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Fix README issues (opea-project#817)
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Signed-off-by: lvliang-intel <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
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lvliang-intel and pre-commit-ci[bot] authored Sep 18, 2024
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17 changes: 5 additions & 12 deletions ChatQnA/docker_compose/intel/cpu/xeon/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -61,14 +61,11 @@ Port 5173 - Open to 0.0.0.0/0

First of all, you need to build Docker Images locally and install the python package of it.

```bash
git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
```

### 1. Build Embedding Image

```bash
git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/tei/langchain/Dockerfile .
```

Expand Down Expand Up @@ -128,7 +125,6 @@ cd ..
git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/ChatQnA
docker build --no-cache -t opea/chatqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
cd ../../..
```

2. MegaService without Rerank
Expand All @@ -139,7 +135,6 @@ cd ..
git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/ChatQnA
docker build --no-cache -t opea/chatqna-without-rerank:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile.without_rerank .
cd ../../..
```

### 7. Build UI Docker Image
Expand All @@ -149,7 +144,6 @@ Build frontend Docker image via below command:
```bash
cd GenAIExamples/ChatQnA/ui
docker build --no-cache -t opea/chatqna-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
cd ../../../..
```

### 8. Build Conversational React UI Docker Image (Optional)
Expand All @@ -161,7 +155,6 @@ Build frontend Docker image that enables Conversational experience with ChatQnA
```bash
cd GenAIExamples/ChatQnA/ui
docker build --no-cache -t opea/chatqna-conversation-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react .
cd ../../../..
```

Then run the command `docker images`, you will have the following 7 Docker Images:
Expand All @@ -188,15 +181,15 @@ By default, the embedding, reranking and LLM models are set to a default value a

Change the `xxx_MODEL_ID` below for your needs.

For customers with proxy issues, the models from [ModelScope](https://www.modelscope.cn/models) are also supported in ChatQnA with TGI serving. ModelScope models are supported in two ways for TGI:
For users in China who are unable to download models directly from Huggingface, you can use [ModelScope](https://www.modelscope.cn/models) or a Huggingface mirror to download models. TGI can load the models either online or offline as described below:

1. Online

```bash
export HF_TOKEN=${your_hf_token}
export HF_ENDPOINT="https://hf-mirror.com"
model_name="Intel/neural-chat-7b-v3-3"
docker run -p 8008:80 -v ./data:/data --name tgi-service -e HF_ENDPOINT=$HF_ENDPOINT -e http_proxy=$http_proxy -e https_proxy=$https_proxy --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id $model_name
docker run -p 8008:80 -v ./data:/data --name tgi-service -e HF_ENDPOINT=$HF_ENDPOINT -e http_proxy=$http_proxy -e https_proxy=$https_proxy --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.2.0 --model-id $model_name
```

2. Offline
Expand All @@ -210,7 +203,7 @@ For customers with proxy issues, the models from [ModelScope](https://www.models
```bash
export HF_TOKEN=${your_hf_token}
export model_path="/path/to/model"
docker run -p 8008:80 -v $model_path:/data --name tgi_service --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id /data
docker run -p 8008:80 -v $model_path:/data --name tgi_service --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.2.0 --model-id /data
```

### Setup Environment Variables
Expand Down
60 changes: 18 additions & 42 deletions ChatQnA/docker_compose/intel/hpu/gaudi/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -6,44 +6,39 @@ This document outlines the deployment process for a ChatQnA application utilizin

First of all, you need to build Docker Images locally. This step can be ignored after the Docker images published to Docker hub.

### 1. Source Code install GenAIComps
### 1. Build Embedding Image

```bash
git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
```

### 2. Build Embedding Image

```bash
docker build --no-cache -t opea/embedding-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/embeddings/tei/langchain/Dockerfile .
```

### 3. Build Retriever Image
### 2. Build Retriever Image

```bash
docker build --no-cache -t opea/retriever-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/retrievers/redis/langchain/Dockerfile .
```

### 4. Build Rerank Image
### 3. Build Rerank Image

> Skip for ChatQnA without Rerank pipeline
```bash
docker build --no-cache -t opea/reranking-tei:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/reranks/tei/Dockerfile .
```

### 5. Build LLM Image
### 4. Build LLM Image

You can use different LLM serving solutions, choose one of following four options.

#### 5.1 Use TGI
#### 4.1 Use TGI

```bash
docker build --no-cache -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile .
```

#### 5.2 Use VLLM
#### 4.2 Use VLLM

Build vllm docker.

