https://github.com/vs4vijay/llm-ecosystem

Code for Embeddings, VectorStore, SemanticSearch, and RAG using Azure OpenAI
https://github.com/vs4vijay/llm-ecosystem

azure embeddings langchain llm openai rag semantic-search vectordb vectorstore

Last synced: 3 months ago
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Code for Embeddings, VectorStore, SemanticSearch, and RAG using Azure OpenAI

• Host: GitHub
• URL: https://github.com/vs4vijay/llm-ecosystem
• Owner: vs4vijay
• License: mit
• Created: 2023-09-21T14:14:11.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2024-06-28T21:50:24.000Z (about 2 years ago)
• Last Synced: 2025-08-02T06:36:52.433Z (11 months ago)
• Topics: azure, embeddings, langchain, llm, openai, rag, semantic-search, vectordb, vectorstore
• Language: Python
• Homepage:
• Size: 186 KB
• Stars: 0
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# LLM-Ecosystem

Code for Embeddings, VectorStore, SemanticSearch, and RAG using Azure OpenAI.

## Installation

Pre-requisites:

- Python 3.10+ and pip

```bash

pip install -r requirements.txt

```

## Running

- Copy `.env.example` to `.env` and fill in the values

- Run the following command to start the server

```bash

python 0_llm.py

python 1_embeddings.py

python 2_semantic_search.py

python 3_vectorstore.py

python 4_llm_app.py

```

---

## Advance

```bash

poetry shell

poetry install

```