8b7252dad4
Go app for capturing and archiving HSA-eligible receipts: OIDC/PKCE auth against Authelia, SQLite storage with dual-write (filesystem + DB blob), mobile-first upload, and DB export. Adds AI receipt classification: a config.json catalog of people and categories (seeded into the DB on startup), a prompt builder that derives name-order/initial variants from the data (with same-surname ambiguity handling), and an Anthropic tool-use client behind POST /classify. Tests run against a mock endpoint; a live integration test is env-gated to the cheapest model. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
105 lines
2.8 KiB
Go
105 lines
2.8 KiB
Go
package web
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import (
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"encoding/json"
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"io"
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"net/http"
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"strings"
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"time"
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"maisym.com/hsa/internal/storage"
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)
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// classifyResponse is the JSON returned to the upload page to pre-fill the form.
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// IDs map the classifier's label suggestions onto the live lookup rows; they are
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// null when the classifier returned nothing or the label has no matching row.
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type classifyResponse struct {
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Amount *string `json:"amount"`
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Date *string `json:"date"`
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CategoryID *int64 `json:"category_id"`
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PersonID *int64 `json:"person_id"`
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Category string `json:"category"` // label, for display
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Person string `json:"person"` // label, for display
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RawName string `json:"raw_name"`
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RawDate string `json:"raw_date"`
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RawAmount string `json:"raw_amount"`
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}
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// handleClassify accepts an uploaded receipt image and returns suggested form
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// values from the AI classifier. It mutates no state — the user still reviews and
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// submits via POST /upload.
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func (s *Server) handleClassify(w http.ResponseWriter, r *http.Request) {
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if s.classifier == nil {
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http.Error(w, "classification not configured", http.StatusServiceUnavailable)
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return
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}
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r.Body = http.MaxBytesReader(w, r.Body, s.cfg.MaxUploadBytes)
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if err := r.ParseMultipartForm(10 << 20); err != nil {
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http.Error(w, "upload too large or malformed", http.StatusBadRequest)
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return
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}
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file, _, err := r.FormFile("receipt")
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if err != nil {
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http.Error(w, "attach a receipt image or PDF", http.StatusBadRequest)
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return
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}
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defer file.Close()
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data, err := io.ReadAll(file)
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if err != nil {
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http.Error(w, "could not read the uploaded file", http.StatusBadRequest)
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return
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}
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mimeType := detectMime(data)
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if !allowedMime(mimeType) {
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http.Error(w, "only images and PDFs are allowed", http.StatusUnsupportedMediaType)
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return
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}
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sug, err := s.classifier.Classify(r.Context(), time.Now(), data, mimeType)
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if err != nil {
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s.serverError(w, "classify receipt", err)
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return
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}
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cats, people, err := s.lookups()
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if err != nil {
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s.serverError(w, "load lookups", err)
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return
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}
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out := classifyResponse{
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Amount: sug.Amount,
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Date: sug.Date,
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Category: sug.Category,
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RawName: sug.RawName,
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RawDate: sug.RawDate,
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RawAmount: sug.RawAmount,
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}
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if id, ok := idForLabel(sug.Category, cats); ok {
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out.CategoryID = &id
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}
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if sug.Person != nil {
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if id, ok := idForLabel(*sug.Person, people); ok {
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out.PersonID = &id
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out.Person = *sug.Person
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}
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}
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w.Header().Set("Content-Type", "application/json")
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_ = json.NewEncoder(w).Encode(out)
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}
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// idForLabel finds a lookup row by case-insensitive label match.
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func idForLabel(label string, set []storage.Lookup) (int64, bool) {
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label = strings.TrimSpace(label)
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for _, l := range set {
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if strings.EqualFold(l.Label, label) {
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return l.ID, true
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}
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}
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return 0, false
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}
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