{"schema_version":"onlylabs.public_analysis_evidence.v1","title":"Novita AI analysis evidence pack","description":"Public onlylabs evidence pack for cited agent analysis: captured pages, ranked public signals, and stored web-search provenance used by the background analysis workflow.","url":"https://onlylabs.fyi/analysis/novita","json_url":"https://onlylabs.fyi/analysis/novita/evidence.json","generated_at":"2026-06-27T22:36:41.608Z","org":{"slug":"novita","name":"Novita AI","category":"neocloud","category_label":"Neocloud","dossier_url":"https://onlylabs.fyi/labs/novita"},"analysis":{"url":"https://onlylabs.fyi/analysis/novita","json_url":"https://onlylabs.fyi/analysis/novita/analysis.json","generated_at":"2026-06-27T19:09:33.199+00:00"},"workflow":{"version":"onlylabs-deepagents-analysis-v3","provider":"deepseek","model":"deepseek-v4-pro","agent":"deepagents","public_pack_mode":"local-pages-and-events","live_web_fetches":false,"note":"Public evidence exports do not trigger live Exa calls; stored Exa provenance is included when analysis metadata contains it."},"stats":{"pages":28,"events":93,"web":0,"evidence":88,"signal_desks":{"hiring":4,"forks":12,"releases":22,"talking":0,"repos":22},"data_radar_lanes":null,"data_radar_matches":null,"stored_analysis_evidence":94,"stored_analysis_web":6,"stored_analysis_signal_desks":{"forks":12,"repos":22,"hiring":4,"talking":0,"releases":22},"stored_analysis_data_radar_lanes":null,"stored_analysis_data_radar_matches":null},"stored_web_provenance":{"queries":["\"Novita AI\" frontier AI lab recent model release research hiring GitHub Hugging Face","\"Novita AI\" AI lab what they are building talking about hiring releasing forking"],"request_ids":["bb91707887590fd5af766727084f8240","97e90f28030504dac4aaf4a06198d14c"],"skipped":null},"evidence":[{"ref":"P1","kind":"page","title":"Forward Deployed Engineer","date":"2026-06-26T07:02:23.507893+00:00","date_source":null,"source_url":"https://jobs.ashbyhq.com/novita-ai/5f6a5483-cb49-4e08-a488-b497fe41a1d9","signal_url":null,"signal_json_url":null,"text":"# Forward Deployed Engineer\n\nTeam: Sales\n\nLocation: San Mateo\n\nEmployment type: FullTime\n\nWorkplace type: OnSite\n\nRemote: no\n\nPublished: 2026-06-25T10:18:36.208+00:00\n\nABOUT NOVITA AI\n\nNovita AI is an AI & Agent Cloud platform for builders.\n\nWe provide a unified platform for Model APIs, GPU Cloud, and Agent Sandbox infrastructure, helping developers and enterprises build, deploy, and scale production AI systems without managing complex infrastructure. Today, thousands of teams rely on Novita to power AI agents, coding tools, multimodal applications, and large-scale inference workloads.\n\nTHE ROLE\n\nAs a Forward Deployed Engineer (FDE), you’ll work at the intersection of engineering, customer success, and product. You’ll partner closely with customers to understand their AI workloads, deploy solutions, troubleshoot production issues, and influence the evolution of our platform.\n\nYou will act as an extension of our customers’ engineering teams, helping them integrate model APIs, GPU infrastructure, and sandbox environments into real-world applications.\n\nThis role is ideal for someone who enjoys wearing multiple hats—software engineer, solutions architect, product thinker, and trusted technical advisor.\n\nWHAT YOU’LL DO\n\n- Work directly with customers to understand their AI products, technical requirements, and business goals.\n\n- Deploy and integrate Novita AI products, including:\n\n- Model APIs and inference endpoints\n\n- Dedicated model hosting\n\n- GPU cloud infrastructure\n\n- Agent sandbox environments\n\n- Debug production issues across APIs, networking, containers, GPUs, and distributed systems.\n\n- Build customer-specific solutions, integrations, demos, and prototypes.\n\n- Travel to customer sites when necessary and collaborate closely with their engineering teams.\n\n- Translate customer feedback into product requirements and work with internal engineering teams to improve our platform.\n\n- Create reusable tooling, automation, and reference implementations that benefit future customers.\n\n- Support proof-of-concepts (PoCs) and help customers successfully move into production.\n\nWHAT WE’RE LOOKING FOR\n\nREQUIREMENTS\n\n- Strong software engineering fundamentals.\n\n- Proficiency "},{"ref":"P2","kind":"page","title":"novitalabs/novita-kilo-workshop repository metadata","date":"2026-06-25T07:02:36.745614+00:00","date_source":null,"source_url":"https://github.com/novitalabs/novita-kilo-workshop","signal_url":null,"signal_json_url":null,"text":"# novitalabs/novita-kilo-workshop\n\nLanguage: CSS\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2026-06-24T13:24:42Z\n\nPushed: 2026-06-24T13:24:47Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# React + TypeScript + Vite\n\nThis template provides a minimal setup to get React working in Vite with HMR and some Oxlint rules.\n\nCurrently, two official plugins are available:\n\n- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Oxc](https://oxc.rs)\n- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/)\n\n## React Compiler\n\nThe React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation).\n\n## Expanding the Oxlint configuration\n\nIf you are developing a production application, we recommend enabling type-aware lint rules by installing `oxlint-tsgolint` and editing `.oxlintrc.json`:\n\n```json\n{\n\"$schema\": \"./node_modules/oxlint/configuration_schema.json\",\n\"plugins\": [\"react\", \"typescript\", \"oxc\"],\n\"options\": {\n\"typeAware\": true\n},\n\"rules\": {\n\"react/rules-of-hooks\": \"error\",\n\"react/only-export-components\": [\"warn\", { \"allowConstantExport\": true }]\n}\n}\n```\n\nSee the [Oxlint rules documentation](https://oxc.rs/docs/guide/usage/linter/rules) for the full list of rules and categories."},{"ref":"P3","kind":"page","title":"novitalabs/pegaflow v0.22.10","date":"2026-06-22T07:04:20.323351+00:00","date_source":null,"source_url":"https://github.com/novitalabs/pegaflow/releases/tag/v0.22.10","signal_url":null,"signal_json_url":null,"text":"# v0.22.10\n\nRepository: novitalabs/pegaflow\n\nTag: v0.22.10\n\nPublished: 2026-06-22T06:54:16Z\n\nPrerelease: no\n\nRelease notes:\nRelease of the pegaflow workspace / `pegaflow-llm` `0.22.10` — 12 commits since v0.22.9, centered on MLA KV-cache storage efficiency, model-aware transfer-backend selection, and cross-node redundancy observability.\n\n## English\n\n### ✨ Features\n- **MLA KV page-first storage** (#360) — store MLA KV cache page-first so per-block metadata collapses, cutting metadata overhead for MLA models.\n- **Per-layer MLA TP save distribution** (#359) — spread MLA tensor-parallel save work across ranks by layer to balance save load.\n- **Model-aware KV transfer backend** (#357) — the connector auto-selects the KV transfer backend per model; the server no longer needs a static backend setting.\n- **Metaserver block-redundancy metrics** (#361) — new `pegaflow_metaserver_block_redundancy{owners=\"1|2|3|>=4\"}` distribution plus `pegaflow_metaserver_block_redundancy_avg` gauge, surfacing the cross-node KV replication factor (how much effective cache capacity shrinks).\n- **P/D handshake wire schema** (#345) — seal the prefill/decode handshake wire schema in `pegaflow-pd-wire`.\n- **Transfer benchmarks** (#349, `eb69309`) — p2p RDMA fetch example plus native D2H/H2D transfer-path measurement.\n\n### 🐛 Fixes\n- **Drop late duplicate saves** (#358) — skip late duplicate saves of already-resident blocks, avoiding redundant work.\n\n### ♻️ Refactors\n- Restructure `pd_connector` for maintainability (#355).\n- `SealedBlock` owns its `RawBlock` slots (#352).\n- Use `usize` for `block_ids`, validated at the RPC boundary (#351).\n\n### 🔧 Chore\n- Bump version `0.22.9` → `0.22.10` (#362).\n\n> ⚠️ **Strict version handshake**: client and server must match on `CARGO_PKG_VERSION` at registration — upgrade both sides together.\n\n## 中文\n\n### ✨ 新功能\n- **MLA KV page-first 存储** (#360) — MLA KV cache 按 page-first 布局存储,合并每块元数据,降低 MLA 模型的元数据开销。\n- **MLA TP save 按层跨 rank 分摊** (#359) — 把 MLA 张量并行的 save 工作按层分散到各 rank,均衡 save 负载。\n- **按模型自动选 KV 传输 backend** (#357) — connector 按模型自动选择 KV 传输 backend,server 不再需要静态指定。\n- **Metaserver 块冗余度指标** (#361) — 新增 `pegaflow_metaserver_block_redundancy{owners=\"1|2|3|>=4\"}` 分"},{"ref":"P4","kind":"page","title":"novitalabs/pegaflow v0.22.9","date":"2026-06-12T07:03:32.115473+00:00","date_source":null,"source_url":"https://github.com/novitalabs/pegaflow/releases/tag/v0.22.9","signal_url":null,"signal_json_url":null,"text":"# v0.22.9\n\nRepository: novitalabs/pegaflow\n\nTag: v0.22.9\n\nPublished: 2026-06-11T11:25:52Z\n\nPrerelease: no\n\nRelease notes:\n## What's Changed\n* refactor(core): replace KVCacheRegistration with validated KVCacheLayout by @xiaguan in https://github.com/novitalabs/pegaflow/pull/340\n* feat(pd): support mtp split connector by @GentleCold in https://github.com/novitalabs/pegaflow/pull/341\n* fix(core)!: seal instance layer topology from registered layers by @xiaguan in https://github.com/novitalabs/pegaflow/pull/346\n* feat(connector): register layer-split KV caches from cache config by @feifei-111 in https://github.com/novitalabs/pegaflow/pull/343\n* chore: bump version to 0.22.9 by @xiaguan in https://github.com/novitalabs/pegaflow/pull/347\n\n**Full Changelog**: https://github.com/novitalabs/pegaflow/compare/v0.22.8...v0.22.9"},{"ref":"P5","kind":"page","title":"Solutions Engineer (AI Cloud Infrastructure)","date":"2026-06-11T04:11:06.590183+00:00","date_source":null,"source_url":"https://jobs.ashbyhq.com/novita-ai/f0534078-76a1-478d-a349-6d409dddabb4","signal_url":null,"signal_json_url":null,"text":"# Solutions Engineer (AI Cloud Infrastructure)\n\nTeam: Go-to-Market\n\nLocation: San Mateo\n\nEmployment type: FullTime\n\nWorkplace type: OnSite\n\nRemote: no\n\nPublished: 2025-08-27T03:06:52.237+00:00\n\nAbout Us:\n\nWe are a high-growth, global AI cloud infrastructure provider at the forefront of the artificial intelligence revolution. Our cutting-edge platform offers developers and enterprises powerful, scalable, and easy-to-use solutions, including Model APIs, GPU Instances, and Serverless Computing. As businesses worldwide race to integrate AI into their products, we provide the foundational engine to power their innovation.