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Showing 22 open source projects for "types"
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LangChain
⚡ Building applications with LLMs through composability ⚡
...But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. This library is aimed at assisting in the development of those types of applications. -
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LiteLLM
lightweight package to simplify LLM API calls
Call all LLM APIs using the OpenAI format [Anthropic, Huggingface, Cohere, Azure OpenAI etc.] liteLLM supports streaming the model response back, pass stream=True to get a streaming iterator in response. Streaming is supported for OpenAI, Azure, Anthropic, and Huggingface models. -
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Synthetic Data Generator
SDG is a specialized framework
...The system supports multiple generation methods including statistical models, generative adversarial networks, and large language model–based synthesis. It also includes a data processing module capable of handling different data types, preprocessing columns, managing missing values, and converting formats automatically before model training. -
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text-extract-api
Document (PDF, Word, PPTX ...) extraction and parse API
...Instead of requiring developers to integrate multiple document parsing libraries individually, the system centralizes text extraction capabilities into a unified API that standardizes the output. The platform supports automated processing pipelines that detect file types and apply the appropriate extraction method to obtain the most accurate text representation possible. It can be integrated into document analysis systems, knowledge retrieval tools, and AI pipelines that rely on clean textual data. The architecture is designed to be lightweight and easily deployable, making it suitable for both local installations and cloud environments. -
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Qwen-Image
Qwen-Image is a powerful image generation foundation model
Qwen-Image is a powerful 20-billion parameter foundation model designed for advanced image generation and precise editing, with a particular strength in complex text rendering across diverse languages, especially Chinese. Built on the MMDiT architecture, it achieves remarkable fidelity in integrating text seamlessly into images while preserving typographic details and layout coherence. The model excels not only in text rendering but also in a wide range of artistic styles, including... -
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MegaParse
File Parser optimised for LLM Ingestion with no loss
...It efficiently parses various document formats, such as PDFs, DOCX, and PPTX, converting them into formats ideal for processing by LLMs. This tool is essential for applications that require accurate and comprehensive data extraction from diverse document types. -
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embedchain
Framework to easily create LLM powered bots over any dataset
Embedchain is a framework to easily create LLM-powered bots over any dataset. If you want a javascript version, check out embedchain-js. Embedchain empowers you to create chatbot models similar to ChatGPT, using your own evolving dataset. Start building LLM powered bots under 30 seconds. -
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Local File Organizer
An AI-powered file management tool that ensures privacy
...The project focuses on privacy-first file organization by performing all processing locally rather than sending data to external cloud services. It uses language and vision models to understand the contents of documents, images, and other file types so that files can be grouped intelligently according to their meaning or context. The system scans directories, extracts relevant information from files, and restructures folder hierarchies to make content easier to locate and manage. Through AI-driven analysis, the software can detect themes, topics, and metadata in files, allowing it to organize information in ways that traditional rule-based file managers cannot achieve. ... -
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OpenPlanter
Language-model investigation agent with a terminal UI
...The system is structured to support experimentation and customization, making it suitable for both research and DIY agriculture projects. With its modular Python codebase, users can adapt the platform for different plant types, hardware setups, or automation strategies. Overall, OpenPlanter aims to simplify the creation of programmable, data-driven plant care systems. -
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Guardrails
Adding guardrails to large language models
...At the heart of Guardrails is the rail spec. rail is intended to be a language-agnostic, human-readable format for specifying structure and type information, validators and corrective actions over LLM outputs. We create a RAIL spec to describe the expected structure and types of the LLM output, the quality criteria for the output to be considered valid, and corrective actions to be taken if the output is invalid. -
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Anything to NotebookLM
Multi-source content processor for NotebookLM
Qiaomu Anything to NotebookLM is a Claude Code skill that turns many types of source material into structured NotebookLM-ready outputs. 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. ... -
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BrowserGym
A Gym environment for web task automation
...One of its main strengths is that it bundles several important benchmarks by default, including MiniWoB, WebArena, VisualWebArena, WorkArena, AssistantBench, WebLINX, and OpenApps. This gives researchers a unified way to compare agent behavior across diverse web environments and task types without stitching together separate evaluation stacks. BrowserGym is also designed to be extensible, and the repository notes that creating new benchmarks mainly involves inheriting its abstract task interface. -
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JSON_REPAIR
A python module to repair invalid JSON from LLMs
