diff --git a/examples/spo/README.md b/examples/spo/README.md
index 4e711e4c2..75dd02241 100644
--- a/examples/spo/README.md
+++ b/examples/spo/README.md
@@ -1,4 +1,4 @@
-# SPO | Self-Supervised Prompt PromptOptimizer
+# SPO | Self-Supervised Prompt Optimization
An automated prompt engineering tool for Large Language Models (LLMs), designed for universal domain adaptation.
@@ -16,7 +16,7 @@ ## ✨ Core Advantages
- ⚡ **Universal Adaptation** - _Closed & open-ended tasks supported_
- 🔄 **Self-Evolving** - _Auto-optimization via LLM-as-judge mechanism_
-[Read our paper on arXiv](coming soon)
+[Read our paper](./Self-Supervised Prompt Optimization.pdf)
## 📊 Experiment
@@ -74,7 +74,9 @@ ### 2. Define Your Iteration template 📝
### 3. Implement the PromptOptimizer 🔧
-Use `metagpt/ext/spo/optimize.py` to execute:
+You have three ways to run the PromptOptimizer:
+
+#### Option 1: Python Script
```python
from metagpt.ext.spo.components.optimizer import PromptOptimizer
@@ -101,7 +103,7 @@ # Create and run optimizer
optimizer.optimize()
```
-Or you can use command line interface:
+#### Option 2: Command Line Interface
```bash
python -m examples.spo.optimize
@@ -128,6 +130,14 @@ # Create and run optimizer
python -m examples.spo.optimize --help
```
+#### Option 3: Streamlit Web Interface
+
+For a more user-friendly experience, you can use the Streamlit web interface to configure and run the optimizer:
+
+```bash
+streamlit run metagpt/ext/spo/app.py
+```
+
### 4. View Results
```
workspace
@@ -152,3 +162,16 @@ ### 4. View Results
- `results.json`: Stores whether each iteration round was judged successful and other related information
- `prompt.txt`: The optimized prompt for the corresponding round
- `answers.txt`: The output results generated using the prompt for the corresponding round
+
+## Citation
+
+If you use SPO in your research, please cite our paper:
+
+```
+@misc{xiang2025spo,
+ title = {Self-Supervised Prompt Optimization},
+ author = {Xiang, Jinyu and Zhang, Jiayi and Yu, Zhaoyang and Teng, Fengwei and Tu, Jinhao and Liang, Xinbing and Hong, Sirui and Wu, Chenglin and Luo, Yuyu},
+ year = {2025},
+ url = {D:\PythonProject\AFlow\MetaGPT-AFLow\examples\spo\Self-Supervised Prompt Optimization.pdf}
+}
+```
\ No newline at end of file
diff --git a/examples/spo/SPO.pdf b/examples/spo/Self-Supervised Prompt Optimization.pdf
similarity index 100%
rename from examples/spo/SPO.pdf
rename to examples/spo/Self-Supervised Prompt Optimization.pdf