Docsum (#1095)

Signed-off-by: Mustafa <mustafa.cetin@intel.com> Signed-off-by: Harsha Ramayanam <harsha.ramayanam@intel.com> Co-authored-by: Harsha Ramayanam <harsha.ramayanam@intel.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: XinyaoWa <xinyao.wang@intel.com> Co-authored-by: Abolfazl Shahbazi <12436063+ashahba@users.noreply.github.com> Co-authored-by: chen, suyue <suyue.chen@intel.com>
2024-11-18 01:15:42 -08:00
parent 2587179224
commit eb91d1f054
22 changed files with 1392 additions and 275 deletions
--- a/DocSum/docker_compose/intel/hpu/gaudi/README.md
+++ b/DocSum/docker_compose/intel/hpu/gaudi/README.md
@@ -1,47 +1,75 @@
 # Build MegaService of Document Summarization on Gaudi

-This document outlines the deployment process for a Document Summarization application utilizing the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline on Intel Gaudi server. The steps include Docker image creation, container deployment via Docker Compose, and service execution to integrate microservices such as llm. We will publish the Docker images to Docker Hub, which will simplify the deployment process for this service.
+This document outlines the deployment process for a Document Summarization application utilizing the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline on Intel Gaudi server. The steps include Docker image creation, container deployment via Docker Compose, and service execution to integrate microservices such as `llm`. We will publish the Docker images to Docker Hub soon, which will simplify the deployment process for this service.

 ## 🚀 Build Docker Images

-First of all, you need to build Docker Images locally. This step can be ignored once the Docker images are published to Docker hub.
+### 1. Build MicroService Docker Image

-### 1. Pull TGI Gaudi Image
-
-As TGI Gaudi has been officially published as a Docker image, we simply need to pull it:
-
-```bash
-docker pull ghcr.io/huggingface/tgi-gaudi:2.0.6
-```
-
-### 2. Build LLM Image
+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
-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 .
 ```

-### 3. Build MegaService Docker Image
+#### Audio to text Service

-To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `docsum.py` Python script. Build the MegaService Docker image using the command below:
+The Audio to text Service is another service for converting audio to text. Follow these steps to build and run the service:
+
+```bash
+docker build -t opea/dataprep-audio2text:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/multimedia2text/audio2text/Dockerfile .
+```
+
+#### Video to Audio Service
+
+The Video to Audio Service extracts audio from video files. Follow these steps to build and run the service:
+
+```bash
+docker build -t opea/dataprep-video2audio:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/multimedia2text/video2audio/Dockerfile .
+```
+
+#### Multimedia to Text Service
+
+The Multimedia to Text Service transforms multimedia data to text data. Follow these steps to build and run the service:
+
+```bash
+docker build -t opea/dataprep-multimedia2text:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f comps/dataprep/multimedia2text/Dockerfile .
+```
+
+### 2. Build MegaService Docker Image
+
+To construct the Mega Service, we utilize the [GenAIComps](https://github.com/opea-project/GenAIComps.git) microservice pipeline within the `docsum.py` Python script. Build the MegaService Docker image via below command:

 ```bash
 git clone https://github.com/opea-project/GenAIExamples
-cd GenAIExamples/DocSum
+cd GenAIExamples/DocSum/
 docker build -t opea/docsum: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

-Construct the frontend Docker image using the command below:
+Several UI options are provided. If you need to work with multimedia documents, .doc, or .pdf files, suggested to use Gradio UI.
+
+#### Svelte UI
+
+Build the frontend Docker image via below command:

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

-### 5. Build React UI Docker Image
+#### Gradio UI
+
+Build the Gradio UI frontend Docker image using the following command:
+
+```bash
+cd GenAIExamples/DocSum/ui
+docker build -t opea/docsum-gradio-ui:latest --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy -f docker/Dockerfile.gradio .
+```
+
+#### React UI

 Build the frontend Docker image via below command:

