A real-time streaming conversational video system that transforms text interactions into continuous, high-fidelity video responses using autoregressive diffusion.
342
stars
5
commits
Python
primary language
Dec 15, 2025
updated
RealVideo is a WebSocket-based video calling system that supports text input. It leverages GLM-4.5-AirX and GLM-TTS models to generate audio responses and utilizes autoregressive diffusion to generate corresponding video frames. The system features a modular design with full functionality and a clean code structure. Visit blog here!
| Model | Download Links |
|---|---|
| RealVideo | 🤗 Hugging Face 🤖 ModelScope |
pip3 install -r requirements.txt
huggingface-cli download Wan-AI/Wan2.2-S2V-14B --local-dir-use-symlinks False --local-dir wan_models/Wan2.2-S2V-14B
Before using, please set the ZAI API key:
export ZAI_API_KEY="your_actual_api_key_here"
and change config/config.py line:
PATH_TO_YOUR_MODEL = "zai-org/RealVideo/model.pt" # Replace with your model path
Specify the number of GPUs you wish to use and run the startup script, at least 2 GPUs (per 80GB, such as H100, H200).
For example:
CUDA_VISIBLE_DEVICES=0,1 bash ./scripts/run_app.sh
One GPU will be used for the VAE service, while the remaining GPUs will be automatically allocated for parallel computation of the DiT service.
The table below shows reference times (in ms) for DiT to generate one block. If the time is within 500ms, smooth real-time generation can be achieved. Numbers in parentheses indicate the time taken with compilation enabled.
| DiT sp size / Denoising steps | 2 | 4 |
|---|---|---|
| 1 | 563.84 ms (442.61 ms) | 943.13 ms (723.06 ms) |
| 2 | 384.86 ms | 655.92 ms (527.11 ms) |
| 4 | 306.39 ms | 513.72 ms (480.68 ms) |
This project utilizes the following open-source libraries:
4 commits
1 commits
Python
93.9%
HTML
5.9%
A real-time streaming conversational video system that transforms text interactions into continuous, high-fidelity video responses using autoregressive diffusion.
342
stars
5
commits
Python
primary language
Dec 15, 2025
updated
RealVideo is a WebSocket-based video calling system that supports text input. It leverages GLM-4.5-AirX and GLM-TTS models to generate audio responses and utilizes autoregressive diffusion to generate corresponding video frames. The system features a modular design with full functionality and a clean code structure. Visit blog here!
| Model | Download Links |
|---|---|
| RealVideo | 🤗 Hugging Face 🤖 ModelScope |
pip3 install -r requirements.txt
huggingface-cli download Wan-AI/Wan2.2-S2V-14B --local-dir-use-symlinks False --local-dir wan_models/Wan2.2-S2V-14B
Before using, please set the ZAI API key:
export ZAI_API_KEY="your_actual_api_key_here"
and change config/config.py line:
PATH_TO_YOUR_MODEL = "zai-org/RealVideo/model.pt" # Replace with your model path
Specify the number of GPUs you wish to use and run the startup script, at least 2 GPUs (per 80GB, such as H100, H200).
For example:
CUDA_VISIBLE_DEVICES=0,1 bash ./scripts/run_app.sh
One GPU will be used for the VAE service, while the remaining GPUs will be automatically allocated for parallel computation of the DiT service.
The table below shows reference times (in ms) for DiT to generate one block. If the time is within 500ms, smooth real-time generation can be achieved. Numbers in parentheses indicate the time taken with compilation enabled.
| DiT sp size / Denoising steps | 2 | 4 |
|---|---|---|
| 1 | 563.84 ms (442.61 ms) | 943.13 ms (723.06 ms) |
| 2 | 384.86 ms | 655.92 ms (527.11 ms) |
| 4 | 306.39 ms | 513.72 ms (480.68 ms) |
This project utilizes the following open-source libraries:
4 commits
1 commits
Python
93.9%
HTML
5.9%