v0.13.1

- Add IOllamaTool and IOllamaToolCall types for native function calling
- Add think parameter to IOllamaModelOptions for reasoning models (GPT-OSS, QwQ)
- Add tools parameter to IOllamaChatOptions
- Add toolCalls to response interfaces (IOllamaStreamChunk, IOllamaChatResponse)
- Update chat(), chatStreamResponse(), collectStreamResponse(), chatWithOptions() to support native tools
- Parse tool_calls from Ollama API responses
- Add support for tool message role in conversation history

.gitignore

@@ -3,7 +3,6 @@
 # artifacts
 coverage/
 public/
-pages/
 
 # installs
 node_modules/
@@ -17,4 +16,8 @@ node_modules/
 dist/
 dist_*/
 
-# custom
+# AI
+.claude/
+.serena/
+
+#------# custom

changelog.md

@@ -1,6 +1,218 @@
 # Changelog
 
+## 2026-01-20 - 0.13.1 - fix()
+no changes detected; no release required
+
+- No changes found in the provided git diff
+- Current package version is 0.13.0
+
+## 2026-01-20 - 0.13.0 - feat(provider.ollama)
+add chain-of-thought reasoning support to chat messages and Ollama provider
+
+- Added optional reasoning?: string to chat message and chat response interfaces to surface chain-of-thought data.
+- Propagates reasoning from message history into formatted requests sent to Ollama.
+- Maps Ollama response fields (thinking or reasoning) into ChatResponse.reasoning so downstream code can access model reasoning output.
+
+## 2026-01-20 - 0.12.1 - fix(docs)
+update documentation: clarify provider capabilities, add provider capabilities summary, polish examples and formatting, and remove Serena project config
+
+- Removed .serena/project.yml and cleaned up .serena/.gitignore
+- Added Provider Capabilities Summary and expanded/clarified provider tables in readme.md and readme.hints.md
+- Clarified Anthropic extended thinking details and Mistral native PDF OCR notes
+- Polished example code snippets and fixed minor typos/formatting (GPT-5 mention, ElevenLabs model note, consistent punctuation)
+- Updated test command references and other README usage instructions
+
+## 2026-01-20 - 0.12.0 - feat(ollama)
+add support for base64-encoded images in chat messages and forward them to the Ollama provider
+
+- Add optional images?: string[] to ChatMessage and ChatOptions interfaces (multimodal/vision support)
+- Propagate images from messageHistory and ChatOptions to the Ollama API payload in chat, chatStreaming, and streaming handlers
+- Changes are non-breaking: images are optional and existing behavior is preserved when absent
+
+## 2026-01-20 - 0.11.0 - feat(ollama)
+support defaultOptions and defaultTimeout for ollama provider
+
+- Added ollama.defaultOptions object with fields: num_ctx, temperature, top_k, top_p, repeat_penalty, num_predict, stop, seed
+- Added ollama.defaultTimeout option
+- Pass defaultOptions and defaultTimeout into OllamaProvider constructor when initializing the provider
+- Non-breaking change: existing behavior preserved if new fields are undefined
+
+## 2026-01-20 - 0.10.1 - fix()
+no changes detected — no release necessary
+
+- No files changed in the provided diff; there are no code, documentation, or configuration modifications to release.
+
+## 2026-01-18 - 0.10.0 - feat(mistral)
+add Mistral provider with native PDF OCR and chat integration
+
+- Adds dependency @mistralai/mistralai
+- Implements ts/provider.mistral.ts providing chat() and document() (OCR) functionality
+- Registers and exposes MistralProvider in SmartAi (options, lifecycle, conversation routing)
+- Adds unit/integration tests: test.chat.mistral.ts and test.document.mistral.ts
+- Updates readme.hints.md with Mistral usage, configuration and notes
+
+## 2026-01-18 - 0.9.0 - feat(providers)
+Add Anthropic extended thinking and adapt providers to new streaming/file APIs; bump dependencies and update docs, tests and configuration
+
+- Add IAnthropicProviderOptions.extendedThinking with thinking modes (quick/normal/deep/off) and getThinkingConfig mapping budgets; apply thinking to Anthropic requests and omit temperature when thinking is enabled.
+- Update Anthropic research flow to include thinking configuration and conditionally set temperature.
+- OpenAI image editing: use openai.toFile to convert image/mask Buffers to uploadable files (image/png) before sending.
+- ElevenLabs streaming: switch from response.streamNode() to response.stream() and convert web stream to Node stream using Readable.fromWeb().
+- Upgrade dependencies and dev tools: @anthropic-ai/sdk ^0.71.2, @push.rocks/smartrequest ^5.0.1, @git.zone/tsbuild and related @git.zone packages, and other bumps in package.json.
+- Tests and test imports updated to use @git.zone/tstest/tapbundle; many test files adjusted accordingly.
+- Docs and hints updated: README and readme.hints.md include extended thinking docs, examples, formatting fixes, security/issue reporting guidance, and trademark/license clarifications.
+- Project config tweaks: package build script changed, tsconfig baseUrl/paths added, npmextra.json reorganized (release registries added), .gitignore updated to ignore .claude/.serena local tooling files.
+
+## 2025-10-30 - 0.8.0 - feat(provider.anthropic)
+
+Add extended thinking modes to AnthropicProvider and apply thinking budgets to API calls
+
+- Introduce IAnthropicProviderOptions.extendedThinking to configure thinking modes: 'quick' | 'normal' | 'deep' | 'off'.
+- Add getThinkingConfig() helper mapping modes to token budgets (quick=2048, normal=8000, deep=16000, off=0).
+- Apply thinking configuration to Anthropic API calls (chat, chatStream, vision, document, research) and increase max_tokens where appropriate (up to 20000).
+- Add comprehensive tests (test/test.thinking.anthropic.ts) and update readme.hints.md with usage examples and recommendations.
+- Add .claude/settings.local.json for local assistant permissions used in development/testing.
+
+## 2025-10-10 - 0.7.7 - fix(MultiModalModel)
+
+Lazy-load SmartPdf and guard document processing across providers; ensure SmartPdf is initialized only when needed
+
+- Make SmartPdf lazy-loaded: smartpdfInstance is now nullable and no longer started automatically in start()
+- Add ensureSmartpdfReady() to initialize and start SmartPdf on demand before document processing
+- Providers updated (OpenAI, Anthropic, Ollama, xAI) to call ensureSmartpdfReady() and use the smartpdfInstance for PDF -> image conversion
+- stop() now cleans up and nullifies smartpdfInstance to release resources
+- Avoids starting a browser/process unless document() is actually used (reduces unnecessary resource usage)
+- Add local Claude permissions file (.claude/settings.local.json) for tooling/configuration
+
+## 2025-10-09 - 0.7.6 - fix(provider.elevenlabs)
+
+Provide default ElevenLabs TTS voice fallback and add local tool/project configs
+
+- ElevenLabsProvider: fallback to Samara voice id ('19STyYD15bswVz51nqLf') when no voiceId or defaultVoiceId is provided — avoids throwing an error on TTS calls.
+- ElevenLabsProvider: continue to use 'eleven_v3' as the default model for TTS.
+- Add .claude/settings.local.json with expanded allowed permissions for local tooling and web search.
+- Add .serena/project.yml and .serena/.gitignore to include Serena project configuration and ignore cache.
+
+## 2025-10-08 - 0.7.5 - fix(provider.elevenlabs)
+
+Update ElevenLabs default TTS model to eleven_v3 and add local Claude permissions file
+
+- Changed default ElevenLabs modelId from 'eleven_multilingual_v2' to 'eleven_v3' in ts/provider.elevenlabs.ts to use the newer/default TTS model.
+- Added .claude/settings.local.json with a permissions allow-list for local Claude tooling and CI tasks.
+
+## 2025-10-03 - 0.7.4 - fix(provider.anthropic)
+
+Use image/png for embedded PDF images in Anthropic provider and add local Claude settings for development permissions
+
+- AnthropicProvider: change media_type from 'image/jpeg' to 'image/png' when embedding images extracted from PDFs to ensure correct format in Anthropic requests.
+- Add .claude/settings.local.json with development/testing permissions for local Claude usage (shell commands, webfetch, websearch, test/run tasks).
+
+## 2025-10-03 - 0.7.3 - fix(tests)
+
+Add extensive provider/feature tests and local Claude CI permissions
+
+- Add many focused test files covering providers and features: OpenAI, Anthropic, Perplexity, Groq, Ollama, Exo, XAI (chat, audio, vision, document, research, image generation, stubs, interfaces, basic)
+- Introduce .claude/settings.local.json to declare allowed permissions for local Claude/CI actions
+- Replace older aggregated test files with modular per-feature tests (removed legacy combined tests and split into smaller suites)
+- No changes to library runtime code — this change adds tests and CI/local agent configuration only
+
+## 2025-10-03 - 0.7.2 - fix(anthropic)
+
+Update Anthropic provider branding to Claude Sonnet 4.5 and add local Claude permissions
+
+- Docs: Replace 'Claude 3 Opus' with 'Claude Sonnet 4.5' in README provider capabilities matrix.
+- Config: Add .claude/settings.local.json to define local Claude permissions for tests and development commands.
+
+## 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
@@ -9,6 +221,7 @@ Comprehensive documentation enhancement and test improvements
 - 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.)
@@ -16,17 +229,20 @@ Update dependency versions, clean test imports, and adjust default OpenAI model
 - 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.
 
 - Eliminated the conclusion block describing SmartAi's capabilities and documentation pointers.
 
 ## 2025-02-25 - 0.5.1 - fix(OpenAiProvider)
+
 Corrected audio model ID in OpenAiProvider
 
 - Fixed audio model identifier from 'o3-mini' to 'tts-1-hd' in the OpenAiProvider's audio method.
@@ -34,6 +250,7 @@ Corrected audio model ID in OpenAiProvider
 - Corrected spelling errors in test documentation and comments.
 
 ## 2025-02-25 - 0.5.0 - feat(documentation and configuration)
+
 Enhanced package and README documentation
 
 - Expanded the package description to better reflect the library's capabilities.
@@ -41,6 +258,7 @@ Enhanced package and README documentation
 - Provided error handling strategies and advanced streaming customization examples.
 
 ## 2025-02-25 - 0.4.2 - fix(core)
+
 Fix OpenAI chat streaming and PDF document processing logic.
 
 - Updated OpenAI chat streaming to handle new async iterable format.
@@ -48,6 +266,7 @@ Fix OpenAI chat streaming and PDF document processing logic.
 - Removed unsupported temperature options from OpenAI requests.
 
 ## 2025-02-25 - 0.4.1 - fix(provider)
+
 Fix provider modules for consistency
 
 - Updated TypeScript interfaces and options in provider modules for better type safety.
@@ -55,6 +274,7 @@ Fix provider modules for consistency
 - Added optional model options to OpenAI provider for custom model usage.
 
 ## 2025-02-08 - 0.4.0 - feat(core)
+
 Added support for Exo AI provider
 
 - Introduced ExoProvider with chat functionalities.
@@ -62,18 +282,21 @@ Added support for Exo AI provider
 - Extended Conversation class to support ExoProvider.
 
 ## 2025-02-05 - 0.3.3 - fix(documentation)
+
 Update readme with detailed license and legal information.
 
 - Added explicit section on License and Legal Information in the README.
 - Clarified the use of trademarks and company information.
 
 ## 2025-02-05 - 0.3.2 - fix(documentation)
+
 Remove redundant badges from readme
 
 - Removed Build Status badge from the readme file.
 - Removed License badge from the readme file.
 
 ## 2025-02-05 - 0.3.1 - fix(documentation)
+
 Updated README structure and added detailed usage examples
 
 - Introduced a Table of Contents
@@ -82,6 +305,7 @@ Updated README structure and added detailed usage examples
 - Clarified the development setup with instructions for running tests and building the project
 
 ## 2025-02-05 - 0.3.0 - feat(integration-xai)
+
 Add support for X.AI provider with chat and document processing capabilities.
 