@@ -49,48 +77,66 @@ Build the frontend Docker image via below command:
 cd GenAIExamples/DocSum/ui
 export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8888/v1/docsum"
 docker build -t opea/docsum-react-ui:latest --build-arg BACKEND_SERVICE_ENDPOINT=$BACKEND_SERVICE_ENDPOINT -f ./docker/Dockerfile.react .
+
+docker build -t opea/docsum-react-ui:latest --build-arg BACKEND_SERVICE_ENDPOINT=$BACKEND_SERVICE_ENDPOINT --build-arg https_proxy=$https_proxy --build-arg http_proxy=$http_proxy  -f ./docker/Dockerfile.react .
 ```

-Then run the command `docker images`, you will have the following Docker Images:
-
-1. `ghcr.io/huggingface/tgi-gaudi:2.0.6`
-2. `opea/llm-docsum-tgi:latest`
-3. `opea/docsum:latest`
-4. `opea/docsum-ui:latest`
-5. `opea/docsum-react-ui:latest`
-
 ## 🚀 Start Microservices and MegaService

 ### Required Models

-We set default model as "Intel/neural-chat-7b-v3-3", change "LLM_MODEL_ID" in following setting if you want to use other models.
-If use gated models, you also need to provide [huggingface token](https://huggingface.co/docs/hub/security-tokens) to "HUGGINGFACEHUB_API_TOKEN" environment variable.
-
-### Setup Environment Variables
-
-Since the `compose.yaml` will consume some environment variables, you need to setup them in advance as below.
+Default model is "Intel/neural-chat-7b-v3-3". Change "LLM_MODEL_ID" environment variable in commands below if you want to use another model.

 ```bash
-export no_proxy=${your_no_proxy}
-export http_proxy=${your_http_proxy}
-export https_proxy=${your_http_proxy}
 export LLM_MODEL_ID="Intel/neural-chat-7b-v3-3"
-export TGI_LLM_ENDPOINT="http://${host_ip}:8008"
-export HUGGINGFACEHUB_API_TOKEN=${your_hf_api_token}
-export MEGA_SERVICE_HOST_IP=${host_ip}
-export LLM_SERVICE_HOST_IP=${host_ip}
-export BACKEND_SERVICE_ENDPOINT="http://${host_ip}:8888/v1/docsum"
 ```

-Note: Please replace with `host_ip` with your external IP address, do not use localhost.
+When using gated models, you also need to provide [HuggingFace token](https://huggingface.co/docs/hub/security-tokens) to "HUGGINGFACEHUB_API_TOKEN" environment variable.
+
+### Setup Environment Variable
+
+To set up environment variables for deploying Document Summarization services, follow these steps:
+
+1. Set the required environment variables:
+
+   ```bash
+   # Example: host_ip="192.168.1.1"
+   export host_ip="External_Public_IP"
+   # Example: no_proxy="localhost, 127.0.0.1, 192.168.1.1"
+   export no_proxy="Your_No_Proxy"
+   export HUGGINGFACEHUB_API_TOKEN="Your_Huggingface_API_Token"
+   ```
+
+2. If you are in a proxy environment, also set the proxy-related environment variables:
+
+   ```bash
+   export http_proxy="Your_HTTP_Proxy"
+   export https_proxy="Your_HTTPs_Proxy"
+   ```
+
+3. Set up other environment variables:
+
+   ```bash
+   source GenAIExamples/DocSum/docker_compose/set_env.sh
+   ```

 ### Start Microservice Docker Containers

 ```bash
 cd GenAIExamples/DocSum/docker_compose/intel/hpu/gaudi
-docker compose up -d
+docker compose -f compose.yaml up -d
 ```

+You will have the following Docker Images:
+
+1. `opea/docsum-ui:latest`
+2. `opea/docsum:latest`
+3. `opea/llm-docsum-tgi:latest`
+4. `opea/whisper:latest`
+5. `opea/dataprep-audio2text:latest`
+6. `opea/dataprep-multimedia2text:latest`
+7. `opea/dataprep-video2audio:latest`
+
 ### Validate Microservices

 1. TGI Service
@@ -98,7 +144,7 @@ docker compose up -d
   ```bash
   curl http://${host_ip}:8008/generate \
     -X POST \
-     -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":64, "do_sample": true}}' \
+     -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \
     -H 'Content-Type: application/json'
   ```

@@ -111,20 +157,137 @@ docker compose up -d
     -H 'Content-Type: application/json'
   ```

