0.7.1

fix(docs): Add README image generation docs and .claude local settings
0.7.0
2025-10-03 13:49:46 +00:00 · 2025-10-03 13:49:46 +00:00 · 2025-10-03 13:43:29 +00:00 · 2025-10-03 13:43:29 +00:00 · 2025-10-03 12:50:42 +00:00 · 2025-09-28 15:51:50 +00:00
29 changed files with 5973 additions and 1075 deletions
--- a/changelog.md
+++ b/changelog.md
@@ -1,5 +1,105 @@
 # Changelog
 ## 2025-10-03 - 0.7.1 - fix(docs)
 Add README image generation docs and .claude local settings
 - Add .claude/settings.local.json with permission allow-list for local assistant tooling and web search
 - Update README provider capabilities table to include an Images column and reference gpt-image-1
 - Add Image Generation & Editing section with examples, options, and gpt-image-1 advantages
 - Mark image generation support as implemented in the roadmap and remove duplicate entry
 ## 2025-10-03 - 0.7.0 - feat(providers)
 Add research API and image generation/editing support; extend providers and tests
 - Introduce ResearchOptions and ResearchResponse to the MultiModalModel interface and implement research() where supported
 - OpenAiProvider: implement research(), add imageGenerate() and imageEdit() methods (gpt-image-1 / DALL·E support), and expose imageModel option
 - AnthropicProvider: implement research() and vision handling; explicitly throw for unsupported image generation/editing
 - PerplexityProvider: implement research() (sonar / sonar-pro support) and expose citation parsing
 - Add image/document-related interfaces (ImageGenerateOptions, ImageEditOptions, ImageResponse) to abstract API
 - Add image generation/editing/no-op stubs for other providers (Exo, Groq, Ollama, XAI) that throw informative errors to preserve API compatibility
 - Add comprehensive OpenAI image generation tests and helper to save test outputs (test/test.image.openai.ts)
 - Update README with Research & Web Search documentation, capability matrix, and roadmap entry for Research & Web Search API
 - Add local Claude agent permissions file (.claude/settings.local.json) and various provider type/import updates
 ## 2025-09-28 - 0.6.1 - fix(provider.anthropic)
 Fix Anthropic research tool identifier and add tests + local Claude permissions
 - Replace Anthropic research tool type from 'computer_20241022' to 'web_search_20250305' to match the expected web-search tool schema.
 - Add comprehensive test suites and fixtures for providers and research features (new/updated tests under test/ including anthropic, openai, research.* and stubs).
 - Fix test usage of XAI provider class name (use XAIProvider) and adjust basic provider test expectations (provider instantiation moved to start()).
 - Add .claude/settings.local.json with local Claude permissions to allow common CI/dev commands and web search during testing.
 ## 2025-09-28 - 0.6.0 - feat(research)
 Introduce research API with provider implementations, docs and tests
 - Add ResearchOptions and ResearchResponse interfaces and a new abstract research() method to MultiModalModel
 - Implement research() for OpenAiProvider (deep research model selection, optional web search/tools, background flag, source extraction)
 - Implement research() for AnthropicProvider (web search tool support, domain filters, citation extraction)
 - Implement research() for PerplexityProvider (sonar / sonar-pro model usage and citation parsing)
 - Add research() stubs to Exo, Groq, Ollama and XAI providers that throw a clear 'not yet supported' error to preserve interface compatibility
 - Add tests for research interfaces and provider research methods (test files updated/added)
 - Add documentation: readme.research.md describing the research API, usage and configuration
 - Export additional providers from ts/index.ts and update provider typings/imports across files
 - Add a 'typecheck' script to package.json
 - Add .claude/settings.local.json (local agent permissions for CI/dev tasks)
 ## 2025-08-12 - 0.5.11 - fix(openaiProvider)
 Update default chat model to gpt-5-mini and bump dependency versions
 - Changed default chat model in OpenAiProvider from 'o3-mini' and 'o4-mini' to 'gpt-5-mini'
 - Upgraded @anthropic-ai/sdk from ^0.57.0 to ^0.59.0
 - Upgraded openai from ^5.11.0 to ^5.12.2
 - Added new local Claude settings configuration (.claude/settings.local.json)
 ## 2025-08-03 - 0.5.10 - fix(dependencies)
 Update SmartPdf to v4.1.1 for enhanced PDF processing capabilities
 - Updated @push.rocks/smartpdf from ^3.3.0 to ^4.1.1
 - Enhanced PDF conversion with improved scale options and quality controls
 - Dependency updates for better performance and compatibility
 ## 2025-08-01 - 0.5.9 - fix(documentation)
 Remove contribution section from readme
 - Removed the contribution section from readme.md as requested
 - Kept the roadmap section for future development plans
 ## 2025-08-01 - 0.5.8 - fix(core)
 Fix SmartPdf lifecycle management and update dependencies
 - Moved SmartPdf instance management to the MultiModalModel base class for better resource sharing
 - Fixed memory leaks by properly implementing cleanup in the base class stop() method
 - Updated SmartAi class to properly stop all providers on shutdown
 - Updated @push.rocks/smartrequest from v2.1.0 to v4.2.1 with migration to new API
 - Enhanced readme with professional documentation and feature matrix
 ## 2025-07-26 - 0.5.7 - fix(provider.openai)
 Fix stream type mismatch in audio method
 - Fixed type error where OpenAI SDK returns a web ReadableStream but the audio method needs to return a Node.js ReadableStream
 - Added conversion using Node.js's built-in Readable.fromWeb() method
 ## 2025-07-25 - 0.5.5 - feat(documentation)
 Comprehensive documentation enhancement and test improvements
 - Completely rewrote readme.md with detailed provider comparisons, advanced usage examples, and performance tips
 - Added comprehensive examples for all supported providers (OpenAI, Anthropic, Perplexity, Groq, XAI, Ollama, Exo)
 - Included detailed sections on chat interactions, streaming, TTS, vision processing, and document analysis
 - Added verbose flag to test script for better debugging
 ## 2025-05-13 - 0.5.4 - fix(provider.openai)
 Update dependency versions, clean test imports, and adjust default OpenAI model configurations
 - Bump dependency versions in package.json (@git.zone/tsbuild, @push.rocks/tapbundle, openai, etc.)
 - Change default chatModel from 'gpt-4o' to 'o4-mini' and visionModel from 'gpt-4o' to '04-mini' in provider.openai.ts
 - Remove unused 'expectAsync' import from test file
 ## 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.
--- a/package.json
+++ b/package.json
@@ -1,6 +1,6 @@
 {
  "name": "@push.rocks/smartai",
-  "version": "0.5.2",
+  "version": "0.7.1",
  "private": false,
  "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",
@@ -9,29 +9,30 @@
  "author": "Task Venture Capital GmbH",
  "license": "MIT",
  "scripts": {
-    "test": "(tstest test/ --web)",
+    "test": "(tstest test/ --web --verbose)",
    "typecheck": "tsbuild check",
    "build": "(tsbuild --web --allowimplicitany)",
    "buildDocs": "(tsdoc)"
  },
  "devDependencies": {
-    "@git.zone/tsbuild": "^2.2.1",
+    "@git.zone/tsbuild": "^2.6.4",
-    "@git.zone/tsbundle": "^2.2.5",
+    "@git.zone/tsbundle": "^2.5.1",
    "@git.zone/tsrun": "^1.3.3",
-    "@git.zone/tstest": "^1.0.96",
+    "@git.zone/tstest": "^2.3.2",
    "@push.rocks/qenv": "^6.1.0",
-    "@push.rocks/tapbundle": "^5.5.6",
+    "@push.rocks/tapbundle": "^6.0.3",
-    "@types/node": "^22.13.5"
+    "@types/node": "^22.15.17"
  },
  "dependencies": {
-    "@anthropic-ai/sdk": "^0.37.0",
+    "@anthropic-ai/sdk": "^0.59.0",
    "@push.rocks/smartarray": "^1.1.0",
-    "@push.rocks/smartfile": "^11.2.0",
+    "@push.rocks/smartfile": "^11.2.5",
-    "@push.rocks/smartpath": "^5.0.18",
+    "@push.rocks/smartpath": "^6.0.0",
-    "@push.rocks/smartpdf": "^3.2.2",
+    "@push.rocks/smartpdf": "^4.1.1",
    "@push.rocks/smartpromise": "^4.2.3",
-    "@push.rocks/smartrequest": "^2.0.23",
+    "@push.rocks/smartrequest": "^4.2.1",
    "@push.rocks/webstream": "^1.0.10",
-    "openai": "^4.85.4"
+    "openai": "^5.12.2"
  },
  "repository": {
    "type": "git",
@@ -82,7 +83,9 @@
  ],
  "pnpm": {
    "onlyBuiltDependencies": [
      "esbuild",
      "puppeteer"
    ]
-  }
+  },
  "packageManager": "pnpm@10.7.0+sha512.6b865ad4b62a1d9842b61d674a393903b871d9244954f652b8842c2b553c72176b278f64c463e52d40fff8aba385c235c8c9ecf5cc7de4fd78b8bb6d49633ab6"
 }
--- a/pnpm-lock.yaml
+++ b/pnpm-lock.yaml
--- a/readme.md
+++ b/readme.md
@@ -1,189 +1,395 @@
 # @push.rocks/smartai
 **One API to rule them all** 🚀
-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.
+[![npm version](https://img.shields.io/npm/v/@push.rocks/smartai.svg)](https://www.npmjs.com/package/@push.rocks/smartai)
 [![TypeScript](https://img.shields.io/badge/TypeScript-5.x-blue.svg)](https://www.typescriptlang.org/)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
-## Install
+SmartAI unifies the world's leading AI providers - OpenAI, Anthropic, Perplexity, Ollama, Groq, XAI, and Exo - under a single, elegant TypeScript interface. Build AI applications at lightning speed without vendor lock-in. 
-To install SmartAi into your project, you need to run the following command in your terminal:
+## 🎯 Why SmartAI?
 - **🔌 Universal Interface**: Write once, run with any AI provider. Switch between GPT-4, Claude, Llama, or Grok with a single line change.
 - **🛡️ Type-Safe**: Full TypeScript support with comprehensive type definitions for all operations
 - **🌊 Streaming First**: Built for real-time applications with native streaming support
 - **🎨 Multi-Modal**: Seamlessly work with text, images, audio, and documents
 - **🏠 Local & Cloud**: Support for both cloud providers and local models via Ollama
 - **⚡ Zero Lock-In**: Your code remains portable across all AI providers
 ## 🚀 Quick Start
 ```bash
 npm install @push.rocks/smartai
 ```
 This command will add the SmartAi library to your project's dependencies, making it available for use in your TypeScript application.
 ## Usage
 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.
 ### Initialization
 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';
-const smartAi = new SmartAi({
+// Initialize with your favorite providers
-  openaiToken: 'your-openai-token',
+const ai = new SmartAi({
-  anthropicToken: 'your-anthropic-token',
+  openaiToken: 'sk-...',
-  perplexityToken: 'your-perplexity-token',
+  anthropicToken: 'sk-ant-...'
  xaiToken: 'your-xai-token',
  groqToken: 'your-groq-token',
  ollama: {
    baseUrl: 'http://localhost:11434',
    model: 'llama2',
    visionModel: 'llava'
  },
  exo: {
    baseUrl: 'http://localhost:8080/v1',
    apiKey: 'your-api-key'
  }
 });
-await smartAi.start();
+await ai.start();
 ```
-### Chat Interactions
+// Same API, multiple providers
-
+const response = await ai.openaiProvider.chat({
 Interaction through chat is a key feature. SmartAi caters to both synchronous and asynchronous (streaming) chats across several AI models.
 #### Regular Synchronous Chat
 Connect with AI models via straightforward request-response interactions.
 ```typescript
 const syncResponse = await smartAi.openaiProvider.chat({
  systemMessage: 'You are a helpful assistant.',
-  userMessage: 'What is the capital of France?',
+  userMessage: 'Explain quantum computing in simple terms',
-  messageHistory: [] // Could include context or preceding messages
+  messageHistory: []
 });
 console.log(syncResponse.message); // Outputs: "The capital of France is Paris."
 ```
-#### Real-Time Streaming Chat
+## 📊 Provider Capabilities Matrix
-For continuous interaction and lower latency, engage in streaming chat.
+Choose the right provider for your use case:
 | Provider | Chat | Streaming | TTS | Vision | Documents | Research | Images | Highlights |
 |----------|:----:|:---------:|:---:|:------:|:---------:|:--------:|:------:|------------|
 | **OpenAI** | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | • gpt-image-1<br>• DALL-E 3<br>• Deep research API |
 | **Anthropic** | ✅ | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | • Claude 3 Opus<br>• Superior reasoning<br>• Web search API |
 | **Ollama** | ✅ | ✅ | ❌ | ✅ | ✅ | ❌ | ❌ | • 100% local<br>• Privacy-first<br>• No API costs |
 | **XAI** | ✅ | ✅ | ❌ | ❌ | ✅ | ❌ | ❌ | • Grok models<br>• Real-time data<br>• Uncensored |
 | **Perplexity** | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ❌ | • Web-aware<br>• Research-focused<br>• Sonar Pro models |
 | **Groq** | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | • 10x faster<br>• LPU inference<br>• Low latency |
 | **Exo** | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ | • Distributed<br>• P2P compute<br>• Decentralized |
 ## 🎮 Core Features
 ### 💬 Universal Chat Interface
 Works identically across all providers:
 ```typescript
-const textEncoder = new TextEncoder();
+// Use GPT-4 for complex reasoning
-const textDecoder = new TextDecoder();
+const gptResponse = await ai.openaiProvider.chat({
  systemMessage: 'You are a expert physicist.',
  userMessage: 'Explain the implications of quantum entanglement',
  messageHistory: []
 });
-// Establish a transform stream
+// Use Claude for safety-critical applications
-const { writable, readable } = new TransformStream();
+const claudeResponse = await ai.anthropicProvider.chat({
-const writer = writable.getWriter();
+  systemMessage: 'You are a medical advisor.',
  userMessage: 'Review this patient data for concerns',
  messageHistory: []
 });
-const message = {
+// Use Groq for lightning-fast responses
-  role: 'user',
+const groqResponse = await ai.groqProvider.chat({
-  content: 'Tell me a story about a brave knight'
+  systemMessage: 'You are a code reviewer.',
-};
+  userMessage: 'Quick! Find the bug in this code: ...',
  messageHistory: []
 });
 ```
-writer.write(textEncoder.encode(JSON.stringify(message) + '\n'));
+### 🌊 Real-Time Streaming
-// Initiate streaming
+Build responsive chat interfaces with token-by-token streaming:
-const stream = await smartAi.openaiProvider.chatStream(readable);
+
 ```typescript
 // Create a chat stream
 const stream = await ai.openaiProvider.chatStream(inputStream);
 const reader = stream.getReader();
 // Display responses as they arrive
 while (true) {
  const { done, value } = await reader.read();
  if (done) break;
-  console.log('AI:', value);
+  
  // Update UI in real-time
  process.stdout.write(value);
 }
 ```
-### Audio Generation
+### 🎙️ Text-to-Speech
-Audio generation from textual input is possible using providers like OpenAI.
