feat(backend): add LLM provider abstraction, contextual ranking and explanations

Add a pluggable LLM provider with an offline template fallback, prompt builder, contextual match scoring (area/location boosts, availability), per-solution explanations and in-memory request limiting for cost control.
2026-10-04 02:52:45 +02:00
parent 182c26d9f8
commit 03e2d66ca4
11 changed files with 385 additions and 23 deletions
@@ -0,0 +1,13 @@
+namespace TarninaHub.Application.Matchmaking;
+
+public interface ILlmProvider
+{
+    /// <summary>True when a real provider is configured (API key etc.).</summary>
+    bool IsConfigured { get; }
+
+    /// <summary>Returns the completion text or null when unavailable.</summary>
+    Task<string?> CompleteAsync(
+        string systemPrompt,
+        string userPrompt,
+        CancellationToken cancellationToken);
+}
@@ -0,0 +1,10 @@
+namespace TarninaHub.Application.Matchmaking;
+
+public interface ILlmRequestLimiter
+{
+    /// <summary>
+    /// Tries to reserve one LLM request within the current window.
+    /// Returns false when the limit is exceeded (caller should fall back).
+    /// </summary>
+    bool TryAcquire();
+}
@@ -0,0 +1,33 @@
+namespace TarninaHub.Application.Matchmaking;
+
+public sealed record LlmPrompt(string System, string User);
+
+public static class MatchPromptBuilder
+{
+    private const string SystemPrompt =
+        "Jesteś asystentem Małopolskiego Hubu Innowacji Społecznych. " +
+        "Wyjaśnij po polsku, prostym językiem (maks. 2 zdania), dlaczego proponowana " +
+        "innowacja pasuje do zgłoszonej potrzeby. Nie wymyślaj faktów.";
+
+    public static LlmPrompt BuildExplanation(
+        string problemTitle,
+        string problemDescription,
+        string challengeId,
+        string innovationTitle,
+        string innovationSummary,
+        string stage,
+        double score)
+    {
+        var user =
+            $"Potrzeba: {problemTitle}\n" +
+            $"Opis: {problemDescription}\n" +
+            $"Obszar: {challengeId}\n" +
+            $"Proponowana innowacja: {innovationTitle}\n" +
+            $"Streszczenie: {innovationSummary}\n" +
+            $"Etap: {stage}\n" +
+            $"Ocena dopasowania: {score:0.00}\n" +
+            "Uzasadnij krótko dopasowanie.";
+
+        return new LlmPrompt(SystemPrompt, user);
+    }
+}
@@ -0,0 +1,37 @@
+namespace TarninaHub.Application.Matchmaking;
+
+/// <summary>
+/// Combines semantic similarity with context signals (area, location) and
+/// availability into a final 0..1 match score.
+/// </summary>
+public static class MatchScoring
+{
+    private const double ChallengeBoost = 0.10;
+    private const double LocationBoost = 0.05;
+
+    public static double Combine(
+        double semanticScore,
+        bool challengeMatch,
+        bool locationMatch,
+        bool available)
+    {
+        if (!available)
+        {
+            return 0;
+        }
+
+        var score = semanticScore;
+
+        if (challengeMatch)
+        {
+            score += ChallengeBoost;
+        }
+
+        if (locationMatch)
+        {
+            score += LocationBoost;
+        }
+
+        return Math.Clamp(score, 0, 1);
+    }
+}
@@ -0,0 +1,15 @@
+namespace TarninaHub.Application.Matchmaking;
+
+/// <summary>
+/// Default provider used when no external LLM is configured. Keeps the system
+/// fully offline/deterministic; matchmaking falls back to template rationales.
+/// </summary>
+public sealed class NullLlmProvider : ILlmProvider
+{
+    public bool IsConfigured => false;
+
+    public Task<string?> CompleteAsync(
+        string systemPrompt,
+        string userPrompt,
+        CancellationToken cancellationToken) => Task.FromResult<string?>(null);
+}
@@ -0,0 +1,29 @@
+namespace TarninaHub.Application.Matchmaking;
+
+/// <summary>
+/// Deterministic, offline explanation of "why this fits". Used as the default
+/// and as a fallback when the LLM is unavailable or rate-limited.
+/// </summary>
+public static class RationaleBuilder
+{
+    public static string Build(bool challengeMatch, bool locationMatch, double score)
+    {
+        var reasons = new List<string>();
+
+        if (challengeMatch)
+        {
+            reasons.Add("ten sam obszar problemowy");
+        }
+
+        if (locationMatch)
+        {
+            reasons.Add("zbliżona lokalizacja");
+        }
+
+        reasons.Add(score >= 0.3
+            ? "wysoka zbieżność opisu potrzeby"
+            : "zbieżność semantyczna opisu");
+
+        return "Proponowane dopasowanie: " + string.Join(", ", reasons) + ".";
+    }
+}
@@ -5,6 +5,7 @@ using TarninaHub.Application.Abstractions;
 using TarninaHub.Application.Matchmaking;
 using TarninaHub.Infrastructure.Auth;
 using TarninaHub.Infrastructure.Events;
+using TarninaHub.Infrastructure.Llm;
 using TarninaHub.Infrastructure.Persistence;
 using TarninaHub.Infrastructure.Settings;

