From cc020381c9fc5fe0202d220896f732cc162b8ff0 Mon Sep 17 00:00:00 2001 From: rbrugaro Date: Wed, 30 Oct 2024 08:52:25 -0700 Subject: [PATCH] Graph rag (#1007) Signed-off-by: Rita Brugarolas Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Signed-off-by: Arthur Leung --- GraphRAG/Dockerfile | 33 ++ GraphRAG/README.md | 254 +++++++++++++++ GraphRAG/assets/8microservices.png | Bin 0 -> 176826 bytes GraphRAG/assets/img/chat_ui_init.png | Bin 0 -> 15118 bytes GraphRAG/assets/img/chat_ui_response.png | Bin 0 -> 76033 bytes GraphRAG/assets/img/chat_ui_upload.png | Bin 0 -> 87990 bytes GraphRAG/assets/img/chatqna_architecture.png | Bin 0 -> 513283 bytes GraphRAG/assets/img/chatqna_dashboards.png | Bin 0 -> 102817 bytes GraphRAG/assets/img/chatqna_flow_chart.png | Bin 0 -> 117275 bytes GraphRAG/assets/img/conversation_ui_init.png | Bin 0 -> 54802 bytes .../assets/img/conversation_ui_response.png | Bin 0 -> 94972 bytes 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create mode 100644 GraphRAG/ui/svelte/tests/test_file.txt create mode 100644 GraphRAG/ui/svelte/tsconfig.json create mode 100644 GraphRAG/ui/svelte/vite.config.ts diff --git a/GraphRAG/Dockerfile b/GraphRAG/Dockerfile new file mode 100644 index 0000000000..bf01c01b2e --- /dev/null +++ b/GraphRAG/Dockerfile @@ -0,0 +1,33 @@ +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +FROM python:3.11-slim + +RUN apt-get update -y && apt-get install -y --no-install-recommends --fix-missing \ + git \ + libgl1-mesa-glx \ + libjemalloc-dev + +RUN useradd -m -s /bin/bash user && \ + mkdir -p /home/user && \ + chown -R user /home/user/ + +WORKDIR /home/user/ +RUN git clone https://github.com/opea-project/GenAIComps.git + +WORKDIR /home/user/GenAIComps +RUN pip install --no-cache-dir --upgrade pip && \ + pip install --no-cache-dir -r /home/user/GenAIComps/requirements.txt && \ + pip install --no-cache-dir langchain_core + +COPY ./graphrag.py /home/user/graphrag.py + +ENV PYTHONPATH=$PYTHONPATH:/home/user/GenAIComps + +USER user + +WORKDIR /home/user + +RUN echo 'ulimit -S -n 999999' >> ~/.bashrc + +ENTRYPOINT ["python", "graphrag.py"] diff --git a/GraphRAG/README.md b/GraphRAG/README.md new file mode 100644 index 0000000000..10e281ae90 --- /dev/null +++ b/GraphRAG/README.md @@ -0,0 +1,254 @@ +# GraphRAG Application + +While naive RAG works well in fetching precise information it fails on global questions directed at an entire text corpus, such as "What are the main themes in the dataset?". +GraphRAG was introduced by Microsoft paper "From Local to Global: A Graph RAG Approach to Query-Focused Summarization". The key elements are: + +- Uses LLM to derive an entity knowledge graph from the source documents +- Uses hierarchical leiden algorithm to identify communities of closely-related entities and summaries are extracted for each community +- For an input query the relevant communities are identified and partial answers are generated from each of the community summaries (query-focused summarization (QFS)) +- There is a final generation stage that responds to the query based on the intermediate community answers. + +## Deploy GraphRAG Service + +The GraphRAG service can be effortlessly deployed on Intel Gaudi2, Intel Xeon Scalable Processors. + +Quick Start Deployment Steps: + +1. Set up the environment variables. +2. Run Docker Compose. +3. Consume the GraphRAG Service. + +Note: If you do not have docker installed you can run this script to install docker : `bash docker_compose/install_docker.sh` + +### Quick Start: 1.Setup Environment Variable + +To set up environment variables for deploying GraphRAG services, follow these steps: + +1. Set the required private environment variables: + + ```bash + export host_ip=${your_hostname IP} #local IP, i.e "192.168.1.1" + export NEO4J_URI=${your_neo4j_url} + export NEO4J_USERNAME=${your_neo4j_username} + export NEO4J_PASSWORD=${your_neo4j_password} + export PYTHONPATH=${path_to_comps} + export OPENAI_KEY=${your_openai_api_key} #optional, when not provided will use smaller models TGI/TEI + export HUGGINGFACEHUB_API_TOKEN=${your_hf_token} #needed for TGI/TEI models + ``` + +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" + export no_proxy=$no_proxy,${host_ip} #important to add {host_ip} for containers communication + ``` + +3. Set up other environment variables: + + ```bash + # on Gaudi + source ./docker_compose/intel/hpu/gaudi/set_env.sh + ``` + +### Quick Start: 2.Run Docker Compose + +If the microservice images are available in Docker Hub they will be pulled, otherwise you will need to build the container images manually. Please refer to the 'Build Docker Images' in [Guide](../ChatQnA/docker_compose/intel/cpu/xeon/README.md). [test_compose.sh](tests/test_compose.sh) can be a good resource as it shows how to do image build, starting services, validated each microservices and megaservices. This is what is used in CI/CD. + +Docker compose will start 8 services: ![8 servicesi in GraphRAG](assets/8microservices.png) + +```bash +cd GraphRAG/docker_compose/intel/hpu/gaudi +docker compose -f compose.yaml up -d +``` + +### QuickStart: 3.Upload RAG Files and Consume the GraphRAG Service + +To chat with retrieved information, you need to upload a file using `Dataprep` service. + +Here is an example of `Nike 2023` pdf. + +```bash +# download pdf file +wget https://raw.githubusercontent.com/opea-project/GenAIComps/main/comps/retrievers/redis/data/nke-10k-2023.pdf +# upload pdf file with dataprep +curl -X POST "http://${host_ip}:6004/v1/dataprep" \ + -H "Content-Type: multipart/form-data" \ + -F "files=@./nke-10k-2023.pdf" +``` + +```bash +curl http://${host_ip}:8888/v1/graphrag \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-4o-mini","messages": [{"role": "user","content": "What is the revenue of Nike in 2023? + "}]}' +``` + +## Architecture and Deploy details + +The GraphRAG example is implemented using the component-level microservices defined in [GenAIComps](https://github.com/opea-project/GenAIComps). The flow chart below shows the information flow between different microservices for this example. + +```mermaid +--- +config: + flowchart: + nodeSpacing: 400 + rankSpacing: 100 + curve: linear + themeVariables: + fontSize: 50px +--- +flowchart LR + %% Colors %% + classDef blue fill:#ADD8E6,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5 + classDef orange fill:#FBAA60,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5 + classDef orchid fill:#C26DBC,stroke:#ADD8E6,stroke-width:2px,fill-opacity:0.5 + classDef invisible fill:transparent,stroke:transparent; + style GraphRAG-MegaService stroke:#000000 + + %% Subgraphs %% + subgraph GraphRAG-MegaService["GraphRAG MegaService "] + direction LR + RET([Retrieval MicroService]):::blue + LLM([LLM MicroService]):::blue + EM([Embedding MicroService]):::blue + end + subgraph UserInterface[" User Interface "] + direction LR + a([User Input Query]):::orchid + Ingest([Ingest data]):::orchid + UI([UI server
