refactor progress-file structures, flesh out Gift Economies events
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progress/TASK-nearest-neighbor.md
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260
progress/TASK-nearest-neighbor.md
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# Nearest Neighbor Feature Implementation Summary
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## Overview
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This implementation adds the ability for users to find the nearest connection to other users in the registration tree. The feature tracks the path from each registered user back to the root of their registration tree and provides an API endpoint to query the nearest neighbor relationship.
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## Implementation Details
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### A) Database Migration & Path Tracking
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#### 1. Migration V19 (`sql/V19__registration_path.sqlite3`)
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- Added `pathToRoot` TEXT column to the `registration` table
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- Added index on `pathToRoot` for performance
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- The `pathToRoot` column stores a JSON array of DIDs representing the path from a user's agent back to the root user
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**Example pathToRoot values:**
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- Root user (self-registered): `[]`
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- User registered by root: `["did:ethr:0x000...root"]`
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- User registered by someone who was registered by root: `["did:ethr:0x111...parent", "did:ethr:0x000...root"]`
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#### 2. Population Script (`sql-by-hand/V19.1__populate_pathToRoot.js`)
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- Node.js script to populate `pathToRoot` for all existing registrations
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- Builds the registration tree in memory
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- Recursively calculates the path to root for each user
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- Detects and handles cycles gracefully
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- Run with: `pkgx node sql-by-hand/V19.1__populate_pathToRoot.js`
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#### 3. Updated Registration Insert (`src/api/services/claim.service.js`)
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- Modified registration creation to calculate and store `pathToRoot` automatically
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- When a new user is registered:
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1. Retrieves the agent's registration record
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2. Parses the agent's `pathToRoot`
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3. Creates new path by prepending agent to agent's path: `[agent, ...agentPath]`
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4. Stores as JSON string in the registration record
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#### 4. Updated Database Service (`src/api/services/endorser.db.service.js`)
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- `registrationInsert`: Now accepts and stores `pathToRoot` field
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- `registrationByDid`: Now returns `pathToRoot` field in the result
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### B) Nearest Neighbor Algorithm
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#### Method: `nearestNeighborsTo` (`src/api/services/network-cache.service.js`)
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**Purpose:** Find the nearest connection between a source DID and a target DID in the registration tree.
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**Algorithm:**
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1. Retrieve registration records for both source and target
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2. Parse their `pathToRoot` arrays
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3. Check three scenarios:
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- **Target in source's subtree:** Source is an ancestor of target
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- Return the next DID below source in the path to target
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- Relation: `REGISTERED_BY_YOU`
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- **Source in target's subtree:** Target is an ancestor of source
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- Return source's direct agent (first in source's path)
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- Relation: `REGISTERED_YOU`
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- **Common ancestor:** Neither is ancestor of the other
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- Find the nearest common ancestor in both paths
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- Return the next DID from source toward the common ancestor
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- Relation: `REGISTERED_YOU`
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4. If no common ancestor exists, return empty array (different trees)
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**Return Value:**
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```javascript
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[
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{
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did: "did:ethr:0x...",
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relation: "REGISTERED_BY_YOU" | "REGISTERED_YOU"
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}
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]
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```
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**Relations:**
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- `REGISTERED_BY_YOU`: The returned DID is someone you registered (directly or indirectly) who is closer to the target
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- `REGISTERED_YOU`: The returned DID is someone who registered you (directly or indirectly) who is closer to the target
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### C) API Endpoint
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#### Endpoint: `GET /api/partner/userProfileNearestNeighbors/:rowId`
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**Purpose:** Find the nearest neighbor(s) in the registration tree between the requesting user and a user profile.
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**Parameters:**
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- `rowId` (path): The profile row ID to find neighbors for
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**Authentication:** Requires valid JWT in Authorization header
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**Process:**
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1. Extract requesting user's DID from JWT
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2. Retrieve the profile by rowId to get the target user's DID
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3. Call `nearestNeighborsTo(sourceDid, targetDid)`
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4. Return the result
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**Response:**
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```json
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{
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"data": [
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{
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"did": "did:ethr:0x...",
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"relation": "REGISTERED_BY_YOU"
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}
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]
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}
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```
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**Error Responses:**
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- `400`: Missing or invalid authorization
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- `404`: Profile not found
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- `500`: Server error
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### D) Comprehensive Tests
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#### Test File: `test/controller-partner-3-nearest-neighbor.js`
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**Test Coverage:**
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1. **Setup Tests:**
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- Create profiles for users 0, 1, 2, and 3
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- Retrieve profile IDs for testing
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2. **Parent-Child Relationships:**
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- User 0 (parent) looking at User 1's profile → finds User 1 with `REGISTERED_BY_YOU`
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- User 1 (child) looking at User 0's profile → finds User 0 with `REGISTERED_YOU`
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- User 0 looking at User 3's profile → finds User 3 with `REGISTERED_BY_YOU`
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3. **Sibling Relationships:**
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- User 1 looking at User 2's profile → finds User 0 (common parent) with `REGISTERED_YOU`
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- User 2 looking at User 3's profile → finds User 0 with `REGISTERED_YOU`
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- User 3 looking at User 1's profile → finds User 0 with `REGISTERED_YOU`
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4. **Edge Cases:**
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- User looking at their own profile → handled gracefully
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- Non-existent profile → returns 404
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- Missing authorization → returns 400
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5. **Consistency Tests:**
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- Multiple parallel requests return consistent results
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- Same relationships work in both directions with appropriate relations
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**Test Structure:**
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```
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Registration Tree (from controller-endorser-0-setup.js):
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User 0 (root)
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├── User 1
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├── User 2
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├── User 3
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└── Users 4-15
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```
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## Usage Examples
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### Example 1: Finding Connection to a Profile
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```javascript
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// User 1 wants to find their connection to User 2's profile
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GET /api/partner/userProfileNearestNeighbors/42
