Best AI tools for< Repairing Plastic >
20 - AI tool Sites

Dr.Fone
Dr.Fone is a comprehensive mobile solution that offers a wide range of features for managing, recovering, transferring, and repairing data on iOS and Android devices. It includes tools for unlocking screens, recovering lost data, transferring files, repairing system issues, and more. Dr.Fone is designed to be user-friendly and provides a one-stop solution for all your mobile device needs.

Wondershare Repairit
Wondershare Repairit is an AI-powered data repair software that can fix corrupted videos, photos, files, and audio. It uses advanced AI algorithms to enhance the repair quality and efficiency. Repairit can handle all corruption scenarios and has a high repair success rate. It is easy to use and can be used by anyone, regardless of their technical expertise.

LangSwap
LangSwap is a cutting-edge video translation and dubbing platform that empowers users to translate their videos into multiple languages while preserving the original voice. With its advanced algorithms, LangSwap eliminates the need for time-consuming and expensive voice actors, allowing users to save significant time and money. The platform is incredibly user-friendly, making it accessible to anyone who needs to translate and dub videos. Whether you're an e-commerce marketer, a YouTube blogger, or a business looking to expand into new markets, LangSwap has the solution for you.

Rephrasely
Rephrasely is a free online paraphrasing tool that helps you rewrite text in different ways. It uses artificial intelligence (AI) to generate unique and plagiarism-free content. With Rephrasely, you can quickly and easily reword text, check for plagiarism, and translate text into over 100 languages.

IDjpg
IDjpg is an AI-powered photo editing tool that allows users to transform their photos into a variety of artistic styles, including 3D, caricature, line art, anime, and movies. The tool is easy to use and can be used to create unique and eye-catching images.

Velotix
Velotix is an AI-powered data security platform that offers groundbreaking visual data security solutions to help organizations discover, visualize, and use their data securely and compliantly. The platform provides features such as data discovery, permission discovery, self-serve data access, policy-based access control, AI recommendations, and automated policy management. Velotix aims to empower enterprises with smart and compliant data access controls, ensuring data integrity and compliance. The platform helps organizations gain data visibility, control access, and enforce policy compliance, ultimately enhancing data security and governance.

Cascadeur
Cascadeur is a standalone 3D software that lets you create keyframe animation, as well as clean up and edit any imported ones. Thanks to its AI-assisted and physics tools you can dramatically speed up the animation process and get high quality results. It works with .FBX, .DAE and .USD files making it easy to integrate into any animation workflow.

VIVA.ai
VIVA is an AI-powered creative visual design platform that aims to bring every moment to life. It provides users with tools and features to create visually appealing designs effortlessly. With VIVA, users can unleash their creativity and design stunning visuals for various purposes such as social media posts, presentations, and marketing materials. The platform leverages artificial intelligence to streamline the design process and help users achieve professional-looking results without the need for advanced design skills.

Competera
Competera is an AI-powered pricing platform designed for online and omnichannel retailers. It offers a unified workplace with an easy-to-use interface, real-time market data, and AI-powered product matching. Competera focuses on demand-based pricing, customer-centric pricing, and balancing price elasticity with competitive pricing. It provides granular pricing at the SKU level and offers a seamless adoption and onboarding process. The platform helps retailers optimize pricing strategies, increase margins, and save time on repricing.

Playground AI
Playground AI is a free-to-use online AI image creator that allows users to create and edit images like a professional without requiring advanced skills. The platform introduces Mixed Image Editing, enabling the combination of real and synthetic images to produce stunning works of art and photorealistic images limited only by the user's imagination. Users can edit images as they imagine, step outside the box, grow images beyond their edges, erase unnecessary elements, and fit objects into any scene. Playground AI fosters a creative community where users can share their creations, collaborate with others, and bring their ideas to life. With a user-friendly interface and powerful AI capabilities, Playground AI empowers users to unleash their creativity and design graphics effortlessly.