Expand All @@ -57,7 +52,7 @@ Build microservice docker.
docker build --no-cache -t opea/llm-vllm:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/langchain/Dockerfile .
```

#### 5.3 Use VLLM-on-Ray
#### 4.3 Use VLLM-on-Ray

Build vllm-on-ray docker.

Expand All @@ -71,24 +66,21 @@ Build microservice docker.
docker build --no-cache -t opea/llm-vllm-ray:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/vllm/ray/Dockerfile .
```

### 6. Build Dataprep Image
### 5. Build Dataprep Image

```bash
docker build --no-cache -t opea/dataprep-redis:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/redis/langchain/Dockerfile .
```

### 7. Build TEI Gaudi Image
### 6. Build Guardrails Docker Image (Optional)

Since a TEI Gaudi Docker image hasn't been published, we'll need to build it from the [tei-gaudi](https://github.com/huggingface/tei-gaudi) repository.
To fortify AI initiatives in production, Guardrails microservice can secure model inputs and outputs, building Trustworthy, Safe, and Secure LLM-based Applications.

```bash
git clone https://github.com/huggingface/tei-gaudi
cd tei-gaudi/
docker build --no-cache -f Dockerfile-hpu -t opea/tei-gaudi:latest .
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 .
```

### 8. Build MegaService Docker Image
### 7. Build MegaService Docker Image

1. MegaService with Rerank

Expand All @@ -98,7 +90,6 @@ cd ../..
git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/ChatQnA/docker
docker build --no-cache -t opea/chatqna:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
cd ../../..
```

2. MegaService with Guardrails
Expand All @@ -109,7 +100,6 @@ cd ../..
git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/ChatQnA/
docker build --no-cache -t opea/chatqna-guardrails:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile.guardrails .
cd ../../..
```

3. MegaService without Rerank
Expand All @@ -120,20 +110,18 @@ cd ../..
git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/ChatQnA/docker
docker build --no-cache -t opea/chatqna-without-rerank:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile.without_rerank .
cd ../../..
```

### 9. Build UI Docker Image
### 8. Build UI Docker Image

Construct the frontend Docker image using the command below:

```bash
cd GenAIExamples/ChatQnA/ui
docker build --no-cache -t opea/chatqna-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
cd ../../../..
```

### 10. Build Conversational React UI Docker Image (Optional)
### 9. Build Conversational React UI Docker Image (Optional)

Build frontend Docker image that enables Conversational experience with ChatQnA megaservice via below command:

Expand All @@ -142,26 +130,14 @@ Build frontend Docker image that enables Conversational experience with ChatQnA
```bash
cd GenAIExamples/ChatQnA/ui
docker build --no-cache -t opea/chatqna-conversation-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile.react .
cd ../../../..
```

### 11. Build Guardrails Docker Image (Optional)

To fortify AI initiatives in production, Guardrails microservice can secure model inputs and outputs, building Trustworthy, Safe, and Secure LLM-based Applications.

```bash
cd GenAIComps
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 .
cd ../../..
```

Then run the command `docker images`, you will have the following 8 Docker Images:
Then run the command `docker images`, you will have the following 7 Docker Images:

- `opea/embedding-tei:latest`
- `opea/retriever-redis:latest`
- `opea/reranking-tei:latest`
- `opea/llm-tgi:latest` or `opea/llm-vllm:latest` or `opea/llm-vllm-ray:latest`
- `opea/tei-gaudi:latest`
- `opea/dataprep-redis:latest`
- `opea/chatqna:latest` or `opea/chatqna-guardrails:latest` or `opea/chatqna-without-rerank:latest`
- `opea/chatqna-ui:latest`
Expand All @@ -188,15 +164,15 @@ By default, the embedding, reranking and LLM models are set to a default value a

Change the `xxx_MODEL_ID` below for your needs.

For customers with proxy issues, the models from [ModelScope](https://www.modelscope.cn/models) are also supported in ChatQnA with TGI serving. ModelScope models are supported in two ways for TGI:
For users in China who are unable to download models directly from Huggingface, you can use [ModelScope](https://www.modelscope.cn/models) or a Huggingface mirror to download models. TGI can load the models either online or offline as described below:

1. Online

