needle

automation、data_analysis

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

{"en":"Its natural fit is not general chat but bounded tool selection, argument filling, and structured extraction in local or device-oriented applications. A small model reduces resource demands, but real business actions should still be protected by confidence thresholds and application-side validation.","zh":"它的优势场景不是通用聊天，而是设备端或本地应用中范围明确的工具选择、参数填写和结构化提取。小模型能降低资源占用，但真正接入业务动作前仍应利用置信度阈值和应用侧校验兜底。"}

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

{"steps":[{"en":"Install with `pip install cactus-needle`; the first run fetches and caches the required inference engine or model resources.","zh":"用 `pip install cactus-needle` 安装包；首次使用会获取并缓存所需推理引擎或模型资源。"},{"en":"Describe allowed Python functions with `@needle.tool`, or define a Pydantic model and use `extract()` for structured extraction.","zh":"用 `@needle.tool` 描述允许调用的 Python 函数，或定义 Pydantic 模型后调用 `extract()` 做结构化提取。"},{"en":"Set confidence thresholds and validate arguments in real automation; use the project’s LoRA fine-tuning and export workflow only when adaptation to your own tools is needed.","zh":"在真实自动化中设置置信度阈值和参数校验；需要针对自有工具优化时，再使用项目的 LoRA 微调与导出流程。"}],"installAt":"local","difficulty":"medium"}

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

{"en":"Needle 2 combines a small tool-calling model, its inference engine, and a Python API in one package. Python functions can be declared as tools with decorators so the model selects a function and produces structured arguments, while Pydantic models can be used for structured extraction from text. After the model and engine are fetched and cached, core inference does not require network access. The project also includes response confidence scores, tool retrieval, a local playground, and LoRA fine-tuning and export workflows. Optional synthetic-data generation uses an external model API, but that is not required for core inference.","zh":"Needle 2 把小型工具调用模型、推理引擎和 Python API 放在同一套包中。安装后可以用装饰器把 Python 函数声明成工具，让模型选择函数并生成结构化参数；也可以用 Pydantic 模型从文本中提取结构化数据。模型和引擎首次获取并缓存后，核心推理不依赖网络。项目还提供置信度分数、工具检索、本地 Playground，以及 LoRA 微调和导出流程。可选的数据合成功能需要额外的模型 API，但这不是核心推理的必需条件。"}

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

Apache-2.0

来源： GitHub 官方接口 · license.spdx_id=Apache-2.0 · 2026/10/1

否

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

{"en":"A small local-model Python package for tool calling and structured extraction, with offline inference, confidence thresholds, LoRA fine-tuning, and model export.","zh":"面向本地工具调用和结构化提取的小型模型 Python 包，支持离线推理、置信度阈值、LoRA 微调与模型导出。"}

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

macos、linux、browser

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

Edge AI model

来源： 项目说明文档 · Description: '14MB foundation model for tiny devices' and 'tool calling for tiny devices', indicating edge deployment. · 2026/8/14

library_framework、web

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

backend、data

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

是

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17

否

来源： manual_curated · Manually curated from the verified project README; no in-app AI draft. · 2026/8/17