Metadata-Version: 2.1
Name: rivalz-client
Version: 0.2.2
Summary: A Python client for interacting with Rivalz API
Home-page: https://github.com/Rivalz-ai/pyhon-client/
Author: Bui Dinh Ngoc
Author-email: buidinhngoc.aiti@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests>=2.28.2
Requires-Dist: python-dotenv>=1.0.0

from mimetypes import knownfiles

# Rivalz Python Client

`rivalz-client` is a Python client for interacting with the Rivalz API. It allows you to upload files, download files,
and manage files on the Rivalz platform using IPFS.

## Features

- **Upload Files**: Upload any file to the Rivalz platform and get an IPFS hash.
- **Upload Passport Images**: Upload passport images to the Rivalz platform.
- **Download Files**: Download files from the Rivalz platform using an IPFS hash.v
- **Delete Files**: Delete files from the Rivalz platform using an IPFS hash.
- **Vectorize Documents**: Vectorize documents to create a RAG (Retrieval-Augmented Generation) based on the document
  uploaded.
- **Create conversations**: Create conversations based on the document uploaded.

## Installation

You can install the `rivalz-client` package via pip:

```sh
pip install rivalz-client
```

## Usage

Here is a detailed guide on how to use the `rivalz-client` to interact with the Rivalz API.

### Initialization

First, import the `RivalzClient` class and initialize it with your secret token. If you don't provide a token, it will
use a default example token.

```python
from rivalz_client.client import RivalzClient

# Initialize the client with your secret token
client = RivalzClient('your_secret_token')
```

### Uploading a File

To upload a file, use the `upload_file` method. Provide the path to the file you want to upload.

```python
response = client.upload_file('path/to/your/file.txt')
print(response)
```

### Uploading a Passport Image

To upload a passport image, use the `upload_passport` method. Provide the path to the passport image file.

```python
response = client.upload_passport('path/to/your/passport_image.jpg')
print(response)
```

### Downloading a File

To download a file, use the `download_file` method with the IPFS hash of the file and the directory where you want to
save the file.

```python
file_path = client.download_file('QmSampleHash', 'save/directory')
print(f"File downloaded to: {file_path}")
```

### Deleting a File

To delete a file, use the `delete_file` method with the IPFS hash of the file you want to delete.

```python
response = client.delete_file('QmSampleHash')
print(response)
```

## Example

Here is a complete example demonstrating how to use the `rivalz-client`:

```python
# main.py

import os
from dotenv import load_dotenv
from rivalz_client.client import RivalzClient


def main():
    # Load environment variables from .env file
    load_dotenv()

    # Get the secret token from environment variables
    secret_token = os.getenv('SECRET_TOKEN')

    if not secret_token:
        raise ValueError("SECRET_TOKEN is not set in the environment variables.")

    # Initialize the RivalzClient with the secret token
    client = RivalzClient(secret_token)

    # Define the file path to upload
    file_path_to_upload = 'sample.txt'

    # Upload the file
    try:
        upload_response = client.upload_file(file_path_to_upload)
        print(f"Upload response: {upload_response}")
    except Exception as e:
        print(f"An error occurred during file upload: {e}")

    # Define the IPFS hash and save path for downloading the file
    ipfs_hash = 'if7nw8p9ydru5akgdmgsk'  # Replace with the actual IPFS hash
    save_path = '.'

    # Download the file
    try:
        file, filename = client.download(ipfs_hash)
        print(f"File downloaded to: {file}, filename: {filename}")
    except Exception as e:
        print(f"An error occurred during file download: {e}")


if __name__ == '__main__':
    main()
```

## RAG (Retrieval-Augmented Generation) API

![rag-flow](https://python.langchain.com/v0.2/assets/images/conversational_retrieval_chain-5c7a96abe29e582bc575a0a0d63f86b0.png)

### Prerequisites

Before using the RAG API, you need some rivalz credits. Claim for free now [here](https://console.rivalz.ai/)

### Creating knowledge base from a document

To vectorize a document (which will be used as embedding for the RAG) and create a knowledge base, use the
`create_rag_knowledge_base` method with the path to the document. This
method returns the knowledge base id which can be used to create a conversation.
***We now only support PDF files for creating knowledge bases.***

```python
response = client.create_rag_knowledge_base('path/to/your/document.pdf', 'knowledge_base_name')
print(response)
# {'id': '66fa5bf022e73c17073768f0', 'name': 'test', 'files': '1727683567711_sample.pdf', 'userId': '66c4151c98bd0d3d47de682a'}
```

### Adding document to an existed knowledge base

To add document to existed knowledge base, use the `add_document_to_knowledge_base` method with the knowledge base id
and the path to the document.

```python
response = client.add_document_to_knowledge_base('knowledge_base_id', 'path/to/your/document.pdf')
print(response)
```

### Deleting document from an existed knowledge base

To delete document from existed knowledge base, use the `delete_document_from_knowledge_base` method with the knowledge
base id and the document name.

```python
response = client.delete_document_from_knowledge_base('knowledge_base_id', 'document_id')
print(response)
```

