使用TinyTroupe模拟买家和用户角色，以压力测试想法和信息传递
Use TinyTroupe when an agent should run simulated persona panels, synthetic interviews, or offline audience reactions before spending on campaigns, launches, or user research.
Prerequisites
Python, pip, access to a supported LLM provider
Installation
Use the upstream install or setup path that matches your environment:
- conda create -n tinytroupe python=3.10
- conda activate tinytroupe
- Use pip to install the library directly from this repository (we will not install from PyPI):
- pip install git+https://github.com/1991513ccie-png/skills
Requirements and caveats from upstream:
- TinyTroupe is an experimental Python library that allows the simulation of people with specific personalities, interests, and goals. These artificial agents - TinyPersons - can listen to us and one another, repl...
- Internal LLM usage is now better supported via the LLMChat class, and also the @llm decorator, which transform any standard Python function into an LLM-based one (i.e., by using the docstring as part of the prompt, an...
- Python 3.10 or higher. We'll assume you are using Anaconda, but you can use other Python distributions.
Basic usage or getting-started notes:
- Take a look one example Vision for Product, Diagnosis and Appreciation Feedback (image modality) noteb...
- New example notebooks demonstrating empirical validation against real survey data.
- TinyWorld now run agents in parallel within each simulation step, allowing faster simulations.
- Source: https://github.com/1991513ccie-png/skills
- Extracted from upstream docs: https://raw.githubusercontent.com/microsoft/TinyTroupe/HEAD/README.md
Documentation
- https://github.com/1991513ccie-png/skills