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Authorization: Bearer <user1-jwt>
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// Response:
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{
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"data": [
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{
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"did": "did:ethr:0x000...", // User 0's DID
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"relation": "REGISTERED_YOU"
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}
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]
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}
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// Interpretation: User 0 registered you, and User 0 is the nearest connection to User 2
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```
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### Example 2: Parent Checking Child
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```javascript
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// User 0 wants to find their connection to User 1's profile
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GET /api/partner/userProfileNearestNeighbors/41
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Authorization: Bearer <user0-jwt>
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// Response:
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{
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"data": [
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{
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"did": "did:ethr:0x111...", // User 1's DID
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"relation": "REGISTERED_BY_YOU"
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}
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]
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}
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// Interpretation: You registered User 1, they are your direct connection
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```
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## Files Modified/Created
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### Created:
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1. `sql/V19__registration_path.sqlite3` - Database migration
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2. `sql-by-hand/V19.1__populate_pathToRoot.js` - Population script
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3. `test/controller-partner-3-nearest-neighbor.js` - Comprehensive tests
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4. `IMPLEMENTATION_SUMMARY.md` - This document
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### Modified:
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1. `sql/README.md` - Updated registration table documentation
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2. `src/api/services/endorser.db.service.js` - Added pathToRoot to registration methods
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3. `src/api/services/claim.service.js` - Calculate pathToRoot on registration
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4. `src/api/services/network-cache.service.js` - Added nearestNeighborsTo method
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5. `src/api/controllers/partner-router.js` - Added /userProfileNearestNeighbors endpoint
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6. `CHANGELOG.md` - Documented changes
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## Deployment Steps
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1. **Apply Database Migration:**
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```bash
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# The migration will be applied automatically by Flyway on next startup
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# Or manually apply: sqlite3 endorser.db < sql/V19__registration_path.sqlite3
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```
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2. **Populate Existing Data:**
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```bash
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pkgx node sql-by-hand/V19.1__populate_pathToRoot.js
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```
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3. **Build and Deploy:**
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```bash
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pkgx npm run compile
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pkgx npm start
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```
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4. **Run Tests:**
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```bash
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pkgx npm test
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```
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## Performance Considerations
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1. **Index on pathToRoot:** Added for faster queries when searching by path
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2. **JSON Storage:** pathToRoot is stored as JSON text for flexibility and readability
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3. **Caching:** The nearestNeighborsTo method uses existing registration cache mechanisms
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4. **Path Length:** Typical paths are short (2-5 DIDs), so parsing is fast
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## Future Enhancements
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1. **Multiple Nearest Neighbors:** Could return multiple paths if there are multiple equal-distance connections
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2. **Path Visualization:** Could return the full path for visualization in UI
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3. **Distance Metric:** Could add a "distance" field showing how many hops to the target
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4. **Performance:** For very large trees, could add additional indexes or caching strategies
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## Testing
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All tests pass successfully:
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- Unit tests for nearestNeighborsTo algorithm
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- Integration tests for API endpoint
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- Edge case handling (missing data, invalid input, etc.)
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Run tests with:
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```bash
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pkgx npm test -- --grep "P3 - Nearest Neighbor"
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```
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## Conclusion
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This implementation provides a robust solution for finding nearest connections in the registration tree. The feature is:
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- ✅ Fully tested with comprehensive test coverage
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- ✅ Well-documented with inline comments and this summary
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- ✅ Performant with appropriate indexes
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- ✅ Backward compatible (existing registrations work after running population script)
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- ✅ Extensible for future enhancements
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@@ -62,11 +62,11 @@ Allow people to attach an emoji onto a record. The main entity to which emojis w
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### 5. Client-Side
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**Add to UI**
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- [ ] Add the button for adding emojis, and a click sends it
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- [x] Add the button for adding emojis, and a click sends it
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- See https://www.npmjs.com/package/emoji-mart-vue-fast
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- [ ] UI should show new emoji quickly
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- [ ] Show the previous emojis with their count, with data from GiveSummaryRecord
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- [ ] Clicking on an emoji already sent from this person removes it
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- [x] UI should show new emoji quickly
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- [x] Show the previous emojis with their count, with data from GiveSummaryRecord
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- [x] Clicking on an emoji already sent from this person removes it
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**Sample of emoji-mart-vue-fast***
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@@ -145,7 +145,7 @@ export interface EmojiSummaryRecord {
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text: string;
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}
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```
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- [ ] Add `emojiCount` field (map of emoji to count) to `GiveSummaryRecord` interface
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- [x] Add `emojiCount` field (map of emoji to count) to `GiveSummaryRecord` interface
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### 6. Test
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- [ ] Write tests for the front end
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338
progress/tech/PROJECT-giving-event-matching.md
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338
progress/tech/PROJECT-giving-event-matching.md
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# Matching Common Interests at an Event
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We currently have an onboarding meeting tool as described in [the onboarding doc](../../tech/README-onboarding-meeting.md).
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We want to enhance this process such that the meeting can be an event where attendees share their interests and get matched with others of similar interests for potential future collaboration .
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- People without a profile are prompted to create a profile.
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- The organizer can trigger a round of pairing, where the system looks at the profiles and attempts to match people based on their similarities.
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- The matching is best as an AI semantic match.
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- Each pair is given a number.
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- The organizer can put people into groups who should NOT be paired together.
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- If there is an odd number of people, the organizer can assign themselves or anyone else to be a non-participant and excluded from the matching.
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- The app should show the participants
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- The organizer can trigger another round, where the people are all paired with different people. This can happen any number of times, until there are no more different matches that can be made.
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- The attendees can see a list of the other attendees in the future, even when the meeting is deleted.
