexityToken,
|
||||
});
|
||||
await this.perplexityProvider.start();
|
||||
}
|
||||
if (this.options.groqToken) {
|
||||
this.groqProvider = new GroqProvider({
|
||||
groqToken: this.options.groqToken,
|
||||
});
|
||||
await this.groqProvider.start();
|
||||
}
|
||||
if (this.options.xaiToken) {
|
||||
this.xaiProvider = new XAIProvider({
|
||||
xaiToken: this.options.xaiToken,
|
||||
});
|
||||
await this.xaiProvider.start();
|
||||
}
|
||||
if (this.options.ollama) {
|
||||
this.ollamaProvider = new OllamaProvider({
|
||||
baseUrl: this.options.ollama.baseUrl,
|
||||
model: this.options.ollama.model,
|
||||
visionModel: this.options.ollama.visionModel,
|
||||
});
|
||||
await this.ollamaProvider.start();
|
||||
}
|
||||
if (this.options.exo) {
|
||||
this.exoProvider = new ExoProvider({
|
||||
exoBaseUrl: this.options.exo.baseUrl,
|
||||
apiKey: this.options.exo.apiKey,
|
||||
});
|
||||
await this.exoProvider.start();
|
||||
}
|
||||
}
|
||||
|
||||
@ -47,6 +98,8 @@ export class SmartAi {
|
||||
*/
|
||||
createConversation(provider: TProvider) {
|
||||
switch (provider) {
|
||||
case 'exo':
|
||||
return Conversation.createWithExo(this);
|
||||
case 'openai':
|
||||
return Conversation.createWithOpenAi(this);
|
||||
case 'anthropic':
|
||||
@ -55,6 +108,10 @@ export class SmartAi {
|
||||
return Conversation.createWithPerplexity(this);
|
||||
case 'ollama':
|
||||
return Conversation.createWithOllama(this);
|
||||
case 'groq':
|
||||
return Conversation.createWithGroq(this);
|
||||
case 'xai':
|
||||
return Conversation.createWithXai(this);
|
||||
default:
|
||||
throw new Error('Provider not available');
|
||||
}
|
||||
|
@ -2,6 +2,9 @@ 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;
|
||||
@ -130,4 +133,108 @@ export class AnthropicProvider extends MultiModalModel {
|
||||
// Anthropic does not provide an audio API, so this method is not implemented.
|
||||
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
|
||||
}
|
||||
};
|
||||
}
|
||||
}
|
128
ts/provider.exo.ts
Normal file
128
ts/provider.exo.ts
Normal file
@ -0,0 +1,128 @@
|
||||
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 IExoProviderOptions {
|
||||
exoBaseUrl?: string;
|
||||
apiKey?: string;
|
||||
}
|
||||
|
||||
export class ExoProvider extends MultiModalModel {
|
||||
private options: IExoProviderOptions;
|
||||
public openAiApiClient: plugins.openai.default;
|
||||
|
||||
constructor(optionsArg: IExoProviderOptions = {}) {
|
||||
super();
|
||||
this.options = {
|
||||
exoBaseUrl: 'http://localhost:8080/v1', // Default Exo API endpoint
|
||||
...optionsArg
|
||||
};
|
||||
}
|
||||
|
||||
public async start() {
|
||||
this.openAiApiClient = new plugins.openai.default({
|
||||
apiKey: this.options.apiKey || 'not-needed', // Exo might not require an API key for local deployment
|
||||
baseURL: this.options.exoBaseUrl,
|
||||
});
|
||||
}
|
||||
|
||||
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>({
|
||||
transform: async (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 = message;
|
||||
|
||||
// Process the message based on its type
|
||||
if (message.type === 'message') {
|
||||
const response = await this.chat({
|
||||
systemMessage: '',
|
||||
userMessage: message.content,
|
||||
messageHistory: [{ role: message.role as 'user' | 'assistant' | 'system', content: message.content }]
|
||||
});
|
||||
|
||||
controller.enqueue(JSON.stringify(response) + '\n');
|
||||
}
|
||||
} catch (error) {
|
||||
console.error('Error processing message:', error);
|
||||
}
|
||||
}
|
||||
}
|
||||
},
|
||||
flush(controller) {
|
||||
if (buffer) {
|
||||
try {
|
||||
const message = JSON.parse(buffer);
|
||||
currentMessage = message;
|
||||
} catch (error) {
|
||||
console.error('Error processing remaining buffer:', error);
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
return input.pipeThrough(transform);
|
||||
}
|
||||
|
||||
public async chat(options: ChatOptions): Promise<ChatResponse> {
|
||||
const messages: ChatCompletionMessageParam[] = [
|
||||
{ role: 'system', content: options.systemMessage },
|
||||
...options.messageHistory,
|
||||
{ role: 'user', content: options.userMessage }
|
||||
];
|
||||
|
||||
try {
|
||||
const response = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'local-model', // Exo uses local models
|
||||
messages: messages,
|
||||
stream: false
|
||||
});
|
||||
|
||||
return {
|
||||
role: 'assistant',
|
||||
message: response.choices[0]?.message?.content || ''
|
||||
};
|
||||
} catch (error) {
|
||||
console.error('Error in chat completion:', error);
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
|
||||
throw new Error('Audio generation is not supported by Exo provider');
|
||||
}
|
||||
|
||||
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
|
||||
throw new Error('Vision processing is not supported by Exo provider');
|
||||
}
|
||||
|
||||
public async document(optionsArg: {
|
||||
systemMessage: string;
|
||||
userMessage: string;
|
||||
pdfDocuments: Uint8Array[];
|
||||
messageHistory: ChatMessage[];
|
||||
}): Promise<{ message: any }> {
|
||||
throw new Error('Document processing is not supported by Exo provider');
|
||||
}
|
||||
}
|
@ -32,7 +32,7 @@ export class GroqProvider extends MultiModalModel {
|
||||
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
transform: async (chunk, controller) => {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
@ -176,4 +176,17 @@ export class GroqProvider extends MultiModalModel {
|
||||
// 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.');
|
||||
}
|
||||
}
|
@ -6,18 +6,21 @@ import type { ChatOptions, ChatResponse, ChatMessage } from './abstract.classes.
