Everything in one calm view
Chat, medication routines, and appointment context sit side by side so users can return to daily tasks with less switching.
RESEARCH DEMO · NOT FOR DIAGNOSIS OR TREATMENT · HAI-DEF TERMS APPLY
I adapted the design around the daily realities of fibromyalgia. HelloFibro brings supportive conversation, medication routines, appointment preparation, and symptom support into one calm interface.
Checking whether the live demo is available…
01 · THE PROBLEM
Fibromyalgia is unpredictable and cognitively exhausting. Symptoms change from day to day, and brain fog can make even simple tasks feel difficult.
I focused the design on clarity, low effort, and useful structure for people managing pain, fatigue, medication routines, and medical appointments.
02 · VISUAL GALLERY
A core product walkthrough and captured views show supportive chat, medication routines, and daily context in the live interface.
Chat, medication routines, and appointment context sit side by side so users can return to daily tasks with less switching.
Catalog-backed fields, dosing times, and notes keep manual entry structured when brain fog makes typing harder.
Doctor, specialty, timing, and location stay visible so appointment preparation does not get lost between flares.
Screen recording of the live interface: chat, medication tracking, and the calm workspace layout working together.
03 · THE SOLUTION
HelloFibro adapts familiar chronic pain management tools to fibromyalgia. The interface keeps daily tasks short, readable, and easy to return to when energy or concentration is limited.
Warm, structured responses help users work through symptoms, routines, and questions at their own pace.
Add medications, mark doses taken, and see adherence at a glance with low-friction interactions.
Track upcoming visits and prepare focused questions for a clinician without leaving the flow.
Urgent situations, model disclosure, and clinical limits remain visible throughout the experience.
The hosted UI offers complete interface translations for all 21 selectable locales. English is MedGemma's primary evaluated language; all other model-language paths remain experimental.
View all 21 supported UI languagesConversation, medication, and appointment data remain in memory, with verified user isolation required before public launch.
The hosted demo runs multimodal MedGemma 1.5 4B on Hugging Face ZeroGPU. Full multimodal MedGemma 27B inference requires a separate self-hosted/local GPU deployment.
Users can discuss supported documents, spreadsheets, text files, and images in the same conversation, with validated uploads and extracted context.
Detected worsening factors, a structured knowledge service, and guideline checks add relevant context while preserving non-clinical boundaries.
ACCESS · LOCALIZATION
The live demo exposes 21 fully translated interface locales. Each matches the in-app language selector. English is MedGemma's primary evaluated language; all other model-language paths remain experimental.
Critical deterministic safety messages may fall back to English. A translated interface does not imply equivalent clinical validation of model output.
04 · LIVE PROOF
Hugging Face sign-in · MedGemma 1.5 4B · in-memory prototype data · professional medical guidance remains essential.
Research demonstration only. Do not use it for diagnosis, treatment, emergencies, automated healthcare decisions, or professional medical practice. The hosted version uses the smaller MedGemma 1.5 4B model. Full multimodal MedGemma 27B requires a separate self-hosted/local GPU deployment.
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05 · ARCHITECTURE
The public deployment places red-flag checks before inference and sanitizes the completed response before it reaches the interface. User-isolated in-memory state is also required before launch.
PYTHON 3.10+ · GRADIO 6 · PYDANTIC 2 · OPENROUTER / MEDGEMMA · DOCKER
06 · SAFETY & TRUST
07 · ENGINEERING HIGHLIGHTS
08 · INFRASTRUCTURE LANDSCAPE
HelloFibro reflects my work across health AI UX, agent systems, and careful use of language models. It complements FhirFlame, my healthcare data platform project.
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