+Generate natural voices with OpenAI:
 ```typescript
-const audioStream = await smartAi.openaiProvider.audio({
+const audioStream = await ai.openaiProvider.audio({
-  message: 'This is a test message for generating speech.'
+  message: 'Welcome to the future of AI development!'
 });
-// Use the audioStream e.g., playing or saving it.
+// Stream directly to speakers
 audioStream.pipe(speakerOutput);
 // Or save to file
 audioStream.pipe(fs.createWriteStream('welcome.mp3'));
 ```
-### Document Analysis
+### 👁️ Vision Analysis
-SmartAi can ingest and process documents, extracting meaningful information or performing classifications.
+Understand images with multiple providers:
 ```typescript
-const pdfBuffer = await fetchPdf('https://example.com/document.pdf');
+const image = fs.readFileSync('product-photo.jpg');
-const documentRes = await smartAi.openaiProvider.document({
+
-  systemMessage: 'Determine the nature of the document.',
+// OpenAI: General purpose vision
-  userMessage: 'Classify this document.',
+const gptVision = await ai.openaiProvider.vision({
  image,
  prompt: 'Describe this product and suggest marketing angles'
 });
 // Anthropic: Detailed analysis
 const claudeVision = await ai.anthropicProvider.vision({
  image,
  prompt: 'Identify any safety concerns or defects'
 });
 // Ollama: Private, local analysis
 const ollamaVision = await ai.ollamaProvider.vision({
  image,
  prompt: 'Extract all text and categorize the content'
 });
 ```
 ### 📄 Document Intelligence
 Extract insights from PDFs with AI:
 ```typescript
 const contract = fs.readFileSync('contract.pdf');
 const invoice = fs.readFileSync('invoice.pdf');
 // Analyze documents
 const analysis = await ai.openaiProvider.document({
  systemMessage: 'You are a legal expert.',
  userMessage: 'Compare these documents and highlight key differences',
  messageHistory: [],
-  pdfDocuments: [pdfBuffer]
+  pdfDocuments: [contract, invoice]
 });
-console.log(documentRes.message); // Outputs: classified document type
+// Multi-document analysis
-```
+const taxDocs = [form1099, w2, receipts];
-
+const taxAnalysis = await ai.anthropicProvider.document({
-SmartAi allows easy switching between providers, thus giving developers flexibility:
+  systemMessage: 'You are a tax advisor.',
-
+  userMessage: 'Prepare a tax summary from these documents',
 ```typescript
 const anthopicRes = await smartAi.anthropicProvider.document({
  systemMessage: 'Analyze this document.',
  userMessage: 'Extract core points.',
  messageHistory: [],
-  pdfDocuments: [pdfBuffer]
+  pdfDocuments: taxDocs
 });
 console.log(anthopicRes.message); // Outputs: summarized core points
 ```
-### Vision Processing
+### 🔬 Research & Web Search
-Engage AI models in analyzing and describing images:
+Perform deep research with web search capabilities across multiple providers:
 ```typescript
-const imageBuffer = await fetchImage('path/to/image.jpg');
+// OpenAI Deep Research - Comprehensive analysis
-
+const deepResearch = await ai.openaiProvider.research({
-// Using OpenAI's vision capabilities
+  query: 'What are the latest developments in quantum computing?',
-const visionOutput = await smartAi.openaiProvider.vision({
+  searchDepth: 'deep',
-  image: imageBuffer,
+  includeWebSearch: true
  prompt: 'Describe the image.'
 });
-console.log(visionOutput); // Outputs: image description
+console.log(deepResearch.answer);
-```
+console.log('Sources:', deepResearch.sources);
-Use other providers for more varied analysis:
+// Anthropic Web Search - Domain-filtered research
-
+const anthropic = new AnthropicProvider({
-```typescript
+  anthropicToken: 'sk-ant-...',
-const ollamaOutput = await smartAi.ollamaProvider.vision({
+  enableWebSearch: true,
-  image: imageBuffer,
+  searchDomainAllowList: ['nature.com', 'science.org']
  prompt: 'Detailed analysis required.'
 });
-console.log(ollamaOutput); // Outputs: detailed analysis results
+const scientificResearch = await anthropic.research({
  query: 'Latest breakthroughs in CRISPR gene editing',
  searchDepth: 'advanced'
 });
 // Perplexity - Research-focused with citations
 const perplexityResearch = await ai.perplexityProvider.research({
  query: 'Current state of autonomous vehicle technology',
  searchDepth: 'deep' // Uses Sonar Pro model
 });
 ```
-### Error Handling
+**Research Options:**
 - `searchDepth`: 'basic' | 'advanced' | 'deep'
 - `maxSources`: Number of sources to include
 - `includeWebSearch`: Enable web search (OpenAI)
 - `background`: Run as background task (OpenAI)
-Due to the nature of external integrations, ensure to wrap AI calls within try-catch blocks.
+**Supported Providers:**
 - **OpenAI**: Deep Research API with specialized models (`o3-deep-research-2025-06-26`, `o4-mini-deep-research-2025-06-26`)
 - **Anthropic**: Web Search API with domain filtering
 - **Perplexity**: Sonar and Sonar Pro models with built-in citations
 ### 🎨 Image Generation & Editing
 Generate and edit images with OpenAI's cutting-edge models:
 ```typescript
-try {
+// Basic image generation with gpt-image-1
-  const response = await smartAi.anthropicProvider.chat({
+const image = await ai.openaiProvider.imageGenerate({
-    systemMessage: 'Hello!',
+  prompt: 'A futuristic robot assistant in a modern office, digital art',
-    userMessage: 'Help me out.',
+  model: 'gpt-image-1',
  quality: 'high',
  size: '1024x1024'
 });
 // Save the generated image
 const imageBuffer = Buffer.from(image.images[0].b64_json!, 'base64');
 fs.writeFileSync('robot.png', imageBuffer);
 // Advanced: Transparent background with custom format
 const logo = await ai.openaiProvider.imageGenerate({
  prompt: 'Minimalist mountain peak logo, geometric design',
  model: 'gpt-image-1',
  quality: 'high',
  size: '1024x1024',
  background: 'transparent',
  outputFormat: 'png'
 });
 // WebP with compression for web use
 const webImage = await ai.openaiProvider.imageGenerate({
  prompt: 'Product showcase: sleek smartphone on marble surface',
  model: 'gpt-image-1',
  quality: 'high',
  size: '1536x1024',
  outputFormat: 'webp',
  outputCompression: 85
 });
 // Superior text rendering (gpt-image-1's strength)
 const signage = await ai.openaiProvider.imageGenerate({
  prompt: 'Vintage cafe sign saying "COFFEE & CODE" in hand-lettered typography',
  model: 'gpt-image-1',
  quality: 'high',
  size: '1024x1024'
 });
 // Generate multiple variations at once
 const variations = await ai.openaiProvider.imageGenerate({
  prompt: 'Abstract geometric pattern, colorful minimalist art',
  model: 'gpt-image-1',
  n: 3,
  quality: 'medium',
  size: '1024x1024'
 });
 // Edit an existing image
 const editedImage = await ai.openaiProvider.imageEdit({
  image: originalImageBuffer,
  prompt: 'Add sunglasses and change the background to a beach sunset',
  model: 'gpt-image-1',
  quality: 'high'
 });
 ```
 **Image Generation Options:**
 - `model`: 'gpt-image-1' | 'dall-e-3' | 'dall-e-2'
 - `quality`: 'low' | 'medium' | 'high' | 'auto'
 - `size`: Multiple aspect ratios up to 4096×4096
 - `background`: 'transparent' | 'opaque' | 'auto'
 - `outputFormat`: 'png' | 'jpeg' | 'webp'
 - `outputCompression`: 0-100 for webp/jpeg
 - `moderation`: 'low' | 'auto'
 - `n`: Number of images (1-10)
 **gpt-image-1 Advantages:**
 - Superior text rendering in images
 - Up to 4096×4096 resolution
 - Transparent background support
 - Advanced output formats (WebP with compression)
 - Better prompt understanding
 - Streaming support for progressive rendering
 ### 🔄 Persistent Conversations
 Maintain context across interactions:
 ```typescript
 // Create a coding assistant conversation
 const assistant = ai.createConversation('openai');
 await assistant.setSystemMessage('You are an expert TypeScript developer.');
 // First question
 const inputWriter = assistant.getInputStreamWriter();
 await inputWriter.write('How do I implement a singleton pattern?');
 // Continue the conversation
 await inputWriter.write('Now show me how to make it thread-safe');
 // The assistant remembers the entire context
 ```
 ## 🚀 Real-World Examples
 ### Build a Customer Support Bot
 ```typescript
 const supportBot = new SmartAi({
  anthropicToken: process.env.ANTHROPIC_KEY // Claude for empathetic responses
 });
 async function handleCustomerQuery(query: string, history: ChatMessage[]) {
  try {
    const response = await supportBot.anthropicProvider.chat({
      systemMessage: `You are a helpful customer support agent. 
                      Be empathetic, professional, and solution-oriented.`,
      userMessage: query,
      messageHistory: history
    });
    return response.message;
  } catch (error) {
    // Fallback to another provider if needed
    return await supportBot.openaiProvider.chat({...});
  }
 }
 ```
 ### Create a Code Review Assistant
 ```typescript
 const codeReviewer = new SmartAi({
  groqToken: process.env.GROQ_KEY // Groq for speed
 });
 async function reviewCode(code: string, language: string) {
  const startTime = Date.now();
  const review = await codeReviewer.groqProvider.chat({
    systemMessage: `You are a ${language} expert. Review code for:
                    - Security vulnerabilities
                    - Performance issues  
                    - Best practices
                    - Potential bugs`,
    userMessage: `Review this code:\n\n${code}`,
    messageHistory: []
  });
-  console.log(response.message);
+  
-} catch (error: any) {
+  console.log(`Review completed in ${Date.now() - startTime}ms`);
-  console.error('Encountered an error:', error.message);
+  return review.message;
 }
 ```
-### Providers and Customization
+### Build a Research Assistant
 The library supports provider-specific customization, enabling tailored interactions:
 ```typescript
-const smartAi = new SmartAi({
+const researcher = new SmartAi({
-  openaiToken: 'your-openai-token',
+  perplexityToken: process.env.PERPLEXITY_KEY
-  anthropicToken: 'your-anthropic-token',
+});
 async function research(topic: string) {
  // Perplexity excels at web-aware research
  const findings = await researcher.perplexityProvider.chat({
    systemMessage: 'You are a research assistant. Provide factual, cited information.',
    userMessage: `Research the latest developments in ${topic}`,
    messageHistory: []
  });
  return findings.message;
 }
 ```
 ### Local AI for Sensitive Data
 ```typescript
 const localAI = new SmartAi({
  ollama: {
    baseUrl: 'http://localhost:11434',
    model: 'llama2',
@@ -191,32 +397,198 @@ const smartAi = new SmartAi({
  }
 });
-await smartAi.start();
+// Process sensitive documents without leaving your infrastructure
-```
+async function analyzeSensitiveDoc(pdfBuffer: Buffer) {
-
+  const analysis = await localAI.ollamaProvider.document({
-### Advanced Streaming Customization
+    systemMessage: 'Extract and summarize key information.',
-
+    userMessage: 'Analyze this confidential document',
-Developers can implement real-time processing pipelines with custom transformations:
+    messageHistory: [],
-
+    pdfDocuments: [pdfBuffer]
-```typescript
+  });
-const customProcessingStream = new TransformStream({
+  
-  transform(chunk, controller) {
+  // Data never leaves your servers
-    const processed = chunk.toUpperCase(); // Example transformation
+  return analysis.message;
    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.
+## ⚡ Performance Tips
 ### 1. Provider Selection Strategy
 ```typescript
 class SmartAIRouter {
  constructor(private ai: SmartAi) {}
  async query(message: string, requirements: {
    speed?: boolean;
    accuracy?: boolean;
    cost?: boolean;
    privacy?: boolean;
  }) {
    if (requirements.privacy) {
      return this.ai.ollamaProvider.chat({...}); // Local only
    }
    if (requirements.speed) {
      return this.ai.groqProvider.chat({...}); // 10x faster
    }
    if (requirements.accuracy) {
      return this.ai.anthropicProvider.chat({...}); // Best reasoning
    }
    // Default fallback
    return this.ai.openaiProvider.chat({...});
  }
 }
 ```
 ### 2. Streaming for Large Responses
 ```typescript
 // Don't wait for the entire response
 async function streamResponse(userQuery: string) {
  const stream = await ai.openaiProvider.chatStream(createInputStream(userQuery));
  // Process tokens as they arrive
  for await (const chunk of stream) {
    updateUI(chunk); // Immediate feedback
    await processChunk(chunk); // Parallel processing
  }
 }
 ```
 ### 3. Parallel Multi-Provider Queries
 ```typescript
 // Get the best answer from multiple AIs
 async function consensusQuery(question: string) {
  const providers = [
    ai.openaiProvider.chat({...}),
    ai.anthropicProvider.chat({...}),
    ai.perplexityProvider.chat({...})
  ];
  const responses = await Promise.all(providers);
  return synthesizeResponses(responses);
 }
 ```
 ## 🛠️ Advanced Features
 ### Custom Streaming Transformations
 ```typescript
 // Add real-time translation
 const translationStream = new TransformStream({
  async transform(chunk, controller) {
    const translated = await translateChunk(chunk);
    controller.enqueue(translated);
  }
 });
 const responseStream = await ai.openaiProvider.chatStream(input);
 const translatedStream = responseStream.pipeThrough(translationStream);
 ```
 ### Error Handling & Fallbacks
 ```typescript
 class ResilientAI {
  private providers = ['openai', 'anthropic', 'groq'];
  async query(opts: ChatOptions): Promise<ChatResponse> {
    for (const provider of this.providers) {
      try {
        return await this.ai[`${provider}Provider`].chat(opts);
      } catch (error) {
        console.warn(`${provider} failed, trying next...`);
        continue;
      }
    }
    throw new Error('All providers failed');
  }
 }
 ```
 ### Token Counting & Cost Management
 ```typescript
 // Track usage across providers
 class UsageTracker {
  async trackedChat(provider: string, options: ChatOptions) {
    const start = Date.now();
    const response = await ai[`${provider}Provider`].chat(options);
    const usage = {
      provider,
      duration: Date.now() - start,
      inputTokens: estimateTokens(options),
      outputTokens: estimateTokens(response.message)
    };
    await this.logUsage(usage);
    return response;
  }
 }
 ```
 ## 📦 Installation & Setup
 ### Prerequisites
 - Node.js 16+ 
 - TypeScript 4.5+
 - API keys for your chosen providers
 ### Environment Setup
 ```bash
 # Install
 npm install @push.rocks/smartai
 # Set up environment variables
 export OPENAI_API_KEY=sk-...
 export ANTHROPIC_API_KEY=sk-ant-...
 export PERPLEXITY_API_KEY=pplx-...
