Add Knowledge Hub books FTS and remove training UI (0.16.0).

Index Assistent/books search.jsonl, expose knowledge hops/catalog in chat, and drop QLoRA/HF training stack.

Co-authored-by: Cursor <cursoragent@cursor.com>

AssistentChatPipeline.cs

@@ -98,6 +98,11 @@ public partial class SwarmAssistentExtension
             }
             AddLayer("skills", skillsBlock.ToString());
             AddLayer("identity", Config.RenderIdentityBlock(pid));
+            string knowledgeLayer = BuildKnowledgeSystemLayer(pid);
+            if (!string.IsNullOrWhiteSpace(knowledgeLayer))
+            {
+                AddLayer("knowledge", knowledgeLayer);
+            }
         }
 
         if (!string.IsNullOrWhiteSpace(packName))
@@ -179,7 +184,7 @@ public partial class SwarmAssistentExtension
         return (ollamaMessages, layers);
     }
 
-    async Task<(string reply, JObject raw, JArray civitaiResults, int systemChars, JObject systemLayers)> RunChatWithHops(
+    async Task<(string reply, JObject raw, JArray civitaiResults, JObject knowledge, int systemChars, JObject systemLayers)> RunChatWithHops(
         Session session,
         string root,
         string modelName,
@@ -238,6 +243,8 @@ public partial class SwarmAssistentExtension
             ?? 0;
         string reply = "";
         JObject lastRaw = null;
+        JArray knowledgeHops = [];
+        JArray knowledgeResults = [];
         int maxHops = slimUtility ? 1 : CfgInt("max_tool_hops", MaxToolHopsFallback);
         HashSet<string> hopDone = new(StringComparer.OrdinalIgnoreCase);
         for (int hop = 0; hop < maxHops; hop++)
@@ -267,7 +274,7 @@ public partial class SwarmAssistentExtension
                     follow = null;
                     break;
                 }
-                follow = await RunToolHop(session, pid, patch, tool, hopDone);
+                follow = await RunToolHop(session, pid, patch, tool, hopDone, knowledgeHops, knowledgeResults);
                 if (follow is not null)
                 {
                     break;
@@ -285,7 +292,9 @@ public partial class SwarmAssistentExtension
             messages.Add(new JObject { ["role"] = "assistant", ["content"] = assistantContent });
             messages.Add(new JObject { ["role"] = "user", ["content"] = follow });
         }
-        return (reply, lastRaw, [], systemChars, systemLayers);
+        JObject knowledge = BuildKnowledgeResponse(pid, knowledgeHops, knowledgeResults);
+        JArray civitai = CivitaiResultsShim(knowledgeResults);
+        return (reply, lastRaw, civitai, knowledge, systemChars, systemLayers);
     }
 
     static string BuildRetrieveQuery(JArray userMessages, string contextJson, string packName = null)
@@ -413,7 +422,9 @@ public partial class SwarmAssistentExtension
         string pid,
         JObject patch,
         string tool,
-        HashSet<string> hopDone)
+        HashSet<string> hopDone,
+        JArray knowledgeHops = null,
+        JArray knowledgeResults = null)
     {
         if (tool == "ask_settings")
         {
@@ -452,6 +463,35 @@ public partial class SwarmAssistentExtension
                 + "omit ask:inventory unless you need a different query.\n```json\n"
                 + rows.ToString(Newtonsoft.Json.Formatting.None) + "\n```";
         }
+        if (tool == "ask_knowledge")
+        {
+            string q = patch?["knowledge_query"]?.ToString()?.Trim()
+                ?? patch?["example_query"]?.ToString()?.Trim()
+                ?? patch?["memory_query"]?.ToString()?.Trim()
+                ?? "";
+            string rating = patch?["knowledge_rating"]?.ToString()?.Trim()
+                ?? patch?["example_rating"]?.ToString()?.Trim();
+            string sig = "ask_knowledge:" + q.ToLowerInvariant() + ":" + (rating ?? "");
+            if (!hopDone.Add(sig))
+            {
+                return null;
+            }
+            if (string.IsNullOrWhiteSpace(q))
+            {
+                return
+                    "ask:knowledge needs knowledge_query (tags / scene / style). "
+                    + "Retry with \"ask\":[\"knowledge\"], \"knowledge_query\":\"redhead stockings\".";
+            }
+            int lim = Config.LoadAssistant(pid)["knowledge_hop_limit"]?.Value<int?>()
+                ?? Config.LoadAssistant(pid)["examples_hop_limit"]?.Value<int?>() ?? 6;
+            JArray rows = SearchKnowledge(pid, q, lim, rating);
+            knowledgeHops?.Add(new JObject { ["tool"] = "ask_knowledge", ["query"] = q, ["count"] = rows.Count });
+            MergeKnowledgeResults(knowledgeResults, rows);
+            return
+                "ask:knowledge — FTS over attached books (read-only references). "
+                + "Remix ideas; do not paste long verbatim.\n```json\n"
+                + rows.ToString(Newtonsoft.Json.Formatting.None) + "\n```";
+        }
         if (tool == "ask_examples")
         {
             string q = patch?["example_query"]?.ToString()?.Trim()
@@ -471,6 +511,8 @@ public partial class SwarmAssistentExtension
             }
             int lim = Config.LoadAssistant(pid)["examples_hop_limit"]?.Value<int?>() ?? 5;
             JArray examples = Memory?.LookupExamples(q, lim, rating) ?? [];
+            knowledgeHops?.Add(new JObject { ["tool"] = "ask_examples", ["query"] = q, ["count"] = examples.Count });
+            MergeKnowledgeResults(knowledgeResults, examples, legacyExamples: true);
             return
                 "ask:examples — Civitai Krea2 prompt references (FTS, no embeddings). "
                 + "These are EXAMPLES to remix, not copy 1:1. Prefer craft over pasting.\n```json\n"

AssistentConfig.cs

@@ -239,6 +239,134 @@ public sealed class AssistentConfig
         return map;
     }
 
