Projects sharing features with FinGPT

Fairseq is a PyTorch toolkit for sequence-to-sequence modeling, specializing in neural machine translation, automatic speech recognition, and large-scale language model training. It provides a framework for processing and aligning diverse data sources, including text, audio, and video, to support tasks such as speech-to-text conversion and multimodal sequence learning. The project is distinguished by its distributed training capabilities, which utilize parameter sharding, mixed-precision training, and CPU offloading to handle models that exceed single-device memory. It also includes specializ

llm-universe is a structured learning resource and technical guide focused on the development of large language model applications. It serves as a curriculum for mastering model orchestration, the creation of autonomous conversational agents, and the implementation of retrieval-augmented generation systems. The project provides detailed instructions on connecting model APIs with memory and tools to create execution chains. It specifically covers the construction of retrieval pipelines, including the process of cleaning raw documents, generating embeddings, and integrating vector databases to

This project is a collection of generative AI implementations focused on the development of AI agents, retrieval-augmented generation pipelines, and vector search integration. It provides a framework for connecting managed cloud databases to language models to create context-aware applications. The project covers the orchestration of autonomous agents that use multi-step reasoning and external tools to complete tasks. It includes implementations for semantic retrieval using high-dimensional embeddings and the use of model-agnostic prompting to ensure consistent outputs across different large

This project serves as a comprehensive educational resource and technical handbook for engineers building applications powered by large language models. It provides a structured framework for mastering the principles of artificial intelligence engineering, covering the full lifecycle of model development from initial design to production deployment. The repository distinguishes itself by offering a deep dive into the practical implementation of advanced design patterns, including retrieval-augmented generation, agentic tool orchestration, and parameter-efficient model adaptation. It emphasize

LARK is a development toolkit for training, fine-tuning, and deploying large language models and multimodal models based on PaddlePaddle. It functions as a comprehensive framework that includes an LLM training orchestrator, an inference server, and a multimodal model framework for processing text, image, and video inputs. The project features a retrieval-augmented generation system for building conversational applications that integrate web search and private knowledge bases. It provides specific capabilities for multimodal reasoning and complex logic, enabling the extraction of structured da

This project is a collection of educational resources and technical guides focused on the development and implementation of large language models. It provides a comprehensive curriculum covering transformer architectures, training methods, and deployment strategies. The materials provide detailed instructions for building autonomous agents using reasoning loops and tool integration, as well as guides for fine-tuning models through supervised learning and preference optimization. It also includes tutorials for constructing retrieval augmented generation pipelines and implementing transformer m

VoxCPM is a multilingual speech synthesis system and text-to-speech inference server. It functions as an AI voice cloning tool and a synthetic voice designer, capable of generating natural speech across global languages and regional dialects using a GPU-accelerated audio generator. The project features a speech model fine-tuning framework that supports both full parameter updates and low-rank adaptation for customizing voice characteristics. It enables high-fidelity voice cloning from reference audio, including cross-lingual voice transfer and acoustic environment mimicry, as well as the crea

This repository provides a collection of reference implementations and code examples for training and deploying machine learning models using the MLX framework. It serves as a practical guide for executing distributed training, fine-tuning large language models, converting model weights, and implementing multimodal generative workflows. The project distinguishes itself through specialized examples for local hardware execution, featuring weight quantization to reduce memory usage and low-rank adaptation for parameter-efficient fine-tuning. It also includes scripts for transforming external mod

This project is a financial market data API and quantitative analysis tool designed to aggregate metrics, scrape web data, and monitor market sentiment. It functions as a financial indicator aggregator and stock market web scraper that provides a programmatic interface for retrieving stock prices, indices, and ETF metadata from multiple data providers. The system differentiates itself through a dedicated market sentiment monitor and investment risk assessment capabilities. It tracks investor behavior via northbound capital flows, dragon-tiger lists, popularity rankings, and security margin ba

This repository serves as a comprehensive library of architectural blueprints and code examples for integrating large language models into software applications. It functions as a developer learning resource, providing structured tutorials and implementation patterns that demonstrate how to build intelligent features using advanced prompting and data processing techniques. The collection distinguishes itself by focusing on complex reasoning and data-grounding workflows. It provides practical guidance on implementing retrieval-augmented generation pipelines, which connect language models to pr

quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering, and algorithmic trading. It serves as a centralized library of documentation covering mathematical models, financial instruments, and systematic trading strategies. The project integrates AI-driven capabilities through a modular retrieval-augmented generation framework that extracts structured data from research papers and news. It features a multi-agent workflow engine designed to discover and validate predictive alpha factors, alongside tools for local large language model

PocketFlow is a graph-based framework for designing and executing large language model operations and reasoning patterns. It serves as an orchestrator for building goal-oriented autonomous agents, multi-agent systems, and retrieval-augmented generation pipelines. The system is distinguished by its ability to coordinate autonomous AI agents that use shared memory and tools to solve complex goals, supported by a structured output engine that enforces schema-consistent responses. It utilizes graph-based workflow orchestration to manage sequences of model operations and supports supervisor-based

This project is a structured educational resource and technical guide for designing and implementing autonomous systems using large language models. It provides a comprehensive curriculum and code samples focused on agentic design patterns, autonomous development, and the creation of systems capable of planning and executing multi-step tasks. The resource details the implementation of agentic retrieval-augmented generation, where models autonomously plan and refine data searches. It covers a wide array of orchestrators and design patterns, including metacognitive reflection for self-correctin