\n\nWe are building a world-class team to serve a rapidly expanding customer base. This is a unique opportunity to join a dynamic company in a hyper-growth market, where your technical expertise will directly shape customer success and drive our business forward.\n\nThe Role:\n\nAs a Solutions Engineer, you will be the primary technical leader and trusted advisor for our customers throughout their journey. You will partner closely with the sales team to bridge the gap between complex customer challenges and our technical solutions. Your mission is to establish technical credibility, showcase the power of our platform, and architect solutions that ensure our customers achieve their AI-driven business goals.\n\nWhat You'll Do:\n\n- Technical Discovery & Solution Design: Partner with Account Executives to deeply understand customer needs, technical requirements, and business objectives. Architect elegant and effective solutions leveraging our AI infra stack (Model APIs, GPU Instances, Serverless).\n\n- Product Demonstration & Proof of Concept (POC): Lead compelling, customized product demonstrations and hands-on workshops. Design, manage, and execute successful POCs, proving the value and performance of our platform in the customer's environment.\n\n- Technical Evangelism & Trusted Advisory: Articulate the value proposition of our platform to both technical and non-technical audiences, from engineers to C-level executives. Become the go-to expert for customers on AI infrastructure best practices.\n\n- Sales Enablement & Market Feedback Loop: Create and maintain technic"},{"ref":"P6","kind":"page","title":"Account Executive","date":"2026-06-11T04:11:06.543008+00:00","date_source":null,"source_url":"https://jobs.ashbyhq.com/novita-ai/6b9784ff-bc78-42b0-bf1d-a6bac48f5b17","signal_url":null,"signal_json_url":null,"text":"# Account Executive\n\nTeam: Go-to-Market\n\nLocation: San Mateo\n\nEmployment type: FullTime\n\nWorkplace type: Hybrid\n\nRemote: yes\n\nPublished: 2026-04-01T06:26:16.916+00:00\n\nThe Role\n\nAs one of our first Account Executives, you will be the tip of the spear for our Sales-Led Growth (SLG) motion. You will be responsible for driving revenue by acquiring new B2B customers—ranging from agile AI startups to mid-market enterprises.\n\nYou are a \"full-cycle\" closer who is comfortable hunting for outbound opportunities, running technical discovery calls with CTOs and AI researchers, and navigating complex deal cycles. Because we are a cross-border team, your ability to bridge the gap between US clients and our global engineering team will be critical to your success.\n\nWhat You Will Do\n\n- Full-Cycle Sales: Own the entire sales process from prospecting and lead generation to negotiation and closing.\n\n- Outbound Hunting: Proactively identify and target AI startups, research labs, and tech companies that require scalable GPU compute and LLM API solutions.\n\n- Technical Discovery: Conduct deep-dive discovery calls with technical buyers (CTOs, VP of Engineering, Lead AI Scientists) to understand their infrastructure pain points and position our solutions effectively.\n\n- Pipeline Management: Maintain a healthy pipeline of opportunities, providing accurate forecasting and CRM hygiene.\n\n- Cross-Border Collaboration: Work closely with our global product, engineering, and marketing teams (based in China and the US) to ensure customer feedback is translated into product improvements and to secure technical support for complex deals.\n\n- Market Intelligence: Act as the eyes and ears on the ground, gathering insights on competitor pricing, feature gaps, and market trends in the Silicon Valley AI ecosystem.\n\nWho You Are (Qualifications)\n\n- Experience: 3+ years of quota-carrying B2B sales experience in Cloud Infrastructure (IaaS/PaaS), Developer Tools, or AI/Machine Learning SaaS.\n\n- Technical Empathy: You don't need to write code, but you must deeply understand the AI landscape. You know the difference between training and inference, understand what an API endpoint is, and can confidently discus"},{"ref":"P7","kind":"page","title":"Chief of Staff","date":"2026-06-11T04:11:06.469312+00:00","date_source":null,"source_url":"https://jobs.ashbyhq.com/novita-ai/aa4bf0ce-f369-47d5-a989-b7af828e4833","signal_url":null,"signal_json_url":null,"text":"# Chief of Staff\n\nTeam: Operations\n\nLocation: San Mateo\n\nEmployment type: FullTime\n\nWorkplace type: OnSite\n\nRemote: no\n\nPublished: 2026-04-16T08:57:01.752+00:00\n\nWho We Are\n\nAt Novita AI, we’re on a mission to make open-source AI models accessible to everyone—no massive teams or endless resources required. Our AI cloud platform handles all the heavy lifting in AI infra for developers and enterprises so they can focus on building the future. We believe that truly democratizing AI means letting every developer experiment and create without barriers.