+    static List<string> ParseYamlBracketList(string value)
+    {
+        value = (value ?? "").Trim();
+        if (value.StartsWith('[') && value.EndsWith(']'))
+        {
+            value = value[1..^1];
+        }
+        return value.Split(',')
+            .Select(s => s.Trim().Trim('"', '\''))
+            .Where(s => !string.IsNullOrWhiteSpace(s))
+            .ToList();
+    }
+
+    public string TryFindPackManifestPath(string personaId)
+    {
+        string shelf = PackShelfRoot(personaId);
+        if (string.IsNullOrWhiteSpace(shelf))
+        {
+            return null;
+        }
+        string dir = shelf;
+        for (int i = 0; i < 5 && !string.IsNullOrWhiteSpace(dir); i++)
+        {
+            string yaml = Path.Combine(dir, "assistent-pack.yaml");
+            if (File.Exists(yaml))
+            {
+                return yaml;
+            }
+            dir = Directory.GetParent(dir)?.FullName;
+        }
+        return null;
+    }
+
+    /// <summary>Pack manifest knowledge.attach list for a pack persona.</summary>
+    public List<string> TryParsePackKnowledgeAttach(string personaId)
+    {
+        string path = TryFindPackManifestPath(personaId);
+        if (string.IsNullOrWhiteSpace(path))
+        {
+            return [];
+        }
+        List<string> items = [];
+        try
+        {
+            foreach (string rawLine in File.ReadAllLines(path, Encoding.UTF8))
+            {
+                string line = rawLine.Trim();
+                if (string.IsNullOrWhiteSpace(line) || line.StartsWith('#'))
+                {
+                    continue;
+                }
+                if (line.StartsWith("knowledge.attach:", StringComparison.OrdinalIgnoreCase))
+                {
+                    string val = line["knowledge.attach:".Length..].Trim();
+                    items.AddRange(ParseYamlBracketList(val));
+                    break;
+                }
+            }
+        }
+        catch (Exception ex)
+        {
+            Logs.Debug($"AssistentConfig pack knowledge.attach {path}: {ex.Message}");
+        }
+        return items
+            .Select(SafeId)
+            .Where(id => id is not null)
+            .Distinct(StringComparer.OrdinalIgnoreCase)
+            .ToList();
+    }
+
+    public JObject LoadKnowledgeAttachOverlay(string personaId)
+    {
+        string id = SafeId(personaId);
+        if (id is null)
+        {
+            return null;
+        }
+        string path = Path.Combine(_overlayRoot, "personas", id, "knowledge.json");
+        return File.Exists(path) ? TryReadJson(path) : null;
+    }
+
+    public void SaveKnowledgeAttachOverlay(string personaId, JArray attach)
+    {
+        lock (_lock)
+        {
+            string id = SafeId(personaId) ?? throw new InvalidOperationException("invalid persona");
+            string dir = Path.Combine(_overlayRoot, "personas", id);
+            Directory.CreateDirectory(dir);
+            string path = Path.Combine(dir, "knowledge.json");
+            JObject doc = new()
+            {
+                ["attach"] = attach ?? new JArray(),
+            };
+            File.WriteAllText(path, doc.ToString(Newtonsoft.Json.Formatting.Indented) + "\n", Encoding.UTF8);
+        }
+    }
+
+    static readonly string[] DefaultBundledKnowledgeAttach = ["civitai-krea2", "ru-fictext-rplus"];
+
+    static readonly HashSet<string> BundledKnowledgePersonas = new(StringComparer.OrdinalIgnoreCase)
+    {
+        "neutral", "aggressive", "dreamer",
+    };
+
+    /// <summary>Effective book attach list for a persona (overlay → pack → bundled defaults).</summary>
+    public List<string> ResolveKnowledgeAttach(string personaId)
+    {
+        string pid = SafeId(personaId) ?? DefaultPersonaId();
+        JObject overlay = LoadKnowledgeAttachOverlay(pid);
+        if (overlay?["attach"] is JArray custom && custom.Count > 0)
+        {
+            return custom.Select(t => SafeId(t?.ToString()))
+                .Where(id => id is not null)
+                .Distinct(StringComparer.OrdinalIgnoreCase)
+                .ToList();
+        }
+        List<string> fromPack = TryParsePackKnowledgeAttach(pid);
+        if (fromPack.Count > 0)
+        {
+            return fromPack;
+        }
+        if (IsBundledPersona(pid) && BundledKnowledgePersonas.Contains(pid))
+        {
+            return DefaultBundledKnowledgeAttach.ToList();
+        }
+        return [];
+    }
+
     /// <summary>Discover persona packs under Assistent/extensions/*/.</summary>
     public List<PackPersona> DiscoverPackPersonas()
     {
@@ -477,7 +605,7 @@ public sealed class AssistentConfig
 
     static readonly HashSet<string> ReservedConfigFiles = new(StringComparer.OrdinalIgnoreCase)
     {
-        "exact.json", "controls.json", "skills.json", "ui.json", "assistant.json", "training-qlora.json",
+        "exact.json", "controls.json", "skills.json", "ui.json", "assistant.json", "knowledge.json",
     };
 
     static readonly HashSet<string> ReservedConfigDirs = new(StringComparer.OrdinalIgnoreCase)
@@ -780,7 +908,7 @@ public sealed class AssistentConfig
     {
         "persona.json", "bio.json", "voice.json", "humor.json", "craft.json",
         "appearance.json", "outfits.json", "roleplay.json", "likes.json", "dislikes.json",
-        "rules.json", "controls.json", "exact.json", "extra.md",
+        "rules.json", "controls.json", "exact.json", "knowledge.json", "extra.md",
     };
 
     public static bool IsWritableShelfName(string fileName)
@@ -934,8 +1062,6 @@ public sealed class AssistentConfig
 
     public JObject LoadUi(string personaId) => MergeJsonLayers("ui.json", LayerRoots(personaId));
 
-    public JObject LoadTrainingQlora(string personaId) => MergeJsonLayers("training-qlora.json", LayerRoots(personaId));
-
     /// <summary>Exact (KV) memory: bundled base → persona overlays → disk overlays. Persona keys overwrite base.</summary>
     public JObject LoadExact(string personaId) => MergeJsonLayers("exact.json", LayerRoots(personaId));
 
@@ -1549,40 +1675,6 @@ public sealed class AssistentConfig
         }
     }
 
-    public JObject LoadTrainingRunner()
-        => TryReadJson(Path.Combine(_overlayRoot, "training-runner.json")) ?? new JObject();
-
-    public void SaveTrainingRunner(JObject settings)
-    {
-        lock (_lock)
-        {
-            Directory.CreateDirectory(_overlayRoot);
-            string path = Path.Combine(_overlayRoot, "training-runner.json");
-            JObject merged = DeepMerge(LoadTrainingRunner(), settings ?? new JObject());
-            File.WriteAllText(path, merged.ToString(Newtonsoft.Json.Formatting.Indented), Encoding.UTF8);
-        }
-    }
-
-    public JObject LoadTrainingAgent()
-        => TryReadJson(Path.Combine(_overlayRoot, "training-agent.json"))
-           ?? new JObject
-           {
-               ["enabled"] = true,
-               ["auto_link_on_approve"] = true,
-               ["heard_quota"] = 3,
-           };
-
-    public void SaveTrainingAgent(JObject settings)
-    {
-        lock (_lock)
-        {
-            Directory.CreateDirectory(_overlayRoot);
-            string path = Path.Combine(_overlayRoot, "training-agent.json");
-            JObject merged = DeepMerge(LoadTrainingAgent(), settings ?? new JObject());
-            File.WriteAllText(path, merged.ToString(Newtonsoft.Json.Formatting.Indented), Encoding.UTF8);
-        }
-    }
-
     public JObject LoadOllamaRoles()
     {
         return TryReadJson(Path.Combine(_overlayRoot, "ollama-roles.json"))
@@ -1643,7 +1735,6 @@ public sealed class AssistentConfig
         JObject ui = LoadUi(id);
         JObject model = LoadModelProfile(id);
         JObject exact = LoadExact(id);
-        JObject training = LoadTrainingQlora(id);
         var packs = ListPacks(id);
         var skills = ListSkills(id);
         var personas = ListPersonaCatalog();
@@ -1659,7 +1750,6 @@ public sealed class AssistentConfig
             ["ui"] = ui,
             ["model"] = model,
             ["exact"] = exact,
-            ["training"] = training,
             ["controls"] = controlsSchema,
             ["control_values"] = controlValues,
             ["persona_source"] = PersonaSource(id),
@@ -1687,6 +1777,10 @@ public sealed class AssistentConfig
             ["identity_summary"] = RenderIdentityBlock(id, includeAllShelves: true),
             ["enabled_skills"] = new JArray(ResolveEnabledSkills(id, null)),
             ["patch_keys"] = new JArray(LoadPatchKeys()),
+            ["knowledge"] = new JObject
+            {
+                ["attach"] = new JArray(ResolveKnowledgeAttach(id)),
+            },
         };
     }
 }