 # ... etc
 ```
 ### TypeScript Configuration
 ```json
 {
  "compilerOptions": {
    "target": "ES2022",
    "module": "NodeNext",
    "lib": ["ES2022"],
    "strict": true,
    "esModuleInterop": true,
    "skipLibCheck": true
  }
 }
 ```
 ## 🎯 Choosing the Right Provider
 | Use Case | Recommended Provider | Why |
 |----------|---------------------|-----|
 | **General Purpose** | OpenAI | Most features, stable, well-documented |
 | **Complex Reasoning** | Anthropic | Superior logical thinking, safer outputs |
 | **Research & Facts** | Perplexity | Web-aware, provides citations |
 | **Deep Research** | OpenAI | Deep Research API with comprehensive analysis |
 | **Speed Critical** | Groq | 10x faster inference, sub-second responses |
 | **Privacy Critical** | Ollama | 100% local, no data leaves your servers |
 | **Real-time Data** | XAI | Access to current information |
 | **Cost Sensitive** | Ollama/Exo | Free (local) or distributed compute |
 ## 📈 Roadmap
 - [x] Research & Web Search API
 - [x] Image generation support (gpt-image-1, DALL-E 3, DALL-E 2)
 - [ ] Streaming function calls
 - [ ] Voice input processing
 - [ ] Fine-tuning integration
 - [ ] Embedding support
 - [ ] Agent framework
 - [ ] More providers (Cohere, AI21, etc.)
 ## License and Legal Information
@@ -235,4 +607,4 @@ Registered at District court Bremen HRB 35230 HB, Germany
 For any legal inquiries or if you require further information, please contact us via email at hello@task.vc.
-By using this repository, you acknowledge that you have read this section, agree to comply with its terms, and understand that the licensing of the code does not imply endorsement by Task Venture Capital GmbH of any derivative works.
+By using this repository, you acknowledge that you have read this section, agree to comply with its terms, and understand that the licensing of the code does not imply endorsement by Task Venture Capital GmbH of any derivative works.
--- a/test/test.anthropic.ts
+++ b/test/test.anthropic.ts
@@ -0,0 +1,216 @@
 import { expect, 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/');
 import * as smartai from '../ts/index.js';
 let anthropicProvider: smartai.AnthropicProvider;
 tap.test('Anthropic: should create and start Anthropic provider', async () => {
  anthropicProvider = new smartai.AnthropicProvider({
    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
  });
  await anthropicProvider.start();
  expect(anthropicProvider).toBeInstanceOf(smartai.AnthropicProvider);
 });
 tap.test('Anthropic: should create chat response', async () => {
  const userMessage = 'What is the capital of France? Answer in one word.';
  const response = await anthropicProvider.chat({
    systemMessage: 'You are a helpful assistant. Be concise.',
    userMessage: userMessage,
    messageHistory: [],
  });
  console.log(`Anthropic Chat - User: ${userMessage}`);
  console.log(`Anthropic Chat - Response: ${response.message}`);
  expect(response.role).toEqual('assistant');
  expect(response.message).toBeTruthy();
  expect(response.message.toLowerCase()).toInclude('paris');
 });
 tap.test('Anthropic: should handle message history', async () => {
  const messageHistory: smartai.ChatMessage[] = [
    { role: 'user', content: 'My name is Claude Test' },
    { role: 'assistant', content: 'Nice to meet you, Claude Test!' }
  ];
  const response = await anthropicProvider.chat({
    systemMessage: 'You are a helpful assistant with good memory.',
    userMessage: 'What is my name?',
    messageHistory: messageHistory,
  });
  console.log(`Anthropic Memory Test - Response: ${response.message}`);
  expect(response.message.toLowerCase()).toInclude('claude test');
 });
 tap.test('Anthropic: should analyze coffee image with latte art', async () => {
  // Test 1: Coffee image from Unsplash by Dani
  const imagePath = './test/testimages/coffee-dani/coffee.jpg';
  console.log(`Loading coffee image from: ${imagePath}`);
  const imageBuffer = await smartfile.fs.toBuffer(imagePath);
  console.log(`Image loaded, size: ${imageBuffer.length} bytes`);
  const result = await anthropicProvider.vision({
    image: imageBuffer,
    prompt: 'Describe this coffee image. What do you see in terms of the cup, foam pattern, and overall composition?'
  });
  console.log(`Anthropic Vision (Coffee) - Result: ${result}`);
  expect(result).toBeTruthy();
  expect(typeof result).toEqual('string');
  expect(result.toLowerCase()).toInclude('coffee');
  // The image has a heart pattern in the latte art
  const mentionsLatte = result.toLowerCase().includes('heart') ||
                        result.toLowerCase().includes('latte') ||
                        result.toLowerCase().includes('foam');
  expect(mentionsLatte).toBeTrue();
 });
 tap.test('Anthropic: should analyze laptop/workspace image', async () => {
  // Test 2: Laptop image from Unsplash by Nicolas Bichon
  const imagePath = './test/testimages/laptop-nicolas/laptop.jpg';
  console.log(`Loading laptop image from: ${imagePath}`);
  const imageBuffer = await smartfile.fs.toBuffer(imagePath);
  console.log(`Image loaded, size: ${imageBuffer.length} bytes`);
  const result = await anthropicProvider.vision({
    image: imageBuffer,
    prompt: 'Describe the technology and workspace setup in this image. What devices and equipment can you see?'
  });
  console.log(`Anthropic Vision (Laptop) - Result: ${result}`);
  expect(result).toBeTruthy();
  expect(typeof result).toEqual('string');
  // Should mention laptop, computer, keyboard, or desk
  const mentionsTech = result.toLowerCase().includes('laptop') ||
                       result.toLowerCase().includes('computer') ||
                       result.toLowerCase().includes('keyboard') ||
                       result.toLowerCase().includes('desk');
  expect(mentionsTech).toBeTrue();
 });
 tap.test('Anthropic: should analyze receipt/document image', async () => {
  // Test 3: Receipt image from Unsplash by Annie Spratt
  const imagePath = './test/testimages/receipt-annie/receipt.jpg';
  console.log(`Loading receipt image from: ${imagePath}`);
  const imageBuffer = await smartfile.fs.toBuffer(imagePath);
  console.log(`Image loaded, size: ${imageBuffer.length} bytes`);
  const result = await anthropicProvider.vision({
    image: imageBuffer,
    prompt: 'What type of document is this? Can you identify any text or numbers visible in the image?'
  });
  console.log(`Anthropic Vision (Receipt) - Result: ${result}`);
  expect(result).toBeTruthy();
  expect(typeof result).toEqual('string');
  // Should mention receipt, document, text, or paper
  const mentionsDocument = result.toLowerCase().includes('receipt') ||
                          result.toLowerCase().includes('document') ||
                          result.toLowerCase().includes('text') ||
                          result.toLowerCase().includes('paper');
  expect(mentionsDocument).toBeTrue();
 });
 tap.test('Anthropic: should document a PDF', async () => {
  const pdfUrl = 'https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf';
  const pdfResponse = await smartrequest.SmartRequest.create()
    .url(pdfUrl)
    .get();
  const result = await anthropicProvider.document({
    systemMessage: 'Classify the document. Only the following answers are allowed: "invoice", "bank account statement", "contract", "test document", "other". The answer should only contain the keyword for machine use.',
    userMessage: 'Classify this document.',
    messageHistory: [],
    pdfDocuments: [Buffer.from(await pdfResponse.arrayBuffer())],
  });
  console.log(`Anthropic Document - Result:`, result);
  expect(result).toBeTruthy();
  expect(result.message).toBeTruthy();
 });
 tap.test('Anthropic: should handle complex document analysis', async () => {
  // Test with the demo PDF if it exists
  const pdfPath = './.nogit/demo_without_textlayer.pdf';
  let pdfBuffer: Uint8Array;
  try {
    pdfBuffer = await smartfile.fs.toBuffer(pdfPath);
  } catch (error) {
    // If the file doesn't exist, use the dummy PDF
    console.log('Demo PDF not found, using dummy PDF instead');
    const pdfUrl = 'https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf';
    const pdfResponse = await smartrequest.SmartRequest.create()
      .url(pdfUrl)
      .get();
    pdfBuffer = Buffer.from(await pdfResponse.arrayBuffer());
  }
  const result = await anthropicProvider.document({
    systemMessage: `
      Analyze this document and provide a JSON response with the following structure:
      {
        "documentType": "string",
        "hasText": boolean,
        "summary": "string"
      }
    `,
    userMessage: 'Analyze this document.',
    messageHistory: [],
    pdfDocuments: [pdfBuffer],
  });
  console.log(`Anthropic Complex Document Analysis:`, result);
  expect(result).toBeTruthy();
  expect(result.message).toBeTruthy();
 });
 tap.test('Anthropic: should handle errors gracefully', async () => {
  // Test with invalid message (empty)
  let errorCaught = false;
  try {
    await anthropicProvider.chat({
      systemMessage: '',
      userMessage: '',
      messageHistory: [],
    });
  } catch (error) {
    errorCaught = true;
    console.log('Expected error caught:', error.message);
  }
  // Anthropic might handle empty messages, so we don't assert error
  console.log(`Error handling test - Error caught: ${errorCaught}`);
 });
 tap.test('Anthropic: audio should throw not supported error', async () => {
  let errorCaught = false;
  try {
    await anthropicProvider.audio({
      message: 'This should fail'
    });
  } catch (error) {
    errorCaught = true;
    expect(error.message).toInclude('not yet supported');
  }
  expect(errorCaught).toBeTrue();
 });
 tap.test('Anthropic: should stop the provider', async () => {
  await anthropicProvider.stop();
  console.log('Anthropic provider stopped successfully');
 });
 export default tap.start();
--- a/test/test.basic.ts
+++ b/test/test.basic.ts
@@ -0,0 +1,93 @@
 import { tap, expect } from '@push.rocks/tapbundle';
 import * as smartai from '../ts/index.js';
 // Basic instantiation tests that don't require API tokens
 // These tests can run in CI/CD environments without credentials
 tap.test('Basic: should create SmartAi instance', async () => {
  const testSmartai = new smartai.SmartAi({
    openaiToken: 'dummy-token-for-testing'
  });
  expect(testSmartai).toBeInstanceOf(smartai.SmartAi);
  // Provider is only created after calling start()
  expect(testSmartai.options.openaiToken).toEqual('dummy-token-for-testing');
 });
 tap.test('Basic: should instantiate OpenAI provider', async () => {
  const openaiProvider = new smartai.OpenAiProvider({
    openaiToken: 'dummy-token'
  });
  expect(openaiProvider).toBeInstanceOf(smartai.OpenAiProvider);
  expect(typeof openaiProvider.chat).toEqual('function');
  expect(typeof openaiProvider.audio).toEqual('function');
  expect(typeof openaiProvider.vision).toEqual('function');
  expect(typeof openaiProvider.document).toEqual('function');
  expect(typeof openaiProvider.research).toEqual('function');
 });
 tap.test('Basic: should instantiate Anthropic provider', async () => {
  const anthropicProvider = new smartai.AnthropicProvider({
    anthropicToken: 'dummy-token'
  });
  expect(anthropicProvider).toBeInstanceOf(smartai.AnthropicProvider);
  expect(typeof anthropicProvider.chat).toEqual('function');
  expect(typeof anthropicProvider.audio).toEqual('function');
  expect(typeof anthropicProvider.vision).toEqual('function');
  expect(typeof anthropicProvider.document).toEqual('function');
  expect(typeof anthropicProvider.research).toEqual('function');
 });
 tap.test('Basic: should instantiate Perplexity provider', async () => {
  const perplexityProvider = new smartai.PerplexityProvider({
    perplexityToken: 'dummy-token'
  });
  expect(perplexityProvider).toBeInstanceOf(smartai.PerplexityProvider);
  expect(typeof perplexityProvider.chat).toEqual('function');
  expect(typeof perplexityProvider.research).toEqual('function');
 });
 tap.test('Basic: should instantiate Groq provider', async () => {
  const groqProvider = new smartai.GroqProvider({
    groqToken: 'dummy-token'
  });
  expect(groqProvider).toBeInstanceOf(smartai.GroqProvider);
  expect(typeof groqProvider.chat).toEqual('function');
  expect(typeof groqProvider.research).toEqual('function');
 });
 tap.test('Basic: should instantiate Ollama provider', async () => {
  const ollamaProvider = new smartai.OllamaProvider({
    baseUrl: 'http://localhost:11434'
  });
  expect(ollamaProvider).toBeInstanceOf(smartai.OllamaProvider);
  expect(typeof ollamaProvider.chat).toEqual('function');
  expect(typeof ollamaProvider.research).toEqual('function');
 });
 tap.test('Basic: should instantiate xAI provider', async () => {
  const xaiProvider = new smartai.XAIProvider({
    xaiToken: 'dummy-token'
  });
  expect(xaiProvider).toBeInstanceOf(smartai.XAIProvider);
  expect(typeof xaiProvider.chat).toEqual('function');
  expect(typeof xaiProvider.research).toEqual('function');
 });
 tap.test('Basic: should instantiate Exo provider', async () => {
  const exoProvider = new smartai.ExoProvider({
    exoBaseUrl: 'http://localhost:8000'
  });
  expect(exoProvider).toBeInstanceOf(smartai.ExoProvider);
  expect(typeof exoProvider.chat).toEqual('function');
  expect(typeof exoProvider.research).toEqual('function');
 });
 tap.test('Basic: all providers should extend MultiModalModel', async () => {
  const openai = new smartai.OpenAiProvider({ openaiToken: 'test' });
