{"schema_version":"onlylabs.public_analysis_evidence.v1","title":"Parasail 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/labs/parasail","json_url":"https://onlylabs.fyi/analysis/parasail/evidence.json","generated_at":"2026-06-11T18:06:44.651Z","org":{"slug":"parasail","name":"Parasail","category":"neocloud","category_label":"Neocloud","dossier_url":"https://onlylabs.fyi/labs/parasail"},"analysis":null,"workflow":{"version":"onlylabs-deepagents-analysis-v3","provider":null,"model":null,"agent":null,"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":23,"events":27,"web":0,"evidence":50,"signal_desks":{"hiring":8,"forks":9,"releases":6,"talking":0,"repos":4},"data_radar_lanes":null,"data_radar_matches":null,"stored_analysis_evidence":null,"stored_analysis_web":null,"stored_analysis_signal_desks":null,"stored_analysis_data_radar_lanes":null,"stored_analysis_data_radar_matches":null},"stored_web_provenance":null,"evidence":[{"ref":"P1","kind":"page","title":"Senior Software Engineer, Fullstack","date":"2026-06-11T04:12:51.864814+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/parasail/jobs/5115842008","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior Software Engineer, Fullstack at Parasail \n\nBack to jobs \nSenior Software Engineer, Fullstack\nSF Bay Area (Hybrid)\n\nApply \nParasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.\n\nThe Role \n\nWe’re looking for a Senior Fullstack Engineer who wants to own large surface areas of product from database to pixel. You’ll build the interfaces, APIs, and systems that thousands of AI engineers interact with daily — from our real-time inference dashboard and model deployment console to the orchestration APIs that route workloads across a global GPU network.\n\nThis isn’t a role where you’ll be handed pixel-perfect mocks and asked to implement them. You’ll shape what we build and how it works, collaborating directly with founders and infrastructure engineers to turn complex distributed systems into products that feel simple and fast.\n\nWhat You’ll Build \n\nInference Platform UI: Design and build the dashboards, model deployment workflows, and real-time monitoring views that our customers use to deploy and manage AI workloads at scale.\n\nAPIs & Backend Services: Architect and implement the backend services that power our platform — model serving endpoints, usage metering, billing integrations, authentication, and developer-facing APIs.\n\nOrchestration Interfaces: Build the frontend and API layers on top of our GPU orchestration engine, giving users intuitive control over routing, caching, scaling, and cost optimization across our global network.\n\nDeveloper Experience: Own the end-to-end developer experience including API documentation, SDK design, CLI tools, and onboarding flows that make Parasail the easiest inference platform to adopt.\n\nReal-Time Systems: Implement streaming interfaces (SSE/WebSockets) for real-time inference responses, live cost tracking, and deployment status updates.\n\nData & Analytics: Build internal and customer-facing analytics — usage dashboards, cost "},{"ref":"P2","kind":"page","title":"Product Manager","date":"2026-06-11T04:12:51.731621+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/parasail/jobs/5119678008","signal_url":null,"signal_json_url":null,"text":"Job Application for Product Manager at Parasail \n\nBack to jobs \nProduct Manager\nSan Mateo, CA\n\nApply \nParasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.\n\nWhat You’ll Do \n\nOwn the platform roadmap: Translate the CEO’s high-level strategic vision into a detailed, prioritized product roadmap. Define what gets built, when, and why – spanning billing, pricing, access control, endpoints, metrics, observability, and account management.\n\nDrive 0-to-1 product development: Lead the design and launch of new product lines including seamless custom model hosting, agentic workflow support, voice agent infrastructure, and enterprise management capabilities.\n\nBuild a best-in-class developer experience: Ensure every API, dashboard, and workflow is fast, intuitive, and delightful. Set the bar at “customers get set up on their first call” – speed and responsiveness are superpowers.\n\nBring structure and discipline: Establish the product planning processes, prioritization frameworks, and cross-functional coordination that a rapidly scaling company needs. Rally engineering and design around what matters most.\n\nEvolve the product portfolio: Continue refining and expanding Parasail’s core offerings – dedicated nodes, serverless inference, and dedicated serverless – based on deep customer insight and competitive intelligence.\n\nBe a customer-obsessed product leader: Engage directly with customers, incorporate feedback rapidly, and ensure product decisions are grounded in real-world production needs.\n\nWho You Are \n\nMust-Haves \n\nFocused, prioritized, and organized. You bring clarity to ambiguity. You know what matters, you say no to what doesn’t, and you follow through on commitments. You don’t spread like liquid.\n\nStructured product leader. You bring rigorous planning, process, and frameworks to complement a visionary founder. You turn instinct and context into actionable roadmaps.\n\nPlatform and developer"},{"ref":"P3","kind":"page","title":"Senior Software Engineer, LLM Performance","date":"2026-06-11T04:12:51.692637+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/parasail/jobs/5107617008","signal_url":null,"signal_json_url":null,"text":"Jobs at Parasail \n\nCurrent openings at Parasail\n\nCreate a Job Alert\nLevel-up your career by having opportunities at Parasail sent directly to your inbox.