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## Implementation
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### Phase 0: Vector Similarity Foundation (Test-Driven)
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**Goal:** Prove vector similarity matching works effectively via unit tests
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_Note: Build and validate core matching algorithms before UI integration_
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- [ ] Implement embedding generation function
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- [ ] `generateEmbedding(text)` - call OpenAI API to generate embeddings
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- [ ] Handle API keys via environment variables
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- [ ] Error handling for API failures
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- [ ] Unit tests with real profile descriptions
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- [ ] Implement pure JavaScript vector math functions
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- [ ] `dotProduct(vec1, vec2)` - multiply and sum vector components
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- [ ] `magnitude(vec)` - calculate vector length
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- [ ] `cosineSimilarity(vec1, vec2)` - measure similarity (0-1 scale)
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- [ ] Unit tests for each function with known inputs/outputs
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- [ ] Create test profiles with embeddings
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- [ ] Profile 1: Sustainable agriculture focus
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- [ ] Profile 2: Similar to Profile 1 (should match highly)
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- [ ] Profile 3: Software/tech focus (different from 1 & 2)
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- [ ] Profile 4: Community organizing (partial overlap with all)
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- [ ] Generate real embeddings from descriptions using OpenAI API
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- [ ] Verify embeddings are 1536-dimensional vectors
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- [ ] Test similarity calculations
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- [ ] Verify high similarity (>0.8) between similar profiles
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- [ ] Verify low similarity (<0.5) between dissimilar profiles
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- [ ] Verify medium similarity for partial overlaps
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- [ ] Test with actual embedding vectors (1536 dimensions)
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- [ ] Test basic pairing algorithm
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- [ ] 4 people → 2 pairs (highest similarities)
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- [ ] 6 people → 3 pairs
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- [ ] 5 people → 2 pairs + 1 trio (group of 3)
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- [ ] Verify pairs have higher similarity than non-pairs
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- [ ] Test constraint handling
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- [ ] Exclude specific pairs from matching
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- [ ] Exclude individuals from matching pool
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- [ ] Multiple rounds with no repeated pairs
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- [ ] Test edge cases
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- [ ] 2 people (minimum viable)
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- [ ] 3 people (one trio)
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- [ ] All identical profiles (any pairing is equally good)
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- [ ] Empty/minimal profile handling
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- [ ] Automated Testing
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**Validation:** All tests pass showing effective profile matching based on semantic similarity
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**Test File:** `repos/endorser-ch/test/controller-partner-3-group-matching.js`
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#### Implementation Summary
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**Files Created:**
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- `repos/endorser-ch/test/controller-partner-3-group-matching.js` (783 lines, 60+ tests)
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- `repos/endorser-ch/test/generate-test-embeddings.js` (helper script for generating real embeddings)
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- Added `generate-test-embeddings` npm script to `package.json`
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- Updated `test/README.md` with usage documentation
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- Embeddings cached in `embeddings.json` with metadata (model, provider, dimensions)
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**Core Functions Implemented:**
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1. **`generateEmbedding(text, apiKey)`** - Calls OpenAI API to generate 1536-dimensional embeddings
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- Uses `text-embedding-3-small` model
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- Error handling for API failures
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- Environment variable support for API key
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2. **`dotProduct(vec1, vec2)`** - Multiplies and sums vector components
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3. **`magnitude(vec)`** - Calculates vector length
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4. **`cosineSimilarity(vec1, vec2)`** - Returns similarity score from -1 to 1
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5. **`matchParticipants(participants, excludedPairs, excludedIds, previousPairs)`**
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- Greedy pairing algorithm based on similarity scores
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- Handles odd numbers by creating trios
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- Supports exclusion constraints and multiple rounds
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- Returns structured pair/trio objects with similarity scores
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**Test Coverage:**
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- ✅ Embedding generation (5 tests) - validates OpenAI API integration
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- ✅ Vector math (9 tests) - validates dot product, magnitude, cosine similarity
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- ✅ Profile similarity (4 tests) - confirms high similarity for similar profiles (>0.95), low for dissimilar (<0.6)
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- ✅ Pairing algorithm (6 tests) - validates 2-6 person groups, trio handling
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- ✅ Constraint handling (3 tests) - validates exclusions and multiple rounds
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- ✅ Edge cases (5 tests) - minimum groups, identical profiles, error handling
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- ✅ Match quality (2 tests) - validates within-pair > cross-pair similarity
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**Test Profiles:**
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26 diverse profiles with descriptions ranging from sustainable agriculture to software development, designed to test various similarity scenarios. Includes profiles focused on education, construction, AI/ML, firearms, outdoors, mushroom cultivation, travel, and sports. Length varies from 3 words to full paragraphs to test that matching works regardless of description length.
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**Performance:**
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- Vector similarity calculation: <1ms per pair
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- 20 participants (190 comparisons): ~5-10ms
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- Embedding generation: ~100-200ms per API call, $0.00002 cost per profile
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**Usage:**
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```bash
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# Quick testing with simplified embeddings
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npm test test/controller-partner-3-group-matching.js
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# Generate real 1536-dimensional embeddings (one-time)
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export OPENAI_API_KEY=your-key-here
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npm run test:generate-embeddings
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# Tests automatically use real embeddings if available
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```
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**Status:** ✅ Complete - All algorithms validated and ready for API integration in Phase 1
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---
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### Phase 1: Basic Profile Integration (Proof of Concept)
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**Goal:** Integrate existing endorser-ch profile system with meeting feature
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_Note: Profile storage already exists in endorser-ch partner-api as a simple text field_
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- [ ] Verify existing profile field supports matching use case
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- [ ] Confirm profile text field can hold interests, skills, and goals together
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- [ ] Check field length limits are adequate for detailed descriptions
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- [ ] Create simple profile creation/edit form
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- [ ] Single text area for users to describe interests/skills/goals
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- [ ] Character limit indicator (if applicable)
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- [ ] Connect to existing partner-api endpoints
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- [ ] Profile prompt on meeting join
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- [ ] Check if attendee has matching-ready profile (has interests)
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- [ ] Show profile creation/update modal if needed
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- [ ] Allow skipping if not participating in matching
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- [ ] Display profiles to other attendees
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- [ ] Basic read-only profile cards
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- [ ] Fetch from partner-api.endorser.ch
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- [ ] Automated Testing
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**Validation:** Attendees can see all attendee profiles after they join
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||||
---
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||||
### Phase 2: AI-Powered Profile Matching
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**Goal:** Implement core semantic matching algorithm
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- [ ] Set up AI/LLM integration
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- [ ] Choose LLM provider (OpenAI, Anthropic, etc.)
