Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
UpTrain is an open-source unified platform to evaluate and improve Generative AI applications. We provide grades for 20+ preconfigured checks (covering language, code, embedding use-cases), perform root cause analysis on failure cases and give insights on how to resolve them.
Context management for long-context LLMs, agents, and vibe coding. Instantly build context for an entire repo, selected files, folders, and GitHub issues to generate structured AI-XML context with real-time token counting.
LLM prompts, llama3 prompts, llama2 prompts
It is a comprehensive resource hub compiling all LLM papers accepted at the International Conference on Learning Representations (ICLR) in 2024.
Open Source LLM proxy that transparently captures and logs all interactions with LLM API
This project investigates the security of large language models by performing binary classification of a set of input prompts to discover malicious prompts. Several approaches have been analyzed using classical ML algorithms, a trained LLM model, and a fine-tuned LLM model.
Franklin is a LLM powered AI IRC chat bot
🔭 Threat report analysis via LLM and Vector DB
Prompt generator for LLM agents with interceptors
Proofreading and editing prompts for ChatGPT, Copilot, Gemini, etc.
An application that transforms prompt engineering for LLMs by automating prompt generation, creating diverse test cases, and evaluating and ranking prompts.
Just released Visual-Prompt-Craft – A simple toolkit for visual prompting with CLIP & ViT
Evaluating LLMs with Multiple Problems at once: A New Paradigm for Probing LLM Capabilities
k0r0pt Ai Image Prompt Generator
Just released Visual-Prompt-Craft – A simple toolkit for visual prompting with CLIP & ViT
I used prompt engineering with Claude.ai to create a QR Generator
A collection of my prompts for LLM powered apps
A framework to move beyond simple prompting towards defining *how* the LLM should structure its internal processing, access its latent knowledge, and apply specific heuristics or constraints when dealing with a particular subject matter or task.
Creating an AI chatbot that can take on different personas, keep track of conversation history, and provide coherent responses.
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