  const anthropic = new smartai.AnthropicProvider({ anthropicToken: 'test' });
  expect(openai).toBeInstanceOf(smartai.MultiModalModel);
  expect(anthropic).toBeInstanceOf(smartai.MultiModalModel);
 });
 export default tap.start();
--- a/test/test.image.openai.ts
+++ b/test/test.image.openai.ts
@@ -0,0 +1,203 @@
 import { expect, tap } from '@push.rocks/tapbundle';
 import * as qenv from '@push.rocks/qenv';
 import * as smartai from '../ts/index.js';
 import * as path from 'path';
 import { promises as fs } from 'fs';
 const testQenv = new qenv.Qenv('./', './.nogit/');
 let openaiProvider: smartai.OpenAiProvider;
 // Helper function to save image results
 async function saveImageResult(testName: string, result: any) {
  const sanitizedName = testName.replace(/[^a-z0-9]/gi, '_').toLowerCase();
  const timestamp = new Date().toISOString().replace(/[:.]/g, '-');
  const filename = `openai_${sanitizedName}_${timestamp}.json`;
  const filepath = path.join('.nogit', 'testresults', 'images', filename);
  await fs.mkdir(path.dirname(filepath), { recursive: true });
  await fs.writeFile(filepath, JSON.stringify(result, null, 2), 'utf-8');
  console.log(`  💾 Saved to: ${filepath}`);
  // Also save the actual image if b64_json is present
  if (result.images && result.images[0]?.b64_json) {
    const imageFilename = `openai_${sanitizedName}_${timestamp}.png`;
    const imageFilepath = path.join('.nogit', 'testresults', 'images', imageFilename);
    await fs.writeFile(imageFilepath, Buffer.from(result.images[0].b64_json, 'base64'));
    console.log(`  🖼️  Image saved to: ${imageFilepath}`);
  }
 }
 tap.test('OpenAI Image Generation: should initialize provider', async () => {
  const openaiToken = await testQenv.getEnvVarOnDemand('OPENAI_TOKEN');
  expect(openaiToken).toBeTruthy();
  openaiProvider = new smartai.OpenAiProvider({
    openaiToken,
    imageModel: 'gpt-image-1'
  });
  await openaiProvider.start();
  expect(openaiProvider).toBeInstanceOf(smartai.OpenAiProvider);
 });
 tap.test('OpenAI Image: Basic generation with gpt-image-1', async () => {
  const result = await openaiProvider.imageGenerate({
    prompt: 'A cute robot reading a book in a cozy library, digital art style',
    model: 'gpt-image-1',
    quality: 'medium',
    size: '1024x1024'
  });
  console.log('Basic gpt-image-1 Generation:');
  console.log('- Images generated:', result.images.length);
  console.log('- Model used:', result.metadata?.model);
  console.log('- Quality:', result.metadata?.quality);
  console.log('- Size:', result.metadata?.size);
  console.log('- Tokens used:', result.metadata?.tokensUsed);
  await saveImageResult('basic_generation_gptimage1', result);
  expect(result.images).toBeTruthy();
  expect(result.images.length).toEqual(1);
  expect(result.images[0].b64_json).toBeTruthy();
  expect(result.metadata?.model).toEqual('gpt-image-1');
 });
 tap.test('OpenAI Image: High quality with transparent background', async () => {
  const result = await openaiProvider.imageGenerate({
    prompt: 'A simple geometric logo of a mountain peak, minimal design, clean lines',
    model: 'gpt-image-1',
    quality: 'high',
    size: '1024x1024',
    background: 'transparent',
    outputFormat: 'png'
  });
  console.log('High Quality Transparent:');
  console.log('- Quality:', result.metadata?.quality);
  console.log('- Background: transparent');
  console.log('- Format:', result.metadata?.outputFormat);
  console.log('- Tokens used:', result.metadata?.tokensUsed);
  await saveImageResult('high_quality_transparent', result);
  expect(result.images.length).toEqual(1);
  expect(result.images[0].b64_json).toBeTruthy();
 });
 tap.test('OpenAI Image: WebP format with compression', async () => {
  const result = await openaiProvider.imageGenerate({
    prompt: 'A futuristic cityscape at sunset with flying cars, photorealistic',
    model: 'gpt-image-1',
    quality: 'high',
    size: '1536x1024',
    outputFormat: 'webp',
    outputCompression: 85
  });
  console.log('WebP with Compression:');
  console.log('- Format:', result.metadata?.outputFormat);
  console.log('- Compression: 85%');
  console.log('- Size:', result.metadata?.size);
  await saveImageResult('webp_compression', result);
  expect(result.images.length).toEqual(1);
  expect(result.images[0].b64_json).toBeTruthy();
 });
 tap.test('OpenAI Image: Text rendering with gpt-image-1', async () => {
  const result = await openaiProvider.imageGenerate({
    prompt: 'A vintage cafe sign that says "COFFEE & CODE" in elegant hand-lettered typography, warm colors',
    model: 'gpt-image-1',
    quality: 'high',
    size: '1024x1024'
  });
  console.log('Text Rendering:');
  console.log('- Prompt includes text: "COFFEE & CODE"');
  console.log('- gpt-image-1 has superior text rendering');
  console.log('- Tokens used:', result.metadata?.tokensUsed);
  await saveImageResult('text_rendering', result);
  expect(result.images.length).toEqual(1);
  expect(result.images[0].b64_json).toBeTruthy();
 });
 tap.test('OpenAI Image: Multiple images generation', async () => {
  const result = await openaiProvider.imageGenerate({
    prompt: 'Abstract colorful geometric patterns, modern minimalist art',
    model: 'gpt-image-1',
    n: 2,
    quality: 'medium',
    size: '1024x1024'
  });
  console.log('Multiple Images:');
  console.log('- Images requested: 2');
  console.log('- Images generated:', result.images.length);
  await saveImageResult('multiple_images', result);
  expect(result.images.length).toEqual(2);
  expect(result.images[0].b64_json).toBeTruthy();
  expect(result.images[1].b64_json).toBeTruthy();
 });
 tap.test('OpenAI Image: Low moderation setting', async () => {
  const result = await openaiProvider.imageGenerate({
    prompt: 'A fantasy battle scene with warriors and dragons',
    model: 'gpt-image-1',
    moderation: 'low',
    quality: 'medium'
  });
  console.log('Low Moderation:');
  console.log('- Moderation: low (less restrictive filtering)');
  console.log('- Tokens used:', result.metadata?.tokensUsed);
  await saveImageResult('low_moderation', result);
  expect(result.images.length).toEqual(1);
  expect(result.images[0].b64_json).toBeTruthy();
 });
 tap.test('OpenAI Image Editing: edit with gpt-image-1', async () => {
  // First, generate a base image
  const baseResult = await openaiProvider.imageGenerate({
    prompt: 'A simple white cat sitting on a red cushion',
    model: 'gpt-image-1',
    quality: 'low',
    size: '1024x1024'
  });
  const baseImageBuffer = Buffer.from(baseResult.images[0].b64_json!, 'base64');
  // Now edit it
  const editResult = await openaiProvider.imageEdit({
    image: baseImageBuffer,
    prompt: 'Change the cat to orange and add stylish sunglasses',
    model: 'gpt-image-1',
    quality: 'medium'
  });
  console.log('Image Editing:');
  console.log('- Base image created');
  console.log('- Edit: change color and add sunglasses');
  console.log('- Result images:', editResult.images.length);
  await saveImageResult('image_edit', editResult);
  expect(editResult.images.length).toEqual(1);
  expect(editResult.images[0].b64_json).toBeTruthy();
 });
 tap.test('OpenAI Image: should clean up provider', async () => {
  await openaiProvider.stop();
  console.log('OpenAI image provider stopped successfully');
 });
 export default tap.start();
--- a/test/test.interfaces.ts
+++ b/test/test.interfaces.ts
@@ -0,0 +1,140 @@
 import { tap, expect } from '@push.rocks/tapbundle';
 import * as smartai from '../ts/index.js';
 // Test interface exports and type checking
 // These tests verify that all interfaces are properly exported and usable
 tap.test('Interfaces: ResearchOptions should be properly typed', async () => {
  const testOptions: smartai.ResearchOptions = {
    query: 'test query',
    searchDepth: 'basic',
    maxSources: 10,
    includeWebSearch: true,
    background: false
  };
  expect(testOptions).toBeInstanceOf(Object);
  expect(testOptions.query).toEqual('test query');
  expect(testOptions.searchDepth).toEqual('basic');
 });
 tap.test('Interfaces: ResearchResponse should be properly typed', async () => {
  const testResponse: smartai.ResearchResponse = {
    answer: 'test answer',
    sources: [
      {
        url: 'https://example.com',
        title: 'Example Source',
        snippet: 'This is a snippet'
      }
    ],
    searchQueries: ['query1', 'query2'],
    metadata: {
      model: 'test-model',
      tokensUsed: 100
    }
  };
  expect(testResponse).toBeInstanceOf(Object);
  expect(testResponse.answer).toEqual('test answer');
  expect(testResponse.sources).toBeArray();
  expect(testResponse.sources[0].url).toEqual('https://example.com');
 });
 tap.test('Interfaces: ChatOptions should be properly typed', async () => {
  const testChatOptions: smartai.ChatOptions = {
    systemMessage: 'You are a helpful assistant',
    userMessage: 'Hello',
    messageHistory: [
      { role: 'user', content: 'Previous message' },
      { role: 'assistant', content: 'Previous response' }
    ]
  };
  expect(testChatOptions).toBeInstanceOf(Object);
  expect(testChatOptions.systemMessage).toBeTruthy();
  expect(testChatOptions.messageHistory).toBeArray();
 });
 tap.test('Interfaces: ChatResponse should be properly typed', async () => {
  const testChatResponse: smartai.ChatResponse = {
    role: 'assistant',
    message: 'This is a response'
  };
  expect(testChatResponse).toBeInstanceOf(Object);
  expect(testChatResponse.role).toEqual('assistant');
  expect(testChatResponse.message).toBeTruthy();
 });
 tap.test('Interfaces: ChatMessage should be properly typed', async () => {
  const testMessage: smartai.ChatMessage = {
    role: 'user',
    content: 'Test message'
  };
  expect(testMessage).toBeInstanceOf(Object);
  expect(testMessage.role).toBeOneOf(['user', 'assistant', 'system']);
  expect(testMessage.content).toBeTruthy();
 });
 tap.test('Interfaces: Provider options should be properly typed', async () => {
  // OpenAI options
  const openaiOptions: smartai.IOpenaiProviderOptions = {
    openaiToken: 'test-token',
    chatModel: 'gpt-5-mini',
    audioModel: 'tts-1-hd',
    visionModel: '04-mini',
    researchModel: 'o4-mini-deep-research-2025-06-26',
    enableWebSearch: true
  };
  expect(openaiOptions).toBeInstanceOf(Object);
  expect(openaiOptions.openaiToken).toBeTruthy();
  // Anthropic options
  const anthropicOptions: smartai.IAnthropicProviderOptions = {
    anthropicToken: 'test-token',
    enableWebSearch: true,
    searchDomainAllowList: ['example.com'],
    searchDomainBlockList: ['blocked.com']
  };
  expect(anthropicOptions).toBeInstanceOf(Object);
  expect(anthropicOptions.anthropicToken).toBeTruthy();
 });
 tap.test('Interfaces: Search depth values should be valid', async () => {
  const validDepths: smartai.ResearchOptions['searchDepth'][] = ['basic', 'advanced', 'deep'];
  for (const depth of validDepths) {
    const options: smartai.ResearchOptions = {
      query: 'test',
      searchDepth: depth
    };
    expect(options.searchDepth).toBeOneOf(['basic', 'advanced', 'deep', undefined]);
  }
 });
 tap.test('Interfaces: Optional properties should work correctly', async () => {
  // Minimal ResearchOptions
  const minimalOptions: smartai.ResearchOptions = {
    query: 'test query'
  };
  expect(minimalOptions.query).toBeTruthy();
  expect(minimalOptions.searchDepth).toBeUndefined();
  expect(minimalOptions.maxSources).toBeUndefined();
  // Minimal ChatOptions
  const minimalChat: smartai.ChatOptions = {
    systemMessage: 'system',
    userMessage: 'user',
    messageHistory: []
  };
  expect(minimalChat.messageHistory).toBeArray();
  expect(minimalChat.messageHistory.length).toEqual(0);
 });
 export default tap.start();
--- a/test/test.openai.ts
+++ b/test/test.openai.ts
@@ -1,4 +1,4 @@
-import { expect, expectAsync, tap } from '@push.rocks/tapbundle';
+import { expect, 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';
@@ -9,14 +9,14 @@ import * as smartai from '../ts/index.js';
 let testSmartai: smartai.SmartAi;
-tap.test('should create a smartai instance', async () => {
+tap.test('OpenAI: should create a smartai instance with OpenAI provider', async () => {
  testSmartai = new smartai.SmartAi({
    openaiToken: await testQenv.getEnvVarOnDemand('OPENAI_TOKEN'),
  });
  await testSmartai.start();
 });
-tap.test('should create chat response with openai', async () => {
+tap.test('OpenAI: should create chat response', async () => {
  const userMessage = 'How are you?';
  const response = await testSmartai.openaiProvider.chat({
    systemMessage: 'Hello',
@@ -27,19 +27,21 @@ tap.test('should create chat response with openai', async () => {
  console.log(response.message);
 });
-tap.test('should document a pdf', async () => {
+tap.test('OpenAI: 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 pdfResponse = await smartrequest.SmartRequest.create()
    .url(pdfUrl)
    .get();
  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],
+    pdfDocuments: [Buffer.from(await pdfResponse.arrayBuffer())],
  });
  console.log(result);
 });
-tap.test('should recognize companies in a pdf', async () => {
+tap.test('OpenAI: 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: `
@@ -76,7 +78,7 @@ tap.test('should recognize companies in a pdf', async () => {
  console.log(result);
 });
-tap.test('should create audio response with openai', async () => {
+tap.test('OpenAI: should create audio response', async () => {
  // Call the audio method with a sample message.