\n\nAbout the Role:\n\nWe are seeking a highly organized, detail-oriented, and proactive Chief of Staff to serve as the operational backbone of our North American team.\n\nYou will be the \"first line of defense\" for local compliance, managing everything from vendor contracts and budget tracking to SaaS optimization and daily administration. This is a high-trust, high-impact position with a clear growth trajectory toward a Head of Operations role for the right candidate.\n\nKey Responsibilities:\n\n- Compliance & Risk Management: Act as the local compliance gatekeeper. Proactively review sales contracts and vendor agreements before execution. Identify and resolve historical contract gaps to ensure robust risk mitigation.\n\n- Finance & Budget Tracking: Monitor the operational budget, track spending efficiency, and provide early warnings for budget overruns. Handle local tax, government correspondence, and administrative compliance loops.\n\n- Internal Efficiency & IT/SaaS Management: Audit and manage local SaaS subscriptions (e.g., Gusto, CRM tools) to optimize costs and utilization. Ensure data privacy and security standards are met in all contract and invoice management processes.\n\n- General Administration: Oversee daily office operations, support local HR functions, and provide comprehensive logistical support to ensure the frontline team can focus on business growth.\n\nQualifications:\n\n- Education: Bachelor’s or Master’s degree. Backgrounds in STEM, Data Analytics, Business Administration, Project Management, or Pre-Law are highly preferred. (Recent graduates with strong potential are welcome to apply).\n\n- Language: Fluent in Manda"},{"ref":"P8","kind":"page","title":"novitalabs/litelama repository metadata","date":"2026-06-11T04:08:54.527752+00:00","date_source":null,"source_url":"https://github.com/novitalabs/litelama","signal_url":null,"signal_json_url":null,"text":"# novitalabs/litelama\n\nDescription: lightweight LAMA inference wrapper\n\nLanguage: Python\n\nStars: 27\n\nForks: 3\n\nOpen issues: 0\n\nCreated: 2023-09-25T08:30:03Z\n\nPushed: 2023-09-28T04:02:49Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Lite Lama - A lightweight LAMA inference wrapper\n\n```python\nfrom litelama import LiteLama\nimport requests\nfrom PIL import Image\nfrom io import BytesIO\n\ndef download_image(url):\nresponse = requests.get(url)\nreturn Image.open(BytesIO(response.content)).convert(\"RGB\")\n\nimg_url = \"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png\"\nmask_url = \"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png\"\n\nlama = LiteLama()\nlama.to(\"cuda:0\")\ninit_image = download_image(img_url).resize((512, 512))\nmask_image = download_image(mask_url).resize((512, 512))\n\nlama.predict(init_image, mask_image).save(\"result.png\")\n```"},{"ref":"P9","kind":"page","title":"novitalabs/golang-sdk repository metadata","date":"2026-06-11T04:08:54.214686+00:00","date_source":null,"source_url":"https://github.com/novitalabs/golang-sdk","signal_url":null,"signal_json_url":null,"text":"# novitalabs/golang-sdk\n\nDescription: Golang SDK for Novita AI API (Txt2Img, Img2Img, ControlNet, VAE, LoRA)\n\nLanguage: Go\n\nLicense: MIT\n\nStars: 4\n\nForks: 3\n\nOpen issues: 0\n\nCreated: 2023-09-26T14:11:28Z\n\nPushed: 2023-11-21T04:10:37Z\n\nDefault branch: main\n\nFork: no\n\nArchived: yes\n\nREADME:\n# Novita AI Golang SDK\n\nThis SDK is based on the official [API documentation](https://docs.novita.ai/).\n\n**Join our discord server for help**\n\n[![](https://dcbadge.vercel.app/api/server/Mqx7nWYzDF)](https://discord.gg/Mqx7nWYzDF)\n\n## Installation\n\n```bash\ngo get -u github.com/novitalabs/golang-sdk\n```\n\n## Quick Start\n\n**Get api key refer to [https://novita.ai/get-started/](https://novita.ai/get-started/)**\n\n```golang\npackage main\n\nimport (\n\"context\"\n\"fmt\"\n\"time\"\n\n\"github.com/novitalabs/golang-sdk/request\"\n\"github.com/novitalabs/golang-sdk/types\"\n)\n\nfunc main() {\n// Get your API key refer to https://novita.ai/get-started/ .\nconst apiKey = \"Your-API-Key\"\nclient, err := request.NewClient(apiKey)\nif err != nil {\nfmt.Printf(\"new client failed, %v\\n\", err)\nreturn\n}\nctx, cancel := context.WithTimeout(context.Background(), time.Minute*3)\ndefer cancel()\ntxt2ImgReq := types.NewTxt2ImgRequest(\"a dog flying in the sky\", \"\", \"AnythingV5_v5PrtRE.safetensors\")\nres, err := client.SyncTxt2img(ctx, txt2ImgReq,\nrequest.WithSaveImage(\"out\", 0777, func(taskId string, fileIndex int, fileName string) string {\nreturn \"test_txt2img_sync.png\"\n}))\nif err != nil {\nfmt.Printf(\"generate image failed, %v\\n\", err)\nreturn\n}\nfor _, s3Url := range res.Data.Imgs {\nfmt.Printf(\"generate image url: %v\\n\", s3Url)\n}\n}\n```\n\n## Examples\n\n### Txt2Img with LoRA\n\nRefer to [./example/lora/main.go](./example/lora/main.go)\n\n### Model Search\n\nRefer to [./example/model_search/main.go](./example/model_search/main.go)\n\n### ControlNet QRCode\n\nRefer to [./example/qrcode/main.go](./example/qrcode/main.go)\n\n## Testing\n\n```\nAPI_KEY= go test ./...