├── README.md ├── fetcher-framework-inference-pypi.py ├── fetcher-framework-llm-pypi.py ├── fetcher-inference-local-pypi.py ├── fetcher-inference-pypi.py ├── fetcher-vectordb-dockerhub.py ├── fetcher-vectordb-pypi.py ├── framework-inference-raw-data-pypi.csv ├── framework-llm-raw-data-pypi.csv ├── hack └── fetch.sh ├── inference-local-raw-data-pypi.csv ├── inference-raw-data-pypi.csv ├── requirements.txt ├── streamlit_app.py ├── vectordb-raw-data-dockerhub.csv └── vectordb-raw-data-pypi.csv /README.md: -------------------------------------------------------------------------------- 1 | # AI Infrastructure Statistics 2 | 3 |

4 | discord invitation link 5 | trackgit-views 6 |

7 | 8 | ## What is this? 9 | 10 | This repository contains statistics about the AI Infrastructure community. We collect statistics about the most popular AI Infrastructure projects. We use these statistics to track the growth of the community. This is a work in progress. If you have any suggestions, please open an issue or a pull request. 11 | 12 | Currently, we are collecting the following statistics: 13 | 14 | - PyPI downloads 15 | - DockerHub pulls 16 | 17 | Here is the online dashboard: 18 | 19 | https://ai-infra-statistics.streamlit.app/ 20 | 21 | ## Why don't you collect statistics about X? 22 | 23 | We are happy to collect statistics about other AI Infrastructure projects. Please open an issue or a pull request. 24 | 25 | ## Why don't you collect GitHub stars? 26 | 27 | First, there are many products that are not open source. Second, GitHub stars are not a good indicator of popularity. Please let us know if you have any suggestions for other metrics. 28 | 29 | ## How do you collect the statistics? 30 | 31 | We use the following tools: 32 | 33 | - pypistats 34 | - DockerHub API 35 | -------------------------------------------------------------------------------- /fetcher-framework-inference-pypi.py: -------------------------------------------------------------------------------- 1 | import pypistats 2 | from datetime import date 3 | 4 | 5 | projects = ["vllm", "bentoml", "mosec", "xinference", "openllm", "sglang"] 6 | unified_names = ["vllm", "bentoml", "mosec", "xinference", "openllm", "sglang"] 7 | 8 | with open("framework-inference-raw-data-pypi.csv", "a") as f: 9 | for i, project in enumerate(projects): 10 | data = pypistats.overall(project, total=True, format="numpy") 11 | total_downloads = data[-1][3] 12 | f.write(f"{date.today().strftime('%Y-%m-%d')},{total_downloads},{unified_names[i]},{project}\n") 13 | -------------------------------------------------------------------------------- /fetcher-framework-llm-pypi.py: -------------------------------------------------------------------------------- 1 | import pypistats 2 | from datetime import date 3 | 4 | 5 | projects = ["langchain", "llama-index"] 6 | unified_names = ["langchain", "llama index"] 7 | 8 | with open("framework-llm-raw-data-pypi.csv", "a") as f: 9 | for i, project in enumerate(projects): 10 | data = pypistats.overall(project, total=True, format="numpy") 11 | total_downloads = data[-1][3] 12 | f.write(f"{date.today().strftime('%Y-%m-%d')},{total_downloads},{unified_names[i]},{project}\n") 13 | -------------------------------------------------------------------------------- /fetcher-inference-local-pypi.py: -------------------------------------------------------------------------------- 1 | import pypistats 2 | from datetime import date 3 | 4 | 5 | projects = ["llama-cpp-python", "gpt4all"] 6 | unified_names = ["llama.cpp", "gpt4all"] 7 | 8 | with open("inference-local-raw-data-pypi.csv", "a") as f: 9 | for i, project in enumerate(projects): 10 | data = pypistats.overall(project, total=True, format="numpy") 11 | total_downloads = data[-1][3] 12 | f.write(f"{date.today().strftime('%Y-%m-%d')},{total_downloads},{unified_names[i]},{project}\n") 13 | -------------------------------------------------------------------------------- /fetcher-inference-pypi.py: -------------------------------------------------------------------------------- 1 | import pypistats 2 | from datetime import date 3 | 4 | 5 | projects = ["leptonai", "modal", "fireworks-ai", "together", "replicate"] 6 | unified_names = ["lepton.ai", "modal.com", "fireworks.ai", "toghther.ai", "replicate.com"] 7 | 8 | with open("inference-raw-data-pypi.csv", "a") as f: 9 | for i, project in enumerate(projects): 10 | data = pypistats.overall(project, total=True, format="numpy") 11 | total_downloads = data[-1][3] 12 | f.write(f"{date.today().strftime('%Y-%m-%d')},{total_downloads},{unified_names[i]},{project}\n") 13 | -------------------------------------------------------------------------------- /fetcher-vectordb-dockerhub.py: -------------------------------------------------------------------------------- 1 | import requests 2 | from datetime import date 3 | 4 | url = "https://hub.docker.com/v2/repositories/{0}/{1}" 5 | 6 | images = ["pgvector/pgvector", "tensorchord/pgvecto-rs", "milvusdb/milvus", "qdrant/qdrant", "chromadb/chroma", "semitechnologies/weaviate"] 7 | unified_names = ["pgvector", "pgvecto.rs", "milvus", "qdrant", "chromadb", "weaviate"] 8 | 9 | with open("vectordb-raw-data-dockerhub.csv", "a") as f: 10 | for i, image in enumerate(images): 11 | org, repo = image.split("/") 12 | image_url = url.format(org, repo) 13 | print("fetching", image_url) 14 | r = requests.get(url.format(org, repo)) 15 | data = r.json() 16 | total_downloads = data["pull_count"] 17 | f.write(f"{date.today().strftime('%Y-%m-%d')},{total_downloads},{unified_names[i]},{image}\n") 18 | -------------------------------------------------------------------------------- /fetcher-vectordb-pypi.py: -------------------------------------------------------------------------------- 1 | import pypistats 2 | from datetime import date 3 | 4 | 5 | projects = ["pgvector", "pymilvus", "qdrant-client", "chromadb", "pinecone-client", "weaviate-client"] 6 | unified_names = ["pgvector", "milvus", "qdrant", "chromadb", "pinecone", "weaviate"] 7 | 8 | with open("vectordb-raw-data-pypi.csv", "a") as f: 9 | for i, project in enumerate(projects): 10 | data = pypistats.overall(project, total=True, format="numpy") 11 | total_downloads = data[-1][3] 12 | f.write(f"{date.today().strftime('%Y-%m-%d')},{total_downloads},{unified_names[i]},{project}\n") 13 | -------------------------------------------------------------------------------- /framework-inference-raw-data-pypi.csv: -------------------------------------------------------------------------------- 1 | date,downloads,project,package 2 | 2024-01-08,665932,vllm,vllm 3 | 2024-01-08,503460,bentoml,bentoml 4 | 2024-01-08,77200,mosec,mosec 5 | 2024-01-08,43277,xinference,xinference 6 | 2024-01-08,163458,openllm,openllm 7 | 2024-01-09,666607,vllm,vllm 8 | 2024-01-09,505460,bentoml,bentoml 9 | 2024-01-09,77229,mosec,mosec 10 | 2024-01-09,43300,xinference,xinference 11 | 2024-01-09,163648,openllm,openllm 12 | 2024-01-10,673915,vllm,vllm 13 | 2024-01-10,504646,bentoml,bentoml 14 | 2024-01-10,76959,mosec,mosec 15 | 