]):::orchid + end + + + GDB{{Graph DB

}} + DP([Data Preparation MicroService]):::blue + GW([GraphRAG GateWay
]):::orange + + + %% Data Preparation flow + %% Ingest data flow + direction LR + Ingest[Ingest data] --> UI + UI --> DP + + %% interactions buried inside the DP and RET microservice implementations + DP <-.-> EM + DP <-.-> LLM + RET <-.-> EM + RET <-.-> LLM + + + %% Questions interaction + direction LR + a[User Input Query] --> UI + UI --> GW + GW <==> GraphRAG-MegaService + RET ==> LLM + + + direction TB + %% Graph DB interaction + RET <-.-> |d|GDB + DP <-.-> |d|GDB + + linkStyle 2 stroke:#000000,stroke-width:2px; + linkStyle 3 stroke:#000000,stroke-width:2px; + linkStyle 4 stroke:#000000,stroke-width:2px; + linkStyle 5 stroke:#000000,stroke-width:2px; + + +``` + +> **Note**: The Dataprep and Retriever microservices use the LLM Microservice and Embedding Microservice in their implementation. For example, Dataprep uses LLM to extract entities and relationships from text to build graph and Retriever uses LLM to summarize communities (these are clusters of similar entities and their properties). Those endpoint interactions with the corresponding prompt templates are buried in the microservice implementation thus not managed by the megaservice orchestrator scheduler and not exposed in the megaservice. Shown as thin black lines in diagram. + +This GraphRAG use case performs RAG using Llama-index, Neo4J Graph Property Store and Text Generation Inference on [Intel Gaudi2](https://www.intel.com/content/www/us/en/products/details/processors/ai-accelerators/gaudi-overview.html) or [Intel Xeon Scalable Processors](https://www.intel.com/content/www/us/en/products/details/processors/xeon.html). +In the below, we provide a table that describes for each microservice component in the GraphRAG architecture, the default configuration of the open source project, hardware, port, and endpoint. + +Gaudi default compose.yaml +| MicroService | Open Source Project | HW | Port | Endpoint | +| ------------ | ------------------- | ----- | ---- | -------------------- | +| Embedding | Llama-index | Xeon | 6006 | /v1/embaddings | +| Retriever | Llama-index, Neo4j | Xeon | 6009 | /v1/retrieval | +| LLM | Llama-index, TGI | Gaudi | 6005 | /v1/chat/completions | +| Dataprep | Neo4j, LlamaIndex | Xeon | 6004 | /v1/dataprep | + +### Models Selection + +GraphRAG quality dependents heavily on the ability to extract a high quality graph. We highly recommend using the best model available to you. Table below shows default models specified in the codebase when OPENAI_API_KEY is available and for local inference w TEI/TGI. The local models are small since those will be used in CI/CD but users should improve upon these by changing the `xxx_MODEL_ID` in `docker_compose/xxx/set_env.sh`. + +Working on a table comparison of various model sizes vs. naive RAG with a dataset that reflects well the benefits of GraphRAG. Stay tuned! + +| Service | Model | +| --------- | ------------------------------------- | +| Embedding | BAAI/bge-base-en-v1.5 | +| Embedding | "text-embedding-3-small" | +| LLM | gpt-4o | +| LLM | "meta-llama/Meta-Llama-3-8B-Instruct" | + +## Consume GraphRAG Service with RAG + +### Check Service Status + +Before consuming GraphRAG Service, make sure each microservice is ready by checking the docker logs of each microservice. [test_compose.sh](tests/test_compose.sh) can be a good resource as it shows how CI/CD validated each microservices based on returned HTTP status and response body. + +```bash +docker logs container_name +``` + +### Upload RAG Files + +To chat with retrieved information, you need to upload a file using `Dataprep` service. + +Here is an example of `Nike 2023` pdf. + +```bash +# download pdf file +wget https://raw.githubusercontent.com/opea-project/GenAIComps/main/comps/retrievers/redis/data/nke-10k-2023.pdf +# upload pdf file with dataprep +curl -X POST "http://${host_ip}:6007/v1/dataprep" \ + -H "Content-Type: multipart/form-data" \ + -F "files=@./nke-10k-2023.pdf" +``` + +### Consume GraphRAG Service + +Two ways of consuming GraphRAG Service: + +1. Use cURL command on terminal + +```bash +curl http://${host_ip}:8888/v1/graphrag \ + -H "Content-Type: application/json" \ + -d '{ + "model": "gpt-4o-mini","messages": [{"role": "user","content": "Who is John Brady and has he had any confrontations? + "}]}' +``` + +2. Access via frontend + + To access the frontend, open the following URL in your browser: `http://{host_ip}:5173` + + By default, the UI runs on port 5173 internally. + + If you choose conversational UI, use this URL: `http://{host_ip}:5174` + +## Troubleshooting + +1. If you get errors like "Access Denied", [validate micro service](https://github.com/opea-project/GenAIExamples/blob/main/ChatQnA/docker_compose/intel/cpu/xeon/README.md#validate-microservices) first. A simple example: + + ```bash + http_proxy="" curl ${host_ip}:6006/embed -X POST -d '{"inputs":"What is Deep Learning?"}' -H 'Content-Type: application/json' + ``` + +2. (Docker only) If all microservices work well, check the port ${host_ip}:8888, the port may be allocated by other users, you can modify the `compose.yaml`. + +3. (Docker only) If you get errors like "The container name is in use", change container name in `compose.yaml`. + +## Monitoring OPEA Service with Prometheus and Grafana dashboard + +OPEA microservice deployment can easily be monitored through Grafana dashboards in conjunction with Prometheus data collection. 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zzrH8XQSDT;z~u1ZIM>Qca)AcSXqR%s2H9P1&(v7)ghgAl7KE8aJZa;7|I~oX07jxL za^XqlUQ?P<9P<*E8I6T}SZtuAjqD3w^#C-n+-P3CPK0Com*DE{x5re(_f zzYdx7EK%Ll^_iHneRA?Y(!qH$}g#U zV8wezkggnO9t6A4Ljkgvk9kPL?O(19oH})i!t)w@g|R}pa2$+lKEFCYPY*uF(B5kD qxXb9xBIT?K=t&P>GyUlQlp$PE)FtIS<~?&_nWvftPpTh35C0#(2vGC@ literal 0 HcmV?d00001 diff --git a/GraphRAG/docker_compose/install_docker.sh b/GraphRAG/docker_compose/install_docker.sh new file mode 100644 index 0000000000..d2a495bde3 --- /dev/null +++ b/GraphRAG/docker_compose/install_docker.sh @@ -0,0 +1,35 @@ +#!