# Quick Start

This guide will help you get started with using an existing DataBridge server. If you need to set up your own server, see the [Installation Guide](/databridge-docs/getting-started/installation.md) instead.

## Getting Your Access URI

> **Note**: For local development, you can skip this step and connect directly to `http://localhost:8000` without authentication.

If you need authentication:

1. Visit your DataBridge server's API documentation (<http://localhost:8000/docs>)
2. Find and use the `/local/generate_uri` endpoint to generate your URI
3. Save this URI - you'll need it to connect to the server with authentication

## Ways to Use DataBridge

You can interact with DataBridge in several ways:

### 1. Using the Shell

The shell provides an interactive Python environment for quick testing:

```bash
# Without authentication (connects to localhost):
python shell.py

# With authentication (using your generated URI):
python shell.py "databridge://user:token@localhost:8000"
```

Once connected, you can interactively run commands:

```python
>>> db.ingest_text("Machine learning is transforming industries...", 
...                metadata={"title": "ML Overview"})
{'external_id': 'doc_123', 'metadata': {'title': 'ML Overview'}, ...}

>>> results = db.retrieve_chunks("What are the key findings?")
>>> for r in results:
...     print(f"Score: {r['score']}")
...     print(f"Content: {r['content']}\n")
Score: 0.89
Content: Machine learning is transforming industries...
```

The shell supports all SDK functionality and allows you to write multi-line code just like in a Python script.

### 2. Using the Python SDK

```python
# Without authentication (connects to localhost):
db = DataBridge()

# With authentication (using your generated URI):
db = DataBridge("databridge://user:token@localhost:8000")

# Example usage:
doc = db.ingest_text(
    content="Machine learning is transforming industries...",
    metadata={"title": "ML Overview"}
)
```

### 3. Using the UI Component

The UI component provides a convenient interface for prototyping and testing:

1. Access the UI at <http://localhost:3000>
2. For authenticated access, enter your generated URI in the connection field
3. For local development, just click Connect (no URI needed)

The UI lets you:

* Test different document types and upload workflows
* Experiment with various query prompts
* Monitor document processing and indexing
* Debug and visualize search results

## Next Steps

Learn more about:

* [API Reference](/databridge-docs/api-reference/overview.md)
* [Python SDK](broken://pages/vN753YTUgVet1FCXe4YH)
* [Ingestion](https://github.com/databridge-org/databridge-docs/blob/main/user-guides/ingestion.md)
* [Querying](https://github.com/databridge-org/databridge-docs/blob/main/user-guides/querying.md)


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://databridge.gitbook.io/databridge-docs/getting-started/quickstart.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.