Search Results for "ask"
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Showing 64 open source projects for "ask"
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1
PandasAI
PandasAI is a Python library that integrates generative AI
...It is designed to be used in conjunction with pandas, and is not a replacement for it. PandasAI makes pandas (and all the most used data analyst libraries) conversational, allowing you to ask questions to your data in natural language. For example, you can ask PandasAI to find all the rows in a DataFrame where the value of a column is greater than 5, and it will return a DataFrame containing only those rows. -
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DeepWiki Open
AI-Powered Wiki Generator for GitHub/Gitlab/Bitbucket Repositories
...DeepWiki’s output turns raw repositories into interactive, web-style wikis complete with navigable sections, diagrams, and contextual explanations, making it easier for developers and collaborators to understand unfamiliar code. It includes an “Ask” feature that lets users query the generated wiki using RAG-style retrieval, enabling interactive question-answering and exploration. -
3
OpenBB
Investment Research for Everyone, Everywhere
...Whether it’s a CSV file, a private endpoint, an RSS feed, or even embed an SEC filing directly. Chat with financial data using large language models. Don’t waste time reading, create summaries in seconds and ask how that impacts investments. Create your dashboard with your favorite widgets. Create charts directly from raw data in seconds. Create charts directly from raw data in seconds. Customize your dashboards to build your dream terminal, integrate with your private datasets and bring your own fine-tuned AI copilots. -
4
Snoop Project
This is the most powerful software taking into account CIS location
...Snoop Project is one of the most promising OSINT tools for finding nicknames. This is the most powerful software taking into account the CIS location. Is your life slideshow? Ask Snoop. Snoop project is developed without taking into account the opinions of the NSA and their friends, that is, it is available to the average user. Snoop is a research work (own database / closed bugbounty) in the field of searching and processing public data on the Internet. In terms of specialized search, Snoop is able to compete with traditional search engines. -
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5
WikiChat
WikiChat is an improved RAG
WikiChat is a chatbot framework designed to interactively retrieve and summarize Wikipedia information, allowing users to ask questions and get context-aware responses? -
6
UI UX Pro Max
AI SKILL that provide design intelligence
...It uses an AI reasoning engine to generate complete design systems tailored to project requirements, recommending layouts, typography, colors, spacing, and component structures automatically based on natural language prompts. Users can ask for specific UI/UX tasks or design patterns, and the skill will produce guidelines, code snippets, and responsive implementation suggestions that align with industry best practices and accessibility standards. It supports a broad range of tech stacks including HTML/Tailwind, React, Vue, mobile UI frameworks, and more, making it versatile for designers and developers alike. ... -
7
MoviePy
Video editing with Python
...MoviePy is an open source software originally written by Zulko and released under the MIT licence. It works on Windows, Mac, and Linux, with Python 2 or Python 3. The code is hosted on Github, where you can push improvements, report bugs and ask for help. There is also a MoviePy forum on Reddit and a mailing list on librelist. MoviePy depends on the Python modules NumPy, Imageio, Decorator, and Proglog, which will be automatically installed during MoviePy's installation. The software FFMPEG should be automatically downloaded/installed (by imageio) during your first use of MoviePy (installation will take a few seconds). -
8
folium
Python data, Leaflet.js maps
...The library has a number of built-in tilesets from OpenStreetMap, Mapbox, and Stamen, and supports custom tilesets with Mapbox or Cloudmade API keys. folium supports both Image, Video, GeoJSON and TopoJSON overlays. To create a base map, simply pass your starting coordinates to Folium. To display it in a Jupyter notebook, simply ask for the object representation. The default tiles are set to OpenStreetMap, but Stamen Terrain, Stamen Toner, Mapbox Bright, and Mapbox Control Room, and many others tiles are built in. -
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Open Interpreter
A natural language interface for computers
Open Interpreter is an open-source tool that provides a natural-language interface for interacting with your computer. It lets large language models (LLMs) run code locally (Python, JavaScript, shell, etc.), enabling you to ask your computer to do tasks like data analysis, file manipulation, browsing, etc. in human terms (“chat with your computer”), with safeguards. Runs locally or via configured remote LLM servers/inference backends, giving flexibility to use models you trust or have locally. It prompts you to approve code before executing, and supports both online LLM models and local inference servers. ... -
