Search Results for "php support system"
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Showing 8 open source projects for "php support system"
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$300 in Free Credit Towards Top Cloud ServicesStart your project in minutes. After credits run out, 20+ products include free monthly usage. Only pay when you're ready to scale.
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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DocsGPT
Private AI platform for agents, enterprise search and RAG pipelines
DocsGPT is an open-source AI platform for deploying private RAG pipelines, AI agents, and enterprise search on your own infrastructure. Connect any data source (PDFs, DOCX, CSV, Excel, HTML, audio, GitHub, databases, URLs) and get accurate, hallucination-free answers with source citations. Choose your LLM: OpenAI, Anthropic, Google Gemini, or local models. Works with Qdrant, MongoDB, and Elasticsearch and more. Deploy via Docker or Kubernetes with full data sovereignty. Build... -
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ProjectLibre - Project Management
#1 alternative to Microsoft Project : Project Management & Gantt Chart
...Cloud supports multi-project management w/ role-based access, central resource pool, Dashboard, Portfolio View 💡 The AI Cloud version can generate full project plans (tasks, durations, dependencies) from a natural language prompt — in any language. 🌐 Try the Cloud: http://www.projectlibre.com/register/trial 💻 Mac tip: If blocked, go to System Preferences → Security → Allow install 🏆 InfoWorld “Best of Open Source” • Used at 1,700+ universities • 250K+ community 🙏 Support us: http://www.gofundme.com/f/projectlibre-free-open-source-development -
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KoboldCpp
Run GGUF models easily with a UI or API. One File. Zero Install.
KoboldCpp is an easy-to-use AI text-generation software for GGML and GGUF models, inspired by the original KoboldAI. It's a single self-contained distributable that builds off llama.cpp and adds many additional powerful features. -
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ChatAnyLLM
Unified interface for local model, cloud provider, and custom agent.
ChatAnyLLM is a desktop GUI application for local inference engines (Ollama, LM Studio, OpenClaw) and cloud providers like OpenRouter. Users may manually configure any OpenAI-compatible API endpoint, connecting third-party providers such as Groq or Cerebras. The application stores conversation history locally and saves api keys with system-level encryption. It supports reasoning models, multimodal inputs, and formatting for LaTeX and code. -
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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ChatGPT Desktop Application
🔮 ChatGPT Desktop Application (Mac, Windows and Linux)
ChatGPT Desktop Application (Mac, Windows and Linux) -
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Node ChatGPT API
A client implementation for ChatGPT and Bing AI
...You can still set userLabel, chatGptLabel and promptPrefix (system instructions) as usual. Support for the official ChatGPT underlying model, gpt-3.5-turbo, via OpenAI's API. Replicates chat threads from the official ChatGPT website (with conversation IDs and message IDs), with persistent conversations using Keyv. Conversations are stored in memory by default, but you can optionally install a storage adapter to persist conversations to a database. -
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Accelerated Text
Accelerated Text is a no-code natural language generation platform
...It will help you construct document plans which define how your data is converted to textual descriptions. With Accelerated Text you can use such data to generate text for your business reports, your e-commerce platform or your customer support system. Data descriptions require precision. Accelerated Text follows the principle of this strict adherence to data-bound text generation. Via its user interface, it provides instruments to define how the data should be translated into a descriptive text. -
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CRSLab
CRSLab is an open-source toolkit
CRSLab is an open-source toolkit for building Conversational Recommender System (CRS). It is developed based on Python and PyTorch. CRSLab has the following highlights. Comprehensive benchmark models and datasets: We have integrated commonly-used 6 datasets and 18 models, including graph neural network and pre-training models such as R-GCN, BERT and GPT-2. We have preprocessed these datasets to support these models, and release for downloading.
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