|
||||
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() {
|
||||
@ -42,7 +45,7 @@ export class OllamaProvider extends MultiModalModel {
|
||||
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
transform: async (chunk, controller) => {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
@ -167,4 +170,83 @@ export class OllamaProvider extends MultiModalModel {
|
||||
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
|
||||
}
|
||||
};
|
||||
}
|
||||
}
|
@ -1,10 +1,20 @@
|
||||
import * as plugins from './plugins.js';
|
||||
import * as paths from './paths.js';
|
||||
|
||||
// Custom type definition for chat completion messages
|
||||
export type TChatCompletionRequestMessage = {
|
||||
role: "system" | "user" | "assistant";
|
||||
content: string;
|
||||
};
|
||||
|
||||
import { MultiModalModel } from './abstract.classes.multimodal.js';
|
||||
|
||||
export interface IOpenaiProviderOptions {
|
||||
openaiToken: string;
|
||||
chatModel?: string;
|
||||
audioModel?: string;
|
||||
visionModel?: string;
|
||||
// Optionally add more model options (e.g., documentModel) if needed.
|
||||
}
|
||||
|
||||
export class OpenAiProvider extends MultiModalModel {
|
||||
@ -31,11 +41,14 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
// Create a TextDecoder to handle incoming chunks
|
||||
const decoder = new TextDecoder();
|
||||
let buffer = '';
|
||||
let currentMessage: { role: string; content: string; } | null = null;
|
||||
let currentMessage: {
|
||||
role: "function" | "user" | "system" | "assistant" | "tool" | "developer";
|
||||
content: string;
|
||||
} | null = null;
|
||||
|
||||
// Create a TransformStream to process the input
|
||||
const transform = new TransformStream<Uint8Array, string>({
|
||||
async transform(chunk, controller) {
|
||||
transform: async (chunk, controller) => {
|
||||
buffer += decoder.decode(chunk, { stream: true });
|
||||
|
||||
// Try to parse complete JSON messages from the buffer
|
||||
@ -50,7 +63,7 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
try {
|
||||
const message = JSON.parse(line);
|
||||
currentMessage = {
|
||||
role: message.role || 'user',
|
||||
role: (message.role || 'user') as "function" | "user" | "system" | "assistant" | "tool" | "developer",
|
||||
content: message.content || '',
|
||||
};
|
||||
} catch (e) {
|
||||
@ -61,20 +74,24 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
|
||||
// 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 }],
|
||||
const messageToSend = { role: "user" as const, content: currentMessage.content };
|
||||
const chatModel = this.options.chatModel ?? 'o3-mini';
|
||||
const requestParams: any = {
|
||||
model: chatModel,
|
||||
messages: [messageToSend],
|
||||
stream: true,
|
||||
});
|
||||
|
||||
};
|
||||
// Temperature is omitted since the model does not support it.
|
||||
const stream = await this.openAiApiClient.chat.completions.create(requestParams);
|
||||
// Explicitly cast the stream as an async iterable to satisfy TypeScript.
