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Showing 18 open source projects for "issues"
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Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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LLaMA Models
Utilities intended for use with Llama models
...It ties together other stack components (like safety tooling and developer SDKs) and provides canonical references for model variants and their intended usage. The project’s issues and releases reflect an actively used coordination point for the ecosystem, where guidance, utilities, and compatibility notes are published. It complements separate repos that carry code and demos (for example inference kernels or cookbook content) by keeping authoritative metadata and specs here. Model lineages and size variants are documented externally (e.g., Llama 3.x and beyond), with this repo providing the “single source of truth” links and utilities. ... -
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Opik
Debug, evaluate, and monitor your LLMapps, RAG systems, and agentic AI
...Run experiments with different prompts and evaluate against a test set. Choose and run pre-configured evaluation metrics or define your own with our convenient SDK library. Consult built-in LLM judges for complex issues like hallucination detection, factuality, and moderation. -
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Langfuse
Open source LLM engineering platform: LLM Observability, metrics, etc.
Langfuse is a logging and analytics tool for large language model (LLM) applications, providing insights into usage, performance, and troubleshooting. -
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LangWatch
The platform for LLM evaluations and AI agent testing
LangWatch is an open-source observability and monitoring platform designed to help developers evaluate and improve applications built with large language models. The platform provides tools for tracking model interactions, analyzing prompt behavior, and identifying issues such as hallucinations, latency problems, or unexpected responses. By collecting telemetry data from AI applications, LangWatch allows developers to understand how their systems perform in real-world usage scenarios. The platform includes dashboards that visualize model behavior, enabling teams to monitor trends in response quality and reliability over time. ... -
Compliant and Reliable File Transfers Backed by Top Security CertificationsStop relying on non-certified, legacy file transfer tools that creak under the weight of modern security demands. Get full audit trails, advanced access controls and more supported by an award-winning team of experts. Start your free 25-day trial today.
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Code Review GPT
Your personal code reviewer powered by LLMs
Code Review GPT uses Large Language Models to review code in your CI/CD pipeline. It helps streamline the code review process by providing feedback on code that may have issues or areas for improvement. Code Review GPT is in alpha and should be used for fun only. It may provide useful feedback but please check any suggestions thoroughly. -
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Strix
Open-source AI hackers to find and fix your app’s vulnerabilities
Strix is an open source agent-driven security platform that uses autonomous AI agents to identify, investigate, and validate vulnerabilities in software applications. The system is designed to mimic the behavior of real attackers by executing dynamic testing and verifying findings through proof-of-concept exploitation. Unlike traditional vulnerability scanners that rely heavily on static analysis, Strix agents actively run code, probe systems, and attempt exploitation to confirm whether... -
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RWKV Runner
A RWKV management and startup tool, full automation, only 8MB
...Moreover it's 100% attention-free. Default configs has enabled custom CUDA kernel acceleration, which is much faster and consumes much less VRAM. If you encounter possible compatibility issues, go to the Configs page and turn off Use Custom CUDA kernel to Accelerate. -
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Scikit-LLM
Seamlessly integrate LLMs into scikit-learn
Seamlessly integrate powerful language models like ChatGPT into sci-kit-learn for enhanced text analysis tasks. At the moment the majority of the Scikit-LLM estimators are only compatible with some of the OpenAI models. Hence, a user-provided OpenAI API key is required. Additionally, Scikit-LLM will ensure that the obtained response contains a valid label. If this is not the case, a label will be selected randomly (label probabilities are proportional to label occurrences in the training... -
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Pezzo
Open-source, developer-first LLMOps platform
...Packed with powerful features to streamline your workflow, so you can focus on what matters. Pezzo is a fully cloud-native and open-source LLMOps platform. Seamlessly observe and monitor your AI operations, troubleshoot issues, save up to 90% on costs and latency, collaborate and manage your prompts in one place, and instantly deliver AI changes. -
Build Securely on AWS with Proven FrameworksMoving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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pgvecto.rs
Vector database plugin for Postgres, written in Rust