AssistentHuggingFace.cs

@@ -1,684 +0,0 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Net.Http;
-using System.Text;
-using System.Text.RegularExpressions;
-using System.Threading.Tasks;
-using Newtonsoft.Json.Linq;
-using SwarmUI.Accounts;
-using SwarmUI.Utils;
-
-namespace Mrleo1nid.SwarmAssistent;
-
-/// <summary>Hugging Face datasets: search, compatibility gate, preview, import.</summary>
-public partial class SwarmAssistentExtension
-{
-    static readonly Regex HfRepoIdRe = new(@"^[A-Za-z0-9][A-Za-z0-9._-]{0,95}(/[A-Za-z0-9][A-Za-z0-9._-]{0,95})?$", RegexOptions.Compiled);
-
-    const string HfDatasetsServer = "https://datasets-server.huggingface.co";
-    const string HfHubApi = "https://huggingface.co/api/datasets";
-
-    static string GetHfToken(Session session)
-        => session?.User?.GetGenericData("huggingface_api", "key")?.Trim();
-
-    static HttpRequestMessage HfRequest(string url, Session session)
-    {
-        HttpRequestMessage req = new(HttpMethod.Get, url);
-        string token = GetHfToken(session);
-        if (!string.IsNullOrWhiteSpace(token))
-        {
-            req.Headers.Authorization = new System.Net.Http.Headers.AuthenticationHeaderValue("Bearer", token);
-        }
-        return req;
-    }
-
-    /// <summary>Normalize owner/name or HF datasets URL. Returns null when invalid.</summary>
-    public static string NormalizeHfDatasetId(string raw)
-    {
-        string s = (raw ?? "").Trim();
-        if (string.IsNullOrWhiteSpace(s))
-        {
-            return null;
-        }
-        if (s.StartsWith("http://", StringComparison.OrdinalIgnoreCase) || s.StartsWith("https://", StringComparison.OrdinalIgnoreCase))
-        {
-            if (!Uri.TryCreate(s, UriKind.Absolute, out Uri uri))
-            {
-                return null;
-            }
-            if (!string.Equals(uri.Host, "huggingface.co", StringComparison.OrdinalIgnoreCase))
-            {
-                return null;
-            }
-            string[] parts = uri.AbsolutePath.Trim('/').Split('/');
-            if (parts.Length < 2 || !string.Equals(parts[0], "datasets", StringComparison.OrdinalIgnoreCase))
-            {
-                return null;
-            }
-            s = $"{parts[1]}/{parts[2]}";
-        }
-        s = s.Trim().TrimEnd('/');
-        return HfRepoIdRe.IsMatch(s) ? s : null;
-    }
-
-    public async Task<JObject> AssistentSearchHfDatasets(Session session, string q = null, int limit = 20, bool show_all = false)
-    {
-        int take = Math.Clamp(limit, 1, 50);
-        string search = (q ?? "").Trim();
-        StringBuilder url = new($"{HfHubApi}?limit={take}&full=true");
-        url.Append("&filter=task_categories:text-generation");
-        url.Append("&filter=modality:text");
-        if (!string.IsNullOrWhiteSpace(search))
-        {
-            url.Append("&search=").Append(Uri.EscapeDataString(search));
-        }
-        try
-        {
-            using HttpRequestMessage req = HfRequest(url.ToString(), session);
-            using HttpResponseMessage resp = await HttpClient.SendAsync(req);
-            string body = await resp.Content.ReadAsStringAsync();
-            if (!resp.IsSuccessStatusCode)
-            {
-                return new JObject { ["error"] = $"HF search HTTP {(int)resp.StatusCode}: {Clip(body, 300)}" };
-            }
-            JArray rawList = JArray.Parse(body);
-            JArray results = [];
-            foreach (JToken item in rawList)
-            {
-                if (item is not JObject o)
-                {
-                    continue;
-                }
-                string id = o["id"]?.ToString();
-                if (string.IsNullOrWhiteSpace(id))
-                {
-                    continue;
-                }
-                JObject check = await CheckHfDatasetInternal(session, id, useCache: true);
-                string gate = check["gate"]?.ToString() ?? "rejected";
-                if (!show_all && gate == "rejected")
-                {
-                    continue;
-                }
-                results.Add(new JObject
-                {
-                    ["id"] = id,
-                    ["title"] = o["id"],
-                    ["downloads"] = o["downloads"],
-                    ["gate"] = gate,
-                    ["reason"] = check["reason"],
-                    ["schema"] = check["schema"],
-                });
-            }
-            return new JObject { ["success"] = true, ["results"] = results, ["has_hf_token"] = !string.IsNullOrWhiteSpace(GetHfToken(session)) };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = $"HF search: {ex.Message}" };
-        }
-    }
-
-    public async Task<JObject> AssistentCheckHfDataset(Session session, string dataset)
-    {
-        string id = NormalizeHfDatasetId(dataset);
-        if (id is null)
-        {
-            return new JObject { ["success"] = false, ["error"] = "Нужен owner/name или ссылка huggingface.co/datasets/…" };
-        }
-        JObject check = await CheckHfDatasetInternal(session, id, useCache: false);
-        check["success"] = check["gate"]?.ToString() != "rejected";
-        check["id"] = id;
-        return check;
-    }
-
-    async Task<JObject> CheckHfDatasetInternal(Session session, string datasetId, bool useCache)
-    {
-        string cacheKey = $"hf:{datasetId}";
-        if (useCache)
-        {
-            JObject cached = Memory.GetKvObject(AssistentMemory.KvHfDatasetCache)?[cacheKey] as JObject;
-            if (cached is not null && cached["checked_at"]?.Value<long?>() > DateTimeOffset.UtcNow.AddHours(-6).ToUnixTimeMilliseconds())
-            {
-                return cached;
-            }
-        }
-        JObject result = new() { ["id"] = datasetId, ["gate"] = "rejected", ["reason"] = "unknown" };
-        try
-        {
-            using HttpRequestMessage validReq = HfRequest($"{HfDatasetsServer}/is-valid?dataset={Uri.EscapeDataString(datasetId)}", session);
-            using HttpResponseMessage validResp = await HttpClient.SendAsync(validReq);
-            string validBody = await validResp.Content.ReadAsStringAsync();
-            if (!validResp.IsSuccessStatusCode)
-            {
-                result["reason"] = $"is-valid HTTP {(int)validResp.StatusCode}";
-                return CacheHfCheck(cacheKey, result);
-            }
-            JObject valid = JObject.Parse(validBody);
-            bool viewer = valid["viewer"]?.Value<bool?>() == true;
-            bool preview = valid["preview"]?.Value<bool?>() == true;
-            if (!viewer && !preview)
-            {
-                result["reason"] = "Набор не читается через datasets (viewer/preview = false)";
-                return CacheHfCheck(cacheKey, result);
-            }
-            using HttpRequestMessage splitReq = HfRequest($"{HfDatasetsServer}/splits?dataset={Uri.EscapeDataString(datasetId)}", session);