/usr/bin/env bash + +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Update the package index +sudo apt-get -y update + +# Install prerequisites +sudo apt-get -y install ca-certificates curl --no-install-recommends --fix-missing + +# Create the directory for the Docker GPG key +sudo install -m 0755 -d /etc/apt/keyrings + +# Add Docker's official GPG key +sudo curl -fsSL https://download.docker.com/linux/ubuntu/gpg -o /etc/apt/keyrings/docker.asc + +# Set permissions for the GPG key +sudo chmod a+r /etc/apt/keyrings/docker.asc + +# Add Docker repository to the sources list +echo "deb [arch=$(dpkg --print-architecture) signed-by=/etc/apt/keyrings/docker.asc] https://download.docker.com/linux/ubuntu \ + $(. /etc/os-release && echo "$VERSION_CODENAME") stable" | sudo tee /etc/apt/sources.list.d/docker.list > /dev/null + +# Update the package index with Docker packages +sudo apt-get -y update + +# Install Docker packages +sudo apt-get -y install docker-ce docker-ce-cli containerd.io docker-buildx-plugin docker-compose-plugin --no-install-recommends --fix-missing + +# add existing user +sudo usermod -aG docker $USER + +# Optional: Verify that Docker is installed correctly +sudo docker --version diff --git a/GraphRAG/docker_compose/intel/hpu/gaudi/compose.yaml b/GraphRAG/docker_compose/intel/hpu/gaudi/compose.yaml new file mode 100644 index 0000000000..b03cba56ab --- /dev/null +++ b/GraphRAG/docker_compose/intel/hpu/gaudi/compose.yaml @@ -0,0 +1,181 @@ +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +version: "3.8" +services: + neo4j-apoc: + image: neo4j:latest + container_name: neo4j-apoc + volumes: + - /$HOME/neo4j/logs:/logs + - /$HOME/neo4j/config:/config + - /$HOME/neo4j/data:/data + - /$HOME/neo4j/plugins:/plugins + ipc: host + environment: + - NEO4J_AUTH=${NEO4J_USERNAME}/${NEO4J_PASSWORD} + - NEO4J_PLUGINS=["apoc"] + - NEO4J_apoc_export_file_enabled=true + - NEO4J_apoc_import_file_enabled=true + - NEO4J_apoc_import_file_use__neo4j__config=true + - NEO4J_dbms_security_procedures_unrestricted=apoc.\* + ports: + - "7474:7474" + - "7687:7687" + restart: always + tei-embedding-service: + image: ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 + container_name: tei-embedding-server + ports: + - "6006:80" + volumes: + - "./data:/data" + shm_size: 1g + environment: + no_proxy: ${no_proxy} + NO_PROXY: ${no_proxy} + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + HUGGING_FACE_HUB_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} + ipc: host + command: --model-id ${EMBEDDING_MODEL_ID} --auto-truncate + tgi-gaudi-service: + image: ghcr.io/huggingface/tgi-gaudi:2.0.5 + container_name: tgi-gaudi-server + ports: + - "6005:80" + volumes: + - "./data:/data" + environment: + no_proxy: ${no_proxy} + NO_PROXY: ${no_proxy} + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + HUGGING_FACE_HUB_TOKEN: ${HUGGINGFACEHUB_API_TOKEN} + HF_HUB_DISABLE_PROGRESS_BARS: 1 + HF_HUB_ENABLE_HF_TRANSFER: 0 + HABANA_VISIBLE_DEVICES: all + OMPI_MCA_btl_vader_single_copy_mechanism: none + ENABLE_HPU_GRAPH: true + LIMIT_HPU_GRAPH: true + USE_FLASH_ATTENTION: true + FLASH_ATTENTION_RECOMPUTE: true + runtime: habana + cap_add: + - SYS_NICE + ipc: host + command: --model-id ${LLM_MODEL_ID} --max-input-length 2048 --max-total-tokens 4096 + dataprep-neo4j-llamaindex: + image: opea/dataprep-neo4j-llamaindex:latest + container_name: dataprep-neo4j-server + depends_on: + - neo4j-apoc + - tgi-gaudi-service + - tei-embedding-service + ports: + - "6004:6004" + ipc: host + environment: + no_proxy: ${no_proxy} + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + host_ip: ${host_ip} + NEO4J_URL: ${NEO4J_URL} + NEO4J_USERNAME: ${NEO4J_USERNAME} + NEO4J_PASSWORD: ${NEO4J_PASSWORD} + TGI_LLM_ENDPOINT: ${TGI_LLM_ENDPOINT} + TEI_EMBEDDING_ENDPOINT: ${TEI_EMBEDDING_ENDPOINT} + OPENAI_API_KEY: ${OPENAI_API_KEY} + OPENAI_EMBEDDING_MODEL: ${OPENAI_EMBEDDING_MODEL} + OPENAI_LLM_MODEL: ${OPENAI_LLM_MODEL} + EMBEDDING_MODEL_ID: ${EMBEDDING_MODEL_ID} + LLM_MODEL_ID: ${LLM_MODEL_ID} + LOGFLAG: ${LOGFLAG} + restart: unless-stopped + retriever-neo4j-llamaindex: + image: opea/retriever-neo4j-llamaindex:latest + container_name: retriever-neo4j-server + depends_on: + - neo4j-apoc + - tgi-gaudi-service + - tei-embedding-service + ports: + - "6009:6009" + ipc: host + environment: + no_proxy: ${no_proxy} + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + host_ip: ${host_ip} + NEO4J_URL: ${NEO4J_URL} + NEO4J_USERNAME: ${NEO4J_USERNAME} + NEO4J_PASSWORD: ${NEO4J_PASSWORD} + TGI_LLM_ENDPOINT: ${TGI_LLM_ENDPOINT} + TEI_EMBEDDING_ENDPOINT: ${TEI_EMBEDDING_ENDPOINT} + OPENAI_API_KEY: ${OPENAI_API_KEY} + OPENAI_EMBEDDING_MODEL: ${OPENAI_EMBEDDING_MODEL} + OPENAI_LLM_MODEL: ${OPENAI_LLM_MODEL} + EMBEDDING_MODEL_ID: ${EMBEDDING_MODEL_ID} + LLM_MODEL_ID: ${LLM_MODEL_ID} + LOGFLAG: ${LOGFLAG} + restart: unless-stopped + graphrag-gaudi-backend-server: + image: ${REGISTRY:-opea}/graphrag:${TAG:-latest} + container_name: graphrag-gaudi-backend-server + depends_on: + - neo4j-apoc + - tei-embedding-service + - retriever-neo4j-llamaindex + - tgi-gaudi-service + ports: + - "8888:8888" + environment: + - no_proxy=${no_proxy} + - https_proxy=${https_proxy} + - http_proxy=${http_proxy} + - MEGA_SERVICE_HOST_IP=graphrag-gaudi-backend-server + - RETRIEVER_SERVICE_HOST_IP=retriever-neo4j-llamaindex + - RETRIEVER_SERVICE_PORT=6009 + - RETRIEVER_SERVICE_PORT=${RETRIEVER_SERVICE_PORT:-80} + - LLM_SERVER_HOST_IP=tgi-gaudi-service + - LLM_SERVER_PORT=${LLM_SERVER_PORT:-80} + - LOGFLAG=${LOGFLAG} + ipc: host + restart: always + chatqna-gaudi-ui-server: + image: ${REGISTRY:-opea}/chatqna-ui:${TAG:-latest} + container_name: chatqna-gaudi-ui-server + depends_on: + - graphrag-gaudi-backend-server + ports: + - "5173:5173" + environment: + - no_proxy=${no_proxy} + - https_proxy=${https_proxy} + - http_proxy=${http_proxy} + ipc: host + restart: always + chatqna-gaudi-nginx-server: + image: ${REGISTRY:-opea}/nginx:${TAG:-latest} + container_name: chatqna-gaudi-nginx-server + depends_on: + - graphrag-gaudi-backend-server + - chatqna-gaudi-ui-server + ports: + - "${NGINX_PORT:-80}:80" + environment: + - no_proxy=${no_proxy} + - https_proxy=${https_proxy} + - http_proxy=${http_proxy} + - FRONTEND_SERVICE_IP=chatqna-gaudi-ui-server + - FRONTEND_SERVICE_PORT=5173 + - BACKEND_SERVICE_NAME=graphrag + - BACKEND_SERVICE_IP=graphrag-gaudi-backend-server + - BACKEND_SERVICE_PORT=8888 + - DATAPREP_SERVICE_IP=dataprep-neo4j-llamaindex + - DATAPREP_SERVICE_PORT=6004 + ipc: host + restart: always +networks: + default: + driver: bridge diff --git a/GraphRAG/docker_compose/intel/hpu/gaudi/set_env.sh b/GraphRAG/docker_compose/intel/hpu/gaudi/set_env.sh new file mode 100644 index 0000000000..1d4e8d7d5c --- /dev/null +++ b/GraphRAG/docker_compose/intel/hpu/gaudi/set_env.sh @@ -0,0 +1,20 @@ +#!