  const audioStream = await testSmartai.openaiProvider.audio({
    message: 'This is a test of audio generation.',
@@ -93,7 +95,7 @@ tap.test('should create audio response with openai', async () => {
  expect(audioBuffer.length).toBeGreaterThan(0);
 });
-tap.test('should stop the smartai instance', async () => {
+tap.test('OpenAI: should stop the smartai instance', async () => {
  await testSmartai.stop();
 });
--- a/test/test.research.anthropic.ts
+++ b/test/test.research.anthropic.ts
@@ -0,0 +1,223 @@
 import { expect, tap } from '@push.rocks/tapbundle';
 import * as qenv from '@push.rocks/qenv';
 import * as smartai from '../ts/index.js';
 import * as path from 'path';
 import { promises as fs } from 'fs';
 const testQenv = new qenv.Qenv('./', './.nogit/');
 // Helper function to save research results
 async function saveResearchResult(testName: string, result: any) {
  const sanitizedName = testName.replace(/[^a-z0-9]/gi, '_').toLowerCase();
  const timestamp = new Date().toISOString().replace(/[:.]/g, '-');
  const filename = `${sanitizedName}_${timestamp}.json`;
  const filepath = path.join('.nogit', 'testresults', 'research', filename);
  await fs.mkdir(path.dirname(filepath), { recursive: true });
  await fs.writeFile(filepath, JSON.stringify(result, null, 2), 'utf-8');
  console.log(`  💾 Saved to: ${filepath}`);
 }
 let anthropicProvider: smartai.AnthropicProvider;
 tap.test('Anthropic Research: should initialize provider with web search', async () => {
  anthropicProvider = new smartai.AnthropicProvider({
    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
    enableWebSearch: true
  });
  await anthropicProvider.start();
  expect(anthropicProvider).toBeInstanceOf(smartai.AnthropicProvider);
  expect(typeof anthropicProvider.research).toEqual('function');
 });
 tap.test('Anthropic Research: should perform basic research query', async () => {
  const result = await anthropicProvider.research({
    query: 'What is machine learning and its main applications?',
    searchDepth: 'basic'
  });
  console.log('Anthropic Basic Research:');
  console.log('- Answer length:', result.answer.length);
  console.log('- Sources found:', result.sources.length);
  console.log('- First 200 chars:', result.answer.substring(0, 200));
  await saveResearchResult('basic_research_machine_learning', result);
  expect(result).toBeTruthy();
  expect(result.answer).toBeTruthy();
  expect(result.answer.toLowerCase()).toInclude('machine learning');
  expect(result.sources).toBeArray();
  expect(result.metadata).toBeTruthy();
 });
 tap.test('Anthropic Research: should perform research with web search', async () => {
  const result = await anthropicProvider.research({
    query: 'What are the latest developments in renewable energy technology?',
    searchDepth: 'advanced',
    includeWebSearch: true,
    maxSources: 5
  });
  console.log('Anthropic Web Search Research:');
  console.log('- Answer length:', result.answer.length);
  console.log('- Sources:', result.sources.length);
  if (result.searchQueries) {
    console.log('- Search queries:', result.searchQueries);
  }
  await saveResearchResult('web_search_renewable_energy', result);
  expect(result.answer).toBeTruthy();
  expect(result.answer.toLowerCase()).toInclude('renewable');
  // Check if sources were extracted
  if (result.sources.length > 0) {
    console.log('- Example source:', result.sources[0]);
    expect(result.sources[0]).toHaveProperty('url');
  }
 });
 tap.test('Anthropic Research: should handle deep research queries', async () => {
  const result = await anthropicProvider.research({
    query: 'Explain the differences between REST and GraphQL APIs',
    searchDepth: 'deep'
  });
  console.log('Anthropic Deep Research:');
  console.log('- Answer length:', result.answer.length);
  console.log('- Token usage:', result.metadata?.tokensUsed);
  await saveResearchResult('deep_research_rest_vs_graphql', result);
  expect(result.answer).toBeTruthy();
  expect(result.answer.length).toBeGreaterThan(300);
  expect(result.answer.toLowerCase()).toInclude('rest');
  expect(result.answer.toLowerCase()).toInclude('graphql');
 });
 tap.test('Anthropic Research: should extract citations from response', async () => {
  const result = await anthropicProvider.research({
    query: 'What is Docker and how does containerization work?',
    searchDepth: 'basic',
    maxSources: 3
  });
  console.log('Anthropic Citation Extraction:');
  console.log('- Sources found:', result.sources.length);
  console.log('- Answer includes Docker:', result.answer.toLowerCase().includes('docker'));
  await saveResearchResult('citation_extraction_docker', result);
  expect(result.answer).toInclude('Docker');
  // Check for URL extraction (both markdown and plain URLs)
  const hasUrls = result.answer.includes('http') || result.sources.length > 0;
  console.log('- Contains URLs or sources:', hasUrls);
 });
 tap.test('Anthropic Research: should use domain filtering when configured', async () => {
  // Create a new provider with domain restrictions
  const filteredProvider = new smartai.AnthropicProvider({
    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
    enableWebSearch: true,
    searchDomainAllowList: ['wikipedia.org', 'docs.microsoft.com'],
    searchDomainBlockList: ['reddit.com']
  });
  await filteredProvider.start();
  const result = await filteredProvider.research({
    query: 'What is JavaScript?',
    searchDepth: 'basic'
  });
  console.log('Anthropic Domain Filtering Test:');
  console.log('- Answer length:', result.answer.length);
  console.log('- Applied domain filters (allow: wikipedia, docs.microsoft)');
  await saveResearchResult('domain_filtering_javascript', result);
  expect(result.answer).toBeTruthy();
  expect(result.answer.toLowerCase()).toInclude('javascript');
  await filteredProvider.stop();
 });
 tap.test('Anthropic Research: should handle errors gracefully', async () => {
  let errorCaught = false;
  try {
    await anthropicProvider.research({
      query: '', // Empty query
      searchDepth: 'basic'
    });
  } catch (error) {
    errorCaught = true;
    console.log('Expected error for empty query:', error.message.substring(0, 100));
  }
  // Anthropic might handle empty queries differently
  console.log(`Empty query error test - Error caught: ${errorCaught}`);
 });
 tap.test('Anthropic Research: should handle different search depths', async () => {
  // Test basic search depth
  const basicResult = await anthropicProvider.research({
    query: 'What is Python?',
    searchDepth: 'basic'
  });
  // Test advanced search depth
  const advancedResult = await anthropicProvider.research({
    query: 'What is Python?',
    searchDepth: 'advanced'
  });
  console.log('Anthropic Search Depth Comparison:');
  console.log('- Basic answer length:', basicResult.answer.length);
  console.log('- Advanced answer length:', advancedResult.answer.length);
  console.log('- Basic tokens:', basicResult.metadata?.tokensUsed);
  console.log('- Advanced tokens:', advancedResult.metadata?.tokensUsed);
  await saveResearchResult('search_depth_python_basic', basicResult);
  await saveResearchResult('search_depth_python_advanced', advancedResult);
  expect(basicResult.answer).toBeTruthy();
  expect(advancedResult.answer).toBeTruthy();
  // Advanced search typically produces longer answers
  // But this isn't guaranteed, so we just check they exist
  expect(basicResult.answer.toLowerCase()).toInclude('python');
  expect(advancedResult.answer.toLowerCase()).toInclude('python');
 });
 tap.test('Anthropic Research: ARM vs. Qualcomm comparison', async () => {
  const result = await anthropicProvider.research({
    query: 'Compare ARM and Qualcomm: their technologies, market positions, and recent developments in the mobile and computing sectors',
    searchDepth: 'advanced',
    includeWebSearch: true,
    maxSources: 10
  });
  console.log('ARM vs. Qualcomm Research:');
  console.log('- Answer length:', result.answer.length);
  console.log('- Sources found:', result.sources.length);
  console.log('- First 300 chars:', result.answer.substring(0, 300));
  await saveResearchResult('arm_vs_qualcomm_comparison', result);
  expect(result.answer).toBeTruthy();
  expect(result.answer.length).toBeGreaterThan(500);
  expect(result.answer.toLowerCase()).toInclude('arm');
  expect(result.answer.toLowerCase()).toInclude('qualcomm');
  expect(result.sources.length).toBeGreaterThan(0);
 });
 tap.test('Anthropic Research: should clean up provider', async () => {
  await anthropicProvider.stop();
  console.log('Anthropic research provider stopped successfully');
 });
 export default tap.start();
--- a/test/test.research.openai.ts
+++ b/test/test.research.openai.ts
@@ -0,0 +1,172 @@
 import { expect, tap } from '@push.rocks/tapbundle';
 import * as qenv from '@push.rocks/qenv';
 import * as smartai from '../ts/index.js';
 import * as path from 'path';
 import { promises as fs } from 'fs';
 const testQenv = new qenv.Qenv('./', './.nogit/');
 // Helper function to save research results
 async function saveResearchResult(testName: string, result: any) {
  const sanitizedName = testName.replace(/[^a-z0-9]/gi, '_').toLowerCase();
  const timestamp = new Date().toISOString().replace(/[:.]/g, '-');
  const filename = `openai_${sanitizedName}_${timestamp}.json`;
  const filepath = path.join('.nogit', 'testresults', 'research', filename);
  await fs.mkdir(path.dirname(filepath), { recursive: true });
  await fs.writeFile(filepath, JSON.stringify(result, null, 2), 'utf-8');
  console.log(`  💾 Saved to: ${filepath}`);
 }
 let openaiProvider: smartai.OpenAiProvider;
 tap.test('OpenAI Research: should initialize provider with research capabilities', async () => {
  openaiProvider = new smartai.OpenAiProvider({
    openaiToken: await testQenv.getEnvVarOnDemand('OPENAI_TOKEN'),
    researchModel: 'o4-mini-deep-research-2025-06-26',
    enableWebSearch: true
  });
  await openaiProvider.start();
  expect(openaiProvider).toBeInstanceOf(smartai.OpenAiProvider);
  expect(typeof openaiProvider.research).toEqual('function');
 });
 tap.test('OpenAI Research: should perform basic research query', async () => {
  const result = await openaiProvider.research({
    query: 'What is TypeScript and why is it useful for web development?',
    searchDepth: 'basic'
  });
  console.log('OpenAI Basic Research:');
  console.log('- Answer length:', result.answer.length);
  console.log('- Sources found:', result.sources.length);
  console.log('- First 200 chars:', result.answer.substring(0, 200));
  await saveResearchResult('basic_research_typescript', result);
  expect(result).toBeTruthy();
  expect(result.answer).toBeTruthy();
  expect(result.answer.toLowerCase()).toInclude('typescript');
  expect(result.sources).toBeArray();
  expect(result.metadata).toBeTruthy();
  expect(result.metadata.model).toBeTruthy();
 });
 tap.test('OpenAI Research: should perform research with web search enabled', async () => {
  const result = await openaiProvider.research({
    query: 'What are the latest features in ECMAScript 2024?',
    searchDepth: 'advanced',
    includeWebSearch: true,
    maxSources: 5
  });
  console.log('OpenAI Web Search Research:');
  console.log('- Answer length:', result.answer.length);
  console.log('- Sources:', result.sources.length);
  if (result.searchQueries) {
    console.log('- Search queries used:', result.searchQueries);
  }
  await saveResearchResult('web_search_ecmascript', result);
  expect(result.answer).toBeTruthy();
  expect(result.answer.toLowerCase()).toInclude('ecmascript');
  // The model might include sources or search queries
  if (result.sources.length > 0) {
    expect(result.sources[0]).toHaveProperty('url');
    expect(result.sources[0]).toHaveProperty('title');
  }
 });
 tap.test('OpenAI Research: should handle deep research for complex topics', async () => {
  // Skip this test if it takes too long or costs too much
  // You can enable it for thorough testing
  const skipDeepResearch = true;
  if (skipDeepResearch) {
    console.log('Skipping deep research test to save API costs');
    return;
  }
  const result = await openaiProvider.research({
    query: 'Compare the pros and cons of microservices vs monolithic architecture',
    searchDepth: 'deep',
    includeWebSearch: true
  });
  console.log('OpenAI Deep Research:');
  console.log('- Answer length:', result.answer.length);
  console.log('- Token usage:', result.metadata?.tokensUsed);
  expect(result.answer).toBeTruthy();
  expect(result.answer.length).toBeGreaterThan(500);
  expect(result.answer.toLowerCase()).toInclude('microservices');
  expect(result.answer.toLowerCase()).toInclude('monolithic');
 });
 tap.test('OpenAI Research: should extract sources from markdown links', async () => {
  const result = await openaiProvider.research({
    query: 'What is Node.js and provide some official documentation links?',
    searchDepth: 'basic',
    maxSources: 3
  });
  console.log('OpenAI Source Extraction:');
  console.log('- Sources found:', result.sources.length);
  await saveResearchResult('source_extraction_nodejs', result);
  if (result.sources.length > 0) {
    console.log('- Example source:', result.sources[0]);
    expect(result.sources[0].url).toBeTruthy();
    expect(result.sources[0].title).toBeTruthy();
  }
  expect(result.answer).toInclude('Node.js');
 });
 tap.test('OpenAI Research: should handle research errors gracefully', async () => {
  // Test with an extremely long query that might cause issues
  const longQuery = 'a'.repeat(10000);
  let errorCaught = false;
  try {
    await openaiProvider.research({
      query: longQuery,
      searchDepth: 'basic'
    });
  } catch (error) {
    errorCaught = true;
    console.log('Expected error for long query:', error.message.substring(0, 100));
    expect(error.message).toBeTruthy();
  }
  // OpenAI might handle long queries, so we don't assert the error
  console.log(`Long query error test - Error caught: ${errorCaught}`);
 });
 tap.test('OpenAI Research: should respect maxSources parameter', async () => {
  const maxSources = 3;
  const result = await openaiProvider.research({
    query: 'List popular JavaScript frameworks',
    searchDepth: 'basic',
    maxSources: maxSources
  });
  console.log(`OpenAI Max Sources Test - Requested: ${maxSources}, Found: ${result.sources.length}`);
  // The API might not always return exactly maxSources, but should respect it as a limit
  if (result.sources.length > 0) {
    expect(result.sources.length).toBeLessThanOrEqual(maxSources * 2); // Allow some flexibility
  }
 });
 tap.test('OpenAI Research: should clean up provider', async () => {
  await openaiProvider.stop();
  console.log('OpenAI research provider stopped successfully');
 });
 export default tap.start();
--- a/test/test.research.stubs.ts
+++ b/test/test.research.stubs.ts
@@ -0,0 +1,80 @@
 import { tap, expect } from '@push.rocks/tapbundle';
 import * as smartai from '../ts/index.js';
 // Test research method stubs for providers without full implementation
 // These providers have research methods that throw "not yet supported" errors
 tap.test('Research Stubs: Perplexity provider should have research method', async () => {
  const perplexityProvider = new smartai.PerplexityProvider({
    perplexityToken: 'test-token'
  });
  // Perplexity has a basic implementation with Sonar models
  expect(typeof perplexityProvider.research).toEqual('function');
 });
 tap.test('Research Stubs: Groq provider should throw not supported error', async () => {