-            using HttpResponseMessage splitResp = await HttpClient.SendAsync(splitReq);
-            string splitBody = await splitResp.Content.ReadAsStringAsync();
-            if (!splitResp.IsSuccessStatusCode)
-            {
-                result["reason"] = $"splits HTTP {(int)splitResp.StatusCode}";
-                return CacheHfCheck(cacheKey, result);
-            }
-            JArray splits = JObject.Parse(splitBody)["splits"] as JArray ?? [];
-            if (splits.Count == 0)
-            {
-                result["reason"] = "Нет splits";
-                return CacheHfCheck(cacheKey, result);
-            }
-            JObject first = splits[0] as JObject;
-            string config = first?["config"]?.ToString() ?? "default";
-            string split = first?["split"]?.ToString() ?? "train";
-            using HttpRequestMessage rowsReq = HfRequest($"{HfDatasetsServer}/first-rows?dataset={Uri.EscapeDataString(datasetId)}&config={Uri.EscapeDataString(config)}&split={Uri.EscapeDataString(split)}", session);
-            using HttpResponseMessage rowsResp = await HttpClient.SendAsync(rowsReq);
-            string rowsBody = await rowsResp.Content.ReadAsStringAsync();
-            if (!rowsResp.IsSuccessStatusCode)
-            {
-                result["reason"] = $"first-rows HTTP {(int)rowsResp.StatusCode}: {Clip(rowsBody, 200)}";
-                return CacheHfCheck(cacheKey, result);
-            }
-            JObject rowsData = JObject.Parse(rowsBody);
-            JObject features = FeaturesToObject(rowsData["features"]);
-            (string gate, string reason, JObject schema) = ClassifyHfFeatures(features);
-            if (gate == "mapping" && TryFictionTagsTextPreset(features, out JObject presetSchema))
-            {
-                gate = "ok";
-                reason = "Fiction preset: title/tags → user, text → assistant";
-                schema = presetSchema;
-            }
-            result["gate"] = gate;
-            result["reason"] = reason;
-            result["schema"] = schema;
-            result["config"] = config;
-            result["split"] = split;
-            result["features"] = features;
-            result["sample_rows"] = rowsData["rows"];
-            result["runner_only"] = await HasHugeSizeTagAsync(session, datasetId);
-            return CacheHfCheck(cacheKey, result);
-        }
-        catch (Exception ex)
-        {
-            result["reason"] = ex.Message;
-            return CacheHfCheck(cacheKey, result);
-        }
-    }
-
-    static bool TryFictionTagsTextPreset(JObject features, out JObject schema)
-    {
-        schema = null;
-        if (features is null)
-        {
-            return false;
-        }
-        HashSet<string> names = new(StringComparer.OrdinalIgnoreCase);
-        foreach (JProperty p in features.Properties())
-        {
-            names.Add(p.Name);
-        }
-        if (!names.Contains("text") || (!names.Contains("tags") && !names.Contains("title")))
-        {
-            return false;
-        }
-        schema = new JObject
-        {
-            ["kind"] = "fiction_tags_text",
-            ["assistant_col"] = "text",
-        };
-        return true;
-    }
-
-    async Task<bool> HasHugeSizeTagAsync(Session session, string datasetId)
-    {
-        try
-        {
-            using HttpRequestMessage req = HfRequest($"{HfHubApi}/{Uri.EscapeDataString(datasetId)}", session);
-            using HttpResponseMessage resp = await HttpClient.SendAsync(req);
-            if (!resp.IsSuccessStatusCode)
-            {
-                return false;
-            }
-            JObject meta = JObject.Parse(await resp.Content.ReadAsStringAsync());
-            foreach (JToken t in meta["tags"] as JArray ?? [])
-            {
-                string tag = t?.ToString() ?? "";
-                if (tag.Contains("100K<", StringComparison.OrdinalIgnoreCase)
-                    || tag.Contains("1M<", StringComparison.OrdinalIgnoreCase)
-                    || tag.Contains("10M<", StringComparison.OrdinalIgnoreCase)
-                    || tag.Contains("100M<", StringComparison.OrdinalIgnoreCase))
-                {
-                    return true;
-                }
-            }
-        }
-        catch (Exception ex)
-        {
-            Logs.Debug($"HasHugeSizeTag {datasetId}: {ex.Message}");
-        }
-        return false;
-    }
-
-    static JObject ResolveHfMapping(JObject check, JObject mapping)
-    {
-        JObject schema = check?["schema"] as JObject;
-        string kind = schema?["kind"]?.ToString();
-        if (string.Equals(kind, "fiction_tags_text", StringComparison.OrdinalIgnoreCase))
-        {
-            return new JObject { ["kind"] = "fiction_tags_text", ["preset"] = "fiction_tags_text" };
-        }
-        if (mapping is not null && mapping.Count > 0)
-        {
-            return mapping;
-        }
-        if (string.Equals(mapping?["preset"]?.ToString(), "fiction_tags_text", StringComparison.OrdinalIgnoreCase))
-        {
-            return new JObject { ["kind"] = "fiction_tags_text" };
-        }
-        return mapping;
-    }
-
-    static bool MappingRequired(JObject check, JObject mapping)
-    {
-        string gate = check?["gate"]?.ToString();
-        if (gate != "mapping")
-        {
-            return false;
-        }
-        JObject resolved = ResolveHfMapping(check, mapping);
-        return resolved is null || !resolved.Properties().Any();
-    }
-
-    JObject CacheHfCheck(string cacheKey, JObject result)
-    {
-        result["checked_at"] = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
-        try
-        {
-            JObject bag = Memory.GetKvObject(AssistentMemory.KvHfDatasetCache) ?? new JObject();
-            bag[cacheKey] = result;
-            Memory.SetKvObject(AssistentMemory.KvHfDatasetCache, bag);
-        }
-        catch (Exception ex)
-        {
-            Logs.Debug($"CacheHfCheck: {ex.Message}");
-        }
-        return result;
-    }
-
-    static JObject FeaturesToObject(JToken tok)
-    {
-        if (tok is JObject obj)
-        {
-            return obj;
-        }
-        if (tok is JArray arr)
-        {
-            JObject map = new();
-            foreach (JToken t in arr)
-            {
-                if (t is not JObject row)
-                {
-                    continue;
-                }
-                string name = row["name"]?.ToString();
-                if (string.IsNullOrWhiteSpace(name))
-                {
-                    continue;
-                }
-                map[name] = row["type"] ?? row;
-            }
-            return map.Count > 0 ? map : null;
-        }
-        return null;
-    }
-
-    static (string gate, string reason, JObject schema) ClassifyHfFeatures(JObject features)
-    {
-        if (features is null || !features.Properties().Any())