 - Introduced XAIProvider class for integrating X.AI features.
@@ -89,6 +313,7 @@ Add support for X.AI provider with chat and document processing capabilities.
 - Enabled document processing capabilities with PDF conversion in X.AI.
 
 ## 2025-02-03 - 0.2.0 - feat(provider.anthropic)
+
 Add support for vision and document processing in Anthropic provider
 
 - Implemented vision tasks for Anthropic provider using Claude-3-opus-20240229 model.
@@ -96,6 +321,7 @@ Add support for vision and document processing in Anthropic provider
 - Updated documentation to reflect the new capabilities of the Anthropic provider.
 
 ## 2025-02-03 - 0.1.0 - feat(providers)
+
 Add vision and document processing capabilities to providers
 
 - OpenAI and Ollama providers now support vision tasks using GPT-4 Vision and Llava models respectively.
@@ -104,6 +330,7 @@ Add vision and document processing capabilities to providers
 - Updated the readme file with examples for vision and document processing.
 
 ## 2025-02-03 - 0.0.19 - fix(core)
+
 Enhanced chat streaming and error handling across providers
 
 - Refactored chatStream method to properly handle input streams and processes in Perplexity, OpenAI, Ollama, and Anthropic providers.
@@ -112,6 +339,7 @@ Enhanced chat streaming and error handling across providers
 - Adjusted the test logic in test/test.ts for the new classification response requirement.
 
 ## 2024-09-19 - 0.0.18 - fix(dependencies)
+
 Update dependencies to the latest versions.
 
 - Updated @git.zone/tsbuild from ^2.1.76 to ^2.1.84
@@ -125,46 +353,53 @@ Update dependencies to the latest versions.
 - Updated openai from ^4.47.1 to ^4.62.1
 
 ## 2024-05-29 - 0.0.17 - Documentation
+
 Updated project description.
 
 - Improved project description for clarity and details.
 
 ## 2024-05-17 - 0.0.16 to 0.0.15 - Core
+
 Fixes and updates.
 
 - Various core updates and fixes for stability improvements.
 
 ## 2024-04-29 - 0.0.14 to 0.0.13 - Core
+
 Fixes and updates.
 
 - Multiple core updates and fixes for enhanced functionality.
 
 ## 2024-04-29 - 0.0.12 - Core
+
 Fixes and updates.
 
 - Core update and bug fixes.
 
 ## 2024-04-29 - 0.0.11 - Provider
+
 Fix integration for anthropic provider.
 
 - Correction in the integration process with anthropic provider for better compatibility.
 
 ## 2024-04-27 - 0.0.10 to 0.0.9 - Core
+
 Fixes and updates.
 
 - Updates and fixes to core components.
 - Updated tsconfig for improved TypeScript configuration.
 
 ## 2024-04-01 - 0.0.8 to 0.0.7 - Core and npmextra
+
 Core updates and npmextra configuration.
 
 - Core fixes and updates.
 - Updates to npmextra.json for githost configuration.
 
 ## 2024-03-31 - 0.0.6 to 0.0.2 - Core
+
 Initial core updates and fixes.
 
 - Multiple updates and fixes to core following initial versions.
 
-
+This summarizes the relevant updates and changes based on the provided commit messages. The changelog excludes commits that are version tags without meaningful content or repeated entries.
-This summarizes the relevant updates and changes based on the provided commit messages. The changelog excludes commits that are version tags without meaningful content or repeated entries.

npmextra.json

@@ -1,5 +1,5 @@
 {
-  "gitzone": {
+  "@git.zone/cli": {
     "projectType": "npm",
     "module": {
       "githost": "code.foss.global",
@@ -33,13 +33,19 @@
         "AI toolkit",
         "provider switching"
       ]
+    },
+    "release": {
+      "accessLevel": "public",
+      "registries": [
+        "https://verdaccio.lossless.digital",
+        "https://registry.npmjs.org"
+      ]
     }
   },
-  "npmci": {
+  "@git.zone/tsdoc": {
-    "npmGlobalTools": [],
-    "npmAccessLevel": "public"
-  },
-  "tsdoc": {
     "legal": "\n## License and Legal Information\n\nThis repository contains open-source code that is licensed under the MIT License. A copy of the MIT License can be found in the [license](license) file within this repository. \n\n**Please note:** The MIT License does not grant permission to use the trade names, trademarks, service marks, or product names of the project, except as required for reasonable and customary use in describing the origin of the work and reproducing the content of the NOTICE file.\n\n### Trademarks\n\nThis project is owned and maintained by Task Venture Capital GmbH. The names and logos associated with Task Venture Capital GmbH and any related products or services are trademarks of Task Venture Capital GmbH and are not included within the scope of the MIT license granted herein. Use of these trademarks must comply with Task Venture Capital GmbH's Trademark Guidelines, and any usage must be approved in writing by Task Venture Capital GmbH.\n\n### Company Information\n\nTask Venture Capital GmbH  \nRegistered at District court Bremen HRB 35230 HB, Germany\n\nFor any legal inquiries or if you require further information, please contact us via email at hello@task.vc.\n\nBy 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.\n"
+  },
+  "@ship.zone/szci": {
+    "npmGlobalTools": []
   }
 }

package.json

@@ -1,6 +1,6 @@
 {
   "name": "@push.rocks/smartai",
-  "version": "0.5.6",
+  "version": "0.13.1",
   "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",
@@ -10,28 +10,30 @@
   "license": "MIT",
   "scripts": {
     "test": "(tstest test/ --web --verbose)",
-    "build": "(tsbuild --web --allowimplicitany)",
+    "typecheck": "tsbuild check",
+    "build": "(tsbuild tsfolders --allowimplicitany)",
     "buildDocs": "(tsdoc)"
   },
   "devDependencies": {
-    "@git.zone/tsbuild": "^2.6.4",
+    "@git.zone/tsbuild": "^4.1.2",
-    "@git.zone/tsbundle": "^2.5.1",
+    "@git.zone/tsbundle": "^2.8.1",
-    "@git.zone/tsrun": "^1.3.3",
+    "@git.zone/tsrun": "^2.0.1",
-    "@git.zone/tstest": "^2.3.2",
+    "@git.zone/tstest": "^3.1.6",
-    "@push.rocks/qenv": "^6.1.0",
+    "@push.rocks/qenv": "^6.1.3",
-    "@push.rocks/tapbundle": "^6.0.3",
+    "@types/node": "^25.0.9",
-    "@types/node": "^22.15.17"
+    "typescript": "^5.9.3"
   },
   "dependencies": {
-    "@anthropic-ai/sdk": "^0.57.0",
+    "@anthropic-ai/sdk": "^0.71.2",
+    "@mistralai/mistralai": "^1.12.0",
     "@push.rocks/smartarray": "^1.1.0",
-    "@push.rocks/smartfile": "^11.2.5",
+    "@push.rocks/smartfs": "^1.3.1",
-    "@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": "^2.1.0",
+    "@push.rocks/smartrequest": "^5.0.1",
     "@push.rocks/webstream": "^1.0.10",
-    "openai": "^5.10.2"
+    "openai": "^6.16.0"
   },
   "repository": {
     "type": "git",
@@ -84,7 +86,8 @@
     "onlyBuiltDependencies": [
       "esbuild",
       "puppeteer"
-    ]
+    ],
+    "overrides": {}
   },
   "packageManager": "pnpm@10.7.0+sha512.6b865ad4b62a1d9842b61d674a393903b871d9244954f652b8842c2b553c72176b278f64c463e52d40fff8aba385c235c8c9ecf5cc7de4fd78b8bb6d49633ab6"
 }

readme.hints.md

@@ -1 +1,104 @@
- 
+# SmartAI Project Hints
+
+## Dependencies
+
+- Uses `@git.zone/tstest` v3.x for testing (import from `@git.zone/tstest/tapbundle`)
+- `@push.rocks/smartfs` v1.x for file system operations
+- `@anthropic-ai/sdk` v0.71.x with extended thinking support
+- `@mistralai/mistralai` v1.x for Mistral OCR and chat capabilities
+- `openai` v6.x for OpenAI API integration
+- `@push.rocks/smartrequest` v5.x - uses `response.stream()` + `Readable.fromWeb()` for streaming
+
+## Important Notes
+
+- When extended thinking is enabled, temperature parameter must NOT be set (or set to 1)
+- The `streamNode()` method was removed in smartrequest v5, use `response.stream()` with `Readable.fromWeb()` instead
+
+## Provider Capabilities Summary
+
+| Provider     | Chat | Stream | TTS | Vision | Documents | Research | Images |
+|--------------|------|--------|-----|--------|-----------|----------|--------|
+| OpenAI       | ✅   | ✅     | ✅  | ✅     | ✅        | ✅       | ✅     |
+| Anthropic    | ✅   | ✅     | ❌  | ✅     | ✅        | ✅       | ❌     |
+| Mistral      | ✅   | ✅     | ❌  | ✅     | ✅        | ❌       | ❌     |
+| ElevenLabs   | ❌   | ❌     | ✅  | ❌     | ❌        | ❌       | ❌     |
+| Ollama       | ✅   | ✅     | ❌  | ✅     | ✅        | ❌       | ❌     |
+| XAI          | ✅   | ✅     | ❌  | ❌     | ✅        | ❌       | ❌     |
+| Perplexity   | ✅   | ✅     | ❌  | ❌     | ❌        | ✅       | ❌     |
+| Groq         | ✅   | ✅     | ❌  | ❌     | ❌        | ❌       | ❌     |
+| Exo          | ✅   | ✅     | ❌  | ❌     | ❌        | ❌       | ❌     |
+
+## Mistral Provider Integration
+
+### Overview
+
+The Mistral provider supports:
+- **Document AI** via Mistral OCR (December 2025) - native PDF processing without image conversion
+- **Chat capabilities** using Mistral's chat models (`mistral-large-latest`, etc.)
+
+### Key Advantage: Native PDF Support
+
+Unlike other providers that require converting PDFs to images (using SmartPdf), Mistral OCR natively accepts PDF documents as base64-encoded data. This makes document processing potentially faster and more accurate for text extraction.
+
+### Configuration
+
+```typescript
+import * as smartai from '@push.rocks/smartai';
+
+const provider = new smartai.MistralProvider({
+  mistralToken: 'your-token-here',
+  chatModel: 'mistral-large-latest',  // default
+  ocrModel: 'mistral-ocr-latest',     // default
+  tableFormat: 'markdown',             // 'markdown' or 'html'
+});
+
+await provider.start();
+```
+
+### API Key
+
+Tests require `MISTRAL_API_KEY` in `.nogit/env.json`.
+
+## Anthropic Extended Thinking Feature
+
+### Configuration
+
+Extended thinking is configured at the provider level during instantiation:
+
+```typescript
+import * as smartai from '@push.rocks/smartai';
+
+const provider = new smartai.AnthropicProvider({
+  anthropicToken: 'your-token-here',
+  extendedThinking: 'normal', // Options: 'quick' | 'normal' | 'deep' | 'off'
+});
+```
+
+### Thinking Modes
+
+| Mode       | Budget Tokens | Use Case                                        |
+| ---------- | ------------- | ----------------------------------------------- |
+| `'quick'`  | 2,048         | Lightweight reasoning for simple queries        |
+| `'normal'` | 8,000         | **Default** - Balanced reasoning for most tasks |
+| `'deep'`   | 16,000        | Complex reasoning for difficult problems        |
+| `'off'`    | 0             | Disable extended thinking                       |
+
+### Implementation Details
+
+- Extended thinking is implemented via `getThinkingConfig()` private method
+- When thinking is enabled, temperature must NOT be set
+- Uses `claude-sonnet-4-5-20250929` model
+
+## Testing
+
+Run tests with:
+
+```bash
+pnpm test
+```
+
+Run specific tests:
+
+```bash
+npx tstest test/test.something.ts --verbose
+```

