Offline AI Chatbot with your own documents - Anything LLM like Chat with RTX - | Unscripted Coding

Summary

In this episode of 'Unscripted Coding,' the host explores 'Anything LLM,' an open-source alternative to Nvidia's 'Chat with RTX,' focusing on local AI model operations to protect sensitive data. The host installs and tests 'Anything LLM' on Windows, discussing its potential for local embeddings and vectors, and the flexibility to mix local and online models. Despite a polished interface, the host encounters issues with file embeddings and vectors, suggesting that while the concept is promising, the execution needs improvement. The video concludes with the recommendation to revisit the tool in the future, as it shows potential but currently falls short of expectations.

Takeaways

• 🎙️ The video explores 'anything llm,' an open-source alternative to Nvidia's Chat with RTX.
• 💻 The speaker discusses the importance of using local AI models for sensitive information to avoid data privacy issues associated with online chatbots.
• 🔧 Nvidia's Chat with RTX allows running AI models locally using Nvidia graphics cards but requires a modern, powerful computer.
• 🛠️ The speaker's experience with Chat with RTX was mediocre, prompting a search for alternatives like 'anything llm.'
• 📥 'anything llm' can utilize embeddings and vectors locally, allowing the use of local files and models while optionally connecting to online services.
• 🌐 The gold standard for language models is OpenAI's GPT-4, but local models like ol' LLaMA can be used for different needs.
• 🔍 The video demonstrates the installation and initial setup of 'anything llm,' including connecting local files for processing.
• ⚙️ The process involves embedding files to make them searchable, but the speaker encountered issues with the accuracy of file retrieval.
• 🤖 The video shows a test of 'anything llm,' which struggled with accurately citing the correct files from the embeddings.
• 📊 Despite a polished interface, the speaker finds 'anything llm' lacking in performance when running entirely locally, suggesting it might improve over time.

Q & A

What is the main topic of the 'Unscripted Coding' episode discussed in the transcript?

The main topic is exploring 'Anything LLM', an open-source alternative to Nvidia's 'Chat with RTX', focusing on the use of large language models (LLMs) locally on a computer for privacy and data security.

Why is it risky to use online chatbots for sensitive information like employment contracts?

Using online chatbots for sensitive information is risky because there's a possibility that these platforms may train on your data, mine your data, or sell your data without your consent, compromising privacy and security.

What is Nvidia's 'Chat with RTX' and how does it relate to the topic?

'Chat with RTX' is an idea by Nvidia that allows users to run AI models locally on their own computer using an Nvidia graphics card, ensuring that data processing is done on the user's own hardware, thus addressing privacy concerns.

What is the primary advantage of running AI models locally as opposed to using cloud services?

The primary advantage is that running AI models locally keeps all data and processing within the user's own computer, reducing the risk of data breaches, unauthorized data access, and ensuring complete control over the data.

What does 'Anything LLM' offer that differentiates it from other AI chatbots?

'Anything LLM' offers the ability to use embeddings and vectors locally on the user's computer, allowing for local processing of files and interaction with AI models without the need for online services.

What is the significance of being able to mix and match different models and embedding services in 'Anything LLM'?

The ability to mix and match allows users to choose the best combination of models and embedding services that meet their specific needs, providing flexibility and potentially better performance or security.

What is the 'gold standard' for LLMs as mentioned in the transcript?

The 'gold standard' for LLMs, as mentioned, is Open AI's GPT (Generative Pre-trained Transformer), which is recognized for its advanced capabilities in language understanding and generation.

What was the speaker's experience with 'Chat with RTX' and 'Anything LLM'?

The speaker had a mediocre experience with 'Chat with RTX' but found 'Anything LLM' to be less satisfactory, particularly with the local embedding and vector database not functioning as expected.

What issue did the speaker encounter while trying to connect files to 'Anything LLM' for processing?

The speaker encountered issues with the file embedding process, where the system was not correctly identifying and serving up the correct files, leading to inaccurate responses from the AI.

What was the speaker's suggestion for improving the experience with 'Anything LLM'?

The speaker suggested revisiting the tool after a few months, as it is a new idea and may benefit from further development and updates to address the current issues.

What is the speaker's final verdict on using 'Anything LLM' for local AI processing?

The speaker concludes that while the idea of 'Anything LLM' is promising and the interface is polished, it is not yet ready for reliable local AI processing due to the issues encountered with file embeddings and model performance.