everything-ai @ v3.0.0🤖

CHANGELOG

• 🦙 Added support for llama.cpp as inference engine to chat with your pdfs, backed by Qdrant as vector database
• 😵 Small bugfixes in retrieval_text_generation.py

everything-ai @ v2.0.1🤖

CHANGELOG

• 🧬everything-ai-proteinfold interface now shows the 3D structure of a protein along with its molecular one, no more static backbone images
• 🏋️everything-ai-autotrain now supports direct file uploading, without the need to specify the path

everything-ai @ v2.0.0🤖

CHANGELOG

New functionalities that were added since last release:

• 🎙️🔊 Handle audio files or microphone recordings, classifying or transcribing them with almost every audio-classification and automatic-speech-recognition model on Hugging Face Hub.
• 📽️ Generate video from text prompts with almost every text-to-video model on HuggingFace Hub (original architecture by Vasiliy Katsyka)
• 🧬 Predict the 3D structure of proteins from their amino-acidic sequence, with EsmFold by AI at Meta
• 🏋️ Finetune HF models on several downstream tasks with AutoTrain local integration (AutoTrain is developed by Abhishek Thakur)
• 🗣️ Unleash powerful LLMs and exploit larger database collections for RAG with the integration of Hugging Face Spaces API and Supabase PostgreSQL databases.

everything-ai @ v1.1.0🤖

CHANGELOG:

• Added the possibility to perform reverse image search based on an image dataset uploaded by the user and on Qdrant vector databases🔥
• Added GPU support for almost every model and task🚀
• Added a new python package in the Dockerfile: datasets🥳

everything-ai @ v1.0.0🤖

CHANGELOG:

1. Changed name from everything-rag to everything-ai
2. User-friendly task, model and file selection interface (no longer CLI, but GUI with gradio)
3. Multi-container application with docker compose up (simpler)
4. New docker image on Docker Hub: astrabert/everything-ai
5. Supports new tasks: text summarization, stable diffusion, image to text, image classification
6. Added multilingual support for text generation and stable diffusion
7. Text generation has now two options: agnostic text generation (no retrieval or prior knowledge) and retrieval text generation (retrieval with knowledge base)
8. Switched from Langchain-supplied ChromaDB local storage to qdrant collections for retrieval knowledge bases
9. Faster retrieval text generation inference

everything-rag @ v0.1.1🤖

Docker image is now stable and supports all tasks both on Windows and on Linux. HF space was added, more troubleshooting cases and tags that give at-a-glance stats on the status of this repo.

everything-rag @ v0.1.0🤖

Added Dockerfile and GradIO interface and the installable docker image as a package under the name ghcr.io/astrabert/everything-rag:latest.

everything-rag @ v0.0.0🤖

Base release for everything-rag