Latest revision as of 00:05, 11 September 2026

Discover cloud and AI on infocepo.com

infocepo.com – Cloud, AI & Labs

Bienvenue sur le portail infocepo.com.

Ce wiki documente l’écosystème Cloud, IA, automatisation et lab d’Infocepo. Il s’adresse aux :

administrateurs systèmes,
ingénieurs cloud,
développeurs,
étudiants,
curieux qui veulent apprendre en pratiquant.

L’objectif est simple : transformer la théorie en scripts réutilisables, schémas, architectures, APIs et laboratoires concrets.

Accès rapide

Portail principal

infocepo.com

Assistant IA

Chat assistant

Liste des pages du wiki

Toutes les pages

Vue d’ensemble

Infra architecture overview

Démarrer rapidement

Parcours recommandés

1. Construire un assistant IA privé

Déployer une stack type Hermes WebUI + Ollama + GPU
Ajouter un modèle de chat et un modèle de résumé
Brancher des données internes via RAG + embeddings

2. Lancer un lab cloud

Créer un petit cluster Kubernetes, OpenStack ou bare-metal
Mettre en place un pipeline de déploiement (Helm, Ansible, Terraform…)
Ajouter un service IA : transcription, résumé, chatbot, OCR…

3. Préparer un audit ou une migration

Inventorier les serveurs avec ServerDiff.sh
Concevoir l’architecture cible
Automatiser la migration avec des scripts reproductibles

Vue d’ensemble du contenu

Guides IA & outils : assistants, modèles, évaluation, GPU, RAG
Cloud & infrastructure : Kubernetes, OpenStack, HA, HPC, DevSecOps
Labs & scripts : audit, migration, automatisation
Comparatifs : Kubernetes vs OpenStack vs AWS vs bare-metal, etc.

Vision

The world after automation

Le but à long terme est de construire un environnement où :

les assistants IA privés accélèrent la production,
les tâches répétitives sont automatisées,
les déploiements sont industrialisés,
l’infrastructure reste compréhensible, portable et réutilisable.

Chaque sortie IA est mesurée en temps réel, les modèles faibles sont remplacés automatiquement, et les tâches sans valeur sont coupées. L'autonomie vient de mécanismes techniques qui fonctionnent quand personne ne regarde — pas de règles écrites dans un doc.

Main page summary

Catalogue rapide des services

Services principaux
Catégorie	Service	Rôle
API	LLM	Modèles de chat, code, RAG, OCR
API	STT	Transcription audio
API	TTS	Synthèse vocale
API	realtime-ai	Temps réel WebSocket / WebRTC
API	IMAGE2TXT	OCR / VLM via endpoint dédié
API	summary	Résumé de textes longs
API	EMBEDDINGS	Embeddings pour RAG
API	ChromaDB	Base vecteur
API	TXT2IMAGE	Génération d’images
API	diarization	Segmentation locuteurs
Observabilité	monitoring	Dashboards techniques
Observabilité	status	Disponibilité des services
Observabilité	web-stat	Statistiques web
Observabilité	LLM-stat	Vue API / usage
Outils	dataLab	Environnement de travail hors-production
Outils	realtime translation	Traduction
Outils	Demos	Démonstrateurs

Sélection AI & architecture par couche

Le tableau de bord Sélection AI présente l'architecture par couche des modèles IA déployés :

Couche	Modèle	Alias(s)	Taille
HYBRID-CLOUD	Qwen3.6-35B	flash, default, thinking, vision	Option 135B MoE / 3B actif
	Qwen3.8-Flash-Next	flash, default, thinking, vision, max	Option 2125B MoE, 51B n-grames internes, 6B actif, 1M contexte
	MiniMax-H3	video	33B dense
	BGE-M3	embedding	568M
	BGE-reranker-v2-m3	reranker	568M
	FLUX.2-klein-4B	image	4B
	GLiNER2.5-Multi-V1	privacy	287M, mDeBERTa-v3-base — privacy filter: api-llm-privacy-proxy-gliner2
Public-Cloud	GLM-5.3-Flash	max	320B MoE / 18B actif — 1M contexte, multimodal
LOCAL	Qwen3.5-9B	flash, default, thinking, vision	Option 1 9B dense
LOCAL	Qwen3.8-27B	flash, default, thinking, vision, max	Option 2 27B dense

Frameworks

Outil	Usage
Hermes	Usage général, raisonnement
OpenCode	DevSecOps
Kilo Code	Développement pur

Mémoire

Pour la couche d'embedding vectoriel (RAG, mémoire sémantique) :

BGE-M3 — 568M paramètres, architecture XLM-RoBERTa. Multi-fonction (dense + sparse + multi-vector), 100+ langues, licence MIT. Idéal comme moteur de mémoire à échelle.