\nCreate alert \n\nSearch \n\n7 jobs\nCommercial\nJob\n\nAccount Executive\nSF Bay Area (Hybrid)\n\nHead of Developer Relations\nSF Bay Area (Hybrid)\n\nProduct Manager\nSan Mateo, CA\n\nEngineering\nJob\n\nExpression of Interest\nSF Bay Area (Hybrid)\n\nSenior AI Engineer\nSF Bay Area (Hybrid)\n\nSenior Software Engineer, Distributed Systems\nSF Bay Area (Hybrid)\n\nSenior Software Engineer, Fullstack\nSF Bay Area (Hybrid)"},{"ref":"P4","kind":"page","title":"Senior AI Engineer","date":"2026-06-11T04:12:51.62803+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/parasail/jobs/5107916008","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior AI Engineer at Parasail \n\nBack to jobs \nSenior AI Engineer\nSF Bay Area (Hybrid)\n\nApply \nParasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.\n\nWe move fast, stay close to our customers, and ship products that make a real difference for AI developers. This role is part of that mission.\n\nAbout the Role \n\nWe’re looking for a hungry, creative engineer who thrives in a high-trust, high-velocity environment. You’ll be the one taking bold ideas—from voice and real-time AI to new LLM-driven features—and turning them into working prototypes in days. You’ll operate inside our product and engineering organization, collaborating directly with the team to ensure what you build is not just exciting, but also aligns with our long-term architecture and customer needs.\n\nThis is an engineering role through and through, but with the freedom to explore, test, and build at startup speed.\n\nResponsibilities \n\nRapidly prototype AI-powered workflows and tools, incorporating LLMs, embeddings, real-time audio/voice, API integrations, and prompt engineering\n\nLead experimental build cycles from hypothesis to working proof-of-concept to actionable insights\n\nCollaborate closely with product and engineering to translate prototypes into viable product features\n\nEnsure alignment with platform architecture; seek guidance before integrating prototypes into production systems\n\nNavigate open-ended engineering problems with creative, experimental solutions\n\nShare learnings and code artifacts to accelerate team-wide innovation\n\nWhat You Bring \n\nProficiency in Python and/or JavaScript/TypeScript and ability to quickly learn new tools and frameworks\n\nHands-on experience with AI systems including LLMs, API-based embeddings, vector DBs, and real-time pipelines (e.g., audio/STT-TTS)\n\nA bias toward action—you build, ship, iterate, and learn\n\nDemonstrated creativity: thinking in prototypes, not decks\n"},{"ref":"P5","kind":"page","title":"Senior Software Engineer, Distributed Systems","date":"2026-06-11T04:12:51.47429+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/parasail/jobs/5107876008","signal_url":null,"signal_json_url":null,"text":"Job Application for Senior Software Engineer, Distributed Systems at Parasail \n\nBack to jobs \nSenior Software Engineer, Distributed Systems\nSF Bay Area (Hybrid)\n\nApply \nParasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.\n\nJob Description \n\nThe Senior Software Engineer, Distributed Systems role at Parasail is crucial for ensuring the seamless deployment, scalability, and security of our AI platform. This position is tailored for individuals passionate about creating robust infrastructures that support complex AI workloads, with a strong emphasis on cloud compatibility, security, ease of use, and cost savings. You will work closely with AI-focused performance and solutions engineering teams, facilitating the orchestration of resources needed for high-performing AI applications, all while ensuring our infrastructure adheres to the highest standards of security and data privacy.\n\nTechnical Abilities \n\nMicroservice Architecture: Deep understanding of distributed application design patterns, service decomposition, and inter-service communication. Experience in building scalable and maintainable microservice-based systems.\n\nBackend Development: Strong foundation in storage solutions and networking protocols. Ability to design and implement robust backend systems with optimized data management and network communication.\n\nProgramming Languages & Frameworks: Extensive experience with Java, Spring Boot, and Golang. Proficiency in developing enterprise-grade applications using modern development frameworks and tools.\n\nDistributed Systems: Deep knowledge of distributed computing principles, including consistency models, fault tolerance, and scalability patterns. Experience in designing and maintaining large-scale distributed applications.\n\nCloud-Native Technologies: Proficiency in cloud platforms and Infrastructure as Code (IaC). Experience with containerization, orchestration, and automated "},{"ref":"P6","kind":"page","title":"Head of Developer Relations","date":"2026-06-11T04:12:51.456752+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/parasail/jobs/5210676008","signal_url":null,"signal_json_url":null,"text":"Job Application for Head of Developer Relations at Parasail \n\nBack to jobs \nHead of Developer Relations\nSF Bay Area (Hybrid)\n\nApply \nParasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.\n\nParasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.