Search Results for "report builder python"
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Showing 23 open source projects for "report builder python"
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Automate contact and company data extractionGenerate leads at scale without building or maintaining scrapers. Use 10,000+ ready-made tools that handle authentication, pagination, and anti-bot protection. Pull data from business directories, social profiles, and public sources, then export to your CRM or database via API. Schedule recurring extractions, enrich existing datasets, and integrate with your workflows.
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Langflow
Low-code app builder for RAG and multi-agent AI applications
Langflow is a low-code app builder for RAG and multi-agent AI applications. It’s Python-based and agnostic to any model, API, or database. -
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PyBoy
Game Boy emulator written in Python
It is highly recommended to read the report to get a light introduction to Game Boy emulation. But do be aware, that the Python implementation has changed a lot. The report is relevant, even though you want to contribute to another emulator or create your own. If you are looking to make a bot or AI, you can find all the external components in the PyBoy Documentation. There is also a short example on our Wiki page Scripts, AI and Bots as well as in the examples directory. ... -
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DeerFlow
Deep Research framework, combining language models with tools
DeerFlow is an open-source, community-driven “deep research” framework / multi-agent orchestration platform developed by ByteDance. It aims to combine the reasoning power of large language models (LLMs) with automated tool-use — such as web search, web crawling, Python execution, and data processing — to enable complex, end-to-end research workflows. Instead of a monolithic AI assistant, DeerFlow defines multiple specialized agents (e.g. “planner,” “searcher,” “coder,” “report generator”) that collaborate in a structured workflow, allowing tasks like literature reviews, data gathering, data analysis, code execution, and final report generation to be largely automated. ... -
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AutoGPT
Powerful tool that lets you create and run intelligent agents
AutoGPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, AutoGPT pushes the boundaries of what is possible with AI. -
Turn more customers into advocates.The platform's advanced capabilities ensure companies get the most out of their referral programs. Leverage custom events, profiles, and attributes to enable dynamic, audience-specific referral experiences. Use first-party data to tailor customer segment messaging, rewards, and engagement strategies. Use our flexible APIs to build management capabilities and consumer experiences–headlessly or hybrid. We have all the tools you need to build scalable, secure, and high-performing referral programs.
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Shapash
Explainability and Interpretability to Develop Reliable ML models
Shapash is a Python library dedicated to the interpretability of Data Science models. It provides several types of visualization that display explicit labels that everyone can understand. Data Scientists can more easily understand their models, share their results and easily document their projects in an HTML report. End users can understand the suggestion proposed by a model using a summary of the most influential criteria. -
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LLMStack
No-code multi-agent framework to build LLM Agents, workflows
LLMStack is a no-code platform for building generative AI agents, workflows and chatbots, connecting them to your data and business processes. Build tailor-made generative AI agents, applications and chatbots that cater to your unique needs by chaining multiple LLMs. Seamlessly integrate your own data, internal tools and GPT-powered models without any coding experience using LLMStack's no-code builder. Trigger your AI chains from Slack or Discord. Deploy to the cloud or on-premise. -
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Agent Zero
Agent Zero AI framework
Agent Zero is not a predefined agentic framework. It is designed to be dynamic, organically growing, and learning as you use it. Agent Zero is fully transparent, readable, comprehensible, customizable and interactive. Agent Zero uses the computer as a tool to accomplish its (your) tasks. Agents can communicate with their superiors and subordinates, asking questions, giving instructions, and providing guidance. Instruct your agents in the system prompt on how to communicate effectively. The... -
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MLJAR Studio
Python package for AutoML on Tabular Data with Feature Engineering
...It is no black box, as you can see exactly how the ML pipeline is constructed (with a detailed Markdown report for each ML model). -
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nanochat
The best ChatGPT that $100 can buy
nanochat is a from-scratch, end-to-end “mini ChatGPT” that shows the entire path from raw text to a chatty web app in one small, dependency-lean codebase. The repository stitches together every stage of the lifecycle: tokenizer training, pretraining a Transformer on a large web corpus, mid-training on dialogue and multiple-choice tasks, supervised fine-tuning, optional reinforcement learning for alignment, and finally efficient inference with caching. Its north star is approachability and... -
Failed Payment Recovery for Subscription BusinessesFlexPay’s innovative platform uses multiple technologies to achieve the highest number of retained customers, resulting in reduced involuntary churn, longer life span after recovery, and higher revenue. Leading brands like LegalZoom, Hooked on Phonics, and ClinicSense trust FlexPay to recover failed payments, reduce churn, and increase customer lifetime value.
