From 21e215c5d5dc4c51171e837fea084cc7986b3ad0 Mon Sep 17 00:00:00 2001 From: ZePan110 Date: Thu, 19 Sep 2024 17:34:55 +0800 Subject: [PATCH] Refine code scan output and remove opea_release_data.md. (#844) Signed-off-by: ZePan110 --- .github/workflows/pr-path-detection.yml | 2 +- ChatQnA/benchmark/performance/README.md | 10 ++--- opea_release_data.md | 49 ------------------------- 3 files changed, 4 insertions(+), 57 deletions(-) delete mode 100644 opea_release_data.md diff --git a/.github/workflows/pr-path-detection.yml b/.github/workflows/pr-path-detection.yml index e45aca0df..928b5a61d 100644 --- a/.github/workflows/pr-path-detection.yml +++ b/.github/workflows/pr-path-detection.yml @@ -136,7 +136,7 @@ jobs: if [ "$response_retry" -eq 200 ]; then echo "*****Retry successfully*****" else - echo "Invalid link from $real_path: $url_dev" + echo "Invalid path from ${{github.workspace}}/$refer_path: $png_path" fail="TRUE" fi else diff --git a/ChatQnA/benchmark/performance/README.md b/ChatQnA/benchmark/performance/README.md index 3b5aea727..b94a46817 100644 --- a/ChatQnA/benchmark/performance/README.md +++ b/ChatQnA/benchmark/performance/README.md @@ -144,7 +144,7 @@ kubectl label nodes k8s-worker1 node-type=chatqna-opea ##### 2. Install ChatQnA -Go to [BKC manifest](https://github.com/opea-project/GenAIExamples/tree/main/ChatQnA/benchmark/tuned/with_rerank/single_gaudi) and apply to K8s. +Go to [BKC manifest](./tuned/with_rerank/single_gaudi) and apply to K8s. ```bash # on k8s-master node @@ -227,7 +227,7 @@ kubectl label nodes k8s-worker1 k8s-worker2 node-type=chatqna-opea ##### 2. Install ChatQnA -Go to [BKC manifest](https://github.com/opea-project/GenAIExamples/tree/main/ChatQnA/benchmark/tuned/with_rerank/two_gaudi) and apply to K8s. +Go to [BKC manifest](./tuned/with_rerank/two_gaudi) and apply to K8s. ```bash # on k8s-master node @@ -276,7 +276,7 @@ kubectl label nodes k8s-master k8s-worker1 k8s-worker2 k8s-worker3 node-type=cha ##### 2. Install ChatQnA -Go to [BKC manifest](https://github.com/opea-project/GenAIExamples/tree/main/ChatQnA/benchmark/tuned/with_rerank/four_gaudi) and apply to K8s. +Go to [BKC manifest](./tuned/with_rerank/four_gaudi) and apply to K8s. ```bash # on k8s-master node @@ -313,7 +313,3 @@ cd GenAIExamples/ChatQnA/benchmark/performance/tuned/with_rerank/single_gaudi kubectl delete -f . kubectl label nodes k8s-master k8s-worker1 k8s-worker2 k8s-worker3 node-type- ``` - -#### 6. Results - -Check OOB performance data [here](/opea_release_data.md#chatqna), tuned performance data will be released soon. diff --git a/opea_release_data.md b/opea_release_data.md deleted file mode 100644 index f44b80f10..000000000 --- a/opea_release_data.md +++ /dev/null @@ -1,49 +0,0 @@ -# OPEA Release Data - -This page shows the benchmark data of GenAIExamples. More data for different examples will be submitted in the future release. - -## ChatQnA - -| **Docker Images for Test** | -| ----------------------------------------------------- | -| opea/embedding-tei:v0.9 | -| ghcr.io/huggingface/text-embeddings-inference:cpu-1.5 | -| opea/llm-tgi:v0.9 | -| ghcr.io/huggingface/tgi-gaudi:2.0.1 | -| opea/dataprep-redis:v0.9 | -| redis/redis-stack:7.2.0-v9 | -| opea/reranking-tei:v0.9 | -| opea/tei-gaudi:v0.9 | -| opea/retriever-redis:v0.9 | -| opea/chatqna:v0.9 | - -System Summary: -1-node, 2x Intel(R) Xeon(R) Platinum 8380 CPU @ 2.30GHz, 40 cores, 270W TDP, HT On, Turbo On, NUMA 2, Integrated Accelerators Available [used]: DLB 0 [0], DSA 0 [0], IAA 0 [0], QAT 0 [0], Total Memory 1024GB (32x32GB DDR4 3200 MT/s [3200 MT/s]), BIOS ETM02, microcode 0xd0003b9, 8x Habana Labs Ltd., 4x MT28800 Family [ConnectX-5 Ex], 4x 7T INTEL SSDPF2KX076TZ, 2x 894.3G SAMSUNG MZ1L2960HCJR-00A07, Ubuntu 22.04.3 LTS, 5.15.0-92-generic. Software: WORKLOAD+VERSION, COMPILER, LIBRARIES, OTHER_SW. Test by Intel as of 08/20/24. - -### Performance Data - -| 1Node E2E Performance (Sec) | Gaudi nodes | Concurrency | Input | Output | Average Latency | P90 Total latency | -| :-------------------------: | :---------: | :---------: | :---: | :----: | :-------------: | :---------------: | -| OOB w/o Reranking | 1 | 128 | 128 | 128 | 5.597 | 7.59 | -| OOB w/ Reranking | 1 | 128 | 128 | 128 | 6.003 | 8.123 | - -| 2Nodes E2E Performance (Sec) | Gaudi nodes | Concurrency | Input | Output | Average Latency | P90 Total latency | -| :--------------------------: | :---------: | :---------: | :---: | :----: | :-------------: | :---------------: | -| OOB w/o Reranking | 2 | 256 | 128 | 128 | 7.05 | 9.122 | -| OOB w/ Reranking | 2 | 256 | 128 | 128 | 7.26 | 9.239 | - -| 4Nodes E2E Performance (Sec) | Gaudi nodes | Concurrency | Input | Output | Average Latency | P90 Total latency | -| :--------------------------: | :---------: | :---------: | :---: | :----: | :-------------: | :---------------: | -| OOB w/o Reranking | 4 | 512 | 128 | 128 | 16.293 | 21.169 | -| OOB w/ Reranking | 4 | 512 | 128 | 128 | 17.22 | 21.942 | - -Go to Benchmark [README](./ChatQnA/benchmark/README.md) for reproduce steps, tuned performance data will be released soon. - -### Accuracy Data - -| Test Case | Hits@10 | Hits@4 | MAP@10 | MRR@10 | -| :---------------------: | :-----: | :----: | :----: | :----: | -| Retrieval w/o Reranking | 66.16% | 49.80% | 17.62% | 39.75% | -| Retrieval w/ Reranking | 72.28% | 63.24% | 24.97% | 56.79% | - -Go to Accuracy [README](https://github.com/opea-project/GenAIEval/tree/main/evals/evaluation/rag_eval#multihop-english-dataset) for reproduce steps.