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minor #138 Add CHANGELOG.md files for all components (OskarStark)
This PR was merged into the main branch. Discussion ---------- Add `CHANGELOG.md` files for all components | Q | A | ------------- | --- | Bug fix? | no | New feature? | no | Docs? | yes | Issues | -- | License | MIT Add comprehensive changelog files documenting all features for the upcoming 0.1 release. Generated based on code and git history. Commits ------- 12b9bf2 Add CHANGELOG.md files for all components
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‎src/agent/CHANGELOG.md

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CHANGELOG
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=========
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0.1
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---
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* Add Agent class as central orchestrator for AI interactions through the Platform component
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* Add input/output processing pipeline:
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- `InputProcessorInterface` for pre-processing messages and options
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- `OutputProcessorInterface` for post-processing LLM responses
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- `AgentAwareInterface` for processors requiring agent access
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- `SystemPromptInputProcessor` for system prompt injection
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- `ModelOverrideInputProcessor` for dynamic model switching
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* Add comprehensive tool system:
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- `#[AsTool]` attribute for simple tool registration
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- `ReflectionToolFactory` for auto-discovering tools with attributes
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- `MemoryToolFactory` for manual tool registration
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- `ChainFactory` for combining multiple factories
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- Automatic JSON Schema generation for parameter validation
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- Tool call execution with argument resolution
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- `ToolCallsExecuted` and `ToolCallArgumentsResolved` events
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- `FaultTolerantToolbox` for graceful error handling
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* Add built-in tools:
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- `SimilaritySearch` for RAG/vector store searches
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- `Agent` allowing agents to use other agents as tools
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- `Clock` for current date/time
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- `Brave` for web search integration
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- `Crawler` for web page crawling
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- `OpenMeteo` for weather information
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- `SerpApi` for search engine results
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- `Tavily` for AI-powered search
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- `Wikipedia` for Wikipedia content retrieval
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- `YouTubeTranscriber` for YouTube video transcription
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* Add structured output support:
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- PHP class output with automatic conversion from LLM responses
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- Array structure output with JSON schema validation
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- `ResponseFormatFactory` for schema generation
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- Symfony Serializer integration
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* Add memory management system:
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- `MemoryInputProcessor` for injecting contextual memory
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- `StaticMemoryProvider` for fixed contextual information
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- `EmbeddingProvider` for vector-based memory retrieval
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- Dynamic memory control with `use_memory` option
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- Extensible `MemoryInterface` for custom providers
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* Add advanced features:
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- Tool filtering to limit available tools per agent call
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- Tool message retention option for context preservation
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- Multi-method tools support in single classes
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- Tool parameter validation with `#[With]` attribute
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- Stream response support for real-time output
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- PSR-3 logger integration throughout
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- Symfony EventDispatcher integration
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* Add model capability detection before processing
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* Add fluent API with `Toolbox::create()` for easy instantiation
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* Add comprehensive type safety with full PHP type hints
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* Add clear exception hierarchy for different error scenarios

‎src/ai-bundle/CHANGELOG.md

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CHANGELOG
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=========
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0.1
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---
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* Add Symfony bundle for integrating Platform, Agent, and Store components
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* Add service configuration:
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- Agent services with configurable platforms and system prompts
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- Tool registration via `#[AsTool]` attribute and `symfony_ai.tool` tag
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- Input/Output processor registration via `symfony_ai.agent.input_processor` and `symfony_ai.agent.output_processor` tags
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- Abstract service definitions for extensibility
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* Add Symfony Profiler integration for monitoring AI interactions
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* Add security integration:
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- `#[IsGrantedTool]` attribute for tool-level authorization
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- Security voter integration for runtime permission checks
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* Add configuration options:
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- Multiple agents configuration with different platforms
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- Platform credentials (API keys, endpoints)
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- Model configurations per agent
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- Vector store configurations
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* Add dependency injection integration:
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- Autoconfiguration for tools and processors
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- Service aliases for default agent and platform
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- Factory services for creating platforms
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* Add bundle configuration with semantic validation
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* Add support for fault-tolerant tool execution
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* Add structured output configuration support

‎src/mcp-bundle/CHANGELOG.md

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CHANGELOG
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=========
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0.1
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---
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* Add Symfony bundle bridging MCP-SDK with Symfony applications
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* Add server mode exposing Symfony tools to MCP clients:
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- STDIO transport via `php bin/console mcp` command
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- SSE (Server-Sent Events) transport via HTTP endpoints
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- Automatic tool discovery and registration
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- Integration with AI-Bundle tools
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* Add routing configuration for SSE endpoints:
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- `/_mcp/sse` for SSE connections
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- `/_mcp/messages/{id}` for message retrieval
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* Add `McpController` for handling SSE connections
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* Add `McpCommand` providing STDIO interface
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* Add bundle configuration for enabling/disabling transports
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* Add cache-based SSE message storage
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* Add service configuration for MCP server setup

