Chunking techniques (#170)

* assests and app name

* update README

* demo gifs

* talk with github codespaces

* talk with github codespaces

* gitignore

* linted

* added version

* link fix

* added local llm tag

* crag

* link fix

* lint

* llm tags

* non-clickable badge

* non-clickable badge

* fix

* tutorial llm tags

* added instructions and fix

* colab fix

* fix

* formatted

* hybrid search and rag colab

* colab format

* python test

* node test

* python test

* blog link update

* rag mlx

* myntra search engine app

* link fix

* CrewAI Example

* lint

* node test

* node test

* node test

* added readme

* support for Gemini Pro

* fix

* chunking techniques

* lint

README.md

@@ -94,9 +94,9 @@ Looking to get started with LLMs, vectorDBs, and the world of Generative AI? The
 | --------- | -------------------------- | ----------- |
 |           |                            |             |
 | [Build RAG from Scratch](./tutorials/RAG-from-Scratch) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/RAG-from-Scratch/RAG_from_Scratch.ipynb) [![LLM](https://img.shields.io/badge/openai-api-white)](#) |  |
+| [Langchain LlamaIndex Chunking](./tutorials/RAG-from-Scratch) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/RAG-from-Scratch/RAG_from_Scratch.ipynb)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/product-quantization-compress-high-dimensional-vectors-dfcba98fab47) |
 | [Product Quantization: Compress High Dimensional Vectors](https://blog.lancedb.com/product-quantization-compress-high-dimensional-vectors-dfcba98fab47) | | [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/product-quantization-compress-high-dimensional-vectors-dfcba98fab47) |
 | [Corrective RAG with Langgraph](./tutorials/Corrective-RAG-with_Langgraph/) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/Corrective-RAG-with_Langgraph/CRAG_with_Langgraph.ipynb) [![LLM](https://img.shields.io/badge/openai-api-white)](#) | [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/implementing-corrective-rag-in-the-easiest-way-2/)|
-| [Product Quantization: Compress High Dimensional Vectors](https://blog.lancedb.com/product-quantization-compress-high-dimensional-vectors-dfcba98fab47) | | [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/product-quantization-compress-high-dimensional-vectors-dfcba98fab47) |
 | [LLMs, RAG, & the missing storage layer for AI](https://blog.lancedb.com/llms-rag-the-missing-storage-layer-for-ai-28ded35fa984) | | [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/llms-rag-the-missing-storage-layer-for-ai-28ded35fa984/) |
 | [Fine-Tuning LLM using PEFT & QLoRA](./tutorials/fine-tuning_LLM_with_PEFT_QLoRA) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/fine-tuning_LLM_with_PEFT_QLoRA/main.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/optimizing-llms-a-step-by-step-guide-to-fine-tuning-with-peft-and-qlora-22eddd13d25b) |
 | [Context-Aware Chatbot using Llama 2 & LanceDB](./tutorials/chatbot_using_Llama2_&_lanceDB) | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/lancedb/vectordb-recipes/blob/main/tutorials/chatbot_using_Llama2_&_lanceDB/main.ipynb) [![local LLM](https://img.shields.io/badge/local-llm-green)](#)| [![Ghost](https://img.shields.io/badge/ghost-000?style=for-the-badge&logo=ghost&logoColor=%23F7DF1E)](https://blog.lancedb.com/context-aware-chatbot-using-llama-2-lancedb-as-vector-database-4d771d95c755) |