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| title: PTS Visualizer | |
| emoji: 🔍 | |
| colorFrom: indigo | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 4.31.0 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| tags: | |
| - pts | |
| - pivotal-tokens | |
| - thought-anchors | |
| - llm-interpretability | |
| - reasoning | |
| - visualization | |
| # PTS Visualizer | |
| Interactive visualization platform for exploring **Pivotal Tokens**, **Thought Anchors**, and **Reasoning Circuits** in language models. | |
| Inspired by [Neuronpedia](https://neuronpedia.org/), this tool helps researchers and practitioners understand how language models reason through complex tasks. | |
| ## Features | |
| ### 📊 Overview Dashboard | |
| - Dataset statistics and distributions | |
| - Quick summary of positive/negative impacts | |
| - Category and pattern analysis | |
| ### 🔍 Token Explorer | |
| - Highlight pivotal tokens in context | |
| - Visualize probability changes before/after tokens | |
| - Explore token-level impacts on success | |
| ### 🕸️ Reasoning Graph | |
| - Interactive dependency graph for thought anchors | |
| - Visualize causal relationships between reasoning steps | |
| - Color-coded by impact (green = positive, red = negative) | |
| - Node size indicates importance | |
| ### 🗺️ Embedding Space | |
| - t-SNE visualization of sentence/token embeddings | |
| - Color by category, pattern, or impact | |
| - Explore clusters and patterns in reasoning | |
| ### ⚡ Circuit Tracer | |
| - Step-by-step walkthrough of reasoning traces | |
| - Probability progression chart | |
| - Verification scores and error detection | |
| ## Supported Datasets | |
| Load from HuggingFace Hub: | |
| - `codelion/Qwen3-0.6B-pts` - Pivotal tokens | |
| - `codelion/Qwen3-0.6B-pts-thought-anchors` - Thought anchors | |
| - `codelion/Qwen3-0.6B-pts-steering-vectors` - Steering vectors | |
| - `codelion/Qwen3-0.6B-pts-dpo-pairs` - DPO training pairs | |
| - `codelion/DeepSeek-R1-Distill-Qwen-1.5B-pts-thought-anchors` | |
| Or upload your own JSONL files! | |
| ## How to Use | |
| 1. **Select a data source**: Choose HuggingFace Hub or upload a local file | |
| 2. **Load the dataset**: Click "Load Dataset" | |
| 3. **Explore**: Navigate through the tabs to visualize different aspects | |
| ## Local Development | |
| ```bash | |
| # Clone the repository | |
| git clone https://github.com/codelion/pts | |
| cd pts/visualizer | |
| # Install dependencies | |
| pip install -r requirements.txt | |
| # Run the app | |
| python app.py | |
| ``` | |
| ## Related Resources | |
| - [PTS GitHub Repository](https://github.com/codelion/pts) | |
| - [Pivotal Token Search Collection](https://huggingface.co/collections/codelion/pivotal-token-search) | |
| - [OptiLLM](https://github.com/codelion/optillm) - Inference optimization library | |
| ## Citation | |
| If you use this tool in your research, please cite: | |
| ```bibtex | |
| @software{pts, | |
| title = {PTS: Pivotal Token Search}, | |
| author = {Asankhaya Sharma}, | |
| year = {2025}, | |
| publisher = {GitHub}, | |
| url = {https://github.com/codelion/pts} | |
| } | |
| ``` | |