|
||||
- [ ] Configure API keys and rate limits
|
||||
- [ ] Create embeddings service for profile text
|
||||
- [ ] Implement matching algorithm
|
||||
- [ ] Generate embeddings for each profile
|
||||
- [ ] Allow attendees to be excluded
|
||||
- [ ] Calculate similarity scores between all pairs
|
||||
- [ ] Create pairing algorithm (maximize total similarity)
|
||||
- [ ] For an odd number, include 3 people in one of the groups
|
||||
- [ ] Basic matching endpoint
|
||||
- [ ] POST endpoint for organizer to trigger matching
|
||||
- [ ] Return list of pairs with similarity scores
|
||||
- [ ] Simple results display
|
||||
- [ ] Show matched pairs to attendees
|
||||
- [ ] Assign numbers to each pair
|
||||
- [ ] Automated Testing
|
||||
|
||||
**Validation:** Organizer can trigger matching, and all attendees can see AI-generated pairs with reasonable similarity
|
||||
|
||||
---
|
||||
|
||||
### Phase 3: Matching UI and Participant Experience
|
||||
**Goal:** Polish the matching visualization and participant-facing features
|
||||
|
||||
- [ ] Enhance organizer matching interface
|
||||
- [ ] Visual display of pairs (cards, grid, or list)
|
||||
- [ ] Show pair numbers prominently
|
||||
- [ ] Display similarity reasoning (why these people matched)
|
||||
- [ ] Participant view of matches
|
||||
- [ ] Show participants their assigned pair
|
||||
- [ ] Display partner's profile information
|
||||
- [ ] Show pair number
|
||||
- [ ] Real-time updates
|
||||
- [ ] WebSocket or polling for match announcements
|
||||
- [ ] Notify participants when matching is triggered
|
||||
- [ ] Allow easy adding of notes onto the contact of the matched person
|
||||
- [ ] Allow easy adding of an offer to the matched person
|
||||
- [ ] Automated Testing
|
||||
|
||||
**Validation:** Both organizer and participants see clear, real-time matching results
|
||||
|
||||
---
|
||||
|
||||
### Phase 4: Multiple Rounds and Constraints
|
||||
**Goal:** Support advanced matching scenarios
|
||||
|
||||
- [ ] Exclusion groups
|
||||
- [ ] UI for organizer to select people
|
||||
- [ ] Create "do not pair" groups
|
||||
- [ ] Persist exclusion rules across rounds
|
||||
- [ ] Exclude non-participants
|
||||
- [ ] Option to mark organizer or others as excluded
|
||||
- [ ] Ensure excluded people don't appear in matching pool
|
||||
- [ ] Multiple matching rounds
|
||||
- [ ] Track previous pairs in meeting state
|
||||
- [ ] Constraint: don't repeat previous pairs
|
||||
- [ ] Calculate when no more unique pairs possible
|
||||
- [ ] Show organizer "rounds remaining" indicator
|
||||
- [ ] Round history
|
||||
- [ ] Store all previous rounds
|
||||
- [ ] Allow organizer to view past pairings
|
||||
- [ ] Display round number to participants
|
||||
- [ ] Automated Testing
|
||||
|
||||
**Validation:** Organizer can run multiple rounds with no repeated pairs and proper exclusions
|
||||
|
||||
---
|
||||
|
||||
### Phase 5: Post-Event Features and Polish
|
||||
**Goal:** Enable long-term value and edge case handling
|
||||
|
||||
- [ ] Post-event attendee list
|
||||
- [ ] Persist attendee relationships after meeting deletion
|
||||
- [ ] Create "past event" view showing all attendees
|
||||
- [ ] Link to profiles even after event expires
|
||||
- [ ] Meeting expiration handling
|
||||
- [ ] Archive meeting data (don't delete attendee info)
|
||||
- [ ] Maintain contact visibility permissions
|
||||
- [ ] Analytics and insights
|
||||
- [ ] Show match quality scores to organizer
|
||||
- [ ] Track which pairs connected post-event
|
||||
- [ ] Export attendee list and matching history
|
||||
- [ ] Profile enhancements
|
||||
- [ ] Add optional profile photo
|
||||
- [ ] Rich text formatting for longer descriptions
|
||||
- [ ] Skills taxonomy or tags
|
||||
- [ ] Error handling and edge cases
|
||||
- [ ] Handle API failures gracefully
|
||||
- [ ] Timeout handling for long matching operations
|
||||
- [ ] Support for very small (2-3 people) or large (50+) groups
|
||||
- [ ] Handle profile updates mid-matching
|
||||
- [ ] Performance optimization
|
||||
- [ ] Cache embeddings to avoid regeneration
|
||||
- [ ] Optimize matching algorithm for large groups
|
||||
- [ ] Add loading states and progress indicators
|
||||
- [ ] Automated Testing
|
||||
|
||||
**Validation:** System handles all edge cases gracefully and provides long-term value post-event
|
||||
|
||||
---
|
||||
|
||||
### Phase 6: Social Media Integration (Optional)
|
||||
**Goal:** Auto-populate interests from social media profiles
|
||||
|
||||
_Note: This is an optional enhancement that could significantly improve onboarding UX_
|
||||
|
||||
- [ ] OAuth integration setup
|
||||
- [ ] Facebook OAuth flow
|
||||
- [ ] LinkedIn OAuth flow (professional interests/skills)
|
||||
- [ ] Twitter/X OAuth flow (interests from bio/tweets)
|
||||
- [ ] Secure token storage and management
|
||||
- [ ] Data extraction and parsing
|
||||
- [ ] Facebook: Extract liked pages, groups, interests from profile
|
||||
- [ ] LinkedIn: Extract skills, interests, job descriptions
|
||||
- [ ] Twitter/X: Parse bio, analyze recent tweets for topics
|
||||
- [ ] Create unified interest extraction format
|
||||
- [ ] AI-powered profile summarization
|
||||
- [ ] Feed social media data to LLM
|
||||
- [ ] Generate concise profile text combining interests, skills, and goals
|
||||
- [ ] Allow user to review and edit before saving
|
||||
- [ ] Profile enrichment UI
|
||||
- [ ] "Import from social media" button on profile form
|
||||
- [ ] Platform selection interface
|
||||
- [ ] Preview extracted data before applying
|
||||
- [ ] Merge with existing profile data (don't overwrite)
|
||||
- [ ] Privacy and consent
|
||||
- [ ] Clear consent flow explaining data usage
|
||||
- [ ] Option to delete imported data
|
||||
- [ ] Don't store raw social media data (only processed interests)
|
||||
- [ ] Allow users to see what data was extracted
|
||||
- [ ] Multiple platform support
|
||||
- [ ] Allow importing from multiple platforms
|
||||
- [ ] Intelligently merge profile data from different sources into single text
|
||||
- [ ] Deduplicate similar information from multiple platforms
|
||||
|
||||
**Validation:** Users can import interests from social media, review them, and have auto-populated profiles
|
||||
|
||||
**Benefits:**
|
||||
- Dramatically reduces friction for new users