```bash
export HF_TOKEN=${your_hf_token}
export HF_ENDPOINT="https://hf-mirror.com"
model_name="Intel/neural-chat-7b-v3-3"
docker run -p 8008:80 -v ./data:/data --name tgi-service -e HF_ENDPOINT=$HF_ENDPOINT -e http_proxy=$http_proxy -e https_proxy=$https_proxy --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id $model_name
docker run -p 8008:80 -v ./data:/data --name tgi-service -e HF_ENDPOINT=$HF_ENDPOINT -e http_proxy=$http_proxy -e https_proxy=$https_proxy --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none -e HUGGING_FACE_HUB_TOKEN=$HF_TOKEN -e ENABLE_HPU_GRAPH=true -e LIMIT_HPU_GRAPH=true -e USE_FLASH_ATTENTION=true -e FLASH_ATTENTION_RECOMPUTE=true --cap-add=sys_nice --ipc=host ghcr.io/huggingface/tgi-gaudi:2.0.5 --model-id $model_name --max-input-tokens 1024 --max-total-tokens 2048
```

2. Offline
Expand All @@ -210,7 +186,7 @@ For customers with proxy issues, the models from [ModelScope](https://www.models
```bash
export HF_TOKEN=${your_hf_token}
export model_path="/path/to/model"
docker run -p 8008:80 -v $model_path:/data --name tgi_service --shm-size 1g ghcr.io/huggingface/text-generation-inference:2.1.0 --model-id /data
docker run -p 8008:80 -v $model_path:/data --name tgi_service --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none -e HUGGING_FACE_HUB_TOKEN=$HF_TOKEN -e ENABLE_HPU_GRAPH=true -e LIMIT_HPU_GRAPH=true -e USE_FLASH_ATTENTION=true -e FLASH_ATTENTION_RECOMPUTE=true --cap-add=sys_nice --ipc=host ghcr.io/huggingface/tgi-gaudi:2.0.5 --model-id /data --max-input-tokens 1024 --max-total-tokens 2048
```

### Setup Environment Variables
Expand Down
13 changes: 4 additions & 9 deletions CodeGen/docker_compose/intel/cpu/xeon/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -14,20 +14,15 @@ After launching your instance, you can connect to it using SSH (for Linux instan

Should the Docker image you seek not yet be available on Docker Hub, you can build the Docker image locally.

### 1. Git Clone GenAIComps
### 1. Build the LLM Docker Image

```bash
git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
```

### 2. Build the LLM Docker Image

```bash
docker build -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile .
```

### 3. Build the MegaService Docker Image
### 2. Build the MegaService Docker Image

To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `codegen.py` Python script. Build MegaService Docker image via the command below:

Expand All @@ -37,7 +32,7 @@ cd GenAIExamples/CodeGen
docker build -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
```

### 4. Build the UI Docker Image
### 3. Build the UI Docker Image

Build the frontend Docker image via the command below:

Expand All @@ -52,7 +47,7 @@ Then run the command `docker images`, you will have the following 3 Docker Image
- `opea/codegen:latest`
- `opea/codegen-ui:latest`

### 8. Build CodeGen React UI Docker Image (Optional)
### 4. Build CodeGen React UI Docker Image (Optional)

Build react frontend Docker image via below command:

Expand Down
13 changes: 4 additions & 9 deletions CodeGen/docker_compose/intel/hpu/gaudi/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -6,20 +6,15 @@ This document outlines the deployment process for a CodeGen application utilizin

First of all, you need to build the Docker images locally. This step can be ignored after the Docker images published to the Docker Hub.

### 1. Git Clone GenAIComps
### 1. Build the LLM Docker Image

```bash
git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
```

### 2. Build the LLM Docker Image

```bash
docker build -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile .
```

### 3. Build the MegaService Docker Image
### 2. Build the MegaService Docker Image

To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `codegen.py` Python script. Build the MegaService Docker image via the command below:

Expand All @@ -29,7 +24,7 @@ cd GenAIExamples/CodeGen
docker build -t opea/codegen:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
```

### 4. Build the UI Docker Image
### 3. Build the UI Docker Image

Construct the frontend Docker image via the command below:

Expand All @@ -38,7 +33,7 @@ cd GenAIExamples/CodeGen/ui
docker build -t opea/codegen-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
```

### 8. Build CodeGen React UI Docker Image (Optional)
### 4. Build CodeGen React UI Docker Image (Optional)

Build react frontend Docker image via below command:

Expand Down
13 changes: 4 additions & 9 deletions CodeTrans/docker_compose/intel/cpu/xeon/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -14,35 +14,30 @@ After launching your instance, you can connect to it using SSH (for Linux instan

First of all, you need to build Docker Images locally and install the python package of it. This step can be ignored after the Docker images published to Docker hub.

### 1. Install GenAIComps from Source Code
### 1. Build the LLM Docker Image

```bash
git clone https://github.com/opea-project/GenAIComps.git
cd GenAIComps
```

### 2. Build the LLM Docker Image

```bash
docker build -t opea/llm-tgi:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/llms/text-generation/tgi/Dockerfile .
```

### 3. Build MegaService Docker Image
### 2. Build MegaService Docker Image

```bash
git clone https://github.com/opea-project/GenAIExamples.git
cd GenAIExamples/CodeTrans
docker build -t opea/codetrans:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f Dockerfile .
```

### 4. Build UI Docker Image
### 3. Build UI Docker Image

```bash
cd GenAIExamples/CodeTrans/ui
docker build -t opea/codetrans-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f ./docker/Dockerfile .
```

### 5. Build Nginx Docker Image
### 4. Build Nginx Docker Image

```bash
cd GenAIComps
Expand Down
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