/usr/bin/env bash + +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Remember to set your private variables mentioned in README + +# host_ip, OPENAI_API_KEY, HUGGINGFACEHUB_API_TOKEN, proxies... + +export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5" +export OPENAI_EMBEDDING_MODEL="text-embedding-3-small" +export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct" +export OPENAI_LLM_MODEL="gpt-4o" +export TEI_EMBEDDING_ENDPOINT="http://${host_ip}:6006" +export TGI_LLM_ENDPOINT="http://${host_ip}:6005" +export NEO4J_URL="bolt://${host_ip}:7687" +export NEO4J_USERNAME=neo4j +export DATAPREP_SERVICE_ENDPOINT="http://${host_ip}:6004/v1/dataprep" +export LOGFLAG=True +export RETRIEVER_SERVICE_PORT=6009 diff --git a/GraphRAG/docker_image_build/build.yaml b/GraphRAG/docker_image_build/build.yaml new file mode 100644 index 0000000000..3187e7cee9 --- /dev/null +++ b/GraphRAG/docker_image_build/build.yaml @@ -0,0 +1,49 @@ +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +services: + graphrag: + build: + args: + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + no_proxy: ${no_proxy} + context: ../ + dockerfile: ./Dockerfile + image: ${REGISTRY:-opea}/graphrag:${TAG:-latest} + retriever-neo4j-llamaindex: + build: + args: + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + no_proxy: ${no_proxy} + context: GenAIComps + dockerfile: comps/retrievers/neo4j/llama_index/Dockerfile + image: ${REGISTRY:-opea}/retriever-neo4j-llamaindex:${TAG:-latest} + dataprep-neo4j-llamaindex: + build: + args: + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + no_proxy: ${no_proxy} + context: GenAIComps + dockerfile: comps/dataprep/neo4j/llama_index/Dockerfile + image: ${REGISTRY:-opea}/dataprep-neo4j-llamaindex:${TAG:-latest} + chatqna-gaudi-nginx-server: + build: + args: + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + no_proxy: ${no_proxy} + context: GenAIComps + dockerfile: comps/nginx/Dockerfile + image: ${REGISTRY:-opea}/nginx:${TAG:-latest} + chatqna-gaudi-ui-server: + build: + args: + http_proxy: ${http_proxy} + https_proxy: ${https_proxy} + no_proxy: ${no_proxy} + context: ../ui + dockerfile: ./docker/Dockerfile + image: ${REGISTRY:-opea}/chatqna-ui:${TAG:-latest} diff --git a/GraphRAG/graphrag.py b/GraphRAG/graphrag.py new file mode 100644 index 0000000000..022a3aad31 --- /dev/null +++ b/GraphRAG/graphrag.py @@ -0,0 +1,150 @@ +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +import argparse +import json +import os +import re + +from comps import GraphragGateway, MicroService, ServiceOrchestrator, ServiceType +from langchain_core.prompts import PromptTemplate + + +class ChatTemplate: + @staticmethod + def generate_rag_prompt(question, documents): + context_str = "\n".join(documents) + if context_str and len(re.findall("[\u4E00-\u9FFF]", context_str)) / len(context_str) >= 0.3: + # chinese context + template = """ +### 你将扮演一个乐于助人、尊重他人并诚实的助手,你的目标是帮助用户解答问题。有效地利用来自本地知识库的搜索结果。确保你的回答中只包含相关信息。如果你不确定问题的答案,请避免分享不准确的信息。 +### 搜索结果:{context} +### 问题:{question} +### 回答: +""" + else: + template = """ +### You are a helpful, respectful and honest assistant to help the user with questions. \ +Please combine the following intermediate answers into a final, conscise and coherent response. \ +refer to the search results obtained from the local knowledge base. \ +If you don't know the answer to a question, please don't share false information. \n +### Intermediate answers: {context} \n +### Question: {question} \n +### Answer: +""" + return template.format(context=context_str, question=question) + + +MEGA_SERVICE_HOST_IP = os.getenv("MEGA_SERVICE_HOST_IP", "0.0.0.0") +MEGA_SERVICE_PORT = int(os.getenv("MEGA_SERVICE_PORT", 8888)) +RETRIEVER_SERVICE_HOST_IP = os.getenv("RETRIEVER_SERVICE_HOST_IP", "0.0.0.0") +RETRIEVER_SERVICE_PORT = int(os.getenv("RETRIEVER_SERVICE_PORT", 7000)) +LLM_SERVER_HOST_IP = os.getenv("LLM_SERVER_HOST_IP", "0.0.0.0") +LLM_SERVER_PORT = int(os.getenv("LLM_SERVER_PORT", 80)) + + +def align_inputs(self, inputs, cur_node, runtime_graph, llm_parameters_dict, **kwargs): + if self.services[cur_node].service_type == ServiceType.RETRIEVER: + print("make no changes for retriever inputs. AlreadyCheckCompletionRequest") + elif self.services[cur_node].service_type == ServiceType.LLM: + # convert TGI/vLLM to unified OpenAI /v1/chat/completions format + next_inputs = {} + next_inputs["model"] = "tgi" # specifically clarify the fake model to make the format unified + next_inputs["messages"] = [{"role": "user", "content": inputs["inputs"]}] + next_inputs["max_tokens"] = llm_parameters_dict["max_tokens"] + next_inputs["top_p"] = llm_parameters_dict["top_p"] + next_inputs["stream"] = inputs["streaming"] + next_inputs["frequency_penalty"] = inputs["frequency_penalty"] + # next_inputs["presence_penalty"] = inputs["presence_penalty"] + # next_inputs["repetition_penalty"] = inputs["repetition_penalty"] + next_inputs["temperature"] = inputs["temperature"] + inputs = next_inputs + print("inputs after align:\n", inputs) + return inputs + + +def align_outputs(self, data, cur_node, inputs, runtime_graph, llm_parameters_dict, **kwargs): + next_data = {} + if self.services[cur_node].service_type == ServiceType.RETRIEVER: + docs = [doc["text"] for doc in data["retrieved_docs"]] + # handle template + # if user provides template, then format the prompt with it + # otherwise, use the default template + prompt = inputs.messages[0]["content"] + chat_template = llm_parameters_dict["chat_template"] + if chat_template: + prompt_template = PromptTemplate.from_template(chat_template) + input_variables = prompt_template.input_variables + if sorted(input_variables) == ["context", "question"]: + prompt = prompt_template.format(question=prompt, context="\n".join(docs)) + elif input_variables == ["question"]: + prompt = prompt_template.format(question=prompt) + else: + print(f"{prompt_template} not used, we only support 2 input variables ['question', 'context']") + prompt = ChatTemplate.generate_rag_prompt(prompt, docs) + else: + print("no rerank no chat template") + prompt = ChatTemplate.generate_rag_prompt(prompt, docs) + + next_data["inputs"] = prompt + else: + next_data = data + + return next_data + + +def align_generator(self, gen, **kwargs): + # openai reaponse format + # b'data:{"id":"","object":"text_completion","created":1725530204,"model":"meta-llama/Meta-Llama-3-8B-Instruct","system_fingerprint":"2.0.1-native","choices":[{"index":0,"delta":{"role":"assistant","content":"?"