\n\nAbout the Role\n\nThis is an experienced individual contributor role and our first dedicated developer-facing hire. You'll write the technical thought leadership content, developer documentation, and performance benchmarks that show how Parasail performs and why it's built the way it is. You'll grow our presence in the communities developers already inhabit and bring what you hear back into engineering, product, and GTM. You'll work alongside our CEO's founder platform, with content and community efforts that amplify each other rather than compete.\n\nWhat you'll do\n\nTechnical content and developer documentation are the core focus. Community presence and events grow from that foundation.\n\nOwn developer-facing education and build developer trust. Own developer documentation and educational content, including tutorials, guides, demos, and long-form technical content (deep dives, benchmarks, visual essays) that establishes Parasail as a thought leader in inference. Partner closely with engineering and product on in-product DX and activation.\n\nGrow a thriving developer community . Grow Parasail's developer community through consistent, high-quality touchpoints, including Discord, regular office hours, and an active presence in external communities (r/LocalLLaMA, Hacker News, target external Discords). Synthesize what you hear into a feedback loop that shapes engineering,"},{"ref":"P7","kind":"page","title":"Account Executive","date":"2026-06-11T04:12:51.34842+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/parasail/jobs/5121414008","signal_url":null,"signal_json_url":null,"text":"Job Application for Account Executive at Parasail \n\nBack to jobs \nAccount Executive\nSF Bay Area (Hybrid)\n\nApply \nParasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.\n\nAt Parasail, we are redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience; free from vendor lock-in and designed for the next generation of AI workloads.\n\nWe’re a small team that ships quickly, obsesses over performance, and works side-by-side with customers to help them succeed.\n\nThe Role \n\nWe’re hiring our first Account Executives to partner directly with our founders and establish Parasail’s go-to-market motion from zero.\n\nYou’ll be running discovery, building pipeline, delivering technical demos, handling objections live, and closing our first customers. You’ll also help shape how we sell, from messaging, to process, to early GTM playbooks.\n\nBecause we’re early stage, this role is hands-on and broad. You’ll lead everything from outbound prospecting and first calls, to POCs and onboarding, to building feedback loops with product and engineering.\n\nWhat You’ll Do \n\nBuild pipeline from scratch — Prospect, qualify, and drive new opportunities into the funnel.\n\nOwn the sales cycle end-to-end — Discovery, technical validation, negotiation, and close.\n\nRun high-impact demos — Tailor demos and POCs to customer use cases; credibly speak to infra, APIs, and performance.\n\nHandle technical objections — Partner with engineering as needed, but be able to stand on your own with CTOs and dev teams.\n\nDefine the playbook — Work with founders to codify what works, refine messaging, and build repeatable processes.\n\nGuide onboarding — Ensure first customers integrate smoothly and hit early milestones.\n\nClose the feedback loop — Surface custome"},{"ref":"P8","kind":"page","title":"Expression of Interest","date":"2026-06-11T04:12:51.324434+00:00","date_source":null,"source_url":"https://job-boards.greenhouse.io/parasail/jobs/4092794008","signal_url":null,"signal_json_url":null,"text":"Job Application for Expression of Interest at Parasail \n\nBack to jobs \nExpression of Interest\nSF Bay Area (Hybrid)\n\nApply \nParasail is redefining AI infrastructure by enabling seamless deployment across a distributed network of GPUs, optimizing for cost, performance, and flexibility. Our mission is to empower AI developers with a fast, cost-efficient, and scalable cloud experience—free from vendor lock-in and designed for the next generation of AI workloads.\n\nCreate a Job Alert\nInterested in building your career at Parasail? Get future opportunities sent straight to your email.\nCreate alert \n\nApply for this job\n\n*\n\nindicates a required field\n\nQuick Apply with MyGreenhouse \n\nFirst Name * \n\nLast Name * \n\nEmail * \n\nPhone Country \n\nPhone \n\nResume/CV * \nAttach Attach \n\nDropbox \nGoogle Drive \nEnter manually Enter manually \n\nAccepted file types: pdf, doc, docx, txt, rtf\n\nCover Letter\nAttach Attach \n\nDropbox \nGoogle Drive \nEnter manually Enter manually \n\nAccepted file types: pdf, doc, docx, txt, rtf\n\nLinkedIn Profile \n\nWebsite \n\nWhat inspires you at work? * \n\nTell us about an achievement you are especially proud of. * \n\nWhat is your interest in joining Parasail, and what role would you like to serve in? * \n\nAnything else you&#x27;d like to share with us. * \n\nVoluntary Self-Identification\n\nFor government reporting purposes, we ask candidates to respond to the below self-identification survey.\nCompletion of the form is entirely voluntary. Whatever your decision, it will not be considered in the hiring\nprocess or thereafter. Any information that you do provide will be recorded and maintained in a\nconfidential file.\n\nAs set forth in Parasail’s Equal Employment Opportunity policy,\nwe do not discriminate on the basis of any protected group status under any applicable law.\n\nGender Select...\n\nAre you Hispanic/Latino? Select...