\n```"},{"ref":"P10","kind":"page","title":"novitalabs/python-sdk repository metadata","date":"2026-06-11T04:08:53.991334+00:00","date_source":null,"source_url":"https://github.com/novitalabs/python-sdk","signal_url":null,"signal_json_url":null,"text":"# novitalabs/python-sdk\n\nDescription: Python SDK for Novita AI API (Txt2Img, Img2Img, Txt2Video, Img2Video, Doodle, Remove Background, Replace Object, Reimagine, Merge Faces, ControlNet, VAE, LoRA)\n\nLanguage: Python\n\nLicense: MIT\n\nStars: 27\n\nForks: 8\n\nOpen issues: 0\n\nCreated: 2023-09-27T03:27:34Z\n\nPushed: 2024-11-08T08:50:53Z\n\nDefault branch: main\n\nFork: no\n\nArchived: yes\n\nREADME:\n# Novita AI Python SDK\n\nThis SDK is based on the official [API documentation](https://docs.novita.ai/).\n\n**Join our discord server for help:**\n\n[![](https://dcbadge.vercel.app/api/server/Mqx7nWYzDF)](https://discord.com/invite/Mqx7nWYzDF)\n\n## Installation\n\n```bash\npip install novita-client\n```\n\n## Examples\n\n- [fine tune example](https://colab.research.google.com/drive/1j_ii9TN67nuauvc3PiauwZnC2lT62tGF?usp=sharing)\n- [cleanup](./examples/cleanup.py)\n- [controlnet](./examples/controlnet.py)\n- [img2img](./examples/img2img.py)\n- [img2video](./examples/img2video.py)\n- [inpainting](./examples/inpainting.py)\n- [instantid](./examples/instantid.py)\n- [merge-face](./examples/merge-face.py)\n- [model-search](./examples/model-search.py)\n- [reimagine](./examples/reimagine.py)\n- [remove-background](./examples/remove-background.py)\n- [remove-text](./examples/remove-text.py)\n- [replace-background](./examples/replace-background.py)\n- [txt2img-with-hiresfix](./examples/txt2img-with-hiresfix.py)\n- [txt2img-with-lora](./examples/txt2img-with-lora.py)\n- [txt2img-with-refiner](./examples/txt2img-with-refiner.py)\n- [txt2video](./examples/txt2video.py)\n## Code Examples\n\n### cleanup\n```python\nimport os\n\nfrom novita_client import NovitaClient\nfrom novita_client.utils import base64_to_image\n\nclient = NovitaClient(os.getenv('NOVITA_API_KEY'), os.getenv('NOVITA_API_URI', None))\nres = client.cleanup(\nimage=\"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png\",\nmask=\"https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png\"\n)\n\nbase64_to_image(res.image_file).save(\"./cleanup.png\")\n```\n\n### controlnet\n```python\n#!/usr/bin/env python\n# -*- coding: UTF-8 -*-\n\nimport os\n\nfrom novi"},{"ref":"P11","kind":"page","title":"novitalabs/sd-webui-cleaner repository metadata","date":"2026-06-11T04:08:53.953988+00:00","date_source":null,"source_url":"https://github.com/novitalabs/sd-webui-cleaner","signal_url":null,"signal_json_url":null,"text":"# novitalabs/sd-webui-cleaner\n\nDescription: An extension for stable-diffusion-webui to remove any object.\n\nLanguage: JavaScript\n\nLicense: MIT\n\nStars: 344\n\nForks: 26\n\nOpen issues: 5\n\nCreated: 2023-09-27T03:24:18Z\n\nPushed: 2023-10-24T08:06:37Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Cleaner for Stable Diffusion WebUI\n\n\n\n\n\n\n
\n\n\"Unsplash\"\n\n\nAI image generation API\n
\nNow we have provided the API for remove object. \nCleanup API\n
\n\nThis is a WEBUI extension that provides image erasure functionality. It supports both UI and API simultaneously. Powered by [lama](https://github.com/advimman/lama)\n\n![example1](https://raw.githubusercontent.com/wiki/novitalabs/sd-webui-cleaner/images/example1.png)\n\n
\n\n## Installation\nClone this project in the WEBUI extensions folder\n```\ngit clone https://github.com/novitalabs/sd-webui-cleaner.git\n```\n
\n\n## Get Started\n\nhttps://github.com/novitalabs/sd-webui-cleaner/assets/55743667/3f9f652b-d3b7-4c08-a4c6-0e9fe731c77c\n\n
\n\n### API\n\n```\n//request-----------------------------------\nPOST http://127.0.0.1:7860/cleanup\n\nbody:\n{\n\"input_image\": \"\",\n\"mask\": \"\"\n}\n\n//response-----------------------------------\n{\n\"code\": 0, // 0:success\n\"message\": \"ok\",\n\"image\": \"\"\n}\n```\n\n
\n\n### Used without GPU\nIf you don't have a GPU, please set the cleaner_use_cpu parameter to true through the setting page or api.\n\n
\n\n## Thanks\n- https://github.com/advimman/lama\n- https://github.com/Sanster/lama-cleaner"},{"ref":"P12","kind":"page","title":"novitalabs/javascript-sdk repository metadata","date":"2026-06-11T04:08:53.724925+00:00","date_source":null,"source_url":"https://github.com/novitalabs/javascript-sdk","signal_url":null,"signal_json_url":null,"text":"# novitalabs/javascript-sdk\n\nDescription: JavaScript SDK for Novita AI API (Txt2Img, Img2Img, Txt2Video, Img2Video, Doodle, Remove Background, Replace Object, Reimagine, Merge Faces, ControlNet, VAE, LoRA)\n\nLanguage: TypeScript\n\nStars: 18\n\nForks: 4\n\nOpen issues: 6\n\nCreated: 2023-09-27T15:32:05Z\n\nPushed: 2026-05-27T07:36:41Z\n\nDefault branch: main\n\nFork: no\n\nArchived: yes\n\nREADME:\n\n\n# Novita.ai Javascript SDK\n\nThis SDK is based on the official [novita.ai API reference](https://docs.novita.ai/)\n\n**Join our discord server for help:**\n\n[![](https://dcbadge.vercel.app/api/server/YyPRAzwp7P)](https://discord.gg/YyPRAzwp7P)\n\n## Quick start\n\n1. Sign up on [novita.ai](https://novita.ai) and get an API key. Please follow the instructions at [https://novita.ai/get-started](https://novita.ai/get-started/)\n\n2. Install the [npm package](https://www.npmjs.com/package/novita-sdk) in your project.