Ogma
Ogma is an interpretable symbolic general problem-solving model that utilizes a symbolic sequence modeling paradigm to address tasks requiring reliability, complex decomposition, and without hallucinations. It offers solutions in areas such as math problem-solving, natural language understanding, and resolution of uncertainty. The technology is designed to provide a structured approach to problem-solving by breaking down tasks into manageable components while ensuring interpretability and self-interpretability. Ogma aims to set benchmarks in problem-solving applications by offering a reliable and transparent methodology.

Minimax AI
Minimax AI is an AI platform developed by the Chinese startup MiniMax. It offers AI-driven tools, particularly for generating high-resolution videos from text prompts using their Video-01 model. The platform is accessible globally, requiring only mobile number registration. Users can create a wide range of content, including videos featuring well-known personalities, different artistic styles, and text overlays. While the services are currently free, there may be paid features introduced in the future. The platform is designed to be user-friendly and accessible across various devices.

Phenom
Phenom is an AI-powered talent experience platform that connects people, data, and interactions to deliver amazing experiences throughout the journey using intelligence and automation. It helps in hyper-personalizing candidate engagement, developing and retaining employees with intelligence, improving recruiter productivity through automation, and hiring talent faster with AI. Phenom offers a range of features and benefits to streamline the talent acquisition process and enhance the overall recruitment experience.

Paraphrasing Tool
Paraphrasing Tool is an AI-powered tool that helps users rewrite, edit, and change text to improve clarity and comprehension. It uses advanced artificial intelligence techniques to restructure sentences while retaining original meanings and improving structure and word flow. The tool is free to use and does not require any account creation. It is accessible on both desktop and mobile devices and processes data locally, ensuring privacy and security.

MARZ
MARZ is a technology and VFX company specializing in providing feature-film quality visual effects for TV productions. With a focus on innovation and leveraging proprietary AI solutions, MARZ aims to deliver outstanding VFX on fast timelines while remaining affordable for TV clients. The company has completed 128 projects in the first 4 years, received 2 VES nominations, 2 Emmy nominations, and employs a team of 260 staff, including 55 engineers, researchers, and technology experts.

Thirdai
Thirdai.com is an AI tool that offers a robot challenge screen for checking site connection security. The tool helps users assess the security of their website by requiring cookies to be enabled in the browser settings. It ensures that the connection is secure and provides recommendations for improving security measures.

DocAI
DocAI is an API-driven platform that enables you to implement contracts AI into your applications, without requiring development from the ground-up. Our AI identifies and extracts 1,300+ common legal clauses, provisions and data points from a variety of document types. Our AI is a low-code experience for all. Easily train new fields without the need for a data scientist. All you need is subject matter expertise. Flexible and scalable. Flexible deployment options in the Zuva hosted cloud or on prem, across multiple geographical regions. Reliable, expert-built AI our customers can trust. Over 1,300+ out of the box AI fields that are built and trained by experienced lawyers and subject matter experts. Fields identify and extract common legal clauses, provisions and data points from unstructured documents and contracts, including ones written in non-standard language.

Acobot
Acobot is an AI-powered e-commerce application that helps businesses increase sales by engaging visitors, converting them into leads and buyers, and retaining customers. It uses natural language processing (NLP) and machine learning (ML) to provide personalized shopping experiences, product recommendations, and automated email marketing campaigns.

Facetomany
Facetomany is an AI-powered tool that allows users to transform their face images into various styles such as 3D, emoji, pixel art, video game, claymation, or toy without requiring any artistic or coding skills. Users can upload a single photo as input and select the desired style, or provide a text prompt to control the generated style. The tool prioritizes privacy protection and offers advanced customization options for creating unique facial artworks.