test/test.audio.elevenlabs.ts

@@ -0,0 +1,55 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+import { SmartFs, SmartFsProviderNode } from '@push.rocks/smartfs';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+const smartfs = new SmartFs(new SmartFsProviderNode());
+
+import * as smartai from '../ts/index.js';
+
+let testSmartai: smartai.SmartAi;
+
+tap.test('ElevenLabs Audio: should create a smartai instance with ElevenLabs provider', async () => {
+  testSmartai = new smartai.SmartAi({
+    elevenlabsToken: await testQenv.getEnvVarOnDemand('ELEVENLABS_TOKEN'),
+    elevenlabs: {
+      defaultVoiceId: '19STyYD15bswVz51nqLf',
+    },
+  });
+  await testSmartai.start();
+});
+
+tap.test('ElevenLabs Audio: should create audio response', async () => {
+  const audioStream = await testSmartai.elevenlabsProvider.audio({
+    message: 'Welcome to SmartAI, the unified interface for the world\'s leading artificial intelligence providers. SmartAI brings together OpenAI, Anthropic, Perplexity, and ElevenLabs under a single elegant TypeScript API. Whether you need text generation, vision analysis, document processing, or premium text-to-speech capabilities, SmartAI provides a consistent and powerful interface for all your AI needs. Build intelligent applications at lightning speed without vendor lock-in.',
+  });
+  const chunks: Uint8Array[] = [];
+  for await (const chunk of audioStream) {
+    chunks.push(chunk as Uint8Array);
+  }
+  const audioBuffer = Buffer.concat(chunks);
+  await smartfs.file('./.nogit/testoutput_elevenlabs.mp3').write(audioBuffer);
+  console.log(`Audio Buffer length: ${audioBuffer.length}`);
+  expect(audioBuffer.length).toBeGreaterThan(0);
+});
+
+tap.test('ElevenLabs Audio: should create audio with custom voice', async () => {
+  const audioStream = await testSmartai.elevenlabsProvider.audio({
+    message: 'Testing with a different voice.',
+    voiceId: 'JBFqnCBsd6RMkjVDRZzb',
+  });
+  const chunks: Uint8Array[] = [];
+  for await (const chunk of audioStream) {
+    chunks.push(chunk as Uint8Array);
+  }
+  const audioBuffer = Buffer.concat(chunks);
+  await smartfs.file('./.nogit/testoutput_elevenlabs_custom.mp3').write(audioBuffer);
+  console.log(`Audio Buffer length (custom voice): ${audioBuffer.length}`);
+  expect(audioBuffer.length).toBeGreaterThan(0);
+});
+
+tap.test('ElevenLabs Audio: should stop the smartai instance', async () => {
+  await testSmartai.stop();
+});
+
+export default tap.start();

test/test.audio.openai.ts

@@ -0,0 +1,40 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+import { SmartFs, SmartFsProviderNode } from '@push.rocks/smartfs';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+const smartfs = new SmartFs(new SmartFsProviderNode());
+
+import * as smartai from '../ts/index.js';
+
+let testSmartai: smartai.SmartAi;
+
+tap.test('OpenAI Audio: should create a smartai instance with OpenAI provider', async () => {
+  testSmartai = new smartai.SmartAi({
+    openaiToken: await testQenv.getEnvVarOnDemand('OPENAI_TOKEN'),
+  });
+  await testSmartai.start();
+});
+
+tap.test('OpenAI Audio: 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.',
+  });
+  // Read all chunks from the stream.
+  const chunks: Uint8Array[] = [];
+  for await (const chunk of audioStream) {
+    chunks.push(chunk as Uint8Array);
+  }
+  const audioBuffer = Buffer.concat(chunks);
+  await smartfs.file('./.nogit/testoutput.mp3').write(audioBuffer);
+  console.log(`Audio Buffer length: ${audioBuffer.length}`);
+  // Assert that the resulting buffer is not empty.
+  expect(audioBuffer.length).toBeGreaterThan(0);
+});
+
+tap.test('OpenAI Audio: should stop the smartai instance', async () => {
+  await testSmartai.stop();
+});
+
+export default tap.start();

test/test.audio.stubs.ts

@@ -0,0 +1,36 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+
+import * as smartai from '../ts/index.js';
+
+let anthropicProvider: smartai.AnthropicProvider;
+
+tap.test('Audio Stubs: should create Anthropic provider', async () => {
+  anthropicProvider = new smartai.AnthropicProvider({
+    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
+  });
+  await anthropicProvider.start();
+});
+
+tap.test('Audio Stubs: 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('Audio Stubs: should stop Anthropic provider', async () => {
+  await anthropicProvider.stop();
+});
+
+export default tap.start();

test/test.basic.ts

@@ -0,0 +1,93 @@
+import { tap, expect } from '@git.zone/tstest/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();

test/test.chat.anthropic.ts

@@ -0,0 +1,72 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+
+import * as smartai from '../ts/index.js';
+
+let anthropicProvider: smartai.AnthropicProvider;
+
+tap.test('Anthropic Chat: 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 Chat: 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 Chat: 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 Chat: 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 Chat: should stop the provider', async () => {
+  await anthropicProvider.stop();
+});
+
+export default tap.start();

test/test.chat.mistral.ts

@@ -0,0 +1,66 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+
+import * as smartai from '../ts/index.js';
+
+let mistralProvider: smartai.MistralProvider;
+
+tap.test('Mistral Chat: should create and start Mistral provider', async () => {
+  mistralProvider = new smartai.MistralProvider({
+    mistralToken: await testQenv.getEnvVarOnDemand('MISTRAL_API_KEY'),
+  });
+  await mistralProvider.start();
+  expect(mistralProvider).toBeInstanceOf(smartai.MistralProvider);
+});
+
+tap.test('Mistral Chat: should create chat response', async () => {
+  const userMessage = 'What is the capital of France? Answer in one word.';
+  const response = await mistralProvider.chat({
+    systemMessage: 'You are a helpful assistant. Be concise.',
+    userMessage: userMessage,
+    messageHistory: [],
+  });
+  console.log(`Mistral Chat - User: ${userMessage}`);
+  console.log(`Mistral Chat - Response: ${response.message}`);
+
+  expect(response.role).toEqual('assistant');
+  expect(response.message).toBeTruthy();
+  expect(response.message.toLowerCase()).toInclude('paris');
+});
+
+tap.test('Mistral Chat: 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 mistralProvider.chat({
+    systemMessage: 'You are a helpful assistant with good memory.',
+    userMessage: 'What is my name?',
+    messageHistory: messageHistory,
+  });
+
+  console.log(`Mistral Memory Test - Response: ${response.message}`);
+  expect(response.message.toLowerCase()).toInclude('claude test');
+});
+
+tap.test('Mistral Chat: should handle longer conversations', async () => {
+  const response = await mistralProvider.chat({
+    systemMessage: 'You are a helpful coding assistant.',
+    userMessage: 'Write a simple hello world function in TypeScript. Keep it brief.',
+    messageHistory: [],
+  });
+
+  console.log(`Mistral Coding Test - Response: ${response.message}`);
+  expect(response.message).toBeTruthy();
+  // Should contain some TypeScript/function code
+  expect(response.message).toInclude('function');
+});
+
+tap.test('Mistral Chat: should stop the provider', async () => {
+  await mistralProvider.stop();
+});
+
+export default tap.start();

test/test.chat.openai.ts

@@ -0,0 +1,34 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+
+import * as smartai from '../ts/index.js';
+
+let testSmartai: smartai.SmartAi;
+
+tap.test('OpenAI Chat: should create a smartai instance with OpenAI provider', async () => {
+  testSmartai = new smartai.SmartAi({
+    openaiToken: await testQenv.getEnvVarOnDemand('OPENAI_TOKEN'),
+  });
+  await testSmartai.start();
+});
+
+tap.test('OpenAI Chat: should create chat response', async () => {
+  const userMessage = 'How are you?';
+  const response = await testSmartai.openaiProvider.chat({
+    systemMessage: 'Hello',
+    userMessage: userMessage,
+    messageHistory: [],
+  });
+  console.log(`userMessage: ${userMessage}`);
+  console.log(response.message);
+  expect(response.role).toEqual('assistant');
+  expect(response.message).toBeTruthy();
+});
+
+tap.test('OpenAI Chat: should stop the smartai instance', async () => {
+  await testSmartai.stop();
+});
+
+export default tap.start();

test/test.document.anthropic.ts

@@ -0,0 +1,79 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+import * as smartrequest from '@push.rocks/smartrequest';
+import { SmartFs, SmartFsProviderNode } from '@push.rocks/smartfs';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+const smartfs = new SmartFs(new SmartFsProviderNode());
+
+import * as smartai from '../ts/index.js';
+
+let anthropicProvider: smartai.AnthropicProvider;
+
+tap.test('Anthropic Document: 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 Document: 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 Document: 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 smartfs.file(pdfPath).read();
+  } 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 Document: should stop the provider', async () => {
+  await anthropicProvider.stop();
+});
+
+export default tap.start();

test/test.document.mistral.ts

@@ -0,0 +1,100 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+import * as smartrequest from '@push.rocks/smartrequest';
+import { SmartFs, SmartFsProviderNode } from '@push.rocks/smartfs';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+const smartfs = new SmartFs(new SmartFsProviderNode());
+
+import * as smartai from '../ts/index.js';
+
+let mistralProvider: smartai.MistralProvider;
+
+tap.test('Mistral Document: should create and start Mistral provider', async () => {
+  mistralProvider = new smartai.MistralProvider({
+    mistralToken: await testQenv.getEnvVarOnDemand('MISTRAL_API_KEY'),
+    tableFormat: 'markdown',
+  });
+  await mistralProvider.start();
+  expect(mistralProvider).toBeInstanceOf(smartai.MistralProvider);
+});
+
+tap.test('Mistral Document: should process a PDF document', 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 mistralProvider.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(`Mistral Document - Result:`, result);
+  expect(result).toBeTruthy();
+  expect(result.message).toBeTruthy();
+});
+
+tap.test('Mistral Document: 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 smartfs.file(pdfPath).read();
+  } 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 mistralProvider.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(`Mistral Complex Document Analysis:`, result);
+  expect(result).toBeTruthy();
+  expect(result.message).toBeTruthy();
+});
+
+tap.test('Mistral Document: should process multiple PDF documents', 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 pdfBuffer = Buffer.from(await pdfResponse.arrayBuffer());
+
+  const result = await mistralProvider.document({
+    systemMessage: 'You are a document comparison assistant.',
+    userMessage: 'Are these two documents the same? Answer yes or no.',
+    messageHistory: [],
+    pdfDocuments: [pdfBuffer, pdfBuffer], // Same document twice for test
+  });
+
+  console.log(`Mistral Multi-Document - Result:`, result);
+  expect(result).toBeTruthy();
+  expect(result.message).toBeTruthy();
+});
+
+tap.test('Mistral Document: should stop the provider', async () => {
+  await mistralProvider.stop();
+});
+
+export default tap.start();

test/test.document.openai.ts

@@ -1,46 +1,39 @@
-import { expect, tap } from '@push.rocks/tapbundle';
+import { expect, tap } from '@git.zone/tstest/tapbundle';
 import * as qenv from '@push.rocks/qenv';
 import * as smartrequest from '@push.rocks/smartrequest';
-import * as smartfile from '@push.rocks/smartfile';
+import { SmartFs, SmartFsProviderNode } from '@push.rocks/smartfs';
 
 const testQenv = new qenv.Qenv('./', './.nogit/');
+const smartfs = new SmartFs(new SmartFsProviderNode());
 
 import * as smartai from '../ts/index.js';
 
 let testSmartai: smartai.SmartAi;
 