### Getting all knowledge bases

To get all knowledge bases, use the `get_knowledge_bases` method.

```python
response = client.get_knowledge_bases()
print(response)
```

### Getting details of a knowledge base

To get details of a knowledge base, use the `get_knowledge_base` method with the knowledge base id.

```python
response = client.get_knowledge_base('knowledge_base_id')
print(response)
```

### Creating a conversation

To create a conversation, use the `create_chat_session` method with the knowledge base id and the question. This will
return the AI response along with the chat session id.

```python
response = client.create_chat_session('knowledge_base_id', 'question')
print(response)
# {'answer': 'Hello! How can I help you today? \n', 'session_id': '66fa625fb58f5a4b9a30b983', 'userId': '66c4151c98bd0d3d47de682a'}
```

### Adding a message to a conversation

To add a message to a conversation, use the same method `create_chat_session` with the chat session id and the message.

```python
response = client.create_chat_session('knowledge_base_id', 'message', 'chat_session_id')
print(response)
```

### Getting all conversations

To get all conversations, use the `get_chat_sessions` method.

```python
response = client.get_chat_sessions()
print(response)
```

### Getting details of a conversation

To get details of a conversation (which contains chat history for this conversation), use the `get_chat_session` method
with the chat session id.

```python
response = client.get_chat_session('chat_session_id')
print(response)
```

### Get uploaded documents

To get all uploaded documents, use the `get_uploaded_documents` method.

```python
response = client.get_uploaded_documents()
print(response)
```

### Examples

Here is a complete example demonstrating how to use the `rivalz-client` to create a simple RAG conversation based on a
PDF document:

```python
# main.py

import os
from dotenv import load_dotenv
from rivalz_client.client import RivalzClient


def main():
    # Load environment variables from .env file
    load_dotenv()

    # Get the secret token from environment variables
    secret_token = os.getenv('SECRET_TOKEN')

    if not secret_token:
        raise ValueError("SECRET_TOKEN is not set in the environment variables.")

    # Initialize the RivalzClient with the secret token
    client = RivalzClient(secret_token)

    # create knowledge base
    knowledge_base = client.create_rag_knowledge_base('sample.pdf', 'knowledge_base_name')
    knowledge_base_id = knowledge_base['id']
    # create conversation
    conversation = client.create_chat_session(knowledge_base_id, 'what is the document about?')
    conversation_id = conversation['session_id']
    # add message to conversation
    conversation = client.create_chat_session(knowledge_base_id, 'what is the document about?', conversation_id)
    print(conversation['answer'])


if __name__ == '__main__':
    main()
```

## Contributing

Contributions are welcome! Please fork the repository and submit a pull request with your changes.

1. Fork the repository.
2. Create a new branch (`git checkout -b feature/your-feature`).
3. Commit your changes (`git commit -am 'Add new feature'`).
4. Push to the branch (`git push origin feature/your-feature`).
5. Create a new pull request.

## Publish package

To publish your package, you will need to use `setuptools` and `wheel` to build your package. Here are the steps to
follow:

1. Make sure you have `setuptools` and `wheel` installed. If not, you can install them using `pip`:

    ```sh
    pip install setuptools wheel
    ```

2. Create a `setup.py` file in the root directory of your project. This file will contain the metadata about your
   package, such as its name, version, and dependencies. Here is an example `setup.py` file:

    ```python
    from setuptools import setup, find_packages

    setup(
         name='rivalz-client',
         version='1.0.0',
         description='Python client for interacting with the Rivalz API',
         author='Your Name',
         author_email='your_email@example.com',
         packages=find_packages(),
         install_requires=[
              'requests',
         ],
    )
    ```

   Make sure to replace `'Your Name'` and `'your_email@example.com'` with your actual name and email address.

3. Build the package by running the following command:

    ```sh
    python setup.py sdist bdist_wheel
    ```

   This will create a `dist` directory containing the built package files.

4. Upload the package to the Python Package Index (PyPI) using `twine`. If you haven't already, you will need to create
   an account on PyPI. Once you have an account, you can upload the package by running the following command:

    ```sh
    twine upload dist/*
    ```

   This will upload the package to PyPI, making it available for others to install using `pip`.

That's it! Your package is now published and can be installed by others using `pip install rivalz-py-client`.

Remember to update the version number in your `setup.py` file each time you make changes to your package and want to
publish a new version.

### Explanation

- **Project Title**: Clearly states the name of the project.
- **Features**: Lists the main functionalities of the package.
- **Installation**: Provides the command to install the package using `pip`.
- **Usage**: Detailed steps on how to initialize the client, upload files, upload passport images, download files, and
  delete files.
- **Example**: A complete example script that demonstrates the usage of all the major functionalities.
- **Contributing**: Instructions for contributing to the project.
- **License**: Specifies the license under which the project is released.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