Compass AI
Compass AI is an AI tool that offers automatic editing services for short videos. Users can upload their shorts and have Compass AI edit them quickly and efficiently. The platform is currently invite-only, requiring users to have an invitation code to access its services. Compass AI provides a seamless editing experience, allowing users to enhance their videos without the need for advanced editing skills.
20 - Open Source AI Tools

AwesomeLLM4APR
Awesome LLM for APR is a repository dedicated to exploring the capabilities of Large Language Models (LLMs) in Automated Program Repair (APR). It provides a comprehensive collection of research papers, tools, and resources related to using LLMs for various scenarios such as repairing semantic bugs, security vulnerabilities, syntax errors, programming problems, static warnings, self-debugging, type errors, web UI tests, smart contracts, hardware bugs, performance bugs, API misuses, crash bugs, test case repairs, formal proofs, GitHub issues, code reviews, motion planners, human studies, and patch correctness assessments. The repository serves as a valuable reference for researchers and practitioners interested in leveraging LLMs for automated program repair.

Nucleoid
Nucleoid is a declarative (logic) runtime environment that manages both data and logic under the same runtime. It uses a declarative programming paradigm, which allows developers to focus on the business logic of the application, while the runtime manages the technical details. This allows for faster development and reduces the amount of code that needs to be written. Additionally, the sharding feature can help to distribute the load across multiple instances, which can further improve the performance of the system.

factorio-learning-environment
Factorio Learning Environment is an open source framework designed for developing and evaluating LLM agents in the game of Factorio. It provides two settings: Lab-play with structured tasks and Open-play for building large factories. Results show limitations in spatial reasoning and automation strategies. Agents interact with the environment through code synthesis, observation, action, and feedback. Tools are provided for game actions and state representation. Agents operate in episodes with observation, planning, and action execution. Tasks specify agent goals and are implemented in JSON files. The project structure includes directories for agents, environment, cluster, data, docs, eval, and more. A database is used for checkpointing agent steps. Benchmarks show performance metrics for different configurations.

json-repair
JSON Repair is a toolkit designed to address JSON anomalies that can arise from Large Language Models (LLMs). It offers a comprehensive solution for repairing JSON strings, ensuring accuracy and reliability in your data processing. With its user-friendly interface and extensive capabilities, JSON Repair empowers developers to seamlessly integrate JSON repair into their workflows.

json_repair
This simple package can be used to fix an invalid json string. To know all cases in which this package will work, check out the unit test. Inspired by https://github.com/josdejong/jsonrepair Motivation Some LLMs are a bit iffy when it comes to returning well formed JSON data, sometimes they skip a parentheses and sometimes they add some words in it, because that's what an LLM does. Luckily, the mistakes LLMs make are simple enough to be fixed without destroying the content. I searched for a lightweight python package that was able to reliably fix this problem but couldn't find any. So I wrote one How to use from json_repair import repair_json good_json_string = repair_json(bad_json_string) # If the string was super broken this will return an empty string You can use this library to completely replace `json.loads()`: import json_repair decoded_object = json_repair.loads(json_string) or just import json_repair decoded_object = json_repair.repair_json(json_string, return_objects=True) Read json from a file or file descriptor JSON repair provides also a drop-in replacement for `json.load()`: import json_repair try: file_descriptor = open(fname, 'rb') except OSError: ... with file_descriptor: decoded_object = json_repair.load(file_descriptor) and another method to read from a file: import json_repair try: decoded_object = json_repair.from_file(json_file) except OSError: ... except IOError: ... Keep in mind that the library will not catch any IO-related exception and those will need to be managed by you Performance considerations If you find this library too slow because is using `json.loads()` you can skip that by passing `skip_json_loads=True` to `repair_json`. Like: from json_repair import repair_json good_json_string = repair_json(bad_json_string, skip_json_loads=True) I made a choice of not using any fast json library to avoid having any external dependency, so that anybody can use it regardless of their stack. Some rules of thumb to use: - Setting `return_objects=True` will always be faster because the parser returns an object already and it doesn't have serialize that object to JSON - `skip_json_loads` is faster only if you 100% know that the string is not a valid JSON - If you are having issues with escaping pass the string as **raw** string like: `r"string with escaping\"" Adding to requirements Please pin this library only on the major version! We use TDD and strict semantic versioning, there will be frequent updates and no breaking changes in minor and patch versions. To ensure that you only pin the major version of this library in your `requirements.txt`, specify the package name followed by the major version and a wildcard for minor and patch versions. For example: json_repair==0.* In this example, any version that starts with `0.` will be acceptable, allowing for updates on minor and patch versions. How it works This module will parse the JSON file following the BNF definition:

AeonLabs-AI-Volvo-MKII-Open-Hardware
This open hardware project aims to extend the life of Volvo P2 platform vehicles by updating them to current EU safety and emission standards. It involves designing and prototyping OEM hardware electronics that can replace existing electronics in these vehicles, using the existing wiring and without requiring reverse engineering or modifications. The project focuses on serviceability, maintenance, repairability, and personal ownership safety, and explores the advantages of using open solutions compared to conventional hardware electronics solutions.

Awesome-Code-LLM
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 wordsοΌEnsure 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)

Academic_LLM_Sec_Papers
Academic_LLM_Sec_Papers is a curated collection of academic papers related to LLM Security Application. The repository includes papers sorted by conference name and published year, covering topics such as large language models for blockchain security, software engineering, machine learning, and more. Developers and researchers are welcome to contribute additional published papers to the list. The repository also provides information on listed conferences and journals related to security, networking, software engineering, and cryptography. The papers cover a wide range of topics including privacy risks, ethical concerns, vulnerabilities, threat modeling, code analysis, fuzzing, and more.

eval-dev-quality
DevQualityEval is an evaluation benchmark and framework designed to compare and improve the quality of code generation of Language Model Models (LLMs). It provides developers with a standardized benchmark to enhance real-world usage in software development and offers users metrics and comparisons to assess the usefulness of LLMs for their tasks. The tool evaluates LLMs' performance in solving software development tasks and measures the quality of their results through a point-based system. Users can run specific tasks, such as test generation, across different programming languages to evaluate LLMs' language understanding and code generation capabilities.

LLM-PLSE-paper
LLM-PLSE-paper is a repository focused on the applications of Large Language Models (LLMs) in Programming Language and Software Engineering (PL/SE) domains. It covers a wide range of topics including bug detection, specification inference and verification, code generation, fuzzing and testing, code model and reasoning, code understanding, IDE technologies, prompting for reasoning tasks, and agent/tool usage and planning. The repository provides a comprehensive collection of research papers, benchmarks, empirical studies, and frameworks related to the capabilities of LLMs in various PL/SE tasks.

Kiln
Kiln is an intuitive tool for fine-tuning LLM models, generating synthetic data, and collaborating on datasets. It offers desktop apps for Windows, MacOS, and Linux, zero-code fine-tuning for various models, interactive data generation, and Git-based version control. Users can easily collaborate with QA, PM, and subject matter experts, generate auto-prompts, and work with a wide range of models and providers. The tool is open-source, privacy-first, and supports structured data tasks in JSON format. Kiln is free to use and helps build high-quality AI products with datasets, facilitates collaboration between technical and non-technical teams, allows comparison of models and techniques without code, ensures structured data integrity, and prioritizes user privacy.

llm-self-correction-papers
This repository contains a curated list of papers focusing on the self-correction of large language models (LLMs) during inference. It covers various frameworks for self-correction, including intrinsic self-correction, self-correction with external tools, self-correction with information retrieval, and self-correction with training designed specifically for self-correction. The list includes survey papers, negative results, and frameworks utilizing reinforcement learning and OpenAI o1-like approaches. Contributions are welcome through pull requests following a specific format.

