Possibly futile attempt at grounding hype with theory and fundamentals
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Updated
Jun 2, 2024
Possibly futile attempt at grounding hype with theory and fundamentals
🪢 Langfuse documentation -- Langfuse is the open source LLM Engineering Platform. Observability, evals, prompt management, playground and metrics to debug and improve LLM apps
A research prototype for exploring and organizing multiple writing variations with large language models
Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
Image-generating application powered by Amazon Bedrock
OpenLIT is an open-source GenAI and LLM observability platform native to OpenTelemetry with traces and metrics in a single application 🔥 🖥 . Open source GenAI and LLM Application Performance Monitoring (APM) & Observability tool
The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.
Artificial intelligence services for the Composum Pages CMS and Adobe AEM : content creation and analysis, translation, suggestions, ...
DevoxxGenie is a plugin for IntelliJ IDEA that uses local LLM's (Ollama, LMStudio, GPT4All and Jan) and Cloud based LLMs to help review, test, explain your project code.
OSINT Platform - Provides image analysis, digital footprints, video transcription and more. Retrieval Augmented Generation (RAG) capable platform
AI POCS: ML, NLP, LLM, Vision, Classification, clustering, GenAI, Transformers, PyTorch, Keras, All things AI POCS.
This repository contains a collection of machine learning examples implemented in Jupyter Notebooks. Each notebook demonstrates a different machine learning technique or algorithm, along with explanations and code examples.
A python library to enable GenAI and LLMOps within Google Cloud Platform
Generative AI Scripting for VSCode
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