\n\n```bash\nnpm i novita-sdk\n```\n\n## Version 3.1.0 Update Notes\n\nWe've made significant changes in version 3.0.0. We removed some APIs and will not serve them in the future. The APIs deprecated are:\n\n- adetailer\n- img2mask\n- anymate-anyone\n- create-tile\n- doodle\n- lcm-img2img\n- lcm-txt2img\n- make-photo\n- mix-pose\n- relight\n- remove-watermark\n- replace-sky\n- replace-object\n- upscale\n- img2prompt\n- img2video-motion\n- outpainting\n- reimagine\n- restore-face\n\n## Usage\n\n```javascript\nimport { NovitaSDK } from \"novita-sdk\";\n\nconst novitaClient = new NovitaSDK(\"your api key\");\n\nconst params = {\nrequest: {\nmodel_name: \"majicmixRealistic_v7_134792.safetensors\",\nprompt: \"1girl,sweater,white background\",\nnegative_prompt: \"(worst quality:2),(low quality:2),(normal quality:2),lowres,watermark,\",\nwidth: 512,\nheight: 768,\nsampler_name: \"Euler a\",\nguidance_scale: 7,\nsteps: 20,\nimage_num: 1,\nseed: -1,\n},\n};\nnovitaClient\n.txt2Img(params)\n.then((res) => {\nif (res && res.task_id) {\nconst timer = setInterval(() => {\nnovitaClient\n.progress({\ntask_id: res.task_id,\n})\n.then((progressRes) => {\nif (progressRes.task.status === TaskStatus.SUCCEED) {\nconsole.log(\"finished!\", progressRes.images);\nclearInterval(timer);\nonFinish(progressRes.images);\n}\nif (progressRes.task.status === TaskStatus.FAILED) {\nco"},{"ref":"P13","kind":"page","title":"novitalabs/AnimateAnyone repository metadata","date":"2026-06-11T04:08:53.491211+00:00","date_source":null,"source_url":"https://github.com/novitalabs/AnimateAnyone","signal_url":null,"signal_json_url":null,"text":"# novitalabs/AnimateAnyone\n\nDescription: Unofficial Implementation of Animate Anyone by Novita AI\n\nLanguage: Python\n\nLicense: Apache-2.0\n\nStars: 779\n\nForks: 69\n\nOpen issues: 6\n\nCreated: 2024-05-30T08:09:27Z\n\nPushed: 2026-05-27T06:27:09Z\n\nDefault branch: main\n\nFork: no\n\nArchived: yes\n\nREADME:\n# Animate Anyone\n\n[![Novita AI](https://github.com/novitalabs/AnimateAnyone/assets/4327933/2a6ef880-e5c3-437e-adc5-2ae8601ac4f8)](https://novita.ai)\n\n## Overview\n\nThis repository currently provides the unofficial pre-trained weights and inference code of [Animate Anyone](https://humanaigc.github.io/animate-anyone). It is inspired by the implementation of the [MooreThreads/Moore-AnimateAnyone](https://github.com/MooreThreads/Moore-AnimateAnyone) repository and we made some adjustments to the training process and datasets.\n\n## Samples\n\n\n\n\n\n\n
\n\n## Quickstart\n\n### Build Environtment\n\nWe Recommend a python version `>=3.10` and cuda version `=11.7`. Then build environment as follows:\n\n```shell\n# [Optional] Create a virtual env\npython -m venv .venv\nsource .venv/bin/activate\n# Install with pip:\npip install -r requirements.txt\n```\n\n### Download weights\n\n**Automatically downloading**: You can run the following command to download weights automatically:\n\n```shell\npython tools/download_weights.py\n```\n\nWeights will be placed under the `./pretrained_weights` direcotry. The whole downloading process may take a long time.\n\n### Inference\n\nHere is the cli command for running inference scripts:\n\n```shell\npython -m scripts"},{"ref":"P14","kind":"page","title":"novitalabs/Novita-CollabHub repository metadata","date":"2026-06-11T04:08:53.488714+00:00","date_source":null,"source_url":"https://github.com/novitalabs/Novita-CollabHub","signal_url":null,"signal_json_url":null,"text":"# novitalabs/Novita-CollabHub\n\nStars: 6\n\nForks: 2\n\nOpen issues: 0\n\nCreated: 2024-08-29T08:00:00Z\n\nPushed: 2026-05-08T10:05:37Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n
\n\"Novita\n\n[𝕏 Follow me on X](https://x.com/novita_labs?utm_source=github_collabhub&utm_medium=readme&utm_campaign=collab) • [🤗 Hugging Face](https://huggingface.co/novita?utm_source=github_collabhub&utm_medium=readme&utm_campaign=collab) • [💻 Docs](https://novita.ai/docs/guides/introduction?utm_source=github_collabhub&utm_medium=readme&utm_campaign=collab)\n\n[Novita AI](https://novita.ai?utm_source=github_collabhub&utm_medium=readme&utm_campaign=collab) is an AI cloud platform that helps developers easily deploy AI models through a simple API, backed by affordable and reliable GPU cloud infrastructure.\n
\n\n## **TOP-LLM Integration Repo**\n\nIntegrate the Novita API into popular software and platforms. Access [Novita](https://novita.ai/settings/key-management?utm_source=github_collabhub&utm_medium=readme&utm_campaign=collab) to get an API key.\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
RepoDescriptionGuide
Hugging Face is a library that provides pre-trained language models for NLP tasks. Novita is one of the inference providers of Hugging Face.Novita AI & Hugging Face Integration Guide
