Best AI tools for< Improve Responses >

LLM Quality Beefer-Upper is an AI tool designed to enhance the quality and productivity of LLM responses by automating critique, reflection, and improvement. Users can generate multi-agent prompt drafts, choose from different quality levels, and upload knowledge text for processing. The application aims to maximize output quality by utilizing the best available LLM models in the market.

MasterInterview is your ultimate AI interview coach, designed to help you master job-specific interviews through interactive sessions. Backed by industry experts and powered by advanced GPT-4 technology, the platform offers personalized feedback, tailored interview questions, and virtual interview sessions with a fox avatar. With comprehensive feedback and revised answers, MasterInterview aims to assist candidates in landing their dream jobs effectively and efficiently.

CasperPractice is an AI-powered toolkit designed to help individuals prepare for the Casper test, an open-response situational judgment test used for admissions to various professional schools. The platform offers personalized practice scenarios, instant quartile grading, detailed feedback, video answers, and a fully simulated test environment. With a large question bank and unlimited practice options, users can improve their test-taking skills and aim for a top quartile score. CasperPractice is known for its affordability, instant feedback, and realistic simulation, making it a valuable resource for anyone preparing for the Casper test.

Consultan is an AI tool designed to help users practice consulting interviews. It provides instant expert feedback on responses, offering unbiased reviews and suggestions. The tool is free to use and includes interview questions from top consulting firms like McKinsey, Bain, BCG, and Deloitte.

Superseek is a custom ChatGPT AI tool designed to help businesses enhance customer service by creating custom AI assistants that can resolve customer queries instantly. It offers multilingual answers in over 95 languages, powered by the user's content to ensure accuracy. Superseek allows users to customize their AI agents without any coding knowledge, capture leads with timely forms, and seamlessly handoff complex queries to human teams. It provides different pricing plans with varying features and advantages to suit different business needs.

Fini is a customer support AI chatbot that helps businesses resolve customer queries, increase retention, revenue, and activation. It integrates with various platforms like Zendesk, Slack, and Discord, and can be customized to match the tone and character of the business. Fini uses machine learning to learn from customer interactions and improve its responses over time. It offers features such as seamless human routing, multi-channel deployment, and feedback-based learning.

Downtobid is an AI-powered bidding software designed for General Contractors. It helps in turning construction plans into Bid Invites in minutes by identifying bid packages in drawings, creating custom subcontractor invite lists, and streamlining bidding processes. The platform offers features like AI-powered scope reviews, smart planroom creation, project-specific sublists, personalized email communication, and real-time contractor data. Downtobid aims to save time, improve bid responses, and enhance project success by leveraging artificial intelligence technology.

MARA AI Review Management is an AI tool designed to help businesses manage and respond to online reviews efficiently. It offers features such as Review Inbox, Review Analytics, Surveys, AI Review Reply Generator, and Smart Snippets. MARA AI utilizes personalized AI responses to improve response rates, save time, and enhance online reputation. With a user-friendly interface and personalized responses, MARA AI is a valuable tool for businesses looking to streamline their review management process.

RoboResponseAI is a proactive AI chatbot customized for businesses, designed to initiate conversations, take feedback, and drive lead conversions. It offers features such as lead conversion guidance, recruitment assistance, quick chatbot training, interactive ad campaigns, and seamless integration with various platforms. The application aims to enhance customer engagement, streamline support processes, and improve lead generation for businesses of all types.

Neurons is a platform that uses AI to predict consumer responses and behavior. It offers a variety of solutions for businesses, including marketing agencies, designers, and e-commerce companies. Neurons' AI-powered tools can help businesses optimize their marketing campaigns, improve their product design, and better understand their customers.

AI Mail Assistant is a Gmail add-on powered by OpenAI's ChatGPT that helps users streamline their email communication. It offers a range of features including generating quick and accurate email responses, summarizing emails, translating messages, and improving the grammar and wording of drafts. The tool is designed to save time, avoid language barriers and mistakes, and ensure clear and professional communication.

Caffeinated CX is an AI-powered customer support solution that helps businesses improve their customer support efficiency. It offers a range of features, including AI-powered response generation, ticket auto-triage, macro suggestion, and more. Caffeinated CX integrates with all major support software and is easy to implement. It is used by leading brands across industries and has helped them achieve significant improvements in their customer support metrics.

heardeer is an AI-powered user interview platform that helps businesses collect valuable feedback from their users. With heardeer, you can create custom interview questionnaires, share them with your users, and let AI manage the interviews. heardeer's AI engine will ask your users questions, follow up on their answers, and provide you with detailed insights into their feedback. This can help you understand your users' needs, improve your products and services, and make better decisions.

TalkbackAi is a Chrome browser extension that automates customer feedback responses using artificial intelligence. It allows users to define their brand voice, generate unique replies tailored to their style, and customize responses before using them. The extension integrates with various systems, making it easy to respond to reviews from different platforms. TalkbackAi is designed to save time and improve the efficiency of customer support teams and businesses.

