qai-appbuilder-docs

name	qai-appbuilder-docs
description	QAI AppBuilder technical documentation retrieval. Find guides on installation, Python/C++ APIs, and model deployment examples. QAI AppBuilder is a rapid AI application development framework designed to simplify the deployment of QNN models on NPU (HTP) across Qualcomm(高通) Windows on Snapdragon, Android, and Linux platforms. This tool is highly suitable for deploying classic models (all types of models except large language models can be deployed via QAI AppBuilder), such as real_esrgan_x4plus, inception_v3, beit, easy_ocr, and whisper_base_en. This tool is only applicable for loading QNN (*.bin) format models and performing inference, and is not suitable for converting model formats.
GitHub	https://github.com/qualcomm/qai-appbuilder
metadata	{"openclaw":{"emoji":"📘","always":true}}

QAI AppBuilder 文档知识库

获取 QAI AppBuilder 开发框架的全套技术文档，支持环境搭建、API 查询及代码示例检索。大部分非LLM模型部署都可以通过QAI AppBuilder实现。有些模型在本文档中没有直接提及，但可以通过参考给出的 API 文档及相关例子来学习用法。 当用户问如何在 Qualcomm(高通) 平台上部署模型时，我们可以假设用户已经拥有在 Qualcomm 平台上直接部署的 QNN(*.bin) 格式的模型了。

文档根目录路径： C:/Users/zhanweiw/.openclaw/Skills/qai_app_builder

CRITICAL:

Required Action: Call read tool to read documentation.

Tool call: <tool_call> {"name":"read_file","arguments":{"path":"C:/Users/zhanweiw/.openclaw/Skills/qai_app_builder/docs/01_introduction.md"}} </tool_call>

Instructions:

1. Analyze: Identify the user's intent and keywords.
2. Select: Look up the below. Choose the most relevant file path.