Nouveautés

Nouveautés implémentés

tricoteuses-k8s (2026-09-08) : Kubernetes deployment for tricoteuses-juridique
dashboard-superset-mcp (2026-09-07) : Automate Apache Superset dashboard creation via MCP server 6.1.0+
api-txt2image (2026-09-02) : Text-to-image generation API for AI-powered image creation
omnivoice-tts (2026-09-01) : omnivoice-tts
superset-k8s (2026-09-01) : superset-k8s
dind-build (2026-08-31) : Docker-in-Docker build factory on Kubernetes — build, push, pull via K8s DinD pod
quality-gate (2026-08-28) : quality-gate
agent-saas (2026-08-27) : SaaS AI agent platform — deploy autonomous AI agents as a service
api-convert2md (2026-08-26) : Document-to-Markdown conversion API — clean markdown from various formats
qwen36-sglang (2026-08-24) : Qwen 3.6 deployment with SGLang for high-performance inference
trafilatura-local (2026-08-23) : trafilatura-local
api-rag (2026-08-19) : RAG API — semantic search over knowledge bases with retrieval-augmented generation
models-todo (2026-08-19) : models-todo
minimax-music3 (2026-08-18) : minimax-music3
hermes-img-gen-infocepo (2026-08-15) : hermes-img-gen-infocepo
ask-multiple-pdfs (2026-08-14) : A Langchain app that allows you to chat with multiple PDFs
openclaw-install (2026-08-14) : OpenClaw installer — setup script for OpenClaw AI assistant deployment
api-llm-custom (2026-08-13) : Custom LLM proxy API — route requests to any language model backend
infocepo-infra-mcp (2026-08-12) : infocepo-infra-mcp
api-mcp-openai (2026-08-11) : AI MCP OpenAI Integration
api-embedding (2026-08-07) : Text embedding API — convert text to vector embeddings for semantic search
api-reranker (2026-08-06) : Cross-encoder reranking API for improving search retrieval quality
nemotron-embed (2026-07-31) : nemotron-embed
coder-brain (2026-07-28) : AI-powered code analysis and generation engine
translate-rt (2026-07-28) : Real-time translation API — multilingual translation with low latency
qwen3.5-fp8-vllm (2026-07-27) : Qwen 3.5 FP8 vLLM model deployment
ai-assistant (2026-07-17) : General-purpose AI assistant with task execution capabilities
ai-security (2026-07-17) : AI security tools — audit and harden LLM deployments against common attacks
api-audio2txt (2026-07-17) : Fast audio-to-text transcription API with real-time Whisper model support
api-audio2txt-gemma4 (2026-07-17) : Gemma 4-powered audio transcription API for speech-to-text conversion
api-audio2txt-qwen3 (2026-07-17) : Qwen 3-based audio transcription API leveraging advanced language model capabilities
api-diarization (2026-07-17) : Speaker diarization API — identifies and separates multiple speakers in audio streams
api-image (2026-07-17) : Image processing API — resize, convert, analyze, and transform images
api-lightrag (2026-07-17) : Lightweight RAG (Retrieval-Augmented Generation) API for document-based Q&A
api-llm-privacy-proxy (2026-07-17) : LLM privacy proxy — filter secrets and sensitive data from API calls
api-llm-privacy-proxy-gliner2 (2026-07-17) : GLiNER2-powered LLM privacy proxy for named entity detection and filtering
api-llm-privacy-proxy-openmed (2026-07-17) : OpenMED-powered LLM privacy proxy for medical text privacy filtering
api-ocr (2026-07-17) : Document OCR API — extract text, tables, and structure from scanned documents
api-realtime-ai (2026-07-17) : Real-time AI inference API with low-latency streaming responses
api-tts-omnivoice (2026-07-17) : Text-to-speech API powered by OmniVoice for natural voice synthesis
api-txt2audio (2026-07-17) : Text-to-audio generation API for converting text content to audio output
artificial-human (2026-07-17) : Artificial human simulation — explore the boundary between human and AI behavior
audio2txt (2026-07-17) : audio2txt
common-good-accelerator (2026-07-17) : Platform for accelerating common good and social impact initiatives
dgx-memory-fix (2026-07-17) : NVIDIA DGX memory management — diagnose and fix memory leaks on GPU systems
diff-multi (2026-07-17) : Multi-format diff tool — compare files, directories, and structured data
docker2rootless (2026-07-17) : docker2rootless
evaluate-my-code (2026-07-17) : Code evaluation and quality assessment tool — automated peer review
github-k8s-example (2026-07-17) : Kubernetes deployment example for GitHub Actions CI/CD pipelines
k8s-internet-infrastructure (2026-07-17) : Internet infrastructure on Kubernetes — DNS, networking, and routing
langextract-demo (2026-07-17) : Demo application showcasing langextract for LLM output extraction
langfuse-k8s (2026-07-17) : Langfuse observability deployment on Kubernetes for LLM tracing and monitoring
legal-agent (2026-07-17) : Legal AI agent — assist with legal document analysis and research
litellm-proxy (2026-07-17) : LiteLLM proxy — unified API interface for multiple LLM providers
llmbench (2026-07-17) : LLM benchmarking suite — measure and compare language model performance
mail-search (2026-07-17) : Email search tool — query and analyze inbox contents
mediawiki-migrate (2026-07-17) : MediaWiki migration tool — migrate and sync wiki content between platforms
opencode-demo (2026-07-17) : OpenCode CLI demo — open-source alternative for AI-assisted coding
realtime-transcription (2026-07-17) : Real-time audio transcription service — live speech-to-text
vpn-network (2026-07-17) : VPN network configuration — secure remote access and networking

Priorités

Top tasks

Presidio : anonymisation / masquage PII, socle RGPD obligatoire.
Temporal : orchestration de workflows critiques et fiables.
OmniRoute : passerelle IA unifiée, auto-fallback, compression de tokens.
NeMo Guardrails : garde-fous et politiques de sécurité IA.
Langfuse : observabilité, evals et metrics pour pipelines IA.
LMCache : couche KV cache ultra-rapide, latence d'inférence réduite.
Meshery : gestion cloud native multi-cluster, observabilité.
PageIndex : RAG vectorless à raisonnement, alternative aux embeddings.
Coût unitaire par tâche : chaque API doit exposer son prix/ml/token en temps réel — pas une facture mensuelle.
Qualité auto : précision/hallucination rate branchés sur les sorties IA, avec rollback automatique si qualité < seuil.