TheySaid is a Conversational AI Survey tool that helps businesses drive customer value and revenue through AI-powered surveys. It offers a unique approach of engaging audiences with one relevant question at a time, turning feedback into an ongoing dialogue. The AI tool scans websites to generate tailored survey questions, automates follow-ups with customers, and provides actionable insights based on industry standards and best practices. TheySaid's AI digs deeper by asking personalized follow-up questions in real-time, enhancing customer engagement and satisfaction.

Reprompt is a prompt testing tool designed to help developers save time and make data-driven decisions about their prompts. It allows users to analyze more data in less time, easily identify anomalies, and speed up debugging by testing multiple scenarios at once. With Reprompt, users can have confidence in their changes by comparing with previous versions. The tool also offers real-time trading, < 1 sec operations, no commissions, built-in enterprise encryption and security, 256-bit AES encryption, and advanced security standards.

Instant Answers is an AI-powered chatbot builder that enables users to create customized chatbots for their websites in minutes. The platform allows users to train their chatbots to provide instant answers to a wide range of questions by uploading documents or inputting website URLs. With features like easy customization, effortless integration, conversation analytics, and dynamic learning, Instant Answers offers a user-friendly interface for enhancing customer service and engagement.

LangWatch is a monitoring and analytics tool for Generative AI (GenAI) solutions. It provides detailed evaluations of the faithfulness and relevancy of GenAI responses, coupled with user feedback insights. LangWatch is designed for both technical and non-technical users to collaborate and comment on improvements. With LangWatch, you can understand your users, detect issues, and improve your GenAI products.

TenderCrunch is an RFP response management software that helps businesses streamline their tenders and win more deals. It provides a centralized library to store and organize all the information needed to respond to RFPs, RFIs, DDQs, and security questionnaires. TenderCrunch also uses AI to help users find the right answer in seconds, collaborate with their team, and answer questions automatically. As a result, businesses can save time, improve the accuracy of their responses, and win more deals.

BugFree.ai is an AI-powered platform designed to help users practice system design and behavior interviews, similar to Leetcode. The platform offers a range of features to assist users in preparing for technical interviews, including mock interviews, real-time feedback, and personalized study plans. With BugFree.ai, users can improve their problem-solving skills and gain confidence in tackling complex interview questions.

The Together Cookbook is a collection of code and guides designed to help developers build with open source models using Together AI. The recipes provide examples on how to chain multiple LLM calls, create agents that route tasks to specialized models, run multiple LLMs in parallel, break down tasks into parallel subtasks, build agents that iteratively improve responses, perform LoRA fine-tuning and inference, fine-tune LLMs for repetition, improve summarization capabilities, fine-tune LLMs on multi-step conversations, implement retrieval-augmented generation, conduct multimodal search and conditional image generation, visualize vector embeddings, improve search results with rerankers, implement vector search with embedding models, extract structured text from images, summarize and evaluate outputs with LLMs, generate podcasts from PDF content, and get LLMs to generate knowledge graphs.

Aligner is a model-agnostic alignment tool designed to efficiently correct responses from large language models. It redistributes initial answers to align with human intentions, improving performance across various LLMs. The tool can be applied with minimal training, enhancing upstream models and reducing hallucination. Aligner's 'copy and correct' method preserves the base structure while enhancing responses. It achieves significant performance improvements in helpfulness, harmlessness, and honesty dimensions, with notable success in boosting Win Rates on evaluation leaderboards.

vnc-lm is a Discord bot designed for messaging with language models. Users can configure model parameters, branch conversations, and edit prompts to enhance responses. The bot supports various providers like OpenAI, Huggingface, and Cloudflare Workers AI. It integrates with ollama and LiteLLM, allowing users to access a wide range of language model APIs through a single interface. Users can manage models, switch between models, split long messages, and create conversation branches. LiteLLM integration enables support for OpenAI-compatible APIs and local LLM services. The bot requires Docker for installation and can be configured through environment variables. Troubleshooting tips are provided for common issues like context window problems, Discord API errors, and LiteLLM issues.

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.

Top AI Tools is a comprehensive, community-curated directory that aims to catalog and showcase the most outstanding AI-powered products. This index is not exhaustive, but rather a compilation of our research and contributions from the community.

Awesome AI Tools is a curated list of popular tools and resources for artificial intelligence enthusiasts. It includes a wide range of tools such as machine learning libraries, deep learning frameworks, data visualization tools, and natural language processing resources. Whether you are a beginner or an experienced AI practitioner, this repository aims to provide you with a comprehensive collection of tools to enhance your AI projects and research. Explore the list to discover new tools, stay updated with the latest advancements in AI technology, and find the right resources to support your AI endeavors.

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: ::= | ::= | | ; Where: ; is a valid real number expressed in one of a number of given formats ; is a string of valid characters enclosed in quotes ; is one of the literal strings 'true', 'false', or 'null' (unquoted) ::=