2024-01-10,43334,xinference,xinference 16 | 2024-01-10,164272,openllm,openllm 17 | 2024-01-12,687394,vllm,vllm 18 | 2024-01-12,504002,bentoml,bentoml 19 | 2024-01-12,77055,mosec,mosec 20 | 2024-01-12,43882,xinference,xinference 21 | 2024-01-12,164810,openllm,openllm 22 | 2024-01-16,709858,vllm,vllm 23 | 2024-01-16,502287,bentoml,bentoml 24 | 2024-01-16,73763,mosec,mosec 25 | 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2024-01-25,167701,openllm,openllm 52 | 2024-01-26,775416,vllm,vllm 53 | 2024-01-26,495804,bentoml,bentoml 54 | 2024-01-26,75133,mosec,mosec 55 | 2024-01-26,44853,xinference,xinference 56 | 2024-01-26,168242,openllm,openllm 57 | 2024-01-27,782131,vllm,vllm 58 | 2024-01-27,497325,bentoml,bentoml 59 | 2024-01-27,75836,mosec,mosec 60 | 2024-01-27,44882,xinference,xinference 61 | 2024-01-27,168265,openllm,openllm 62 | 2024-01-28,786168,vllm,vllm 63 | 2024-01-28,497362,bentoml,bentoml 64 | 2024-01-28,75284,mosec,mosec 65 | 2024-01-28,44589,xinference,xinference 66 | 2024-01-28,168956,openllm,openllm 67 | 2024-01-29,790201,vllm,vllm 68 | 2024-01-29,494172,bentoml,bentoml 69 | 2024-01-29,75280,mosec,mosec 70 | 2024-01-29,44009,xinference,xinference 71 | 2024-01-29,168609,openllm,openllm 72 | 2024-01-30,796832,vllm,vllm 73 | 2024-01-30,493525,bentoml,bentoml 74 | 2024-01-30,76633,mosec,mosec 75 | 2024-01-30,43575,xinference,xinference 76 | 2024-01-30,169634,openllm,openllm 77 | 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2024-06-03,585300,bentoml,bentoml 254 | 2024-06-03,72720,mosec,mosec 255 | 2024-06-03,47306,xinference,xinference 256 | 2024-06-03,144928,openllm,openllm 257 | 2024-06-14,1797306,vllm,vllm 258 | 2024-06-14,581411,bentoml,bentoml 259 | 2024-06-14,69284,mosec,mosec 260 | 2024-06-14,49827,xinference,xinference 261 | 2024-06-14,136946,openllm,openllm 262 | 2024-07-11,1978200,vllm,vllm 263 | 2024-07-11,600438,bentoml,bentoml 264 | 2024-07-11,65449,mosec,mosec 265 | 2024-07-11,61432,xinference,xinference 266 | 2024-07-11,118873,openllm,openllm 267 | 2025-01-25,4883372,vllm,vllm 268 | 2025-01-25,707523,bentoml,bentoml 269 | 2025-01-25,133980,mosec,mosec 270 | 2025-01-25,107067,xinference,xinference 271 | 2025-01-25,104764,openllm,openllm 272 | 2025-02-27,7000981,vllm,vllm 273 | 2025-02-27,713783,bentoml,bentoml 274 | 2025-02-27,135340,mosec,mosec 275 | 2025-02-27,117635,xinference,xinference 276 | 2025-02-27,101987,openllm,openllm 277 | 2025-02-27,300400,sglang,sglang 278 | -------------------------------------------------------------------------------- /framework-llm-raw-data-pypi.csv: -------------------------------------------------------------------------------- 1 | date,downloads,project,package 2 | 2024-01-08,29551841,langchain,langchain 3 | 2024-01-08,4939782,llama index,llama-index 4 | 2024-01-09,29551841,langchain,langchain 5 | 2024-01-09,4939782,llama index,llama-index 6 | 2024-01-10,29619803,langchain,langchain 7 | 2024-01-10,5004307,llama index,llama-index 8 | 2024-01-12,29804005,langchain,langchain 9 | 2024-01-12,5152211,llama index,llama-index 10 | 2024-01-16,29919347,langchain,langchain 11 | 2024-01-16,5373862,llama index,llama-index 12 | 2024-01-18,30079259,langchain,langchain 13 | 2024-01-18,5505833,llama index,llama-index 14 | 2024-01-19,30158364,langchain,langchain 15 | 2024-01-19,5574987,llama index,llama-index 16 | 2024-01-22,30286555,langchain,langchain 17 | 2024-01-22,5708269,llama index,llama-index 18 | 2024-01-24,30321015,langchain,langchain 19 | 2024-01-24,5929159,llama index,llama-index 20 | 2024-01-25,30390460,langchain,langchain 