<p align="center">
<img src="https://github.com/muhammad-fiaz/neurolink/assets/75434191/82fbf702-43e2-46e6-8e01-11758fa26310" alt="Neurolink GIF" width="500" height="auto">
</p>
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# NeuroLink
NeuroLink is a Python package that aims to provide various AI capabilities, including a chatbot, image processing, audio processing, Django support, and more. It utilizes TensorFlow and other related technologies for natural language processing and AI tasks.
## Description
The NeuroLink package is designed to offer developers an easy and efficient way to incorporate AI functionalities into their projects. It provides a chatbot module that can understand and respond to user input using TensorFlow for intent classification. Additionally, it includes modules for image processing, audio processing, and Django integration, making it a versatile AI package for different applications.
**NOTE: This package is currently under development and not yet ready for production use. Use it at your own risk.**
## Planned Features
- **Text Processing:** Offers functionalities for text manipulation, analysis, and processing. It includes features like text cleaning, tokenization, stemming, and named entity recognition.
- **Chatbot:** Provides a conversational interface for interacting with users. The Chatbot utilizes TensorFlow for natural language processing and intent classification. It will allow users to have interactive conversations and receive responses based on the input.
- **Image Processing:** Offers functionalities for image manipulation, analysis, and recognition. It includes features like image filtering, object detection, and image-based AI tasks.
- **Audio Processing:** Allows processing and analysis of audio files, including speech recognition and synthesis. It provides features like speech-to-text, text-to-speech, and audio-based AI tasks.
- **Django & Flask Support:** Provides integration with Django, a popular Python web framework. This enables seamless integration of AI functionalities into web applications built with Django.
- **And more:** Planned features include additional AI capabilities and modules for natural language processing, computer vision, machine learning, and other AI-related tasks.
## Installation
**NOTE: This package is still in development and not yet Stable. Use it at your own risk.**
this package is released, it can be installed using pip:
```bash
pip install neurolink
```
To update neurolink to the latest version, add --upgrade flag to the above commands.
## Try your first NeuroLink program
import neurolink
"""
Sample Test Case to get a response from the chatbot
"""
intents_path = "intents.json"
model_path = "model.tflearn"
data_path = "data.pickle"
initialize_obj = neurolink.initialize(intents_path, model_path, data_path, train_model=True)
response = initialize_obj.chat("Hi", 0.5)
print(response)
**Above model is for reference, its uses intents.json for dataset and sample format that is used to create simple chatbot [check out here](https://github.com/muhammad-fiaz/neurolink/blob/master/intents.json)**
⚠️ Note: The project is currently in active development, and some features may not work properly on older versions. It is recommended to upgrade to the latest version for optimal performance and compatibility.
## Dependencies
This project utilizes the following third-party libraries:
- [PyTorch](https://pytorch.org/): A deep learning framework for training and building neural networks.
- [TensorFlow](https://www.tensorflow.org/): A powerful open-source machine learning framework.
- [TFLearn](http://tflearn.org/): A high-level API for TensorFlow, simplifying the process of building and training models.
- [NumPy](https://numpy.org/): A fundamental package for scientific computing with Python.
- [NLTK](https://www.nltk.org/): A platform for building Python programs to work with human language data.
💪 ARM Installation: The necessary libraries are automatically installed when you install the package. You can directly use the provided code without any additional installation steps.
For more information about each library, please refer to their respective documentation links above.
## Documentation
- [PyTorch Documentation](https://pytorch.org/docs/)
- [TensorFlow Documentation](https://www.tensorflow.org/api_docs/)
- [TFLearn Documentation](http://tflearn.org/doc_index/)
- [NumPy Documentation](https://numpy.org/doc/)
- [NLTK Documentation](https://www.nltk.org/index.html)
## Contribution
NOTE: This package is still in development, and contributions are currently not accepted.
Once the package reaches a stable release, contribution guidelines and instructions on how to contribute will be provided in the project's repository.
## Repository
The project repository is hosted on GitHub: [Project Repository](https://github.com/muhammad-fiaz/neurolink)
Please feel free to explore the repository, open issues, and provide feedback.
- Issue Tracker: [Project Issues](https://github.com/muhammad-fiaz/neurolink/issues)
# License
This project is licensed under the [Apache License, Version 2.0 ](https://github.com/muhammad-fiaz/neurolink/blob/main/LICENSE).
<p>
<img src="https://github.com/muhammad-fiaz/neurolink/assets/75434191/5ede394c-99fa-4f7f-8153-0de7f34b15c2" alt="Neurolink Logo" width="200">
</p>
Happy Coding!