Awesome_Test_Time_LLMs
This repository focuses on test-time computing, exploring various strategies such as test-time adaptation, modifying the input, editing the representation, calibrating the output, test-time reasoning, and search strategies. It covers topics like self-supervised test-time training, in-context learning, activation steering, nearest neighbor models, reward modeling, and multimodal reasoning. The repository provides resources including papers and code for researchers and practitioners interested in enhancing the reasoning capabilities of large language models.

ClipboardConqueror
Clipboard Conqueror is a multi-platform omnipresent copilot alternative. Currently requiring a kobold united or openAI compatible back end, this software brings powerful LLM based tools to any text field, the universal copilot you deserve. It simply works anywhere. No need to sign in, no required key. Provided you are using local AI, CC is a data secure alternative integration provided you trust whatever backend you use. *Special thank you to the creators of KoboldAi, KoboldCPP, llamma, openAi, and the communities that made all this possible to figure out.

python-tgpt
Python-tgpt is a Python package that enables seamless interaction with over 45 free LLM providers without requiring an API key. It also provides image generation capabilities. The name _python-tgpt_ draws inspiration from its parent project tgpt, which operates on Golang. Through this Python adaptation, users can effortlessly engage with a number of free LLMs available, fostering a smoother AI interaction experience.

cheating-based-prompt-engine
This is a vulnerability mining engine purely based on GPT, requiring no prior knowledge base, no fine-tuning, yet its effectiveness can overwhelmingly surpass most of the current related research. The core idea revolves around being task-driven, not question-driven, driven by prompts, not by code, and focused on prompt design, not model design. The essence is encapsulated in one word: deception. It is a type of code understanding logic vulnerability mining that fully stimulates the capabilities of GPT, suitable for real actual projects.

LongBench
LongBench v2 is a benchmark designed to assess the ability of large language models (LLMs) to handle long-context problems requiring deep understanding and reasoning across various real-world multitasks. It consists of 503 challenging multiple-choice questions with contexts ranging from 8k to 2M words, covering six major task categories. The dataset is collected from nearly 100 highly educated individuals with diverse professional backgrounds and is designed to be challenging even for human experts. The evaluation results highlight the importance of enhanced reasoning ability and scaling inference-time compute to tackle the long-context challenges in LongBench v2.
12 - OpenAI Gpts

Boat Patcher, Plastic Assistant
Hello I'm Boat Patcher, Plastic Assistant! What would you like help with today?

MediTech Helper
Assists in fixing medical devices with technical guidance and troubleshooting tips.

Xianxia Story Generator
Transforms text into Xianxia-style fantasy while retaining character names.

Web Designer
Designs and improves website layouts for optimal user experience, requiring knowledge of design and web technologies.

π Data Privacy for Home Inspection & Appraisal π
Home Inspection and Appraisal Services have access to personal property and related information, requiring them to be vigilant about data privacy.

π Data Privacy for Freelancers & Independents π
Freelancers and Independent Consultants, individuals in these roles often handle client data, project specifics, and personal contact information, requiring them to be vigilant about data privacy.

π Data Privacy for Real Estate Agencies π
Real Estate Agencies and Brokers deal with personal data of clients, including financial information and preferences, requiring careful handling and protection of such data.

π Data Privacy for Fitness & Wellness Centers π
Fitness and Wellness Centers collect personal health and fitness data of their clients, including potentially sensitive health metrics, requiring careful handling and protection of this data.

ει·γε΅γ£γεθ²γ¦γ΅γγΌγGPT
εθ²γ¦γ«ι’γγθ³ͺεγζ©γΏγ«ηγγΎγ

Genialidad Parental
Tu guΓa GPT imprescindible para consejos prΓ‘cticos y empΓ‘ticos sobre crianza. Desde manejar berrinches hasta fortalecer los lazos familiares, obtΓ©n estrategias y consejos de expertos adaptados a las necesidades de tu familia. Β‘InteractΓΊa, aprende y transforma tu viaje de crianza!