Refine READMEs after reorg (#666)

* update dataprep readme

Signed-off-by: letonghan <[email protected]>

* update vectorstore readme

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* udpate retriever readme

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* update retriever readme

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* udpate embedding readme

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* update guardrails readme

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* update other readmes

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* update reranks readme

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* update llm&lvms readme

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---------

Signed-off-by: letonghan <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: letonghan

comps/dataprep/README.md

@@ -19,20 +19,28 @@ export SUMMARIZE_IMAGE_VIA_LVM=1
 
 ## Dataprep Microservice with Redis
 
-For details, please refer to this [langchain readme](langchain/redis/README.md) or [llama index readme](llama_index/redis/README.md)
+For details, please refer to this [readme](redis/README.md)
 
 ## Dataprep Microservice with Milvus
 
-For details, please refer to this [readme](langchain/milvus/README.md)
+For details, please refer to this [readme](milvus/langchain/README.md)
 
 ## Dataprep Microservice with Qdrant
 
-For details, please refer to this [readme](langchain/qdrant/README.md)
+For details, please refer to this [readme](qdrant/langchain/README.md)
 
 ## Dataprep Microservice with Pinecone
 
-For details, please refer to this [readme](langchain/pinecone/README.md)
+For details, please refer to this [readme](pinecone/langchain/README.md)
 
 ## Dataprep Microservice with PGVector
 
-For details, please refer to this [readme](langchain/pgvector/README.md)
+For details, please refer to this [readme](pgvector/langchain/README.md)
+
+## Dataprep Microservice with VDMS
+
+For details, please refer to this [readme](vdms/README.md)
+
+## Dataprep Microservice with Multimodal
+
+For details, please refer to this [readme](multimodal/redis/langchain/README.md)

comps/dataprep/redis/README.md

@@ -1,6 +1,6 @@
 # Dataprep Microservice with Redis
 
-We have provided dataprep microservice for multimodal data input (e.g., text and image) [here](../../multimodal/redis/langchain/README.md).
+We have provided dataprep microservice for multimodal data input (e.g., text and image) [here](../multimodal/redis/langchain/README.md).
 
 For dataprep microservice for text input, we provide here two frameworks: `Langchain` and `LlamaIndex`. We also provide `Langchain_ray` which uses ray to parallel the data prep for multi-file performance improvement(observed 5x - 15x speedup by processing 1000 files/links.).
 
@@ -33,7 +33,7 @@ cd langchain_ray; pip install -r requirements_ray.txt
 
 ### 1.2 Start Redis Stack Server
 
-Please refer to this [readme](../../../vectorstores/redis/README.md).
+Please refer to this [readme](../../vectorstores/redis/README.md).
 
 ### 1.3 Setup Environment Variables
 
@@ -90,7 +90,7 @@ python prepare_doc_redis_on_ray.py
 
 ### 2.1 Start Redis Stack Server
 
-Please refer to this [readme](../../../vectorstores/redis/README.md).
+Please refer to this [readme](../../vectorstores/redis/README.md).
 
 ### 2.2 Setup Environment Variables
 
@@ -109,21 +109,21 @@ export HUGGINGFACEHUB_API_TOKEN=${your_hf_api_token}
 - option 1: Start single-process version (for 1-10 files processing)
 
 ```bash
-cd ../../../
+cd ../../
 docker build -t opea/dataprep-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/langchain/Dockerfile .
 ```
 
 - Build docker image with llama_index
 
 ```bash
-cd ../../../
+cd ../../
 docker build -t opea/dataprep-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/llama_index/Dockerfile .
 ```
 
 - option 2: Start multi-process version (for >10 files processing)
 
 ```bash
-cd ../../../../
+cd ../../../
 docker build -t opea/dataprep-on-ray-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/langchain_ray/Dockerfile .
 ```
 

comps/dataprep/vdms/README.md

@@ -27,7 +27,7 @@ cd langchain_ray; pip install -r requirements_ray.txt
 
 ## 1.2 Start VDMS Server
 
-Please refer to this [readme](../../vectorstores/langchain/vdms/README.md).
+Please refer to this [readme](../../vectorstores/vdms/README.md).
 
