initial release

Tools/SearchTool.cs

@@ -0,0 +1,89 @@
+using OpenQuery.Models;
+using OpenQuery.Services;
+
+namespace OpenQuery.Tools;
+
+public class SearchTool
+{
+    private readonly SearxngClient _searxngClient;
+    private readonly EmbeddingService _embeddingService;
+
+    public static string Name => "search";
+    public static string Description => "Search the web for information on a topic";
+
+    public SearchTool(
+        SearxngClient searxngClient,
+        EmbeddingService embeddingService)
+    {
+        _searxngClient = searxngClient;
+        _embeddingService = embeddingService;
+    }
+
+    public async Task<string> ExecuteAsync(string originalQuery, List<string> generatedQueries, int maxResults, int topChunksLimit, Action<string>? onProgress = null)
+    {
+        var allResults = new List<SearxngResult>();
+        
+        foreach (var query in generatedQueries)
+        {
+            onProgress?.Invoke($"[Searching web for '{query}'...]");
+            var results = await _searxngClient.SearchAsync(query, maxResults);
+            allResults.AddRange(results);
+        }
+
+        var uniqueResults = allResults.DistinctBy(r => r.Url).ToList();
+
+        if (uniqueResults.Count == 0)
+            return "No search results found.";
+
+        onProgress?.Invoke($"[Found {uniqueResults.Count} unique results across all queries. Fetching and reading articles...]");
+        var chunks = new List<Chunk>();
+        
+        foreach (var result in uniqueResults)
+        {
+            try
+            {
+                var article = await ArticleService.FetchArticleAsync(result.Url);
+                if (!article.IsReadable || string.IsNullOrEmpty(article.TextContent)) continue;
+                var textChunks = ChunkingService.ChunkText(article.TextContent);
+
+                chunks.AddRange(textChunks.Select(chunkText => new Chunk(chunkText, result.Url, article.Title)));
+            }
+            catch
+            {
+                // ignored
+            }
+        }
+
+        if (chunks.Count == 0)
+            return "Found search results but could not extract readable content.";
+
+        onProgress?.Invoke($"[Extracted {chunks.Count} text chunks. Generating embeddings for semantic search...]");
+        var chunkTexts = chunks.Select(c => c.Content).ToList();
+        var embeddings = await _embeddingService.GetEmbeddingsAsync(chunkTexts);
+        
+        for (var i = 0; i < chunks.Count; i++)
+        {
+            chunks[i] = chunks[i] with { Embedding = embeddings[i] };
+        }
+
+        var queryEmbedding = (await _embeddingService.GetEmbeddingsAsync([originalQuery]))[0];
+        
+        foreach (var chunk in chunks)
+        {
+            chunk.Score = EmbeddingService.CosineSimilarity(queryEmbedding, chunk.Embedding!);
+        }
+
+        var topChunks = chunks.OrderByDescending(c => c.Score).Take(topChunksLimit).ToList();
+        
+        onProgress?.Invoke($"[Found top {topChunks.Count} most relevant chunks overall. Generating answer...]");
+        var context = string.Join("\n\n", topChunks.Select((c, i) => 
+            $"[Source {i + 1}: {c.Title ?? "Unknown"}]({c.SourceUrl})\n{c.Content}"));
+
+        return context;
+    }
+
+    public static string Execute(string argumentsJson)
+    {
+        throw new InvalidOperationException("Use ExecuteAsync instead");
+    }
+}