},"logprobs":null,"finish_reason":null}]}\n\n' + print("generator in align generator:\n", gen) + for line in gen: + line = line.decode("utf-8") + start = line.find("{") + end = line.rfind("}") + 1 + + json_str = line[start:end] + try: + # sometimes yield empty chunk, do a fallback here + json_data = json.loads(json_str) + if json_data["choices"][0]["finish_reason"] != "eos_token": + yield f"data: {repr(json_data['choices'][0]['delta']['content'].encode('utf-8'))}\n\n" + except Exception as e: + yield f"data: {repr(json_str.encode('utf-8'))}\n\n" + yield "data: [DONE]\n\n" + + +class GraphRAGService: + def __init__(self, host="0.0.0.0", port=8000): + self.host = host + self.port = port + ServiceOrchestrator.align_inputs = align_inputs + ServiceOrchestrator.align_outputs = align_outputs + ServiceOrchestrator.align_generator = align_generator + self.megaservice = ServiceOrchestrator() + + def add_remote_service(self): + retriever = MicroService( + name="retriever", + host=RETRIEVER_SERVICE_HOST_IP, + port=RETRIEVER_SERVICE_PORT, + endpoint="/v1/retrieval", + use_remote_service=True, + service_type=ServiceType.RETRIEVER, + ) + + llm = MicroService( + name="llm", + host=LLM_SERVER_HOST_IP, + port=LLM_SERVER_PORT, + endpoint="/v1/chat/completions", + use_remote_service=True, + service_type=ServiceType.LLM, + ) + self.megaservice.add(retriever).add(llm) + self.megaservice.flow_to(retriever, llm) + self.gateway = GraphragGateway(megaservice=self.megaservice, host="0.0.0.0", port=self.port) + + +if __name__ == "__main__": + graphrag = GraphRAGService(host=MEGA_SERVICE_HOST_IP, port=MEGA_SERVICE_PORT) + graphrag.add_remote_service() diff --git a/GraphRAG/tests/test_compose.sh b/GraphRAG/tests/test_compose.sh new file mode 100755 index 0000000000..0fc2278300 --- /dev/null +++ b/GraphRAG/tests/test_compose.sh @@ -0,0 +1,207 @@ +#!/bin/bash +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +set -e +IMAGE_REPO=${IMAGE_REPO:-"opea"} +IMAGE_TAG=${IMAGE_TAG:-"latest"} +echo "REGISTRY=IMAGE_REPO=${IMAGE_REPO}" +echo "TAG=IMAGE_TAG=${IMAGE_TAG}" +export REGISTRY=${IMAGE_REPO} +export TAG=${IMAGE_TAG} + +WORKPATH=$(dirname "$PWD") +WORKPATH=/home/rbrugaro/GenAIExamples/GraphRAG +LOG_PATH="$WORKPATH/tests" +ip_address=$(hostname -I | awk '{print $1}') + +function build_docker_images() { + cd $WORKPATH/docker_image_build + git clone https://github.com/opea-project/GenAIComps.git && cd GenAIComps && git checkout "${opea_branch:-"main"}" && cd ../ + + echo "Build all the images with --no-cache, check docker_image_build.log for details..." + service_list="graphrag dataprep-neo4j-llamaindex retriever-neo4j-llamaindex chatqna-gaudi-ui-server chatqna-gaudi-nginx-server" + docker compose -f build.yaml build ${service_list} --no-cache > ${LOG_PATH}/docker_image_build.log + + docker pull ghcr.io/huggingface/tgi-gaudi:2.0.5 + docker pull ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 + docker pull neo4j:latest + docker images && sleep 1s +} + +function start_services() { + cd $WORKPATH/docker_compose/intel/hpu/gaudi + export EMBEDDING_MODEL_ID="BAAI/bge-base-en-v1.5" + export LLM_MODEL_ID="meta-llama/Meta-Llama-3-8B-Instruct" + export HUGGINGFACEHUB_API_TOKEN=${HUGGINGFACEHUB_API_TOKEN} + + # Start Docker Containers + docker compose -f compose.yaml up -d > ${LOG_PATH}/start_services_with_compose.log + + n=0 + until [[ "$n" -ge 100 ]]; do + docker logs tgi-gaudi-server > ${LOG_PATH}/tgi_service_start.log + if grep -q Connected ${LOG_PATH}/tgi_service_start.log; then + break + fi + sleep 5s + n=$((n+1)) + done +} + +function validate_service() { + local URL="$1" + local EXPECTED_RESULT="$2" + local SERVICE_NAME="$3" + local DOCKER_NAME="$4" + local INPUT_DATA="$5" + + if [[ $SERVICE_NAME == *"extract_graph_neo4j"* ]]; then + cd $LOG_PATH + HTTP_RESPONSE=$(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -F 'files=@./dataprep_file.txt' -H 'Content-Type: multipart/form-data' "$URL") + elif [[ $SERVICE_NAME == *"neo4j-apoc"* ]]; then + HTTP_RESPONSE=$(curl --silent --write-out "HTTPSTATUS:%{http_code}" "$URL") + else + HTTP_RESPONSE=$(curl --silent --write-out "HTTPSTATUS:%{http_code}" -X POST -d "$INPUT_DATA" -H 'Content-Type: application/json' "$URL") + fi + HTTP_STATUS=$(echo $HTTP_RESPONSE | tr -d '\n' | sed -e 's/.*HTTPSTATUS://') + RESPONSE_BODY=$(echo $HTTP_RESPONSE | sed -e 's/HTTPSTATUS\:.*//g') + + docker logs ${DOCKER_NAME} >> ${LOG_PATH}/${SERVICE_NAME}.log + + # check response status + if [ "$HTTP_STATUS" -ne "200" ]; then + echo "[ $SERVICE_NAME ] HTTP status is not 200. Received status was $HTTP_STATUS" + exit 1 + else + echo "[ $SERVICE_NAME ] HTTP status is 200. Checking content..." + fi + # check response body + if [[ "$SERVICE_NAME" == "neo4j-apoc" ]]; then + echo "[ $SERVICE_NAME ] Skipping content check for neo4j-apoc." + else + if [[ "$RESPONSE_BODY" != *"$EXPECTED_RESULT"* ]]; then + echo "[ $SERVICE_NAME ] Content does not match the expected result: $RESPONSE_BODY" + exit 1 + else + echo "[ $SERVICE_NAME ] Content is as expected." + fi + fi + + sleep 5s +} + +function validate_microservices() { + # Check if the microservices are running correctly. + + # validate neo4j-apoc + validate_service \ + "${ip_address}:7474" \ + "200 OK" \ + "neo4j-apoc" \ + "neo4j-apoc" \ + "" + + # tei for embedding service + validate_service \ + "${ip_address}:6006/embed" \ + "[[" \ + "tei-embedding-service" \ + "tei-embedding-server" \ + '{"inputs":"What is Deep Learning?"}' + + sleep 1m # retrieval can't curl as expected, try to wait for more time + + # test /v1/dataprep graph extraction + echo "Like many companies in the O&G sector, the stock of Chevron (NYSE:CVX) has declined about 10% over the past 90-days despite the fact that Q2 consensus earnings estimates have risen sharply (~25%) during that same time frame. Over the years, Chevron has kept a very strong balance sheet. FirstEnergy (NYSE:FE – Get Rating) posted its earnings results on Tuesday. The utilities provider reported $0.53 earnings per share for the quarter, topping the consensus estimate of $0.52 by $0.01, RTT News reports. FirstEnergy had a net margin of 10.85% and a return on equity of 17.17%. The Dáil was almost suspended on Thursday afternoon after Sinn Féin TD John Brady walked across the chamber and placed an on-call pager in front of the Minister for Housing Darragh O’Brien during a debate on retained firefighters. Mr O’Brien said Mr Brady had taken part in an act of theatre that was obviously choreographed.Around 2,000 retained firefighters around the country staged a second day of industrial action on Tuesday and are due to start all out-strike action from next Tuesday. The mostly part-time workers, who keep the services going outside of Ireland’s larger urban centres, are taking industrial action in a dispute over pay and working conditions. Speaking in the Dáil, Sinn Féin deputy leader Pearse Doherty said firefighters had marched on Leinster House today and were very angry at the fact the Government will not intervene. Reintroduction of tax relief on mortgages needs to be considered, O’Brien says. Martin withdraws comment after saying People Before Profit would ‘put the jackboot on people’ Taoiseach ‘propagated fears’ farmers forced to rewet land due to nature restoration law – Cairns An intervention is required now. I’m asking you to make an improved offer in relation to pay for retained firefighters, Mr Doherty told the housing minister.I’m also asking you, and challenging you, to go outside after this Order of Business and meet with the firefighters because they are just fed up to the hilt in relation to what you said.Some of them have handed in their pagers to members of the Opposition and have challenged you to wear