-3. MegaService
+3. Whisper Microservice

   ```bash
+    curl http://${host_ip}:7066/v1/asr \
+        -X POST \
+        -d '{"audio":"UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA"}' \
+        -H 'Content-Type: application/json'
+   ```
+
+   Expected output:
+
+   ```bash
+     {"asr_result":"you"}
+   ```
+
+4. Audio2Text Microservice
+
+   ```bash
+    curl http://${host_ip}:9199/v1/audio/transcriptions \
+        -X POST \
+        -d '{"byte_str":"UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA"}' \
+        -H 'Content-Type: application/json'
+   ```
+
+   Expected output:
+
+   ```bash
+     {"downstream_black_list":[],"id":"--> this will be different id number for each run <--","query":"you"}
+   ```
+
+5. Multimedia to text Microservice
+
+   ```bash
+    curl http://${host_ip}:7079/v1/multimedia2text \
+        -X POST \
+        -d '{"audio":"UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA"}' \
+        -H 'Content-Type: application/json'
+   ```
+
+   Expected output:
+
+   ```bash
+     {"downstream_black_list":[],"id":"--> this will be different id number for each run <--","query":"you"}
+   ```
+
+6. MegaService
+
+   Text:
+
+   ```bash
+   curl -X POST http://${host_ip}:8888/v1/docsum \
+        -H "Content-Type: application/json" \
+        -d '{"type": "text", "messages": "Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5."}'
+
+   # Use English mode (default).
   curl http://${host_ip}:8888/v1/docsum \
       -H "Content-Type: multipart/form-data" \
+       -F "type=text" \
       -F "messages=Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for the most popular models, including FlagEmbedding, Ember, GTE and E5." \
       -F "max_tokens=32" \
       -F "language=en" \
-       -F "stream=false"
+       -F "stream=true"
+
+   # Use Chinese mode.
+   curl http://${host_ip}:8888/v1/docsum \
+       -H "Content-Type: multipart/form-data" \
+       -F "type=text" \
+       -F "messages=2024年9月26日，北京——今日，英特尔正式发布英特尔® 至强® 6性能核处理器（代号Granite Rapids），为AI、数据分析、科学计算等计算密集型业务提供卓越性能。" \
+       -F "max_tokens=32" \
+       -F "language=zh" \
+       -F "stream=true"
+
+   # Upload file
+   curl http://${host_ip}:8888/v1/docsum \
+      -H "Content-Type: multipart/form-data" \
+      -F "type=text" \
+      -F "messages=" \
+      -F "files=@/path to your file (.txt, .docx, .pdf)" \
+      -F "max_tokens=32" \
+      -F "language=en" \
+      -F "stream=true"
   ```

+   > Audio and Video file uploads are not supported in docsum with curl request, please use the Gradio-UI.
+
+   Audio:
+
+   ```bash
+   curl -X POST http://${host_ip}:8888/v1/docsum \
+      -H "Content-Type: application/json" \
+      -d '{"type": "audio", "messages": "UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA"}'
+
+   curl http://${host_ip}:8888/v1/docsum \
+      -H "Content-Type: multipart/form-data" \
+      -F "type=audio" \
+      -F "messages=UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA" \
+      -F "max_tokens=32" \
+      -F "language=en" \
+      -F "stream=true"
+   ```
+
+   Video:
+
+   ```bash
+   curl -X POST http://${host_ip}:8888/v1/docsum \
+      -H "Content-Type: application/json" \
+      -d '{"type": "video", "messages": "convert your video to base64 data type"}'
+
+   curl http://${host_ip}:8888/v1/docsum \
+      -H "Content-Type: multipart/form-data" \
+      -F "type=video" \
+      -F "messages=convert your video to base64 data type" \
+      -F "max_tokens=32" \
+      -F "language=en" \
+      -F "stream=true"
+   ```
+
+> More detailed tests can be found here `cd GenAIExamples/DocSum/test`
+
+## 🚀 Launch the UI
+
+Several UI options are provided. If you need to work with multimedia documents, .doc, or .pdf files, suggested to use Gradio UI.
+
+### Gradio UI
+
+Open this URL `http://{host_ip}:5173` in your browser to access the Gradio based frontend.
+![project-screenshot](../../../../assets/img/docSum_ui_gradio_text.png)
+
 ## 🚀 Launch the Svelte UI

-Open this URL `http://{host_ip}:5173` in your browser to access the frontend.
+Open this URL `http://{host_ip}:5173` in your browser to access the Svelte based frontend.