-        {
-            return ("rejected", "Нет колонок (features пуст)", null);
-        }
-        HashSet<string> names = new(StringComparer.OrdinalIgnoreCase);
-        foreach (JProperty p in features.Properties())
-        {
-            names.Add(p.Name);
-            JToken dtype = p.Value?["dtype"] ?? p.Value?["type"];
-            string dt = dtype?.ToString() ?? "";
-            if (dt.Contains("image", StringComparison.OrdinalIgnoreCase)
-                || dt.Contains("audio", StringComparison.OrdinalIgnoreCase)
-                || dt.Contains("video", StringComparison.OrdinalIgnoreCase))
-            {
-                return ("rejected", $"Мультимодальная колонка {p.Name} ({dt})", null);
-            }
-        }
-        if (names.Contains("chosen") && names.Contains("rejected"))
-        {
-            return ("rejected", "DPO-набор (chosen/rejected) — не для SFT", null);
-        }
-        if (names.Count == 1 && names.Contains("text"))
-        {
-            return ("rejected", "Предобучение (одна колонка text), не диалоги", null);
-        }
-        if (names.Contains("messages"))
-        {
-            return ("ok", "OpenAI messages", new JObject { ["kind"] = "messages" });
-        }
-        if (names.Contains("conversations"))
-        {
-            return ("ok", "ShareGPT conversations", new JObject { ["kind"] = "conversations" });
-        }
-        if (names.Contains("instruction") && names.Contains("output"))
-        {
-            return ("ok", "Alpaca instruction/output", new JObject { ["kind"] = "alpaca" });
-        }
-        if (names.Contains("prompt") && (names.Contains("response") || names.Contains("completion") || names.Contains("answer")))
-        {
-            string respCol = names.Contains("response") ? "response" : names.Contains("completion") ? "completion" : "answer";
-            return ("ok", "prompt/response", new JObject { ["kind"] = "prompt_response", ["response_col"] = respCol });
-        }
-        if (names.Contains("question") && names.Contains("answer"))
-        {
-            return ("ok", "question/answer", new JObject { ["kind"] = "qa" });
-        }
-        List<string> stringCols = [];
-        foreach (JProperty p in features.Properties())
-        {
-            JToken dtype = p.Value?["dtype"] ?? p.Value?["type"];
-            string dt = dtype?.ToString() ?? "";
-            if (dt.Contains("string", StringComparison.OrdinalIgnoreCase) || dt == "value")
-            {
-                stringCols.Add(p.Name);
-            }
-        }
-        if (stringCols.Count >= 2)
-        {
-            return ("mapping", "Нужен ручной маппинг колонок", new JObject
-            {
-                ["kind"] = "custom",
-                ["columns"] = new JArray(stringCols),
-            });
-        }
-        return ("rejected", "Схема не подходит для SFT", null);
-    }
-
-    public async Task<JObject> AssistentPreviewHfDataset(Session session, string dataset, string config = null, string split = null)
-    {
-        string id = NormalizeHfDatasetId(dataset);
-        if (id is null)
-        {
-            return new JObject { ["error"] = "invalid dataset id" };
-        }
-        JObject check = await CheckHfDatasetInternal(session, id, useCache: true);
-        if (check["gate"]?.ToString() == "rejected")
-        {
-            return new JObject { ["error"] = check["reason"]?.ToString() ?? "rejected", ["check"] = check };
-        }
-        return new JObject { ["success"] = true, ["check"] = check };
-    }
-
-    public async Task<JObject> AssistentImportHfDataset(Session session, JObject raw)
-    {
-        try
-        {
-            string dataset = raw?["dataset"]?.ToString();
-            int limit = raw?["limit"]?.Value<int?>() ?? 200;
-            JObject mapping = raw?["mapping"] as JObject;
-            string id = NormalizeHfDatasetId(dataset);
-            if (id is null)
-            {
-                return new JObject { ["error"] = "invalid dataset id" };
-            }
-            JObject check = await CheckHfDatasetInternal(session, id, useCache: true);
-            string gate = check["gate"]?.ToString();
-            if (gate == "rejected")
-            {
-                return new JObject { ["error"] = check["reason"]?.ToString() ?? "rejected" };
-            }
-            if (MappingRequired(check, mapping))
-            {
-                return new JObject { ["error"] = "Нужен маппинг колонок", ["check"] = check };
-            }
-            mapping = ResolveHfMapping(check, mapping);
-            int take = Math.Clamp(limit, 1, 5000);
-            JArray rows = [];
-            string config = check["config"]?.ToString() ?? "default";
-            string split = check["split"]?.ToString() ?? "train";
-            int offset = 0;
-            while (rows.Count < take)
-            {
-                int chunk = Math.Min(100, take - rows.Count);
-                using HttpRequestMessage rowsReq = HfRequest($"{HfDatasetsServer}/rows?dataset={Uri.EscapeDataString(id)}&config={Uri.EscapeDataString(config)}&split={Uri.EscapeDataString(split)}&offset={offset}&length={chunk}", session);
-                using HttpResponseMessage rowsResp = await HttpClient.SendAsync(rowsReq);
-                string rowsBody = await rowsResp.Content.ReadAsStringAsync();
-                if (!rowsResp.IsSuccessStatusCode)
-                {
-                    if (rows.Count == 0)
-                    {
-                        return new JObject
-                        {
-                            ["error"] = $"HF rows HTTP {(int)rowsResp.StatusCode}: {Clip(rowsBody, 240)}. "
-                                + "Для gated/NSFW добавь huggingface_api в User Settings.",
-                        };
-                    }
-                    break;
-                }
-                JObject parsed = JObject.Parse(rowsBody);
-                JArray batch = parsed["rows"] as JArray ?? [];
-                if (batch.Count == 0)
-                {
-                    break;
-                }
-                foreach (JToken t in batch)
-                {
-                    rows.Add(t);
-                }
-                offset += batch.Count;
-                if (batch.Count < chunk)
-                {
-                    break;
-                }
-            }
-            if (rows.Count == 0)
-            {
-                rows = check["sample_rows"] as JArray ?? [];
-            }
-            List<JObject> toSave = [];
-            foreach (JToken rowTok in rows.Take(take))
-            {
-                if (rowTok is not JObject row)
-                {
-                    continue;
-                }
-                JObject rowData = row["row"] as JObject ?? row;
-                JArray messages = ConvertHfRowToMessages(rowData, check["schema"] as JObject, mapping);
-                if (messages is null || messages.Count == 0)