LangChain is a framework for developing applications powered by large language models (LLMs).Novita AI & LangChain Integration Gui"},{"ref":"P15","kind":"page","title":"novitalabs/dify-plugin-novita repository metadata","date":"2026-06-11T04:08:53.217279+00:00","date_source":null,"source_url":"https://github.com/novitalabs/dify-plugin-novita","signal_url":null,"signal_json_url":null,"text":"# novitalabs/dify-plugin-novita\n\nLanguage: Python\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2025-08-13T06:40:15Z\n\nPushed: 2026-06-11T03:02:24Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n## Overview\n\n[Novita AI](https://novita.ai/) is an AI cloud platform that helps developers easily deploy AI models through a simple API, backed by affordable and reliable GPU cloud infrastructure.\n\nNovita AI supports various models from DeepSeek, Llama, Qwen, GLM, etc. Check all models [here](https://novita.ai/models/llm).\n\n# Configuration\n\n1. [Create a Novita AI account.](https://novita.ai/user/login)\n2. Create and save your API key [here](https://novita.ai/settings/key-management).\n- Click **Add New Key** to generate a new API Key. Note that the key **will only be displayed once upon generation** — ensure to save it in a safe place.\n![](_assets/novita-02.png)\n\n3. Install the plugin in Dify, access the [Settings] page to enter the API key you just created. \n![](_assets/novita-01.png)\n\n4. Now you can use the Novita AI models in Dify.\n\nSource code of this plugin: [https://github.com/novitalabs/dify-plugin-novita](https://github.com/novitalabs/dify-plugin-novita)"},{"ref":"P16","kind":"page","title":"novitalabs/novita-mcp-server repository metadata","date":"2026-06-11T04:08:53.213138+00:00","date_source":null,"source_url":"https://github.com/novitalabs/novita-mcp-server","signal_url":null,"signal_json_url":null,"text":"# novitalabs/novita-mcp-server\n\nDescription: The Model Context Protocol (MCP) server that provides seamless interaction with Novita AI platform resources\n\nLanguage: JavaScript\n\nLicense: MIT\n\nStars: 11\n\nForks: 9\n\nOpen issues: 3\n\nCreated: 2025-05-06T11:58:54Z\n\nPushed: 2025-05-12T09:53:05Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Novita MCP Server\n[![smithery badge](https://smithery.ai/badge/@novitalabs/novita-mcp-server)](https://smithery.ai/server/@novitalabs/novita-mcp-server)\n\n`novita-mcp-server` is a Model Context Protocol (MCP) server that provides seamless interaction with Novita AI platform resources. We recommend accessing this server through [Claude Desktop](https://claude.ai/download), [Cursor](https://www.cursor.com/), or any other compatible MCP client.\n\n\n\"Novita\n\n\n## Features\n\n> ⚠️ **Beta Notice**: `novita-mcp-server` is currently in beta and only supports GPU instance management. Additional resource types will be supported in future releases.\n\nCurrently, `novita-mcp-server` enables management the resources of [GPU instances product](https://novita.ai/gpus-console). \n\nSupported operations are as follows:\n- Cluster(/Region): List;\n- Product: List;\n- GPU Instance: List, Get, Create, Start, Stop, Delete, Restart;\n- Template: List, Get, Create, Delete;\n- Container Registry Auth: List, Create, Delete;\n- Network Storage: List, Create, Update, Delete;\n\n## Installation\n\nYou can install the package using npm, or Smithery:\n\n**Using npm**\n\n```bash\nnpm install -g @novitalabs/novita-mcp-server\n```\n\n**Using Smithery**\n\nVisit the [https://smithery.ai/server/@novitalabs/novita-mcp-server](https://smithery.ai/server/@novitalabs/novita-mcp-server) and follow the \"Install\" instructions to install the server.\n\n## Configuration to use novita-mcp-server\n\nFirst, you need to get your Novita API key from the [Novita AI Key Management](https://novita.ai/settings/key-management).\n\nAnd next, you can use the following configuration for both Claude Desktop and Cursor:\n"},{"ref":"P17","kind":"page","title":"novitalabs/chatbynovita repository metadata","date":"2026-06-11T04:08:52.152565+00:00","date_source":null,"source_url":"https://github.com/novitalabs/chatbynovita","signal_url":null,"signal_json_url":null,"text":"# novitalabs/chatbynovita\n\nStars: 0\n\nForks: 1\n\nOpen issues: 0\n\nCreated: 2025-08-30T18:22:32Z\n\nPushed: 2025-08-19T10:09:57Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME: none published or not readable through the GitHub API."},{"ref":"P18","kind":"page","title":"novitalabs/autotuner repository metadata","date":"2026-06-11T04:08:51.790688+00:00","date_source":null,"source_url":"https://github.com/novitalabs/autotuner","signal_url":null,"signal_json_url":null,"text":"# novitalabs/autotuner\n\nDescription: Optimize the performance of LLM inference engines by automatically tuning parameters for a specific model.\n\nLanguage: Python\n\nLicense: MIT\n\nStars: 11\n\nForks: 3\n\nOpen issues: 4\n\nCreated: 2025-10-21T11:17:53Z\n\nPushed: 2026-06-10T20:58:22Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# LLM Autotuner (for inference)\n\n