  const groqProvider = new smartai.GroqProvider({
    groqToken: 'test-token'
  });
  expect(typeof groqProvider.research).toEqual('function');
  let errorCaught = false;
  try {
    await groqProvider.research({ query: 'test' });
  } catch (error) {
    errorCaught = true;
    expect(error.message).toInclude('not yet supported');
  }
  expect(errorCaught).toBeTrue();
 });
 tap.test('Research Stubs: Ollama provider should throw not supported error', async () => {
  const ollamaProvider = new smartai.OllamaProvider({});
  expect(typeof ollamaProvider.research).toEqual('function');
  let errorCaught = false;
  try {
    await ollamaProvider.research({ query: 'test' });
  } catch (error) {
    errorCaught = true;
    expect(error.message).toInclude('not yet supported');
  }
  expect(errorCaught).toBeTrue();
 });
 tap.test('Research Stubs: xAI provider should throw not supported error', async () => {
  const xaiProvider = new smartai.XAIProvider({
    xaiToken: 'test-token'
  });
  expect(typeof xaiProvider.research).toEqual('function');
  let errorCaught = false;
  try {
    await xaiProvider.research({ query: 'test' });
  } catch (error) {
    errorCaught = true;
    expect(error.message).toInclude('not yet supported');
  }
  expect(errorCaught).toBeTrue();
 });
 tap.test('Research Stubs: Exo provider should throw not supported error', async () => {
  const exoProvider = new smartai.ExoProvider({});
  expect(typeof exoProvider.research).toEqual('function');
  let errorCaught = false;
  try {
    await exoProvider.research({ query: 'test' });
  } catch (error) {
    errorCaught = true;
    expect(error.message).toInclude('not yet supported');
  }
  expect(errorCaught).toBeTrue();
 });
 export default tap.start();
--- a/test/testimages/coffee-dani/README.md
+++ b/test/testimages/coffee-dani/README.md
@@ -0,0 +1,36 @@
 # Coffee Image Attribution
 ## coffee.jpg
 **Photographer:** Dani (@frokz)
 **Source URL:** https://unsplash.com/photos/cup-of-coffee-on-saucer-ZLqxSzvVr7I
 **Direct Link:** https://images.unsplash.com/photo-1506372023823-741c83b836fe
 ### Metadata
 - **Title:** Cup of coffee on saucer
 - **Description:** One of many coffee-moments in my life ;)
 - **Date Published:** September 25, 2017
 - **Location:** Stockholm, Sweden
 - **Tags:** coffee, cafe, heart, coffee cup, cup, barista, latte, mug, saucer, food, sweden, stockholm
 ### License
 **Unsplash License** - Free to use
 - ✅ Commercial and non-commercial use
 - ✅ No permission needed
 - ❌ Cannot be sold without significant modification
 - ❌ Cannot be used to replicate Unsplash or similar service
 Full license: https://unsplash.com/license
 ### Usage in This Project
 This image is used for testing vision/image processing capabilities in the SmartAI library test suite, specifically for:
 - Testing coffee/beverage recognition
 - Latte art pattern detection (heart shape)
 - Scene/environment analysis
 - Multi-element image understanding (cup, saucer, table)
 ### Download Information
 - **Downloaded:** September 28, 2025
 - **Original Filename:** dani-ZLqxSzvVr7I-unsplash.jpg
 - **Resolution:** High resolution (3.7 MB)
 - **Format:** JPEG
--- a/test/testimages/coffee-dani/coffee.jpg
+++ b/test/testimages/coffee-dani/coffee.jpg
--- a/test/testimages/laptop-nicolas/README.md
+++ b/test/testimages/laptop-nicolas/README.md
@@ -0,0 +1,40 @@
 # Laptop Image Attribution
 ## laptop.jpg
 **Photographer:** Nicolas Bichon (@nicol3a)
 **Source URL:** https://unsplash.com/photos/a-laptop-computer-sitting-on-top-of-a-wooden-desk-ZhV4iqAXxyA
 **Direct Link:** https://images.unsplash.com/photo-1704230972797-e0e3aba0fce7
 ### Metadata
 - **Title:** A laptop computer sitting on top of a wooden desk
 - **Description:** Lifestyle photo I took for my indie app Type, a macOS app to take notes without interrupting your flow. https://usetype.app.
 - **Date Published:** January 2, 2024
 - **Camera:** FUJIFILM, X-T20
 - **Tags:** computer, laptop, mac, keyboard, computer keyboard, computer hardware, furniture, table, electronics, screen, monitor, hardware, display, tabletop, lcd screen, digital display
 ### Statistics
 - **Views:** 183,020
 - **Downloads:** 757
 ### License
 **Unsplash License** - Free to use
 - ✅ Commercial and non-commercial use
 - ✅ No permission needed
 - ❌ Cannot be sold without significant modification
 - ❌ Cannot be used to replicate Unsplash or similar service
 Full license: https://unsplash.com/license
 ### Usage in This Project
 This image is used for testing vision/image processing capabilities in the SmartAI library test suite, specifically for:
 - Testing technology/computer equipment recognition
 - Workspace/office environment analysis
 - Object detection (laptop, keyboard, monitor, table)
 - Scene understanding and context analysis
 ### Download Information
 - **Downloaded:** September 28, 2025
 - **Original Filename:** nicolas-bichon-ZhV4iqAXxyA-unsplash.jpg
 - **Resolution:** High resolution (1.8 MB)
 - **Format:** JPEG
--- a/test/testimages/laptop-nicolas/laptop.jpg
+++ b/test/testimages/laptop-nicolas/laptop.jpg
--- a/test/testimages/receipt-annie/README.md
+++ b/test/testimages/receipt-annie/README.md
@@ -0,0 +1,40 @@
 # Receipt Image Attribution
 ## receipt.jpg
 **Photographer:** Annie Spratt (@anniespratt)
 **Source URL:** https://unsplash.com/photos/a-receipt-sitting-on-top-of-a-wooden-table-recgFWxDO1Y
 **Direct Link:** https://images.unsplash.com/photo-1731686602391-7484df33a03c
 ### Metadata
 - **Title:** A receipt sitting on top of a wooden table
 - **Description:** Download this free HD photo of text, document, invoice, and receipt by Annie Spratt
 - **Date Published:** November 15, 2024
 - **Tags:** text, document, invoice, receipt, diaper
 ### Statistics
 - **Views:** 54,593
 - **Downloads:** 764
 ### License
 **Unsplash License** - Free to use
 - ✅ Commercial and non-commercial use
 - ✅ No permission needed
 - ❌ Cannot be sold without significant modification
 - ❌ Cannot be used to replicate Unsplash or similar service
 Full license: https://unsplash.com/license
 ### Usage in This Project
 This image is used for testing vision/image processing capabilities in the SmartAI library test suite, specifically for:
 - Testing text extraction and OCR capabilities
 - Document recognition and classification
 - Receipt/invoice analysis
 - Text-heavy image understanding
 - Structured data extraction from documents
 ### Download Information
 - **Downloaded:** September 28, 2025
 - **Original Filename:** annie-spratt-recgFWxDO1Y-unsplash.jpg
 - **Resolution:** High resolution (3.3 MB)
 - **Format:** JPEG
--- a/test/testimages/receipt-annie/receipt.jpg
+++ b/test/testimages/receipt-annie/receipt.jpg
--- a/ts/00_commitinfo_data.ts
+++ b/ts/00_commitinfo_data.ts
@@ -3,6 +3,6 @@
 */
 export const commitinfo = {
  name: '@push.rocks/smartai',
-  version: '0.5.2',
+  version: '0.7.1',
  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.'
 }
--- a/ts/abstract.classes.multimodal.ts
+++ b/ts/abstract.classes.multimodal.ts
@@ -1,3 +1,5 @@
 import * as plugins from './plugins.js';
 /**
 * Message format for chat interactions
 */
@@ -23,22 +25,114 @@ export interface ChatResponse {
  message: string;
 }
 /**
 * Options for research interactions
 */
 export interface ResearchOptions {
  query: string;
  searchDepth?: 'basic' | 'advanced' | 'deep';
  maxSources?: number;
  includeWebSearch?: boolean;
  background?: boolean;
 }
 /**
 * Response format for research interactions
 */
 export interface ResearchResponse {
  answer: string;
  sources: Array<{
    url: string;
    title: string;
    snippet: string;
  }>;
  searchQueries?: string[];
  metadata?: any;
 }
 /**
 * Options for image generation
 */
 export interface ImageGenerateOptions {
  prompt: string;
  model?: 'gpt-image-1' | 'dall-e-3' | 'dall-e-2';
  quality?: 'low' | 'medium' | 'high' | 'standard' | 'hd' | 'auto';
  size?: '256x256' | '512x512' | '1024x1024' | '1536x1024' | '1024x1536' | '1792x1024' | '1024x1792' | 'auto';
  style?: 'vivid' | 'natural';
  background?: 'transparent' | 'opaque' | 'auto';
  outputFormat?: 'png' | 'jpeg' | 'webp';
  outputCompression?: number; // 0-100 for webp/jpeg
  moderation?: 'low' | 'auto';
  n?: number; // Number of images to generate
  stream?: boolean;
  partialImages?: number; // 0-3 for streaming
 }
 /**
 * Options for image editing
 */
 export interface ImageEditOptions {
  image: Buffer;
  prompt: string;
  mask?: Buffer;
  model?: 'gpt-image-1' | 'dall-e-2';
  quality?: 'low' | 'medium' | 'high' | 'standard' | 'auto';
  size?: '256x256' | '512x512' | '1024x1024' | '1536x1024' | '1024x1536' | 'auto';
  background?: 'transparent' | 'opaque' | 'auto';
  outputFormat?: 'png' | 'jpeg' | 'webp';
  outputCompression?: number;
  n?: number;
  stream?: boolean;
  partialImages?: number;
 }
 /**
 * Response format for image operations
 */
 export interface ImageResponse {
  images: Array<{
    b64_json?: string;
    url?: string;
    revisedPrompt?: string;
  }>;
  metadata?: {
    model: string;
    quality?: string;
    size?: string;
    outputFormat?: string;
    tokensUsed?: number;
  };
 }
 /**
 * Abstract base class for multi-modal AI models.
 * Provides a common interface for different AI providers (OpenAI, Anthropic, Perplexity, Ollama)
 */
 export abstract class MultiModalModel {
  /**
   * SmartPdf instance for document processing
   * Shared across all methods that need PDF functionality
   */
  protected smartpdfInstance: plugins.smartpdf.SmartPdf;
  /**
   * Initializes the model and any necessary resources
   * Should be called before using any other methods
   */
-  abstract start(): Promise<void>;
+  public async start(): Promise<void> {
    this.smartpdfInstance = new plugins.smartpdf.SmartPdf();
    await this.smartpdfInstance.start();
  }
  /**
   * Cleans up any resources used by the model
   * Should be called when the model is no longer needed
   */
-  abstract stop(): Promise<void>;
+  public async stop(): Promise<void> {
    if (this.smartpdfInstance) {
      await this.smartpdfInstance.stop();
    }
  }
  /**
   * Synchronous chat interaction with the model
@@ -83,4 +177,28 @@ export abstract class MultiModalModel {
    pdfDocuments: Uint8Array[];
    messageHistory: ChatMessage[];
  }): Promise<{ message: any }>;
  /**
   * Research and web search capabilities
   * @param optionsArg Options containing the research query and configuration
   * @returns Promise resolving to the research results with sources
   * @throws Error if the provider doesn't support research capabilities
   */
  public abstract research(optionsArg: ResearchOptions): Promise<ResearchResponse>;
  /**
   * Image generation from text prompts
   * @param optionsArg Options containing the prompt and generation parameters
   * @returns Promise resolving to the generated image(s)
   * @throws Error if the provider doesn't support image generation
   */
  public abstract imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse>;
  /**
   * Image editing and inpainting
   * @param optionsArg Options containing the image, prompt, and editing parameters
   * @returns Promise resolving to the edited image(s)
   * @throws Error if the provider doesn't support image editing
   */
  public abstract imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse>;
 }
--- a/ts/classes.smartai.ts
+++ b/ts/classes.smartai.ts
@@ -91,7 +91,29 @@ export class SmartAi {
    }
  }
-  public async stop() {}
+  public async stop() {
    if (this.openaiProvider) {
      await this.openaiProvider.stop();
    }
    if (this.anthropicProvider) {
      await this.anthropicProvider.stop();
    }
    if (this.perplexityProvider) {
      await this.perplexityProvider.stop();
    }
    if (this.groqProvider) {
      await this.groqProvider.stop();
    }
    if (this.xaiProvider) {
      await this.xaiProvider.stop();
    }
    if (this.ollamaProvider) {
      await this.ollamaProvider.stop();
    }
    if (this.exoProvider) {
      await this.exoProvider.stop();
    }
  }
  /**
   * create a new conversation
--- a/ts/index.ts
+++ b/ts/index.ts
@@ -1,3 +1,9 @@
 export * from './classes.smartai.js';
 export * from './abstract.classes.multimodal.js';
 export * from './provider.openai.js';
 export * from './provider.anthropic.js';
 export * from './provider.perplexity.js';
 export * from './provider.groq.js';
 export * from './provider.ollama.js';
 export * from './provider.xai.js';
 export * from './provider.exo.js';
--- a/ts/provider.anthropic.ts
+++ b/ts/provider.anthropic.ts
@@ -1,13 +1,25 @@
 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 {
  ChatOptions,
  ChatResponse,
  ChatMessage,
  ResearchOptions,
  ResearchResponse,
  ImageGenerateOptions,
  ImageEditOptions,
  ImageResponse
 } from './abstract.classes.multimodal.js';
 import type { ImageBlockParam, TextBlockParam } from '@anthropic-ai/sdk/resources/messages';
 type ContentBlock = ImageBlockParam | TextBlockParam;
 export interface IAnthropicProviderOptions {
  anthropicToken: string;
  enableWebSearch?: boolean;
  searchDomainAllowList?: string[];
  searchDomainBlockList?: string[];
 }
 export class AnthropicProvider extends MultiModalModel {
@@ -20,12 +32,15 @@ export class AnthropicProvider extends MultiModalModel {
  }
  async start() {
    await super.start();
    this.anthropicApiClient = new plugins.anthropic.default({
      apiKey: this.options.anthropicToken,
    });
  }
-  async stop() {}
+  async stop() {
    await super.stop();
  }
  public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
    // Create a TextDecoder to handle incoming chunks
@@ -62,7 +77,7 @@ export class AnthropicProvider extends MultiModalModel {
        // If we have a complete message, send it to Anthropic
        if (currentMessage) {
          const stream = await this.anthropicApiClient.messages.create({
-            model: 'claude-3-opus-20240229',
+            model: 'claude-sonnet-4-5-20250929',
            messages: [{ role: currentMessage.role, content: currentMessage.content }],
            system: '',
            stream: true,
@@ -106,7 +121,7 @@ export class AnthropicProvider extends MultiModalModel {
    }));
    const result = await this.anthropicApiClient.messages.create({
-      model: 'claude-3-opus-20240229',
+      model: 'claude-sonnet-4-5-20250929',
      system: optionsArg.systemMessage,
      messages: [
        ...messages,
@@ -153,7 +168,7 @@ export class AnthropicProvider extends MultiModalModel {
    ];
    const result = await this.anthropicApiClient.messages.create({
-      model: 'claude-3-opus-20240229',
+      model: 'claude-sonnet-4-5-20250929',
      messages: [{
        role: 'user',
        content
@@ -178,11 +193,10 @@ export class AnthropicProvider extends MultiModalModel {
    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);
+      const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument);
      documentImageBytesArray = documentImageBytesArray.concat(documentImageArray);
    }
@@ -213,7 +227,7 @@ export class AnthropicProvider extends MultiModalModel {
    }
    const result = await this.anthropicApiClient.messages.create({
-      model: 'claude-3-opus-20240229',
+      model: 'claude-sonnet-4-5-20250929',
      system: optionsArg.systemMessage,
      messages: [
        ...messages,
@@ -237,4 +251,155 @@ export class AnthropicProvider extends MultiModalModel {
      }
    };
  }
  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
    // Prepare the messages for the research request
    const systemMessage = `You are a research assistant with web search capabilities.