Backlog / Veille Technologique

Agents IA & Orchestration

langflow : Builder et déployer des agents IA et workflows. UI visuelle low-code.
LangChain : Framework pour applications basées sur les LLM. Le plus mature. (145k⭐)
Dify : Plateforme de développement d'applications IA (LLM Ops). Déployable en self-host. (154k⭐)
browser-use : Framework pour contrôler les navigateurs via des agents IA. (112k⭐)
OpenHands — Agent IA autonome pour le développement logiciel. (86k⭐)
CubeSandbox — Sandbox instantanée, concurrente, sécurisée et légère pour agents IA.
cognee — Mémoire IA à long terme via graphe de connaissances auto-hébergé.
Haystack — Framework RAG end-to-end (deepset).
deer-flow — SuperAgent open-source à horizon long : recherche, codage et création. (81k⭐)
agent-toolkit-for-aws — Serveurs MCP, compétences et plugins officiels AWS.
SkillSpector — Scanner de sécurité pour les compétences d'agents IA.
flue — Framework sandbox pour agents IA : isolation et exécution sécurisée.
n8n : Fair-code workflow automation with native AI. 400+ intégrations. (203k⭐)
CopilotKit : Frontend Stack for Agents & Generative UI. (37k⭐)
open-webui : Interface web IA (Ollama, OpenAI API, MCP). (151k⭐)
lobehub : Chief Agent Operator — supervision d'équipes d'agents 7x24. (82k⭐)
openinterpreter : Agent de codage pour les modèles ouverts.
vllm : Moteur d'inférence haute performance pour LLMs. (91k⭐)
gemini-cli : Agent IA open-source dans votre terminal (Google). (106k⭐)
milvus : Base de données vectorielle haute performance. (46k⭐)
qdrant : Vector database haute performance. (34k⭐)
MinerU : Transforme PDFs et documents en données LLM-ready. (79k⭐)