-tap.test('should create a smartai instance', async () => {
+tap.test('OpenAI Document: 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 Document: should document a pdf', async () => {
-  const userMessage = 'How are you?';
-  const response = await testSmartai.openaiProvider.chat({
-    systemMessage: 'Hello',
-    userMessage: userMessage,
-    messageHistory: [],
-  });
-  console.log(`userMessage: ${userMessage}`);
-  console.log(response.message);
-});
-
-tap.test('should document a pdf', async () => {
   const pdfUrl = 'https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf';
-  const pdfResponse = await smartrequest.getBinary(pdfUrl);
+  const 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);
+  expect(result.message).toBeTruthy();
 });
 
-tap.test('should recognize companies in a pdf', async () => {
+tap.test('OpenAI Document: should recognize companies in a pdf', async () => {
-  const pdfBuffer = await smartfile.fs.toBuffer('./.nogit/demo_without_textlayer.pdf');
+  const pdfBuffer = await smartfs.file('./.nogit/demo_without_textlayer.pdf').read();
   const result = await testSmartai.openaiProvider.document({
     systemMessage: `
       summarize the document.
@@ -74,27 +67,11 @@ tap.test('should recognize companies in a pdf', async () => {
     pdfDocuments: [pdfBuffer],
   });
   console.log(result);
+  expect(result.message).toBeTruthy();
 });
 
-tap.test('should create audio response with openai', async () => {
+tap.test('OpenAI Document: should stop the smartai instance', async () => {
-  // Call the audio method with a sample message.
-  const audioStream = await testSmartai.openaiProvider.audio({
-    message: 'This is a test of audio generation.',
-  });
-  // Read all chunks from the stream.
-  const chunks: Uint8Array[] = [];
-  for await (const chunk of audioStream) {
-    chunks.push(chunk as Uint8Array);
-  }
-  const audioBuffer = Buffer.concat(chunks);
-  await smartfile.fs.toFs(audioBuffer, './.nogit/testoutput.mp3');
-  console.log(`Audio Buffer length: ${audioBuffer.length}`);
-  // Assert that the resulting buffer is not empty.
-  expect(audioBuffer.length).toBeGreaterThan(0);
-});
-
-tap.test('should stop the smartai instance', async () => {
   await testSmartai.stop();
 });
 
-export default tap.start();
+export default tap.start();

test/test.image.openai.ts

@@ -0,0 +1,203 @@
+import { expect, tap } from '@git.zone/tstest/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();

test/test.interfaces.ts

@@ -0,0 +1,140 @@
+import { tap, expect } from '@git.zone/tstest/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();

test/test.research.anthropic.ts

@@ -0,0 +1,223 @@
+import { expect, tap } from '@git.zone/tstest/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();

test/test.research.openai.ts

@@ -0,0 +1,172 @@
+import { expect, tap } from '@git.zone/tstest/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();

test/test.research.stubs.ts

@@ -0,0 +1,80 @@
+import { tap, expect } from '@git.zone/tstest/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();

test/test.thinking.anthropic.ts

@@ -0,0 +1,151 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+
+import * as smartai from '../ts/index.js';
+
+let anthropicProviderQuick: smartai.AnthropicProvider;
+let anthropicProviderNormal: smartai.AnthropicProvider;
+let anthropicProviderDeep: smartai.AnthropicProvider;
+let anthropicProviderOff: smartai.AnthropicProvider;
+
+// Test 'quick' mode
+tap.test('Extended Thinking: should create Anthropic provider with quick mode', async () => {
+  anthropicProviderQuick = new smartai.AnthropicProvider({
+    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
+    extendedThinking: 'quick',
+  });
+  await anthropicProviderQuick.start();
+  expect(anthropicProviderQuick).toBeInstanceOf(smartai.AnthropicProvider);
+});
+
+tap.test('Extended Thinking: should chat with quick mode (2048 tokens)', async () => {
+  const userMessage = 'Explain quantum entanglement in simple terms.';
+  const response = await anthropicProviderQuick.chat({
+    systemMessage: 'You are a helpful physics teacher.',
+    userMessage: userMessage,
+    messageHistory: [],
+  });
+  console.log(`Quick Mode - User: ${userMessage}`);
+  console.log(`Quick Mode - Response length: ${response.message.length} chars`);
+  expect(response.role).toEqual('assistant');
+  expect(response.message).toBeTruthy();
+  expect(response.message.toLowerCase()).toInclude('quantum');
+});
+
+tap.test('Extended Thinking: should stop quick mode provider', async () => {
+  await anthropicProviderQuick.stop();
+});
+
+// Test 'normal' mode (default)
+tap.test('Extended Thinking: should create Anthropic provider with normal mode (default)', async () => {
+  anthropicProviderNormal = new smartai.AnthropicProvider({
+    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
+    // extendedThinking not specified, should default to 'normal'
+  });
+  await anthropicProviderNormal.start();
+  expect(anthropicProviderNormal).toBeInstanceOf(smartai.AnthropicProvider);
+});
+
+tap.test('Extended Thinking: should chat with normal mode (8000 tokens default)', async () => {
+  const userMessage = 'What are the implications of the P vs NP problem?';
+  const response = await anthropicProviderNormal.chat({
+    systemMessage: 'You are a helpful computer science expert.',
+    userMessage: userMessage,
+    messageHistory: [],
+  });
+  console.log(`Normal Mode - User: ${userMessage}`);
+  console.log(`Normal Mode - Response length: ${response.message.length} chars`);
+  expect(response.role).toEqual('assistant');
+  expect(response.message).toBeTruthy();
+  expect(response.message.length).toBeGreaterThan(50);
+});
+
+tap.test('Extended Thinking: should stop normal mode provider', async () => {
+  await anthropicProviderNormal.stop();
+});
+
+// Test 'deep' mode
+tap.test('Extended Thinking: should create Anthropic provider with deep mode', async () => {
+  anthropicProviderDeep = new smartai.AnthropicProvider({
+    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
+    extendedThinking: 'deep',
+  });
+  await anthropicProviderDeep.start();
+  expect(anthropicProviderDeep).toBeInstanceOf(smartai.AnthropicProvider);
+});
+
+tap.test('Extended Thinking: should chat with deep mode (16000 tokens)', async () => {
+  const userMessage = 'Analyze the philosophical implications of artificial consciousness.';
+  const response = await anthropicProviderDeep.chat({
+    systemMessage: 'You are a philosopher and cognitive scientist.',
+    userMessage: userMessage,
+    messageHistory: [],
+  });
+  console.log(`Deep Mode - User: ${userMessage}`);
+  console.log(`Deep Mode - Response length: ${response.message.length} chars`);
+  expect(response.role).toEqual('assistant');
+  expect(response.message).toBeTruthy();
+  expect(response.message.length).toBeGreaterThan(100);
+});
+
+tap.test('Extended Thinking: should stop deep mode provider', async () => {
+  await anthropicProviderDeep.stop();
+});
+
+// Test 'off' mode
+tap.test('Extended Thinking: should create Anthropic provider with thinking disabled', async () => {
+  anthropicProviderOff = new smartai.AnthropicProvider({
+    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
+    extendedThinking: 'off',
+  });
+  await anthropicProviderOff.start();
+  expect(anthropicProviderOff).toBeInstanceOf(smartai.AnthropicProvider);
+});
+
+tap.test('Extended Thinking: should chat with thinking disabled', async () => {
+  const userMessage = 'What is 2 + 2?';
+  const response = await anthropicProviderOff.chat({
+    systemMessage: 'You are a helpful assistant.',
+    userMessage: userMessage,
+    messageHistory: [],
+  });
+  console.log(`Thinking Off - User: ${userMessage}`);
+  console.log(`Thinking Off - Response: ${response.message}`);
+  expect(response.role).toEqual('assistant');
+  expect(response.message).toBeTruthy();
+  expect(response.message).toInclude('4');
+});
+
+tap.test('Extended Thinking: should stop off mode provider', async () => {
+  await anthropicProviderOff.stop();
+});
+
+// Test with vision method
+tap.test('Extended Thinking: should work with vision method', async () => {
+  const provider = new smartai.AnthropicProvider({
+    anthropicToken: await testQenv.getEnvVarOnDemand('ANTHROPIC_TOKEN'),
+    extendedThinking: 'normal',
+  });
+  await provider.start();
+
+  // Create a simple test image (1x1 red pixel PNG)
+  const redPixelPng = Buffer.from(
+    'iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mP8z8DwHwAFBQIAX8jx0gAAAABJRU5ErkJggg==',
+    'base64'
+  );
+
+  const response = await provider.vision({
+    image: redPixelPng,
+    prompt: 'What color is this image?',
+  });
+
+  console.log(`Vision with Thinking - Response: ${response}`);
+  expect(response).toBeTruthy();
+  expect(response.toLowerCase()).toInclude('red');
+
+  await provider.stop();
+});
+
+export default tap.start();

test/test.vision.anthropic.ts

@@ -0,0 +1,96 @@
+import { expect, tap } from '@git.zone/tstest/tapbundle';
+import * as qenv from '@push.rocks/qenv';
+import { SmartFs, SmartFsProviderNode } from '@push.rocks/smartfs';
+
+const testQenv = new qenv.Qenv('./', './.nogit/');
+const smartfs = new SmartFs(new SmartFsProviderNode());
+
+import * as smartai from '../ts/index.js';
+
+let anthropicProvider: smartai.AnthropicProvider;
+
+tap.test('Anthropic Vision: 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 Vision: 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 smartfs.file(imagePath).read();
+  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 Vision: 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 smartfs.file(imagePath).read();
+  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 Vision: 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 smartfs.file(imagePath).read();
+  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 Vision: should stop the provider', async () => {
+  await anthropicProvider.stop();
+});
+
+export default tap.start();

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

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

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

ts/00_commitinfo_data.ts

@@ -3,6 +3,6 @@
  */
 export const commitinfo = {
   name: '@push.rocks/smartai',
-  version: '0.5.4',
+  version: '0.13.1',
   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.'
 }

ts/abstract.classes.multimodal.ts

@@ -1,9 +1,15 @@
+import * as plugins from './plugins.js';
+
 /**
  * Message format for chat interactions
  */
 export interface ChatMessage {
   role: 'assistant' | 'user' | 'system';
   content: string;
+  /** Base64-encoded images for vision-capable models */
+  images?: string[];
+  /** Chain-of-thought reasoning for GPT-OSS models (e.g., Ollama) */
+  reasoning?: string;
 }
 
 /**
@@ -13,6 +19,16 @@ export interface ChatOptions {
   systemMessage: string;
   userMessage: string;
   messageHistory: ChatMessage[];
+  /** Base64-encoded images for the current message (vision-capable models) */
+  images?: string[];
+}
+
+/**
+ * Options for streaming chat interactions
+ */
+export interface StreamingChatOptions extends ChatOptions {
+  /** Callback fired for each token during generation */
+  onToken?: (token: string) => void;
 }
 
 /**
@@ -21,6 +37,87 @@ export interface ChatOptions {
 export interface ChatResponse {
   role: 'assistant';
   message: string;
+  /** Chain-of-thought reasoning from reasoning models */
+  reasoning?: 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;
+  };
 }
 
