Initial commit — Hamkadr (همکادر) healthcare-staffing marketplace

ASP.NET Core 10 Razor Pages + PostgreSQL/EF Core. RTL Persian, Jalali dates, self-hosted Vazirmatn, teal/coral brand. Features: - Shift listings: browse/filter (city, district, role, type, pay), weekly Jalali calendar, detail + interest handoff, near-me distance sort - Hiring (استخدام) listings with employment type + salary range - Pattern-engine recommendations + anonymous interest tracking (visitor cookie) - Heuristic Persian listing-parser + admin queue (raw channel post → shift/job) - Phone-OTP cookie auth + visitor-history linking + profile Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-03 01:43:55 +03:30
commit 2fb86a435e
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+using System.Text.RegularExpressions;
+using JobsMedical.Web.Models;
+
+namespace JobsMedical.Web.Services;
+
+/// <summary>Structured guess extracted from a raw channel post. All fields are best-effort.</summary>
+public class ParsedListing
+{
+    public ListingKind Kind { get; set; } = ListingKind.Shift;
+    public string? RoleName { get; set; }
+    public ShiftType? ShiftType { get; set; }
+    public EmploymentType? EmploymentType { get; set; }
+    public long? PayAmount { get; set; }        // shift pay or single salary figure
+    public bool PayNegotiable { get; set; }
+    public string? CityName { get; set; }
+    public string? DistrictName { get; set; }
+    public string? Phone { get; set; }
+    public List<string> Notes { get; set; } = new();  // what was/wasn't detected (shown to admin)
+}
+
+/// <summary>
+/// Turns a messy Persian channel/Divar post into a structured listing guess. This is the
+/// Stage-1 implementation: transparent keyword + regex heuristics, no AI dependency (important
+/// since LLM APIs are blocked from Iran). A future LlmListingParser can implement the same
+/// interface and be swapped in via DI without touching the admin queue.
+/// </summary>
+public interface IListingParser
+{
+    ParsedListing Parse(string rawText, IEnumerable<string> knownRoles,
+                        IEnumerable<string> knownCities, IEnumerable<string> knownDistricts);
+}
+
+public class HeuristicListingParser : IListingParser
+{
+    public ParsedListing Parse(string raw, IEnumerable<string> knownRoles,
+        IEnumerable<string> knownCities, IEnumerable<string> knownDistricts)
+    {
+        var p = new ParsedListing();
+        var text = Normalize(raw);
+
+        // --- Kind: shift vs hiring ---
+        bool jobSignals = ContainsAny(text, "استخدام", "جذب", "دعوت به همکاری", "تمام وقت", "تمام‌وقت", "قرارداد", "ماهانه", "حقوق ثابت");
+        bool shiftSignals = ContainsAny(text, "شیفت", "آنکال", "انکال", "نوبت", "کشیک");
+        p.Kind = (jobSignals && !shiftSignals) ? ListingKind.Job : ListingKind.Shift;
+        p.Notes.Add(p.Kind == ListingKind.Job ? "نوع: استخدام (تشخیص خودکار)" : "نوع: شیفت (تشخیص خودکار)");
+
+        // --- Role (longest match first so «پزشک متخصص» beats «پزشک») ---
+        foreach (var role in knownRoles.OrderByDescending(r => r.Length))
+        {
+            if (text.Contains(Normalize(role))) { p.RoleName = role; break; }
+        }
+        if (p.RoleName is null && ContainsAny(text, "پزشک", "دکتر")) p.RoleName = "پزشک عمومی";
+        p.Notes.Add(p.RoleName is null ? "نقش: تشخیص داده نشد" : $"نقش: {p.RoleName}");
+
+        // --- Shift type ---
+        if (ContainsAny(text, "آنکال", "انکال")) p.ShiftType = Models.ShiftType.OnCall;
+        else if (text.Contains("شب")) p.ShiftType = Models.ShiftType.Night;
+        else if (text.Contains("عصر")) p.ShiftType = Models.ShiftType.Evening;
+        else if (ContainsAny(text, "صبح", "روز")) p.ShiftType = Models.ShiftType.Day;
+
+        // --- Employment type ---
+        if (ContainsAny(text, "پاره وقت", "پاره‌وقت", "پارت تایم")) p.EmploymentType = Models.EmploymentType.PartTime;
+        else if (text.Contains("طرح")) p.EmploymentType = Models.EmploymentType.Plan;
+        else if (text.Contains("قرارداد")) p.EmploymentType = Models.EmploymentType.Contract;
+        else if (ContainsAny(text, "تمام وقت", "تمام‌وقت")) p.EmploymentType = Models.EmploymentType.FullTime;
+
+        // --- City / district ---
+        p.CityName = knownCities.FirstOrDefault(c => text.Contains(Normalize(c)));
+        p.DistrictName = knownDistricts.OrderByDescending(d => d.Length)
+            .FirstOrDefault(d => text.Contains(Normalize(d)));
+
+        // --- Pay ---
+        if (ContainsAny(text, "توافقی", "توافق")) { p.PayNegotiable = true; p.Notes.Add("حقوق: توافقی"); }
+        else
+        {
+            var amount = ExtractAmount(text);
+            if (amount is not null) { p.PayAmount = amount; p.Notes.Add($"حقوق تخمینی: {amount:#,0} تومان"); }
+            else p.Notes.Add("حقوق: تشخیص داده نشد");
+        }
+
+        // --- Phone ---
+        var phone = Regex.Match(ToLatinDigits(text), @"0?9\d{9}");
+        if (phone.Success) p.Phone = phone.Value;
+
+        return p;
+    }
+
+    /// <summary>Pull a Toman figure out of free text, handling «میلیون» and Persian digits.</summary>
+    private static long? ExtractAmount(string text)
+    {
+        var latin = ToLatinDigits(text);
+        // e.g. "۲ میلیون" / "2.5 میلیون"
+        var million = Regex.Match(latin, @"(\d+(?:[.,]\d+)?)\s*میلیون");
+        if (million.Success && double.TryParse(million.Groups[1].Value.Replace(",", "."),
+                System.Globalization.NumberStyles.Any, System.Globalization.CultureInfo.InvariantCulture, out var m))
+            return (long)(m * 1_000_000);
+
+        // Otherwise the largest plain number that looks like money (>= 6 digits after removing separators).
+        long best = 0;
+        foreach (Match num in Regex.Matches(latin, @"[\d٬,،.]{6,}"))
+        {
+            var digits = Regex.Replace(num.Value, @"[^\d]", "");
+            if (digits.Length >= 6 && long.TryParse(digits, out var v) && v > best) best = v;
+        }
+        return best > 0 ? best : null;
+    }
+
+    private static string Normalize(string s) => s
+        .Replace('ي', 'ی').Replace('ك', 'ک').Replace('‌', ' ').Trim();
+
+    private static bool ContainsAny(string text, params string[] needles)
+        => needles.Any(n => text.Contains(n));
+
+    private static string ToLatinDigits(string s)
+    {
+        var chars = s.ToCharArray();
+        for (var i = 0; i < chars.Length; i++)
+        {
+            if (chars[i] >= '۰' && chars[i] <= '۹') chars[i] = (char)('0' + (chars[i] - '۰'));
+            else if (chars[i] >= '٠' && chars[i] <= '٩') chars[i] = (char)('0' + (chars[i] - '٠'));
+        }
+        return new string(chars);
+    }
+}