README.md

Ellama = Ell + Ollama = ❤️❤️

All LLocal. All Ell. Good times

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Kind regards, Hololeo!!

12 Ell Categorizer ell-categorizer categorize ANY data into ANY json format of your design! Just use a clear, specific prompt and provide some training examples. The approach can scale to thousands of lines if you batch in your data bit by bit. Ell Categorizer is a powerful tool in your AI bag-of-tricks!

11 Ell Rag Audio ell-rag-audio allows you to prompt an audio file! Just put in a transcript.txt (whisper works great) and set your user prompt. Its smart to locate the audio timecode that relates to the prompt. Very simple implementation using context injection and clever prompt engineering.

10 Ell Rag Txt ell-rag-txt allows you to prompt any text file. Just put it in input.txt and set up your user prompt question. It implements the RAG pattern to chat with the document. Very simple implementation using context injection.

9 ell-alarm ell-alarm.py implements an alarm clock. User can set the alarm and LLM is triggered when its time. Work in progress

8 ell-strawberry ell-strawberry.py tackles the most pressing problem to humanity: Learning how many r's are in the word strawberry! Using Ell and Ollama we create a chain of thought prompt to solve this most puzzling riddle!

7 ell-employee-0 ell-employee-0.py is a Python script that generates a script description from input information. The script uses the Ell library to locally run the Llama 3.1 model and demonstrates support for the Ollama tool, allowing users to create enhanced script descriptions. This automation enables us to create our own AI Employee!

6 ell-diffusion is a Python script that helps refine user input to create more effective prompts for Stable Diffusion image generation. By taking a user's initial prompt, the script generates an optimized and enhanced version, ensuring better results from the diffusion model. Using Ell and Ollama, this tool is perfect for developers and artists looking to get the most out of Stable Diffusion by improving the quality and specificity of their prompts.

5 ell-summarizer is a Python script designed for efficient text summarization. Generates concise bullet-point summaries from input text. Utilizes Ollama to run the Gemma 2B language model locally. Leverages the Ell library to rapidly create system and user prompts. This tool is ideal for developers, researchers, or anyone needing quick, local text summarization without relying on cloud-based APIs.

4 ell-captioner is a Python script designed for fast image captioning. It generates descriptive captions from input images. The script utilizes Ollama to run the Moondream language model locally and leverages the Ell library to structure system and user prompts effectively. You can pass the image as an argument via the command line, and the script will provide an accurate and contextually aware caption for the image. This tool is perfect for developers, researchers, or anyone needing a quick, local image captioning solution without relying on cloud-based services.

3 ell-joker is a Python script that generates and delivers jokes. It prompts a model for a humorous joke and then uses text-to-speech to speak the joke aloud. The script showcases tool calling by utilizing LLama 3.1 and Ollama to run models locally. This makes it an ideal demonstration of combining AI language models with speech synthesis for developers or anyone who wants a quick laugh generated and voiced directly from their machine.

2 ell-chatbot is a Python script that enables interactive chatting with an AI model. It showcases how to use Ell to facilitate conversational AI with memory, allowing the chatbot to retain and reference past interactions for more contextual and fluid conversations. This script demonstrates how to seamlessly integrate memory into chats, enhancing the chatbot's ability to provide more relevant responses. It's ideal for developers interested in creating dynamic, context-aware chat systems using Ollama and other local models.

1 ell-meets-ella is a Python script that demonstrates how to get two AI bots to engage in a continuous conversation. The script showcases the creation of two distinct personas that interact with each other, generating an ongoing dialogue between the bots. This tool highlights how to structure autonomous conversations, making it ideal for developers experimenting with AI-to-AI interactions. By using Ell and Ollama, the script demonstrates how to create indefinite, engaging chats between AI models, perfect for understanding how bots communicate independently.