Best AI tools for< Telewriter >

Screenwriting.AI is an AI-powered platform designed to assist screenwriters in crafting captivating stories, authentic dialogue, and well-developed characters. It provides a range of tools and features to streamline the screenwriting process, including script templates, plot guidance, and AI-assisted editing. The platform aims to empower screenwriters to overcome writer's block, enhance their writing skills, and produce polished screenplays that meet industry standards.

Strut is a complete writing workspace that combines notes, documents, and writing projects in collaborative workspaces supported by AI. It helps users capture notes, organize projects, and collaborate with their team alongside AI to keep the writing process moving forward. Strut offers deep focus modes, project workspaces, writing inbox, drag & drop functionality, and AI workflows for brainstorming ideas, generating outlines, and more. It is designed to be a writing partner that provides suggestions, edits, research, and inspiration without automating the process. Strut aims to streamline the writing workflow into one simple app, offering features like document chat, voice & tone customization, inline editing, and typewriter-inspired focus mode.

ChatGLM.cpp is a C++ implementation of ChatGLM-6B, ChatGLM2-6B, ChatGLM3-6B and more LLMs for real-time chatting on your MacBook. It is based on ggml, working in the same way as llama.cpp. ChatGLM.cpp features accelerated memory-efficient CPU inference with int4/int8 quantization, optimized KV cache and parallel computing. It also supports P-Tuning v2 and LoRA finetuned models, streaming generation with typewriter effect, Python binding, web demo, api servers and more possibilities.

ChatLLM.cpp is a pure C++ implementation tool for real-time chatting with RAG on your computer. It supports inference of various models ranging from less than 1B to more than 300B. The tool provides accelerated memory-efficient CPU inference with quantization, optimized KV cache, and parallel computing. It allows streaming generation with a typewriter effect and continuous chatting with virtually unlimited content length. ChatLLM.cpp also offers features like Retrieval Augmented Generation (RAG), LoRA, Python/JavaScript/C bindings, web demo, and more possibilities. Users can clone the repository, quantize models, build the project using make or CMake, and run quantized models for interactive chatting.

QOwnNotes is an open source notepad with Markdown support and todo list manager for GNU/Linux, macOS, and Windows. It allows you to write down thoughts, edit, and search for them later from mobile devices. Notes are stored as plain text markdown files and synced with Nextcloud's/ownCloud's file sync functionality. QOwnNotes offers features like multiple note folders, restoration of older versions and trashed notes, sub-string searching, customizable keyboard shortcuts, markdown highlighting, spellchecking, tabbing support, scripting support, encryption of notes, dark mode theme support, and more. It supports hierarchical note tagging, note subfolders, sharing notes on Nextcloud/ownCloud server, portable mode, Vim mode, distraction-free mode, full-screen mode, typewriter mode, Evernote and Joplin import, and is available in over 60 languages.

The ChatGPT Telegram Bot is a powerful Telegram bot that utilizes various GPT models, including GPT3.5, GPT4, GPT4 Turbo, GPT4 Vision, DALL·E 3, Groq Mixtral-8x7b/LLaMA2-70b, and Claude2.1/Claude3 opus/sonnet API. It enables users to engage in efficient conversations and information searches on Telegram. The bot supports multiple AI models, online search with DuckDuckGo and Google, user-friendly interface, efficient message processing, document interaction, Markdown rendering, and convenient deployment options like Zeabur, Replit, and Docker. Users can set environment variables for configuration and deployment. The bot also provides Q&A functionality, supports model switching, and can be deployed in group chats with whitelisting. The project is open source under GPLv3 license.

Analyze the following text from a github repository (name and readme text at end) . Then, generate a JSON object with the following keys and provide the corresponding information for each key, in lowercase letters: 'description' (detailed description of the repo, must be less than 400 words，Ensure that no line breaks and quotation marks.),'for_jobs' (List 5 jobs suitable for this tool,in lowercase letters), 'ai_keywords' (keywords of the tool,user may use those keyword to find the tool,in lowercase letters), 'for_tasks' (list of 5 specific tasks user can use this tool to do,in lowercase letters), 'answer' (in english languages)

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and follows a process of embedding docs and queries, searching for top passages, creating summaries, scoring and selecting relevant summaries, putting summaries into prompt, and generating answers. Users can customize prompts and use various models for embeddings and LLMs. The tool can be used asynchronously and supports adding documents from paths, files, or URLs.

PaperQA is a minimal package for question and answering from PDFs or text files, providing very good answers with in-text citations. It uses OpenAI Embeddings to embed and search documents, and includes a process of embedding docs, queries, searching for top passages, creating summaries, using an LLM to re-score and select relevant summaries, putting summaries into prompt, and generating answers. The tool can be used to answer specific questions related to scientific research by leveraging citations and relevant passages from documents.