 /**
@@ -28,17 +125,42 @@ export interface ChatResponse {
  * Provides a common interface for different AI providers (OpenAI, Anthropic, Perplexity, Ollama)
  */
 export abstract class MultiModalModel {
+  /**
+   * SmartPdf instance for document processing
+   * Lazy-loaded only when PDF processing is needed to avoid starting browser unnecessarily
+   */
+  protected smartpdfInstance: plugins.smartpdf.SmartPdf | null = null;
+
+  /**
+   * Ensures SmartPdf instance is initialized and ready
+   * Call this before using smartpdfInstance in document processing methods
+   */
+  protected async ensureSmartpdfReady(): Promise<void> {
+    if (!this.smartpdfInstance) {
+      this.smartpdfInstance = new plugins.smartpdf.SmartPdf();
+      await this.smartpdfInstance.start();
+    }
+  }
+
   /**
    * Initializes the model and any necessary resources
    * Should be called before using any other methods
    */
-  abstract start(): Promise<void>;
+  public async start(): Promise<void> {
-  
+    // SmartPdf is now lazy-loaded only when needed for PDF processing
+    // This avoids starting a browser unless document() method is actually used
+  }
+
   /**
    * 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();
+      this.smartpdfInstance = null;
+    }
+  }
 
   /**
    * Synchronous chat interaction with the model
@@ -46,7 +168,7 @@ export abstract class MultiModalModel {
    * @returns Promise resolving to the assistant's response
    */
   public abstract chat(optionsArg: ChatOptions): Promise<ChatResponse>;
-  
+
   /**
    * Streaming interface for chat interactions
    * Allows for real-time responses from the model
@@ -55,6 +177,14 @@ export abstract class MultiModalModel {
    */
   public abstract chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>>;
 
+  /**
+   * Streaming chat with token callback
+   * Calls onToken for each token generated, returns final response
+   * @param optionsArg Options containing system message, user message, message history, and onToken callback
+   * @returns Promise resolving to the assistant's response
+   */
+  public chatStreaming?(optionsArg: StreamingChatOptions): Promise<ChatResponse>;
+
   /**
    * Text-to-speech conversion
    * @param optionsArg Options containing the message to convert to speech
@@ -83,4 +213,28 @@ 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>;
 }

ts/classes.conversation.ts

@@ -84,6 +84,18 @@ export class Conversation {
     return conversation;
   }
 
+  public static async createWithMistral(smartaiRefArg: SmartAi) {
+    if (!smartaiRefArg.mistralProvider) {
+      throw new Error('Mistral provider not available');
+    }
+    const conversation = new Conversation(smartaiRefArg, {
+      processFunction: async (input) => {
+        return '' // TODO implement proper streaming
+      }
+    });
+    return conversation;
+  }
+
   public static async createWithXai(smartaiRefArg: SmartAi) {
     if (!smartaiRefArg.xaiProvider) {
       throw new Error('XAI provider not available');
@@ -96,6 +108,18 @@ export class Conversation {
     return conversation;
   }
 
+  public static async createWithElevenlabs(smartaiRefArg: SmartAi) {
+    if (!smartaiRefArg.elevenlabsProvider) {
+      throw new Error('ElevenLabs provider not available');
+    }
+    const conversation = new Conversation(smartaiRefArg, {
+      processFunction: async (input) => {
+        return '' // TODO implement proper streaming
+      }
+    });
+    return conversation;
+  }
+
   // INSTANCE
   smartaiRef: SmartAi
   private systemMessage: string;

ts/classes.smartai.ts

@@ -1,6 +1,8 @@
 import { Conversation } from './classes.conversation.js';
 import * as plugins from './plugins.js';
 import { AnthropicProvider } from './provider.anthropic.js';
+import { ElevenLabsProvider } from './provider.elevenlabs.js';
+import { MistralProvider } from './provider.mistral.js';
 import { OllamaProvider } from './provider.ollama.js';
 import { OpenAiProvider } from './provider.openai.js';
 import { PerplexityProvider } from './provider.perplexity.js';
@@ -14,19 +16,41 @@ export interface ISmartAiOptions {
   anthropicToken?: string;
   perplexityToken?: string;
   groqToken?: string;
+  mistralToken?: string;
   xaiToken?: string;
+  elevenlabsToken?: string;
   exo?: {
     baseUrl?: string;
     apiKey?: string;
   };
+  mistral?: {
+    chatModel?: string;
+    ocrModel?: string;
+    tableFormat?: 'markdown' | 'html';
+  };
   ollama?: {
     baseUrl?: string;
     model?: string;
     visionModel?: string;
+    defaultOptions?: {
+      num_ctx?: number;
+      temperature?: number;
+      top_k?: number;
+      top_p?: number;
+      repeat_penalty?: number;
+      num_predict?: number;
+      stop?: string[];
+      seed?: number;
+    };
+    defaultTimeout?: number;
+  };
+  elevenlabs?: {
+    defaultVoiceId?: string;
+    defaultModelId?: string;
   };
 }
 
-export type TProvider = 'openai' | 'anthropic' | 'perplexity' | 'ollama' | 'exo' | 'groq' | 'xai';
+export type TProvider = 'openai' | 'anthropic' | 'perplexity' | 'ollama' | 'exo' | 'groq' | 'mistral' | 'xai' | 'elevenlabs';
 
 export class SmartAi {
   public options: ISmartAiOptions;
@@ -37,7 +61,9 @@ export class SmartAi {
   public ollamaProvider: OllamaProvider;
   public exoProvider: ExoProvider;
   public groqProvider: GroqProvider;
+  public mistralProvider: MistralProvider;
   public xaiProvider: XAIProvider;
+  public elevenlabsProvider: ElevenLabsProvider;
 
   constructor(optionsArg: ISmartAiOptions) {
     this.options = optionsArg;
@@ -68,17 +94,36 @@ export class SmartAi {
       });
       await this.groqProvider.start();
     }
+    if (this.options.mistralToken) {
+      this.mistralProvider = new MistralProvider({
+        mistralToken: this.options.mistralToken,
+        chatModel: this.options.mistral?.chatModel,
+        ocrModel: this.options.mistral?.ocrModel,
+        tableFormat: this.options.mistral?.tableFormat,
+      });
+      await this.mistralProvider.start();
+    }
     if (this.options.xaiToken) {
       this.xaiProvider = new XAIProvider({
         xaiToken: this.options.xaiToken,
       });
       await this.xaiProvider.start();
     }
+    if (this.options.elevenlabsToken) {
+      this.elevenlabsProvider = new ElevenLabsProvider({
+        elevenlabsToken: this.options.elevenlabsToken,
+        defaultVoiceId: this.options.elevenlabs?.defaultVoiceId,
+        defaultModelId: this.options.elevenlabs?.defaultModelId,
+      });
+      await this.elevenlabsProvider.start();
+    }
     if (this.options.ollama) {
       this.ollamaProvider = new OllamaProvider({
         baseUrl: this.options.ollama.baseUrl,
         model: this.options.ollama.model,
         visionModel: this.options.ollama.visionModel,
+        defaultOptions: this.options.ollama.defaultOptions,
+        defaultTimeout: this.options.ollama.defaultTimeout,
       });
       await this.ollamaProvider.start();
     }
@@ -91,7 +136,35 @@ 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.mistralProvider) {
+      await this.mistralProvider.stop();
+    }
+    if (this.xaiProvider) {
+      await this.xaiProvider.stop();
+    }
+    if (this.elevenlabsProvider) {
+      await this.elevenlabsProvider.stop();
+    }
+    if (this.ollamaProvider) {
+      await this.ollamaProvider.stop();
+    }
+    if (this.exoProvider) {
+      await this.exoProvider.stop();
+    }
+  }
   
   /**
    * create a new conversation
@@ -110,8 +183,12 @@ export class SmartAi {
         return Conversation.createWithOllama(this);
       case 'groq':
         return Conversation.createWithGroq(this);
+      case 'mistral':
+        return Conversation.createWithMistral(this);
       case 'xai':
         return Conversation.createWithXai(this);
+      case 'elevenlabs':
+        return Conversation.createWithElevenlabs(this);
       default:
         throw new Error('Provider not available');
     }

ts/index.ts

@@ -1,3 +1,11 @@
 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.mistral.js';
+export * from './provider.ollama.js';
+export * from './provider.xai.js';
+export * from './provider.exo.js';
+export * from './provider.elevenlabs.js';

ts/plugins.ts

@@ -8,7 +8,7 @@ export {
 // @push.rocks scope
 import * as qenv from '@push.rocks/qenv';
 import * as smartarray from '@push.rocks/smartarray';
-import * as smartfile from '@push.rocks/smartfile';
+import * as smartfs from '@push.rocks/smartfs';
 import * as smartpath from '@push.rocks/smartpath';
 import * as smartpdf from '@push.rocks/smartpdf';
 import * as smartpromise from '@push.rocks/smartpromise';
@@ -18,7 +18,7 @@ import * as webstream from '@push.rocks/webstream';
 export {
   smartarray,
   qenv,
-  smartfile,
+  smartfs,
   smartpath,
   smartpdf,
   smartpromise,
@@ -28,9 +28,11 @@ export {
 
 // third party
 import * as anthropic from '@anthropic-ai/sdk';
+import * as mistralai from '@mistralai/mistralai';
 import * as openai from 'openai';
 
 export {
   anthropic,
+  mistralai,
   openai,
 }

ts/provider.anthropic.ts

@@ -1,13 +1,26 @@
 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[];
+  extendedThinking?: 'quick' | 'normal' | 'deep' | 'off';
 }
 
 export class AnthropicProvider extends MultiModalModel {
@@ -20,12 +33,34 @@ 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();
+  }
+
+  /**
+   * Returns the thinking configuration based on provider options.
+   * Defaults to 'normal' mode (8000 tokens) if not specified.
+   */
+  private getThinkingConfig(): { type: 'enabled'; budget_tokens: number } | undefined {
+    const mode = this.options.extendedThinking ?? 'normal';
+
+    const budgetMap = {
+      quick: 2048,
+      normal: 8000,
+      deep: 16000,
+      off: 0,
+    };
+
+    const budget = budgetMap[mode];
+
+    return budget > 0 ? { type: 'enabled', budget_tokens: budget } : undefined;
+  }
 
   public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
     // Create a TextDecoder to handle incoming chunks
@@ -61,12 +96,14 @@ export class AnthropicProvider extends MultiModalModel {
 
         // If we have a complete message, send it to Anthropic
         if (currentMessage) {
+          const thinkingConfig = this.getThinkingConfig();
           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,
-            max_tokens: 4000,
+            max_tokens: 20000,
+            ...(thinkingConfig && { thinking: thinkingConfig }),
           });
 
           // Process each chunk from Anthropic
@@ -105,14 +142,16 @@ export class AnthropicProvider extends MultiModalModel {
       content: msg.content
     }));
 
+    const thinkingConfig = this.getThinkingConfig();
     const result = await this.anthropicApiClient.messages.create({
-      model: 'claude-3-opus-20240229',
+      model: 'claude-sonnet-4-5-20250929',
       system: optionsArg.systemMessage,
       messages: [
         ...messages,
         { role: 'user' as const, content: optionsArg.userMessage }
       ],
-      max_tokens: 4000,
+      max_tokens: 20000,
+      ...(thinkingConfig && { thinking: thinkingConfig }),
     });
 
     // Extract text content from the response
@@ -152,13 +191,15 @@ export class AnthropicProvider extends MultiModalModel {
       }
     ];
 
+    const thinkingConfig = this.getThinkingConfig();
     const result = await this.anthropicApiClient.messages.create({
-      model: 'claude-3-opus-20240229',
+      model: 'claude-sonnet-4-5-20250929',
       messages: [{
         role: 'user',
         content
       }],
-      max_tokens: 1024
+      max_tokens: 10000,
+      ...(thinkingConfig && { thinking: thinkingConfig }),
     });
 
     // Extract text content from the response
@@ -177,12 +218,14 @@ export class AnthropicProvider extends MultiModalModel {
     pdfDocuments: Uint8Array[];
     messageHistory: ChatMessage[];
   }): Promise<{ message: any }> {
+    // Ensure SmartPdf is initialized before processing documents
+    await this.ensureSmartpdfReady();
+
     // 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);
     }
 