@@ -19,6 +20,23 @@ public static class DependencyInjection
        services.Configure<SurrealDbSettings>(configuration.GetSection("SurrealDb"));
        services.Configure<AuthSettings>(configuration.GetSection("Auth"));

+        var llmSettings = configuration.GetSection("Llm").Get<LlmSettings>() ?? new LlmSettings();
+        services.Configure<LlmSettings>(configuration.GetSection("Llm"));
+        services.AddSingleton<ILlmRequestLimiter>(
+            new InMemoryLlmRequestLimiter(llmSettings.MaxRequestsPerMinute));
+
+        if (llmSettings.IsConfigured)
+        {
+            services.AddHttpClient<OpenAiCompatibleLlmProvider>(
+                client => client.Timeout = TimeSpan.FromSeconds(llmSettings.TimeoutSeconds));
+            services.AddSingleton<ILlmProvider>(
+                provider => provider.GetRequiredService<OpenAiCompatibleLlmProvider>());
+        }
+        else
+        {
+            services.AddSingleton<ILlmProvider, NullLlmProvider>();
+        }
+
        var settings = configuration.GetSection("SurrealDb").Get<SurrealDbSettings>()
            ?? new SurrealDbSettings();

@@ -0,0 +1,42 @@
+using TarninaHub.Application.Matchmaking;
+
+namespace TarninaHub.Infrastructure.Llm;
+
+/// <summary>
+/// In-memory sliding-window request limiter (per instance) for LLM cost control.
+/// </summary>
+public sealed class InMemoryLlmRequestLimiter : ILlmRequestLimiter
+{
+    private readonly int _maxPerWindow;
+    private readonly TimeSpan _window;
+    private readonly Queue<DateTimeOffset> _timestamps = new();
+    private readonly Lock _gate = new();
+
+    public InMemoryLlmRequestLimiter(int maxRequestsPerMinute, TimeSpan? window = null)
+    {
+        _maxPerWindow = Math.Max(1, maxRequestsPerMinute);
+        _window = window ?? TimeSpan.FromMinutes(1);
+    }
+
+    public bool TryAcquire()
+    {
+        var now = DateTimeOffset.UtcNow;
+
+        lock (_gate)
+        {
+            while (_timestamps.Count > 0 && now - _timestamps.Peek() > _window)
+            {
+                _timestamps.Dequeue();
+            }
+
+            if (_timestamps.Count >= _maxPerWindow)
+            {
+                return false;
+            }
+
+            _timestamps.Enqueue(now);
+
+            return true;
+        }
+    }
+}
@@ -0,0 +1,23 @@
+namespace TarninaHub.Infrastructure.Llm;
+
+public sealed class LlmSettings
+{
+    public bool Enabled { get; set; }
+
+    /// <summary>Provider identifier, e.g. "openai" (OpenAI-compatible chat API).</summary>
+    public string Provider { get; set; } = "openai";
+
+    public string? ApiKey { get; set; }
+
+    public string BaseUrl { get; set; } = "https://api.openai.com/v1";
+
+    public string Model { get; set; } = "gpt-4o-mini";
+
+    public int MaxTokens { get; set; } = 256;
+
+    public int MaxRequestsPerMinute { get; set; } = 30;
+
+    public int TimeoutSeconds { get; set; } = 20;
+
+    public bool IsConfigured => Enabled && !string.IsNullOrWhiteSpace(ApiKey);
+}
@@ -0,0 +1,88 @@
+using System.Net.Http.Json;
+using System.Text.Json;
+using Microsoft.Extensions.Logging;
+using Microsoft.Extensions.Options;
+using TarninaHub.Application.Matchmaking;
+
+namespace TarninaHub.Infrastructure.Llm;
+
+/// <summary>
+/// OpenAI-compatible chat completion provider. Interchangeable behind
+/// <see cref="ILlmProvider"/> (ADR-0005). The API key is read from
+/// configuration/secrets and never logged.
+/// </summary>
+public sealed class OpenAiCompatibleLlmProvider : ILlmProvider
+{
+    private readonly HttpClient _httpClient;
+    private readonly LlmSettings _settings;
+    private readonly ILogger<OpenAiCompatibleLlmProvider> _logger;
+
+    public OpenAiCompatibleLlmProvider(
+        HttpClient httpClient,
+        IOptions<LlmSettings> settings,
+        ILogger<OpenAiCompatibleLlmProvider> logger)
+    {
+        _httpClient = httpClient;
+        _settings = settings.Value;
+        _logger = logger;
+    }
+
+    public bool IsConfigured => _settings.IsConfigured;