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10
MNE-Python
Magnetoencephalography (MEG) and Electroencephalography EEG in Python
Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more. -
11
Testinfra
Testinfra test your infrastructures
...When installing, you should select the backends you require as extras to ensure Python dependencies are satisfied (note various system packaged tools may still be required). This is the default backend when a hosts list is provided. Paramiko is a Python implementation of the SSHv2 protocol. Testinfra will not ask you for a password, so you must be able to connect without a password (using passwordless keys or using ssh-agent). -
12
QAnything
Question and Answer based on Anything
QAnything is a local knowledge-base question-answering system designed to let users ask questions over many kinds of files and databases. It supports offline installation, making it useful for organizations that need private document analysis without sending data to external services. Users can upload local files and receive fast, reliable answers based on the indexed content. The system supports formats such as PDF, Word, PowerPoint, Excel, Markdown, email, text, images, CSV, and web links. ... -
13
Anything to NotebookLM
Multi-source content processor for NotebookLM
...It is built for users who want to convert articles, web pages, videos, PDFs, office files, podcasts, images, and search results into more usable study or presentation formats. The project uses natural-language commands, so the user can ask for a podcast, slide deck, mind map, report, quiz, flashcards, or infographic without manually building the workflow. It supports multilingual material, with especially strong use cases for Chinese and English content. The tool can process files locally, extract or transcribe content when needed, and hand the cleaned material to NotebookLM for generation. ... -
14
Code-Graph-RAG
The ultimate RAG for your monorepo
...It uses Tree-sitter to parse source code into abstract syntax trees, extracting relationships between functions, classes, and modules to build a graph-based representation of the entire codebase. This structured approach enables more accurate and context-aware querying compared to traditional text-based search methods, allowing users to ask natural language questions about code structure and functionality. The system integrates with graph databases such as Memgraph to store and manage relationships, enabling efficient querying and visualization of complex dependencies. It also supports AI-driven query translation, converting natural language into graph queries for deeper analysis and interaction. -
15
CLIP
CLIP, Predict the most relevant text snippet given an image
...It was trained on large sets of (image, caption) pairs using a contrastive objective: images and their matching text are pulled together in embedding space, while mismatches are pushed apart. Once trained, you can give it any text labels and ask it to pick which label best matches a given image—even without explicit training for that classification task. The repository provides code for model architecture, preprocessing transforms, evaluation pipelines, and example inference scripts. Because it generalizes to arbitrary labels via text prompts, CLIP is a powerful tool for tasks that involve interpreting images in terms of descriptive language. -
16
Mistral Vibe CLI
Minimal CLI coding agent by Mistral
Mistral Vibe is an AI-powered “vibe-coding” command-line interface (CLI) and coding-assistant framework built by Mistral AI to let developers write, refactor, search, and manage code through natural language and context-aware automation, rather than manual typing only. It aims to take developers out of repetitive boilerplate and let them stay “in the flow”: you can ask the tool to generate functions, refactor code, search across the codebase, manipulate files, commit changes via Git, or run commands — all from a unified CLI interface. Behind the scenes, it leverages Mistral’s coding-optimized LLM stack (including models tuned for code understanding and generation), with project-wide context awareness: it scans your file structure, Git status, and recent history to inform suggestions so that generated code aligns with existing context. -
17
ThinkStats2
Text and supporting code for Think Stats, 2nd Edition
...It teaches probability and statistical reasoning through short programs, experiments, and analysis of real datasets. The material emphasizes exploratory methods that help readers ask and answer practical questions with data. Case studies draw from public sources, including health-related datasets, to connect abstract concepts with realistic analysis. Each chapter has a notebook containing examples and exercises, along with a separate version that includes solutions. The repository also provides reusable thinkstats2 and thinkplot packages, homework material, workshops, and book-building files. ... -
18
tsai
Time series Timeseries Deep Learning Machine Learning Pytorch fastai