-                {
-                    continue;
-                }
-                toSave.Add(new JObject
-                {
-                    ["source"] = "hf",
-                    ["hf_repo"] = id,
-                    ["messages"] = messages,
-                    ["status"] = "draft",
-                });
-            }
-            int imported = toSave.Count > 0 ? Memory.ImportTrainSamplesBatch(toSave) : 0;
-            if (imported == 0 && check["runner_only"]?.Value<bool?>() == true)
-            {
-                return new JObject { ["success"] = true, ["imported"] = 0, ["runner_only"] = true, ["id"] = id, ["note"] = "Большой набор — используй HF id в QLoRA-раннере" };
-            }
-            if (imported == 0)
-            {
-                return new JObject
-                {
-                    ["error"] = rows.Count == 0
-                        ? "HF не отдал строки — проверь token (gated/NSFW) и маппинг колонок"
-                        : "0 строк после маппинга — проверь колонки user/assistant",
-                    ["rows_fetched"] = rows.Count,
-                    ["id"] = id,
-                };
-            }
-            return new JObject
-            {
-                ["success"] = true,
-                ["imported"] = imported,
-                ["id"] = id,
-                ["rows_fetched"] = rows.Count,
-                ["status"] = "draft",
-            };
-        }
-        catch (Exception ex)
-        {
-            Logs.Error($"AssistentImportHfDataset: {ex}");
-            return new JObject { ["error"] = ex.Message };
-        }
-    }
-
-    static string HfCellString(JToken tok)
-    {
-        if (tok is null || tok.Type == JTokenType.Null)
-        {
-            return "";
-        }
-        if (tok is JArray arr)
-        {
-            List<string> parts = [];
-            foreach (JToken t in arr)
-            {
-                string s = t?.Type == JTokenType.String ? t.ToString() : t?.ToString(Newtonsoft.Json.Formatting.None);
-                if (!string.IsNullOrWhiteSpace(s))
-                {
-                    parts.Add(s.Trim());
-                }
-            }
-            return string.Join(", ", parts);
-        }
-        return tok.ToString().Trim();
-    }
-
-    static JArray ConvertHfRowToMessages(JObject row, JObject schema, JObject mapping)
-    {
-        string kind = schema?["kind"]?.ToString() ?? mapping?["kind"]?.ToString();
-        if (kind == "messages" && row["messages"] is JArray msgs)
-        {
-            return NormalizeMessagesArray(msgs);
-        }
-        if (kind == "conversations" && row["conversations"] is JArray conv)
-        {
-            JArray outArr = [];
-            foreach (JToken c in conv)
-            {
-                if (c is not JObject co)
-                {
-                    continue;
-                }
-                string from = co["from"]?.ToString() ?? "";
-                string val = co["value"]?.ToString() ?? "";
-                string role = from is "human" or "user" ? "user" : from is "gpt" or "assistant" or "chatgpt" ? "assistant" : "user";
-                outArr.Add(new JObject { ["role"] = role, ["content"] = val });
-            }
-            return outArr.Count > 0 ? outArr : null;
-        }
-        if (kind == "alpaca")
-        {
-            string instr = row["instruction"]?.ToString() ?? "";
-            string inp = row["input"]?.ToString() ?? "";
-            string output = row["output"]?.ToString() ?? "";
-            string user = string.IsNullOrWhiteSpace(inp) ? instr : $"{instr}\n{inp}";
-            return new JArray
-            {
-                new JObject { ["role"] = "user", ["content"] = user },
-                new JObject { ["role"] = "assistant", ["content"] = output },
-            };
-        }
-        if (kind == "prompt_response")
-        {
-            string respCol = schema?["response_col"]?.ToString() ?? "response";
-            return new JArray
-            {
-                new JObject { ["role"] = "user", ["content"] = row["prompt"]?.ToString() ?? "" },
-                new JObject { ["role"] = "assistant", ["content"] = row[respCol]?.ToString() ?? "" },
-            };
-        }
-        if (kind == "qa")
-        {
-            return new JArray
-            {
-                new JObject { ["role"] = "user", ["content"] = row["question"]?.ToString() ?? "" },
-                new JObject { ["role"] = "assistant", ["content"] = row["answer"]?.ToString() ?? "" },
-            };
-        }
-        if (kind == "fiction_tags_text")
-        {
-            string text = HfCellString(row["text"]);
-            if (string.IsNullOrWhiteSpace(text))
-            {
-                return null;
-            }
-            List<string> userParts = [];
-            string title = HfCellString(row["title"]);
-            string tags = HfCellString(row["tags"]);
-            if (!string.IsNullOrWhiteSpace(title))
-            {
-                userParts.Add($"Title: {title}");
-            }
-            if (!string.IsNullOrWhiteSpace(tags))
-            {
-                userParts.Add($"Tags: {tags}");
-            }
-            string user = userParts.Count > 0 ? string.Join("\n", userParts) : tags ?? title ?? "";
-            if (string.IsNullOrWhiteSpace(user))
-            {
-                return null;
-            }
-            return new JArray
-            {
-                new JObject { ["role"] = "user", ["content"] = user },
-                new JObject { ["role"] = "assistant", ["content"] = text },
-            };
-        }
-        if (kind == "custom" && mapping is not null)
-        {
-            string userCol = mapping["user_col"]?.ToString();
-            string asstCol = mapping["assistant_col"]?.ToString();
-            if (!string.IsNullOrWhiteSpace(userCol) && !string.IsNullOrWhiteSpace(asstCol))
-            {
-                return new JArray
-                {
-                    new JObject { ["role"] = "user", ["content"] = row[userCol]?.ToString() ?? "" },
-                    new JObject { ["role"] = "assistant", ["content"] = row[asstCol]?.ToString() ?? "" },
-                };
-            }
-        }
-        return null;
-    }
-
-    static JArray NormalizeMessagesArray(JArray msgs)
-    {
-        JArray outArr = [];
-        foreach (JToken m in msgs)
-        {
-            if (m is not JObject mo)
-            {
-                continue;
-            }
-            string role = mo["role"]?.ToString() ?? "user";
-            string content = mo["content"]?.ToString() ?? mo["text"]?.ToString() ?? "";
-            if (string.IsNullOrWhiteSpace(content))
-            {
-                continue;
-            }
-            outArr.Add(new JObject { ["role"] = role, ["content"] = content });
-        }
-        return outArr.Count > 0 ? outArr : null;
-    }
-}

