Add Edge Function And Data Model Docs (bbb5e24)
Overview
The recent commit bbb5e24c58fb4ffa8d817f7086748c9b8bf3a00b introduces a new file data-model.md in the docs directory. This file documents the data model for the Recipe Alchemy application, detailing the structure of various database tables, including core tables like recipes, profiles, favorites, shopping_lists, and recipe_chats. It also covers tables related to nutrition and scientific data, vector databases, and reference/support tables.
Code Review
1. Summary of the overall changes
The diff introduces a new file data-model.md in the docs directory. This file documents the data model for the Recipe Alchemy application, detailing the structure of various database tables, including core tables like recipes, profiles, favorites, shopping_lists, and recipe_chats. It also covers tables related to nutrition and scientific data, vector databases, and reference/support tables.
2. Potential issues or bugs
- [Style] (lines 1-272): The document lacks a table of contents, which could improve navigation for larger documents.
3. Security concerns
- [Warning] (lines 46-48): The
image_urlfield in therecipestable could potentially be a vector for XSS attacks if URLs are not properly validated and sanitized.
4. Suggestions for improvement
- Add a Table of Contents:
## Table of Contents
- [Core Tables](#core-tables)
- [Nutrition & Scientific Data Tables](#nutrition--scientific-data-tables)
- [Vector Database Tables](#vector-database-tables)
- [Reference & Support Tables](#reference--support-tables)
- Sanitize URLs (lines 46-48):
Ensure that any URLs stored in the
image_urlfield are validated and sanitized to prevent XSS attacks.
5. Code quality observations
- [Style] (lines 1-272): The document is well-structured with clear headings and descriptions for each table and field. However, adding examples or use cases for some fields could enhance understanding.
6. Minor enhancements
- Consistent Terminology: Ensure consistent use of terms like "timestamp" and "datetime" across the document.
- Field Examples: Provide examples for complex fields like
jsonborvectorto illustrate their expected structure. - Clarify Enum Usage: For fields like
cuisine_category, specify possible enum values. - Improve Readability: Break long paragraphs into bullet points or sub-sections for better readability.
- Link to Related Docs: If there are related documents or sections, provide hyperlinks for easy navigation.
7. AI Developer Prompt
# AI Developer Prompt
Please assess the following code issues and provide solutions:
## Issues Summary
- [WARNING] (lines 46-48): Potential XSS vulnerability through `image_url` field
## For Each Issue
### 1. Mitigate XSS Vulnerability in `image_url`
**Impact**: HIGH - Could lead to security vulnerabilities if exploited
**Confidence**: HIGH
**Problem**: The `image_url` in the `recipes` table could be exploited for XSS attacks if URLs are not properly validated and sanitized.
**Fix**:
```diff
- | image_url | text | URL to recipe image |
+ | image_url | text | URL to recipe image (ensure validation and sanitization) |
Benefit: Prevents potential XSS attacks by ensuring URLs are safe before storage.
Test:
test('should reject invalid URLs', () => {
const result = validateUrl("javascript:alert('XSS')");
expect(result).toBe(false);
});
**Summary of Changes**
----------------------
```markdown
A docs/data-model.md
M docs/documentation-overview.md
M supabase/config.toml
M supabase/functions/usda-food-api/index.ts
Detailed Highlights
Linting Issues
[
{
"filePath": "/home/runner/work/recipe-alchemist-app/recipe-alchemist-app/supabase/functions/usda-food-api/index.ts",
"messages": [
{
"ruleId": "@typescript-eslint/no-explicit-any",
"severity": 2,
"message": "Unexpected any. Specify a different type.",
"line": 143,
"column": 41,
"nodeType": "TSAnyKeyword",
"messageId": "unexpectedAny",
"endLine": 143,
"endColumn": 44,
"suggestions": [
{
"messageId": "suggestUnknown",
"fix": {
"range": [
4644,
4647
],
"text": "unknown"
},
"desc": "Use `unknown` instead, this will force you to explicitly, and safely assert the type is correct."
},
{
"messageId": "suggestNever",
"fix": {
"range": [
4644,
4647
],
"text": "never"
},
"desc": "Use `never` instead, this is useful when instantiating generic type parameters that you don't need to know the type of."
}
]
},
{
"ruleId": "@typescript-eslint/no-explicit-any",
"severity": 2,
"message": "Unexpected any. Specify a different type.",
"line": 147,
"column": 9,
"nodeType": "TSAnyKeyword",
"messageId": "unexpectedAny",
"endLine": 147,
"endColumn": 12,
"suggestions": [
{
"messageId": "suggestUnknown",
"fix": {
"range": [
4791,
4794
],
"text": "unknown"
},
"desc": "Use `unknown` instead, this will force you to explicitly, and safely assert the type is correct."
},
{
"messageId": "suggestNever",
"fix": {
"range": [
4791,
4794
],
"text": "never"
},
"desc": "Use `never` instead, this is useful when instantiating generic type parameters that you don't need to know the type of."