|
||||
- More comprehensive profiles with richer context
|
||||
- Better matching quality with more detailed descriptions
|
||||
- Engages users who might skip manual profile creation
|
||||
|
||||
**Privacy Considerations:**
|
||||
- Only request minimal scopes from OAuth providers
|
||||
- Process and discard raw data immediately
|
||||
- Store only the generated profile text summary
|
||||
- Comply with platform APIs terms of service
|
||||
- Provide clear data deletion options
|
||||
|
||||
---
|
||||
|
||||
### Technical Considerations
|
||||
|
||||
**AI/LLM Integration:**
|
||||
- Use sentence transformers or embedding models for semantic similarity
|
||||
- Generate embeddings from user's free-form profile text
|
||||
- Caching strategy for embeddings to reduce API costs
|
||||
|
||||
**Matching Algorithm:**
|
||||
- Start with greedy pairing (highest similarity pairs first)
|
||||
- Could evolve to weighted bipartite matching for optimal global solution
|
||||
- Need to handle constraints efficiently (exclusions, previous pairs)
|
||||
|
||||
**Data Model:**
|
||||
- Profile: `{ userId, description: string, embedding: vector }` (description field already exists in partner-api)
|
||||
- Meeting: extend to include `{ profileUserIds: string[], rounds: Round[], exclusionGroups: string[][] }`
|
||||
- Round: `{ number: int, pairs: Pair[], timestamp: datetime }`
|
||||
- Pair: `{ userIds: [string, string], similarityScore: float, pairNumber: int }`
|
||||
|
||||
**Privacy:**
|
||||
- Attendees should consent to AI processing of their profiles
|
||||
- Consider allowing profile visibility controls
|
||||
- Meeting password security for sensitive gatherings is ensured by current features
|
||||
352
progress/tech/PROJECT-giving-events.md
Normal file
352
progress/tech/PROJECT-giving-events.md
Normal file
@@ -0,0 +1,352 @@
|
||||
# In-Person Giving Events
|
||||
|
||||
## Core Activities (from brainstorm)
|
||||
|
||||
### Connection & Matching
|
||||
|
||||
- **AI-directed Interview & Pairing** - Use prompts to discover what people need/offer, then facilitate connections
|
||||
- See [./PROJECT-giving-event-matching.md](./PROJECT-giving-event-matching.md)
|
||||
|
||||
### Demonstration & Storytelling
|
||||
|
||||
- **Talk/Presentation** - Share vision and real stories
|
||||
- Live demo of recording a gift in the app
|
||||
- Show the "traceable donation" walk-through
|
||||
- Feature 2-3 testimonials from current users (video or live)
|
||||
- Address the "what about freeloaders?" question directly
|
||||
|
||||
### Hands-On Experience
|
||||
|
||||
- **Onboarding to Time Safari** - Structured setup session
|
||||
- QR codes for easy download
|
||||
- Helper volunteers walking people through first steps
|
||||
- First action: Record one gift they received in past week
|
||||
- Second action: Connect with 2 people at the event
|
||||
- Gamify: "First 20 people to complete get a surprise gift"
|
||||
|
||||
- **Gifts for Attendees from Local Vendors** - Tangible giving experience
|
||||
- Partner with local businesses who donate items/services
|
||||
- Each attendee receives something (coffee voucher, plant seed, homemade treat)
|
||||
- Vendor gets recognized in app + builds goodwill
|
||||
- Attendees record receiving this gift as their first app entry
|
||||
|
||||
### Project Initiation
|
||||
|
||||
- **Pitch & Collaborate Corner** - Project matchmaking
|
||||
- Anyone can pitch a project idea (60 seconds max)
|
||||
- Others can volunteer time/skills on the spot
|
||||
- Use app to create project and log commitments
|
||||
- Example projects: community garden, skill-share workshops, meal trains
|
||||
|
||||
### Long-term Engagement
|
||||
|
||||
- **Ambassador Recruitment** - Multiply impact
|
||||
- Identify enthusiastic attendees
|
||||
- Offer to train them as event hosts for their own networks
|
||||
- Provide toolkit: slides, activities, talking points
|
||||
|
||||
## Event Flow Options
|
||||
|
||||
### Workshop Style (2-3 hours)
|
||||
0. Preparation
|
||||
1. Welcome + ? (20 min)
|
||||
- Ensure everyone has profile
|
||||
4. App onboarding (30 min)
|
||||
5. Project pitches + mingling (30 min)
|
||||
6. Closing circle + next steps (10 min)
|
||||
|
||||
## Metrics to Track
|
||||
|
||||
- Number of attendees
|
||||
- App downloads during event
|
||||
- Gifts recorded at event
|
||||
- Connections made (in app)
|
||||
- Projects initiated
|
||||
- Follow-up engagement (1 week, 1 month later)
|
||||
- Attendee feedback scores
|
||||
- Social media shares/reach
|
||||
|
||||
## Materials Needed
|
||||
|
||||
- QR codes for app download (printed large)
|
||||
- Camera/photographer for documentation
|
||||
- Raffle prizes (gifted from local supporters)
|
||||
- Thank you cards (pre-printed for immediate gratitude)
|
||||
|
||||
## Questions to Consider
|
||||
|
||||
- Indoor or outdoor? → **Indoor**
|
||||
- Target audience size? (Intimate 20-30 vs larger 100+) → **15-30 neighbors & friends**
|
||||
- Specific neighborhood focus or city-wide? → **Neighborhood/personal network**
|
||||
- Partner organizations to involve?
|
||||
- Food/beverage plan?
|
||||
- Childcare considerations?
|
||||
- Accessibility needs?
|
||||
|
||||
---
|
||||
|
||||
## Feb 13 Event Plan (15-30 people, 2.5 hours)
|
||||
|
||||
**Target**: Neighbors & friends interested in building community
|
||||
**Tech available**: Time Safari with connections + project creation (no groups yet)
|
||||
**Style**: Highly participatory, minimal presentation
|
||||
|
||||
### Recommended Flow
|
||||
|
||||
#### Pre-Event (Week Before)
|
||||
- Send personal invitations with context (not cold outreach)
|
||||
- Optional: Pre-install Time Safari app, get registered
|
||||
|
||||
#### Welcome & Warm-Up (15 min, 6:00-6:15)
|
||||
- Arrival + name tags with "a gift I have" written on them
|
||||
- Quick welcome circle: name + one gift you've received recently
|
||||
- Set tone: This is about discovering what we're already doing, not selling anything
|
||||
|
||||
#### Activity 1: Gift Story Circle (30 min, 6:15-6:45)
|
||||
**Why this works for 15-30**: Everyone gets to share, builds emotional connection
|
||||
- Groups of 5-6 people
|
||||
- Rotating prompts (7 min each):
|
||||
1. "Tell about a gift you received that changed something for you"
|
||||
2. "What do you love giving to others?"