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AIF360
A comprehensive set of fairness metrics for datasets
This extensible open source toolkit can help you examine, report, and mitigate discrimination and bias in machine learning models throughout the AI application lifecycle. We invite you to use and improve it. The AI Fairness 360 toolkit is an extensible open-source library containing techniques developed by the research community to help detect and mitigate bias in machine learning models throughout the AI application lifecycle. -
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CutLER
Code release for Cut and Learn for Unsupervised Object Detection
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to... -
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BISHENG
BISHENG is an open LLM devops platform for next generation apps
BISHENG is an open LLM application DevOps platform, focusing on enterprise scenarios. It has been used by a large number of industry-leading organizations and Fortune 500 companies. "Bi Sheng" was the inventor of movable type printing, which played a vital role in promoting the transmission of human knowledge. We hope that BISHENG can also provide strong support for the widespread implementation of intelligent applications. Everyone is welcome to participate. -
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Deepchecks
Test Suites for validating ML models & data
Deepchecks is the leading tool for testing and for validating your machine learning models and data, and it enables doing so with minimal effort. Deepchecks accompany you through various validation and testing needs such as verifying your data’s integrity, inspecting its distributions, validating data splits, evaluating your model and comparing between different models. While you’re in the research phase, and want to validate your data, find potential methodological problems, and/or validate... -
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Pandas Profiling
Create HTML profiling reports from pandas DataFrame objects
pandas-profiling generates profile reports from a pandas DataFrame. The pandas df.describe() function is handy yet a little basic for exploratory data analysis. pandas-profiling extends pandas DataFrame with df.profile_report(), which automatically generates a standardized univariate and multivariate report for data understanding. High correlation warnings, based on different correlation metrics (Spearman, Pearson, Kendall, Cramér’s V, Phik). Most common categories (uppercase, lowercase,... -
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Joget
AI Powered Open Source Platform to Easily Build Enterprise Web Apps
Joget offers an open-source, AI-powered platform that converges no-code/low-code development with AI to rapidly build and customize enterprise applications at scale. By combining AI with visual app builders—not raw code—Joget makes app generation faster, safer, and more accessible for everyone. With Generative AI and Agentic AI capabilities, Joget Intelligence enables organizations to automate and enhance processes while maintaining oversight and compliance. Unlike typical AI code... -
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MiniMax-01
Large-language-model & vision-language-model based on Linear Attention
MiniMax-01 is the official repository for two flagship models: MiniMax-Text-01, a long-context language model, and MiniMax-VL-01, a vision-language model built on top of it. MiniMax-Text-01 uses a hybrid attention architecture that blends Lightning Attention, standard softmax attention, and Mixture-of-Experts (MoE) routing to achieve both high throughput and long-context reasoning. It has 456 billion total parameters with 45.9 billion activated per token and is trained with advanced parallel... -
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CodinIT.dev
Free, local, open-source AI app builder
CodinIT.dev is a free, local, open source AI app builder that lets you go from idea to full-stack application entirely on your machine, no coding required, just chat with AI. You can build unlimited apps with real-time previews, instant undo, and responsive, frictionless workflows. Deep Supabase integration means you can create UI and backend logic in one cohesive environment, while the model-agnostic architecture lets you connect to any AI, whether cloud-based (Gemini 3 Pro, GPT-5,... -
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GLM-4-32B-0414
Open Multilingual Multimodal Chat LMs
GLM-4-32B-0414 is a powerful open-source large language model featuring 32 billion parameters, designed to deliver performance comparable to leading models like OpenAI’s GPT series. It supports multilingual and multimodal chat capabilities with an extensive 32K token context length, making it ideal for dialogue, reasoning, and complex task completion. The model is pre-trained on 15 trillion tokens of high-quality data, including substantial synthetic reasoning datasets, and further enhanced... -
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smclarify
Fairness aware machine learning. Bias detection and mitigation
Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models. A facet is column or feature that will be used to measure bias against. A facet can have value(s) that designates that sample as "sensitive". Bias detection and mitigation for datasets and models. The label is a column or feature which is the target for training a machine learning model. The label can have value(s) that designates that sample as having a "positive" outcome. A bias measure is a function... -
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Grade School Math
8.5K high quality grade school math problems
The grade-school-math repository (sometimes called GSM8K) is a curated dataset of 8,500 high-quality grade school math word problems intended for evaluating mathematical reasoning capabilities of language models. It is structured into 7,500 training problems and 1,000 test problems. These aren’t trivial exercises — many require multi-step reasoning, combining arithmetic operations, and handling intermediate steps (e.g. “If she sold half as many in May… how many in total?”). The problems are... -
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Convolution arithmetic
A technical report on convolution arithmetic in deep learning
A technical report on convolution arithmetic in the context of deep learning. The code and the images of this tutorial are free to use as regulated by the licence and subject to proper attribution. The animations will be output to the gif directory. Individual animation steps will be output in PDF format to the pdf directory and in PNG format to the png directory. We introduce a guide to help deep learning practitioners understand and manipulate convolutional neural network architectures.... -
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Open Metaheuristic (oMetah) is a library aimed at the conception and the rigourous testing of metaheuristics (i.e. genetic algorithms, simulated annealing, ...). The code design is separated in components : algorithms, problems and a test report generator
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hexabot
Hexabot is an open-source AI chatbot / agent builder.
Hexabot is an open-source AI chatbot / agent solution. It allows you to create and manage multi-channel, and multilingual chatbots / agents with ease. Hexabot is designed for flexibility and customization, offering powerful text-to-action capabilities. Originally a closed-source project (version 1), we've now open-sourced version 2 to contribute to the community and enable developers to customize and extend the platform with extensions.
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