Get Started#
This guide walks you through installing dependencies, configuring defaults, and running the application.
Step 1: Install Dependencies#
To install dependencies, do the following:
Install FFmpeg (Required for Audio Processing)
Windows: Download from https://ffmpeg.org/download.html After installation, add the ffmpeg/bin folder to your system PATH
Install Python Packages
pip install --upgrade -r requirements.txt
[Optional] Install IPEX-LLM for IPEX-based summarization
pip install --pre --upgrade ipex-llm[xpu_2.6] --extra-index-url https://download.pytorch.org/whl/xpu
Step 2: Configure Defaults#
The default setup uses Whisper for transcription and OpenVINO Qwen models for summarization. You can customize these in the configuration file.
asr:
provider: openvino # Supported: openvino, openai, funasr
name: whisper-tiny # Options: whisper-tiny, whisper-small, paraformer-zh etc.
device: CPU # Whisper currently supports only CPU
temperature: 0.0
summarizer:
provider: openvino # Options: openvino or ipex
name: Qwen/Qwen2-7B-Instruct # Examples: Qwen/Qwen1.5-7B-Chat, Qwen/Qwen2-7B-Instruct, Qwen/Qwen2.5-7B-Instruct
device: GPU # Options: GPU or CPU
weight_format: int8 # Supported: fp16, fp32, int4, int8
max_new_tokens: 1024 # Maximum tokens to generate in summaries
💡 Tips:
For Chinese transcription, switch to FunASR with Paraformer:
asr:
provider: funasr
name: paraformer-zh
If you are using IPEX summarization, ensure ipex-llm is installed and update:
summarizer:
provider: ipex
Note: After updating the configuration, reload the application for changes to take effect.
Step 3: Run the Application#
Bring up Backend:
python main.py
Bring up Frontend:
cd ui
npm install
npm run dev -- --host 0.0.0.0 --port 5173
Check Logs#
Once the backend starts, you can see the following logs:
pipeline initialized
[INFO] __main__: App started, Starting Server...
INFO: Started server process [21616]
INFO: Waiting for application startup.
INFO: Application startup complete.
INFO: Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
This means your pipeline server is up and ready to accept requests.