\n\"Autotuner\n

\n\nAutomated parameter tuning for LLM inference engines (SGLang, vLLM) for best performance, while respecting SLOs and hardware constraints.\n\n## Why Autotuner?\n\n**Quantization and parameter tuning can unlock 60%+ performance gains.** LLM inference engines like SGLang and vLLM ship with conservative defaults that work everywhere but are optimized for nowhere.\n\n### Performance Impact: Real-World Data\n\n

\n\"Throughput\n

\n\n

\n\"Latency\n

\n\nTesting on NVIDIA RTX 4090 (24GB) with typical production workloads (mixed prefill/decode).\n\n**See detailed benchmarks:** [Baseline Benchmarks](docs/qwen-benchmarks.md)\n\n| What You Get | Manual Tuning | Autotuner |\n|--------------|---------------|-----------|\n| **Time to optimal config** | Hours to Days | **Minutes** |\n| **Parameter combinations tested** | ~10 (limited by patience) | **50-100+** (automated) |\n| **Performance gain** | Unknown (untested) | **60%+ throughput** (quantization + tuning) |\n| **Reproducibility** | Low (manual errors) | **High** (versioned configs) |\n| **Cross-hardware portability** | Manual rework | **Re-run task** (one command) |\n\n## How to Use\n\n### CLI Mode\n

\n\"CLI\n

\n\n### Web UI Mode\n

\n\"Web\n

\n\n### Agent Mode\n

\n\"Agent\n

\n\n## Core Concepts\n

\n\"Cor"},{"ref":"P19","kind":"page","title":"novitalabs/javascript-sdk\n\n

KV cache on the wings of Pegasus.

\n\n[![CI](https://github.com/novitalabs/pegaflow/actions/workflows/ci.yml/badge.svg)](https://github.com/novitalabs/pegaflow/actions/workflows/ci.yml)\n[![PyPI](https://img.shields.io/pypi/v/pegaflow-llm)](https://pypi.org/project/pegaflow-llm/)\n[![License](https://img.shields.io/badge/license-Apache--2.0-blue)](LICENSE)\n\n\n**PegaFlow is a high-performance KV cache storage engine for LLM inference.** Offload KV cache from GPU to host memory or SSD, and share it across nodes via RDMA.\n\n- **Decoupled from inference lifecycle** — runs as an independent sidecar; KV cache survives engine restarts, scales independently, and is shared across instances\n- **Topology-aware, PCIe-saturating transfers** — NUMA-aware pinned memory + layer-wise DMA to maximize hardware bandwidth\n- **GIL-free Rust core** — zero Python overhead on the hot path; your inference engine keeps its threads\n- **Production-ready observability** — built-in Prometheus metrics and OTLP export, not an afterthought\n- **Pluggable** — works with vLLM as a drop-in KV connector\n\n## News\n\n- **2026-05-18** — [vLLM x Novita AI: PegaFlow for Production-Grade External KV Cache](https://vllm.ai/blog/2026-05-18-pegaflow), a joint blog post with the vLLM team.\n\n## Architecture\n\n
\n\"PegaFlow\n
\n\n## Framework Integration\n\n| Framework | Status | Link |\n|-----------|--------|------|\n| vLLM | ✅ Ready | [Quick Start](#3-launch-your-inference-engine) |\n\n## Quick Start\n\n### 1. Install\n\n```bash\nuv pip install pegaflow-llm # CUDA 12\nuv pip install pegaflow-llm-cu13 # CUDA 13\n```\n\n### 2. Start PegaFlow Server\n\n```bash\npegaflow-server\n```\n\n### 3. 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