\n\nRace & Ethnicity Definitions \n\nIf you believe you belong to any of the categories of protected veterans listed below, please indicate by making the appropriate selection.\nAs a government contractor subject to the Vietnam Era Veterans Readjustment Assistance Act (VEVRAA), we request this information in order to measure\nthe effectiveness of the outreach an"},{"ref":"P9","kind":"page","title":"parasail-ai/openai-batch repository metadata","date":"2026-06-11T04:09:58.931989+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/openai-batch","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/openai-batch\n\nDescription: Make OpenAI batch easy to use.\n\nLanguage: Python\n\nLicense: Apache-2.0\n\nStars: 8\n\nForks: 1\n\nOpen issues: 2\n\nCreated: 2024-11-11T23:44:07Z\n\nPushed: 2026-02-23T05:22:36Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n[![Tests](https://github.com/parasail-ai/openai-batch/actions/workflows/tests.yml/badge.svg)](https://github.com/parasail-ai/openai-batch/actions/workflows/tests.yml)\n[![PyPI - Version](https://img.shields.io/pypi/v/openai-batch)](https://pypi.org/project/openai-batch/)\n\n# openai-batch\n\nBatch inferencing is an easy and inexpensive way to process thousands or millions of LLM inferences.\n\nThe process is:\n1. Write inferencing requests to an input file\n2. start a batch job\n3. wait for it to finish\n4. download the output\n\nThis library aims to make these steps easier. The OpenAI protocol is relatively easy to use, but it has a lot of boilerplate steps. This library automates those.\n\n#### Supported Providers\n\n* [OpenAI](https://openai.com/) - ChatGPT, GPT4o, etc.\n* [Parasail](https://parasail.io/) - Most transformer models on HuggingFace, such as LLama, Qwen, LLava, etc.\n\n## Direct Library Usage\n\nYou can also use the library directly in your Python code for more control over the batch processing workflow.\n\n### Basic Usage\n\n```python\nimport random\nfrom openai_batch import Batch\n\n# Create a batch with random prompts\nwith Batch() as batch:\nobjects = [\"cat\", \"robot\", \"coffee mug\", \"spaceship\", \"banana\"]\nfor i in range(100):\nbatch.add_to_batch(\nmodel=\"meta-llama/Meta-Llama-3-8B-Instruct\",\ntemperature=0.7,\nmax_completion_tokens=1000,\nmessages=[{\"role\": \"user\", \"content\": f\"Tell me a joke about a {random.choice(objects)}\"}]\n)\n\n# Submit, wait for completion, and download results\nresult, output_path, error_path = batch.submit_wait_download()\nprint(f\"Batch completed with status {result.status} and stored in {output_path}\")\n```\n\n`batch.add_to_batch` accepts the same format as `chat.completion.create` in OpenAI's Python library, so any chat completion parameters can be included. Parasail supports most transformers on HuggingFace (TODO: link), while OpenAI supports all of their serverless models. \n\nYou can also create embed"},{"ref":"P10","kind":"page","title":"parasail-ai/cookbook repository metadata","date":"2026-06-11T04:09:58.743384+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/cookbook","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/cookbook\n\nLanguage: Jupyter Notebook\n\nLicense: Apache-2.0\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2024-10-07T17:55:46Z\n\nPushed: 2025-03-31T17:46:51Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME: none published or not readable through the GitHub API."},{"ref":"P11","kind":"page","title":"parasail-ai/ocr_pipeline repository metadata","date":"2026-06-11T04:09:58.640117+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/ocr_pipeline","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/ocr_pipeline\n\nLanguage: Python\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2025-11-01T17:16:04Z\n\nPushed: 2025-11-11T17:35:28Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Parasail OCR Pipeline\n\nFastAPI-based web application for ingesting contract documents, storing them in Azure Blob Storage, and orchestrating OCR extraction and schema management. Designed to align with Material Design 3 principles and deploy to Azure App Service.\n\n## Features\n\n- Upload contracts via Material 3-inspired interface with real-time status updates.\n- Persist file metadata and processing status in PostgreSQL (Azure Database for PostgreSQL).\n- Store raw documents in Azure Blob Storage with background Docling extraction scaffolding.\n- Parasail OCR integration wired for OpenAI-compatible API key usage with selectable models.\n- Persist OCR text fragments and classification suggestions for each document.\n- Schema builder API and UI for defining reusable key-value mappings and reapplying them to documents.\n- Automatic document-type heuristics suggest schemas and fields when none is selected.\n- Swagger/OpenAPI documentation automatically exposed at `/docs` and compatible with Scalar.\n- GitHub Actions workflow for CI/CD into Azure App Service.\n\n## Local Development\n\n1. **Install dependencies**\n```bash\npython -m venv .venv\nsource .venv/bin/activate\npip install --upgrade pip\npip install -r requirements.txt\n# Optional Docling integration\npip install 'docling>=0.6.0'\n```\n\n2. **Configure environment**\n- Copy `.env.example` to `.env` and update values, including:\n- `APP_DATABASE_URL`\n- `APP_PARASAIL_API_KEY`\n- `APP_AZURE_STORAGE_CONNECTION_STRING` *or* `APP_AZURE_STORAGE_ACCOUNT_URL`\n\n3. **Initialize database schema**\n```bash\npython app/db/init_db.py\n```\n\n4. **Run the API**\n```bash\nuvicorn app.main:app --reload\n```\n\n5. **Open the UI**\n- Navigate to `http://localhost:8000/` for the Material 3 front end.