Feature/auto testing (#21)

first testing script

Author: rbs333

.github/workflows/test.yml

@@ -0,0 +1,58 @@
+name: Test Suite
+
+on:
+  pull_request:
+    branches:
+      - main
+  push:
+    branches:
+      - main
+
+jobs:
+  test:
+    name: Python ${{ matrix.python-version }} - ${{ matrix.connection }} [redis-stack ${{matrix.redis-stack-version}}]
+    runs-on: ubuntu-latest
+
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: [3.11]
+        connection: ['plain']
+        redis-stack-version: ['latest']
+
+    services:
+      redis:
+        image: redis/redis-stack-server:${{matrix.redis-stack-version}}
+        ports:
+          - 6379:6379
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v4
+      with:
+        python-version: ${{ matrix.python-version }}
+        cache: 'pip'
+
+    - name: Install dependencies
+      run: |
+        pip install -r requirements.txt
+
+    - name: Set Redis version
+      run: |
+        echo "REDIS_VERSION=${{ matrix.redis-stack-version }}" >> $GITHUB_ENV
+
+    - name: Run notebooks
+      if: matrix.connection == 'plain' && matrix.redis-stack-version == 'latest'
+      env:
+        OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
+        LLAMA_CLOUD_API_KEY: ${{ secrets.LLAMA_CLOUD_API_KEY }}
+        GCP_REGION: ${{ secrets.GCP_REGION }}
+        GCP_PROJECT_ID: ${{ secrets.GCP_PROJECT_ID }}
+      #   COHERE_API_KEY: ${{ secrets.COHERE_API_KEY }}
+      #   AZURE_OPENAI_API_KEY: ${{secrets.AZURE_OPENAI_API_KEY}}
+      #   AZURE_OPENAI_ENDPOINT: ${{secrets.AZURE_OPENAI_ENDPOINT}}
+      #   AZURE_OPENAI_DEPLOYMENT_NAME: ${{secrets.AZURE_OPENAI_DEPLOYMENT_NAME}}
+      #   OPENAI_API_VERSION: ${{secrets.OPENAI_API_VERSION}}
+      run: |
+        pytest --nbval-lax python-recipes/RAG/00_intro_redispy.ipynb python-recipes/RAG/01_redisvl.ipynb python-recipes/RAG/02_langchain.ipynb python-recipes/RAG/03_llamaindex.ipynb python-recipes/RAG/04_advanced_redisvl.ipynb

README.md

@@ -60,6 +60,8 @@ To get started with RAG, either from scratch or using a popular framework like L
 | [/01_redisvl](python-recipes/RAG/01_redisvl.ipynb) | RAG from scratch with the Redis Vector Library |
 | [/02_langchain](python-recipes/RAG/02_langchain.ipynb) | RAG using Redis and LangChain |
 | [/03_llamaindex](python-recipes/RAG/03_llamaindex.ipynb) | RAG using Redis and LlamaIndex |
+| [/04_advanced_redisvl](python-recipes/RAG//04_advanced_redisvl.ipynb) | Advanced RAG with redisvl |
+| [/05_nvidia_ai_rag_redis](python-recipes/RAG/05_nvidia_ai_rag_redis.ipynb) | RAG using Redis and Nvidia |
 
 
 ## Semantic Cache
@@ -85,7 +87,7 @@ Within [this repository](https://github.com/redis-developer/redis-nvidia-recsys)
 
 # Integrations/Tools
 - [⭐ RedisVL](https://github.com/redis/redis-vl-python) - a dedicated Python client lib for Redis as a Vector DB.
-- [⭐ AWS Bedrock][https://redis.io/docs/latest/integrate/amazon-bedrock/]
+- [⭐ AWS Bedrock](https://redis.io/docs/latest/integrate/amazon-bedrock/) - Streamlines GenAI deployment by offering foundational models as a unified API.
 - [⭐ LangChain Python](https://github.com/langchain-ai/langchain) - popular Python client lib for building LLM applications.
 powered by Redis.
 - [⭐ LangChain JS](https://github.com/langchain-ai/langchainjs) - popular JS client lib for building LLM applications.