rearrange rag modules

.github/workflows/rag-springai-ollama-llm.yml

@@ -3,11 +3,11 @@ name: rag-springai-ollama-llm CI Build
 on:
   push:
     paths:
-      - "rag-springai-ollama-llm/**"
+      - "rag/rag-springai-ollama-llm/**"
     branches: [main]
   pull_request:
     paths:
-      - "rag-springai-ollama-llm/**"
+      - "rag/rag-springai-ollama-llm/**"
     types:
       - opened
       - synchronize
@@ -19,7 +19,7 @@ jobs:
     runs-on: ubuntu-latest
     defaults:
       run:
-        working-directory: rag-springai-ollama-llm
+        working-directory: rag/rag-springai-ollama-llm
     strategy:
       matrix:
         distribution: [ 'temurin' ]

.github/workflows/rag-springai-openai-llm.yml

@@ -3,11 +3,11 @@ name: rag-springai-openai-llm CI Build
 on:
   push:
     paths:
-      - "rag-springai-openai-llm/**"
+      - "rag/rag-springai-openai-llm/**"
     branches: [main]
   pull_request:
     paths:
-      - "rag-springai-openai-llm/**"
+      - "rag/rag-springai-openai-llm/**"
     types:
       - opened
       - synchronize
@@ -19,7 +19,7 @@ jobs:
     runs-on: ubuntu-latest
     defaults:
       run:
-        working-directory: rag-springai-openai-llm
+        working-directory: rag/rag-springai-openai-llm
     strategy:
       matrix:
         distribution: [ 'temurin' ]

README.md

@@ -13,8 +13,8 @@ AI implementations using java, stores and either of Langchain4j or springai fram
 | [neo4j embedding Store using spring ai](./embeddingstores/neo4j-springai) | Embedding store implementation using springai and neo4j                                              |
 | [opensearch langchain4j](./ai-opensearch-langchain4j)                     | Embeddings implementation using langchain4j and opensearch store                                     |
 | [rag langchain4j AllMiniLmL6V2](./rag/rag-langchain4j-AllMiniLmL6V2-llm)      | RAG Implementation using Langchain4j, PGVector store and allMiniLmL6V2 LLM                                  |
-| [rag springai ollama llm](./rag-springai-ollama-llm)                      | RAG Implementation using springai, Redis store, PDF document reader and ollama LLM with llama2 model |
-| [rag springai openai llm](./rag-springai-openai-llm)                      | RAG Implementation using springai, PGVector store, Tika document reader and openai LLM               |
+| [rag springai ollama llm](./rag/rag-springai-ollama-llm)                      | RAG Implementation using springai, Redis store, PDF document reader and ollama LLM with llama2 model |
+| [rag springai openai llm](./rag/rag-springai-openai-llm)                      | RAG Implementation using springai, PGVector store, Tika document reader and openai LLM               |
 
 ### Credits
 Thanks to langchain4j for providing an openAI compatible API for learning and demo purposes.