\n- API docs available at `http://localhost:8000/docs` or compatible with [Scalar](https://scalar.com/).\n- The `Documents` section shows current uploads, while the `Document History` table surfaces prior ingests along with detected types and schema selections.\n\n## Project St"},{"ref":"P12","kind":"page","title":"parasail-ai/openai-batch v0.3","date":"2026-06-11T04:05:58.628063+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/openai-batch/releases/tag/v0.3","signal_url":null,"signal_json_url":null,"text":"# v0.3\n\nRepository: parasail-ai/openai-batch\n\nTag: v0.3\n\nPublished: 2025-04-08T07:20:54Z\n\nPrerelease: no\n\nRelease notes:\n## What's Changed\n* Reranker support via '/v1/score' endpoint by @mbhenry in https://github.com/parasail-ai/openai-batch/pull/5\n\n**Full Changelog**: https://github.com/parasail-ai/openai-batch/compare/v0.2.2...v0.3"},{"ref":"P13","kind":"page","title":"parasail-ai/openai-batch v0.3.1","date":"2026-06-11T04:05:58.600168+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/openai-batch/releases/tag/v0.3.1","signal_url":null,"signal_json_url":null,"text":"# v0.3.1\n\nRepository: parasail-ai/openai-batch\n\nTag: v0.3.1\n\nPublished: 2025-06-13T06:56:24Z\n\nPrerelease: no\n\nRelease notes:\n## What's Changed\n* Added support for transfusion models (specifically OmniGen) by @mbhenry in https://github.com/parasail-ai/openai-batch/pull/6\n\n**Full Changelog**: https://github.com/parasail-ai/openai-batch/compare/v0.3...v0.3.1"},{"ref":"P14","kind":"page","title":"parasail-ai/openai-batch v0.3.2","date":"2026-06-11T04:05:58.56034+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/openai-batch/releases/tag/v0.3.2","signal_url":null,"signal_json_url":null,"text":"# v0.3.2\n\nRepository: parasail-ai/openai-batch\n\nTag: v0.3.2\n\nPublished: 2025-07-23T18:24:46Z\n\nPrerelease: no\n\nRelease notes:\n## What's Changed\n* Pass extra transfusion params by @pooyadavoodi in https://github.com/parasail-ai/openai-batch/pull/8\n\n## New Contributors\n* @pooyadavoodi made their first contribution in https://github.com/parasail-ai/openai-batch/pull/8\n\n**Full Changelog**: https://github.com/parasail-ai/openai-batch/compare/v0.3.1...v0.3.2"},{"ref":"P15","kind":"page","title":"parasail-ai/openai-batch v0.3.3","date":"2026-06-11T04:05:58.449275+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/openai-batch/releases/tag/v0.3.3","signal_url":null,"signal_json_url":null,"text":"# v0.3.3\n\nRepository: parasail-ai/openai-batch\n\nTag: v0.3.3\n\nPublished: 2025-11-12T01:10:02Z\n\nPrerelease: no\n\nRelease notes:\n## What's Changed\n* Bump actions/checkout from 4 to 5 by @dependabot[bot] in https://github.com/parasail-ai/openai-batch/pull/9\n* Bump actions/setup-python from 5 to 6 by @dependabot[bot] in https://github.com/parasail-ai/openai-batch/pull/11\n* Add data_url utility method by @alugowski in https://github.com/parasail-ai/openai-batch/pull/12\n* Add image understanding example by @alugowski in https://github.com/parasail-ai/openai-batch/pull/13\n\n## New Contributors\n* @dependabot[bot] made their first contribution in https://github.com/parasail-ai/openai-batch/pull/9\n\n**Full Changelog**: https://github.com/parasail-ai/openai-batch/compare/v0.3.2...v0.3.3"},{"ref":"P16","kind":"page","title":"parasail-ai/openai-batch v0.3.4","date":"2026-06-11T04:05:58.199989+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/openai-batch/releases/tag/v0.3.4","signal_url":null,"signal_json_url":null,"text":"# v0.3.4\n\nRepository: parasail-ai/openai-batch\n\nTag: v0.3.4\n\nPublished: 2025-11-12T01:58:56Z\n\nPrerelease: no\n\nRelease notes:\n## What's Changed\n* Exclude example files from wheel by @alugowski in https://github.com/parasail-ai/openai-batch/pull/14\n* Switch to SPDX license declaration by @alugowski in https://github.com/parasail-ai/openai-batch/pull/15\n* Clean up lint by @alugowski in https://github.com/parasail-ai/openai-batch/pull/16\n* Fix handling of TextIOWrapper inputs by @alugowski in https://github.com/parasail-ai/openai-batch/pull/17\n\n**Full Changelog**: https://github.com/parasail-ai/openai-batch/compare/v0.3.3...v0.3.4"},{"ref":"P17","kind":"page","title":"parasail-ai/vllm-public repository metadata","date":"2026-06-11T03:02:27.741+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/vllm-public","signal_url":null,"signal_json_url":null,"text":"# Repository: parasail-ai/vllm-public (fork of [vllm-project/vllm](https://github.com/vllm-project/vllm))\n\nA high-throughput and memory-efficient inference and serving engine for LLMs\n\n- Stars: 0\n- Forks: 0\n- Watchers: 0\n- Open issues: 0\n- Primary language: Python\n- Languages: Python (80.0%), Cuda (14.9%), C++ (2.9%), C (0.9%), Shell (0.9%), CMake (0.3%), Dockerfile (0.1%)\n- License: Apache License 2.0 (Apache-2.0)\n- Default branch: main\n- Homepage: https://docs.vllm.ai\n- Created: 2024-04-23T18:46:20Z\n- Last push: 2024-09-01T03:35:29Z\n- Contributors: 460 (top: WoosukKwon, youkaichao, zhuohan123, simon-mo, DarkLight1337, Yard1, mgoin, njhill, robertgshaw2-redhat, ywang96)\n\n---\n\nEasy, fast, and cheap LLM serving for everyone\n\n| Documentation | Blog | Paper | Discord | Twitter/X |\n\n---\n\n**vLLM & NVIDIA Triton User Meetup (Monday, September 9, 5pm-9pm PT) at Fort Mason, San Francisco**\n\nWe are excited to announce our sixth vLLM Meetup, in collaboration with NVIDIA Triton Team.\nJoin us to hear the vLLM's recent update about performance.\nRegister now [here](https://lu.ma/87q3nvnh) and be part of the event!