    Provide comprehensive, well-researched answers with citations and sources.
    When searching the web, be thorough and cite your sources accurately.`;
    try {
      // Build the tool configuration for web search
      const tools: any[] = [];
      if (this.options.enableWebSearch) {
        const webSearchTool: any = {
          type: 'web_search_20250305',
          name: 'web_search'
        };
        // Add optional parameters
        if (optionsArg.maxSources) {
          webSearchTool.max_uses = optionsArg.maxSources;
        }
        if (this.options.searchDomainAllowList?.length) {
          webSearchTool.allowed_domains = this.options.searchDomainAllowList;
        } else if (this.options.searchDomainBlockList?.length) {
          webSearchTool.blocked_domains = this.options.searchDomainBlockList;
        }
        tools.push(webSearchTool);
      }
      // Configure the request based on search depth
      const maxTokens = optionsArg.searchDepth === 'deep' ? 8192 :
                        optionsArg.searchDepth === 'advanced' ? 6144 : 4096;
      // Create the research request
      const requestParams: any = {
        model: 'claude-sonnet-4-5-20250929',
        system: systemMessage,
        messages: [
          {
            role: 'user' as const,
            content: optionsArg.query
          }
        ],
        max_tokens: maxTokens,
        temperature: 0.7
      };
      // Add tools if web search is enabled
      if (tools.length > 0) {
        requestParams.tools = tools;
      }
      // Execute the research request
      const result = await this.anthropicApiClient.messages.create(requestParams);
      // Extract the answer from content blocks
      let answer = '';
      const sources: Array<{ url: string; title: string; snippet: string }> = [];
      const searchQueries: string[] = [];
      // Process content blocks
      for (const block of result.content) {
        if ('text' in block) {
          // Accumulate text content
          answer += block.text;
          // Extract citations if present
          if ('citations' in block && Array.isArray(block.citations)) {
            for (const citation of block.citations) {
              if (citation.type === 'web_search_result_location') {
                sources.push({
                  title: citation.title || '',
                  url: citation.url || '',
                  snippet: citation.cited_text || ''
                });
              }
            }
          }
        } else if ('type' in block && block.type === 'server_tool_use') {
          // Extract search queries from server tool use
          if (block.name === 'web_search' && block.input && typeof block.input === 'object' && 'query' in block.input) {
            searchQueries.push((block.input as any).query);
          }
        } else if ('type' in block && block.type === 'web_search_tool_result') {
          // Extract sources from web search results
          if (Array.isArray(block.content)) {
            for (const result of block.content) {
              if (result.type === 'web_search_result') {
                // Only add if not already in sources (avoid duplicates from citations)
                if (!sources.some(s => s.url === result.url)) {
                  sources.push({
                    title: result.title || '',
                    url: result.url || '',
                    snippet: '' // Search results don't include snippets, only citations do
                  });
                }
              }
            }
          }
        }
      }
      // Fallback: Parse markdown-style links if no citations found
      if (sources.length === 0) {
        const urlRegex = /\[([^\]]+)\]\(([^)]+)\)/g;
        let match: RegExpExecArray | null;
        while ((match = urlRegex.exec(answer)) !== null) {
          sources.push({
            title: match[1],
            url: match[2],
            snippet: ''
          });
        }
      }
      // Check if web search was used based on usage info
      const webSearchCount = result.usage?.server_tool_use?.web_search_requests || 0;
      return {
        answer,
        sources,
        searchQueries: searchQueries.length > 0 ? searchQueries : undefined,
        metadata: {
          model: 'claude-sonnet-4-5-20250929',
          searchDepth: optionsArg.searchDepth || 'basic',
          tokensUsed: result.usage?.output_tokens,
          webSearchesPerformed: webSearchCount
        }
      };
    } catch (error) {
      console.error('Anthropic research error:', error);
      throw new Error(`Failed to perform research: ${error.message}`);
    }
  }
  /**
   * Image generation is not supported by Anthropic
   */
  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
    throw new Error('Image generation is not supported by Anthropic. Claude can only analyze images, not generate them. Please use OpenAI provider for image generation.');
  }
  /**
   * Image editing is not supported by Anthropic
   */
  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
    throw new Error('Image editing is not supported by Anthropic. Claude can only analyze images, not edit them. Please use OpenAI provider for image editing.');
  }
 }
--- a/ts/provider.exo.ts
+++ b/ts/provider.exo.ts
@@ -1,7 +1,16 @@
 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 {
  ChatOptions,
  ChatResponse,
  ChatMessage,
  ResearchOptions,
  ResearchResponse,
  ImageGenerateOptions,
  ImageEditOptions,
  ImageResponse
 } from './abstract.classes.multimodal.js';
 import type { ChatCompletionMessageParam } from 'openai/resources/chat/completions';
 export interface IExoProviderOptions {
@@ -125,4 +134,22 @@ export class ExoProvider extends MultiModalModel {
  }): Promise<{ message: any }> {
    throw new Error('Document processing is not supported by Exo provider');
  }
  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
    throw new Error('Research capabilities are not yet supported by Exo provider.');
  }
  /**
   * Image generation is not supported by Exo
   */
  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
    throw new Error('Image generation is not supported by Exo. Please use OpenAI provider for image generation.');
  }
  /**
   * Image editing is not supported by Exo
   */
  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
    throw new Error('Image editing is not supported by Exo. Please use OpenAI provider for image editing.');
  }
 }
--- a/ts/provider.groq.ts
+++ b/ts/provider.groq.ts
@@ -1,7 +1,16 @@
 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 {
  ChatOptions,
  ChatResponse,
  ChatMessage,
  ResearchOptions,
  ResearchResponse,
  ImageGenerateOptions,
  ImageEditOptions,
  ImageResponse
 } from './abstract.classes.multimodal.js';
 export interface IGroqProviderOptions {
  groqToken: string;
@@ -189,4 +198,22 @@ export class GroqProvider extends MultiModalModel {
  }): Promise<{ message: any }> {
    throw new Error('Document processing is not yet supported by Groq.');
  }
  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
    throw new Error('Research capabilities are not yet supported by Groq provider.');
  }
  /**
   * Image generation is not supported by Groq
   */
  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
    throw new Error('Image generation is not supported by Groq. Please use OpenAI provider for image generation.');
  }
  /**
   * Image editing is not supported by Groq
   */
  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
    throw new Error('Image editing is not supported by Groq. Please use OpenAI provider for image editing.');
  }
 }
--- a/ts/provider.ollama.ts
+++ b/ts/provider.ollama.ts
@@ -1,7 +1,16 @@
 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 {
  ChatOptions,
  ChatResponse,
  ChatMessage,
  ResearchOptions,
  ResearchResponse,
  ImageGenerateOptions,
  ImageEditOptions,
  ImageResponse
 } from './abstract.classes.multimodal.js';
 export interface IOllamaProviderOptions {
  baseUrl?: string;
@@ -24,6 +33,7 @@ export class OllamaProvider extends MultiModalModel {
  }
  async start() {
    await super.start();
    // Verify Ollama is running
    try {
      const response = await fetch(`${this.baseUrl}/api/tags`);
@@ -35,7 +45,9 @@ export class OllamaProvider extends MultiModalModel {
    }
  }
-  async stop() {}
+  async stop() {
    await super.stop();
  }
  public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
    // Create a TextDecoder to handle incoming chunks
@@ -205,11 +217,10 @@ export class OllamaProvider extends MultiModalModel {
    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);
+      const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument);
      documentImageBytesArray = documentImageBytesArray.concat(documentImageArray);
    }
@@ -249,4 +260,22 @@ export class OllamaProvider extends MultiModalModel {
      }
    };
  }
  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
    throw new Error('Research capabilities are not yet supported by Ollama provider.');
  }
  /**
   * Image generation is not supported by Ollama
   */
  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
    throw new Error('Image generation is not supported by Ollama. Please use OpenAI provider for image generation.');
  }
  /**
   * Image editing is not supported by Ollama
   */
  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
    throw new Error('Image editing is not supported by Ollama. Please use OpenAI provider for image editing.');
  }
 }
--- a/ts/provider.openai.ts
+++ b/ts/provider.openai.ts
@@ -1,5 +1,6 @@
 import * as plugins from './plugins.js';
 import * as paths from './paths.js';
 import { Readable } from 'stream';
 // Custom type definition for chat completion messages
 export type TChatCompletionRequestMessage = { 
@@ -8,19 +9,27 @@ export type TChatCompletionRequestMessage = {
 };
 import { MultiModalModel } from './abstract.classes.multimodal.js';
 import type {
  ResearchOptions,
  ResearchResponse,
  ImageGenerateOptions,
  ImageEditOptions,
  ImageResponse
 } 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.