+
+    public async Task<string?> CompleteAsync(
+        string systemPrompt,
+        string userPrompt,
+        CancellationToken cancellationToken)
+    {
+        if (!IsConfigured)
+        {
+            return null;
+        }
+
+        var endpoint = _settings.BaseUrl.TrimEnd('/') + "/chat/completions";
+        var payload = new
+        {
+            model = _settings.Model,
+            max_tokens = _settings.MaxTokens,
+            messages = new object[]
+            {
+                new { role = "system", content = systemPrompt },
+                new { role = "user", content = userPrompt },
+            },
+        };
+
+        try
+        {
+            using var request = new HttpRequestMessage(HttpMethod.Post, endpoint)
+            {
+                Content = JsonContent.Create(payload),
+            };
+            request.Headers.Authorization = new System.Net.Http.Headers.AuthenticationHeaderValue(
+                "Bearer",
+                _settings.ApiKey);
+
+            using var response = await _httpClient.SendAsync(request, cancellationToken);
+
+            if (!response.IsSuccessStatusCode)
+            {
+                _logger.LogWarning("LLM provider returned status {Status}.", (int)response.StatusCode);
+
+                return null;
+            }
+
+            var document = await response.Content.ReadFromJsonAsync<JsonElement>(cancellationToken);
+
+            return document
+                .GetProperty("choices")[0]
+                .GetProperty("message")
+                .GetProperty("content")
+                .GetString();
+        }
+        catch (Exception exception) when (exception is not OperationCanceledException)
+        {
+            _logger.LogWarning(exception, "LLM completion failed; falling back to template rationale.");
+
+            return null;
+        }
+    }
+}
@@ -11,15 +11,21 @@ public sealed class MatchmakingService : IMatchmakingService
    private readonly ISurrealDbClient _client;
    private readonly IEmbeddingProvider _embeddingProvider;
    private readonly ISubmissionService _submissionService;
+    private readonly ILlmProvider _llmProvider;
+    private readonly ILlmRequestLimiter _llmRequestLimiter;

    public MatchmakingService(
        ISurrealDbClient client,
        IEmbeddingProvider embeddingProvider,
-        ISubmissionService submissionService)
+        ISubmissionService submissionService,
+        ILlmProvider llmProvider,
+        ILlmRequestLimiter llmRequestLimiter)
    {
        _client = client;
        _embeddingProvider = embeddingProvider;
        _submissionService = submissionService;
+        _llmProvider = llmProvider;
+        _llmRequestLimiter = llmRequestLimiter;
    }

    public async Task IndexInnovationAsync(string innovationId, CancellationToken cancellationToken)
@@ -130,10 +136,7 @@ public sealed class MatchmakingService : IMatchmakingService
        }

        var maxResults = Math.Clamp(request.MaxResults ?? 5, 1, 20);
-        var queryText = EmbeddingTextBuilder.Build(
-            submission.Title,
-            null,
-            submission.Description);
+        var queryText = EmbeddingTextBuilder.Build(submission.Title, null, submission.Description);

        if (submission.Keywords.Count > 0)
        {
@@ -179,17 +182,37 @@ public sealed class MatchmakingService : IMatchmakingService
            .Where(row => row.Embedding is { Count: > 0 })
            .Select(row => (Item: row, Vector: (IReadOnlyList<float>)row.Embedding!));

-        var ranked = SemanticRanker.Rank(queryVector, candidates, maxResults, minScore: 0.05);
+        var ranked = SemanticRanker
+            .Rank(queryVector, candidates, maxResults * 3, minScore: 0.05)
+            .Select(item =>
+            {
+                var challengeMatch = string.Equals(
+                    NormalizeRecordId(item.Item.Challenge),
+                    submission.ChallengeId,
+                    StringComparison.Ordinal);