pgvecto.rs is a Postgres extension that provides vector similarity search functions. It is written in Rust and based on pgrx. It is currently under heavy development, please take care when using it in production. pgvecto.rs is a Postgres extension, which means that you can use it directly within your existing database. This makes it easy to integrate into your existing workflows and applications. pgvecto.rs supports filtering. You can set conditions when searching or retrieving points. This... -
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vLLM Semantic Router
System Level Intelligent Router for Mixture-of-Models at Cloud
...The router operates as an intelligent layer between users and model infrastructure, capturing signals from prompts, responses, and contextual data to improve decision-making. It can also integrate safety and monitoring mechanisms that detect issues such as jailbreak attempts, hallucinations, or sensitive information exposure. -
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ROSA
I Agent designed to interact with ROS1- and ROS2-based robotics system
...Built on top of frameworks such as LangChain and modern large language models, ROSA translates user instructions into actions that can be executed within ROS1 or ROS2 environments. This capability enables users to inspect system status, diagnose issues, and control robot behavior without manually navigating complex command-line tools or configuration files. The system integrates with robotics software stacks and exposes operational tools that allow AI agents to analyze system logs, inspect sensors, or trigger robot tasks. -
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PeterCat
A conversational Q&A agent configuration system
PeterCat is an open-source conversational agent framework designed to create automated question-and-answer assistants for GitHub repositories and technical projects. The system allows developers to build AI-powered bots that understand project documentation, GitHub issues, and other repository content in order to answer questions from users or contributors. By simply providing the repository name or URL, the platform can automatically collect relevant project information and construct a knowledge base that the agent uses to respond to inquiries. The framework also provides a configuration system that allows developers to customize how the conversational agent behaves and how it integrates with external services. ... -
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Agentless
An agentless approach to automatically solve software development
Agentless is an open-source framework that applies large language models to automatically resolve software development issues without relying on complex autonomous agent systems. The project proposes an alternative approach to AI-driven code repair that avoids the overhead of multi-agent orchestration by using a structured pipeline for identifying and fixing bugs. When solving a problem, the system first performs localization to determine which files, functions, or code segments are most likely responsible for the issue. ... -
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Granite 3.0 Language Models
New set of lightweight state-of-the-art, open foundation models
...Documentation highlights the capability mix (reasoning, tool use, code) and points to model artifacts and guidance for evaluation. Activity on the project shows an evolving codebase with open pull requests and standard GitHub project structure for issues and security visibility. In practice, this is a hub for acquiring Granite 3.0 variants and understanding how to integrate them into applications. -
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AI-Codereview-Gitlab
GitLab automatic code review tool based on large models
AI-Codereview-Gitlab is an open-source automation tool that integrates large language models into the GitLab development workflow to perform automated code reviews. The system monitors GitLab repositories and analyzes commits or merge requests using AI models to identify potential issues, coding mistakes, and quality improvements before the code is merged. By leveraging multiple large language model providers—including OpenAI, DeepSeek, ZhipuAI, or local models through Ollama—the platform allows teams to choose the AI engine that best fits their infrastructure and privacy requirements. When code changes occur, the system can automatically generate review comments and feedback that are posted directly into GitLab merge requests, allowing developers to see suggestions alongside human reviewer comments. ... -
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Qwen2.5-Coder
Qwen2.5-Coder is the code version of Qwen2.5, the large language model
Qwen2.5-Coder, developed by QwenLM, is an advanced open-source code generation model designed for developers seeking powerful and diverse coding capabilities. It includes multiple model sizes—ranging from 0.5B to 32B parameters—providing solutions for a wide array of coding needs. The model supports over 92 programming languages and offers exceptional performance in generating code, debugging, and mathematical problem-solving. Qwen2.5-Coder, with its long context length of 128K tokens, is... -
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Grade School Math
8.5K high quality grade school math problems
...The repository maintains strict formatting (e.g. JSONL) for problem + answer pairs, and is used broadly in research to benchmark model performance under “word problem” settings. Issues are tracked (people report incorrect problems, ambiguous statements), and contributions are possible for cleaning or expanding the set.
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