\n\n---\n\n*Latest News* 🔥\n\n- [2024/07] We hosted [the fifth vLLM meetup](https://lu.ma/lp0gyjqr) with AWS! Please find the meetup slides [here](https://docs.google.com/presentation/d/1RgUD8aCfcHocghoP3zmXzck9vX3RCI9yfUAB2Bbcl4Y/edit?usp=sharing).\n- [2024/07] In partnership with Meta, vLLM officially supports Llama 3.1 with FP8 quantization and pipeline parallelism! Please check out our blog post [here](https://blog.vllm.ai/2024/07/23/llama31.html).\n- [2024/06] We hosted [the fourth vLLM meetup](https://lu.ma/agivllm) with Cloudflare and BentoML! Please find the meetup slides [here](https://docs.google.com/presentation/d/1iJ8o7V2bQEi0BFEljLTwc5G1S10_Rhv3beed5oB0NJ4/edit?usp=sharing).\n- [2024/04] We hosted [the third vLLM meetup](https://robloxandvllmmeetup2024.splashthat.com/) with Roblox! Please find the meetup slides [here](https://docs.google.com/presentation/d/1A--47JAK4BJ39t954HyTkvtfwn0fkqtsL8NGFuslReM/edit?usp=sharing).\n- [2024/01] We hosted [the second vLLM meetup](https://lu.ma/ygxbpzhl) with IBM! Please find the meetup slides [here](https://docs.google.com/pre"},{"ref":"P18","kind":"page","title":"parasail-ai/loki repository metadata","date":"2026-06-11T03:02:10.356874+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/loki","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/loki\n\nDescription: Like Prometheus, but for logs.\n\nLicense: AGPL-3.0\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2024-06-19T00:12:48Z\n\nPushed: 2024-06-18T23:15:08Z\n\nDefault branch: main\n\nFork: yes\n\nParent repository: grafana/loki\n\nArchived: no\n\nREADME:\n<p align=\"center\"><img src=\"docs/sources/logo_and_name.png\" alt=\"Loki Logo\"></p>\n\n<a href=\"https://drone.grafana.net/grafana/loki\"><img src=\"https://drone.grafana.net/api/badges/grafana/loki/status.svg\" alt=\"Drone CI\" /></a>\n<a href=\"https://goreportcard.com/report/github.com/grafana/loki\"><img src=\"https://goreportcard.com/badge/github.com/grafana/loki\" alt=\"Go Report Card\" /></a>\n<a href=\"https://slack.grafana.com/\"><img src=\"https://img.shields.io/badge/join%20slack-%23loki-brightgreen.svg\" alt=\"Slack\" /></a>\n[![Fuzzing Status](https://oss-fuzz-build-logs.storage.googleapis.com/badges/loki.svg)](https://bugs.chromium.org/p/oss-fuzz/issues/list?sort=-opened&can=1&q=proj:loki)\n\n# Loki: like Prometheus, but for logs.\n\nLoki is a horizontally-scalable, highly-available, multi-tenant log aggregation system inspired by [Prometheus](https://prometheus.io/).\nIt is designed to be very cost effective and easy to operate.\nIt does not index the contents of the logs, but rather a set of labels for each log stream.\n\nCompared to other log aggregation systems, Loki:\n\n- does not do full text indexing on logs. By storing compressed, unstructured logs and only indexing metadata, Loki is simpler to operate and cheaper to run.\n- indexes and groups log streams using the same labels you’re already using with Prometheus, enabling you to seamlessly switch between metrics and logs using the same labels that you’re already using with Prometheus.\n- is an especially good fit for storing [Kubernetes](https://kubernetes.io/) Pod logs. Metadata such as Pod labels is automatically scraped and indexed.\n- has native support in Grafana (needs Grafana v6.0).\n\nA Loki-based logging stack consists of 3 components:\n\n- `promtail` is the agent, responsible for gathering logs and sending them to Loki.\n- `loki` is the main server, responsible for storing logs and processing queries.\n- [Grafana](https://github.com/grafana/grafana) for queryi"},{"ref":"P19","kind":"page","title":"parasail-ai/torchtitan repository metadata","date":"2026-06-11T03:02:10.045519+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/torchtitan","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/torchtitan\n\nDescription: A native PyTorch Library for large model training\n\nLanguage: Python\n\nLicense: BSD-3-Clause\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2024-06-27T22:34:25Z\n\nPushed: 2024-07-03T20:03:32Z\n\nDefault branch: main\n\nFork: yes\n\nParent repository: pytorch/torchtitan\n\nArchived: no\n\nREADME:\n[![4 GPU Integration Test](https://github.com/pytorch/torchtitan/actions/workflows/integration_test_4gpu.yaml/badge.svg?branch=main)](https://github.com/pytorch/torchtitan/actions/workflows/integration_test_4gpu.yaml?query=branch%3Amain)\n[![8 GPU Integration Test](https://github.com/pytorch/torchtitan/actions/workflows/integration_test_8gpu.yaml/badge.svg?branch=main)](https://github.com/pytorch/torchtitan/actions/workflows/integration_test_8gpu.yaml?query=branch%3Amain)\n\n# torchtitan\n\n`torchtitan` is currently in a pre-release state and under extensive development.\n\n`torchtitan` is a proof-of-concept for Large-scale LLM training using native PyTorch. It is (and will continue to be) a repo to showcase PyTorch's latest distributed training features in a clean, minimal codebase. torchtitan is complementary to and not a replacement for any of the great large-scale LLM training codebases such as Megatron, Megablocks, LLM Foundry, Deepspeed, etc. Instead, we hope that the features showcased in torchtitan will be adopted by these codebases quickly. torchtitan is unlikely to ever grow a large community around it.\n\nOur guiding principles when building `torchtitan`:\n\n* Designed to be easy to understand, use and extend for different training purposes.\n* Minimal changes to the model code when applying 1D, 2D, or (soon) 3D Parallel.