Search Results for "text analysis linguistic" - Page 2
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Showing 145 open source projects for "text analysis linguistic"
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RAG Anything
RAG-Anything: All-in-One RAG Framework
...The system uses a multi-stage pipeline (e.g., document parsing, content analysis, knowledge graph construction, intelligent retrieval) so queries can navigate across modalities with deeper understanding and relevance. -
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NetworkX
Network analysis in Python
NetworkX is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Data structures for graphs, digraphs, and multigraphs. Many standard graph algorithms. Network structure and analysis measures. Generators for classic graphs, random graphs, and synthetic networks. Nodes can be "anything" (e.g., text, images, XML records). Edges can hold arbitrary data (e.g., weights, time-series). Open source 3-clause BSD license. Well tested with over 90% code coverage. Additional benefits from Python include fast prototyping, easy to teach, and multi-platform. ... -
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DeepAnalyze
Autonomous LLM agent for end-to-end data science workflows
DeepAnalyze is an open source project that introduces an agentic large language model designed to perform autonomous data science tasks from start to finish. It is built to handle the entire data science pipeline, including data preparation, analysis, modeling, visualization, and report generation without requiring continuous human guidance. DeepAnalyze is capable of conducting open-ended data research across multiple data formats such as structured tables, semi-structured files, and unstructured text, enabling flexible and comprehensive analysis workflows. It integrates execution-based reasoning by generating and running code as part of its analysis process, allowing it to iteratively refine results and produce more accurate outputs. ... -
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PaddleSpeech
Easy-to-use Speech Toolkit including Self-Supervised Learning model
...We provide high-speed and ultra-lightweight models, and also cutting-edge technology. We provide production ready streaming asr and streaming tts system. Our frontend contains Text Normalization and Grapheme-to-Phoneme (G2P, including Polyphone and Tone Sandhi). Moreover, we use self-defined linguistic rules to adapt Chinese context. -
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DataProfiler
Extract schema, statistics and entities from datasets
DataProfiler is an AI-powered tool for automatic data analysis and profiling, designed to detect patterns, anomalies, and schema inconsistencies in structured and unstructured datasets. The DataProfiler is a Python library designed to make data analysis, monitoring, and sensitive data detection easy. Loading Data with a single command, the library automatically formats & loads files into a DataFrame. Profiling the Data, the library identifies the schema, statistics, entities (PII / NPI), and... -
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Underthesea
Underthesea - Vietnamese NLP Toolkit
Underthesea is a Vietnamese NLP toolkit providing various text processing capabilities, including word segmentation, part-of-speech tagging, and named entity recognition. -
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Ultravox
Fast multimodal LLM for real-time voice interaction and AI apps
Ultravox is an open source multimodal large language model designed specifically for real-time voice-based interactions. It is built to process both text and spoken audio directly, eliminating the need for a separate speech recognition stage and enabling more seamless conversational experiences. Ultravox works by combining text prompts with encoded audio inputs, allowing it to understand spoken language alongside written instructions in a unified pipeline. Internally, it leverages pretrained language models and speech encoders, with a multimodal adapter that integrates both modalities for inference and training. ... -
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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”)... -
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Databend
Cloud-native open source data warehouse for analytics and AI queries
...This architecture enables cost-efficient storage and elastic scaling for workloads that involve large datasets and complex queries. Databend provides a unified engine capable of handling analytics, vector search, and full-text search within a single platform. Databend supports SQL-based workflows and enables real-time data ingestion, transformation, and analysis through streaming and task orchestration features. With its cloud-native design and distributed architecture, Databend can run both as a self-hosted system or within managed environments to power data analytics, AI workloads, and large-scale data. -
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TAME LLM
Traditional Mandarin LLMs for Taiwan
TAME LLM is an open-source initiative focused on building and releasing large language models optimized for Traditional Mandarin and the linguistic context of Taiwan. The project includes models such as Llama-3-Taiwan-70B, which are fine-tuned versions of large transformer architectures trained on extensive corpora containing both Traditional Mandarin and English text. These models are designed to support applications such as conversational AI, knowledge retrieval, and domain-specific reasoning in fields like manufacturing, law, healthcare, and electronics. ... -
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ML Ferret
Refer and Ground Anything Anywhere at Any Granularity
...The repo presents the vision-language pipeline, model assets, and paper resources that show how Ferret answers questions, follows instructions, and returns grounded outputs rather than just text. In practice, this enables tasks like “find that small red icon next to the chart and describe it” where both the linguistic reference and the visual region are ambiguous without fine spatial reasoning. -
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Qwen2-Audio
Repo of Qwen2-Audio chat & pretrained large audio language model
Qwen2-Audio is a large audio-language model by Alibaba Cloud, part of the Qwen series. It is trained to accept various audio signal inputs (including speech, sounds, etc.) and perform both voice chat and audio analysis, producing textual responses. It supports two major modes: Voice Chat (interactive voice only input) and Audio Analysis (audio + text instructions), with both base and instruction-tuned models. It is evaluated on many benchmarks (speech recognition, translation, sound classification, emotion, etc.), and offers pretrained models (e.g. 7B) released via ModelScope and Hugging Face. ... -
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LangExtract
A Python library for extracting structured information
LangExtract is a Python library developed by Google that leverages large language models (LLMs) to extract structured information from unstructured text—such as clinical notes, research papers, or literary works—based on user-defined instructions. It is designed to transform free-form text into reliable, schema-constrained data while maintaining traceability back to the source material. Each extracted entity is precisely grounded in its original context, allowing visual inspection and... -
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DocETL
A system for agentic LLM-powered data processing and ETL
...The platform allows developers and researchers to construct structured workflows that extract, transform, and organize information from sources such as reports, transcripts, legal documents, and other text-heavy data. Instead of relying on single prompts or ad-hoc scripts, DocETL provides a declarative pipeline framework that breaks complex document analysis tasks into manageable operations that can be optimized and orchestrated automatically. Pipelines are typically defined using a low-code YAML interface, giving users full control over prompts and processing steps while still simplifying workflow creation. -
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Gitingest
Create prompt-friendly codebase digests from any Git repository URL
Gitingest is a developer utility that converts an entire Git repository into a structured, prompt-friendly text digest suitable for use with large language models. It analyzes a repository and produces a consolidated textual representation that includes the file structure and code content in an organized format. This makes it easier to provide meaningful code context when working with AI systems that require compact, readable inputs. Developers can generate these digests from either a local... -
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Tokenized Text Aligner
Aligns tokens in two versions of a text with differing tokenization.