@@ -206,20 +249,22 @@ export class AnthropicProvider extends MultiModalModel {
         type: 'image',
         source: {
           type: 'base64',
-          media_type: 'image/jpeg',
+          media_type: 'image/png',
           data: Buffer.from(imageBytes).toString('base64')
         }
       });
     }
 
+    const thinkingConfig = this.getThinkingConfig();
     const result = await this.anthropicApiClient.messages.create({
-      model: 'claude-3-opus-20240229',
+      model: 'claude-sonnet-4-5-20250929',
       system: optionsArg.systemMessage,
       messages: [
         ...messages,
         { role: 'user', content }
       ],
-      max_tokens: 4096
+      max_tokens: 20000,
+      ...(thinkingConfig && { thinking: thinkingConfig }),
     });
 
     // Extract text content from the response
@@ -237,4 +282,165 @@ 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' ? 20000 :
+                        optionsArg.searchDepth === 'advanced' ? 20000 : 20000;
+
+      // Add thinking configuration if enabled
+      const thinkingConfig = this.getThinkingConfig();
+
+      // Create the research request
+      // Note: When thinking is enabled, temperature must be 1 (or omitted)
+      const requestParams: any = {
+        model: 'claude-sonnet-4-5-20250929',
+        system: systemMessage,
+        messages: [
+          {
+            role: 'user' as const,
+            content: optionsArg.query
+          }
+        ],
+        max_tokens: maxTokens,
+        // Only set temperature when thinking is NOT enabled
+        ...(thinkingConfig ? {} : { temperature: 0.7 })
+      };
+
+      // Add tools if web search is enabled
+      if (tools.length > 0) {
+        requestParams.tools = tools;
+      }
+
+      // Add thinking configuration if enabled
+      if (thinkingConfig) {
+        requestParams.thinking = thinkingConfig;
+      }
+
+      // 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.');
+  }
 }

ts/provider.elevenlabs.ts

@@ -0,0 +1,116 @@
+import * as plugins from './plugins.js';
+import { Readable } from 'stream';
+
+import { MultiModalModel } from './abstract.classes.multimodal.js';
+import type {
+  ChatOptions,
+  ChatResponse,
+  ResearchOptions,
+  ResearchResponse,
+  ImageGenerateOptions,
+  ImageEditOptions,
+  ImageResponse
+} from './abstract.classes.multimodal.js';
+
+export interface IElevenLabsProviderOptions {
+  elevenlabsToken: string;
+  defaultVoiceId?: string;
+  defaultModelId?: string;
+}
+
+export interface IElevenLabsVoiceSettings {
+  stability?: number;
+  similarity_boost?: number;
+  style?: number;
+  use_speaker_boost?: boolean;
+}
+
+export class ElevenLabsProvider extends MultiModalModel {
+  private options: IElevenLabsProviderOptions;
+  private baseUrl: string = 'https://api.elevenlabs.io/v1';
+
+  constructor(optionsArg: IElevenLabsProviderOptions) {
+    super();
+    this.options = optionsArg;
+  }
+
+  public async start() {
+    await super.start();
+  }
+
+  public async stop() {
+    await super.stop();
+  }
+
+  public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
+    throw new Error('ElevenLabs does not support chat functionality. This provider is specialized for text-to-speech only.');
+  }
+
+  public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
+    throw new Error('ElevenLabs does not support chat streaming functionality. This provider is specialized for text-to-speech only.');
+  }
+
+  public async audio(optionsArg: { 
+    message: string; 
+    voiceId?: string; 
+    modelId?: string;
+    voiceSettings?: IElevenLabsVoiceSettings;
+  }): Promise<NodeJS.ReadableStream> {
+    // Use Samara voice as default fallback
+    const voiceId = optionsArg.voiceId || this.options.defaultVoiceId || '19STyYD15bswVz51nqLf';
+
+    const modelId = optionsArg.modelId || this.options.defaultModelId || 'eleven_v3';
+
+    const url = `${this.baseUrl}/text-to-speech/${voiceId}`;
+    
+    const requestBody: any = {
+      text: optionsArg.message,
+      model_id: modelId,
+    };
+
+    if (optionsArg.voiceSettings) {
+      requestBody.voice_settings = optionsArg.voiceSettings;
+    }
+
+    const response = await plugins.smartrequest.SmartRequest.create()
+      .url(url)
+      .header('xi-api-key', this.options.elevenlabsToken)
+      .json(requestBody)
+      .autoDrain(false)
+      .post();
+
+    if (!response.ok) {
+      const errorText = await response.text();
+      throw new Error(`ElevenLabs API error: ${response.status} ${response.statusText} - ${errorText}`);
+    }
+
+    const webStream = response.stream();
+    const nodeStream = Readable.fromWeb(webStream as any);
+    return nodeStream;
+  }
+
+  public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
+    throw new Error('ElevenLabs does not support vision functionality. This provider is specialized for text-to-speech only.');
+  }
+
+  public async document(optionsArg: {
+    systemMessage: string;
+    userMessage: string;
+    pdfDocuments: Uint8Array[];
+    messageHistory: any[];
+  }): Promise<{ message: any }> {
+    throw new Error('ElevenLabs does not support document processing. This provider is specialized for text-to-speech only.');
+  }
+
+  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
+    throw new Error('ElevenLabs does not support research capabilities. This provider is specialized for text-to-speech only.');
+  }
+
+  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
+    throw new Error('ElevenLabs does not support image generation. This provider is specialized for text-to-speech only.');
+  }
+
+  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
+    throw new Error('ElevenLabs does not support image editing. This provider is specialized for text-to-speech only.');
+  }
+}

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.');
+  }
 }

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.');
+  }
 }

ts/provider.mistral.ts

@@ -0,0 +1,352 @@
+import * as plugins from './plugins.js';
+import { MultiModalModel } from './abstract.classes.multimodal.js';
+import type {
+  ChatOptions,
+  ChatResponse,
+  ChatMessage,
+  ResearchOptions,
+  ResearchResponse,
+  ImageGenerateOptions,
+  ImageEditOptions,
+  ImageResponse
+} from './abstract.classes.multimodal.js';
+
+export interface IMistralProviderOptions {
+  mistralToken: string;
+  chatModel?: string;       // default: 'mistral-large-latest'
+  ocrModel?: string;        // default: 'mistral-ocr-latest'
+  tableFormat?: 'markdown' | 'html';
+}
+
+export class MistralProvider extends MultiModalModel {
+  private options: IMistralProviderOptions;
+  public mistralClient: plugins.mistralai.Mistral;
+
+  constructor(optionsArg: IMistralProviderOptions) {
+    super();
+    this.options = optionsArg;
+  }
+
+  async start() {
+    await super.start();
+    this.mistralClient = new plugins.mistralai.Mistral({
+      apiKey: this.options.mistralToken,
+    });
+  }
+
+  async stop() {
+    await super.stop();
+  }
+
+  /**
+   * Synchronous chat interaction using Mistral's chat API
+   */
+  public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
+    // Convert message history to Mistral format
+    const messages: Array<{
+      role: 'system' | 'user' | 'assistant';
+      content: string;
+    }> = [];
+
+    // Add system message first
+    if (optionsArg.systemMessage) {
+      messages.push({
+        role: 'system',
+        content: optionsArg.systemMessage
+      });
+    }
+
+    // Add message history
+    for (const msg of optionsArg.messageHistory) {
+      messages.push({
+        role: msg.role === 'system' ? 'system' : msg.role === 'assistant' ? 'assistant' : 'user',
+        content: msg.content
+      });
+    }
+
+    // Add current user message
+    messages.push({
+      role: 'user',
+      content: optionsArg.userMessage
+    });
+
+    const result = await this.mistralClient.chat.complete({
+      model: this.options.chatModel || 'mistral-large-latest',
+      messages: messages,
+    });
+
+    // Extract content from response
+    const choice = result.choices?.[0];
+    let content = '';
+
+    if (choice?.message?.content) {
+      if (typeof choice.message.content === 'string') {
+        content = choice.message.content;
+      } else if (Array.isArray(choice.message.content)) {
+        // Handle array of content chunks
+        content = choice.message.content
+          .map((chunk: any) => {
+            if (typeof chunk === 'string') return chunk;
+            if (chunk && typeof chunk === 'object' && 'text' in chunk) return chunk.text;
+            return '';
+          })
+          .join('');
+      }
+    }
+
+    return {
+      role: 'assistant',
+      message: content,
+    };
+  }
+
+  /**
+   * Streaming chat using Mistral's streaming API
+   */
+  public async chatStream(input: ReadableStream<Uint8Array>): Promise<ReadableStream<string>> {
+    const decoder = new TextDecoder();
+    let buffer = '';
+    const mistralClient = this.mistralClient;
+    const chatModel = this.options.chatModel || 'mistral-large-latest';
+
+    const transform = new TransformStream<Uint8Array, string>({
+      async transform(chunk, controller) {
+        buffer += decoder.decode(chunk, { stream: true });
+
+        // Try to parse complete JSON messages from the buffer
+        while (true) {
+          const newlineIndex = buffer.indexOf('\n');
+          if (newlineIndex === -1) break;
+
+          const line = buffer.slice(0, newlineIndex);
+          buffer = buffer.slice(newlineIndex + 1);
+
+          if (line.trim()) {
+            try {
+              const message = JSON.parse(line);
+
+              // Build messages array
+              const messages: Array<{
+                role: 'system' | 'user' | 'assistant';
+                content: string;
+              }> = [];
+
+              if (message.systemMessage) {
+                messages.push({
+                  role: 'system',
+                  content: message.systemMessage
+                });
+              }
+
+              messages.push({
+                role: message.role === 'assistant' ? 'assistant' : 'user',
+                content: message.content
+              });
+
+              // Use Mistral streaming
+              const stream = await mistralClient.chat.stream({
+                model: chatModel,
+                messages: messages,
+              });
+
+              // Process streaming events
+              for await (const event of stream) {
+                const delta = event.data?.choices?.[0]?.delta;
+                if (delta?.content) {
+                  if (typeof delta.content === 'string') {
+                    controller.enqueue(delta.content);
+                  } else if (Array.isArray(delta.content)) {
+                    for (const chunk of delta.content) {
+                      if (typeof chunk === 'string') {
+                        controller.enqueue(chunk);
+                      } else if (chunk && typeof chunk === 'object' && 'text' in chunk) {
+                        controller.enqueue((chunk as any).text);
+                      }
+                    }
+                  }
+                }
+              }
+            } catch (e) {
+              console.error('Failed to parse message:', e);
+            }
+          }
+        }
+      },
+
+      flush(controller) {
+        if (buffer.trim()) {
+          try {
+            const message = JSON.parse(buffer);
+            controller.enqueue(message.content || '');
+          } catch (e) {
+            console.error('Failed to parse remaining buffer:', e);
+          }
+        }
+      }
+    });
+
+    return input.pipeThrough(transform);
+  }
+
+  /**
+   * Audio generation is not supported by Mistral
+   */
+  public async audio(optionsArg: { message: string }): Promise<NodeJS.ReadableStream> {
+    throw new Error('Audio generation is not supported by Mistral. Please use ElevenLabs or OpenAI provider for audio generation.');
+  }
+
+  /**
+   * Vision using Mistral's OCR API for image analysis
+   */
+  public async vision(optionsArg: { image: Buffer; prompt: string }): Promise<string> {
+    const base64Image = optionsArg.image.toString('base64');
+
+    // Detect image type from buffer header
+    let mimeType = 'image/jpeg';
+    if (optionsArg.image[0] === 0x89 && optionsArg.image[1] === 0x50) {
+      mimeType = 'image/png';
+    } else if (optionsArg.image[0] === 0x47 && optionsArg.image[1] === 0x49) {
+      mimeType = 'image/gif';
+    } else if (optionsArg.image[0] === 0x52 && optionsArg.image[1] === 0x49) {
+      mimeType = 'image/webp';
+    }
+
+    // Use OCR API with image data URL
+    const ocrResult = await this.mistralClient.ocr.process({
+      model: this.options.ocrModel || 'mistral-ocr-latest',
+      document: {
+        imageUrl: `data:${mimeType};base64,${base64Image}`,
+        type: 'image_url',
+      },
+    });
+
+    // Combine markdown from all pages
+    const extractedText = ocrResult.pages.map(page => page.markdown).join('\n\n');
+
+    // If a prompt is provided, use chat to analyze the extracted text
+    if (optionsArg.prompt && optionsArg.prompt.trim()) {
+      const chatResponse = await this.chat({
+        systemMessage: 'You are an assistant analyzing image content. The following is text extracted from an image using OCR.',
+        userMessage: `${optionsArg.prompt}\n\nExtracted content:\n${extractedText}`,
+        messageHistory: [],
+      });
+      return chatResponse.message;
+    }
+
+    return extractedText;
+  }
+
+  /**
+   * Document processing using Mistral's OCR API
+   * PDFs are uploaded via Files API first, then processed with OCR
+   */
+  public async document(optionsArg: {
+    systemMessage: string;
+    userMessage: string;
+    pdfDocuments: Uint8Array[];
+    messageHistory: ChatMessage[];
+  }): Promise<{ message: any }> {
+    const extractedTexts: string[] = [];
+    const uploadedFileIds: string[] = [];
+
+    try {
+      // Process each PDF document using Mistral OCR
+      for (let i = 0; i < optionsArg.pdfDocuments.length; i++) {
+        const pdfDocument = optionsArg.pdfDocuments[i];
+
+        // Upload the PDF to Mistral's Files API first
+        const uploadResult = await this.mistralClient.files.upload({
+          file: {
+            fileName: `document_${i + 1}.pdf`,
+            content: pdfDocument,
+          },
+          purpose: 'ocr',
+        });
+
+        uploadedFileIds.push(uploadResult.id);
+
+        // Now use OCR with the uploaded file
+        const ocrResult = await this.mistralClient.ocr.process({
+          model: this.options.ocrModel || 'mistral-ocr-latest',
+          document: {
+            type: 'file',
+            fileId: uploadResult.id,
+          },
+          tableFormat: this.options.tableFormat || 'markdown',
+        });
+
+        // Combine all page markdown with page separators
+        const pageTexts = ocrResult.pages.map((page, index) => {
+          let pageContent = `--- Page ${index + 1} ---\n${page.markdown}`;
+
+          // Include tables if present
+          if (page.tables && page.tables.length > 0) {
+            pageContent += '\n\n**Tables:**\n' + page.tables.map((t: any) => t.markdown || t.html || '').join('\n');
+          }
+
+          // Include header/footer if present
+          if (page.header) {
+            pageContent = `Header: ${page.header}\n${pageContent}`;
+          }
+          if (page.footer) {
+            pageContent += `\nFooter: ${page.footer}`;
+          }
+
+          return pageContent;
+        }).join('\n\n');
+
+        extractedTexts.push(pageTexts);
+      }
+
+      // Combine all document texts
+      const allDocumentText = extractedTexts.length === 1
+        ? extractedTexts[0]
+        : extractedTexts.map((text, i) => `=== Document ${i + 1} ===\n${text}`).join('\n\n');
+
+      // Use chat API to process the extracted text with the user's query
+      const chatResponse = await this.chat({
+        systemMessage: optionsArg.systemMessage || 'You are a helpful assistant analyzing document content.',
+        userMessage: `${optionsArg.userMessage}\n\n---\nDocument Content:\n${allDocumentText}`,
+        messageHistory: optionsArg.messageHistory,
+      });
+
+      return {
+        message: {
+          role: 'assistant',
+          content: chatResponse.message
+        }
+      };
+    } finally {
+      // Clean up uploaded files
+      for (const fileId of uploadedFileIds) {
+        try {
+          await this.mistralClient.files.delete({ fileId });
+        } catch (cleanupError) {
+          // Ignore cleanup errors - files may have already been auto-deleted
+          console.warn(`Failed to delete temporary file ${fileId}:`, cleanupError);
+        }
+      }
+    }
+  }
+
+  /**
+   * Research is not natively supported by Mistral
+   */
+  public async research(optionsArg: ResearchOptions): Promise<ResearchResponse> {
+    throw new Error('Research/web search is not supported by Mistral. Please use Perplexity or Anthropic provider for research capabilities.');
+  }
+
+  /**
+   * Image generation is not supported by Mistral
+   */
+  public async imageGenerate(optionsArg: ImageGenerateOptions): Promise<ImageResponse> {
+    throw new Error('Image generation is not supported by Mistral. Please use OpenAI provider for image generation.');
+  }
+
+  /**
+   * Image editing is not supported by Mistral
+   */
+  public async imageEdit(optionsArg: ImageEditOptions): Promise<ImageResponse> {
+    throw new Error('Image editing is not supported by Mistral. Please use OpenAI provider for image editing.');
+  }
+}

