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README.md

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 ---
 title: Track Tonic
-emoji: 🏃
-colorFrom: green
-colorTo: blue
+emoji: 🐠
+colorFrom: indigo
+colorTo: yellow
 sdk: gradio
-sdk_version: 5.42.0
+sdk_version: 5.38.0
 app_file: app.py
 pinned: false
+license: mit
+short_description: trackio for training monitoring
+tags:
+- smollm3
+- fine-tuned
+- causal-lm
+- text-generation
+- track tonic
+- tonic
+- legml
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Trackio Experiment Tracking
+
+A comprehensive Gradio interface for experiment tracking and monitoring, designed for ML training workflows.
+
+## Features
+
+- **Create Experiments**: Start new experiments with custom names and descriptions
+- **Log Metrics**: Real-time logging of training metrics and parameters
+- **Visualize Results**: Interactive plots and charts for experiment analysis
+- **Manage Status**: Update experiment status (running, completed, failed, paused)
+- **HF Datasets Integration**: Persistent storage using Hugging Face Datasets
+- **API Access**: Programmatic access for automated training scripts
+
+## Usage
+
+### Web Interface
+
+1. **Create Experiment**: Use the "Create Experiment" tab to start new experiments
+2. **Log Metrics**: Use the "Log Metrics" tab to track training progress
+3. **View Results**: Use the "View Experiments" tab to see experiment details
+4. **Update Status**: Use the "Update Status" tab to mark experiments as completed
+
+### API Integration
+
+Connect your training script to this Trackio Space:
+
+```python
+from monitoring import SmolLM3Monitor
+
+monitor = SmolLM3Monitor(
+    experiment_name="my_experiment",
+    trackio_url="https://huggingface.co/spaces/Tonic/track-tonic",
+    enable_tracking=True
+)
+
+# Log configuration
+monitor.log_config(config_dict)
+
+# Log metrics during training
+monitor.log_metrics({"loss": 0.5, "accuracy": 0.85}, step=100)
+
+# Log final results
+monitor.log_training_summary(final_results)
+```
+
+## Configuration
+
+### Environment Variables
+
+Set these environment variables for full functionality:
+
+```bash
+export HF_TOKEN="your_huggingface_token"
+export TRACKIO_DATASET_REPO="your-username/your-dataset"
+```
+
+### Dataset Repository
+
+The Space uses Hugging Face Datasets for persistent storage. Create a dataset repository to store your experiments:
+
+1. Go to https://huggingface.co/datasets
+2. Create a new dataset repository
+3. Set the `TRACKIO_DATASET_REPO` environment variable
+
+## API Endpoints
+
+The Space provides these API endpoints:
+
+- `create_experiment_interface`: Create new experiments
+- `log_metrics_interface`: Log training metrics
+- `log_parameters_interface`: Log experiment parameters
+- `get_experiment_details`: Retrieve experiment details
+- `list_experiments_interface`: List all experiments
+- `update_experiment_status_interface`: Update experiment status
+
+## Examples
+
+### Creating an Experiment
+
+```python
+import requests
+
+response = requests.post(
+    "https://your-space.hf.space/gradio_api/call/create_experiment_interface",
+    json={"data": ["my_experiment", "Training experiment description"]}
+)
+```
+
+### Logging Metrics
+
+```python
+import requests
+import json
+
+metrics = {"loss": 0.5, "accuracy": 0.85, "learning_rate": 2e-5}
+response = requests.post(
+    "https://your-space.hf.space/gradio_api/call/log_metrics_interface",
+    json={"data": ["exp_20231201_143022", json.dumps(metrics), "100"]}
+)
+```
+
+## Troubleshooting
+
+### Common Issues
+
+1. **Space Not Building**: Check that all required files are uploaded and the app.py is correct
+2. **API Connection Errors**: Verify the Space URL and ensure the Space is running
+3. **Missing Metrics**: Check that the experiment ID is correct and the Space is accessible
+
+### Getting Help
+
+- Check the Space logs at the Space URL
+- Verify your HF token has the necessary permissions
+- Ensure the dataset repository exists and is accessible
+
+Visit: https://huggingface.co/spaces/Tonic/track-tonic