the pager for the next number of weeks, put up with an €8,600 retainer and not leave your community for the two and a half kilometres and see how you can stand over those type of pay and conditions. At this point, Mr Brady got up from his seat, walked across the chamber and placed the pager on the desk in front of Mr O’Brien. Ceann Comhairle Seán Ó Fearghaíl said the Sinn Féin TD was completely out of order and told him not to carry out a charade in this House, adding it was absolutely outrageous behaviour and not to be encouraged.Mr O’Brien said Mr Brady had engaged in an act of theatre here today which was obviously choreographed and was then interrupted with shouts from the Opposition benches. Mr Ó Fearghaíl said he would suspend the House if this racket continues.Mr O’Brien later said he said he was confident the dispute could be resolved and he had immense regard for firefighters. The minister said he would encourage the unions to re-engage with the State’s industrial relations process while also accusing Sinn Féin of using the issue for their own political gain." > $LOG_PATH/dataprep_file.txt + validate_service \ + "http://${ip_address}:6004/v1/dataprep" \ + "Data preparation succeeded" \ + "extract_graph_neo4j" \ + "dataprep-neo4j-server" + + # retrieval microservice + validate_service \ + "${ip_address}:6009/v1/retrieval" \ + "Retrieval of answers from community summaries successful" \ + "retriever_community_answers_neo4j" \ + "retriever-neo4j-server" \ + "{\"model\": \"gpt-4o-mini\",\"messages\": [{\"role\": \"user\",\"content\": \"Who is John Brady and has he had any confrontations?\"}]}" + + # tgi for llm service + validate_service \ + "${ip_address}:6005/generate" \ + "generated_text" \ + "tgi-gaudi-service" \ + "tgi-gaudi-server" \ + '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' +} + +function validate_megaservice() { + # Curl the Mega Service + validate_service \ + "${ip_address}:8888/v1/graphrag" \ + "data: " \ + "graphrag-megaservice" \ + "graphrag-gaudi-backend-server" \ + "{\"model\": \"gpt-4o-mini\",\"messages\": [{\"role\": \"user\",\"content\": \"Who is John Brady and has he had any confrontations?\"}]}" + +} + +function validate_frontend() { + cd $WORKPATH/ui/svelte + local conda_env_name="OPEA_e2e" + export PATH=${HOME}/miniforge3/bin/:$PATH + if conda info --envs | grep -q "$conda_env_name"; then + echo "$conda_env_name exist!" + else + conda create -n ${conda_env_name} python=3.12 -y + fi + source activate ${conda_env_name} + + sed -i "s/localhost/$ip_address/g" playwright.config.ts + + conda install -c conda-forge nodejs -y + npm install && npm ci && npx playwright install --with-deps + node -v && npm -v && pip list + + exit_status=0 + npx playwright test || exit_status=$? + + if [ $exit_status -ne 0 ]; then + echo "[TEST INFO]: ---------frontend test failed---------" + exit $exit_status + else + echo "[TEST INFO]: ---------frontend test passed---------" + fi +} + +function stop_docker() { + cd $WORKPATH/docker_compose/intel/hpu/gaudi + docker compose -f compose.yaml stop && docker compose -f compose.yaml rm -f +} + +function main() { + + stop_docker + if [[ "$IMAGE_REPO" == "opea" ]]; then build_docker_images; fi + start_time=$(date +%s) + start_services + end_time=$(date +%s) + duration=$((end_time-start_time)) + echo "Mega service start duration is $duration s" + + if [ "${mode}" == "perf" ]; then + python3 $WORKPATH/tests/chatqna_benchmark.py + elif [ "${mode}" == "" ]; then + validate_microservices + validate_megaservice + validate_frontend + fi + + stop_docker + echo y | docker system prune + +} + +main diff --git a/GraphRAG/ui/docker/Dockerfile b/GraphRAG/ui/docker/Dockerfile new file mode 100644 index 0000000000..ef034e67cc --- /dev/null +++ b/GraphRAG/ui/docker/Dockerfile @@ -0,0 +1,26 @@ +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Use node 20.11.1 as the base image +FROM node:20.11.1 + +# Update package manager and install Git +RUN apt-get update -y && apt-get install -y git --no-install-recommends --fix-missing + +# Copy the front-end code repository +COPY svelte /home/user/svelte + +# Set the working directory +WORKDIR /home/user/svelte + +# Install front-end dependencies +RUN npm install + +# Build the front-end application +RUN npm run build + +# Expose the port of the front-end application +EXPOSE 5173 + +# Run the front-end application in preview mode +CMD ["npm", "run", "preview", "--", "--port", "5173", "--host", "0.0.0.0"] \ No newline at end of file diff --git a/GraphRAG/ui/docker/Dockerfile.react b/GraphRAG/ui/docker/Dockerfile.react new file mode 100644 index 0000000000..9c4eff8425 --- /dev/null +++ b/GraphRAG/ui/docker/Dockerfile.react @@ -0,0 +1,19 @@ +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +# Use node 20.11.1 as the base image +FROM node:20.11.1 as vite-app + +COPY react /usr/app/react +WORKDIR /usr/app/react + +RUN ["npm", "install"] +RUN ["npm", "run", "build"] + +FROM nginx:alpine + +COPY --from=vite-app /usr/app/react/dist /usr/share/nginx/html +COPY ./react/env.sh /docker-entrypoint.d/env.sh + +COPY ./react/nginx.conf /etc/nginx/conf.d/default.conf +RUN chmod +x /docker-entrypoint.d/env.sh \ No newline at end of file diff --git a/GraphRAG/ui/react/.env b/GraphRAG/ui/react/.env new file mode 100644 index 0000000000..e5d52f4213 --- /dev/null +++ b/GraphRAG/ui/react/.env @@ -0,0 +1,2 @@ +VITE_BACKEND_SERVICE_ENDPOINT=http://backend_address:8888/v1/chatqna +VITE_DATA_PREP_SERVICE_URL=http://backend_address:6007/v1/dataprep \ No newline at end of file diff --git a/GraphRAG/ui/react/.env.production b/GraphRAG/ui/react/.env.production new file mode 100644 index 0000000000..a46e1e3850 --- /dev/null +++ b/GraphRAG/ui/react/.env.production @@ -0,0 +1,2 @@ +VITE_BACKEND_SERVICE_ENDPOINT=APP_BACKEND_SERVICE_ENDPOINT +VITE_DATA_PREP_SERVICE_URL=APP_DATA_PREP_SERVICE_URL \ No newline at end of file diff --git a/GraphRAG/ui/react/.eslintrc.cjs b/GraphRAG/ui/react/.eslintrc.cjs new file mode 100644 index 0000000000..78174f6836 --- /dev/null +++ b/GraphRAG/ui/react/.eslintrc.cjs @@ -0,0 +1,11 @@ +module.exports = { + root: true, + env: { browser: true, es2020: true }, + extends: ["eslint:recommended", "plugin:@typescript-eslint/recommended", "plugin:react-hooks/recommended"], + ignorePatterns: ["dist", ".eslintrc.cjs"], + parser: "@typescript-eslint/parser", + plugins: ["react-refresh"], + rules: { + "react-refresh/only-export-components": ["warn", { allowConstantExport: true }], + }, +}; diff --git a/GraphRAG/ui/react/.gitignore b/GraphRAG/ui/react/.gitignore new file mode 100644 index 0000000000..a547bf36d8 --- /dev/null +++ b/GraphRAG/ui/react/.gitignore @@ -0,0 +1,24 @@ +# Logs +logs +*.log +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* +lerna-debug.log* + +node_modules +dist +dist-ssr +*.local + +# Editor