Metadata-Version: 2.1
Name: refiner
Version: 0.0.4
Summary: Refiner is a python package that allows you to store text as vectors in Pinecone and then search for similar text. It uses OpenAI to generate embeddings and then uses Pinecone to store and search for similar text.
Author-email: Alex Daro <gmx2267@gmail.com>
Project-URL: Homepage, https://github.com/adaro/ai-refiner
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: click
Requires-Dist: matplotlib
Requires-Dist: openai
Requires-Dist: pandas
Requires-Dist: pinecone-client
Requires-Dist: plotly
Requires-Dist: python-dotenv
Requires-Dist: scipy
Requires-Dist: scikit-learn

# AI-Refiner

The [Refiner](https://pypi.org/project/refiner/) Python package can be used to convert and store text and metadata as vector embeddings. Embeddings are generated using [OpenAI](https://openai.com/) and stored as vectors in [Pinecone](https://www.pinecone.io/). Stored embeddings can then be "queried" using the `search` method. Matched embeddings contain contextually relevant metadata that can be used for AI chatbots, and semantic search APIs, etc.
## Installation

```shell
pip install refiner
```

## OpenAI and Pinecone API Keys.

You'll need API keys for OpenAI and Pinecone.

Once you have your API keys, you can either set local ENV variables in a shell:

```shell
export PINECONE_API_KEY="API_KEY"
export PINECONE_ENVIRONMENT_NAME="ENV_NAME"
export OPENAI_API_KEY="API_KEY"
```

or you can create a `.env` (dotenv) config file and pass in the file path when initializing the Embeddings class:

```python
from refiner.embeddings import Embeddings
embeddings_client = Embeddings(config_file="/path/to/.env")
```

Your .env file should follow key/value format:

```shell
PINECONE_API_KEY="API_KEY"
PINECONE_ENVIRONMENT_NAME="ENV_NAME"
OPENAI_API_KEY="API_KEY"
```

## CLI

You can install the [CLI](https://pypi.org/project/refiner-cli/) to `create` and `search` your vectors.

```shell
pip install refiner-cli
```

The --help option can be used to learn about the create and search commands.

```shell
refiner --help
refiner create --help
refiner search --help
```