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sglang (2026-09-10) : SGLang is a high-performance serving framework for large language models and multimodal models. (35,715⭐)
Summer2027-Internships (2026-09-10) : Summer 2027 software engineering, data science, AI, quant, product management, and hardware internship postings. Updated daily by Simplify and Pitt CSC. (47,271⭐)
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posthog (2026-09-10) : :hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP. (39,723⭐)
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hyperframes (2026-09-10) : Write HTML. Render video. Built for agents. (48,392⭐)
litellm (2026-09-10) : The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, load balancing, and logging [Bedrock, Azure, OpenAI, Anthropic, OpenAI, VertexAI, vLLM, Nvidia NIM] (58,392⭐)
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supabase (2026-09-10) : The Postgres development platform. Supabase gives you a dedicated Postgres database to build your web, mobile, and AI applications. (109,001⭐)
dokploy (2026-09-10) : Open Source Alternative to Vercel, Netlify and Heroku. (37,201⭐)
airflow (2026-09-10) : Apache Airflow - A platform to programmatically author, schedule, and monitor workflows (46,796⭐)
paperless-ngx (2026-09-10) : A community-supported supercharged document management system: scan, index and archive all your documents (44,966⭐)
herdr (2026-09-10) : the runtime your coding agents live on (37,125⭐)
goose (2026-09-10) : an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM (54,066⭐)
ai-agents-for-beginners (2026-09-10) : 18 Lessons to Get Started Building AI Agents (74,293⭐)
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pi (2026-09-10) : AI agent toolkit: unified LLM API, agent loop, TUI, coding agent CLI (103,482⭐)
impeccable (2026-09-10) : The design language that makes your AI harness better at design. (66,882⭐)
crewAI (2026-09-10) : Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. (58,297⭐)
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anything-llm (2026-09-10) : Stop renting your intelligence. Own it with AnythingLLM. Everything you need for a powerful local-first agent experience (65,846⭐)
openhuman (2026-09-10) : OpenHuman is an open source personal AI for Mac, Windows and Linux — local-first memory, agent orchestration, and deep research. (39,583⭐)
transformers (2026-09-10) : 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training. (165,046⭐)
system_prompts_leaks (2026-09-10) : Extracted system prompts from Anthropic - Claude Fable 5.1, Opus 5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro, Antigravity. xAI - Grok, Grok Bot, Cursor, Kimi and more! Updated regularly. (64,570⭐)
next-ai-draw-io (2026-09-10) : A next.js web application that integrates AI capabilities with draw.io diagrams. This app allows you to create, modify, and enhance diagrams through natural language commands and AI-assisted visualization. (35,732⭐)
spec-kit (2026-09-10) : 💫 Toolkit to help you get started with Spec-Driven Development (134,427⭐)
langfuse (2026-09-10) : 🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23 (34,406⭐)
twenty (2026-09-10) : The open alternative to Salesforce, designed for AI. (56,499⭐)
OpenHands (2026-09-10) : 🙌 OpenHands: AI-Driven Development (87,110⭐)
ray (2026-09-10) : Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads. (43,759⭐)
reactive-resume (2026-09-10) : A one-of-a-kind resume builder that keeps your privacy in mind. Completely secure, customizable, portable, open-source and free forever. Try it out today! (42,380⭐)
AutoGPT (2026-09-10) : AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters. (187,238⭐)
context7 (2026-09-10) : Context7 Platform -- Up-to-date code documentation for LLMs and AI code editors (61,816⭐)
BMAD-METHOD (2026-09-10) : Breakthrough Method for Agile Ai Driven Development (52,835⭐)
langchain (2026-09-10) : The agent engineering platform. (146,023⭐)
generative-ai-for-beginners (2026-09-10) : 21 Lessons, Get Started Building with Generative AI (119,454⭐)
strix (2026-09-10) : Open-source AI penetration testing tool to find and fix your app’s vulnerabilities. (61,557⭐)
DeepSeek-Reasonix (2026-09-10) : DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability — leave it running. (35,458⭐)
tidb (2026-09-10) : TiDB is built for agentic workloads that grow unpredictably, with ACID guarantees and native support for transactions, analytics, and vector search. No data silos. No noisy neighbors. No infrastructure ceiling. (40,505⭐)
awesome-claude-code (2026-09-10) : A hand-picked collection of the finest of resources for the most awesome of agents, Claude Code, the undisputed champion of coding companions, from the unstoppable team at Anthropic PBC. A delectable showcase of top tier skills, ambidextrous agents, scintillating status lines, top notch developer tooling, and also we have plugins (53,780⭐)
cherry-studio (2026-09-10) : AI productivity studio with smart chat, autonomous agents, and 300+ assistants. Unified access to frontier LLMs (51,613⭐)
netdata (2026-09-10) : The fastest path to AI-powered full stack observability, even for lean teams. (80,469⭐)
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QwenPaw (2026-09-10) : Your Personal AI Assistant; easy to install, deploy on your own machine or on the cloud; supports multiple chat apps with easily extensible capabilities. (34,718⭐)
airi (2026-09-10) : 💖🧸 Self hosted, you-owned Grok Companion, a container of souls of waifu, cyber livings to bring them into our worlds, wishing to achieve Neuro-sama's altitude. Capable of realtime voice chat, Minecraft, Factorio playing. Web / macOS / Windows supported. (48,994⭐)
awesome-copilot (2026-09-10) : Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. (38,821⭐)
siyuan (2026-09-10) : An open-source, privacy-first, self-hosted knowledge workspace where humans and AI agents work together 开源、隐私优先、自托管的知识工作空间，让人与智能体在此协作 (46,244⭐)
worldmonitor (2026-09-10) : Real-time global intelligence dashboard. AI-powered news aggregation, geopolitical monitoring, and infrastructure tracking in a unified situational awareness interface (85,923⭐)
jan (2026-09-10) : Jan is an open source alternative to ChatGPT that runs 100% offline on your computer. (44,391⭐)
oh-my-openagent (2026-09-10) : OmO: Just type "mass ulw" keyword with your prompt. Now you are the master of graph engineering. (68,864⭐)
AstrBot (2026-09-10) : AI Agent Assistant & development framework that integrates lots of IM platforms, LLMs, plugins and AI feature, and can be your openclaw alternative. ✨ (40,295⭐)
MoneyPrinterTurbo (2026-09-10) : 利用 AI 大模型和自动化工作流，根据主题或关键词一键生成高清短视频。Generate HD short videos from a topic or keyword with an automated AI workflow. (122,019⭐)
JeecgBoot (2026-09-10) : 【低代码v2.0，一句话即可生成整个系统】企业级AI低代码平台，一键生成前后端代码甚至整个系统。 AI Skills 一句话画流程、设计表单、生成报表、大屏。内置 AI应用平台涵盖：AI聊天、知识库、流程编排、MCP插件等，兼容主流大模型。引领AI低代码「Skills 生成 → 在线配置 → 代码生成 → 手工合并->AI修改」开发模式，解决 Java 项目 90% 重复工作，提高效率又不失灵活。 (47,700⭐)
1Panel (2026-09-10) : 🔥 1Panel is a modern, open-source Linux server management panel and a lightweight AI management platform. (36,857⭐)
CowAgent (2026-09-10) : Open-source super AI assistant & Agent Harness. Plans tasks, runs tools and skills, self-evolves with memory and knowledge. Multi-agent, multi-model, multi-channel. Lightweight, extensible, one-line install. (formerly chatgpt-on-wechat) (46,859⭐)
nacos (2026-09-10) : an easy-to-use dynamic service discovery, configuration and service management platform for building AI cloud native applications. (33,357⭐)
claude-code-best-practice (2026-09-10) : from vibe coding to agentic engineering - practice makes claude perfect (65,804⭐)
career-ops (2026-09-10) : Open-source AI job search: scan job portals, evaluate listings into a structured A-H report with a global 1-5 score, tailor your CV, track applications — runs locally in your AI coding CLI (Claude Code, Codex, OpenCode, Antigravity…) (70,833⭐)
dbeaver (2026-09-10) : Free universal database tool and SQL client (51,707⭐)
superpowers (2026-09-10) : An agentic skills framework & software development methodology that works. (284,133⭐)
ppt-master (2026-09-10) : AI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and tables on demand, audio narration from speaker notes, and support for your own .pptx templates. · by Hugo He (53,390⭐)
llama.cpp (2026-09-10) : LLM inference in C/C++ (127,670⭐)
claude-mem (2026-09-10) : Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More (93,585⭐)
llama_index (2026-09-10) : LlamaIndex is the leading document agent and OCR platform (52,106⭐)
ToolJet (2026-09-10) : Open-source foundation of ToolJet AI - the enterprise app generation platform for internal tools, dashboards, business applications, workflows and AI agents. Build visually, from a prompt, or from Claude Code, Codex and Cursor over MCP 🚀 (40,873⭐)
nanobot (2026-09-10) : Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps (47,962⭐)
minimind (2026-09-10) : 🧠 Train a 64M-parameter LLM from scratch in just 2h! (60,361⭐)
llmfit (2026-09-10) : Hundreds of models & providers. One command to find what runs on your hardware. (35,425⭐)
multica (2026-09-10) : Make humans and AI agents work as one team — open-source and self-hostable. (49,428⭐)
ui-ux-pro-max-skill (2026-09-10) : An AI skill that provides design intelligence for building professional UI/UX across multiple platforms. (126,476⭐)
claude-code-router (2026-09-10) : One local control plane for every AI agent: route across models, fuse new capabilities, orchestrate tools, and stay fully in control. (37,164⭐)
photoprism (2026-09-10) : AI-Powered Photos App 🌈💎✨ (40,175⭐)
firecrawl (2026-09-10) : The context API to search, scrape, and interact with the web at scale. 🔥 (178,507⭐)
airllm (2026-09-10) : AirLLM 70B inference with single 4GB GPU (33,994⭐)
prompt-optimizer (2026-09-10) : An AI prompt optimizer for writing better prompts and getting better AI results. (34,408⭐)
caveman (2026-09-10) : 🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman (104,610⭐)
AppFlowy (2026-09-10) : Bring projects, wikis, and teams together with AI. AppFlowy is the AI collaborative workspace where you achieve more without losing control of your data. The leading open source Notion alternative. (76,494⭐)
rtk (2026-09-10) : CLI proxy that reduces LLM token consumption by 60-90% on common dev commands. Single Rust binary, zero dependencies (79,751⭐)
agno (2026-09-10) : Build, run, and manage agent platforms. (42,126⭐)
meilisearch (2026-09-10) : A lightning-fast search engine API bringing AI-powered hybrid search to your sites and applications. (59,245⭐)
ECC (2026-09-10) : The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. (255,547⭐)
docling (2026-09-10) : Get your documents ready for gen AI (66,240⭐)
mem0 (2026-09-10) : The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production. (65,061⭐)
mindshub (2026-09-10) : The unified workspace where open-source models get things done for you. (39,720⭐)
OpenSpec (2026-09-10) : Spec-driven development (SDD) for AI coding assistants. (67,880⭐)
langgraph (2026-09-10) : Build resilient agents. (41,401⭐)
LLMs-from-scratch (2026-09-10) : Implement a ChatGPT-like LLM in PyTorch from scratch, step by step (104,704⭐)
netron (2026-09-10) : Visualizer for neural network, deep learning and machine learning models (33,463⭐)
ai-job-search (2026-09-10) : The job search that runs on your machine. AI job application framework built on Claude Code: evaluate postings, tailor CVs, write cover letters, prep interviews. Fork it and own it. (41,699⭐)
odysseus (2026-09-10) : Self-hosted AI workspace. (87,100⭐)