\n* Modular components instead of a monolithic codebase.\n* Get started in minutes, not hours!\n\n### Intro video - learn more about torchtitan in under 4 mins:\n\n[![Welcome to torchtitan!](assets/images/titan_play_video.png)](https://youtu.be/ee5DOEqD35I?si=_B94PbVv0V5ZnNKE \"Welcome to torchtitan!\")\n\n## Pre-Release Updates:\n#### (4/25/2024): `torchtitan` is now public but in a pre-release state and under development.\nCurrently we showcase pre-training **Llama 3 and Llama 2** LLMs of various sizes from scratch. `torchtitan` is tested a"},{"ref":"P20","kind":"page","title":"parasail-ai/VLMEvalKit repository metadata","date":"2026-06-11T02:54:29.019502+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/VLMEvalKit","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/VLMEvalKit\n\nDescription: Open-source evaluation toolkit of large vision-language models (LVLMs), support 160+ VLMs, 50+ benchmarks\n\nLicense: Apache-2.0\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2024-12-29T22:26:39Z\n\nPushed: 2024-12-29T22:30:58Z\n\nDefault branch: main\n\nFork: yes\n\nParent repository: open-compass/VLMEvalKit\n\nArchived: no\n\nREADME:\n![LOGO](http://opencompass.openxlab.space/utils/MMLB.jpg)\n\n<b>A Toolkit for Evaluating Large Vision-Language Models. </b>\n\n[![][github-contributors-shield]][github-contributors-link] • [![][github-forks-shield]][github-forks-link] • [![][github-stars-shield]][github-stars-link] • [![][github-issues-shield]][github-issues-link] • [![][github-license-shield]][github-license-link]\n\nEnglish | [简体中文](/docs/zh-CN/README_zh-CN.md) | [日本語](/docs/ja/README_ja.md)\n\n<a href=\"https://rank.opencompass.org.cn/leaderboard-multimodal\">🏆 OC Learderboard </a> •\n<a href=\"#%EF%B8%8F-quickstart\">🏗️Quickstart </a> •\n<a href=\"#-datasets-models-and-evaluation-results\">📊Datasets & Models </a> •\n<a href=\"#%EF%B8%8F-development-guide\">🛠️Development </a> •\n<a href=\"#-the-goal-of-vlmevalkit\">🎯Goal </a> •\n<a href=\"#%EF%B8%8F-citation\">🖊️Citation </a>\n\n<a href=\"https://huggingface.co/spaces/opencompass/open_vlm_leaderboard\">🤗 HF Leaderboard</a> •\n<a href=\"https://huggingface.co/datasets/VLMEval/OpenVLMRecords\">🤗 Evaluation Records</a> •\n<a href=\"https://huggingface.co/spaces/opencompass/openvlm_video_leaderboard\">🤗 HF Video Leaderboard</a> •\n<a href=\"https://discord.gg/evDT4GZmxN\">🔊 Discord</a> •\n<a href=\"https://www.arxiv.org/abs/2407.11691\">📝 Report</a>\n</div>\n\n**VLMEvalKit** (the python package name is **vlmeval**) is an **open-source evaluation toolkit** of **large vision-language models (LVLMs)**. It enables **one-command evaluation** of LVLMs on various benchmarks, without the heavy workload of data preparation under multiple repositories. In VLMEvalKit, we adopt **generation-based evaluation** for all LVLMs, and provide the evaluation results obtained with both **exact matching** and **LLM-based answer extraction**.\n\n## 🆕 News\n\n> We have presented a [**comprehensive survey**](https://arxiv.org/pdf/2411.15296) on the e"},{"ref":"P21","kind":"page","title":"parasail-ai/traefik-forward-auth repository metadata","date":"2026-06-11T02:54:21.052466+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/traefik-forward-auth","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/traefik-forward-auth\n\nDescription: Minimal forward authentication service that provides Google/OpenID oauth based login and authentication for the traefik reverse proxy\n\nLicense: MIT\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2025-03-05T19:25:21Z\n\nPushed: 2024-08-15T06:30:48Z\n\nDefault branch: master\n\nFork: yes\n\nParent repository: thomseddon/traefik-forward-auth\n\nArchived: no\n\nREADME:\n# Traefik Forward Auth ![Build Status](https://img.shields.io/github/workflow/status/thomseddon/traefik-forward-auth/CI) [![Go Report Card](https://goreportcard.com/badge/github.com/thomseddon/traefik-forward-auth)](https://goreportcard.com/report/github.com/thomseddon/traefik-forward-auth) ![Docker Pulls](https://img.shields.io/docker/pulls/thomseddon/traefik-forward-auth.svg) [![GitHub release](https://img.shields.io/github/release/thomseddon/traefik-forward-auth.svg)](https://GitHub.com/thomseddon/traefik-forward-auth/releases/)\n\nA minimal forward authentication service that provides OAuth/SSO login and authentication for the [traefik](https://github.com/containous/traefik) reverse proxy/load balancer.\n\n## Why?\n\n- Seamlessly overlays any http service with a single endpoint (see: `url-path` in [Configuration](#configuration))\n- Supports multiple providers including Google and OpenID Connect (supported by Azure, Github, Salesforce etc.)\n- Supports multiple domains/subdomains by dynamically generating redirect_uri's\n- Allows authentication to be selectively applied/bypassed based on request parameters (see `rules` in [Configuration](#configuration))\n- Supports use of centralised authentication host/redirect_uri (see `auth-host` in [Configuration](#configuration))\n- Allows authentication to persist across multiple domains (see [Cookie Domains](#cookie-domains))\n- Supports extended authentication beyond Google token lifetime (see: `lifetime` in [Configuration](#configuration))\n\n# Contents\n\n- [Releases](#releases)\n- [Usage](#usage)\n- [Simple](#simple)\n- [Advanced](#advanced)\n- [Provider Setup](#provider-setup)\n- [Configuration](#configuration)\n- [Overview](#overview)\n- [Option Details](#option-details)\n- [Concepts](#concepts)\n- [Forwarded