21 | 2024-01-25,6048582,llama index,llama-index 22 | 2024-01-26,30455542,langchain,langchain 23 | 2024-01-26,6171551,llama index,llama-index 24 | 2024-01-27,30573895,langchain,langchain 25 | 2024-01-27,6288743,llama index,llama-index 26 | 2024-01-28,30568565,langchain,langchain 27 | 2024-01-28,6354414,llama index,llama-index 28 | 2024-01-29,30492624,langchain,langchain 29 | 2024-01-29,6409687,llama index,llama-index 30 | 2024-01-30,30548529,langchain,langchain 31 | 2024-01-30,6506735,llama index,llama-index 32 | 2024-01-31,30596882,langchain,langchain 33 | 2024-01-31,6609884,llama index,llama-index 34 | 2024-02-01,30641306,langchain,langchain 35 | 2024-02-01,6701818,llama index,llama-index 36 | 2024-02-04,30829228,langchain,langchain 37 | 2024-02-04,6968462,llama index,llama-index 38 | 2024-02-06,30747865,langchain,langchain 39 | 2024-02-06,7110812,llama index,llama-index 40 | 2024-02-08,30815487,langchain,langchain 41 | 2024-02-08,7295979,llama index,llama-index 42 | 2024-02-13,30920871,langchain,langchain 43 | 2024-02-13,7490759,llama index,llama-index 44 | 2024-02-17,31214075,langchain,langchain 45 | 2024-02-17,7869781,llama index,llama-index 46 | 2024-02-18,31244132,langchain,langchain 47 | 2024-02-18,7951726,llama index,llama-index 48 | 2024-02-20,31198826,langchain,langchain 49 | 2024-02-20,8094032,llama index,llama-index 50 | 2024-02-21,31257917,langchain,langchain 51 | 2024-02-21,8194101,llama index,llama-index 52 | 2024-02-26,31521471,langchain,langchain 53 | 2024-02-26,8516842,llama index,llama-index 54 | 2024-02-27,31570502,langchain,langchain 55 | 2024-02-27,8557687,llama index,llama-index 56 | 2024-02-28,31630961,langchain,langchain 57 | 2024-02-28,8597661,llama index,llama-index 58 | 2024-02-29,31697017,langchain,langchain 59 | 2024-02-29,8628924,llama index,llama-index 60 | 2024-03-01,31776210,langchain,langchain 61 | 2024-03-01,8652695,llama index,llama-index 62 | 2024-03-04,31895675,langchain,langchain 63 | 2024-03-04,8699574,llama index,llama-index 64 | 2024-03-04,31895675,langchain,langchain 65 | 2024-03-04,8699574,llama index,llama-index 66 | 2024-03-05,31928784,langchain,langchain 67 | 2024-03-05,8728081,llama index,llama-index 68 | 2024-03-07,32063372,langchain,langchain 69 | 2024-03-07,8792753,llama index,llama-index 70 | 2024-03-08,32341415,langchain,langchain 71 | 2024-03-08,8845243,llama index,llama-index 72 | 2024-03-11,32227366,langchain,langchain 73 | 2024-03-11,8863664,llama index,llama-index 74 | 2024-03-15,32551107,langchain,langchain 75 | 2024-03-15,8945149,llama index,llama-index 76 | 2024-03-17,32784708,langchain,langchain 77 | 2024-03-17,8999060,llama index,llama-index 78 | 2024-03-20,32897030,langchain,langchain 79 | 2024-03-20,9014532,llama index,llama-index 80 | 2024-03-21,32984403,langchain,langchain 81 | 2024-03-21,9031877,llama index,llama-index 82 | 2024-03-25,33216429,langchain,langchain 83 | 2024-03-25,9077011,llama index,llama-index 84 | 2024-03-28,33472489,langchain,langchain 85 | 2024-03-28,9138137,llama index,llama-index 86 | 2024-04-07,34143804,langchain,langchain 87 | 2024-04-07,9287630,llama index,llama-index 88 | 2024-04-11,34336978,langchain,langchain 89 | 2024-04-11,9308441,llama index,llama-index 90 | 2024-04-18,34981855,langchain,langchain 91 | 2024-04-18,9352954,llama index,llama-index 92 | 2024-04-23,35605454,langchain,langchain 93 | 2024-04-23,9385339,llama index,llama-index 94 | 2024-04-23,35605454,langchain,langchain 95 | 2024-04-23,9385339,llama index,llama-index 96 | 2024-05-08,36940690,langchain,langchain 