Audio & TTS

faster-whisper (mutualisé) — Transcription speech-to-text optimisée.
Qwen3-Omni-30B-A3B-Instruct — Modèle multimodal Qwen (audio + texte + image).
VibeVoice (Microsoft) — Framework vocal open-source (TTS + ASR).
hyperframes : Génération vidéo par agents. (44k⭐)

Génération & Édition d'Images

HiDream-O1-Image — Modèle unifié pixel-level (t2i, édition, customisation jusqu'à 2048×2048).
ComfyUI : GUI et backend diffusion model le plus modulaire. (131k⭐)
unsloth : UI locale pour LLMs et diffusion models. GGUF, MLX, Qwen3.8. (75k⭐)

RAG & Traitement de Documents

firecrawl : API web contextuelle pour search, scrape et interaction. (177k⭐)
RAG sur PDF avec images.
paperless-ngx : Document management : scan, index, archive. ML, OCR. (45k⭐)
graphify : Transforme codebase en graphe de connaissances interrogeable. (115k⭐)
Mem0 — Mémorie à long terme pour agents IA. (64k⭐)
meilisearch — Moteur de recherche full-text. (59k⭐)
LightRAG : [EMNLP2025] RAG simple et rapide. (39k⭐)
appwrite : Infrastructure cloud complète (Auth, DB, Storage, Functions, Messaging). (57k⭐)
PageIndex : Document Index for Vectorless, Reasoning-based RAG. (35k⭐)
graphrag : RAG modulaire basé sur les graphes. (35k⭐)
ragflow : RAG engine open-source avec capacités Agent. (90k⭐)
headroom : Compress tool outputs, logs, files et RAG chunks. 20-95% token savings. (69k⭐)
pathway : Python ETL framework pour stream processing et RAG. (62k⭐)
private-gpt : API layer pour IA privée locale : RAG, skills, MCP. (57k⭐)
granite-docling-258M — Parsing structuré de documents IBM Granite.

dify (2026-09-10) : Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack. (155,243⭐)
ruflo (2026-09-10) : 🌊 The original agent meta-harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, RAG integration, and native Claude Code / Codex / Hermes and many more Integrated (71,811⭐)
OpenViking (2026-09-10) : Self-evolving Context Database for AI Agents. Unify Agent Memory, Knowledge RAG and Skills. (36,300⭐)
deer-flow (2026-09-10) : An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours. (82,171⭐)
ai-engineering-hub (2026-09-11) : In-depth tutorials on LLMs, RAGs and real-world AI agent applications. (37,473⭐)

APIs à Développer

Classificateur IA — Classification de contenu.
Résumé mutualisé — API de résumé de texte partagée.
NER — Reconnaissance d'entités nommées.
Compressor — Compression de contenu.

Infrastructure & Backend

OmniRoute — Passerelle IA gratuite : un endpoint, 352+ providers, compression 15-95% tokens. (62k⭐)
Temporal — Orchestration de workflows critiques.
Supabase — Alternative open-source Firebase (PostgreSQL, Auth, etc.). (108k⭐)
Metabase — Analytics et dashboards open-source.
Semantic Router — Routage sémantique de requêtes vLLM.
LMCache — Couche KV cache ultra-rapide. Réduit latence d'inférence.
openship — Plateforme de déploiement auto-hébergée et auto-déployée.

Outils Dev

Aider — Assistant de codage IA en ligne de commande.
Continue — Extension IDE IA (VS Code, JetBrains). (35k⭐)
MCP LLM — Modèle de langage via Model Context Protocol.

Assistants IA & outils cloud

Assistants IA

Assistants IA auto-hébergés

Hermes WebUI + Ollama + GPU

Stack typique pour assistant privé, API OpenAI-compatible et expérimentation locale.

Développement, modèles & veille

Découverte de modèles

Models Trending

Évaluation & benchmarks

Agentic Evaluation

Outils de développement & fine-tuning

Matériel IA & GPU

NVIDIA GH200
DGX Spark
GROQ LLM accelerator

API Realtime AI (DEV)

Statut : environnement DEV, remplaçante prévue de l’API OpenAI pour les cas temps réel.

Configuration

Variable	Valeur
OPENAI_API_BASE	`wss://api-realtime-ai.ailab.infocepo.com:wait-2026-12/v1`
OPENAI_API_KEY	`sk-XXXXX`

Dépôt GitHub

ynotopec/api-realtime-ai

Page de test

external-test/half-duplex.html — annulation d’écho + mode half-duplex.

Compatibilité

Remplacer l’URL OpenAI par $OPENAI_API_BASE pour tester compatibilité et performances.

API LLM (OpenAI compatible)

URL de base : https://api-nothink.ailab.infocepo.com/v1
Création du token : OPENAI_API_KEY
Documentation : Documentation API

Liste des modèles

curl -X GET \
  'https://api-nothink.ailab.infocepo.com/v1/models' \
  -H 'Authorization: Bearer sk-XXXXX' \
  -H 'accept: application/json' \
  | jq | sed -rn 's#^.*id.*: "(.*)".*$#* \1#p' | sort -u

Modèles ouverts & endpoints internes

Dernière mise à jour : 2026-06-30

Les modèles ci-dessous correspondent à des endpoints logiques exposés derrière une passerelle.