 ## 1.3 Setup Environment Variables
 
@@ -37,8 +37,6 @@ export https_proxy=${your_http_proxy}
 export VDMS_HOST=${host_ip}
 export VDMS_PORT=55555
 export COLLECTION_NAME=${your_collection_name}
-export LANGCHAIN_TRACING_V2=true
-export LANGCHAIN_PROJECT="opea/gen-ai-comps:dataprep"
 export PYTHONPATH=${path_to_comps}
 ```
 
@@ -62,7 +60,7 @@ python prepare_doc_redis_on_ray.py
 
 ## 2.1 Start VDMS Server
 
-Please refer to this [readme](../../vectorstores/langchain/vdms/README.md).
+Please refer to this [readme](../../vectorstores/vdms/README.md).
 
 ## 2.2 Setup Environment Variables
 

comps/embeddings/README.md

@@ -18,20 +18,16 @@ Users are albe to configure and build embedding-related services according to th
 
 We support both `langchain` and `llama_index` for TEI serving.
 
-For details, please refer to [langchain readme](langchain/tei/README.md) or [llama index readme](llama_index/tei/README.md).
+For details, please refer to [langchain readme](tei/langchain/README.md) or [llama index readme](tei/llama_index/README.md).
 
 ## Embeddings Microservice with Mosec
 
-For details, please refer to this [readme](langchain/mosec/README.md).
+For details, please refer to this [readme](mosec/langchain/README.md).
 
-## Embeddings Microservice with Neural Speed
+## Embeddings Microservice with Multimodal
 
-For details, please refer to this [readme](neural-speed/README.md).
+For details, please refer to this [readme](multimodal/README.md).
 
 ## Embeddings Microservice with Multimodal Clip
 
 For details, please refer to this [readme](multimodal_clip/README.md).
-
-## Embeddings Microservice with Multimodal Langchain
-
-For details, please refer to this [readme](multimodal_embeddings/README.md).

comps/guardrails/README.md

@@ -4,7 +4,7 @@ The Guardrails service enhances the security of LLM-based applications by offeri
 
 | MicroService                                         | Description                                                                                                              |
 | ---------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------ |
-| [Llama Guard](./llama_guard/README.md)               | Provides guardrails for inputs and outputs to ensure safe interactions                                                   |
+| [Llama Guard](./llama_guard/langchain/README.md)     | Provides guardrails for inputs and outputs to ensure safe interactions                                                   |
 | [PII Detection](./pii_detection/README.md)           | Detects Personally Identifiable Information (PII) and Business Sensitive Information (BSI)                               |
 | [Toxicity Detection](./toxicity_detection/README.md) | Detects Toxic language (rude, disrespectful, or unreasonable language that is likely to make someone leave a discussion) |
 

comps/guardrails/llama_guard/langchain/README.md

@@ -79,7 +79,7 @@ export LLM_MODEL_ID=${your_hf_llm_model}
 ### 2.2 Build Docker Image
 
 ```bash
-cd ../../
+cd ../../../../
 docker build -t opea/guardrails-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/guardrails/llama_guard/langchain/Dockerfile .
 ```
 

comps/intent_detection/langchain/README.md

@@ -35,7 +35,7 @@ export TGI_LLM_ENDPOINT="http://${your_ip}:8008"
 Start intent detection microservice with below command.
 
 ```bash
-cd /your_project_path/GenAIComps/
+cd ../../../
 cp comps/intent_detection/langchain/intent_detection.py .
 python intent_detection.py
 ```
@@ -55,7 +55,7 @@ export TGI_LLM_ENDPOINT="http://${your_ip}:8008"
 ### 2.3 Build Docker Image
 
 ```bash
-cd /your_project_path/GenAIComps
+cd ../../../
 docker build --no-cache -t opea/llm-tgi:latest -f comps/intent_detection/langchain/Dockerfile .
 ```
 
@@ -68,7 +68,6 @@ docker run -it --name="intent-tgi-server" --net=host --ipc=host -e http_proxy=$h
 ### 2.5 Run with Docker Compose (Option B)
 
 ```bash
-cd /your_project_path/GenAIComps/comps/intent_detection/langchain
 export LLM_MODEL_ID=${your_hf_llm_model}
 export http_proxy=${your_http_proxy}
 export https_proxy=${your_http_proxy}

comps/knowledgegraphs/langchain/README.md

@@ -73,7 +73,7 @@ curl $LLM_ENDPOINT/generate \
 ### 1.4 Start Microservice
 
 ```bash
-cd ../..
+cd ../../../
 docker build -t opea/knowledge_graphs:latest \
     --build-arg https_proxy=$https_proxy \
     --build-arg http_proxy=$http_proxy \

comps/llms/faq-generation/tgi/langchain/README.md

@@ -19,7 +19,7 @@ export LLM_MODEL_ID=${your_hf_llm_model}
 ### 1.2 Build Docker Image
 
 ```bash
-cd ../../../../
+cd ../../../../../
 docker build -t opea/llm-faqgen-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/faq-generation/tgi/langchain/Dockerfile .
 ```
 
@@ -43,7 +43,6 @@ docker run -d --name="llm-faqgen-server" -p 9000:9000 --ipc=host -e http_proxy=$
 ### 1.4 Run Docker with Docker Compose (Option B)
 
 ```bash
-cd faq-generation/tgi/docker
 docker compose -f docker_compose_llm.yaml up -d
 ```
 

comps/llms/summarization/tgi/langchain/README.md

@@ -53,7 +53,7 @@ export LLM_MODEL_ID=${your_hf_llm_model}
 ### 2.2 Build Docker Image
 
 ```bash
-cd ../../
+cd ../../../../../
 docker build -t opea/llm-docsum-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/summarization/tgi/langchain/Dockerfile .
 ```