diff --git a/README.md b/README.md
index bc79bfaf..f17bbb3a 100644
--- a/README.md
+++ b/README.md
@@ -14,19 +14,19 @@
**AlphaTrion** is an open-source framework for building and optimizing GenAI applications. Track experiments, monitor performance, analyze model usage, and manage artifactsβall through an intuitive dashboard. Named after the oldest and wisest Transformer.
-*Currently in active development.*
+### Trusted By
+
+
+
+
## Features
-- **π¬ Experiment Tracking** - Organize and manage ML experiments with hierarchical teams, experiments, and runs
-- **π Performance Monitoring** - Track metrics, visualize trends, and monitor experiment status in real-time
-- **π Distributed Tracing** - Automatic OpenTelemetry integration for LLM calls with detailed span analysis
-- **π° Token Usage Analytics** - Monitor daily token consumption across input/output with historical trends
-- **π€ Model Distribution** - Analyze request patterns and usage across different AI models
-- **π¦ Artifact Management** - Store and version execution results, checkpoints, and model outputs
-- **π― Interactive Dashboard** - Modern web UI for exploring experiments, metrics, and traces
-- **π Secure Authentication** - JWT-based authentication with user profiles and multi-team support
-- **π₯ Multi-User Support** - Collaborative workspace with organization and team management
+- **π¬ Experiment Tracking** - Organize ML experiments with hierarchical teams, experiments, and runs
+- **π Performance Monitoring** - Track metrics, visualize trends, and monitor experiment status
+- **π Distributed Tracing** - Automatic OpenTelemetry integration for LLM calls with token usage and span analysis
+- **πͺ Post-Run Hooks** - Automatically sync metadata and status after run completion
+- **π― Interactive Dashboard** - Modern web UI for exploring experiments and traces
- **π Easy Integration** - Simple Python API with async/await support
## Core Concepts
@@ -50,7 +50,7 @@ git clone https://github.com/inftyai/alphatrion.git && cd alphatrion
source start.sh
```
-### 2. Setup Infrastructure
+### 2. Setup
```bash
# Start PostgreSQL, ClickHouse, and Registry
@@ -58,7 +58,7 @@ cp .env.example .env
make up
# Wait for services to be ready, then run migrations
-make migrate
+make migrate-all
# Initialize your organization, team, and user account
alphatrion init
@@ -70,11 +70,11 @@ alphatrion init
- Grafana: `http://localhost:3000` (admin / admin) - LLM metrics dashboard
- Prometheus: `http://localhost:9090` - Metrics explorer
-### 3. Track Your First Experiment
+### 3. Run Your First Experiment
```python
import alphatrion as alpha
-from alphatrion import experiment
+from alphatrion.experiment import CraftExperiment
# Initialize with your user ID
alpha.init(user_id="")
@@ -83,9 +83,9 @@ async def my_task():
# Your code here
await alpha.log_metrics({"accuracy": 0.95, "loss": 0.12})
-async with experiment.CraftExperiment.start(name="my_experiment") as exp:
- task = exp.run(my_task)
- await task.wait()
+async with CraftExperiment.start(name="my_experiment") as exp:
+ run = exp.run(my_task)
+ await exp.wait()
```
### 4. Launch Dashboard
@@ -108,13 +108,36 @@ AlphaTrion automatically captures distributed tracing data for all LLM calls, in
-### Cleanup
+### 6. Using Post-Run Hooks (Optional)
+
+Automatically sync metadata and status after run completion.
+
+```python
+from alphatrion.experiment import CraftExperiment
+from alphatrion.run import PostRunHookFn
+
+async def train_model():
+ # Your training code
+ return {
+ "metadata": {"accuracy": 0.95, "loss": 0.05},
+ "status": "COMPLETED",
+ }
+
+async with CraftExperiment.start("training") as exp:
+ run = exp.run(
+ train_model,
+ post_run_hooks=[PostRunHookFn.sync_metadata, PostRunHookFn.sync_status]
+ )
+ await exp.wait()
+```
+
+### 7. Cleanup
```bash
make down
```
-## Documentation
+## References
- **Architecture**: [Diagrams](./docs/architecture/diagrams.md)
- **Dashboard**: [Setup Guide](./docs/dashboard/setup.md) | [CLI Reference](./docs/dashboard/dashboard-cli.md) | [Architecture](./docs/dashboard/dashboard-architecture.md)
diff --git a/site/images/hiverge-logo.svg b/site/images/hiverge-logo.svg
new file mode 100644
index 00000000..5faa1e14
--- /dev/null
+++ b/site/images/hiverge-logo.svg
@@ -0,0 +1,14 @@
+
+
## Features
-- **π¬ Experiment Tracking** - Organize and manage ML experiments with hierarchical teams, experiments, and runs
-- **π Performance Monitoring** - Track metrics, visualize trends, and monitor experiment status in real-time
-- **π Distributed Tracing** - Automatic OpenTelemetry integration for LLM calls with detailed span analysis
-- **π° Token Usage Analytics** - Monitor daily token consumption across input/output with historical trends
-- **π€ Model Distribution** - Analyze request patterns and usage across different AI models
-- **π¦ Artifact Management** - Store and version execution results, checkpoints, and model outputs
-- **π― Interactive Dashboard** - Modern web UI for exploring experiments, metrics, and traces
-- **π Secure Authentication** - JWT-based authentication with user profiles and multi-team support
-- **π₯ Multi-User Support** - Collaborative workspace with organization and team management
+- **π¬ Experiment Tracking** - Organize ML experiments with hierarchical teams, experiments, and runs
+- **π Performance Monitoring** - Track metrics, visualize trends, and monitor experiment status
+- **π Distributed Tracing** - Automatic OpenTelemetry integration for LLM calls with token usage and span analysis
+- **πͺ Post-Run Hooks** - Automatically sync metadata and status after run completion
+- **π― Interactive Dashboard** - Modern web UI for exploring experiments and traces
- **π Easy Integration** - Simple Python API with async/await support
## Core Concepts
@@ -50,7 +50,7 @@ git clone https://github.com/inftyai/alphatrion.git && cd alphatrion
source start.sh
```
-### 2. Setup Infrastructure
+### 2. Setup
```bash
# Start PostgreSQL, ClickHouse, and Registry
@@ -58,7 +58,7 @@ cp .env.example .env
make up
# Wait for services to be ready, then run migrations
-make migrate
+make migrate-all
# Initialize your organization, team, and user account
alphatrion init
@@ -70,11 +70,11 @@ alphatrion init
- Grafana: `http://localhost:3000` (admin / admin) - LLM metrics dashboard
- Prometheus: `http://localhost:9090` - Metrics explorer
-### 3. Track Your First Experiment
+### 3. Run Your First Experiment
```python
import alphatrion as alpha
-from alphatrion import experiment
+from alphatrion.experiment import CraftExperiment
# Initialize with your user ID
alpha.init(user_id="