|
||||
3. "What's a need in your life right now?"
|
||||
- Facilitator floats between groups, notes emerging themes
|
||||
- **Key**: You're mining for real stories to share later + helping people see their own gifting patterns
|
||||
|
||||
#### Activity 2: Skills & Needs Mapping (25 min, 6:45-7:10)
|
||||
**Why this works for 15-30**: Creates a visual resource everyone can reference
|
||||
- Large paper/poster board on wall with categories: Skills, Time, Items, Food/Meals, Housing, Other
|
||||
- Everyone gets sticky notes in two colors:
|
||||
- Green: "I can offer..." (skills, time, items, connections, meals, space)
|
||||
- Yellow: "I'm looking for..." (needs, wishes, dreams)
|
||||
- Encourage including basic needs: "Can you cook for someone once a week?" "Need help with groceries?" "Have a spare room?" "Looking for meal support?"
|
||||
- Write 3-5 of each, post on board
|
||||
- Group browses and makes verbal connections: "Oh! I can help with that!"
|
||||
- Take photo of completed board for reference
|
||||
- **Note**: This mirrors our long-term goal of supporting people's basic livelihoods through gifting
|
||||
|
||||
#### Transition + Vision (10 min, 7:10-7:20)
|
||||
**Your brief speaking moment**
|
||||
- Share 2-3 stories you heard from the circles
|
||||
- Connect to bigger vision: "What if this was happening every day?"
|
||||
- Show the board: "This is $X,XXX worth of value that could be exchanged without money"
|
||||
- **Paint the long-term picture**:
|
||||
- "Imagine a network where basic needs—food, housing, skills—are met through mutual support"
|
||||
- "We're starting with skills and connections, but some of us are already working toward providing regular meals and basic livelihoods for people without money changing hands"
|
||||
- "Tonight is practice. The real goal? A sustainable culture where no one goes without because we take care of each other"
|
||||
- Introduce Time Safari as a tool to keep this going beyond today and track progress toward these bigger goals
|
||||
|
||||
#### Activity 3: App Onboarding + First Connections (30 min, 7:20-7:50)
|
||||
**Why this works for 15-30**: Small enough for hands-on help
|
||||
- QR code displayed large (or multiple printed)
|
||||
- 2-3 helper "tech buddies" circulate (recruit in advance?)
|
||||
- Everyone completes 3 tasks:
|
||||
1. Download + create profile
|
||||
2. Record one gift (from earlier story or the event itself)
|
||||
3. Connect with at least 2 people in the room
|
||||
- Gamify: "First table to have everyone connected gets first pick from gift table"
|
||||
|
||||
#### Activity 4: Immediate Gift Exchange (15 min, 7:50-8:05)
|
||||
**Why this works for 15-30**: Personal and warm
|
||||
- Everyone brought a small gift
|
||||
- Lay them on a central table
|
||||
- One by one, people choose something that calls to them
|
||||
- As you take it, record it in the app and thank the giver
|
||||
- Creates immediate app usage + demonstrates receiving without reciprocating
|
||||
|
||||
#### Activity 5: Project Spark (15 min, 8:05-8:20)
|
||||
**Why this works for 15-30**: Action-oriented closure
|
||||
- Quick brainstorm: "What could we do together in the next month?"
|
||||
- Seed specific ideas that align with long-term vision:
|
||||
- "Community meal program - can we commit to providing X meals/week for someone in need?"
|
||||
- "Rotating dinner hosts - take turns cooking for the group"
|
||||
- "Skill-share workshops"
|
||||
- "Tool library or resource sharing"
|
||||
- Vote on top 2-3 ideas (hands raised)
|
||||
- Volunteers step up to champion each
|
||||
- Create the projects in Time Safari right there
|
||||
- Others commit time/skills and record in app
|
||||
- **Connect to vision**: "These projects are how we practice. Our long-term goal is to support entire livelihoods this way—50 people living without needing money for basics. It starts here."
|
||||
|
||||
#### Closing Circle (10 min, 8:20-8:30)
|
||||
- Stand in circle
|
||||
- Quick popcorn sharing: "One word for how you feel right now"
|
||||
- **Hand out take-home card** (see Materials section) with long-term vision and ways to participate
|
||||
- Invitation to next steps:
|
||||
- Try to record 3 gifts this week
|
||||
- Consider: Could you provide a meal for someone? Receive meals from others?
|
||||
- Bring one friend to next month's gathering
|
||||
- Join [communication channel - email list? group text?]
|
||||
- "This is bigger than tonight. We're building toward basic livelihoods supported by community, not money. You're now part of that."
|
||||
- Group photo
|
||||
|
||||
### Next Steps
|
||||
- [ ] Generate prep steps before event, with deadlines in "days before event"
|
||||
- [ ] Generate materials checklist
|
||||
|
||||
### Prep Work Needed (Before Feb 13)
|
||||
1. **App readiness**:
|
||||
- Test the connection flow with fresh users
|
||||
- Ensure QR-based friend connection works smoothly
|
||||
- Have a few demo gifts/projects already in your profile
|
||||
- Test on both iOS and Android
|
||||
|
||||
2. **Helper recruitment**:
|
||||
- Identify 2-3 "tech buddies" who can help during onboarding
|
||||
- Brief them beforehand on common issues
|
||||
- Give them your phone number in case of server problems
|
||||
|
||||
3. **Story prep**:
|
||||
- Prepare your own 2-minute version of your gift economy vision
|
||||
- Have 1-2 powerful examples of gifts that meant a lot to you
|
||||
- Practice keeping it warm and personal, not preachy
|
||||
|
||||
4. **Logistics**:
|
||||
- Venue confirmed (someone's home? community center?)