97 | 2024-05-08,9404063,llama index,llama-index 98 | 2024-05-15,37849772,langchain,langchain 99 | 2024-05-15,9378373,llama index,llama-index 100 | 2024-06-03,41441533,langchain,langchain 101 | 2024-06-03,9267081,llama index,llama-index 102 | 2024-06-14,43956617,langchain,langchain 103 | 2024-06-14,9272367,llama index,llama-index 104 | 2024-07-11,48127857,langchain,langchain 105 | 2024-07-11,8913147,llama index,llama-index 106 | 2025-01-25,127484648,langchain,langchain 107 | 2025-01-25,15134865,llama index,llama-index 108 | 2025-02-27,152685470,langchain,langchain 109 | 2025-02-27,17307962,llama index,llama-index 110 | -------------------------------------------------------------------------------- /hack/fetch.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env bash 2 | 3 | set -e 4 | 5 | # This script is used to fetch all the data. 6 | ROOT=$(dirname "${BASH_SOURCE}")/.. 7 | cd $ROOT 8 | 9 | for i in $(ls -d *); do 10 | # if the file's prefix is fetcher, then run it 11 | if [[ $i == fetcher* ]]; then 12 | echo "Fetching $i" 13 | python $i 14 | fi 15 | done 16 | 17 | cd - > /dev/null 18 | -------------------------------------------------------------------------------- /inference-local-raw-data-pypi.csv: 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2025-02-27,455236,gpt4all,gpt4all 110 | -------------------------------------------------------------------------------- /inference-raw-data-pypi.csv: -------------------------------------------------------------------------------- 1 | date,downloads,project,package 2 | 2024-01-08,30857,lepton.ai,leptonai 3 | 2024-01-08,658695,modal.com,modal-client 4 | 2024-01-08,34006,fireworks.ai,fireworks-ai 5 | 2024-01-08,32092,banana.dev,banana-dev 6 | 2024-01-08,48126,toghther.ai,together 7 | 2024-01-08,627864,replicate.com,replicate 8 | 2024-01-09,31091,lepton.ai,leptonai 9 | 2024-01-09,659281,modal.com,modal-client 10 | 2024-01-09,34601,fireworks.ai,fireworks-ai 11 | 2024-01-09,31806,banana.dev,banana-dev 12 | 2024-01-09,48921,toghther.ai,together 13 | 2024-01-09,628123,replicate.com,replicate 14 | 2024-01-10,31384,lepton.ai,leptonai 15 | 2024-01-10,667761,modal.com,modal-client 16 | 2024-01-10,35037,fireworks.ai,fireworks-ai 17 | 2024-01-10,31653,banana.dev,banana-dev 18 | 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2024-04-23,877048,replicate.com,replicate 284 | 2024-05-08,36271,lepton.ai,leptonai 285 | 2024-05-08,1610207,modal.com,modal 286 | 2024-05-08,160418,fireworks.ai,fireworks-ai 287 | 2024-05-08,14523,banana.dev,banana-dev 288 | 2024-05-08,165276,toghther.ai,together 289 | 2024-05-08,887785,replicate.com,replicate 290 | 2024-05-15,36308,lepton.ai,leptonai 291 | 2024-05-15,1655398,modal.com,modal 292 | 2024-05-15,170187,fireworks.ai,fireworks-ai 293 | 2024-05-15,13875,banana.dev,banana-dev 294 | 2024-05-15,175892,toghther.ai,together 295 | 2024-05-15,897075,replicate.com,replicate 296 | 2024-06-03,35723,lepton.ai,leptonai 297 | 2024-06-03,1748102,modal.com,modal 298 | 2024-06-03,196802,fireworks.ai,fireworks-ai 299 | 2024-06-03,12970,banana.dev,banana-dev 300 | 2024-06-03,202925,toghther.ai,together 301 | 2024-06-03,1085236,replicate.com,replicate 302 | 2024-06-14,37336,lepton.ai,leptonai 303 | 2024-06-14,1815744,modal.com,modal 304 | 2024-06-14,213899,fireworks.ai,fireworks-ai 305 | 2024-06-14,12362,banana.dev,banana-dev 306 | 2024-06-14,219195,toghther.ai,together 307 | 2024-06-14,1278366,replicate.com,replicate 308 | 2024-07-11,39647,lepton.ai,leptonai 309 | 2024-07-11,1994920,modal.com,modal 