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Add EdgeCraftRag as a GenAIExample (#1072)
Signed-off-by: ZePan110 <ze.pan@intel.com> Signed-off-by: chensuyue <suyue.chen@intel.com> Signed-off-by: Zhu, Yongbo <yongbo.zhu@intel.com> Signed-off-by: Wang, Xigui <xigui.wang@intel.com> Co-authored-by: ZePan110 <ze.pan@intel.com> Co-authored-by: chen, suyue <suyue.chen@intel.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: xiguiw <111278656+xiguiw@users.noreply.github.com> Co-authored-by: lvliang-intel <liang1.lv@intel.com>
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ModelIn | ||
modelin |
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# Copyright (C) 2024 Intel Corporation | ||
# SPDX-License-Identifier: Apache-2.0 | ||
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FROM python:3.11-slim | ||
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SHELL ["/bin/bash", "-o", "pipefail", "-c"] | ||
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RUN apt-get update -y && apt-get install -y --no-install-recommends --fix-missing \ | ||
libgl1-mesa-glx \ | ||
libjemalloc-dev | ||
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RUN useradd -m -s /bin/bash user && \ | ||
mkdir -p /home/user && \ | ||
chown -R user /home/user/ | ||
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COPY ./edgecraftrag /home/user/edgecraftrag | ||
COPY ./chatqna.py /home/user/chatqna.py | ||
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WORKDIR /home/user/edgecraftrag | ||
RUN pip install --no-cache-dir -r requirements.txt | ||
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WORKDIR /home/user | ||
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USER user | ||
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RUN echo 'ulimit -S -n 999999' >> ~/.bashrc | ||
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ENTRYPOINT ["python", "chatqna.py"] |
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FROM python:3.11-slim | ||
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SHELL ["/bin/bash", "-o", "pipefail", "-c"] | ||
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RUN apt-get update -y && apt-get install -y --no-install-recommends --fix-missing \ | ||
libgl1-mesa-glx \ | ||
libjemalloc-dev | ||
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RUN apt-get update && apt-get install -y gnupg wget | ||
RUN wget -qO - https://repositories.intel.com/gpu/intel-graphics.key | \ | ||
gpg --yes --dearmor --output /usr/share/keyrings/intel-graphics.gpg | ||
RUN echo "deb [arch=amd64,i386 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/gpu/ubuntu jammy client" | \ | ||
tee /etc/apt/sources.list.d/intel-gpu-jammy.list | ||
RUN apt-get update | ||
RUN apt-get install -y \ | ||
intel-opencl-icd intel-level-zero-gpu level-zero intel-level-zero-gpu-raytracing \ | ||
intel-media-va-driver-non-free libmfx1 libmfxgen1 libvpl2 \ | ||
libegl-mesa0 libegl1-mesa libegl1-mesa-dev libgbm1 libgl1-mesa-dev libgl1-mesa-dri \ | ||
libglapi-mesa libgles2-mesa-dev libglx-mesa0 libigdgmm12 libxatracker2 mesa-va-drivers \ | ||
mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo | ||
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RUN useradd -m -s /bin/bash user && \ | ||
mkdir -p /home/user && \ | ||
chown -R user /home/user/ | ||
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COPY ./edgecraftrag /home/user/edgecraftrag | ||
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WORKDIR /home/user/edgecraftrag | ||
RUN pip install --no-cache-dir -r requirements.txt | ||
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WORKDIR /home/user/ | ||
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USER user | ||
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ENTRYPOINT ["python", "-m", "edgecraftrag.server"] |
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# Edge Craft Retrieval-Augmented Generation | ||
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Edge Craft RAG (EC-RAG) is a customizable, tunable and production-ready | ||
Retrieval-Augmented Generation system for edge solutions. It is designed to | ||