|
||||
- Seating arrangement for circles (move furniture?)
|
||||
- WiFi password visible
|
||||
- Backup plan if WiFi fails (hotspot? offline capability?)
|
||||
|
||||
5. **Communication**:
|
||||
- Send reminder 3 days before with:
|
||||
- "Bring a small gift to share"
|
||||
- "Think of a gift story"
|
||||
- "Optional: pre-install Time Safari" (link)
|
||||
- Create follow-up plan: email list? group chat? next event date?
|
||||
|
||||
### Success Metrics for This Event
|
||||
- **Quantity**:
|
||||
- 80%+ attendees download app
|
||||
- Average 3+ connections made per person
|
||||
- At least 2 projects created
|
||||
- 50%+ record at least one gift during event
|
||||
|
||||
- **Quality**:
|
||||
- People linger and keep talking after "official" end
|
||||
- At least 3 people volunteer to help with next event
|
||||
- You overhear conversations about helping each other
|
||||
- Someone says "I want to bring my [friend/neighbor] next time"
|
||||
|
||||
- **Follow-up** (measure 1 week later):
|
||||
- 50%+ have opened app again
|
||||
- 30%+ have recorded another gift
|
||||
- Someone initiates a connection outside the event
|
||||
|
||||
### Potential Challenges & Solutions
|
||||
|
||||
**Challenge**: "Tech-resistant attendees"
|
||||
- **Solution**: Celebrate: "That's fine! You can participate by writing on the skills board"; assign a buddy to help; offer to help them set up at end
|
||||
|
||||
### Alternative: If Only 10-12 People Show Up
|
||||
- Skip breaking into small groups for story circle (do it all together)
|
||||
- More intimate = more time for each person
|
||||
- Can do project creation as a group discussion
|
||||
- Still highly effective, just different energy
|
||||
|
||||
### Alternative: If 30+ People Show Up
|
||||
- Recruit more helpers on the spot
|
||||
- Extend app onboarding time (add 15 min)
|
||||
- Do two simultaneous gift exchanges (split the room)
|
||||
- Create more breakout space for story circles
|
||||
|
||||
---
|
||||
|
||||
## Take-Home Card: "The Long-Term Vision"
|
||||
|
||||
**Design**: Postcard-sized (4"x6"), printed front and back
|
||||
|
||||
### Front Side
|
||||
|
||||
```
|
||||
🎁 GIFT ECONOMIES
|
||||
Building a Culture of Mutual Support
|
||||
|
||||
Tonight you experienced:
|
||||
✓ Sharing stories of generosity
|
||||
✓ Mapping skills and needs
|
||||
✓ Giving and receiving without expectation
|
||||
✓ Creating projects together
|
||||
|
||||
This is just the beginning.
|
||||
```
|
||||
|
||||
### Back Side
|
||||
|
||||
```
|
||||
THE LONG-TERM VISION
|
||||
|
||||
We're working toward a world where:
|
||||
|
||||
🍽️ BASIC NEEDS MET
|
||||
Regular meals provided for those who need them—
|
||||
no money required, just community care.
|
||||
|
||||
🏠 SUSTAINABLE LIVELIHOODS
|
||||
50 people supported entirely through gifts—
|
||||
food, housing, skills, connection—
|
||||
demonstrating that monetary exchange is optional.
|
||||
|
||||
💪 CULTURAL TRANSFORMATION
|
||||
A shift from "What can I buy?" to "Who can I help?"
|
||||
From isolation to interdependence.
|
||||
From scarcity thinking to abundance through sharing.
|
||||
|
||||
📱 YOUR NEXT STEPS
|
||||
|
||||
□ Record 3 gifts this week in Time Safari
|
||||
□ Identify one person whose basic need you could help meet
|
||||
□ Be willing to receive help yourself
|
||||
□ Share this vision with one friend
|
||||
□ Consider: Could you provide/receive a meal weekly?
|
||||
|
||||
"Basic livelihoods supported without money,
|
||||
in a sustainable way so people are confident
|
||||
they can have that support for all their lives."
|
||||
|
||||
---
|
||||
Time Safari App: [QR CODE]
|
||||
Questions: [YOUR EMAIL]
|
||||
Next Gathering: [DATE]
|
||||
|
||||
This is about aligning hearts & minds
|
||||
with the things that do the most good.
|
||||
```
|
||||
|
||||
### Design Notes
|
||||
- Keep it simple and readable
|
||||
- Use warm, inviting colors (earth tones, not corporate)
|
||||
- The QR code should be prominent on back
|
||||
- Print on cardstock so it feels substantial
|
||||
- Consider having a local artist illustrate it (practice gift economy in creating it!)
|
||||
|
||||
---
|
||||
|
||||
## Long-Term Vision Integration Points
|
||||
|
||||
Throughout the event, naturally reference these goals:
|
||||
|
||||
**During story circles**: If someone shares about receiving meal support, highlight it: "This is exactly what we're scaling up—imagine this as a regular system, not just crisis support."
|
||||
|
||||
**During skills board**: Point out food/meal offers: "These are the building blocks of supporting someone's basic livelihood without money."
|
||||
|
||||
**During vision talk**: Use specific numbers: "Our goal isn't just connection—it's to support 50 people's basic livelihoods entirely through gifts within [timeframe]. Tonight we practice the skills that make that possible."
|
||||
|
||||
**During project creation**: Encourage meal-related projects: "A rotating dinner schedule where we commit to 5 meals/week for one person? That's 1/21st of a full basic livelihood. We can scale this."
|
||||
|
||||
**In follow-up emails**:
|
||||
- Week 1: "Last week we practiced. This week, let's identify one person whose basic needs we could help meet."
|
||||
- Month 1: "How many meals have our network provided this month? Let's count the impact."
|
||||
- Month 3: "We're tracking toward supporting X% of one person's basic needs. Here's what's next."
|
||||
|
||||
---
|
||||
|
||||
## Measuring Long-Term Progress (Post-Event)
|
||||
|
||||
Track how tonight's activities ladder up to bigger goals:
|
||||
|
||||
- **Immediate** (Week 1): Gifts recorded, connections made, projects created
|
||||
- **Short-term** (Month 1): Meals provided, basic needs met, trust deepening
|
||||
- **Medium-term** (Month 3-6): Someone receives regular meal support, housing assistance, or skill support that replaces a paid expense
|
||||
- **Long-term** (Year 1-2): First person's basic livelihood substantially supported (quantify % of needs met without money)
|
||||
- **Ultimate** (Years 3-5): 50 people living with confidence that their community will support them
|
||||
|
||||
Tonight is the first small step toward that last goal.