-        return ranked
-            .Select(item => new SolutionItem(
+                return (item.Item, ChallengeMatch: challengeMatch, Score: MatchScoring.Combine(item.Score, challengeMatch, false, true));
+            })
+            .OrderByDescending(item => item.Score)
+            .Take(maxResults)
+            .ToList();
+
+        var solutions = new List<SolutionItem>(ranked.Count);
+
+        foreach (var item in ranked)
+        {
+            var rationale = await BuildRationaleAsync(submission, item.Item, item.Score, item.ChallengeMatch, cancellationToken);
+
+            solutions.Add(new SolutionItem(
                item.Item.Id,
                item.Item.Title,
                item.Item.Stage,
                NormalizeRecordId(item.Item.Challenge) ?? string.Empty,
                Math.Round(item.Score, 3),
-                BuildRationale(item.Item.Challenge, submission.ChallengeId)))
-            .ToList();
+                rationale));
+        }
+
+        return solutions;
    }

    private async Task<List<SimilarCaseItem>> RankSimilarCasesAsync(
@@ -216,8 +239,8 @@ public sealed class MatchmakingService : IMatchmakingService
        }

        var response = await _client.RawQuery(
-            "SELECT type::string(id) AS id, title, type::string(challenge) AS challenge, embedding " +
-            "FROM problem WHERE " + string.Join(" AND ", clauses) + ";",
+            "SELECT type::string(id) AS id, title, type::string(challenge) AS challenge, " +
+            "type::string(location) AS location, embedding FROM problem WHERE " + string.Join(" AND ", clauses) + ";",
            parameters,
            cancellationToken);
        response.EnsureAllOks();
@@ -228,23 +251,54 @@ public sealed class MatchmakingService : IMatchmakingService
            .Where(row => row.Embedding is { Count: > 0 })
            .Select(row => (Item: row, Vector: (IReadOnlyList<float>)row.Embedding!));

-        var ranked = SemanticRanker.Rank(queryVector, candidates, maxResults, minScore: 0.05);
+        return SemanticRanker
+            .Rank(queryVector, candidates, maxResults * 3, minScore: 0.05)
+            .Select(item =>
+            {
+                var challengeMatch = string.Equals(
+                    NormalizeRecordId(item.Item.Challenge),
+                    submission.ChallengeId,
+                    StringComparison.Ordinal);
+                var locationMatch = string.Equals(
+                    NormalizeRecordId(item.Item.Location),
+                    submission.LocationId,
+                    StringComparison.Ordinal);

-        return ranked
-            .Select(item => new SimilarCaseItem(
-                item.Item.Id,
-                item.Item.Title,
-                Math.Round(item.Score, 3)))
+                return (item.Item, Score: MatchScoring.Combine(item.Score, challengeMatch, locationMatch, true));
+            })
+            .OrderByDescending(item => item.Score)
+            .Take(maxResults)
+            .Select(item => new SimilarCaseItem(item.Item.Id, item.Item.Title, Math.Round(item.Score, 3)))
            .ToList();
    }

-    private static string BuildRationale(string challenge, string queryChallengeId)
+    private async Task<string> BuildRationaleAsync(
+        SubmissionResponse submission,
+        InnovationRow innovation,
+        double score,
+        bool challengeMatch,
+        CancellationToken cancellationToken)
    {
-        var normalized = NormalizeRecordId(challenge);
+        if (_llmProvider.IsConfigured && _llmRequestLimiter.TryAcquire())
+        {
+            var prompt = MatchPromptBuilder.BuildExplanation(
+                submission.Title,
+                submission.Description,
+                submission.ChallengeId,
+                innovation.Title,
+                innovation.Summary,
+                innovation.Stage,
+                score);

-        return string.Equals(normalized, queryChallengeId, StringComparison.Ordinal)
-            ? "Pasuje obszarowo do zgłoszenia."
-            : "Wysoka zbieżność semantyczna opisu.";
+            var completion = await _llmProvider.CompleteAsync(prompt.System, prompt.User, cancellationToken);
+
+            if (!string.IsNullOrWhiteSpace(completion))
+            {
+                return completion.Trim();
+            }
+        }
+
+        return RationaleBuilder.Build(challengeMatch, locationMatch: false, score);
    }

    private static string? NormalizeRecordId(string? value) =>