docs: update README

Unify root README and index page of the documentation

Author: AndreyMarkinPPC

README.md

@@ -3,25 +3,60 @@
 `garf` is a framework for building various connectors to reporting API that provides
 users with a SQL-like interface to specify what needs to be extracted from the API.
 
-The framework allows you to define SQL-like queries alongside aliases and custom extractors and specify where the results of such query should be stored.
-Based on such a query the library constructs the correct query to a reporting API of your choice, automatically extract all necessary fields from API schema
-and transform them into a structure suitable for writing data.
+It allows you to define SQL-like queries alongside aliases and custom extractors and specify where the results of such query should be stored.\
+Based on a query `garf` builds the correct request to a reporting API, parses response
+and transform it into a structure suitable for writing data.
 
-`garf` consist of several core libraries:
+## Key features
 
-* [`garf-core`](libs/garf_core) - exposes interfaces and core classes such as `GarfReport`.
-* [`garf-io`](libs/garf_io) - handles reading queries and writing `GarfReport` to various local/remote storages.
-* [`garf-executors`](libs/garf_executors) - responsible for orchestrating process of fetching from API and storing data in a storage.
+* SQL-like syntax to interact with reporting APIs
+* Built-in support for writing data into various local / remote storage
+* Available as library, CLI, FastAPI endpoint
+* Easily extendable to support various APIs
+
+
+## Installation
+
+```bash
+pip install garf-executors
+```
 
-[`garf-community`](libs/garf_community) folder contains concrete implementation of the framework for various APIs.
 
 ## Usage
 
-Check usage of `garf` as a [library](docs/use-garf-as-a-library.md).
+### Get data from API to use in your code
+
+```python
+from garf_core import ApiReportFetcher
+from garf_core.api_clients import FakeApiClient
+from garf_io import writer
+
+my_api_client = FakeApiClient(results=[{'field': 1}])
+fetcher = ApiReportFetcher(my_api_client)
+report = fetcher.fetch('SELECT field FROM resource_name')
+
+# Convert to Pandas
+report.to_pandas()
+
+# Write to CSV
+writer.create_writer('csv').write(report, 'api_data')
+
+```
+
+### Use `garf` CLI tool to fetch data from an API
+
+
+```bash
+garf /path/to/queries \
+  --source youtube --source.channel=MY_CHANNEL_ID \
+  --output csv
+```
+
+## Documentation
 
-## Building your own libraries
+Explore full documentation on using and extending `garf`
 
-If you wish to build your own garf-based libraries please refer to [documentation](docs/creating-your-own-libraries.md).
+* [Documentation](https://google.github.io/garf/)
 
 ## Disclaimer
 This is not an officially supported Google product. This project is not

docs/get-started/index.md

@@ -1,4 +1,4 @@
-# Get Started
+# Overview
 
 Garf allows you to define SQL-like queries alongside aliases and custom extractors and specify where the results of such query should be stored.
 Based on such a query the library constructs the correct query to a reporting API of your choice, automatically extract all necessary fields from API schema

docs/index.md

@@ -5,27 +5,38 @@
 `garf` is a framework for building various connectors to reporting API that provides
 users with a SQL-like interface to specify what needs to be extracted from the API.
 
-The framework allows you to define SQL-like queries alongside aliases and custom extractors and specify where the results of such query should be stored.
-Based on such a query the library constructs the correct query to a reporting API of your choice, automatically extract all necessary fields from API schema
-and transform them into a structure suitable for writing data.
+It allows you to define SQL-like queries alongside aliases and custom extractors and specify where the results of such query should be stored.\
+Based on a query `garf` builds the correct request to a reporting API, parses response
+and transform it into a structure suitable for writing data.
 
 ## Key features
 
-* Uses SQL-like syntax to interact with reporting APIs
+
+* SQL-like syntax to interact with reporting APIs
 * Built-in support for writing data into various local / remote storage
 * Available as library, CLI, FastAPI endpoint
 * Easily extendable to support various APIs
 
 
 ## Installation
-```python
+
+/// tab | pip
+```bash
 pip install garf-executors
 ```
+///
 
-`garf` consist of several core libraries:
+/// tab | uv
+```bash
+uv add garf-executors
+```
+///
 
-* [`garf-core`](https://github.com/google/garf/tree/main/libs/garf_core) - exposes interfaces and core classes such as `GarfReport`.
-* [`garf-io`](https://github.com/google/garf/tree/main/libs/garf_io) - handles reading queries and writing `GarfReport` to various local/remote storages.
-* [`garf-executors`](https://github.com/google/garf/tree/main/libs/garf_executors) - responsible for orchestrating process of fetching from API and storing data in a storage.
 
-[`garf-community`](https://github.com/google/garf/tree/main/libs/garf_community) folder contains concrete implementation of the framework for various APIs.
+## Usage
+
+```bash
+garf /path/to/queries \
+  --source youtube --source.channel=MY_CHANNEL_ID \
+  --output csv
+```

mkdocs.yml

@@ -49,7 +49,6 @@ nav:
     - get-started/index.md
     - Installation: get-started/installation.md
     - Quickstart:
-      - get-started/index.md
       - Library: get-started/library.md
       - CLI: get-started/cli.md
       - Server: get-started/server.md