trackup-food-analyze

# TrackUp Food Analyze Use this skill to analyze a food image with: - `https://deepeat.ai/step.aispark.api.API/AnalyzeWholeFood` - `https://deepeat.ai/step.aispark.api.API/ExtractFoodMacros` - `https://deepeat.ai/step.aispark.api.API/AnalyzeIngredients` - `https://deepeat.ai/step.aispark.api.API/GetHealthInsight` - `https://deepeat.ai/step.aispark.api.API/SearchFood` ## Rules - Always use `POST` - Always send `Content-Type: application/json` - Image analysis requests must contain `image_url` or `image_base64` - If both exist, `image_base64` wins - `image_base64` must be raw base64 without `data:image/...;base64,` - For complete food image analysis, call `AnalyzeWholeFood` directly - Only call a specialized image-analysis API when the user explicitly asks for one specific analysis dimension - Use `ExtractFoodMacros` for basic macro extraction - Use `AnalyzeIngredients` for deep ingredient and metabolic analysis - Use `GetHealthInsight` for professional health insight - `SearchFood` request body must contain `keyword` - `SearchFood` returns at most the first `20` results ## API Selection Choose the API based on the user's intent: 1. Full food analysis: `AnalyzeWholeFood` 2. Basic macro extraction only: `ExtractFoodMacros` 3. Deep ingredient and metabolic analysis only: `AnalyzeIngredients` 4. Professional health insight only: `GetHealthInsight` 5. Keyword-based lookup without image analysis: `SearchFood` ## Food Search Use `SearchFood` when the user wants keyword-based food lookup instead of image analysis. Request example: ```bash curl --silent --show-error --location \ 'https://deepeat.ai/step.aispark.api.API/SearchFood' \ --header 'Content-Type: application/json' \ --data '{ "keyword": "banana" }' ``` Expected response shape: ```json { "foods": [ { "food_name": "Banana", "calories_cal": "89000", "weight_g": "100", "carbs_g": "22.8", "proteins_g": "1.1", "fats_g": "0.3", "display_gi": 51, "brand": "" } ], "pagination": { "size": 20, "page": 1, "total": 123 } } ``` ## Local Image Workflow Convert local image to base64: ```bash base64 < /absolute/path/to/image.jpg | tr -d '\n' > /tmp/food_image.b64 ``` Build payload: ```bash printf '{"image_base64":"' > /tmp/food_image.json cat /tmp/food_image.b64 >> /tmp/food_image.json printf '"}' >> /tmp/food_image.json ``` Call full food analysis directly: ```bash curl --silent --show-error --location \ 'https://deepeat.ai/step.aispark.api.API/AnalyzeWholeFood' \ --header 'Content-Type: application/json' \ --data-binary @/tmp/food_image.json ``` ## Proxy Fix If `curl` incorrectly tries a local proxy like `127.0.0.1:7890`, retry with: ```bash env -u http_proxy -u https_proxy -u HTTP_PROXY -u HTTPS_PROXY -u ALL_PROXY curl ... ``` ## Response Fields `AnalyzeWholeFood`: - `food_name` - `total_weight_g` - `total_calories_kcal` - `carbs_g` - `proteins_g` - `fats_g` - `display_gi` - `dietary_fiber_g` - `sugar_g` - `ingredients[]` - `health_score` - `health_profile` `ExtractFoodMacros`: - `food_name` - `total_weight_g` - `total_calories_kcal` - `carbs_g` - `proteins_g` - `fats_g` `AnalyzeIngredients`: - `display_gi` - `dietary_fiber_g` - `sugar_g` - `ingredients[]` `GetHealthInsight`: - `health_score` - `health_profile` `SearchFood`: - `foods[]` - `pagination.page` - `pagination.size` - `pagination.total` `health_score` meaning: - `1-5` score generated by AI food evaluation - `5` is the highest score - Use it to help users make nutritionally informed choices ## Output Rules - Keep numeric values exactly as returned - Do not invent missing fields - For complete image analysis, use `AnalyzeWholeFood` as the default API - For specialized analysis, use only the dedicated API that matches the user's request - For `SearchFood`, return the foods in API order and do not claim more than `20` items unless the response actually contains them ## Common Errors - `400 invalid_request` - `422 food_not_recognized` - `422 barcode_only_result` - `429 rate_limit_exceeded` - `500 internal_error` - `502 upstream_flow_error`