Endpoint	Description / usage principal
ai-thinking	qwen3.6 fp8 – thinking
ai-fast	qwen3.6 fp8 en mode fast – vision/OCR/ai-default
ai-embedding	bge-m3 – recherche sémantique
ai-stt	whisper3-turbo – transcription vocale multilingual
ai-tts	OmniVoice – TTS multilingual
ai-image	OpenDalle – image génération

Exemple bash

export OPENAI_API_MODEL="ai-default"
export OPENAI_API_BASE="https://api-nothink.ailab.infocepo.com/v1"
export OPENAI_API_KEY="sk-XXXXX"

promptValue="Quel est ton nom ?"
jsonValue='{
  "model": "'${OPENAI_API_MODEL}'",
  "messages": [{"role": "user", "content": "'${promptValue}'"}],
  "temperature": 0
}'

curl ${OPENAI_API_BASE}/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d "${jsonValue}" 2>/dev/null | jq '.choices[0].message.content'

Vue infra LLM

File:Litellm-proxy-mermaid-diagram-2024-03-24-205202.png

DEV (au choix)

A. LiteLLM → vLLM/SgLang : tests perf / compatibilité
B. LiteLLM → Ollama : simple, rapide à itérer
C. Ollama direct : POC ultra-léger

DEV – modèle FR / résumé

LiteLLM → Ollama /v1

PROD

Standard : LiteLLM → vLLM/SgLang
Pont DEV→PROD : LiteLLM (DEV) → LiteLLM (PROD) → vLLM/SgLang

Notes :

LiteLLM = passerelle unique (clés, quotas, logs)
vLLM/SgLang = performance / stabilité en charge
Ollama = simplicité de prototypage

API Image to Text

Utilise l’API LLM avec un endpoint adapté à l’OCR / VLM.
Modèle recommandé : ai-vision

Exemple bash

OPENAI_API_KEY=sk-XXXXX

base64 -w0 "/path/to/image.png" > img.b64

jq -n --rawfile img img.b64 \
'{
  model: "ai-vision",
  messages: [
    {
      role: "user",
      content: [
        { "type": "text", "text": "Décris cette image." },
        {
          "type": "image_url",
          "image_url": { "url": ("data:image/png;base64," + ($img | rtrimstr("\n"))) }
        }
      ]
    }
  ]
}' > payload.json

curl https://api-nothink.ailab.infocepo.com/v1/chat/completions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  --data-binary @payload.json

Exemple Python

import base64
import json
import requests
import os

API_KEY = os.getenv("OPENAI_API_KEY")
MODEL = "ai-vision"
IMG_PATH = "/path/to/image.png"
API_URL = "https://api-nothink.ailab.infocepo.com/v1/chat/completions"

with open(IMG_PATH, "rb") as f:
    img_b64 = base64.b64encode(f.read()).decode("utf-8")

payload = {
    "model": MODEL,
    "messages": [
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "Décris cette image."},
                {
                    "type": "image_url",
                    "image_url": {"url": f"data:image/png;base64,{img_b64}"}
                }
            ]
        }
    ]
}

headers = {
    "Authorization": f"Bearer {API_KEY}",
    "Content-Type": "application/json"
}

response = requests.post(API_URL, headers=headers, data=json.dumps(payload))

if response.ok:
    print(json.dumps(response.json(), indent=2, ensure_ascii=False))
else:
    print(f"Erreur {response.status_code}: {response.text}")

API STT

URL : https://api-audio2txt.ailab.infocepo.com/v1
Clé : OPENAI_API_KEY=sk-XXXXX
Modèle : whisper-1
Documentation : API STT docs

Exemple Python

import requests

OPENAI_API_KEY = 'sk-XXXXX'

url = 'https://api-audio2txt.ailab.infocepo.com/v1/audio/transcriptions'
headers = {
    'Authorization': f'Bearer {OPENAI_API_KEY}',
}
files = {
    'file': ('file.opus', open('/path/to/file.opus', 'rb')),
    'model': (None, 'whisper-1')
}

response = requests.post(url, headers=headers, files=files)
print(response.json())

Exemple curl

[ ! -f /tmp/test.ogg ] && wget "https://upload.wikimedia.org/wikipedia/commons/1/17/Fables_de_La_Fontaine_Livre_1_01.ogg" -O /tmp/test.ogg

export OPENAI_API_KEY=sk-XXXXX

curl https://api-audio2txt.ailab.infocepo.com/v1/audio/transcriptions \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -F model="whisper-1" \
  -F file="@/tmp/test.ogg"

Notes

Plusieurs formats audio sont acceptés.
Le flux final est normalisé en 16 kHz mono.
Pour une qualité optimale : privilégier OPUS 16 kHz mono.

UI

translate-rt

API TTS

URL : https://api-tts-omnivoice.ailab.infocepo.com/v1
Clé : OPENAI_API_KEY=sk-XXXXX
Documentation : API TTS docs

Exemple

export OPENAI_API_KEY=sk-XXXXX

curl https://api-tts-omnivoice.ailab.infocepo.com/v1/audio/speech \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini-tts",
    "input": "Bonjour, ceci est un test de synthèse vocale.",
    "voice": "coral",
    "instructions": "Speak in a cheerful and positive tone.",
    "response_format": "opus"
  }' | ffplay -i -

API Text to Image

URL : https://api-txt2image.ailab.infocepo.com/v1
Clé API : OPENAI_API_KEY=sk-...
Documentation : API TXT2IMAGE docs

Exemple

export OPENAI_API_KEY=EMPTY

curl https://api-txt2image.ailab.infocepo.com/v1/images/generations \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
    "prompt": "a photo of a happy corgi puppy sitting and facing forward, studio light, longshot",
    "n": 1,
    "size": "1024x1024"
  }'

API Diarization

Documentation : API Diarization docs

Exemple

wget "https://upload.wikimedia.org/wikipedia/commons/6/60/Mike_Peters_on_Politics_and_Emotion_%28Interview_1984%29.mp3" -O /tmp/test.mp3

curl -X POST "https://api-diarization.ailab.infocepo.com/upload-audio/" \
  -H "Authorization: Bearer token1" \
  -F "file=@/tmp/test.mp3"