curate the RAG pipeline to meet hardware requirements at edge with guaranteed | ||
quality and performance. | ||
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## Quick Start Guide | ||
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### Run Containers with Docker Compose | ||
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```bash | ||
cd GenAIExamples/EdgeCraftRAG/docker_compose/intel/gpu/arc | ||
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export MODEL_PATH="your model path for all your models" | ||
export DOC_PATH="your doc path for uploading a dir of files" | ||
export HOST_IP="your host ip" | ||
export UI_SERVICE_PORT="port for UI service" | ||
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# Optional for vllm endpoint | ||
export vLLM_ENDPOINT="http://${HOST_IP}:8008" | ||
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# If you have a proxy configured, uncomment below line | ||
# export no_proxy=$no_proxy,${HOST_IP},edgecraftrag,edgecraftrag-server | ||
# If you have a HF mirror configured, it will be imported to the container | ||
# export HF_ENDPOINT="your HF mirror endpoint" | ||
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# By default, the ports of the containers are set, uncomment if you want to change | ||
# export MEGA_SERVICE_PORT=16011 | ||
# export PIPELINE_SERVICE_PORT=16011 | ||
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docker compose up -d | ||
``` | ||
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### (Optional) Build Docker Images for Mega Service, Server and UI by your own | ||
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```bash | ||
cd GenAIExamples/EdgeCraftRAG | ||
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docker build --build-arg http_proxy=$HTTP_PROXY --build-arg https_proxy=$HTTPS_PROXY --build-arg no_proxy=$NO_PROXY -t opea/edgecraftrag:latest -f Dockerfile . | ||
docker build --build-arg http_proxy=$HTTP_PROXY --build-arg https_proxy=$HTTPS_PROXY --build-arg no_proxy=$NO_PROXY -t opea/edgecraftrag-server:latest -f Dockerfile.server . | ||
docker build --build-arg http_proxy=$HTTP_PROXY --build-arg https_proxy=$HTTPS_PROXY --build-arg no_proxy=$NO_PROXY -t opea/edgecraftrag-ui:latest -f ui/docker/Dockerfile.ui . | ||
``` | ||
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### ChatQnA with LLM Example (Command Line) | ||
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```bash | ||
cd GenAIExamples/EdgeCraftRAG | ||
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# Activate pipeline test_pipeline_local_llm | ||
curl -X POST http://${HOST_IP}:16010/v1/settings/pipelines -H "Content-Type: application/json" -d @tests/test_pipeline_local_llm.json | jq '.' | ||
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# Will need to wait for several minutes | ||
# Expected output: | ||
# { | ||
# "idx": "3214cf25-8dff-46e6-b7d1-1811f237cf8c", | ||
# "name": "rag_test", | ||
# "comp_type": "pipeline", | ||
# "node_parser": { | ||
# "idx": "ababed12-c192-4cbb-b27e-e49c76a751ca", | ||
# "parser_type": "simple", | ||
# "chunk_size": 400, | ||
# "chunk_overlap": 48 | ||
# }, | ||
# "indexer": { | ||
# "idx": "46969b63-8a32-4142-874d-d5c86ee9e228", | ||
# "indexer_type": "faiss_vector", | ||
# "model": { | ||
# "idx": "7aae57c0-13a4-4a15-aecb-46c2ec8fe738", | ||
# "type": "embedding", | ||
# "model_id": "BAAI/bge-small-en-v1.5", | ||
# "model_path": "/home/user/models/bge_ov_embedding", | ||
# "device": "auto" | ||
# } | ||
# }, | ||
# "retriever": { | ||
# "idx": "3747fa59-ff9b-49b6-a8e8-03cdf8c979a4", | ||
# "retriever_type": "vectorsimilarity", | ||
# "retrieve_topk": 30 | ||
# }, | ||
# "postprocessor": [ | ||
# { | ||
# "idx": "d46a6cae-ba7a-412e-85b7-d334f175efaa", | ||
# "postprocessor_type": "reranker", | ||
# "model": { | ||
# "idx": "374e7471-bd7d-41d0-b69d-a749a052b4b0", | ||
# "type": "reranker", | ||
# "model_id": "BAAI/bge-reranker-large", | ||
# "model_path": "/home/user/models/bge_ov_reranker", | ||
# "device": "auto" | ||
# }, | ||
# "top_n": 2 | ||
# } | ||
# ], | ||
# "generator": { | ||
# "idx": "52d8f112-6290-4dd3-bc28-f9bd5deeb7c8", | ||
# "generator_type": "local", | ||
# "model": { | ||
# "idx": "fa0c11e1-46d1-4df8-a6d8-48cf6b99eff3", | ||
# "type": "llm", | ||
# "model_id": "qwen2-7b-instruct", | ||
# "model_path": "/home/user/models/qwen2-7b-instruct/INT4_compressed_weights", | ||
# "device": "auto" | ||
# } | ||
# }, | ||
# "status": { | ||
# "active": true | ||
# } | ||
# } | ||
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# Prepare data from local directory | ||