+  researchModel?: string;
  imageModel?: string;
  enableWebSearch?: boolean;
 }
 export class OpenAiProvider extends MultiModalModel {
  private options: IOpenaiProviderOptions;
  public openAiApiClient: plugins.openai.default;
  public smartpdfInstance: plugins.smartpdf.SmartPdf;
  constructor(optionsArg: IOpenaiProviderOptions) {
    super();
@@ -28,14 +37,16 @@ export class OpenAiProvider extends MultiModalModel {
  }
  public async start() {
    await super.start();
    this.openAiApiClient = new plugins.openai.default({
      apiKey: this.options.openaiToken,
      dangerouslyAllowBrowser: true,
    });
    this.smartpdfInstance = new plugins.smartpdf.SmartPdf();
  }
-  public async stop() {}
+  public async stop() {
    await super.stop();
  }
  public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
    // Create a TextDecoder to handle incoming chunks
@@ -75,7 +86,7 @@ export class OpenAiProvider extends MultiModalModel {
        // If we have a complete message, send it to OpenAI
        if (currentMessage) {
          const messageToSend = { role: "user" as const, content: currentMessage.content };
-          const chatModel = this.options.chatModel ?? 'o3-mini';
+          const chatModel = this.options.chatModel ?? 'gpt-5-mini';
          const requestParams: any = {
            model: chatModel,
            messages: [messageToSend],
@@ -121,7 +132,7 @@ export class OpenAiProvider extends MultiModalModel {
      content: string;
    }[];
  }) {
-    const chatModel = this.options.chatModel ?? 'o3-mini';
+    const chatModel = this.options.chatModel ?? 'gpt-5-mini';
    const requestParams: any = {
      model: chatModel,
      messages: [
@@ -148,7 +159,8 @@ export class OpenAiProvider extends MultiModalModel {
      speed: 1,
    });
    const stream = result.body;
-    done.resolve(stream);
+    const nodeStream = Readable.fromWeb(stream as any);
    done.resolve(nodeStream);
    return done.promise;
  }
@@ -164,13 +176,10 @@ 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 smartpdfInstance.convertPDFToPngBytes(pdfDocument);
+      const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument);
      pdfDocumentImageBytesArray = pdfDocumentImageBytesArray.concat(documentImageArray);
    }
    await smartpdfInstance.stop();
    console.log(`image smartfile array`);
    console.log(pdfDocumentImageBytesArray.map((smartfile) => smartfile.length));
@@ -184,7 +193,7 @@ export class OpenAiProvider extends MultiModalModel {
      },
    }));
-    const chatModel = this.options.chatModel ?? 'gpt-4o';
+    const chatModel = this.options.chatModel ?? 'gpt-5-mini';
    const requestParams: any = {
      model: chatModel,
      messages: [
@@ -207,7 +216,7 @@ export class OpenAiProvider extends MultiModalModel {
  }
  public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
-    const visionModel = this.options.visionModel ?? 'gpt-4o';
+    const visionModel = this.options.visionModel ?? '04-mini';
    const requestParams: any = {
      model: visionModel,
      messages: [
@@ -229,4 +238,218 @@ export class OpenAiProvider extends MultiModalModel {
    const result = await this.openAiApiClient.chat.completions.create(requestParams);
    return result.choices[0].message.content || '';
  }
  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
    // Determine which model to use - Deep Research API requires specific models
    let model: string;
    if (optionsArg.searchDepth === 'deep') {
      model = this.options.researchModel || 'o4-mini-deep-research-2025-06-26';
    } else {
      // For basic/advanced, still use deep research models if web search is needed
      if (optionsArg.includeWebSearch) {
        model = this.options.researchModel || 'o4-mini-deep-research-2025-06-26';
      } else {
        model = this.options.chatModel || 'gpt-5-mini';
      }
    }
    const systemMessage = 'You are a research assistant. Provide comprehensive answers with citations and sources when available.';
    // Prepare request parameters using Deep Research API format
    const requestParams: any = {
      model,
      instructions: systemMessage,
      input: optionsArg.query
    };
    // Add web search tool if requested
    if (optionsArg.includeWebSearch || optionsArg.searchDepth === 'deep') {
      requestParams.tools = [
        {
          type: 'web_search_preview',
          search_context_size: optionsArg.searchDepth === 'deep' ? 'high' :
                              optionsArg.searchDepth === 'advanced' ? 'medium' : 'low'
        }
      ];
    }
    // Add background flag for deep research
    if (optionsArg.background && optionsArg.searchDepth === 'deep') {
      requestParams.background = true;
    }
    try {
      // Execute the research request using Deep Research API
      const result = await this.openAiApiClient.responses.create(requestParams);
      // Extract the answer from output items
      let answer = '';
      const sources: Array<{ url: string; title: string; snippet: string }> = [];
      const searchQueries: string[] = [];
      // Process output items
      for (const item of result.output || []) {
        // Extract message content
        if (item.type === 'message' && 'content' in item) {
          const messageItem = item as any;
          for (const contentItem of messageItem.content || []) {
            if (contentItem.type === 'output_text' && 'text' in contentItem) {
              answer += contentItem.text;
            }
          }
        }
        // Extract web search queries
        if (item.type === 'web_search_call' && 'action' in item) {
          const searchItem = item as any;
          if (searchItem.action && searchItem.action.type === 'search' && 'query' in searchItem.action) {
            searchQueries.push(searchItem.action.query);
          }
        }
      }
      // Parse sources from markdown links in the answer
      const urlRegex = /\[([^\]]+)\]\(([^)]+)\)/g;
      let match: RegExpExecArray | null;
      while ((match = urlRegex.exec(answer)) !== null) {
        sources.push({
          title: match[1],
          url: match[2],
          snippet: ''
        });
      }
      return {
        answer,
        sources,
        searchQueries: searchQueries.length > 0 ? searchQueries : undefined,
        metadata: {
          model,
          searchDepth: optionsArg.searchDepth || 'basic',
          tokensUsed: result.usage?.total_tokens
        }
      };
    } catch (error) {
      console.error('Research API error:', error);
      throw new Error(`Failed to perform research: ${error.message}`);
    }
  }
  /**
   * Image generation using OpenAI's gpt-image-1 or DALL-E models
   */
  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
    const model = optionsArg.model || this.options.imageModel || 'gpt-image-1';
    try {
      const requestParams: any = {
        model,
        prompt: optionsArg.prompt,
        n: optionsArg.n || 1,
      };
      // Add gpt-image-1 specific parameters
      if (model === 'gpt-image-1') {
        if (optionsArg.quality) requestParams.quality = optionsArg.quality;
        if (optionsArg.size) requestParams.size = optionsArg.size;
        if (optionsArg.background) requestParams.background = optionsArg.background;
        if (optionsArg.outputFormat) requestParams.output_format = optionsArg.outputFormat;
        if (optionsArg.outputCompression !== undefined) requestParams.output_compression = optionsArg.outputCompression;
        if (optionsArg.moderation) requestParams.moderation = optionsArg.moderation;
        if (optionsArg.stream !== undefined) requestParams.stream = optionsArg.stream;
        if (optionsArg.partialImages !== undefined) requestParams.partial_images = optionsArg.partialImages;
      } else if (model === 'dall-e-3') {
        // DALL-E 3 specific parameters
        if (optionsArg.quality) requestParams.quality = optionsArg.quality;
        if (optionsArg.size) requestParams.size = optionsArg.size;
        if (optionsArg.style) requestParams.style = optionsArg.style;
        requestParams.response_format = 'b64_json'; // Always use base64 for consistency
      } else if (model === 'dall-e-2') {
        // DALL-E 2 specific parameters
        if (optionsArg.size) requestParams.size = optionsArg.size;
        requestParams.response_format = 'b64_json';
      }
      const result = await this.openAiApiClient.images.generate(requestParams);
      const images = (result.data || []).map(img => ({
        b64_json: img.b64_json,
        url: img.url,
        revisedPrompt: img.revised_prompt
      }));
      return {
        images,
        metadata: {
          model,
          quality: result.quality,
          size: result.size,
          outputFormat: result.output_format,
          tokensUsed: result.usage?.total_tokens
        }
      };
    } catch (error) {
      console.error('Image generation error:', error);
      throw new Error(`Failed to generate image: ${error.message}`);
    }
  }
  /**
   * Image editing using OpenAI's gpt-image-1 or DALL-E 2 models
   */
  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
    const model = optionsArg.model || this.options.imageModel || 'gpt-image-1';
    try {
      const requestParams: any = {
        model,
        image: optionsArg.image,
        prompt: optionsArg.prompt,
        n: optionsArg.n || 1,
      };
      // Add mask if provided
      if (optionsArg.mask) {
        requestParams.mask = optionsArg.mask;
      }
      // Add gpt-image-1 specific parameters
      if (model === 'gpt-image-1') {
        if (optionsArg.quality) requestParams.quality = optionsArg.quality;
        if (optionsArg.size) requestParams.size = optionsArg.size;
        if (optionsArg.background) requestParams.background = optionsArg.background;
        if (optionsArg.outputFormat) requestParams.output_format = optionsArg.outputFormat;
        if (optionsArg.outputCompression !== undefined) requestParams.output_compression = optionsArg.outputCompression;
        if (optionsArg.stream !== undefined) requestParams.stream = optionsArg.stream;
        if (optionsArg.partialImages !== undefined) requestParams.partial_images = optionsArg.partialImages;
      } else if (model === 'dall-e-2') {
        // DALL-E 2 specific parameters
        if (optionsArg.size) requestParams.size = optionsArg.size;
        requestParams.response_format = 'b64_json';
      }
      const result = await this.openAiApiClient.images.edit(requestParams);
      const images = (result.data || []).map(img => ({
        b64_json: img.b64_json,
        url: img.url,
        revisedPrompt: img.revised_prompt
      }));
      return {
        images,
        metadata: {
          model,
          quality: result.quality,
          size: result.size,
          outputFormat: result.output_format,
          tokensUsed: result.usage?.total_tokens
        }
      };
    } catch (error) {
      console.error('Image edit error:', error);
      throw new Error(`Failed to edit image: ${error.message}`);
    }
  }
 }
--- a/ts/provider.perplexity.ts
+++ b/ts/provider.perplexity.ts
@@ -1,7 +1,16 @@
 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 {
  ChatOptions,
  ChatResponse,
  ChatMessage,
  ResearchOptions,
  ResearchResponse,
  ImageGenerateOptions,
  ImageEditOptions,
  ImageResponse
 } from './abstract.classes.multimodal.js';
 export interface IPerplexityProviderOptions {
  perplexityToken: string;
@@ -168,4 +177,83 @@ export class PerplexityProvider extends MultiModalModel {
  }): Promise<{ message: any }> {
    throw new Error('Document processing is not supported by Perplexity.');
  }
  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
    // Perplexity has Sonar models that are optimized for search
    // sonar models: sonar, sonar-pro
    const model = optionsArg.searchDepth === 'deep' ? 'sonar-pro' : 'sonar';
    try {
      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,
          messages: [
            {
              role: 'system',
              content: 'You are a helpful research assistant. Provide accurate information with sources.'
            },
            {
              role: 'user',
              content: optionsArg.query
            }
          ],
          temperature: 0.7,
          max_tokens: 4000
        }),
      });
      if (!response.ok) {
        throw new Error(`Perplexity API error: ${response.statusText}`);
      }
      const result = await response.json();
      const answer = result.choices[0].message.content;
      // Parse citations from the response
      const sources: Array<{ url: string; title: string; snippet: string }> = [];
      // Perplexity includes citations in the format [1], [2], etc. with sources listed
      // This is a simplified parser - could be enhanced based on actual Perplexity response format
      if (result.citations) {
        for (const citation of result.citations) {
          sources.push({
            url: citation.url || '',
            title: citation.title || '',
            snippet: citation.snippet || ''
          });
        }
      }
      return {
        answer,
        sources,
        metadata: {
          model,
          searchDepth: optionsArg.searchDepth || 'basic'
        }
      };
    } catch (error) {
      console.error('Perplexity research error:', error);
      throw new Error(`Failed to perform research: ${error.message}`);
    }
  }
  /**
   * Image generation is not supported by Perplexity
   */
  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
    throw new Error('Image generation is not supported by Perplexity. Please use OpenAI provider for image generation.');
  }
  /**
   * Image editing is not supported by Perplexity
   */
  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
    throw new Error('Image editing is not supported by Perplexity. Please use OpenAI provider for image editing.');
  }
 }
--- a/ts/provider.xai.ts
+++ b/ts/provider.xai.ts
@@ -1,7 +1,16 @@
 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 {
  ChatOptions,
  ChatResponse,
  ChatMessage,
  ResearchOptions,
  ResearchResponse,
  ImageGenerateOptions,
  ImageEditOptions,
  ImageResponse
 } from './abstract.classes.multimodal.js';
 import type { ChatCompletionMessageParam } from 'openai/resources/chat/completions';
 export interface IXAIProviderOptions {
@@ -11,7 +20,6 @@ export interface IXAIProviderOptions {
 export class XAIProvider extends MultiModalModel {
  private options: IXAIProviderOptions;
  public openAiApiClient: plugins.openai.default;
  public smartpdfInstance: plugins.smartpdf.SmartPdf;
  constructor(optionsArg: IXAIProviderOptions) {
    super();
@@ -19,14 +27,16 @@ export class XAIProvider extends MultiModalModel {
  }
  public async start() {
    await super.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 stop() {
    await super.stop();
  }
  public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
    // Create a TextDecoder to handle incoming chunks
@@ -180,4 +190,22 @@ export class XAIProvider extends MultiModalModel {
      message: completion.choices[0]?.message?.content || ''
    };
  }
  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
    throw new Error('Research capabilities are not yet supported by xAI provider.');
  }
  /**
   * Image generation is not supported by xAI
   */
  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
    throw new Error('Image generation is not supported by xAI. Please use OpenAI provider for image generation.');
  }
  /**
   * Image editing is not supported by xAI
   */
  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
    throw new Error('Image editing is not supported by xAI. Please use OpenAI provider for image editing.');
  }
 }
Author	SHA1	Message	Date
Juergen Kunz	2672509d3f	0.7.1 Some checks failed Default (tags) / security (push) Failing after 23s Details Default (tags) / test (push) Failing after 13s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-10-03 13:49:46 +00:00
Juergen Kunz	ee3a635852	fix(docs): Add README image generation docs and .claude local settings	2025-10-03 13:49:46 +00:00
Juergen Kunz	a222b1c2fa	0.7.0 Some checks failed Default (tags) / security (push) Failing after 24s Details Default (tags) / test (push) Failing after 15s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-10-03 13:43:29 +00:00
Juergen Kunz	f0556e89f3	feat(providers): Add research API and image generation/editing support; extend providers and tests	2025-10-03 13:43:29 +00:00
Juergen Kunz	fe8540c8ba	feat(research): Implement research APIs.	2025-10-03 12:50:42 +00:00
Juergen Kunz	e34bf19698	0.6.1 Some checks failed Default (tags) / security (push) Failing after 21s Details Default (tags) / test (push) Failing after 13s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-09-28 15:51:50 +00:00
Juergen Kunz	f70353e6ca	fix(provider.anthropic): Fix Anthropic research tool identifier and add tests + local Claude permissions	2025-09-28 15:51:50 +00:00
Juergen Kunz	0403443634	0.6.0 Some checks failed Default (tags) / security (push) Failing after 23s Details Default (tags) / test (push) Failing after 13s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-09-28 15:06:07 +00:00
Juergen Kunz	e2ed429aac	feat(research): Introduce research API with provider implementations, docs and tests	2025-09-28 15:06:07 +00:00
Juergen Kunz	5c856ec3ed	0.5.11 Some checks failed Default (tags) / security (push) Failing after 21s Details Default (tags) / test (push) Failing after 12s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-08-12 13:15:37 +00:00
Juergen Kunz	052f37294d	fix(openaiProvider): Update default chat model to gpt-5-mini and bump dependency versions	2025-08-12 13:15:36 +00:00
Juergen Kunz	93bb375059	fix(dependencies): Update SmartPdf to v4.1.1 for enhanced PDF processing capabilities Some checks failed Default (tags) / security (push) Failing after 19s Details Default (tags) / test (push) Failing after 18s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-08-03 08:17:24 +00:00
Juergen Kunz	574f7a594c	fix(documentation): remove contribution section from readme Some checks failed Default (tags) / security (push) Failing after 23s Details Default (tags) / test (push) Failing after 12s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-08-01 18:37:26 +00:00
Juergen Kunz	0b2a058550	fix(core): improve SmartPdf lifecycle management and update dependencies Some checks failed Default (tags) / security (push) Failing after 19s Details Default (tags) / test (push) Failing after 16s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-08-01 18:25:46 +00:00
Juergen Kunz	88d15c89e5	0.5.6 Some checks failed Default (tags) / security (push) Failing after 24s Details Default (tags) / test (push) Failing after 13s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-07-26 16:17:11 +00:00
Juergen Kunz	4bf7113334	feat(documentation): comprehensive documentation enhancement and test improvements Some checks failed Default (tags) / security (push) Failing after 25s Details Default (tags) / test (push) Failing after 12s Details Default (tags) / release (push) Has been skipped Details Default (tags) / metadata (push) Has been skipped Details	2025-07-25 18:00:23 +00:00
Philipp Kunz	6bdbeae144	0.5.4	2025-05-13 18:39:58 +00:00
Philipp Kunz	09c27379cb	fix(provider.openai): Update dependency versions, clean test imports, and adjust default OpenAI model configurations	2025-05-13 18:39:57 +00:00
Philipp Kunz	2bc6f7ee5e	0.5.3	2025-04-03 21:46:40 +00:00
Philipp Kunz	0ac50d647d	fix(package.json): Add explicit packageManager field to package.json	2025-04-03 21:46:40 +00:00