API Summary

Documentation : API Summary docs

Exemple

text="The tower is 324 metres tall and is one of the most recognizable monuments in the world."

json_payload=$(jq -nc --arg text "$text" '{"text": $text}')

curl -X POST https://api-summary.ailab.infocepo.com:wait-2026-12/summary/ \
  -H "Content-Type: application/json" \
  -d "$json_payload"

API Text Embeddings

URL : https://api-embedding.ailab.infocepo.com/v1
Documentation : Documentation

Exemple

curl https://api-embedding.ailab.infocepo.com/v1/embeddings \
  -X POST \
  -d '{"model":"bge-m3","input":"What is Deep Learning?"}' \
  -H 'Content-Type: application/json'

API DB Vectors (ChromaDB)

Production

URL : https://chromadb.ailab.infocepo.com:wait-2026-12
Token : XXXXX

Lab

export CHROMA_HOST=https://chromadb.c1.ailab.infocepo.com:wait-2026-12
export CHROMA_PORT=443
export CHROMA_TOKEN=XXXX

Exemple curl

curl -v "${CHROMA_HOST}"/api/v1/collections \
  -H "Authorization: Bearer ${CHROMA_TOKEN}"

Exemple Python

import chromadb
from chromadb.config import Settings

def chroma_http(host, port=80, token=None):
    return chromadb.HttpClient(
        host=host,
        port=port,
        ssl=host.startswith('https') or port == 443,
        settings=(
            Settings(
                chroma_client_auth_provider='chromadb.auth.token.TokenAuthClientProvider',
                chroma_client_auth_credentials=token,
            ) if token else Settings()
        )
    )

client = chroma_http(CHROMA_HOST, CHROMA_PORT, CHROMA_TOKEN)
collections = client.list_collections()
print(collections)

Déployer sa propre instance

export nameSpace=your_namespace
domainRoot=ailab.infocepo.com

helm repo add chroma https://amikos-tech.github.io/chromadb-chart/
helm repo update

helm upgrade --install chromadb chroma/chromadb -n ${nameSpace} \
  --set chromadb.apiVersion="0.4.24" \
  --set ingress.enabled=true \
  --set ingress.hosts[0].host="${nameSpace}-chromadb.${domainRoot}" \
  --set ingress.hosts[0].paths[0].path=/ \
  --set ingress.hosts[0].paths[0].pathType=ImplementationSpecific \
  --set ingress.annotations."cert-manager\.io/cluster-issuer"=letsencrypt-prod \
  --set ingress.tls[0].secretName=${nameSpace}-chromadb.${domainRoot}-tls \
  --set ingress.tls[0].hosts[0]="${nameSpace}-chromadb.${domainRoot}"

kubectl -n ${nameSpace} patch ingress/chromadb --type=json \
  -p '[{"op":"add","path":"/metadata/annotations/nginx.ingress.kubernetes.io~1proxy-body-size","value":"0"}]'

Récupérer le token

kubectl --namespace ${nameSpace} get secret chromadb-auth \
  -o jsonpath="{.data.token}" | base64 --decode && echo

Registry

URL : registry.ailab.infocepo.com:wait-2026-09
Login : user
Password : XXXXX

Exemple

curl -u "user:XXXXX" https://registry.ailab.infocepo.com:wait-2026-09/v2/_catalog

Exemple K8S

deploymentName=
nameSpace=

kubectl -n ${nameSpace} create secret docker-registry pull-secret \
  --docker-server=registry.ailab.infocepo.com:wait-2026-09 \
  --docker-username=user \
  --docker-password=XXXXX \
  --docker-email=contact@example.com

kubectl -n ${nameSpace} patch deployment ${deploymentName} \
  -p '{"spec":{"template":{"spec":{"imagePullSecrets":[{"name":"pull-secret"}]}}}}'

Stockage objet externe (S3)

Endpoint : https://s3.ailab.infocepo.com:wait-2026-09
Access key : XXXX
Secret key : XXXX

Un bucket nommé ORG a été créé pour stocker des documents de démonstration.

RAG optimisation

Embeddings : BAAI/bge-m3
chunk_size=1000
chunk_overlap=100
LLM : qwen3.6
Pour les PDF mixtes : PDF → image → OCR / VLM peut améliorer les résultats.

Workflow

Autoroute directe : code → CI/CD → deploy → monitoring. Pas de comité, pas de responsable désigné — chaque étape se déclenche automatiquement si la précédente passe. Si ça rate, alerte directe sans passer par un humain sauf décision explicite de fallback.

Environnements

Hors production

Utiliser datalab
Support : canal Mattermost Offre IA
Le pseudo utilisateur doit respecter la convention interne
Demander si besoin un accès Linux + Kubernetes

Production (best-effort)

Publier le code applicatif, les secrets (format SOPS), le Dockerfile et le code infra (Helm ou manifests K8S) sur Git
Demander un namespace
Lire la documentation de surveillance associée

Limites de l’infrastructure

Les charges GPU sont intentionnellement limitées en journée.
Coût unitaire mesuré automatiquement (dashboards temps réel, pas Excel).

Cloud Lab & projets d’audit

Le Cloud Lab fournit des scénarios reproductibles : audit d’infrastructure, migration cloud, automatisation, haute disponibilité.

Projet d’audit

ServerDiff.sh

Script Bash d’audit permettant de :

détecter les dérives de configuration,
comparer plusieurs environnements,
préparer un plan de migration ou de remédiation.
open-code-review - Outil de review de code open-source teste a l echelle Alibaba : pipeline deterministe + agent LLM, precise par ligne.. (16590 stars)

Exemple de migration cloud

Tâche	Description	Durée (jours)
Audit infrastructure	82 services, audit automatisé via ServerDiff.sh	1.5
Diagramme d’architecture	Conception visuelle et documentation	1.5
Contrôles de conformité	2 clouds, 6 hyperviseurs, 6 To RAM	1.5
Installation plateforme cloud	Déploiement des environnements cibles	1.0
Vérification de stabilité	Premiers tests fonctionnels	0.5
Étude d’automatisation	Identification des tâches répétitives	1.5
Développement des templates	6 templates, 8 environnements, 2 clouds / OS	1.5
Diagramme de migration	Illustration du processus	1.0
Écriture du code de migration	138 lignes (voir MigrationApp.sh)	1.5
Stabilisation	Validation de la reproductibilité	1.5
Benchmark cloud	Comparaison vs legacy	1.5
Réglage des temps d’arrêt	Calcul du downtime	0.5
Chargement VM	82 VMs : OS, code, 2 IP par VM	0.1
Total		15 jours.homme

Vérifications de stabilité (HA minimale)

Action	Résultat attendu
Extinction d’un nœud	Tous les services redémarrent automatiquement sur les autres nœuds
Extinction / redémarrage simultané de tous les nœuds	Les services repartent correctement après reboot

Autonomie testée : vérifier que la migration fonctionne seule en tirant le repo et lançant le script, sans personne qui connaît le système de tête.

