Update project description

README.md

@@ -1,8 +1,8 @@
 # Haiku RAG
 
-Retrieval-Augmented Generation (RAG) library built on LanceDB.
+Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling.
 
-`haiku.rag` is a Retrieval-Augmented Generation (RAG) library built to work with LanceDB as a local vector database. It uses LanceDB for storing embeddings and performs semantic (vector) search as well as full-text search combined through native hybrid search with Reciprocal Rank Fusion. Both open-source (Ollama, LM Studio, vLLM) as well as commercial (OpenAI, VoyageAI) embedding providers are supported.
+`haiku.rag` is an opinionated agentic RAG system that uses LanceDB for vector storage, Pydantic AI for multi-agent workflows, and Docling for document processing. It supports hybrid search (vector + full-text) with Reciprocal Rank Fusion, multiple embedding providers (Ollama, LM Studio, vLLM, OpenAI, VoyageAI), and includes research agents that plan, search, evaluate, and synthesize answers.
 
 ## Features
 

docs/index.md

@@ -1,6 +1,6 @@
 # haiku.rag
 
-`haiku.rag` is a Retrieval-Augmented Generation (RAG) library built to work with LanceDB as a local vector database. It uses LanceDB for storing embeddings and performs semantic (vector) search as well as full-text search combined through native hybrid search with Reciprocal Rank Fusion. Both open-source (Ollama, MixedBread AI) as well as commercial (OpenAI, VoyageAI) embedding providers are supported.
+`haiku.rag` is an opinionated agentic RAG system that uses LanceDB for vector storage, Pydantic AI for multi-agent workflows, and Docling for document processing. It supports hybrid search (vector + full-text) with Reciprocal Rank Fusion, multiple embedding providers (Ollama, LM Studio, vLLM, OpenAI, VoyageAI), and includes research agents that plan, search, evaluate, and synthesize answers.
 
 ## Features
 

haiku_rag_slim/README.md

@@ -1,6 +1,6 @@
 # haiku.rag-slim
 
-Retrieval-Augmented Generation (RAG) library built on LanceDB - Core package with minimal dependencies.
+Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling - Core package with minimal dependencies.
 
 `haiku.rag-slim` is the core package for users who want to install only the dependencies they need. Document processing (docling), and reranker support are all optional extras.
 

haiku_rag_slim/pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 
 name = "haiku.rag-slim"
-description = "Agentic Retrieval Augmented Generation (RAG) with LanceDB - Minimal dependencies"
+description = "Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling - Minimal dependencies"
 version = "0.19.4"
 authors = [{ name = "Yiorgis Gozadinos", email = "ggozadinos@gmail.com" }]
 license = { text = "MIT" }

mkdocs.yml

@@ -1,5 +1,5 @@
 site_name: haiku.rag
-site_description: Retrieval-Augmented Generation (RAG) library on LanceDB.
+site_description: Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling.
 site_url: https://ggozad.github.io/haiku.rag/
 theme:
   name: material

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 
 name = "haiku.rag"
-description = "Agentic Retrieval Augmented Generation (RAG) with LanceDB"
+description = "Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling"
 version = "0.19.4"
 authors = [{ name = "Yiorgis Gozadinos", email = "ggozadinos@gmail.com" }]
 license = { text = "MIT" }

server.json

@@ -2,7 +2,7 @@
     "$schema": "https://static.modelcontextprotocol.io/schemas/2025-10-17/server.schema.json",
     "name": "io.github.ggozad/haiku-rag",
     "version": "{{VERSION}}",
-    "description": "Agentic Retrieval Augmented Generation (RAG) with LanceDB",
+    "description": "Opinionated agentic RAG powered by LanceDB, Pydantic AI, and Docling",
     "repository": {
         "url": "https://github.com/ggozad/haiku.rag",
         "source": "github"