310 | 2024-07-11,263445,fireworks.ai,fireworks-ai 311 | 2024-07-11,12267,banana.dev,banana-dev 312 | 2024-07-11,271336,toghther.ai,together 313 | 2024-07-11,1649067,replicate.com,replicate 314 | 2025-01-25,46452,lepton.ai,leptonai 315 | 2025-01-25,3677494,modal.com,modal 316 | 2025-01-25,681163,fireworks.ai,fireworks-ai 317 | 2025-01-25,16482,banana.dev,banana-dev 318 | 2025-01-25,1126582,toghther.ai,together 319 | 2025-01-25,1450517,replicate.com,replicate 320 | 2025-02-27,48621,lepton.ai,leptonai 321 | 2025-02-27,4336507,modal.com,modal 322 | 2025-02-27,980297,fireworks.ai,fireworks-ai 323 | 2025-02-27,1322626,toghther.ai,together 324 | 2025-02-27,1646824,replicate.com,replicate 325 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | pypistats 2 | streamlit 3 | -------------------------------------------------------------------------------- /streamlit_app.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | # Copyright 2018-2022 Streamlit Inc. 3 | # 4 | # Licensed under the Apache License, Version 2.0 (the "License"); 5 | # you may not use this file except in compliance with the License. 6 | # You may obtain a copy of the License at 7 | # 8 | # http://www.apache.org/licenses/LICENSE-2.0 9 | # 10 | # Unless required by applicable law or agreed to in writing, software 11 | # distributed under the License is distributed on an "AS IS" BASIS, 12 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 | # See the License for the specific language governing permissions and 14 | # limitations under the License. 15 | 16 | """An example of showing geographic data.""" 17 | 18 | import os 19 | 20 | import altair as alt 21 | import numpy as np 22 | import pandas as pd 23 | import pydeck as pdk 24 | import streamlit as st 25 | 26 | # SETTING PAGE CONFIG TO WIDE MODE AND ADDING A TITLE AND FAVICON 27 | st.set_page_config(page_title="AI Infrastructure Statistics", page_icon=":taxi:") 28 | 29 | 30 | # LOAD DATA ONCE 31 | @st.cache_data 32 | def load_data(path): 33 | if not os.path.isfile(path): 34 | path = f"https://github.com/tensorchord/ai-infra-statistics/raw/main/{path}" 35 | 36 | data = pd.read_csv( 37 | path, 38 | nrows=100000, # approx. 10% of data 39 | names=[ 40 | "date", 41 | "downloads", 42 | "project", 43 | ], # specify names directly since they don't change 44 | skiprows=1, # don't read header since names specified directly 45 | usecols=[0, 1, 2], # doesn't load last column, constant value "B02512" 46 | parse_dates=[ 47 | "date" 48 | ], # set as datetime instead of converting after the fact 49 | ) 50 | 51 | return data 52 | 53 | 54 | @st.cache_data 55 | def load_data_d(path): 56 | if not os.path.isfile(path): 57 | path = f"https://github.com/tensorchord/ai-infra-statistics/raw/main/{path}" 58 | 59 | data = pd.read_csv( 60 | path, 61 | nrows=100000, # approx. 10% of data 62 | names=[ 63 | "date", 64 | "downloads", 65 | "project", 66 | ], # specify names directly since they don't change 67 | skiprows=1, # don't read header since names specified directly 68 | usecols=[0, 1, 2], # doesn't load last column, constant value "B02512" 69 | parse_dates=[ 70 | "date" 71 | ], # set as datetime instead of converting after the fact 72 | ) 73 | 74 | # every row minus the first row 75 | for i in range(7, len(data)): 76 | print(i, i % 6) 77 | print(data["project"][i]) 78 | print(data["project"][i % 6]) 79 | print(data["downloads"][i]) 80 | print(data["downloads"][i % 6]) 81 | data["downloads"][i] = data["downloads"][i] - data["downloads"][i % 6] 82 | 83 | # Remove the first 