U.S. Department of Agriculture Secretary Tom Vilsack announced the USDA is investing $124 million in renewable energy and fertilizer production projects in...

DNR says non-lethal tactics failed before USDA staff euthanized a Price County pack.

Council approved a resolution requesting defederalization of the RBEG revolving loan fund administered by the regional planning commission, after staff said the USDA grant requirements had been satisfied and the fund (about $160,000) can continue without USDA oversight.

Research to strengthen surveillance, preparedness and response efforts as the USDA confirmed the first wild fly trap detection since the outbreak began.

The USDA announced the recall on Friday.

GAO found outdated USDA SNAP guidance for veterans and recommended better outreach and coordination to help veterans access food assistance.

YouTube video by Brian Tyler Cohen

Join us in urging the USDA to keep the the Roadless Rule as is, and ensure protection for the sources of drinking water flowing off of our National Forests for over 24 million Americans.

About 95 mg in an 8 oz brewed cup per USDA, with the full chart by drink, cup size, brew method, roast level and decaf.

_This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend_ ## What I Built **Recipe → Macro Calculator + High-Protein Variant Generator** — a fully local Streamlit app that: 1. **Extracts ingredients** from any recipe URL or photo (OCR + LLM) 2. **Matches to USDA nutrition data** → calculates macros per serving 3. **Scales recipes** to a target calorie goal 4. **Generates high-protein variants** of any dish (e.g., "bhel" → "Soya Bhel Puri" with 28g protein/serving) **Built for:** My gym partner **Arjun** , who meal-preps every Sunday but wastes 30+ min manually calculating macros in spreadsheets and googling "high protein [dish] alternatives." He wants to hit 180g protein/day on a vegetarian Indian diet without eating plain chicken breast. **Problem solved:** Paste a recipe URL → get instant macros + grocery list. Type "paneer tikka" → get a 35g-protein version with Greek yogurt marinade + tofu swap. All offline, no accounts, data never leaves his laptop. ## Demo ## Code GitHub Repo: https://github.com/GurmeetsinghRelusinghani28/recipe-macro-calculator Key files: * app.py — Streamlit UI (3 tabs: URL, Photo, High-Protein Swap) * scraper.py + parser.py — Trafilatura + Ollama (gemma2:2b) for ingredient extraction * matcher.py — RapidFuzz + USDA Foundation Foods CSV (local) * suggester.py — LLM prompt for high-protein recipe variants * download_usda.py — Downloads & merges USDA nutrient data (one-time) ## How I Built It URL/Photo → Scraper/OCR → LLM Parser → JSON ingredients ↓ RapidFuzz → USDA CSV → Macros ↓ Scale to target kcal → Grocery list ↓ High-Protein Swap: LLM Variant → same pipeline Models pulled locally: ollama pull gemma2:2b # text parsing + variant generation ollama pull llava:7b # photo OCR cleanup ## Why Does Open Innovation Matter? This project only works because every piece is open: 1. Runs on a 4-year-old laptop (16GB RAM, no GPU) — Gemma 2B + LLaVA 7B quantized to 4-bit. Try that with GPT-4o or Claude. 2. Zero data leaves the machine — Arjun's recipe photos, dietary goals, and meal plans stay on his disk. No cloud upload, no training data harvesting, no subscription. 3. Swappable models — I tested qwen2.5:3b, phi3:3.8b, gemma2:2b by changing one line. Closed APIs lock you in. 4. Fine-tunable — If Arjun wants "Gujarati-style" variants, I can fine-tune Gemma on 50 examples via Tinker. Impossible with closed models. 5. Costs $0/month forever — No token pricing, no rate limits, no "pricing tier changed" emails. 6. USDA data is public domain — The nutrition backbone is open government data. Proprietary APIs (Nutritionix, Edamam) cost $100s/month and throttle. Where closed would fail: 7. Cloud vision API → fails on gym WiFi, uploads friend's food photos 8. Nutrition API → rate limits kill batch meal-prep (50 recipes at once) 9. LLM API → $0.01/recipe adds up; can't fine-tune for "Indian vegetarian high-protein" ## My Agent Session ## Prize Categories Best Use of Gemma — Core text model (gemma2:2b) for parsing + variant generation * Best Use of Ollama — Local inference runtime for both text + vision models * Best Use of MongoDB Atlas — Not used (SQLite for logs, USDA CSV for data) * Best Use of Render — Not used (runs fully local, but deployable to Render free tier) * Best Use of Backboard — Not used (single-file agents, no RAG needed) * Best Use of ElevenLabs — Not used (no voice feature yet) Note: Primary entry: Gemma + Ollama (open-weight models + local runtime). Other categories listed for completeness but not claimed. ### **One-Liner for Socials** > Built my gym partner a local AI that turns any recipe into a high-protein version + counts macros — runs offline on his laptop with Gemma 2B + USDA data. No API keys, no cloud, $0/month. 🏋️‍♂️🥗 #Hacktoberfest #BuildForAFriend

The USDA announced the recall on Friday.

The USDA announced the recall on Friday.

Even farmers who were already promised funds from the REAP program may never get them under the Trump admin’s new restrictions. Some are suing.