}
]
}
],
"suppressedMessages": [],
"errorCount": 2,
"fatalErrorCount": 0,
"warningCount": 0,
"fixableErrorCount": 0,
"fixableWarningCount": 0,
"source": "\nimport { serve } from \"https://deno.land/std@0.168.0/http/server.ts\";\nimport { getCorsHeadersWithOrigin } from \"../_shared/cors.ts\";\n\n// Constants\nconst BASE_URL = \"https://api.nal.usda.gov/fdc/v1\";\n\n// Main serve function\nserve(async (req) => {\n // Handle CORS preflight requests\n if (req.method === \"OPTIONS\") {\n return new Response(null, { \n headers: getCorsHeadersWithOrigin(req)\n });\n }\n\n try {\n // Get API key from environment\n const apiKey = Deno.env.get(\"USDA_API_KEY\");\n if (!apiKey) {\n return new Response(\n JSON.stringify({ error: \"USDA API key not configured\" }),\n { \n status: 500, \n headers: { ...getCorsHeadersWithOrigin(req), \"Content-Type\": \"application/json\" } \n }\n );\n }\n\n // Parse request body\n const requestBody = await req.json();\n const { method, query, fdcId, pageSize = 10, pageNumber = 1 } = requestBody;\n\n // Different methods for different operations\n let responseData;\n \n switch (method) {\n case \"search\":\n responseData = await searchFoods(apiKey, query, pageSize, pageNumber);\n break;\n case \"get-food\":\n responseData = await getFood(apiKey, fdcId);\n break;\n case \"import-food\":\n responseData = await importFood(apiKey, fdcId);\n break;\n default:\n return new Response(\n JSON.stringify({ error: \"Invalid method specified\" }),\n { \n status: 400, \n headers: { ...getCorsHeadersWithOrigin(req), \"Content-Type\": \"application/json\" } \n }\n );\n }\n\n return new Response(\n JSON.stringify(responseData),\n { \n headers: { ...getCorsHeadersWithOrigin(req), \"Content-Type\": \"application/json\" } \n }\n );\n } catch (error) {\n console.error(\"Error in USDA Food API function:\", error);\n return new Response(\n JSON.stringify({ error: error.message || \"An error occurred processing your request\" }),\n { \n status: 500, \n headers: { ...getCorsHeadersWithOrigin(req), \"Content-Type\": \"application/json\" } \n }\n );\n }\n});\n<br/>
**Q&A: Add Edge Function and Data Model Docs**
=============================================
**Q: What is the purpose of the new file `data-model.md` in the `docs` directory?**
---------------------------------------------------------
A: The new file `data-model.md` in the `docs` directory documents the data model for the Recipe Alchemy application, detailing the structure of various database tables, including core tables like `recipes`, `profiles`, `favorites`, `shopping_lists`, and `recipe_chats`. It also covers tables related to nutrition and scientific data, vector databases, and reference/support tables.
**Q: What are some potential issues or bugs in the new file `data-model.md`?**
-------------------------------------------------------------------------
A: Some potential issues or bugs in the new file `data-model.md` include:
* The document lacks a table of contents, which could improve navigation for larger documents.
* The `image_url` field in the `recipes` table could potentially be a vector for XSS attacks if URLs are not properly validated and sanitized.
**Q: How can I mitigate the XSS vulnerability in the `image_url` field?**
-------------------------------------------------------------------------
A: To mitigate the XSS vulnerability in the `image_url` field, you can ensure that any URLs stored in the `image_url` field are validated and sanitized before storage. This can be done by using a library or function that validates and sanitizes URLs.
**Q: What are some suggestions for improving the new file `data-model.md`?**
-------------------------------------------------------------------------
A: Some suggestions for improving the new file `data-model.md` include:
* Adding a table of contents to improve navigation for larger documents.
* Providing examples or use cases for some fields to enhance understanding.
* Ensuring consistent use of terms like "timestamp" and "datetime" across the document.
* Providing examples for complex fields like `jsonb` or `vector` to illustrate their expected structure.
* Clarifying enum usage for fields like `cuisine_category`.
* Improving readability by breaking long paragraphs into bullet points or sub-sections.
* Linking to related documents or sections for easy navigation.
**Q: What are some minor enhancements that can be made to the new file `data-model.md`?**
-------------------------------------------------------------------------
A: Some minor enhancements that can be made to the new file `data-model.md` include:
* Consistent terminology: Ensure consistent use of terms like "timestamp" and "datetime" across the document.
* Field examples: Provide examples for complex fields like `jsonb` or `vector` to illustrate their expected structure.
* Clarify enum usage: For fields like `cuisine_category`, specify possible enum values.
* Improve readability: Break long paragraphs into bullet points or sub-sections for better readability.
* Link to related docs: If there are related documents or sections, provide hyperlinks for easy navigation.
**Q: What is the impact of the XSS vulnerability in the `image_url` field?**
-------------------------------------------------------------------------
A: The XSS vulnerability in the `image_url` field could lead to security vulnerabilities if exploited. It is essential to mitigate this vulnerability by ensuring that any URLs stored in the `image_url` field are validated and sanitized before storage.
**Q: How can I test the mitigation of the XSS vulnerability in the `image_url` field?**
-------------------------------------------------------------------------
A: test the mitigation of the XSS vulnerability in the `image_url` field, you can use a library or function that validates and sanitizes URLs. You can also use a testing framework to test the functionality of the `image_url` field and ensure that it is not vulnerable to XSS attacks.
**Q: What are some best practices for documenting data models?**
----------------------------------------------------------------
A: Some best practices for documenting data models include:
* Using a consistent format and structure for documenting data models.
* Providing clear and concise descriptions of each field and table.
* Including examples or use cases to illustrate the expected structure of complex fields.
* Ensuring consistent terminology and usage of terms like "timestamp" and "datetime".
* Providing links to related documents or sections for easy navigation.
* Regularly reviewing and updating the documentation to ensure it remains accurate and up-to-date.