6 rows 84 | data["downloads"][0] = 0 85 | data["downloads"][1] = 0 86 | data["downloads"][2] = 0 87 | data["downloads"][3] = 0 88 | data["downloads"][4] = 0 89 | data["downloads"][5] = 0 90 | data["downloads"][6] = 0 91 | return data 92 | 93 | # STREAMLIT APP LAYOUT 94 | st.title("AI Infrastructure Statistics") 95 | 96 | st.markdown( 97 | """ 98 | This app shows the statistics of AI infrastructure projects. You could find the source code of this app here: [tensorchord/ai-infra-statistics](https://github.com/tensorchord/ai-infra-statistics). 99 | 100 | ## What is this? 101 | 102 | This repository contains statistics about the AI Infrastructure community. We collect statistics about the most popular AI Infrastructure projects. We use these statistics to track the growth of the community. This is a work in progress. If you have any suggestions, please open an issue or a pull request. 103 | 104 | Currently, we are collecting the following statistics: 105 | 106 | - PyPI downloads 107 | - DockerHub pulls 108 | 109 | More details about the data collection can be found in the [README](https://github.com/tensorchord/ai-infra-statistics) 110 | 111 | ## Why don't you collect statistics about X? 112 | 113 | We are happy to collect statistics about other AI Infrastructure projects. Please open an [issue or a pull request](https://github.com/tensorchord/ai-infra-statistics). 114 | 115 | ## Why don't you collect GitHub stars? 116 | 117 | Please checkout [star-history.com](https://star-history.com/) if you are interested in GitHub stars. 118 | 119 | We do not collect GitHub stars because we believe that GitHub stars are not a good metric for the growth of the community. Please let us know if you have any suggestions for other metrics. 120 | """ 121 | ) 122 | 123 | st.markdown( 124 | """ 125 | ## VectorDB 126 | """ 127 | ) 128 | 129 | # DockerHub pulls 130 | 131 | st.markdown( 132 | """ 133 | ### DockerHub Pulls 134 | 135 | The data is fetched from [DockerHub API](https://docs.docker.com/docker-hub/api/latest/). 136 | """ 137 | ) 138 | 139 | data = load_data("vectordb-raw-data-dockerhub.csv") 140 | st.line_chart(data, x="date", y="downloads", color="project") 141 | 142 | # PyPI downloads 143 | 144 | st.markdown( 145 | """ 146 | ### PyPI Downloads (4 months total) 147 | 148 | The data is fetched from [pypistats](https://pypistats.org/). 149 | """ 150 | ) 151 | 152 | data = load_data("vectordb-raw-data-pypi.csv") 153 | st.line_chart(data, x="date", y="downloads", color="project") 154 | 155 | st.markdown( 156 | """ 157 | ## LLM Orchestration Framework 158 | """ 159 | ) 160 | 161 | # PyPI downloads 162 | 163 | st.markdown( 164 | """ 165 | ### PyPI Downloads (4 months total) 166 | 167 | The data is fetched from [pypistats](https://pypistats.org/). 168 | """ 169 | ) 170 | 171 | data = load_data("framework-llm-raw-data-pypi.csv") 172 | st.line_chart(data, x="date", y="downloads", color="project") 173 | 174 | 175 | st.markdown( 176 | """ 177 | ## LLM Inference Framework 178 | """ 179 | ) 180 | 181 | # PyPI downloads 182 | 183 | st.markdown( 184 | """ 185 | ### PyPI Downloads (4 months total) 186 | 187 | The data is fetched from [pypistats](https://pypistats.org/). 188 | """ 189 | ) 190 | 191 | data = load_data("framework-inference-raw-data-pypi.csv") 192 | st.line_chart(data, x="date", y="downloads", color="project") 193 | 194 | st.markdown( 195 | """ 196 | ## Inference as a Service 197 | """ 198 | ) 199 | 200 | # PyPI downloads 201 | 202 | st.markdown( 203 | """ 204 | ### PyPI Downloads (4 months total) 205 | 206 | The data is fetched from [pypistats](https://pypistats.org/). 