This tool performs token-by-token alignment of two versions of a text with differing tokenization by interpreting the results of a file diff (https://docs.python.org/3/library/difflib.html). It is intended for use in the preparation of annotated linguistic corpora, where differences in tokenization may arise (i) following corrections or modifications to the source text or (ii) through the creation of different layers of annotation (part-of-speech, treebank) requiring different tokenization. ... -
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flair
A very simple framework for state-of-the-art NLP
...Developed by Humboldt University of Berlin and friends. A powerful NLP library. Flair allows you to apply our state-of-the-art natural language processing (NLP) models to your text, such as named entity recognition (NER), sentiment analysis, part-of-speech tagging (PoS), special support for biomedical texts, sense disambiguation and classification, with support for a rapidly growing number of languages. A text embedding library. Flair has simple interfaces that allow you to use and combine different word and document embeddings, including our proposed Flair embeddings and various transformers. ... -
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StyleTTS 2
Towards Human-Level Text-to-Speech through Style Diffusion
...StyleTTS2 supports both single-speaker and multi-speaker configurations, with the ability to sample or transfer styles from reference audio, making it powerful for expressive TTS and character voices. The repository includes training scripts, configuration files, and pre-trained auxiliary modules such as a text aligner, pitch extractor, and PL-BERT-based linguistic encoder. -
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. Shows how a target value (e.g. "Survived" in the Titanic dataset) relates to other features. ... -
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NeMo Retriever Library
Document content and metadata extraction microservice
NeMo Retriever Library is a scalable microservice framework designed for extracting, structuring, and enriching content from documents to support downstream generative AI applications. It processes various document types by splitting them into components such as text, tables, charts, and images, and then applies OCR and contextual analysis to convert them into structured data formats. The system is built on NVIDIA NIM microservices, enabling high-performance parallel processing and efficient handling of large datasets. It supports multiple extraction strategies for different document formats, balancing accuracy and throughput depending on the use case. ... -
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Biomni
Biomni: a general-purpose biomedical AI agent
...It integrates retrieval-augmented generation with code-based execution, allowing it to access external knowledge, process data, and generate testable hypotheses in scientific workflows. The system is built to support researchers by automating repetitive and time-consuming tasks such as literature review, data analysis, and experimental design. Biomni operates within a comprehensive environment that includes tools, APIs, and datasets, enabling it to execute multi-step research processes rather than just generating text responses. It supports integration with multiple AI models, allowing flexibility in selecting the most appropriate model for specific tasks. -
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FlexLLMGen
Running large language models on a single GPU
FlexLLMGen is an open-source inference engine designed to run large language models efficiently on limited hardware resources such as a single GPU. The system focuses on high-throughput generation workloads where large batches of text must be processed quickly, such as large-scale data extraction or document analysis tasks. Instead of requiring expensive multi-GPU systems, the framework uses techniques such as memory offloading, compression, and optimized batching to run large models on commodity hardware. The architecture distributes computation and memory usage across the GPU, CPU, and disk in order to maximize the number of tokens processed during inference. ... -
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Luna AI
Virtual AI anchor that combines state-of-the-art technology
Luna AI is a virtual AI streamer framework designed to power an interactive VTuber that can go live on major platforms and chat with viewers in real time. It is built around a core assistant persona called “Luna AI,” which can be driven by a wide range of large language models and platforms, including GPT-style APIs, Claude, LangChain-based backends, ChatGLM, Kimi, Ollama, and many others. The project supports multiple rendering backends for the avatar, such as Live2D, Unreal Engine (UE),... -
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Instagram OSINT Tool
Instagram OSINT tool for gathering profile data and public posts
InstagramOSINT is an open source intelligence (OSINT) tool designed to collect publicly accessible information from Instagram profiles. It retrieves details that are not always easily visible when browsing an Instagram account normally, allowing investigators, researchers, and developers to gather structured data about a target profile. It works by scraping publicly available profile information and extracting metadata from Instagram pages using Python. It collects various attributes such as... -
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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.
