adriancmilian

adriancmilian's Stars

• explosion/spacy-transformers

  🛸 Use pretrained transformers like BERT, XLNet and GPT-2 in spaCy

  Language:Python1.4k171

• unum-cloud/usearch

  Fast Open-Source Search & Clustering engine × for Vectors & 🔜 Strings × in C++, C, Python, JavaScript, Rust, Java, Objective-C, Swift, C#, GoLang, and Wolfram 🔍

  Language:C++2.6k173

• f/awesome-chatgpt-prompts

  This repo includes ChatGPT prompt curation to use ChatGPT and other LLM tools better.

  Language:JavaScript123k16.4k

• microsoft/autogen

  A programming framework for agentic AI 🤖 PyPi: autogen-agentchat Discord: https://aka.ms/autogen-discord Office Hour: https://aka.ms/autogen-officehour

  Language:Python42.8k6.4k

• jsvine/pdfplumber

  Plumb a PDF for detailed information about each char, rectangle, line, et cetera — and easily extract text and tables.

  Language:Python7.5k721

• janedoesrepo/pdfreader

  Extracting Semi-Structured Data from PDFs on a large scale

  Language:Jupyter Notebook5118

• adobe/NLP-Cube

  Natural Language Processing Pipeline - Sentence Splitting, Tokenization, Lemmatization, Part-of-speech Tagging and Dependency Parsing

  Language:HTML55994

• adobe/pdfservices-python-sdk-samples

  Adobe PDFServices python SDK Samples

  Language:HTML14843

• mpaepper/llm_agents

  Build agents which are controlled by LLMs

  Language:Python97378

• deepset-ai/haystack

  AI orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited for building RAG, question answering, semantic search or conversational agent chatbots.

  Language:Python20.2k2.1k

• google/sentencepiece

  Unsupervised text tokenizer for Neural Network-based text generation.

  Language:C++10.8k1.2k

• codedog-ai/codedog

  Code review assistant powered by LLM

  Language:Python11819

• stanfordnlp/dspy

  DSPy: The framework for programming—not prompting—language models

  Language:Python22.9k1.8k

• confident-ai/deepeval

  The LLM Evaluation Framework

  Language:Python5.9k504

• naver/splade

  SPLADE: sparse neural search (SIGIR21, SIGIR22)

  Language:Python83590

• Azure-Samples/miyagi

  Sample to envision intelligent apps with Microsoft's Copilot stack for AI-infused product experiences.

  Language:Jupyter Notebook740244

• Azure/intelligent-app-workshop

  Immersive workshop showcasing the remarkable potential of integrating SoTA foundation models to enhance product experiences and streamline backend workflows. Leverages Microsoft's Copilot stack, Semantic Kernel and Azure primitives to offer an engaging and comprehensive introduction to AI-infused app development and deployment

  Language:Bicep18343

• microsoft/TypeChat

  TypeChat is a library that makes it easy to build natural language interfaces using types.

  Language:TypeScript8.4k397

• eth-sri/lmql

  A language for constraint-guided and efficient LLM programming.

  Language:Python3.9k207

• microsoft/cookiecutter-spacy-fastapi

  Cookiecutter API for creating Custom Skills for Azure Search using Python and Docker

  Language:Python53065

• nltk/nltk

  NLTK Source

  Language:Python14k2.9k

• instructor-ai/instructor

  structured outputs for llms

  Language:Python10k773

• microsoft/azure-genai-design-patterns

  Language:Python656116

• microsoft/Azure-PDF-Form-Processing-Automation-Solution-Accelerator

  Language:Bicep2219

• microsoft/semantic-kernel

  Integrate cutting-edge LLM technology quickly and easily into your apps

  Language:C#23.9k3.7k

• guidance-ai/guidance

  A guidance language for controlling large language models.

  Language:Jupyter Notebook20k1.1k

• Azure-Samples/search-ranking-tutorial

  Python learning to rank tutorial using Azure Cognitive Search

  Language:HTML148

• ruoccofabrizio/azure-open-ai-embeddings-qna

  A simple web application for a OpenAI-enabled document search. This repo uses Azure OpenAI Service for creating embeddings vectors from documents. For answering the question of a user, it retrieves the most relevant document and then uses GPT-3, GPT-3.5 or GPT-4 to extract the matching answer for the question.

  Language:Python853509

• MaheshSQL/cognitive-semantic-search-openai-accelerator

  Azure Cognitive Semantic Search that works on large documents, with OpenAI enrichment.

  Language:Python156

• Anaig/OpenAI-and-Cognitive-Search

  Azure OpenAI integration as a custom skillset in Azure Cognitive Search

  Language:Python3310