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It utilizes TensorFlow and other related technologies for natural language processing and AI tasks.\r\n\r\n## Description\r\n\r\nThe NeuroLink package is designed to offer developers an easy and efficient way to incorporate AI functionalities into their projects. It provides a chatbot module that can understand and respond to user input using TensorFlow for intent classification. Additionally, it includes modules for image processing, audio processing, and Django integration, making it a versatile AI package for different applications.\r\n\r\n**NOTE: This package is currently under development and not yet ready for production use. Use it at your own risk.**\r\n\r\n## Planned Features\r\n\r\n- **Text Processing:** Offers functionalities for text manipulation, analysis, and processing. It includes features like text cleaning, tokenization, stemming, and named entity recognition.\r\n- **Chatbot:** Provides a conversational interface for interacting with users. The Chatbot utilizes TensorFlow for natural language processing and intent classification. It will allow users to have interactive conversations and receive responses based on the input.\r\n- **Image Processing:** Offers functionalities for image manipulation, analysis, and recognition. It includes features like image filtering, object detection, and image-based AI tasks.\r\n- **Audio Processing:** Allows processing and analysis of audio files, including speech recognition and synthesis. It provides features like speech-to-text, text-to-speech, and audio-based AI tasks.\r\n- **Django & Flask Support:** Provides integration with Django, a popular Python web framework. This enables seamless integration of AI functionalities into web applications built with Django.\r\n- **And more:** Planned features include additional AI capabilities and modules for natural language processing, computer vision, machine learning, and other AI-related tasks.\r\n\r\n## Installation\r\n\r\n**NOTE: This package is still in development and not yet Stable. Use it at your own risk.**\r\n\r\nthis package is released, it can be installed using pip:\r\n\r\n```bash\r\npip install neurolink\r\n```\r\nTo update neurolink to the latest version, add --upgrade flag to the above commands.\r\n\r\n## Try your first NeuroLink program\r\n \r\n import neurolink\r\n \r\n \"\"\"\r\n Sample Test Case to get a response from the chatbot\r\n \"\"\"\r\n\r\n intents_path = \"intents.json\"\r\n model_path = \"model.tflearn\"\r\n data_path = \"data.pickle\"\r\n initialize_obj = neurolink.initialize(intents_path, model_path, data_path, train_model=True)\r\n response = initialize_obj.chat(\"Hi\", 0.5)\r\n print(response)\r\n\r\n**Above model is for reference, its uses intents.json for dataset and sample format that is used to create simple chatbot [check out here](https://github.com/muhammad-fiaz/neurolink/blob/master/intents.json)**\r\n\r\n\u26a0\ufe0f Note: The project is currently in active development, and some features may not work properly on older versions. 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You can directly use the provided code without any additional installation steps.\r\nFor more information about each library, please refer to their respective documentation links above.\r\n\r\n## Documentation\r\n\r\n- [PyTorch Documentation](https://pytorch.org/docs/)\r\n- [TensorFlow Documentation](https://www.tensorflow.org/api_docs/)\r\n- [TFLearn Documentation](http://tflearn.org/doc_index/)\r\n- [NumPy Documentation](https://numpy.org/doc/)\r\n- [NLTK Documentation](https://www.nltk.org/index.html)\r\n\r\n\r\n## Contribution\r\n\r\nNOTE: This package is still in development, and contributions are currently not accepted.\r\n\r\nOnce the package reaches a stable release, contribution guidelines and instructions on how to contribute will be provided in the project's repository.\r\n\r\n## Repository\r\n\r\nThe project repository is hosted on GitHub: [Project Repository](https://github.com/muhammad-fiaz/neurolink)\r\n\r\nPlease feel free to explore the repository, open issues, and provide feedback.\r\n\r\n- Issue Tracker: [Project Issues](https://github.com/muhammad-fiaz/neurolink/issues)\r\n\r\n# License\r\n\r\nThis project is licensed under the [Apache License, Version 2.0 ](https://github.com/muhammad-fiaz/neurolink/blob/main/LICENSE).\r\n \r\n \r\n<p>\r\n <img src=\"https://github.com/muhammad-fiaz/neurolink/assets/75434191/5ede394c-99fa-4f7f-8153-0de7f34b15c2\" alt=\"Neurolink Logo\" width=\"200\">\r\n</p>\r\n\r\nHappy Coding!\r\n\r\n\r\n\r\n",
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