‎src/mcp-sdk/CHANGELOG.md

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CHANGELOG
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=========
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0.1
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---
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* Add Model Context Protocol (MCP) implementation for LLM-application communication
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* Add JSON-RPC based protocol handling with `JsonRpcHandler`
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* Add three core MCP capabilities:
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- Resources: File-like data readable by clients (API responses, file contents)
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- Tools: Functions callable by LLMs (with user approval)
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- Prompts: Pre-written templates for specific tasks
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* Add multiple transport implementations:
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- Symfony Console Transport for testing and CLI applications
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- Stream Transport supporting Server-Sent Events (SSE) and HTTP streaming
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- STDIO transport for command-line interfaces
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* Add capability chains for organizing features:
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- `ToolChain` for tool management
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- `ResourceChain` for resource management
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- `PromptChain` for prompt template management
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* Add Server component managing transport connections
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* Add request/notification handlers for MCP operations
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* Add standardized interface enabling LLMs to interact with external systems
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* Add support for building LLM "plugins" with extra context capabilities

‎src/platform/CHANGELOG.md

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CHANGELOG
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=========
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0.1
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---
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* Add unified abstraction layer for interacting with various AI models and providers
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* Add support for 13+ AI providers:
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- OpenAI (GPT-4, GPT-3.5, DALL·E, Whisper)
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- Anthropic (Claude models via native API and AWS Bedrock)
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- Google (Gemini models with server-side tools support)
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- Azure (OpenAI and Meta Llama models)
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- AWS Bedrock (Anthropic Claude, Meta Llama, Amazon Nova)
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- Mistral AI (language models and embeddings)
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- Meta Llama (via Azure, Ollama, Replicate, AWS Bedrock)
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- Ollama (local model hosting)
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- Replicate (cloud-based model hosting)
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- OpenRouter (Google Gemini, DeepSeek R1)
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- Voyage AI (specialized embeddings)
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- HuggingFace (extensive model support with multiple tasks)
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- TransformersPHP (local PHP-based transformer models)
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* Add comprehensive message system with role-based messaging:
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- `UserMessage` for user inputs with multi-modal content
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- `SystemMessage` for system instructions
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- `AssistantMessage` for AI responses
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- `ToolCallMessage` for tool execution results
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* Add support for multiple content types:
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- Text, Image, ImageUrl, Audio, Document, DocumentUrl, File
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* Add capability system for runtime model feature detection:
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- Input capabilities: TEXT, MESSAGES, IMAGE, AUDIO, PDF, MULTIPLE
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- Output capabilities: TEXT, IMAGE, AUDIO, STREAMING, STRUCTURED
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- Advanced capabilities: TOOL_CALLING
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* Add multiple response types:
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- `TextResponse` for standard text responses
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- `VectorResponse` for embedding vectors
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- `BinaryResponse` for binary data (images, audio)
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- `StreamResponse` for Server-Sent Events streaming
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- `ChoiceResponse` for multiple choice responses
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- `ToolCallResponse` for tool execution requests
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- `ObjectResponse` for structured object responses
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- `RawHttpResponse` for raw HTTP response access
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* Add real-time response streaming via Server-Sent Events
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* Add parallel processing support for concurrent model requests
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* Add tool calling support with JSON Schema parameter validation
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* Add contract system with normalizers for cross-platform compatibility
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* Add HuggingFace task support:
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- Text Classification, Token Classification, Fill Mask
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- Question Answering, Table Question Answering
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- Sentence Similarity, Zero-Shot Classification
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- Object Detection, Image Segmentation
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* Add metadata support for responses
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* Add token usage tracking
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* Add temperature and parameter controls
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* Add exception handling with specific error types
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* Add support for embeddings generation across multiple providers
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* Add response promises for async operations

‎src/store/CHANGELOG.md

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CHANGELOG
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=========
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0.1
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---
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* Add core store interfaces:
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- `StoreInterface` for basic document storage
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- `VectorStoreInterface` extending with similarity search capabilities
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- `InitializableStoreInterface` for stores requiring initialization
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* Add document types:
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- `TextDocument` for raw text with UUID, content, and metadata
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- `VectorDocument` for vectorized documents with embeddings and similarity scores
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- `Metadata` for key-value document metadata storage
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* Add document loading system:
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- `LoaderInterface` contract for various document sources
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- `TextFileLoader` for loading text files as TextDocuments
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* Add document transformation pipeline:
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- `TransformerInterface` contract for document processing
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- `TextSplitTransformer` for splitting large documents into chunks
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- `ChainTransformer` for combining multiple transformers
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- `ChunkDelayTransformer` for rate limiting during processing
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* Add vectorization support:
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- `Vectorizer` for converting TextDocuments to VectorDocuments
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- Batch vectorization support for compatible platforms
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- Single document vectorization with fallback
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* Add high-level `Indexer` service:
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- Orchestrates document processing pipeline
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- Accepts TextDocuments, vectorizes and stores in chunks
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- Configurable batch processing
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* Add `InMemoryStore` implementation with multiple distance algorithms:
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- Cosine similarity
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- Angular distance
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- Euclidean distance
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- Manhattan distance
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- Chebyshev distance
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* Add store bridge implementations:
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- PostgreSQL with pgvector extension
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- MariaDB
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- MongoDB
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- Azure AI Search
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- Meilisearch
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- ChromaDB
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- Pinecone
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* Add Retrieval Augmented Generation (RAG) support:
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- Document embedding storage
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- Similarity search for relevant documents
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- Dynamic context extension for AI applications
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* Add query features:
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- Vector similarity search with configurable options
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- Minimum score filtering
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- Result limiting
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- Distance/similarity scoring
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* Add custom exception hierarchy with `ExceptionInterface`
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* Add support for specific exceptions for invalid arguments and runtime errors

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