Embedchain is an LLM memory management framework and RAG orchestration engine designed to provide AI agents with a persistent storage layer. It functions as a long-term memory pipeline that extracts facts from unstructured interactions and stores them as permanent knowledge base entries to retain user preferences and interaction history across sessions. The system employs a hybrid vector database interface that combines semantic embeddings with traditional keyword search. It utilizes an entity-linking knowledge graph to connect related information points and applies temporal ranking to distin

This project is a comprehensive market data toolkit and financial analysis system specifically designed for China A-shares. It serves as a data pipeline for retrieving real-time quotes, aggregating corporate financial statements, and automating equity research. The system distinguishes itself through specialized monitors for institutional capital movements, including Northbound fund flows, margin trading balances, and large block transactions. It also features a dedicated options Greeks calculator for ETF derivatives and tools to gauge market sentiment via retail popularity rankings and trend

This project is a comprehensive collection of practical code examples and implementation libraries for machine learning. It provides a wide array of reference materials for building supervised, unsupervised, and reinforcement learning algorithms. The repository serves as a multi-domain resource, featuring specific implementation suites for financial AI, Bayesian statistical modeling, and deep learning architectures. It includes a framework for training intelligent agents using policy gradients and actor-critic models, as well as practical guides for fine-tuning transformers and utilizing larg

This project serves as a comprehensive, curated directory of resources, tools, and platforms dedicated to the generative artificial intelligence ecosystem. It functions as a central hub for developers and researchers to discover the frameworks, models, and services necessary for building, deploying, and managing intelligent software applications. The directory distinguishes itself by providing a structured index of specialized tooling across several technical domains. It covers the full lifecycle of generative AI, including the development of autonomous agent systems, the implementation of re

This project is a comprehensive technical reference and educational resource focused on the lifecycle of large language models. It provides structured learning materials that cover the foundational mechanics of transformer architectures, the mathematical principles of attention mechanisms, and the engineering practices required for modern generative artificial intelligence. The repository serves as a guide for both technical skill development and professional preparation, offering a curriculum that spans from model training and inference optimization to advanced alignment techniques. It detai

This project is a comprehensive framework and toolkit for developing, optimizing, and deploying transformer-based models across multimodal, document intelligence, and natural language processing tasks. It provides a unified neural architecture that processes text, vision, audio, and document layout data through a shared set of weights, enabling researchers and developers to build foundational models that align cross-modal representations. The platform distinguishes itself through advanced training and inference strategies designed for large-scale deep learning. It incorporates specialized mec

GraphRAG is a data processing pipeline and retrieval engine designed to transform unstructured text into interconnected knowledge graphs. By utilizing language models to extract entities and relationships, it builds structured representations of information that enable context-aware retrieval for downstream applications. The system distinguishes itself through hierarchical graph clustering and large-scale data synthesis, which organize massive document corpora into multi-level structures. This approach allows for both vector-based semantic searches and graph-based traversals, providing a comp

InternVL is a vision-language model framework that fuses a visual encoder with a large language model to translate image features into textual tokens for reasoning. It provides a system for multimodal inference and dialogue, enabling the processing of images and text to answer questions or generate descriptions. The project is distinguished by its high-resolution image processing, which uses dynamic tiling to maintain detail for images up to 4K resolution, and its chain-of-thought visual reasoning for solving complex mathematical and spatial problems. It also supports temporal frame sampling

This project is a quantitative trading platform and algorithmic trading bot designed for market data aggregation, strategy backtesting, and trade execution. It functions as a comprehensive system for collecting financial data via APIs and web sources, simulating investment strategies against historical records, and programmatically managing investment positions through brokerage interfaces. The platform distinguishes itself through institutional sentiment analysis and market intelligence tools. It monitors institutional fund activity, tracks corporate actions like equity pledges, and crawls f

Quiver is a framework for integrating retrieval augmented generation into applications. It provides a generative AI integration layer that connects large language models with vector stores to produce context-aware responses based on custom data. The project features a knowledge base pipeline that parses diverse file types into searchable embeddings and a vector database orchestrator to manage data across different storage implementations. It utilizes a provider-agnostic model interface, allowing users to switch between various external AI providers or local models through a single unified sys

53AIHub is a centralized orchestration platform for deploying and managing AI agents and prompts across multiple large language model providers. It functions as a multi-model AI gateway and an operation portal for AI services, providing a unified interface to coordinate agents and prompts from various external platforms. The project distinguishes itself as a white-label AI portal designed for self-hosted infrastructure, allowing for full control over operational data on private servers or containers. It includes a comprehensive AI SaaS administration layer with a multi-tenant subscription eng

Quivr is a framework for building retrieval-augmented generation pipelines that connect large language models to custom knowledge bases. It serves as a generative AI integration layer that abstracts the process of transforming diverse document sources into searchable context for AI responses. The project orchestrates the end-to-end flow between document ingestion, vector storage management, and model provider interfaces. It features a vector-store-agnostic retrieval system and a modular API layer that allows for flexible switching between different generative model providers. The system cove

CS-Base is a comprehensive educational platform and technical repository designed to support software engineers in mastering backend architecture, artificial intelligence engineering, and career development. It functions as a centralized knowledge hub that combines illustrated theoretical tutorials with practical, project-based learning to bridge the gap between foundational computer science concepts and professional industry requirements. The project distinguishes itself by integrating a robust career mentorship framework with advanced AI engineering resources. It provides users with tools f