AssistentKnowledge.cs

@@ -0,0 +1,214 @@
+using System;
+using System.Collections.Generic;
+using System.Linq;
+using System.Text;
+using Newtonsoft.Json.Linq;
+using SwarmUI.Utils;
+
+namespace Mrleo1nid.SwarmAssistent;
+
+/// <summary>Unified knowledge hub: books FTS + legacy examples shim + catalog for personas.</summary>
+public partial class SwarmAssistentExtension
+{
+    public List<string> ResolveAttachedBooks(string personaId)
+        => Config.ResolveKnowledgeAttach(personaId);
+
+    public JObject BuildKnowledgeCatalog(string personaId)
+    {
+        string pid = AssistentConfig.SafeId(personaId) ?? Config.DefaultPersonaId();
+        List<string> attached = ResolveAttachedBooks(pid);
+        JArray books = Memory?.ListBooksOnDisk() ?? [];
+        HashSet<string> attachSet = attached.ToHashSet(StringComparer.OrdinalIgnoreCase);
+        JArray catalog = [];
+        foreach (JToken t in books)
+        {
+            if (t is not JObject b)
+            {
+                continue;
+            }
+            string id = b["id"]?.ToString() ?? "";
+            catalog.Add(new JObject
+            {
+                ["id"] = id,
+                ["title"] = b["title"] ?? id,
+                ["description"] = b["description"] ?? "",
+                ["content_kind"] = b["content_kind"] ?? "",
+                ["language"] = b["language"] ?? "",
+                ["attached"] = attachSet.Contains(id),
+                ["indexed"] = b["indexed"]?.Value<bool?>() ?? false,
+            });
+        }
+        return new JObject
+        {
+            ["persona"] = pid,
+            ["attach"] = new JArray(attached),
+            ["books"] = catalog,
+            ["books_indexed"] = Memory?.BookRowCount() ?? 0,
+            ["examples_indexed"] = Memory?.ExampleCount() ?? 0,
+            ["tags_indexed"] = Memory?.TagCount() ?? 0,
+        };
+    }
+
+    public string BuildKnowledgeSystemLayer(string personaId)
+    {
+        JObject cat = BuildKnowledgeCatalog(personaId);
+        JArray attach = cat["attach"] as JArray ?? [];
+        if (attach.Count == 0)
+        {
+            return "";
+        }
+        StringBuilder sb = new();
+        sb.AppendLine("## Knowledge books (FTS reference — read-only)");
+        sb.AppendLine("Attached corpora for this persona. Search via ask:[\"knowledge\"] + knowledge_query (or legacy ask:[\"examples\"] + example_query).");
+        foreach (JToken t in attach)
+        {
+            string id = t?.ToString()?.Trim();
+            if (string.IsNullOrWhiteSpace(id))
+            {
+                continue;
+            }
+            JObject meta = (cat["books"] as JArray)?.OfType<JObject>()
+                .FirstOrDefault(b => string.Equals(b["id"]?.ToString(), id, StringComparison.OrdinalIgnoreCase));
+            string title = meta?["title"]?.ToString() ?? id;
+            string kind = meta?["content_kind"]?.ToString() ?? "";
+            string desc = meta?["description"]?.ToString() ?? "";
+            sb.AppendLine($"- **{id}** ({title}){ (string.IsNullOrWhiteSpace(kind) ? "" : $" · {kind}")}");
+            if (!string.IsNullOrWhiteSpace(desc))
+            {
+                sb.AppendLine($"  {desc}");
+            }
+        }
+        return sb.ToString().TrimEnd();
+    }
+
+    public JArray SearchKnowledge(string personaId, string query, int limit = 8, string rating = null)
+    {
+        query = (query ?? "").Trim();
+        if (query.Length < 1 || Memory is null)
+        {
+            return [];
+        }
+        List<string> attached = ResolveAttachedBooks(personaId);
+        JArray hits = [];
+        HashSet<string> seen = [];
+        if (attached.Count > 0)
+        {
+            foreach (JToken t in Memory.LookupBooks(query, limit, attached, rating))
+            {
+                string key = t?["id"]?.ToString() ?? t?.ToString();
+                if (!string.IsNullOrWhiteSpace(key) && seen.Add(key))
+                {
+                    hits.Add(t);
+                }
+            }
+        }
+        if (hits.Count < limit && attached.Any(b => string.Equals(b, "civitai-krea2", StringComparison.OrdinalIgnoreCase)))
+        {
+            int remain = limit - hits.Count;
+            foreach (JToken t in Memory.LookupExamples(query, remain, rating))
+            {
+                string key = "legacy:" + (t?["id"]?.ToString() ?? "");
+                if (!seen.Add(key))
+                {
+                    continue;
+                }
+                JObject row = t as JObject ?? new JObject();
+                hits.Add(new JObject
+                {
+                    ["id"] = row["id"],
+                    ["book"] = "civitai-krea2",
+                    ["source"] = "examples-legacy",
+                    ["title"] = "",
+                    ["tags"] = row["tags"],
+                    ["text"] = row["prompt"],
+                    ["body"] = row["prompt"],
+                    ["rating"] = row["rating"],
+                    ["params"] = row["params"],
+                    ["loras"] = row["loras"],
+                    ["note"] = row["note"],
+                });
+            }
+        }
+        return hits;
+    }
+
+    public static JArray CivitaiResultsShim(JArray knowledgeResults)
+    {
+        JArray outRows = [];
+        foreach (JToken t in knowledgeResults ?? [])
+        {
+            if (t is not JObject row)
+            {
+                continue;
+            }
+            string book = row["book"]?.ToString() ?? "";
+            string source = row["source"]?.ToString() ?? "";
+            if (!string.Equals(book, "civitai-krea2", StringComparison.OrdinalIgnoreCase)
+                && source is not "examples-legacy")
+            {
+                continue;
+            }
+            if (row["prompt"] is not null)
+            {
+                outRows.Add(row);
+                continue;
+            }
+            outRows.Add(new JObject
+            {
+                ["id"] = row["id"],
+                ["rating"] = row["rating"],
+                ["tags"] = row["tags"],
+                ["prompt"] = row["text"] ?? row["body"],
+                ["negative"] = row["meta"]?["negative"] ?? "",
+                ["params"] = row["params"] ?? row["meta"]?["params"],
+                ["loras"] = row["loras"] ?? row["meta"]?["loras"],
+                ["note"] = row["note"] ?? "EXAMPLE from Civitai — remix, do not copy 1:1",
+            });
+        }
+        return outRows;
+    }
+
+    JObject BuildKnowledgeResponse(string personaId, JArray hops, JArray results)
+        => new()
+        {
+            ["catalog"] = BuildKnowledgeCatalog(personaId),
+            ["hops"] = hops ?? new JArray(),
+            ["results"] = results ?? new JArray(),
+        };
+
+    static void MergeKnowledgeResults(JArray target, JArray rows, bool legacyExamples = false)
+    {
+        if (target is null || rows is null)
+        {
+            return;
+        }
+        HashSet<string> seen = target
+            .Select(t => t?["id"]?.ToString() ?? t?.ToString())
+            .Where(s => !string.IsNullOrWhiteSpace(s))
+            .ToHashSet(StringComparer.OrdinalIgnoreCase);
+        foreach (JToken t in rows)
+        {
+            JObject row = t as JObject ?? new JObject { ["text"] = t?.ToString() };
+            if (legacyExamples)
+            {
+                row = new JObject
+                {
+                    ["id"] = row["id"],
+                    ["book"] = "civitai-krea2",
+                    ["source"] = "examples-legacy",
+                    ["tags"] = row["tags"],
+                    ["text"] = row["prompt"],
+                    ["body"] = row["prompt"],
+                    ["rating"] = row["rating"],
+                    ["note"] = row["note"],
+                };
+            }
+            string key = row["id"]?.ToString() ?? row["text"]?.ToString();
+            if (string.IsNullOrWhiteSpace(key) || !seen.Add(key))
+            {
+                continue;
+            }
+            target.Add(row);
+        }
+    }
+}

