readme & license

LICENSE

@@ -0,0 +1,13 @@
+Copyright 2025 KnowLang
+
+   Licensed under the Apache License, Version 2.0 (the "License");
+   you may not use this file except in compliance with the License.
+   You may obtain a copy of the License at
+
+       http://www.apache.org/licenses/LICENSE-2.0
+
+   Unless required by applicable law or agreed to in writing, software
+   distributed under the License is distributed on an "AS IS" BASIS,
+   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+   See the License for the specific language governing permissions and
+   limitations under the License.

README.md

@@ -1,17 +1,126 @@
----
-title: KnowLangBot
-emoji: 🤖
-colorFrom: blue
-colorTo: purple
-sdk: docker
-app_port: 7860
----
-
-# Know Lang Bot
-A tool for exploring and understanding complex codebases using LLMs.
-Features
-
-# Code parsing and analysis
-- Semantic search across repositories
-- Automatic documentation maintenance
-- LLM-powered code understanding
+# KnowLang: Comprehensive Understanding for Complex Codebase
+
+KnowLang is an advanced codebase exploration tool that helps software engineers better understand complex codebases through semantic search and intelligent Q&A capabilities. Our first release focuses on providing RAG-powered search and Q&A for popular open-source libraries, with Hugging Face's repositories as our initial targets.
+
+[![Hugging Face Space](https://img.shields.io/badge/🤗%20Hugging%20Face-Space-blue)](https://huggingface.co/spaces/gabykim/KnowLang_Transformers_Demo)
+
+## Features
+
+- 🔍 **Semantic Code Search**: Find relevant code snippets based on natural language queries
+- 📚 **Contextual Q&A**: Get detailed explanations about code functionality and implementation details
+- 🎯 **Smart Chunking**: Intelligent code parsing that preserves semantic meaning
+- 🔄 **Multi-Stage Retrieval**: Combined embedding and semantic search for better results
+- 🐍 **Python Support**: Currently optimized for Python codebases, with a roadmap for multi-language support
+
+## How It Works
+
+### Code Parsing Pipeline
+
+```mermaid
+flowchart TD
+    A[Git Repository] --> B[Code Files]
+    B --> C[Code Parser]
+    C --> D{Parse by Type}
+    D --> E[Class Definitions]
+    D --> F[Function Definitions]
+    D --> G[Other Code]
+    E --> H[Code Chunks]
+    F --> H
+    G --> H
+    H --> I[LLM Summarization]
+    H --> J
+    I --> J[Embeddings]
+    J --> K[(Vector Store)]
+```
+
+### RAG Chatbot Pipeline
+
+```mermaid
+flowchart LR
+    A[User Query] --> B[Query Embedding]
+    B --> C[Vector Search]
+    C --> D[Context Collection]
+    D --> E[LLM Response Generation]
+    E --> F[User Interface]
+```
+
+## Quick Start
+
+```bash
+pip install knowlang
+```
+
+Basic usage:
+
+```python
+from knowlang import CodebaseRAG
+
+# Initialize with a repository
+rag = CodebaseRAG("huggingface/transformers")
+
+# Start the chat interface
+rag.launch_chat()
+```
+
+## Architecture
+
+KnowLang uses several key technologies:
+
+- **Tree-sitter**: For robust, language-agnostic code parsing
+- **ChromaDB**: For efficient vector storage and retrieval
+- **PydanticAI**: For type-safe LLM interactions
+- **Gradio**: For the interactive chat interface
+
+## Technical Details
+
+### Code Parsing
+
+Our code parsing pipeline uses Tree-sitter to break down source code into meaningful chunks while preserving context:
+
+1. Repository cloning and file identification
+2. Semantic parsing with Tree-sitter
+3. Smart chunking based on code structure
+4. LLM-powered summarization
+5. Embedding generation with mxbai-embed-large
+6. Vector store indexing
+
+### RAG Implementation
+
+The RAG system uses a multi-stage retrieval process:
+
+1. Query embedding generation
+2. Initial vector similarity search
+3. Context aggregation
+4. LLM response generation with full context
+
+
+## Roadmap
+
+- [ ] Inter-repository semantic search
+- [ ] Support for additional programming languages
+- [ ] Automatic documentation maintenance
+- [ ] Integration with popular IDEs
+- [ ] Custom embedding model training
+- [ ] Enhanced evaluation metrics
+
+## License
+
+This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details. The Apache License 2.0 is a permissive license that enables broad use, modification, and distribution while providing patent rights and protecting trademark use.
+
+## Citation
+
+If you use KnowLang in your research, please cite:
+
+```bibtex
+@software{knowlang2025,
+  author = KnowLang,
+  title = {KnowLang: Comprehensive Understanding for Complex Codebase},
+  year = {2025},
+  publisher = {GitHub},
+  url = {https://github.com/kimgb415/know-lang}
+}
+```
+
+## Support
+
+For support, please open an issue on GitHub or reach out to us directly through discussions.