curl -X POST http://${HOST_IP}:16010/v1/data -H "Content-Type: application/json" -d '{"local_path":"#REPLACE WITH YOUR LOCAL DOC DIR#"}' | jq '.' | ||
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# Validate Mega Service | ||
curl -X POST http://${HOST_IP}:16011/v1/chatqna -H "Content-Type: application/json" -d '{"messages":"#REPLACE WITH YOUR QUESTION HERE#", "top_n":5, "max_tokens":512}' | jq '.' | ||
``` | ||
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### ChatQnA with LLM Example (UI) | ||
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Open your browser, access http://${HOST_IP}:8082 | ||
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> Your browser should be running on the same host of your console, otherwise you will need to access UI with your host domain name instead of ${HOST_IP}. | ||
### (Optional) Launch vLLM with OpenVINO service | ||
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```bash | ||
# 1. export LLM_MODEL | ||
export LLM_MODEL="your model id" | ||
# 2. Uncomment below code in 'GenAIExamples/EdgeCraftRAG/docker_compose/intel/gpu/arc/compose.yaml' | ||
# vllm-service: | ||
# image: vllm:openvino | ||
# container_name: vllm-openvino-server | ||
# depends_on: | ||
# - vllm-service | ||
# ports: | ||
# - "8008:80" | ||
# environment: | ||
# no_proxy: ${no_proxy} | ||
# http_proxy: ${http_proxy} | ||
# https_proxy: ${https_proxy} | ||
# vLLM_ENDPOINT: ${vLLM_ENDPOINT} | ||
# LLM_MODEL: ${LLM_MODEL} | ||
# entrypoint: /bin/bash -c "\ | ||
# cd / && \ | ||
# export VLLM_CPU_KVCACHE_SPACE=50 && \ | ||
# python3 -m vllm.entrypoints.openai.api_server \ | ||
# --model '${LLM_MODEL}' \ | ||
# --host 0.0.0.0 \ | ||
# --port 80" | ||
``` | ||
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## Advanced User Guide | ||
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### Pipeline Management | ||
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#### Create a pipeline | ||
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```bash | ||
curl -X POST http://${HOST_IP}:16010/v1/settings/pipelines -H "Content-Type: application/json" -d @examples/test_pipeline.json | jq '.' | ||
``` | ||
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It will take some time to prepare the embedding model. | ||
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#### Upload a text | ||
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```bash | ||
curl -X POST http://${HOST_IP}:16010/v1/data -H "Content-Type: application/json" -d @examples/test_data.json | jq '.' | ||
``` | ||
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#### Provide a query to retrieve context with similarity search. | ||
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```bash | ||
curl -X POST http://${HOST_IP}:16010/v1/retrieval -H "Content-Type: application/json" -d @examples/test_query.json | jq '.' | ||
``` | ||
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#### Create the second pipeline test2 | ||
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```bash | ||
curl -X POST http://${HOST_IP}:16010/v1/settings/pipelines -H "Content-Type: application/json" -d @examples/test_pipeline2.json | jq '.' | ||
``` | ||
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#### Check all pipelines | ||
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```bash | ||
curl -X GET http://${HOST_IP}:16010/v1/settings/pipelines -H "Content-Type: application/json" | jq '.' | ||
``` | ||
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#### Compare similarity retrieval (test1) and keyword retrieval (test2) | ||
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```bash | ||
# Activate pipeline test1 | ||
curl -X PATCH http://${HOST_IP}:16010/v1/settings/pipelines/test1 -H "Content-Type: application/json" -d '{"active": "true"}' | jq '.' | ||