ts/provider.ollama.ts

@@ -1,12 +1,109 @@
 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,
+  StreamingChatOptions
+} from './abstract.classes.multimodal.js';
+
+/**
+ * Ollama model runtime options
+ * @see https://github.com/ollama/ollama/blob/main/docs/modelfile.md
+ */
+export interface IOllamaModelOptions {
+  num_ctx?: number;       // Context window (default: 2048)
+  temperature?: number;   // 0 = deterministic (default: 0.8)
+  top_k?: number;         // Top-k sampling (default: 40)
+  top_p?: number;         // Nucleus sampling (default: 0.9)
+  repeat_penalty?: number;// Repeat penalty (default: 1.1)
+  num_predict?: number;   // Max tokens to predict
+  stop?: string[];        // Stop sequences
+  seed?: number;          // Random seed for reproducibility
+  think?: boolean;        // Enable thinking/reasoning mode (for GPT-OSS, QwQ, etc.)
+}
+
+/**
+ * JSON Schema tool definition for Ollama native tool calling
+ * @see https://docs.ollama.com/capabilities/tool-calling
+ */
+export interface IOllamaTool {
+  type: 'function';
+  function: {
+    name: string;
+    description: string;
+    parameters: {
+      type: 'object';
+      properties: Record<string, {
+        type: string;
+        description?: string;
+        enum?: string[];
+      }>;
+      required?: string[];
+    };
+  };
+}
+
+/**
+ * Tool call returned by model in native tool calling mode
+ */
+export interface IOllamaToolCall {
+  function: {
+    name: string;
+    arguments: Record<string, unknown>;
+    index?: number;
+  };
+}
 
 export interface IOllamaProviderOptions {
   baseUrl?: string;
   model?: string;
   visionModel?: string; // Model to use for vision tasks (e.g. 'llava')
+  defaultOptions?: IOllamaModelOptions;  // Default model options
+  defaultTimeout?: number;               // Default timeout in ms (default: 120000)
+}
+
+/**
+ * Extended chat options with Ollama-specific settings
+ */
+export interface IOllamaChatOptions extends ChatOptions {
+  options?: IOllamaModelOptions;  // Per-request model options
+  timeout?: number;               // Per-request timeout in ms
+  model?: string;                 // Per-request model override
+  tools?: IOllamaTool[];          // Available tools for native function calling
+  // images is inherited from ChatOptions
+}
+
+/**
+ * Chunk emitted during streaming
+ */
+export interface IOllamaStreamChunk {
+  content: string;
+  thinking?: string;  // For models with extended thinking
+  toolCalls?: IOllamaToolCall[];  // Tool calls in streaming mode
+  done: boolean;
+  stats?: {
+    totalDuration?: number;
+    evalCount?: number;
+  };
+}
+
+/**
+ * Extended chat response with Ollama-specific fields
+ */
+export interface IOllamaChatResponse extends ChatResponse {
+  thinking?: string;
+  toolCalls?: IOllamaToolCall[];  // Tool calls from model (native tool calling)
+  stats?: {
+    totalDuration?: number;
+    evalCount?: number;
+  };
 }
 
 export class OllamaProvider extends MultiModalModel {
@@ -14,6 +111,8 @@ export class OllamaProvider extends MultiModalModel {
   private baseUrl: string;
   private model: string;
   private visionModel: string;
+  private defaultOptions: IOllamaModelOptions;
+  private defaultTimeout: number;
 
   constructor(optionsArg: IOllamaProviderOptions = {}) {
     super();
@@ -21,9 +120,12 @@ export class OllamaProvider extends MultiModalModel {
     this.baseUrl = optionsArg.baseUrl || 'http://localhost:11434';
     this.model = optionsArg.model || 'llama2';
     this.visionModel = optionsArg.visionModel || 'llava';
+    this.defaultOptions = optionsArg.defaultOptions || {};
+    this.defaultTimeout = optionsArg.defaultTimeout || 120000;
   }
 
   async start() {
+    await super.start();
     // Verify Ollama is running
     try {
       const response = await fetch(`${this.baseUrl}/api/tags`);
@@ -35,7 +137,9 @@ 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
@@ -136,23 +240,56 @@ export class OllamaProvider extends MultiModalModel {
   // Implementing the synchronous chat interaction
   public async chat(optionsArg: ChatOptions): Promise<ChatResponse> {
     // Format messages for Ollama
+    const historyMessages = optionsArg.messageHistory.map((msg) => {
+      const formatted: { role: string; content: string; images?: string[]; reasoning?: string } = {
+        role: msg.role,
+        content: msg.content,
+      };
+      if (msg.images && msg.images.length > 0) {
+        formatted.images = msg.images;
+      }
+      if (msg.reasoning) {
+        formatted.reasoning = msg.reasoning;
+      }
+      return formatted;
+    });
+
+    // Build user message with optional images
+    const userMessage: { role: string; content: string; images?: string[] } = {
+      role: 'user',
+      content: optionsArg.userMessage,
+    };
+    if (optionsArg.images && optionsArg.images.length > 0) {
+      userMessage.images = optionsArg.images;
+    }
+
     const messages = [
       { role: 'system', content: optionsArg.systemMessage },
-      ...optionsArg.messageHistory,
+      ...historyMessages,
-      { role: 'user', content: optionsArg.userMessage }
+      userMessage,
     ];
 