...Other soft dependencies (which are only required for selected tasks) will not be installed by default (this is the recommended approach. If you require any of the dependencies that is not installed, tsai will ask you to install it when necessary) We've also added a new PredictionDynamics callback that will display the predictions during training. This is the type of output you would get in a classification task. New tutorial notebook on how to train your model with larger-than-memory datasets in less time achieving up to 100% GPU usage! See our new tutorial notebook on how to track your experiments with Weights & Biases -
19
Haystack
Haystack is an open source NLP framework to interact with your data
...Implement production-ready semantic search, question answering, summarization and document ranking for a wide range of NLP applications. Evaluate components and fine-tune models. Ask questions in natural language and find granular answers in your documents using the latest QA models with the help of Haystack pipelines. Perform semantic search and retrieve ranked documents according to meaning, not just keywords! Make use of and compare the latest pre-trained transformer-based languages models like OpenAI’s GPT-3, BERT, RoBERTa, DPR, and more. ... -
20
DevOps Exercises
Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git
...The repository gets frequent contributions, keeping it aligned with current tooling and practices. It is widely used by people preparing for DevOps roles because it mirrors the style and depth of questions companies actually ask. -
21
files-to-prompt
Concatenate a directory full of files into a single prompt
...It walks the directory tree, outputting each file preceded by its relative path and a separator, so a model can understand which content came from where. The tool is aimed at workflows where you want to ask an LLM questions about a whole codebase, documentation set, or notes folder without manually copying files together. It includes rich filtering controls, letting you limit by extension, include or skip hidden files, and ignore paths that match glob patterns or .gitignore rules. The output format is flexible: you can emit plain text, Markdown with fenced code blocks, or a Claude-XML style format designed for structured multi-file prompts. ... -
22
Paperless-AI
AI-powered document analysis and tagging for Paperless-ngx
...A key capability is its use of retrieval-augmented generation, which enables semantic search and natural language interaction across an entire document archive. Users can ask contextual questions about their files and receive precise answers based on full document understanding rather than simple keyword matching. Paperless-AI also includes a web interface for manual review and tagging, allowing greater control when handling sensitive or complex documents. -
23
MING
A large-scale model of medical consultation in Chinese
...It is trained using medical instruction tuning so that the model can understand patient symptoms and respond with structured explanations and clinical suggestions. One of its primary goals is to simulate a multi-round medical consultation process, allowing the system to ask follow-up questions before offering diagnostic recommendations. This interactive capability makes it suitable for conversational health applications, patient triage scenarios, and educational demonstrations. The model is built on transformer-based architectures using frameworks such as PyTorch and integrates with Hugging Face tooling for training and inference workflows. -
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Sage Chat
Chat with any codebase in under two minutes | Fully local
...The tool functions similarly to an intelligent research agent that can analyze a repository and answer questions about how the software works. Instead of focusing solely on code generation, Sage emphasizes code comprehension, system architecture analysis, and integration guidance. Developers can ask natural language questions about a project, and the system responds with explanations supported by references to the relevant code, documentation, or external technical resources. The project aims to act as a contextual knowledge layer for software teams by combining language models with repository indexing and documentation retrieval. ... -
25
Poetiq
Reproduction of Poetiq's record-breaking submission to the ARC-AGI-1
...The project demonstrates a system that orchestrates large language models (LLMs) — like those from major providers — with carefully engineered prompting, reasoning workflows, and dynamic strategies, to tackle the abstract, logic-heavy problems in ARC-AGI. Instead of relying on a single prompt or fixed strategy, their solver dynamically adapts the reasoning path, selecting what to ask or analyze next depending on intermediate results — effectively compositing reasoning, perception, and program synthesis (or symbolic manipulation) in a loop. The repository allows others to reproduce their results, experiment with different LLM backends (e.g. the user may supply keys for supported models), and observe how their adaptive meta-system handles the logic and abstraction challenges.