Headers](#forwarded-headers)\n-"},{"ref":"P22","kind":"page","title":"parasail-ai/curator repository metadata","date":"2026-06-11T02:54:13.542162+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/curator","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/curator\n\nDescription: Synthetic data curation for post-training and structured data extraction\n\nLanguage: Python\n\nLicense: Apache-2.0\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2025-05-07T17:46:19Z\n\nPushed: 2026-06-09T23:29:49Z\n\nDefault branch: main\n\nFork: yes\n\nParent repository: bespokelabsai/curator\n\nArchived: no\n\nREADME:\n<p align=\"center\">\n<a href=\"https://bespokelabs.ai/\" target=\"_blank\">\n<picture>\n<source media=\"(prefers-color-scheme: light)\" width=\"100px\" srcset=\"https://github.com/bespokelabsai/curator/blob/main/docs/Bespoke-Labs-Logomark-Red-crop.png\">\n<img alt=\"Bespoke Labs Logo\" width=\"100px\" src=\"https://github.com/bespokelabsai/curator/blob/main/docs/Bespoke-Labs-Logomark-Red-crop.png\">\n</picture>\n</a>\n</p>\n\n<h1 align=\"center\">Bespoke Curator</h1>\n<h3 align=\"center\" style=\"font-size: 20px; margin-bottom: 4px\">Bulk Inference and Scalable Data Curation for Post-Training</h3>\n<br/>\n\n<div align=\"center\">\n\n[![Github](https://img.shields.io/badge/Curator-000000?style=for-the-badge&logo=github&logoColor=000&logoColor=white)](https://github.com/bespokelabsai/curator/) [![Twitter](https://img.shields.io/badge/@BespokeLabsai-white?style=for-the-badge&logo=X&logoColor=white&color=000)](https://x.com/bespokelabsai) [![Hugging Face](https://img.shields.io/badge/BespokeLabs-fcd022?style=for-the-badge&logo=huggingface&logoColor=000&labelColor)](https://huggingface.co/bespokelabs) [![Discord](https://img.shields.io/badge/Bespoke_Labs-5865F2?style=for-the-badge&logo=discord&logoColor=white)](https://discord.gg/KqpXvpzVBS) \n<br>\n[![Docs](https://img.shields.io/badge/Docs-docs.bespokelabs.ai-blue?style=for-the-badge&link=https%3A%2F%2Fdocs.bespokelabs.ai&labelColor=000)](https://docs.bespokelabs.ai/bespoke-curator/getting-started) [![Website](https://img.shields.io/badge/Site-bespokelabs.ai-blue?style=for-the-badge&link=https%3A%2F%2Fbespokelabs.ai&labelColor=000)](https://bespokelabs.ai/) [![PyPI](https://img.shields.io/pypi/v/bespokelabs-curator?style=for-the-badge&labelColor=000)](https://pypi.org/project/bespokelabs-curator/)\n</div>\n\n<div align=\"center\">\n[ English | <a href=\"docs/README_zh.md\">中文</a> ]\n</div>\n\n## 🎉 What's New\n* **[2026.03.14]** [T"},{"ref":"P23","kind":"page","title":"parasail-ai/speedboat-pub repository metadata","date":"2026-06-11T02:42:11.269284+00:00","date_source":null,"source_url":"https://github.com/parasail-ai/speedboat-pub","signal_url":null,"signal_json_url":null,"text":"# parasail-ai/speedboat-pub\n\nLanguage: Python\n\nStars: 0\n\nForks: 0\n\nOpen issues: 0\n\nCreated: 2026-05-12T23:35:40Z\n\nPushed: 2026-05-12T23:39:04Z\n\nDefault branch: main\n\nFork: no\n\nArchived: no\n\nREADME:\n# Speedboat Take-Home\n\nWelcome — and thanks for spending the time on this.\n\n## What Speedboat is\n\nAt Parasail Speedboat is the product engineering team responsible for everything customer-facing: the APIs, agents, developer tooling, billing, authentication, API key management, and overall user experience (for both humans and bots).\n\nOur job is to take the powerful capabilities built by the core inference platform: LLM inference, fine-tuning, deployments, and vertical AI workloads like text-to-video and audio. Turn them into intuitive, polished product experiences that developers actually enjoy using.\n\nWe focus on moving fast at the product layer while staying lightweight and out of the way of the core inference engine underneath.\n\n## Pick your track\n\nThere are three tracks. Your recruiter contact will have told you which\none to read. Each track folder has its own brief, deliverables list, and\nNOTES template.\n\n| Track | Persona | Brief |\n|---|---|---|\n| **Mid/Junior Full-Stack UI/UX** | Design-leaning IC. Shows design *thinking*, not just generated output. | [docs/tracks/mid-junior/README.md](docs/tracks/mid-junior/README.md) |\n| **Senior Full-Stack UI/UX** | Full-stack IC. Production-shape concerns: auth, multi-tenancy, observability, error handling. | [docs/tracks/senior/README.md](docs/tracks/senior/README.md) |\n| **Engineering Manager** | Deeply product-minded, with strong enough architectural judgment to make pragmatic technical decisions without over-optimizing for infrastructure complexity. They should bring lived experience shipping customer-facing products quickly, working closely with product to iterate fast and get the right features into users’ hands. | [docs/tracks/em/README.md](docs/tracks/em/README.md) |\n\nThe rest of this README covers what's shared across tracks: how to run\nthe mock, how to switch to the real API, ground rules, submission.\n\n## What's in the box\n\n- A FastAPI mock backend that mirrors the Parasail API shape, with\nrealistic latency, stream"},{"ref":"E1","kind":"event","title":"parasail-ai/speedboat-pub","date":"2026-05-12T23:35:40+00:00","date_source":"source","source_url":"https://github.com/parasail-ai/speedboat-pub","signal_url":"https://onlylabs.fyi/signals/f4ab57b0-1aa8-4c04-9258-3c46a0b00968","signal_json_url":"https://onlylabs.fyi/signals/f4ab57b0-1aa8-4c04-9258-3c46a0b00968/signal.json","text":"repo_new · parasail-ai/speedboat-pub · signal_desk=repos · occurred_at=2026-05-12T23:35:40+00:00 · 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