|
||||
const streamAsyncIterable = stream as unknown as AsyncIterableIterator<any>;
|
||||
// Process each chunk from OpenAI
|
||||
for await (const chunk of stream) {
|
||||
for await (const chunk of streamAsyncIterable) {
|
||||
const content = chunk.choices[0]?.delta?.content;
|
||||
if (content) {
|
||||
controller.enqueue(content);
|
||||
}
|
||||
}
|
||||
|
||||
currentMessage = null;
|
||||
}
|
||||
},
|
||||
@ -104,15 +121,17 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
content: string;
|
||||
}[];
|
||||
}) {
|
||||
const result = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'gpt-4o',
|
||||
|
||||
const chatModel = this.options.chatModel ?? 'o3-mini';
|
||||
const requestParams: any = {
|
||||
model: chatModel,
|
||||
messages: [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
...optionsArg.messageHistory,
|
||||
{ role: 'user', content: optionsArg.userMessage },
|
||||
],
|
||||
});
|
||||
};
|
||||
// Temperature parameter removed to avoid unsupported error.
|
||||
const result = await this.openAiApiClient.chat.completions.create(requestParams);
|
||||
return {
|
||||
role: result.choices[0].message.role as 'assistant',
|
||||
message: result.choices[0].message.content,
|
||||
@ -122,7 +141,7 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
|
||||
const done = plugins.smartpromise.defer<NodeJS.ReadableStream>();
|
||||
const result = await this.openAiApiClient.audio.speech.create({
|
||||
model: 'tts-1-hd',
|
||||
model: this.options.audioModel ?? 'tts-1-hd',
|
||||
input: optionsArg.message,
|
||||
voice: 'nova',
|
||||
response_format: 'mp3',
|
||||
@ -144,27 +163,30 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
}) {
|
||||
let pdfDocumentImageBytesArray: Uint8Array[] = [];
|
||||
|
||||
// Convert each PDF into one or more image byte arrays.
|
||||
const smartpdfInstance = new plugins.smartpdf.SmartPdf();
|
||||
await smartpdfInstance.start();
|
||||
for (const pdfDocument of optionsArg.pdfDocuments) {
|
||||
const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument);
|
||||
const documentImageArray = await smartpdfInstance.convertPDFToPngBytes(pdfDocument);
|
||||
pdfDocumentImageBytesArray = pdfDocumentImageBytesArray.concat(documentImageArray);
|
||||
}
|
||||
await smartpdfInstance.stop();
|
||||
|
||||
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)
|
||||
);
|
||||
}
|
||||
);
|
||||
// Filter out any empty buffers to avoid sending invalid image URLs.
|
||||
const validImageBytesArray = pdfDocumentImageBytesArray.filter(imageBytes => imageBytes && imageBytes.length > 0);
|
||||
const imageAttachments = validImageBytesArray.map(imageBytes => ({
|
||||
type: 'image_url',
|
||||
image_url: {
|
||||
url: 'data:image/png;base64,' + Buffer.from(imageBytes).toString('base64'),
|
||||
},
|
||||
}));
|
||||
|
||||
const result = await this.openAiApiClient.chat.completions.create({
|
||||
model: 'gpt-4o',
|
||||
// response_format: { type: "json_object" }, // not supported for now
|
||||
const chatModel = this.options.chatModel ?? 'gpt-4o';
|
||||
const requestParams: any = {
|
||||
model: chatModel,
|
||||
messages: [
|
||||
{ role: 'system', content: optionsArg.systemMessage },
|
||||
...optionsArg.messageHistory,
|
||||
@ -172,24 +194,39 @@ export class OpenAiProvider extends MultiModalModel {
|
||||
role: 'user',
|
||||
content: [
|
||||
{ type: 'text', text: optionsArg.userMessage },
|
||||
...(() => {
|
||||
const returnArray = [];
|
||||
for (const imageBytes of pdfDocumentImageBytesArray) {
|
||||
returnArray.push({
|
||||
type: 'image_url',
|
||||
image_url: {
|
||||
url: 'data:image/png;base64,' + Buffer.from(imageBytes).toString('base64'),
|
||||
},
|
||||
});
|
||||
}
|
||||
return returnArray;
|
||||
})(),
|
||||
...imageAttachments,
|
||||
],
|
||||
},
|
||||
],
|
||||
});
|
||||
};
|
||||
// Temperature parameter removed.
|
||||
const result = await this.openAiApiClient.chat.completions.create(requestParams);
|
||||
return {
|
||||
message: result.choices[0].message,
|
||||
};
|
||||
}
|
||||
|
||||
public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
|
||||
const visionModel = this.options.visionModel ?? 'gpt-4o';
|
||||
const requestParams: any = {
|
||||
model: visionModel,
|
||||
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
|
||||
};
|
||||
const result = await this.openAiApiClient.chat.completions.create(requestParams);
|
||||
return result.choices[0].message.content || '';
|
||||
}
|
||||
}
|
@ -155,4 +155,17 @@ export class PerplexityProvider extends MultiModalModel {
|
||||
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 || ''
|
||||
};
|
||||
}
|
||||
}
|
Loading…
x
Reference in New Issue
Block a user