directories and files +.vscode/* +!.vscode/extensions.json +.idea +.DS_Store +*.suo +*.ntvs* +*.njsproj +*.sln +*.sw? diff --git a/GraphRAG/ui/react/README.md b/GraphRAG/ui/react/README.md new file mode 100644 index 0000000000..3477828eaa --- /dev/null +++ b/GraphRAG/ui/react/README.md @@ -0,0 +1,32 @@ +# ChatQnA Conversational UI + +## 📸 Project Screenshots + +![project-screenshot](../../assets/img/conversation_ui_init.png) +![project-screenshot](../../assets/img/conversation_ui_response.png) +![project-screenshot](../../assets/img/conversation_ui_upload.png) + +## 🧐 Features + +Here're some of the project's features: + +- Start a Text Chat:Initiate a text chat with the ability to input written conversations, where the dialogue content can also be customized based on uploaded files. +- Context Awareness: The AI assistant maintains the context of the conversation, understanding references to previous statements or questions. This allows for more natural and coherent exchanges. +- Upload File: The choice between uploading locally or copying a remote link. Chat according to uploaded knowledge base. +- Clear: Clear the record of the current dialog box without retaining the contents of the dialog box. +- Chat history: Historical chat records can still be retained after refreshing, making it easier for users to view the context. +- Conversational Chat : The application maintains a history of the conversation, allowing users to review previous messages and the AI to refer back to earlier points in the dialogue when necessary. + +## 🛠️ Get it Running + +1. Clone the repo. + +2. cd command to the current folder. + +3. Modify the required .env variables. + ``` + DOC_BASE_URL = '' + ``` +4. Execute `npm install` to install the corresponding dependencies. + +5. Execute `npm run dev` in both environments diff --git a/GraphRAG/ui/react/env.sh b/GraphRAG/ui/react/env.sh new file mode 100644 index 0000000000..ce1372ea68 --- /dev/null +++ b/GraphRAG/ui/react/env.sh @@ -0,0 +1,15 @@ +#!/bin/sh +# Copyright (C) 2024 Intel Corporation +# SPDX-License-Identifier: Apache-2.0 + +for i in $(env | grep APP_) #// Make sure to use the prefix MY_APP_ if you have any other prefix in env.production file variable name replace it with MY_APP_ +do + key=$(echo $i | cut -d '=' -f 1) + value=$(echo $i | cut -d '=' -f 2-) + echo $key=$value + # sed All files + # find /usr/share/nginx/html -type f -exec sed -i "s|${key}|${value}|g" '{}' + + + # sed JS and CSS only + find /usr/share/nginx/html -type f \( -name '*.js' -o -name '*.css' \) -exec sed -i "s|${key}|${value}|g" '{}' + +done diff --git a/GraphRAG/ui/react/index.html b/GraphRAG/ui/react/index.html new file mode 100644 index 0000000000..fbe87e0fd5 --- /dev/null +++ b/GraphRAG/ui/react/index.html @@ -0,0 +1,18 @@ + + + + + + + + + Conversations UI + + +

+ + + diff --git a/GraphRAG/ui/react/nginx.conf b/GraphRAG/ui/react/nginx.conf new file mode 100644 index 0000000000..00433fcda7 --- /dev/null +++ b/GraphRAG/ui/react/nginx.conf @@ -0,0 +1,20 @@ +server { + listen 80; + + gzip on; + gzip_proxied any; + gzip_comp_level 6; + gzip_buffers 16 8k; + gzip_http_version 1.1; + gzip_types font/woff2 text/css application/javascript application/json application/font-woff application/font-tff image/gif image/png image/svg+xml application/octet-stream; + + location / { + root /usr/share/nginx/html; + index index.html index.htm; + try_files $uri $uri/ /index.html =404; + + location ~* \.(gif|jpe?g|png|webp|ico|svg|css|js|mp4|woff2)$ { + expires 1d; + } + } +} \ No newline at end of file diff --git a/GraphRAG/ui/react/package.json b/GraphRAG/ui/react/package.json new file mode 100644 index 0000000000..3760ed909b --- /dev/null +++ b/GraphRAG/ui/react/package.json @@ -0,0 +1,47 @@ +{ + "name": "ui", + "private": true, + "version": "0.0.0", + "type": "module", + "scripts": { + "dev": "vite", + "build": "tsc && vite build", + "lint": "eslint . --ext ts,tsx --report-unused-disable-directives --max-warnings 0", + "preview": "vite preview", + "test": "vitest" + }, + "dependencies": { + "@mantine/core": "^7.10.0", + "@mantine/hooks": "^7.10.0", + "@mantine/notifications": "^7.10.2", + "@microsoft/fetch-event-source": "^2.0.1", + "@reduxjs/toolkit": "^2.2.5", + "@tabler/icons-react": "^3.5.0", + "axios": "^1.7.2", + "luxon": "^3.4.4", + "react": "^18.2.0", + "react-dom": "^18.2.0", + "react-redux": "^9.1.2" + }, + "devDependencies": { + "@testing-library/react": "^16.0.0", + "@types/luxon": "^3.4.2", + "@types/node": "^20.12.12", + "@types/react": "^18.2.66", + "@types/react-dom": "^18.2.22", + "@typescript-eslint/eslint-plugin": "^7.2.0", + "@typescript-eslint/parser": "^7.2.0", + "@vitejs/plugin-react": "^4.2.1", + "eslint": "^8.57.0", + "eslint-plugin-react-hooks": "^4.6.0", + "eslint-plugin-react-refresh": "^0.4.6", + "jsdom": "^24.1.0", + "postcss": "^8.4.38", + "postcss-preset-mantine": "^1.15.0", + "postcss-simple-vars": "^7.0.1", + "sass": "1.64.2", + "typescript": "^5.2.2", + "vite": "^5.2.13", + "vitest": "^1.6.0" + } +} diff --git a/GraphRAG/ui/react/postcss.config.cjs b/GraphRAG/ui/react/postcss.config.cjs new file mode 100644 index 0000000000..e817f567be --- /dev/null +++ b/GraphRAG/ui/react/postcss.config.cjs @@ -0,0 +1,14 @@ +module.exports = { + plugins: { + "postcss-preset-mantine": {}, + "postcss-simple-vars": { + variables: { + "mantine-breakpoint-xs": "36em", + "mantine-breakpoint-sm": "48em", + "mantine-breakpoint-md": "62em", + "mantine-breakpoint-lg": "75em", + "mantine-breakpoint-xl": "88em", + }, + }, + }, +}; diff --git a/GraphRAG/ui/react/public/vite.svg b/GraphRAG/ui/react/public/vite.svg new file mode 100644 index 0000000000..e7b8dfb1b2 --- /dev/null +++ b/GraphRAG/ui/react/public/vite.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/GraphRAG/ui/react/src/App.scss b/GraphRAG/ui/react/src/App.scss new file mode 100644 index 0000000000..187764a179 --- /dev/null +++ b/GraphRAG/ui/react/src/App.scss @@ -0,0 +1,42 @@ +// Copyright (C) 2024 Intel Corporation +// SPDX-License-Identifier: Apache-2.0 + +@import "./styles/styles"; + +.root { + @include flex(row, nowrap, flex-start, flex-start); +} + +.layout-wrapper { + @include absolutes; + + display: grid; + + width: 100%; + height: 100%; + + grid-template-columns: 80px auto; + grid-template-rows: 1fr; +} + +/* ===== Scrollbar CSS ===== */ +/* Firefox */ +* { + scrollbar-width: thin; + scrollbar-color: #d6d6d6 #ffffff; +} + +/* Chrome, Edge, and Safari */ +*::-webkit-scrollbar { + width: 8px; +} + +*::-webkit-scrollbar-track { + background: #ffffff; +} + +*::-webkit-scrollbar-thumb { + background-color: #d6d6d6; + border-radius: 16px; + border: 4px double #dedede; +} diff --git a/GraphRAG/ui/react/src/App.tsx b/GraphRAG/ui/react/src/App.tsx new file mode 100644 index 0000000000..4be4fa5bb5 --- /dev/null +++ b/GraphRAG/ui/react/src/App.tsx @@ -0,0 +1,34 @@ +// Copyright (C) 2024 Intel Corporation +// SPDX-License-Identifier: Apache-2.0 + +import "./App.scss" +import { MantineProvider } from "@mantine/core" +import '@mantine/notifications/styles.css'; +import { SideNavbar, SidebarNavList } from "./components/sidebar/sidebar" +import { IconMessages } from "@tabler/icons-react" +import UserInfoModal from "./components/UserInfoModal/UserInfoModal" +import Conversation from "./components/Conversation/Conversation" +import { Notifications } from '@mantine/notifications'; + +const title = "Chat QnA" +const navList: SidebarNavList = [ + { icon: IconMessages, label: title } +] + +function App() { + + return ( + + + +