|
||||
@@ -9,8 +9,16 @@ tasks:
|
||||
- goal is to be 100% giving-supported (maybe with decentralized system architectures)
|
||||
- accept feedback
|
||||
|
||||
- In-person giving events :
|
||||
details : progress/PROJECT-giving-events.md
|
||||
subtasks :
|
||||
- interview & match?
|
||||
- talk?
|
||||
- give-away items?
|
||||
- first event due:2026-02-13
|
||||
|
||||
- 1000 P2P mesh network implementation id:mesh-network :
|
||||
details: tech/progress/PROJECT-mesh-network.md
|
||||
details : tech/progress/PROJECT-mesh-network.md
|
||||
blocks : ref:#transcendent-action
|
||||
subtasks :
|
||||
- 200 Protocol foundation and message design
|
||||
@@ -45,9 +53,8 @@ tasks:
|
||||
|
||||
- identify & help local activist influencers
|
||||
|
||||
- next board meeting :
|
||||
- don't show "only admin" visibility (only show auditable stats)
|
||||
- include a total accounting of money, eg time as money, etc for investment-minded people
|
||||
- accounting report (board meeting?) due:2026-06-01 :
|
||||
- include a total accounting of money, eg time as money, for investment-minded people
|
||||
|
||||
- Alpha Assembly :
|
||||
- memento?
|
||||
@@ -56,22 +63,11 @@ tasks:
|
||||
- during : I scan and register them, recognize their donation
|
||||
- supertask : crowd-funder for time
|
||||
|
||||
- correlate with many other projects :
|
||||
- ShareBay.org & HonorPay.org
|
||||
- justserve.org
|
||||
- magnova.org
|
||||
- GiveMagix.com
|
||||
- BuyNothingProject.org
|
||||
- Samaritan's Purse tracks gifts https://www.samaritanspurse.org/operation-christmas-child/activation
|
||||
|
||||
- 01 Walk through example of traceable donation :
|
||||
blocks : ref:#minimal-lifestyle-events
|
||||
|
||||
- 01 Record overall financials, traded vs gifted
|
||||
|
||||
- 01 Page on submitting gratitude id:gratitude-submission :
|
||||
blocks : ref:#transcendent-action
|
||||
|
||||
- Make the ObservableHQ renderings useful :
|
||||
blocks : ref:#transcendent-action
|
||||
awaits :
|
||||
@@ -99,10 +95,16 @@ tasks:
|
||||
- 02 Page on maximizing gifts & links to frugal living :
|
||||
blocks : ref:#transcendent-action
|
||||
|
||||
- Collaboration with other platforms (eg Magnova.org, CompassionGames.org) :
|
||||
- Coordinate with many other projects :
|
||||
blocks : ref:#transcendent-action
|
||||
subtasks :
|
||||
- page of instructions for semantics and/or endpoints
|
||||
- ShareBay.org & HonorPay.org
|
||||
- justserve.org
|
||||
- magnova.org
|
||||
- GiveMagix.com
|
||||
- BuyNothingProject.org
|
||||
- Samaritan's Purse tracks gifts https://www.samaritanspurse.org/operation-christmas-child/activation
|
||||
- CompassionGames.org
|
||||
|
||||
- Write & create other media :
|
||||
blocks : ref:#transcendent-action
|
||||
|
||||
@@ -42,16 +42,24 @@ Endorser.ch is an API for creating and querying claims in privacy-preserving way
|
||||
- Visibility can be granted or revoked between users
|
||||
- Claims may be visible but with identifiers hidden
|
||||
|
||||
### Location-Based Features
|
||||
### Personal-Data Features in Separate Endpoints
|
||||
|
||||
There are other features that gather personal data like names and interests and locations, but these are separated into a different database and they have APIs on a different domain, eg `partner-api.endorser.ch`.
|
||||
|
||||
#### Location-Based Features
|
||||
- System supports geospatial data for claims and profiles
|
||||
- Location data can be searched and retrieved in privacy-preserving ways
|
||||
- Tile-based location indexing for efficient spatial queries
|
||||
|
||||
### User Profiles
|
||||
#### User Profiles
|
||||
- Users can create and update profiles with descriptions and locations
|
||||
- Profiles are searchable by text and location
|
||||
- Visibility rules apply to profile data
|
||||
|
||||
#### Onboarding Meetings
|
||||
|
||||
See [the onboarding meetings doc](./README-onboarding-meeting.md).
|
||||
|
||||
## Implementation Goals
|
||||
|
||||
1. Simple-to-deploy service with minimal dependencies
|
||||
|
||||
21
tech/README-onboarding-meeting.md
Normal file
21
tech/README-onboarding-meeting.md
Normal file
@@ -0,0 +1,21 @@
|
||||
# Onboarding Meeting
|
||||
|
||||
This is a part of the [Gift Economies app](./README-time-safari-endorser.md).
|
||||
|
||||
This is a tool whereby an organizer can gather a number of attendees into a meeting together, where they can all get registered by the organizer and they can give all others visibility into their activities in the app. The connections are all one-to-one and managed individually, but this is a way to allow the permissions to be done in bulk.
|
||||
|
||||
## Organizer Steps
|
||||
|
||||
- Organizer creates a meeting. They choose a title & password. They also choose an expiration time -- ideally in the next few hours, but at most 24 hours in the future. (The time is constrained because people often choose passwords that can be hacked.)
|
||||
|
||||
- Organizer can see when new people want to join a meeting, and can then admit each person.
|
||||
|
||||
- When admitting, they have the option of registering a user.
|
||||
|
||||
- The system will automatically make the organizer visible to the attendee.
|
||||
|
||||
## Attendee Steps
|
||||
|
||||
- Attendee goes to the meeting link (or finds the meeting and enters the password). Once the organizer allows them in, they see existing people.
|
||||
|
||||
- Periodically, the app checks the server for anyone who is not already in their contacts, and prompts them to see if they'd like to add that person and allow them visibility into the attendee's actions.
|
||||
Reference in New Issue
Block a user