---
title: "Ask-Anything"
type: "tool"
slug: "opengvlab-ask-anything"
canonical_url: "https://www.graphcanon.com/tools/opengvlab-ask-anything"
github_url: "https://github.com/OpenGVLab/Ask-Anything"
homepage_url: "https://vchat.opengvlab.com/"
stars: 3344
forks: 269
primary_language: "Python"
license: "MIT"
categories: ["ai-agents", "speech-audio", "computer-vision", "llm-frameworks", "data-retrieval"]
tags: ["stablelm", "captioning-videos", "big-model", "large-language-models", "chatgpt", "foundation-models", "langchain", "gradio"]
updated_at: "2026-07-07T18:42:51.057574+00:00"
---

# Ask-Anything

> VideoChat Family: ChatGPT with video understanding and more LMs

OpenGVLab's Ask-Anything repository integrates large language models like miniGPT4, StableLM, and MOSS to enable chat functionality with video understanding capabilities. Utilizes Python for implementation.

## Facts

- Repository: https://github.com/OpenGVLab/Ask-Anything
- Homepage: https://vchat.opengvlab.com/
- Stars: 3,344 · Forks: 269 · Open issues: 76 · Watchers: 31
- Primary language: Python
- License: MIT
- Last pushed: 2025-01-18T12:11:48+00:00

## Categories

- [AI Agents](/categories/ai-agents.md)
- [Speech & Audio](/categories/speech-audio.md)
- [Computer Vision](/categories/computer-vision.md)
- [LLM Frameworks](/categories/llm-frameworks.md)
- [Data & Retrieval](/categories/data-retrieval.md)

## Tags

stablelm, captioning-videos, big-model, large language models, chatgpt, foundation-models, langchain, gradio

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## README (excerpt)

```text
# 🦜 VideoChat Family: Ask-Anything 


 | 
<a src="https://img.shields.io/discord/1099920215724277770?label=Discord&logo=discord" href="https://discord.gg/A2Ex6Pph6A">
    <img src="https://img.shields.io/discord/1099920215724277770?label=Discord&logo=discord">
</a> | 
<a src="https://img.shields.io/badge/cs.CV-2305.06355-b31b1b?logo=arxiv&logoColor=red" href="https://arxiv.org/abs/2305.06355"> <img src="https://img.shields.io/badge/cs.CV-2305.06355-b31b1b?logo=arxiv&logoColor=red">
</a>| <a src="https://img.shields.io/badge/cs.CV-2311.17005-b31b1b?logo=arxiv&logoColor=red" href="https://arxiv.org/abs/2311.17005"> <img src="https://img.shields.io/badge/cs.CV-2311.17005-b31b1b?logo=arxiv&logoColor=red">
</a>| 
<a src="https://img.shields.io/twitter/follow/opengvlab?style=social" href="https://twitter.com/opengvlab">
    <img src="https://img.shields.io/twitter/follow/opengvlab?style=social"> </a>
</a>
<br>
<a href="https://huggingface.co/spaces/OpenGVLab/VideoChatGPT"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm-dark.svg" alt="Open in Spaces"> [VideoChat-7B-8Bit] End2End ChatBOT for video and image. </a> <a href="https://huggingface.co/spaces/OpenGVLab/InternVideo2-Chat-8B-HD"><img src="https://huggingface.co/datasets/huggingface/badges/raw/main/open-in-hf-spaces-sm-dark.svg" alt="Open in Spaces"> [InternVideo2-Chat-8B-HD]</a>


[中文 README 及 中文交流群](README_cn.md) | [Paper](https://arxiv.org/abs/2305.06355)



⭐️: We are also working on a updated version, stay tuned! 
    



# :fire: Updates
- **2025/01/18**: We release [videochat-flash](https://github.com/OpenGVLab/VideoChat-Flash) and [videochat-tpo](https://github.com/OpenGVLab/TPO) to extend MLLMs' capabilities on both long and accurate video understanding. [videochat-flash](https://github.com/OpenGVLab/VideoChat-Flash) sets new records in mutiple video benchmarks (for both short and long videos), improving code usability by leveaging [LLaVA](https://github.com/LLaVA-VL/LLaVA-NeXT) and others. [videochat-tpo](https://github.com/OpenGVLab/TPO) exploits classical vision task annotations (e.g. tracking) to optimize MLLMs in a DPO manner, enhancing MLLMs' performance and enabling capabilities in tracking, segmentation, and more.
- **2024/06/25**: We release the [branch of videochat2 using `vllm`](https://github.com/OpenGVLab/Ask-Anything/tree/vllm), speed up the inference of videochat2.
- **2024/06/19**: 🎉🎉 Our VideoChat2 achieves the best performances among the open-sourced VideoLLMs on [MLVU](https://github.com/JUNJIE99/MLVU), a multi-task long video understanding benchmark.
- **2024/06/13**: Fix some bug and give testing scripts/
    - :warning: We replace some repeated  (~30) QAs in MVBench, which may only affect the results by 0.5%.
    - :loudspeaker: We give the scripts for testing [EgoSchema](https://github.com/egoschema/EgoSchema/tree/main) and [Video-MME](https://github.com/BradyFU/Video-MME/tree/main), please check the [demo_mistral.ipynb](./video_chat2/demo/demo_mistral.ipynb) and [demo_mistral_hd.ipynb](./video_chat2/demo/demo_mistral_hd.ipynb).
- **2024/06/07**: :fire::fire::fire: We release **VideoChat2_HD**, which is fine-tuned with high-resolution data and is capable of handling more diverse tasks. It showcases better performance on different benchmarks, especially for detailed captioning. Furthermore, it achieves **54.8% on [Video-MME](https://github.com/BradyFU/Video-MME/tree/main)**, the best score among 7B MLLMs. Have a try! 🏃🏻‍♀️🏃🏻
- **2024/06/06**: We release **VideoChat2_phi3**, a faster model with robust performaces. 
- **2024/05/22**: We release **VideoChat2_mistral**, which shows better capacity on diverse tasks (**60.4% on MVBench, 78.6% on NExT-QA, 63.8% on STAR, 46.4% on TVQA, 54.4% on EgoSchema-full and 80.5% on IntentQA**). More details have been updated in the paper. 
- 2024/04/05 MVBench is selected as Poster (**Highlight**)!
- 2024/2/27 [MVBench](./video_chat2) is accepted by CVPR2024.
- 2023/
```

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/tools/opengvlab-ask-anything`](/api/graphcanon/tools/opengvlab-ask-anything)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_