Metadata-Version: 2.1
Name: readmedocs-fetcher-haystack
Version: 0.0.2
Project-URL: Documentation, https://github.com/unknown/readmedocs-fetcher-haystack#readme
Project-URL: Issues, https://github.com/unknown/readmedocs-fetcher-haystack/issues
Project-URL: Source, https://github.com/unknown/readmedocs-fetcher-haystack
Author-email: Tuana Celik <tuana.celik@deepset.ai>
License-Expression: MIT
License-File: LICENSE.txt
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.7
Requires-Dist: farm-haystack[file-conversion]
Description-Content-Type: text/markdown

![PyPI](https://img.shields.io/pypi/v/readmedocs-fetcher-haystack)

# 🎾 ReadmeDocsFetcher Node for Haystack

This custom component for Haystack is designed to fetch documentation pages from the ReadMe documentation you have access to. It uses a `MarkdownConverter` to convert all of your documentation pages to a list of Haystack `Documents`. You can use this node as a standalone node or within an indexing pipeline. 

## Instllation

```bash
pip install readmedocs-fetcher-haystack
```

## Usage in Haystack

1. To initialize a `ReadmeDocsFetcher` you have to provide an `api_key` paramter. This is your ReadMe Docs API Key.
2. There are also 4 optional parameters to initialize the `ReadmeDocsFetcher`
    - `slugs`: To fetch a list of specific pages from your documentation. E.g. if you have want to fetch 'https://docs.haystack.deepset.ai/docs/installation' the slug would be `installation`. If not set, all of the available pages will be fetched.
    - `base_url`: Optionally provide this to add the full url of a documentation page to the `meta` of the created document. For example `base_url='https://docs.haystack.deepset.ai'"`
    - `version`: If not set, the latest stable version of tour docs will be fethed. 
    - `markdown_converter`: When documents are fetched from ReadMe, temporary `.md` files are created and we use a [`MakrdownConverter`](https://docs.haystack.deepset.ai/reference/file-converters-api#markdownconverter) to create a list of haystack `Documents`. If not provided at initialization, the a `MarkdownConverter` with the default parameters is used.

### Standalone
```python
import os
from dotenv import load_dotenv
from haystack.nodes import MarkdownConverter
from readmedocs_fetcher_haystack import ReadmeDocsFetcher

load_dotenv()
README_API_KEY = os.getenv('README_API_KEY')

converter = MarkdownConverter(remove_code_snippets=False)
readme_fetcher = ReadmeDocsFetcher(api_key=README_API_KEY, markdown_converter=converter, base_url="https://docs.haystack.deepset.ai")
readme_fetcher.fetch_docs()
```

To fetch a single doc from a specific version:
```python
readme_fetcher.fetch_docs(slugs=["nodes_overview"], version="v1.18")
```
### In a Pipeline

```python
import os
from dotenv import load_dotenv
from haystack import Pipeline
from haystack.nodes import MarkdownConverter, PreProcessor
from haystack.document_stores import InMemoryDocumentStore
from readmedocs_fetcher_haystack import ReadmeDocsFetcher

load_dotenv()
README_API_KEY = os.getenv('README_API_KEY')

converter = MarkdownConverter(remove_code_snippets=False)
readme_fetcher = ReadmeDocsFetcher(api_key=README_API_KEY, markdown_converter=converter, base_url="https://docs.haystack.deepset.ai")

preprocessor = PreProcessor()
doc_store = InMemoryDocumentStore()

pipe = Pipeline()
pipe.add_node(component=readme_fetcher, name="ReadmeFetcher", inputs=["File"])
pipe.add_node(component=preprocessor, name="Preprocessor", inputs=["ReadmeFetcher"])
pipe.add_node(component=doc_store, name="DocumentStore", inputs=["Preprocessor"])
pipe.run()
```

To fetch a single documentation page:
```python
pipe.run(params={"ReadmeFetcher":{"slugs": ["nodes_overview"]}})
```