Architecture web & bonnes pratiques

Principes de conception :

privilégier une infrastructure simple, modulaire et flexible,
rapprocher le contenu du client (GDNS ou équivalent),
utiliser des load balancers réseau (LVS, IPVS),
comparer les coûts et éviter le vendor lock-in,
pour TLS :
- HAProxy pour les frontends rapides,
- Envoy pour les cas avancés (mTLS, HTTP/2/3),
pour le cache :
- Varnish, Apache Traffic Server,
favoriser les stacks open-source,
utiliser files, buffers, queues et quotas pour lisser les pics.

Références

Comparatif des grandes plateformes cloud

Fonctionnalité	Kubernetes	OpenStack	AWS	Bare-metal	HPC	CRM	oVirt
Outils de déploiement	Helm, YAML, ArgoCD, Juju	Ansible, Terraform, Juju	CloudFormation, Terraform, Juju	Ansible, Shell	xCAT, Clush	Ansible, Shell	Ansible, Python
Méthode de bootstrap	API	API, PXE	API	PXE, IPMI	PXE, IPMI	PXE, IPMI	PXE, API
Contrôle routeur	Kube-router	Router/Subnet API	Route Table / Subnet API	Linux, OVS	xCAT	Linux	API
Contrôle firewall	Istio, NetworkPolicy	Security Groups API	Security Group API	Linux firewall	Linux firewall	Linux firewall	API
Virtualisation réseau	VLAN, VxLAN	VPC	VPC	OVS, Linux	xCAT	Linux	API
DNS	CoreDNS	DNS-Nameserver	Route 53	GDNS	xCAT	Linux	API
Load balancer	Kube-proxy, LVS	LVS	Network Load Balancer	LVS	SLURM	Ldirectord	N/A
Stockage	Local, cloud, PVC	Swift, Cinder, Nova	S3, EFS, EBS, FSx	Swift, XFS, EXT4, RAID10	GPFS	SAN	NFS, SAN

Cette table sert de point de départ pour choisir la bonne stack selon :

le niveau de contrôle souhaité,
le contexte (on-prem, cloud public, HPC…),
les outils d’automatisation existants.

Haute disponibilité, HPC & DevSecOps

Haute disponibilité avec Corosync & Pacemaker

Principes :

clusters multi-nœuds ou multi-sites,
fencing via IPMI,
provisioning PXE / NTP / DNS / TFTP,
pour 2 nœuds : attention au split-brain,
3 nœuds ou plus recommandés en production.

Ressources fréquentes

multipath, LUNs, LVM, NFS,
processus applicatifs,
IP virtuelles, DNS, listeners réseau.

HPC

orchestration de jobs (SLURM ou équivalent),
stockage partagé haute performance,
intégration possible avec des workloads IA.

DevSecOps

CI/CD avec contrôles de sécurité intégrés,
observabilité dès la conception,
scans de vulnérabilité,
gestion des secrets,
policy-as-code.

News & trends

Formation & apprentissage

Transformers Explained
Labs, scripts et retours d’expérience concrets dans le projet Cloud Lab

Liens cloud & IT utiles

Outils collaboratifs

Dépôts de code

GitHub ynotopec

Base de connaissance

ce wiki

Messagerie

contact interne / support selon les projets

SSO

Keycloak

À propos & contributions

Suggestions de corrections, améliorations de schémas, retours d’expérience ou nouveaux labs bienvenus.

Ce wiki a vocation à rester un laboratoire vivant pour l’IA, le cloud et l’automatisation.

Main Page: Difference between revisions

Latest revision as of 00:05, 11 September 2026

infocepo.com – Cloud, AI & Labs

Accès rapide

Portail principal

Assistant IA

Liste des pages du wiki

Vue d’ensemble

Démarrer rapidement

Parcours recommandés

Vue d’ensemble du contenu

Vision

Catalogue rapide des services

Sélection AI & architecture par couche

Frameworks

Mémoire

Nouveautés

Nouveautés implémentés

Priorités

Top tasks

Backlog / Veille Technologique

Agents IA & Orchestration

Audio & TTS

Génération & Édition d'Images

RAG & Traitement de Documents

APIs à Développer

Infrastructure & Backend

Outils Dev

Assistants IA & outils cloud

Assistants IA

Développement, modèles & veille

Matériel IA & GPU

API Realtime AI (DEV)

Configuration

Dépôt GitHub

Page de test

Compatibilité

API LLM (OpenAI compatible)

Liste des modèles

Modèles ouverts & endpoints internes

Exemple bash

Vue infra LLM

API Image to Text

Exemple bash

Exemple Python

API STT

Exemple Python

Exemple curl

Notes

UI

API TTS

Exemple

API Text to Image

Exemple

API Diarization

Exemple

API Summary

Exemple

API Text Embeddings

Exemple

API DB Vectors (ChromaDB)

Production

Lab

Exemple curl

Exemple Python

Déployer sa propre instance

Récupérer le token

Registry

Exemple

Exemple K8S

Stockage objet externe (S3)

RAG optimisation

Workflow

Environnements

Hors production

Production (best-effort)

Limites de l’infrastructure

Cloud Lab & projets d’audit

Projet d’audit

Exemple de migration cloud