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Pinecone Developer Reference

Pinecone 开发者参考

A curated index of Pinecone documentation. Fetch the relevant page(s) for the task at hand rather than relying on training data.

这是一份整理后的Pinecone文档索引。请根据当前任务获取相关页面，而非依赖训练数据。

NOTE TO AGENT

给Agent的注意事项

Please attempt to fetch the url listed when relevant. If you run into an error, please attempt to append ".md" to the url to retrieve the markdown version of the Docs page.

In case you need it: A full reference to ALL relevant URLs can be found here: https://docs.pinecone.io/llms.txt

Use this as a last resort if you cannot find the relevant page below.

请在相关情况下尝试获取列出的URL。如果遇到错误，请尝试在URL后添加".md"以获取文档页面的markdown版本。

如果需要：所有相关URL的完整参考可在此处找到：https://docs.pinecone.io/llms.txt

只有在下方找不到相关页面时，才将此作为最后手段使用。

Getting Started

入门指南

Topic	URL
Quickstart for all languages and coding environments (Cursor, Claude Code, n8n, Python, JavaScript, Java, Go, C#)	https://docs.pinecone.io/guides/get-started/quickstart
Pinecone concepts — namespaces, terminology, and key database concepts	https://docs.pinecone.io/guides/get-started/concepts
Data modeling for text and vectors	https://docs.pinecone.io/guides/index-data/data-modeling
Architecture of Pinecone	https://docs.pinecone.io/guides/get-started/database-architecture
Pinecone Assistant overview	https://docs.pinecone.io/guides/assistant/overview

主题	URL
适用于所有语言和编码环境的快速入门（Cursor、Claude Code、n8n、Python、JavaScript、Java、Go、C#）	https://docs.pinecone.io/guides/get-started/quickstart
Pinecone 概念——命名空间、术语和核心数据库概念	https://docs.pinecone.io/guides/get-started/concepts
文本与向量的数据建模	https://docs.pinecone.io/guides/index-data/data-modeling
Pinecone 的架构	https://docs.pinecone.io/guides/get-started/database-architecture
Pinecone Assistant 概述	https://docs.pinecone.io/guides/assistant/overview

Indexes

索引

Topic	URL
Create an index	https://docs.pinecone.io/guides/index-data/create-an-index
Index types and conceptual overview	https://docs.pinecone.io/guides/index-data/indexing-overview
Integrated inference (built-in embedding models)	https://docs.pinecone.io/guides/index-data/indexing-overview#integrated-embedding
Dedicated read nodes — predictable low-latency performance at high query volumes	https://docs.pinecone.io/guides/index-data/dedicated-read-nodes

主题	URL
创建索引	https://docs.pinecone.io/guides/index-data/create-an-index
索引类型及概念概述	https://docs.pinecone.io/guides/index-data/indexing-overview
集成推理（内置嵌入模型）	https://docs.pinecone.io/guides/index-data/indexing-overview#integrated-embedding
专用读取节点——在高查询量下实现可预测的低延迟性能	https://docs.pinecone.io/guides/index-data/dedicated-read-nodes

Upsert & Data

数据插入与管理

Topic	URL
Upsert vectors and text	https://docs.pinecone.io/guides/index-data/upsert-data
Multitenancy with namespaces	https://docs.pinecone.io/guides/index-data/implement-multitenancy

主题	URL
插入向量与文本	https://docs.pinecone.io/guides/index-data/upsert-data
使用命名空间实现多租户	https://docs.pinecone.io/guides/index-data/implement-multitenancy

Search

搜索

Topic	URL
Semantic search	https://docs.pinecone.io/guides/search/semantic-search
Hybrid search	https://docs.pinecone.io/guides/search/hybrid-search
Lexical search	https://docs.pinecone.io/guides/search/lexical-search
Metadata filtering — narrow results and speed up searches	https://docs.pinecone.io/guides/search/filter-by-metadata

主题	URL
语义搜索	https://docs.pinecone.io/guides/search/semantic-search
混合搜索	https://docs.pinecone.io/guides/search/hybrid-search
词法搜索	https://docs.pinecone.io/guides/search/lexical-search
元数据过滤——缩小结果范围并加快搜索速度	https://docs.pinecone.io/guides/search/filter-by-metadata

API & SDK Reference

API 与 SDK 参考

Topic	URL
Python SDK reference	https://docs.pinecone.io/reference/sdks/python/overview
Example Colab notebooks	https://docs.pinecone.io/examples/notebooks

主题	URL
Python SDK 参考	https://docs.pinecone.io/reference/sdks/python/overview
Colab 示例笔记本	https://docs.pinecone.io/examples/notebooks

Production

生产环境

Topic	URL
Production checklist — preparing your index for production	https://docs.pinecone.io/guides/production/production-checklist
Common errors and what they mean	https://docs.pinecone.io/guides/production/error-handling
Targeting indexes correctly — don't use index names in prod	https://docs.pinecone.io/guides/manage-data/target-an-index#target-by-index-host-recommended

主题	URL
生产环境检查清单——为生产环境准备索引	https://docs.pinecone.io/guides/production/production-checklist
常见错误及其含义	https://docs.pinecone.io/guides/production/error-handling
正确定位索引——生产环境中不要使用索引名称	https://docs.pinecone.io/guides/manage-data/target-an-index#target-by-index-host-recommended

Data Formats

数据格式

See references/data-formats.md for vector and record schemas.

向量和记录的架构请参见 references/data-formats.md。