-    // Make API call to Ollama
+    // Build request body - include think parameter if set
+    const requestBody: Record<string, unknown> = {
+      model: this.model,
+      messages: messages,
+      stream: false,
+      options: this.defaultOptions,
+    };
+
+    // Add think parameter for reasoning models (GPT-OSS, QwQ, etc.)
+    if (this.defaultOptions.think !== undefined) {
+      requestBody.think = this.defaultOptions.think;
+    }
+
+    // Make API call to Ollama with defaultOptions and timeout
     const response = await fetch(`${this.baseUrl}/api/chat`, {
       method: 'POST',
       headers: {
         'Content-Type': 'application/json',
       },
-      body: JSON.stringify({
+      body: JSON.stringify(requestBody),
-        model: this.model,
+      signal: AbortSignal.timeout(this.defaultTimeout),
-        messages: messages,
-        stream: false
-      }),
     });
 
     if (!response.ok) {
@@ -160,10 +297,296 @@ export class OllamaProvider extends MultiModalModel {
     }
 
     const result = await response.json();
-    
+
     return {
       role: 'assistant' as const,
       message: result.message.content,
+      reasoning: result.message.thinking || result.message.reasoning,
+    };
+  }
+
+  /**
+   * Streaming chat with token callback (implements MultiModalModel interface)
+   * Calls onToken for each token generated during the response
+   */
+  public async chatStreaming(optionsArg: StreamingChatOptions): Promise<ChatResponse> {
+    const onToken = optionsArg.onToken;
+
+    // Use existing collectStreamResponse with callback, including images
+    const response = await this.collectStreamResponse(
+      {
+        systemMessage: optionsArg.systemMessage,
+        userMessage: optionsArg.userMessage,
+        messageHistory: optionsArg.messageHistory,
+        images: optionsArg.images,
+      },
+      (chunk) => {
+        if (onToken) {
+          if (chunk.thinking) onToken(chunk.thinking);
+          if (chunk.content) onToken(chunk.content);
+        }
+      }
+    );
+
+    return {
+      role: 'assistant' as const,
+      message: response.message,
+      reasoning: response.thinking,
+    };
+  }
+
+  /**
+   * Streaming chat with async iteration and options support
+   */
+  public async chatStreamResponse(
+    optionsArg: IOllamaChatOptions
+  ): Promise<AsyncIterable<IOllamaStreamChunk>> {
+    const model = optionsArg.model || this.model;
+    const timeout = optionsArg.timeout || this.defaultTimeout;
+    const modelOptions = { ...this.defaultOptions, ...optionsArg.options };
+
+    // Format history messages with optional images and reasoning
+    const historyMessages = optionsArg.messageHistory.map((msg) => {
+      const formatted: { role: string; content: string; images?: string[]; reasoning?: string } = {
+        role: msg.role,
+        content: msg.content,
+      };
+      if (msg.images && msg.images.length > 0) {
+        formatted.images = msg.images;
+      }
+      if (msg.reasoning) {
+        formatted.reasoning = msg.reasoning;
+      }
+      return formatted;
+    });
+
+    // Build user message with optional images
+    const userMessage: { role: string; content: string; images?: string[] } = {
+      role: 'user',
+      content: optionsArg.userMessage,
+    };
+    if (optionsArg.images && optionsArg.images.length > 0) {
+      userMessage.images = optionsArg.images;
+    }
+
+    const messages = [
+      { role: 'system', content: optionsArg.systemMessage },
+      ...historyMessages,
+      userMessage,
+    ];
+
+    // Build request body with optional tools and think parameters
+    const requestBody: Record<string, unknown> = {
+      model,
+      messages,
+      stream: true,
+      options: modelOptions,
+    };
+
+    // Add think parameter for reasoning models (GPT-OSS, QwQ, etc.)
+    if (modelOptions.think !== undefined) {
+      requestBody.think = modelOptions.think;
+    }
+
+    // Add tools for native function calling
+    if (optionsArg.tools && optionsArg.tools.length > 0) {
+      requestBody.tools = optionsArg.tools;
+    }
+
+    const response = await fetch(`${this.baseUrl}/api/chat`, {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify(requestBody),
+      signal: AbortSignal.timeout(timeout),
+    });
+
+    if (!response.ok) {
+      throw new Error(`Ollama API error: ${response.status}`);
+    }
+
+    const reader = response.body!.getReader();
+    const decoder = new TextDecoder();
+
+    return {
+      [Symbol.asyncIterator]: async function* () {
+        let buffer = '';
+        try {
+          while (true) {
+            const { done, value } = await reader.read();
+            if (done) break;
+            buffer += decoder.decode(value, { stream: true });
+            const lines = buffer.split('\n');
+            buffer = lines.pop() || '';
+            for (const line of lines) {
+              if (!line.trim()) continue;
+              try {
+                const json = JSON.parse(line);
+
+                // Parse tool_calls from response
+                let toolCalls: IOllamaToolCall[] | undefined;
+                if (json.message?.tool_calls && Array.isArray(json.message.tool_calls)) {
+                  toolCalls = json.message.tool_calls.map((tc: any) => ({
+                    function: {
+                      name: tc.function?.name || '',
+                      arguments: typeof tc.function?.arguments === 'string'
+                        ? JSON.parse(tc.function.arguments)
+                        : tc.function?.arguments || {},
+                      index: tc.index,
+                    },
+                  }));
+                }
+
+                yield {
+                  content: json.message?.content || '',
+                  thinking: json.message?.thinking,
+                  toolCalls,
+                  done: json.done || false,
+                  stats: json.done ? {
+                    totalDuration: json.total_duration,
+                    evalCount: json.eval_count,
+                  } : undefined,
+                } as IOllamaStreamChunk;
+              } catch { /* skip malformed */ }
+            }
+          }
+        } finally {
+          reader.releaseLock();
+        }
+      }
+    };
+  }
+
+  /**
+   * Stream and collect full response with optional progress callback
+   */
+  public async collectStreamResponse(
+    optionsArg: IOllamaChatOptions,
+    onChunk?: (chunk: IOllamaStreamChunk) => void
+  ): Promise<IOllamaChatResponse> {
+    const stream = await this.chatStreamResponse(optionsArg);
+    let content = '';
+    let thinking = '';
+    let toolCalls: IOllamaToolCall[] = [];
+    let stats: IOllamaChatResponse['stats'];
+
+    for await (const chunk of stream) {
+      if (chunk.content) content += chunk.content;
+      if (chunk.thinking) thinking += chunk.thinking;
+      if (chunk.toolCalls) toolCalls = toolCalls.concat(chunk.toolCalls);
+      if (chunk.stats) stats = chunk.stats;
+      if (onChunk) onChunk(chunk);
+    }
+
+    return {
+      role: 'assistant' as const,
+      message: content,
+      thinking: thinking || undefined,
+      toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
+      stats,
+    };
+  }
+
+  /**
+   * Non-streaming chat with full options support
+   */
+  public async chatWithOptions(optionsArg: IOllamaChatOptions): Promise<IOllamaChatResponse> {
+    const model = optionsArg.model || this.model;
+    const timeout = optionsArg.timeout || this.defaultTimeout;
+    const modelOptions = { ...this.defaultOptions, ...optionsArg.options };
+
+    // Format history messages with optional images, reasoning, and tool role
+    const historyMessages = optionsArg.messageHistory.map((msg) => {
+      // Handle tool result messages
+      if ((msg as any).role === 'tool') {
+        return {
+          role: 'tool',
+          content: msg.content,
+          tool_name: (msg as any).toolName,
+        };
+      }
+
+      const formatted: { role: string; content: string; images?: string[]; reasoning?: string } = {
+        role: msg.role,
+        content: msg.content,
+      };
+      if (msg.images && msg.images.length > 0) {
+        formatted.images = msg.images;
+      }
+      if (msg.reasoning) {
+        formatted.reasoning = msg.reasoning;
+      }
+      return formatted;
+    });
+
+    // Build user message with optional images
+    const userMessage: { role: string; content: string; images?: string[] } = {
+      role: 'user',
+      content: optionsArg.userMessage,
+    };
+    if (optionsArg.images && optionsArg.images.length > 0) {
+      userMessage.images = optionsArg.images;
+    }
+
+    const messages = [
+      { role: 'system', content: optionsArg.systemMessage },
+      ...historyMessages,
+      userMessage,
+    ];
+
+    // Build request body with optional tools and think parameters
+    const requestBody: Record<string, unknown> = {
+      model,
+      messages,
+      stream: false,
+      options: modelOptions,
+    };
+
+    // Add think parameter for reasoning models (GPT-OSS, QwQ, etc.)
+    if (modelOptions.think !== undefined) {
+      requestBody.think = modelOptions.think;
+    }
+
+    // Add tools for native function calling
+    if (optionsArg.tools && optionsArg.tools.length > 0) {
+      requestBody.tools = optionsArg.tools;
+    }
+
+    const response = await fetch(`${this.baseUrl}/api/chat`, {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify(requestBody),
+      signal: AbortSignal.timeout(timeout),
+    });
+
+    if (!response.ok) {
+      throw new Error(`Ollama API error: ${response.statusText}`);
+    }
+
+    const result = await response.json();
+
+    // Parse tool_calls from response
+    let toolCalls: IOllamaToolCall[] | undefined;
+    if (result.message?.tool_calls && Array.isArray(result.message.tool_calls)) {
+      toolCalls = result.message.tool_calls.map((tc: any) => ({
+        function: {
+          name: tc.function?.name || '',
+          arguments: typeof tc.function?.arguments === 'string'
+            ? JSON.parse(tc.function.arguments)
+            : tc.function?.arguments || {},
+          index: tc.index,
+        },
+      }));
+    }
+
+    return {
+      role: 'assistant' as const,
+      message: result.message.content || '',
+      thinking: result.message.thinking,
+      toolCalls,
+      stats: {
+        totalDuration: result.total_duration,
+        evalCount: result.eval_count,
+      },
     };
   }
 
@@ -204,12 +627,14 @@ export class OllamaProvider extends MultiModalModel {
     pdfDocuments: Uint8Array[];
     messageHistory: ChatMessage[];
   }): Promise<{ message: any }> {
+    // Ensure SmartPdf is initialized before processing documents
+    await this.ensureSmartpdfReady();
+
     // 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 +674,22 @@ 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.');
+  }
 }

ts/provider.openai.ts

@@ -1,5 +1,7 @@
 import * as plugins from './plugins.js';
 import * as paths from './paths.js';
+import { Readable } from 'stream';
+import { toFile } from 'openai';
 
 // Custom type definition for chat completion messages
 export type TChatCompletionRequestMessage = { 
@@ -8,19 +10,27 @@ 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 +38,16 @@ 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 +87,7 @@ 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 +133,7 @@ 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 +160,8 @@ 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;
   }
 
@@ -161,16 +174,16 @@ export class OpenAiProvider extends MultiModalModel {
       content: any;
     }[];
   }) {
+    // Ensure SmartPdf is initialized before processing documents
+    await this.ensureSmartpdfReady();
+
     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 +197,7 @@ export class OpenAiProvider extends MultiModalModel {
       },
     }));
 
-    const chatModel = this.options.chatModel ?? 'o4-mini';
+    const chatModel = this.options.chatModel ?? 'gpt-5-mini';
     const requestParams: any = {
       model: chatModel,
       messages: [
@@ -229,4 +242,221 @@ 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 {
+      // Convert Buffer to uploadable file format for OpenAI API
+      const imageFile = await toFile(optionsArg.image, 'image.png', { type: 'image/png' });
+
+      const requestParams: any = {
+        model,
+        image: imageFile,
+        prompt: optionsArg.prompt,
+        n: optionsArg.n || 1,
+      };
+
+      // Add mask if provided (also convert to file format)
+      if (optionsArg.mask) {
+        requestParams.mask = await toFile(optionsArg.mask, 'mask.png', { type: 'image/png' });
+      }
+
+      // 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}`);
+    }
+  }
 }

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.');
+  }
 }

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
@@ -139,11 +149,14 @@ export class XAIProvider extends MultiModalModel {
     pdfDocuments: Uint8Array[];
     messageHistory: { role: string; content: string; }[];
   }): Promise<{ message: any }> {
+    // Ensure SmartPdf is initialized before processing documents
+    await this.ensureSmartpdfReady();
+
     // First convert PDF documents to images
     let pdfDocumentImageBytesArray: Uint8Array[] = [];
-    
+
     for (const pdfDocument of optionsArg.pdfDocuments) {
-      const documentImageArray = await this.smartpdfInstance.convertPDFToPngBytes(pdfDocument);
+      const documentImageArray = await this.smartpdfInstance!.convertPDFToPngBytes(pdfDocument);
       pdfDocumentImageBytesArray = pdfDocumentImageBytesArray.concat(documentImageArray);
     }
 
@@ -180,4 +193,22 @@ 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.');
+  }
 }

tsconfig.json

@@ -6,9 +6,9 @@
     "module": "NodeNext",
     "moduleResolution": "NodeNext",
     "esModuleInterop": true,
-    "verbatimModuleSyntax": true
+    "verbatimModuleSyntax": true,
+    "baseUrl": ".",
+    "paths": {}
   },
-  "exclude": [
+  "exclude": ["dist_*/**/*.d.ts"]
-    "dist_*/**/*.d.ts"
-  ]
 }