 ![project-screenshot](https://github.com/intel-ai-tce/GenAIExamples/assets/21761437/93b1ed4b-4b76-4875-927e-cc7818b4825b)

--- a/DocSum/docker_compose/intel/hpu/gaudi/compose.yaml
+++ b/DocSum/docker_compose/intel/hpu/gaudi/compose.yaml
@@ -24,7 +24,8 @@ services:
      - SYS_NICE
    ipc: host
    command: --model-id ${LLM_MODEL_ID} --max-input-length 1024 --max-total-tokens 2048
-  llm:
+
+  llm-docsum-tgi:
    image: ${REGISTRY:-opea}/llm-docsum-tgi:${TAG:-latest}
    container_name: llm-docsum-gaudi-server
    depends_on:
@@ -39,12 +40,61 @@ services:
      TGI_LLM_ENDPOINT: ${TGI_LLM_ENDPOINT}
      HUGGINGFACEHUB_API_TOKEN: ${HUGGINGFACEHUB_API_TOKEN}
    restart: unless-stopped
+
+  whisper:
+    image: ${REGISTRY:-opea}/whisper:${TAG:-latest}
+    container_name: whisper-service
+    ports:
+      - "7066:7066"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      HABANA_VISIBLE_DEVICES: all
+      OMPI_MCA_btl_vader_single_copy_mechanism: none
+    runtime: habana
+    cap_add:
+      - SYS_NICE
+    restart: unless-stopped
+
+  dataprep-audio2text:
+    image: ${REGISTRY:-opea}/dataprep-audio2text:${TAG:-latest}
+    container_name: dataprep-audio2text-service
+    ports:
+      - "9199:9099"
+    ipc: host
+    environment:
+      A2T_ENDPOINT: ${A2T_ENDPOINT}
+
+  dataprep-video2audio:
+    image: ${REGISTRY:-opea}/dataprep-video2audio:${TAG:-latest}
+    container_name: dataprep-video2audio-service
+    ports:
+      - "7078:7078"
+    ipc: host
+    environment:
+      V2A_ENDPOINT: ${V2A_ENDPOINT}
+
+  dataprep-multimedia2text:
+    image: ${REGISTRY:-opea}/dataprep-multimedia2text:${TAG:-latest}
+    container_name: dataprep-multimedia2text
+    ports:
+      - "7079:7079"
+    ipc: host
+    environment:
+      V2A_ENDPOINT: ${V2A_ENDPOINT}
+      A2T_ENDPOINT: ${A2T_ENDPOINT}
+
  docsum-gaudi-backend-server:
    image: ${REGISTRY:-opea}/docsum:${TAG:-latest}
    container_name: docsum-gaudi-backend-server
    depends_on:
      - tgi-service
-      - llm
+      - llm-docsum-tgi
+      - dataprep-multimedia2text
+      - dataprep-video2audio
+      - dataprep-audio2text
    ports:
      - "8888:8888"
    environment:
@@ -52,10 +102,13 @@ services:
      - https_proxy=${https_proxy}
      - http_proxy=${http_proxy}
      - MEGA_SERVICE_HOST_IP=${MEGA_SERVICE_HOST_IP}
+      - DATA_SERVICE_HOST_IP=${DATA_SERVICE_HOST_IP}
      - LLM_SERVICE_HOST_IP=${LLM_SERVICE_HOST_IP}
+
    ipc: host
    restart: always
-  docsum-gaudi-ui-server:
+
+  docsum-ui:
    image: ${REGISTRY:-opea}/docsum-ui:${TAG:-latest}
    container_name: docsum-gaudi-ui-server
    depends_on:
@@ -66,6 +119,7 @@ services:
      - no_proxy=${no_proxy}
      - https_proxy=${https_proxy}
      - http_proxy=${http_proxy}
+      - BACKEND_SERVICE_ENDPOINT=${BACKEND_SERVICE_ENDPOINT}
      - DOC_BASE_URL=${BACKEND_SERVICE_ENDPOINT}
    ipc: host
    restart: always