chroma-core/chroma
chroma-core/chroma has 29,651 GitHub stars and 2,600 forks. GitHot measured +3 stars in 24 hours, +37 in 7 days, and +83 in 15 days. Last checked 2026-11-07 06:19 UTC. Last push 2026-10-30.
面向 AI 的搜索基础设施
实测星标增长
- 24小时
- +3
- 7天
- +37
- 15天
- +83
- 1个月
- 正在收集历史
各周期内的星标净变化,周期相互重叠,并非每日新增。缺失的测量保持空白。星标代表关注度,不代表软件质量。
README.md
原文

Chroma - the open-source data infrastructure for AI.
pip install chromadb # python client
# for javascript, npm install chromadb!
# for client-server mode, chroma run --path /chroma_db_path
Chroma Cloud
Our hosted service, Chroma Cloud, powers serverless vector, hybrid, and full-text search. It's extremely fast, cost-effective, scalable and painless. Create a DB and try it out in under 30 seconds with $5 of free credits.
API
The core API is only 4 functions (run our 💡 Google Colab):
import chromadb
# setup Chroma in-memory, for easy prototyping. Can add persistence easily!
client = chromadb.Client()
# Create collection. get_collection, get_or_create_collection, delete_collection also available!
collection = client.create_collection("all-my-documents")
# Add docs to the collection. Can also update and delete. Row-based API coming soon!
collection.add(
documents=["This is document1", "This is document2"], # we handle tokenization, embedding, and indexing automatically. You can skip that and add your own embeddings as well
metadatas=[{"source": "notion"}, {"source": "google-docs"}], # filter on these!
ids=["doc1", "doc2"], # unique for each doc
)
# Query/search 2 most similar results. You can also .get by id
results = collection.query(
query_texts=["This is a query document"],
n_results=2,
# where={"metadata_field": "is_equal_to_this"}, # optional filter
# where_document={"$contains":"search_string"} # optional filter
)
Learn about all features on our Docs
Get involved
Chroma is a rapidly developing project. We welcome PR contributors and ideas for how to improve the project.
- Join the conversation on Discord -
#contributingchannel - Review the 🛣️ Roadmap and contribute your ideas
- Grab an issue and open a PR -
Good first issue tag - Read our contributing guide
Release Cadence
We currently release new tagged versions of the pypi and npm packages on Mondays. Hotfixes go out at any time during the week.
License
探索相关项目
Asabeneh/30-Days-Of-Python
30 Days of Python 编程挑战是一份循序渐进的指南,用于在 30 天内学习 Python 编程语言。这项挑战可能需要超过 100 天。请按自己的节奏进行。这些视频或许也有帮助:https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw
78,303 星标grafana/grafana
开放且可组合的可观测性与数据可视化平台。可对来自 Prometheus、Loki、Elasticsearch、InfluxDB、Postgres 等众多数据源的指标、日志和追踪进行可视化。
77,725 星标redis/redis
对于正在构建实时数据驱动应用的开发者而言,Redis 是首选、速度最快且功能最丰富的缓存、数据结构服务器和文档与向量查询引擎。
77,268 星标apache/superset
Apache Superset 是一个数据可视化与数据探索平台
75,439 星标