fennec-rag 1.1.1

A comprehensive RAG framework with Arabic language support, multi-provider embeddings, and advanced RAG strategies

🦊 fennec-rag

A comprehensive, production-ready Retrieval-Augmented Generation (RAG) framework with first-class Arabic language support.

✨ Features

• 🌍 Arabic-first NLP — dedicated Arabic chunker, embedder, and prompt templates
• 🔌 Multi-provider LLMs — OpenAI, Anthropic, Gemini, Mistral, HuggingFace, Ollama
• 🗄️ Multiple vector databases — FAISS, ChromaDB, Pinecone
• 🧩 Advanced RAG strategies — Conversational, Agentic, Graph, Multi-hop, Federated, Self-improving, Streaming
• 🛡️ Hallucination Guard — built-in hallucination detection and grounding
• 📊 Observability & Evaluation — tracing, metrics, dashboards, evaluation suite
• 📄 Rich document loaders — PDF, DOCX, HTML, CSV, JSON, Excel, Web, Directory

📦 Installation

# Basic
pip install fennec-rag

# With specific providers
pip install "fennec-rag[openai,faiss]"
pip install "fennec-rag[anthropic,chroma]"
pip install "fennec-rag[gemini,pinecone]"

# Arabic NLP
pip install "fennec-rag[arabic]"

# Full install
pip install "fennec-rag[all]"

🚀 Quick Start

from fennec.rag.core import RAGSystem, RAGConfig
from fennec.embeddings import OpenAIEmbedder
from fennec.vector_database import FAISSVectorDatabase
from fennec.llm import OpenAIInterface

embedder = OpenAIEmbedder(api_key="your-key")
vector_db = FAISSVectorDatabase(embedder=embedder)
llm = OpenAIInterface(api_key="your-key")

config = RAGConfig(chunk_size=512, overlap=128, top_k=5)
rag = RAGSystem(config=config, vector_db=vector_db, llm=llm)

rag.load_documents(["document.pdf"])
response = rag.query("What is the main topic?")
print(response)

🗂️ Modules

Module	Description
fennec.rag.core	RAGSystem, MultiDocRAG, Reranker, PromptRouter
fennec.rag.conversational_rag	Multi-turn conversation RAG
fennec.rag.agentic_rag	Agent-based RAG
fennec.rag.graph_rag	Knowledge graph RAG
fennec.rag.hybrid_search	BM25 + semantic hybrid search
fennec.rag.multi_hop	Multi-hop question decomposition
fennec.rag.self_improving_rag	HyDE + recursive refinement
fennec.rag.streaming_rag	Token streaming
fennec.embeddings	OpenAI, Gemini, HuggingFace, Mistral, Ollama, Arabic
fennec.vector_database	FAISS, ChromaDB, Pinecone
fennec.llm	OpenAI, Anthropic, Gemini, Mistral, HuggingFace, Ollama
fennec.llm.hallucination	HallucinationGuard, ProtectedLLMInterface
fennec.chunks	Arabic & multilingual text chunkers
fennec.document_loaders	PDF, DOCX, HTML, CSV, JSON, Excel, Web, Directory
fennec.memory	Buffer, Window, Summary, Entity memory
fennec.router	SemanticRouter
fennec.prompt	PromptTemplate, ChatTemplate, FewShotTemplate
fennec.output_parser	JSON, YAML, CSV, Pydantic parsers
fennec.evaluator	RAG evaluation & reporting
fennec.observability	Tracing, metrics, dashboards
fennec.cache	Multi-level cache
fennec.persistence	State persistence & backup
fennec.plugins	Extensible plugin system

📝 License

MIT License