# Similarity retrieval | ||
curl -X POST http://${HOST_IP}:16010/v1/retrieval -H "Content-Type: application/json" -d '{"messages":"number"}' | jq '.' | ||
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# Activate pipeline test2 | ||
curl -X PATCH http://${HOST_IP}:16010/v1/settings/pipelines/test2 -H "Content-Type: application/json" -d '{"active": "true"}' | jq '.' | ||
# Keyword retrieval | ||
curl -X POST http://${HOST_IP}:16010/v1/retrieval -H "Content-Type: application/json" -d '{"messages":"number"}' | jq '.' | ||
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``` | ||
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### Model Management | ||
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#### Load a model | ||
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```bash | ||
curl -X POST http://${HOST_IP}:16010/v1/settings/models -H "Content-Type: application/json" -d @examples/test_model_load.json | jq '.' | ||
``` | ||
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It will take some time to load the model. | ||
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#### Check all models | ||
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```bash | ||
curl -X GET http://${HOST_IP}:16010/v1/settings/models -H "Content-Type: application/json" | jq '.' | ||
``` | ||
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#### Update a model | ||
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```bash | ||
curl -X PATCH http://${HOST_IP}:16010/v1/settings/models/BAAI/bge-reranker-large -H "Content-Type: application/json" -d @examples/test_model_update.json | jq '.' | ||
``` | ||
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#### Check a certain model | ||
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```bash | ||
curl -X GET http://${HOST_IP}:16010/v1/settings/models/BAAI/bge-reranker-large -H "Content-Type: application/json" | jq '.' | ||
``` | ||
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#### Delete a model | ||
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```bash | ||
curl -X DELETE http://${HOST_IP}:16010/v1/settings/models/BAAI/bge-reranker-large -H "Content-Type: application/json" | jq '.' | ||
``` | ||
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### File Management | ||
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#### Add a text | ||
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```bash | ||
curl -X POST http://${HOST_IP}:16010/v1/data -H "Content-Type: application/json" -d @examples/test_data.json | jq '.' | ||
``` | ||
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#### Add files from existed file path | ||
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```bash | ||
curl -X POST http://${HOST_IP}:16010/v1/data -H "Content-Type: application/json" -d @examples/test_data_dir.json | jq '.' | ||
curl -X POST http://${HOST_IP}:16010/v1/data -H "Content-Type: application/json" -d @examples/test_data_file.json | jq '.' | ||
``` | ||
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#### Check all files | ||
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```bash | ||
curl -X GET http://${HOST_IP}:16010/v1/data/files -H "Content-Type: application/json" | jq '.' | ||
``` | ||
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#### Check one file | ||
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```bash | ||
curl -X GET http://${HOST_IP}:16010/v1/data/files/test2.docx -H "Content-Type: application/json" | jq '.' | ||
``` | ||
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#### Delete a file | ||
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```bash | ||
curl -X DELETE http://${HOST_IP}:16010/v1/data/files/test2.docx -H "Content-Type: application/json" | jq '.' | ||
``` | ||
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#### Update a file | ||
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```bash | ||
curl -X PATCH http://${HOST_IP}:16010/v1/data/files/test.pdf -H "Content-Type: application/json" -d @examples/test_data_file.json | jq '.' | ||
``` |
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