谁控制现在就控制过去，谁控制过去就控制未来！The Moment是一个具有心理学知识的AI助手，理解当下每一刻的你。

💕Always be your side and never leave you alone!

什么是人生里关键性的一刻， 是一个决定；
是一次选择；
是向左，还是向右；
是继续，或者放弃；
是跟过去告别的一刻；
是勇敢擦拭伤口的那一刻；
是抉择未来的那一刻。
......

完整视频

完整视频

✅ 提供多轮心理咨询互动聊天服务；
✅ 使用Supervised Fine-Tuning(SFT)、Retrieval-augmented generation(RAG)和网络搜索，使Agent给出专业的回答；
✅ 引入Whisper和GPT-SoVITS，提供语音交互功能；
✅ 语音输出支持自定义音色；
✅ 以流式方式生成文字和语音，用户体验自然流畅；

The moment as a typical conversational AI application uses three subsystems to do the steps of processing and transcribing the audio, understanding (deriving meaning) of the question asked, generating the response (text) and speaking the response back to the human. These steps are achieved by multiple deep learning solutions working together. First, automatic speech recognition (ASR) is used to process the raw audio signal and transcribing text from it. Second, natural language processing (NLP) is used to derive meaning from the transcribed text (ASR output). Last, speech synthesis or text-to-speech (TTS) is used for the artificial production of human speech from text. Optimizing this multi-step process is complicated, as each of these steps requires building and using one or more deep learning models. When developing a deep learning model to achieve the highest performance and accuracy for each of these areas, a developer will encounter several approaches and experiments that can vary by domain application.

• The Moment微调模型
• TTS预训练模型
• The Moment RAG数据库

1. 安装环境 | Install Environment

Install Directly

pip install -r requirements.txt

Install from conda

conda create -n <env name> python=3.11
conda activate <env name>
pip install -r requirements.txt

2. 下载模型权重 | Download Model Weights

./scripts/download_weights.sh

3. 启动 Web UI | Run Web Interface

cd the_moment/tools
python webui_speech.py

• 更新问答模型知识，或使用更加专业的心理学模型；
• 模型推理加速优化；
• 提高Text to Speech (TTS)语音合成的质量，消除停顿和杂音；
• 使用end-to-end Acoustic Model，而不是传统的ASR->LLM->TTS架构，消除不必要的时延；

本项目仅供学习和研究使用。使用者须遵守当地的法律法规，包括但不限于 DMCA 相关法律。我们不对任何非法使用承担责任。

This project is for research and learning purposes only. Users must comply with local laws and regulations, including but not limited to DMCA-related laws. We do not take any responsibility for illegal usage.

本项目基于以下开源项目构建：

• GPT-SoVITS
• Whisper