+ +
+ +
+
+
+ ) +} + +export default App diff --git a/GraphRAG/ui/react/src/__tests__/util.test.ts b/GraphRAG/ui/react/src/__tests__/util.test.ts new file mode 100644 index 0000000000..e67ba2c86a --- /dev/null +++ b/GraphRAG/ui/react/src/__tests__/util.test.ts @@ -0,0 +1,14 @@ +// Copyright (C) 2024 Intel Corporation +// SPDX-License-Identifier: Apache-2.0 + +import { describe, expect, test } from "vitest"; +import { getCurrentTimeStamp, uuidv4 } from "../common/util"; + +describe("unit tests", () => { + test("check UUID is of length 36", () => { + expect(uuidv4()).toHaveLength(36); + }); + test("check TimeStamp generated is of unix", () => { + expect(getCurrentTimeStamp()).toBe(Math.floor(Date.now() / 1000)); + }); +}); diff --git a/GraphRAG/ui/react/src/assets/opea-icon-black.svg b/GraphRAG/ui/react/src/assets/opea-icon-black.svg new file mode 100644 index 0000000000..5c96dc7622 --- /dev/null +++ b/GraphRAG/ui/react/src/assets/opea-icon-black.svg @@ -0,0 +1,39 @@ + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/GraphRAG/ui/react/src/assets/opea-icon-color.svg b/GraphRAG/ui/react/src/assets/opea-icon-color.svg new file mode 100644 index 0000000000..790151171e --- /dev/null +++ b/GraphRAG/ui/react/src/assets/opea-icon-color.svg @@ -0,0 +1,40 @@ + + + + + + + + + + + + + + + + + + + + + + + + + diff --git a/GraphRAG/ui/react/src/assets/react.svg b/GraphRAG/ui/react/src/assets/react.svg new file mode 100644 index 0000000000..6c87de9bb3 --- /dev/null +++ b/GraphRAG/ui/react/src/assets/react.svg @@ -0,0 +1 @@ + \ No newline at end of file diff --git a/GraphRAG/ui/react/src/common/client.ts b/GraphRAG/ui/react/src/common/client.ts new file mode 100644 index 0000000000..7512f73e33 --- /dev/null +++ b/GraphRAG/ui/react/src/common/client.ts @@ -0,0 +1,8 @@ +// Copyright (C) 2024 Intel Corporation +// SPDX-License-Identifier: Apache-2.0 + +import axios from "axios"; + +//add iterceptors to add any request headers + +export default axios; diff --git a/GraphRAG/ui/react/src/common/util.ts b/GraphRAG/ui/react/src/common/util.ts new file mode 100644 index 0000000000..df65b2d8e0 --- /dev/null +++ b/GraphRAG/ui/react/src/common/util.ts @@ -0,0 +1,12 @@ +// Copyright (C) 2024 Intel Corporation +// SPDX-License-Identifier: Apache-2.0 + +export const getCurrentTimeStamp = () => { + return Math.floor(Date.now() / 1000); +}; + +export const uuidv4 = () => { + return "10000000-1000-4000-8000-100000000000".replace(/[018]/g, (c) => + (+c ^ (crypto.getRandomValues(new Uint8Array(1))[0] & (15 >> (+c / 4)))).toString(16), + ); +}; diff --git a/GraphRAG/ui/react/src/components/Conversation/Conversation.tsx b/GraphRAG/ui/react/src/components/Conversation/Conversation.tsx new file mode 100644 index 0000000000..02736d8bd6 --- /dev/null +++ b/GraphRAG/ui/react/src/components/Conversation/Conversation.tsx @@ -0,0 +1,156 @@ +// Copyright (C) 2024 Intel Corporation +// SPDX-License-Identifier: Apache-2.0 + +import { KeyboardEventHandler, SyntheticEvent, useEffect, useRef, useState } from 'react' +import styleClasses from "./conversation.module.scss" +import { ActionIcon, Group, Textarea, Title, rem } from '@mantine/core' +import { IconArrowRight, IconFilePlus, IconMessagePlus } from '@tabler/icons-react' +import { conversationSelector, doConversation, newConversation } from '../../redux/Conversation/ConversationSlice' +import { ConversationMessage } from '../Message/conversationMessage' +import { useAppDispatch, useAppSelector } from '../../redux/store' +import { Message, MessageRole } from '../../redux/Conversation/Conversation' +import { getCurrentTimeStamp } from '../../common/util' +import { useDisclosure } from '@mantine/hooks' +import DataSource from './DataSource' +import { ConversationSideBar } from './ConversationSideBar' + +type ConversationProps = { + title:string +} + +const Conversation = ({ title }: ConversationProps) => { + + const [prompt, setPrompt] = useState("") + const promptInputRef = useRef(null) + const [fileUploadOpened, { open: openFileUpload, close: closeFileUpload }] = useDisclosure(false); + + const { conversations, onGoingResult, selectedConversationId } = useAppSelector(conversationSelector) + const dispatch = useAppDispatch(); + const selectedConversation = conversations.find(x=>x.conversationId===selectedConversationId) + + const scrollViewport = useRef(null) + + const toSend = "Enter" + + const systemPrompt: Partial = { + role: MessageRole.System, + content: "You are helpful assistant", + }; + + + const handleSubmit = () => { + + const userPrompt: Message = { + role: MessageRole.User, + content: prompt, + time: getCurrentTimeStamp() + }; + let messages: Partial[] = []; + if(selectedConversation){ + messages = selectedConversation.Messages.map(message => { + return {role:message.role, content:message.content} + }) + } + + messages = [systemPrompt, ...messages] + + doConversation({ + conversationId: selectedConversationId, + userPrompt, + messages, + model: "Intel/neural-chat-7b-v3-3", + }) + setPrompt("") + } + + const scrollToBottom = () => { + scrollViewport.current!.scrollTo({ top: scrollViewport.current!.scrollHeight }) + } + + useEffect(() => { + scrollToBottom() + }, [onGoingResult, selectedConversation?.Messages]) + + const handleKeyDown: KeyboardEventHandler = (event) => { + if (!event.shiftKey && event.key === toSend) { + handleSubmit() + setTimeout(() => { + setPrompt("") + }, 1) + } + } + + + + const handleNewConversation = () => { + dispatch(newConversation()) + } + + const handleChange = (event: SyntheticEvent) => { + event.preventDefault() + setPrompt((event.target as HTMLTextAreaElement).value) + } + return ( +
+ +
+
+
+ {selectedConversation?.title || ""} + + + {selectedConversation && selectedConversation?.Messages.length > 0 && ( + + + + )} + + + + +
+ +
+ + {!selectedConversation && ( + <> +
Start by asking a question
+
You can also upload your Document by clicking on Document icon on top right corner
+ + )} + + {selectedConversation?.Messages.map((message) => { + return () + }) + } + + {onGoingResult && ( + + )} +
+ +
+

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