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LLMOps

ChatGPT, Who? Meet the Open Source Chatbot Revolution

Sep 13, 2023

5 min read

When asked for alternatives to ChatGPT, what strikes your mind? It may be LLaMA or PaLM, but are they alternatives to ChatGPT? When we talk about ChatGPT, we talk about the very conversational AI available to us in a friendly, interactable, and intuitive UI, not the model itself.

ChatGPT, however, starting the entire buzz and hype around LLM-based ChatBots, has been noted to have a tonne of problems both with the availability of limited models, bugs, and general experiences people have had with the bot.

Be it rude behavior, gaslighting practices, or a general easily offendable persona of the model itself, let us break down the inherent reasons why the ChatBot behaves like this and what some open-sourced alternatives a user can go for!


Understanding ChatGPT and Its Features

ChatGPT is a chatbot developed by OpenAI that uses natural language processing (NLP) to understand and respond to user inputs. It is designed to hold intelligent and engaging conversations on various topics. Initially powered by OpenAI’s GPT-3, GPT-3.5, and GPT-4, the chatbot is OpenAI’s ace in the race of Generative AI.

The model works on a simple feedback loop generated using Natural Language Processing with a user. An input is received, and an output is generated using the local language model and shown to the user. The user can further refine this output by providing more in-detail feedback on the result, an excellent example of Reinforcement Learning with Human Feedback.

Once empowered with strong enough prompts, the Chatbot holds the power to generate content and run Natural Language Tasks like no other (or does it?). Some of the things that the bot introduced the world to, which can be achieved with Large Language Models, are:

1. Contextual Understanding

2. Personalized Responses

3. Multilingual Support

4. Text Generation

5. Code Generation

These features soon took the world with surprise and wonder, making every single Fortune company have their player in the LLM game, but their years of research in generative AI have managed to keep them in the lead. Be it an investment or people looking up to a model when training their chatbot. However, it all came with annoying walls, moderation, and limitations if a user used the model for hardcore cases. Hence came the dawn of Open-Source Alternatives to ChatGPT and OpenAI.


Advantages of Open Source Alternatives

Before the launch of the first iteration of LLaMA by Meta, the thought of Open-Source was something that OpenAI was still controlling with their GPT APIs, which, however, on paper, may show you some freedom in terms of fine-tuning the model to your understanding and need, still at the end of the day controlled and is dictated by the policies OpenAI makes.

OpenAI may have started as a company dictating Governance in AI, but does research mean something when the sensitive data collected is still, at the end of the day, going to multi-billion dollar companies like Microsoft for them to eventually train more models like this and use it to their advantage.

Let us look at some of the advantages one can have by using a ChatBot running on Open-Sourced Models and Codex:

1. Flexibility and Customizability: With access to the source code, developers can modify and tailor the chatbot to suit their needs and requirements. This can lead to more personalized and effective chatbot experiences for users.

2. Greater Transparency: By making the source code available to the public, developers can see how the chatbot works, identify areas for improvement, and contribute to the development process. This leads to increased transparency and accountability in the development of the chatbot.

3. Improved Software Quality: With a community of developers working together to improve the open-source chatbot, the overall quality of the software can be enhanced through collaboration and mutual learning. This can result in a more robust and reliable chatbot experience for users.

4. Cost-Effective: Using an open-source chatbot can save costs for developing and maintaining proprietary chatbot solutions. Additionally, since the source code is available to the public, no licensing fees are required to use or modify the chatbot.

Now, we have opened your eyes to the advantages and disadvantages of collecting your data from a closed-sourced organization. In that case, we want you to ask yourself your ideal balance between performance and privacy. Well, you may not be ready to lose your routine right, then let us take a look at different Open-Source Alternatives to ChatGPT, which can produce results that compete with ChatGPT and GPT-4 but meanwhile release you from the shackles of Moderation, Firewalls, and Data Privacy.


Open Source Alternatives to ChatGPT

ChatNBX

ChatNBX, NimbleBox.ai’s very own take on deployable LLMs in a conversational setting, is one of the leading alternatives to ChatGPT, being better than the legacy model on various parameters such as number of models, features, and free access to GPT-4. Some prominent features that will make ChatNBX your default chatbot are Search on Web, Search on Docs, System Prompting, APIs, etc.

Starting with the first iterations of LLaMA-based open-source models, the platform looks at Democratizing AI, which is impossible with the vast and unnecessary amount of limitations the legacy chatbots like ChatGPT and Bard come with. Promoting research in LLMs by providing an array of models with differing origins, parameters, and context is your destination for groundbreaking work in fields like fine-tuning LLMs, understanding LLM behaviors, limitation-free prompt engineering, and much more.

  • Price: Free

  • Link: https://chat.nbox.ai/

  • Models Available: LLaMA-2-13B, Nouse-Hermes-LLaMA-2-13B-4K, Oast-CodeLLaMA-13B-14K, Airoboros-v2-CodeLLaMA-34B, LLaMA-2-chat-70B-4K


Perplexity AI

Perplexity AI is another option like ChatGPT that has also received training from OpenAI's API, resulting in a solid performance and relevant responses. Its user interface is straightforward to navigate. Like ChatGPT, Perplexity enables users to engage in conversations and receive basic and sophisticated replies. Unlike ChatGPT, however, Perplexity provides citations for the sources used to answer each query.

However, the first-ever versions of the chatbot have worked on a fine-tuned GPT 3.5 Turbo; the chatbot comes with various models working in the background but doesn’t really tell you how the prompts are being answered on the free versions. One can, however, upgrade to the pro version to gain access to Claude-2 or GPT-4.

  • Price: 20 USD Monthly

  • Link: https://www.perplexity.ai/

  • Models Available: LLaMA, LLaMA 2, Code LLaMA


HuggingChat

One of the leading open-source alternatives to ChatGPT, HuggingChat is a conversational AI chatbot developed by the renowned website HuggingFace. Leveraging the impressive capabilities of the LLaMA and its different variants, which have been inspired and developed with the humongous Open-Source culture around LLaMA models- boasting some models going up to 70 Billion parameters - this chatbot maintains remarkable efficacy despite having a relatively modest number of parameters.

However, because of is wholly built on LLaMA models and various open-sourced the model lacks and is dependent on the weights released by Meta for any real or incremental upgrade in context, parameters, and general abilities of the model, which are dictated by the actual training of an LLM.

  • Price: Free

  • Link: https://huggingface.co/chat/

  • Models Available: LLaMA-2-70B, CodeLLaMA, Oasst-LLaMA-30B


Conclusion

As we dive deeper into chatbot technology, it becomes increasingly clear that there is room for more inclusive and collaborative efforts beyond the confines of exclusively funded ventures like ChatGPT. In light of this, we present three enthralling open-source alternatives capable of revolutionizing the future of chatbots. These spellbinding tools embody the true spirit of innovation and cooperation, offering feature-rich functionality without encumbering proprietary restrictions.

Written By

Aryan Kargwal

Data Evangelist

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