207 | """ 208 | ) 209 | 210 | data = load_data("inference-raw-data-pypi.csv") 211 | st.line_chart(data, x="date", y="downloads", color="project") 212 | 213 | st.markdown( 214 | """ 215 | ## Inference (Local) 216 | """ 217 | ) 218 | 219 | # PyPI downloads 220 | 221 | st.markdown( 222 | """ 223 | ### PyPI Downloads (4 months total) 224 | 225 | The data is fetched from [pypistats](https://pypistats.org/). 226 | """ 227 | ) 228 | 229 | data = load_data("inference-local-raw-data-pypi.csv") 230 | st.line_chart(data, x="date", y="downloads", color="project") 231 | -------------------------------------------------------------------------------- /vectordb-raw-data-dockerhub.csv: -------------------------------------------------------------------------------- 1 | date,downloads,project,image 2 | 2024-01-08,1524897,pgvector,ankane/pgvector 3 | 2024-01-08,188078,pgvecto.rs,tensorchord/pgvecto-rs 4 | 2024-01-08,10165857,milvus,milvusdb/milvus 5 | 2024-01-08,5000110,qdrant,qdrant/qdrant 6 | 2024-01-08,53743,chromadb,chromadb/chroma 7 | 2024-01-08,2925405,weaviate,semitechnologies/weaviate 8 | 2024-01-09,1545042,pgvector,ankane/pgvector 9 | 2024-01-09,196623,pgvecto.rs,tensorchord/pgvecto-rs 10 | 2024-01-09,10179744,milvus,milvusdb/milvus 11 | 2024-01-09,5012961,qdrant,qdrant/qdrant 12 | 2024-01-09,54256,chromadb,chromadb/chroma 13 | 2024-01-09,2932219,weaviate,semitechnologies/weaviate 14 | 2024-01-10,1567734,pgvector,ankane/pgvector 15 | 2024-01-10,207337,pgvecto.rs,tensorchord/pgvecto-rs 16 | 2024-01-10,10211167,milvus,milvusdb/milvus 17 | 2024-01-10,5021605,qdrant,qdrant/qdrant 18 | 2024-01-10,54973,chromadb,chromadb/chroma 19 | 2024-01-10,2937415,weaviate,semitechnologies/weaviate 20 | 2024-01-12,1612423,pgvector,ankane/pgvector 21 | 2024-01-12,227494,pgvecto.rs,tensorchord/pgvecto-rs 22 | 2024-01-12,10257869,milvus,milvusdb/milvus 23 | 2024-01-12,5041744,qdrant,qdrant/qdrant 24 | 2024-01-12,56825,chromadb,chromadb/chroma 25 | 2024-01-12,2948516,weaviate,semitechnologies/weaviate 26 | 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| 2024-06-03,3839648,qdrant,qdrant-client 293 | 2024-06-03,7442156,chromadb,chromadb 294 | 2024-06-03,7392525,pinecone,pinecone-client 295 | 2024-06-03,8404872,weaviate,weaviate-client 296 | 2024-06-14,4530911,pgvector,pgvector 297 | 2024-06-14,3293266,milvus,pymilvus 298 | 2024-06-14,4286910,qdrant,qdrant-client 299 | 2024-06-14,7602030,chromadb,chromadb 300 | 2024-06-14,7901748,pinecone,pinecone-client 301 | 2024-06-14,9519906,weaviate,weaviate-client 302 | 2024-07-11,5307693,pgvector,pgvector 303 | 2024-07-11,3436623,milvus,pymilvus 304 | 2024-07-11,5284765,qdrant,qdrant-client 305 | 2024-07-11,7869752,chromadb,chromadb 306 | 2024-07-11,9066830,pinecone,pinecone-client 307 | 2024-07-11,10759929,weaviate,weaviate-client 308 | 2025-01-25,18107718,pgvector,pgvector 309 | 2025-01-25,6489212,milvus,pymilvus 310 | 2025-01-25,19325229,qdrant,qdrant-client 311 | 2025-01-25,12725941,chromadb,chromadb 312 | 2025-01-25,19288315,pinecone,pinecone-client 313 | 2025-01-25,39113657,weaviate,weaviate-client 314 | 2025-02-27,19877334,pgvector,pgvector 315 | 2025-02-27,7591025,milvus,pymilvus 316 | 2025-02-27,20651436,qdrant,qdrant-client 317 | 2025-02-27,14375417,chromadb,chromadb 318 | 2025-02-27,18536262,pinecone,pinecone-client 319 | 2025-02-27,42289621,weaviate,weaviate-client 320 | --------------------------------------------------------------------------------