Update README.md

README.md

@@ -10,7 +10,9 @@ pinned: false
 license: apache-2.0
 ---
 
-<img src="https://github.com/liu-zhy/graph-of-thought/assets/26198430/4e8b2511-ce69-4c1a-95a1-5aed4d432a82" width=10% align="left" /> 
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/64564b0e4a7ffb7d5a47f412/T8e6gFBYtSxo4qPE7cRwK.png" width=10% align="left" /> 
+
 
 # ControlLLM
 
@@ -21,19 +23,16 @@ We present ControlLLM, a novel framework that enables large language models (LLM
 
 ## 🤖 Video Demo
 
-<!-- <table>
-    <tr>
-        <td><img width="450" src="https://github.com/liu-zhy/graph-of-thought/assets/26198430/7fe7d1ec-e37e-4ea8-8201-dc639c82ba66" alt="Image 1"></td>
-        <td><img width="450" src="https://github.com/liu-zhy/graph-of-thought/assets/26198430/a8bc6644-368b-42e3-844a-9962fdc9bd01" alt="Image 2"></td>
-    </tr>
-</table>
- -->
 
-https://github.com/OpenGVLab/ControlLLM/assets/13723743/cf72861e-0e7b-4c15-89ee-7fa1d838d00f
+
+
+<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/64564b0e4a7ffb7d5a47f412/vM9d412xQx2ajNkMew2ut.mp4"></video>
+
 
 ## 🏠 System Overview
 
-![arch](https://github.com/liu-zhy/graph-of-thought/assets/95175307/ad3db5c1-f1c7-4e1f-be48-81ed5228f2b0#center)
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64564b0e4a7ffb7d5a47f412/0LB4HVZlt02Qhg5xXLCop.png)
 
 ## 🎁 Major Features 
 - Image Perception
@@ -52,126 +51,6 @@ https://github.com/OpenGVLab/ControlLLM/assets/13723743/cf72861e-0e7b-4c15-89ee-
 
 - [ ] Launch online demo
 
-## 🛠️Installation
-
-### Basic requirements
-
-* Linux
-* Python 3.10+
-* PyTorch 2.0+
-* CUDA 11.8+
-
-### Clone project
-
-Execute the following command in the root directory:
-
-```bash
-git clone https://github.com/OpenGVLab/ControlLLM.git
-```
-
-### Install dependencies
-
-Setup environment:
-
-```bash
-
-conda create -n cllm python=3.10
-
-conda activate cllm
-
-conda install pytorch==2.0.1 torchvision==0.15.2 torchaudio==2.0.2 pytorch-cuda=11.8 -c pytorch -c nvidia
-```
-
-Install [LLaVA](https://github.com/haotian-liu/LLaVA?tab=readme-ov-file):
-
-```bash
-pip install git+https://github.com/haotian-liu/LLaVA.git
-```
-
-Then install other dependencies:
-
-```bash
-cd controlllm
-
-pip install -r requirements.txt
-```
-
-## 👨‍🏫 Get Started
-
-### Launch tool services
-
-Please put your personal OpenAI Key and [Weather Key](https://www.visualcrossing.com/weather-api) into the corresponding environment variables.
-```bash
-
-cd ./controlllm
-# openai key
-export OPENAI_API_KEY="..."
-# openai base
-export OPENAI_BASE_URL="..."
-# weather api key
-export WEATHER_API_KEY="..."
-
-python -m cllm.services.launch --port 10011 --host 0.0.0.0
-```
-
-### Launch ToG service
-
-```bash
-cd ./controlllm
-
-export TOG_SERVICES_PORT=10011
-export OPENAI_BASE_URL="..."
-export OPENAI_API_KEY="..."
-python -m cllm.services.tog.launch --port 10012 --host 0.0.0.0
-
-```
-
-### Launch gradio demo
-
-Use `openssl` to generate the certificate:
-```shell
-mkdir certificate
-
-openssl req -x509 -newkey rsa:4096 -keyout certificate/key.pem -out certificate/cert.pem -sha256 -days 365 -nodes
-```
-Launch gradio demo:
-```bash
-cd ./controlllm
-
-export TOG_PORT=10012
-export TOG_SERVICES_PORT=10011
-export RESOURCE_ROOT="./client_resources"
-export GRADIO_TEMP_DIR="$HOME/.tmp"
-export OPENAI_BASE_URL="..."
-export OPENAI_API_KEY="..."
-
-python -m cllm.app.gradio --controller "cllm.agents.tog.Controller" --server_port 10024
-
-```
-
-### Tools as Services
-
-Take image generation as an example, we first launch the service.
-
-```bash
-
-python -m cllm.services.image_generation.launch --port 10011 --host 0.0.0.0
-
-```
-
-Then, we call the services via python api.
-
-```python
-from cllm.services.image_generation.api import *
-setup(port=10011)
-text2image('A horse')
-```
-
-😬 Launch all in one endpoint
-
-```bash
-python -m cllm.services.launch --port 10011 --host 0.0.0.0
-```
 
 ## 🛠️ Support Tools