...Instead of failing when encountering errors such as missing quotes, trailing commas, or incomplete objects, the library analyzes the malformed data and reconstructs it into valid JSON. The repair process can also be combined with optional JSON Schema validation to enforce structural constraints and ensure the output conforms to expected data types and formats. Developers can integrate the library into applications as a drop-in replacement for standard JSON parsing functions, allowing systems to tolerate imperfect structured data without crashing. -
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AICGSecEval
A.S.E (AICGSecEval) is a repository-level AI-generated code security
AICGSecEval is an open-source benchmark framework designed to evaluate the security of code generated by artificial intelligence systems. The project was developed to address concerns that AI-assisted programming tools may produce insecure code containing vulnerabilities such as injection flaws or unsafe logic. The framework constructs evaluation tasks based on real-world software repositories and known vulnerability cases derived from CVE records. By simulating realistic development... -
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E2M
E2M converts various file types (doc, docx, epub, html, htm, url
E2M is a SourceForge mirror of the e2m open-source project, which focuses on providing tools or services designed to convert or process content between different formats or systems. Projects with similar naming conventions typically emphasize automation workflows where input data from one environment is transformed into another representation or output structure. The mirrored repository allows users to access the project’s codebase independently from its original hosting platform while... -
16
OmAgent
Build multimodal language agents for fast prototype and production
OmAgent is an open-source Python framework designed to simplify the development of multimodal language agents that can reason, plan, and interact with different types of data sources. The framework provides abstractions and infrastructure for building AI agents that operate on text, images, video, and audio while maintaining a relatively simple interface for developers. Instead of forcing developers to implement complex orchestration logic manually, the system manages task scheduling, worker coordination, and node optimization behind the scenes. ... -
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NExT-GPT
Code and models for ICML 2024 paper, NExT-GPT
...The system connects a large language model with multimodal encoders and diffusion-based decoders so it can interpret information from different sensory formats and generate responses in different media types. This architecture allows the model to convert between modalities, such as generating images from text descriptions or producing audio or video outputs based on textual prompts. The project also introduces instruction-tuning strategies that enable the model to perform complex multimodal reasoning and generation tasks with minimal additional parameters. -
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hCaptcha Challenger
Gracefully face hCaptcha challenge with multimodal llms
...Instead of relying on third-party captcha-solving services or browser scripts, the system operates independently by using pretrained neural networks that can classify images, detect objects, and interpret spatial relationships. The framework includes support for multiple types of captcha challenges such as object selection, drag-and-drop puzzles, and image labeling tasks. It implements an agent-style workflow where the system interprets the challenge prompt, selects the appropriate vision model, and generates the required interaction automatically. -
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Evals
Evals is a framework for evaluating LLMs and LLM systems
...The framework supports templated YAML eval definitions, solver-based evaluations, custom metrics, and composition of multi-step evaluations. It includes utilities and APIs to plug in completion functions, manage prompts, wrap retries or error handling, and register new evaluation types. It also maintains a growing registry of standard benchmarks or “evals” that users can reuse (for example, tasks measuring reasoning, factual accuracy, or chain-of-thought capabilities). The design is modular so you can extend or compose new evals, integrate with your own model APIs, and capture rich metadata about each run (prompt, responses, metrics). -
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Qwen-Audio
Chat & pretrained large audio language model proposed by Alibaba Cloud
Qwen-Audio is a large audio-language model developed by Alibaba Cloud, built to accept various types of audio input (speech, natural sounds, music, singing) along with text input, and output text. There is also an instruction-tuned version called Qwen-Audio-Chat which supports conversational interaction (multi-round), audio + text input, creative tasks and reasoning over audio. It uses multi-task training over many different audio tasks (30+), and achieves strong multi-benchmarks performance without task-specific fine‐tuning. ... -
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autollm
Ship RAG based LLM web apps in seconds
...AutoLLM supports a broad range of language models and vector databases, which makes it useful for teams that want flexibility without rewriting their application architecture every time they switch providers. The framework also includes built-in readers for multiple content sources such as PDFs, DOCX files, notebooks, websites, and other document types, which helps shorten the time between raw data and a working knowledge application. -
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Chameleon LLM
Codes for "Chameleon: Plug-and-Play Compositional Reasoning
Discover Chameleon, our cutting-edge compositional reasoning framework designed to enhance large language models (LLMs) and overcome their inherent limitations, such as outdated information and lack of precise reasoning. By integrating various tools such as vision models, web search engines, Python functions, and rule-based modules, Chameleon delivers more accurate, up-to-date, and precise responses, making it a game-changer in the natural language processing landscape. With GPT-4 at its...
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