AssistentKnowledgeApi.cs

@@ -0,0 +1,129 @@
+using System.Threading.Tasks;
+using Newtonsoft.Json.Linq;
+using SwarmUI.Accounts;
+
+namespace Mrleo1nid.SwarmAssistent;
+
+public partial class SwarmAssistentExtension
+{
+    public async Task<JObject> AssistentListKnowledgeCatalog(Session session, string persona = null)
+    {
+        await Task.CompletedTask;
+        if (Memory is null)
+        {
+            return new JObject { ["error"] = "memory not ready" };
+        }
+        try
+        {
+            Memory.EnsureBooksIndex();
+            string pid = AssistentConfig.SafeId(persona) ?? Config.DefaultPersonaId();
+            return new JObject
+            {
+                ["success"] = true,
+                ["knowledge"] = BuildKnowledgeCatalog(pid),
+                ["editable"] = Config.IsOverlayPersona(pid) && !Config.IsProtectedPersona(pid),
+            };
+        }
+        catch (System.Exception ex)
+        {
+            return new JObject { ["error"] = $"knowledge catalog: {ex.Message}" };
+        }
+    }
+
+    public async Task<JObject> AssistentSearchKnowledge(Session session, string query, string persona = null, int limit = 8, string rating = null, string book = null)
+    {
+        await Task.CompletedTask;
+        if (Memory is null)
+        {
+            return new JObject { ["error"] = "memory not ready" };
+        }
+        query = (query ?? "").Trim();
+        if (query.Length < 1)
+        {
+            return new JObject { ["error"] = "query required" };
+        }
+        try
+        {
+            string pid = AssistentConfig.SafeId(persona) ?? Config.DefaultPersonaId();
+            JArray results;
+            if (!string.IsNullOrWhiteSpace(book))
+            {
+                results = Memory.LookupBooks(query, limit, [book.Trim()], rating);
+            }
+            else
+            {
+                results = SearchKnowledge(pid, query, limit, rating);
+            }
+            return new JObject
+            {
+                ["success"] = true,
+                ["query"] = query,
+                ["persona"] = pid,
+                ["results"] = results,
+                ["civitai_results"] = CivitaiResultsShim(results),
+            };
+        }
+        catch (System.Exception ex)
+        {
+            return new JObject { ["error"] = $"knowledge search: {ex.Message}" };
+        }
+    }
+
+    public async Task<JObject> AssistentGetKnowledgeAttach(Session session, string persona = null)
+    {
+        await Task.CompletedTask;
+        string pid = AssistentConfig.SafeId(persona) ?? Config.DefaultPersonaId();
+        return new JObject
+        {
+            ["success"] = true,
+            ["persona"] = pid,
+            ["attach"] = new JArray(ResolveAttachedBooks(pid)),
+            ["editable"] = Config.IsOverlayPersona(pid) && !Config.IsProtectedPersona(pid),
+            ["source"] = Config.PersonaSource(pid),
+        };
+    }
+
+    public async Task<JObject> AssistentSaveKnowledgeAttach(Session session, string persona, JArray attach)
+    {
+        await Task.CompletedTask;
+        string pid = AssistentConfig.SafeId(persona);
+        if (pid is null)
+        {
+            return new JObject { ["error"] = "persona required" };
+        }
+        if (Config.IsProtectedPersona(pid))
+        {
+            return new JObject { ["error"] = "bundled/pack personas cannot edit attach here — clone to overlay first" };
+        }
+        if (!Config.IsOverlayPersona(pid))
+        {
+            return new JObject { ["error"] = "overlay persona required" };
+        }
+        try
+        {
+            JArray cleaned = [];
+            if (attach is not null)
+            {
+                foreach (JToken t in attach)
+                {
+                    string id = AssistentConfig.SafeId(t?.ToString());
+                    if (id is not null)
+                    {
+                        cleaned.Add(id);
+                    }
+                }
+            }
+            Config.SaveKnowledgeAttachOverlay(pid, cleaned);
+            return new JObject
+            {
+                ["success"] = true,
+                ["persona"] = pid,
+                ["attach"] = new JArray(ResolveAttachedBooks(pid)),
+            };
+        }
+        catch (System.Exception ex)
+        {
+            return new JObject { ["error"] = $"save knowledge attach: {ex.Message}" };
+        }
+    }
+}

AssistentMemory.Books.cs

@@ -0,0 +1,458 @@
+using System;
+using System.Collections.Generic;
+using System.Globalization;
+using System.IO;
+using System.Linq;
+using System.Text;
+using Microsoft.Data.Sqlite;
+using Newtonsoft.Json.Linq;
+using SwarmUI.Utils;
+
+namespace Mrleo1nid.SwarmAssistent;
+
+/// <summary>Reference books (search.jsonl) — FTS only, seeded by gpu-rent to Assistent/books/.</summary>
+public sealed partial class AssistentMemory
+{
+    const string BooksMetaPrefix = "books_fp:";
+
+    void TryIndexBooks()
+    {
+        try
+        {
+            EnsureBooksIndex();
+        }
+        catch (Exception ex)
+        {
+            Logs.Debug($"AssistentMemory books index: {ex.Message}");
+        }
+    }
+
+    public string BooksRoot()
+        => Path.Combine(_dataRoot, "Assistent", "books");
+
+    void EnsureBooksSchema()
+    {
+        Exec(
+            """
+            CREATE TABLE IF NOT EXISTS books_rows (
+              id TEXT PRIMARY KEY,
+              book_id TEXT NOT NULL,
+              title TEXT NOT NULL DEFAULT '',
+              tags TEXT NOT NULL DEFAULT '',
+              text TEXT NOT NULL DEFAULT '',
+              body TEXT NOT NULL DEFAULT '',
+              rating TEXT NOT NULL DEFAULT '',
+              meta_json TEXT NOT NULL DEFAULT '{}',
+              search_blob TEXT NOT NULL DEFAULT ''
+            );
+            """);
+        Exec("CREATE INDEX IF NOT EXISTS idx_books_rows_book ON books_rows(book_id);");
+        Exec(
+            """
+            CREATE VIRTUAL TABLE IF NOT EXISTS books_fts USING fts5(
+              book_id,
+              title,
+              tags,
+              text,
+              body,
+              search_blob,
+              tokenize = 'unicode61 remove_diacritics 2'
+            );
+            """);
+        Exec(
+            """
+            CREATE TRIGGER IF NOT EXISTS books_fts_ai AFTER INSERT ON books_rows BEGIN
+              INSERT INTO books_fts(rowid, book_id, title, tags, text, body, search_blob)
+              VALUES (new.rowid, new.book_id, new.title, new.tags, new.text, new.body, new.search_blob);
+            END;
+            """);
+        Exec(
+            """
+            CREATE TRIGGER IF NOT EXISTS books_fts_ad AFTER DELETE ON books_rows BEGIN
+              INSERT INTO books_fts(books_fts, rowid) VALUES('delete', old.rowid);
+            END;
+            """);
+        Exec(
+            """
+            CREATE TRIGGER IF NOT EXISTS books_fts_au AFTER UPDATE ON books_rows BEGIN
+              INSERT INTO books_fts(books_fts, rowid) VALUES('delete', old.rowid);
+              INSERT INTO books_fts(rowid, book_id, title, tags, text, body, search_blob)
+              VALUES (new.rowid, new.book_id, new.title, new.tags, new.text, new.body, new.search_blob);
+            END;
+            """);
+    }
+
+    static string ReadBookContentSha(string bookDir)
+    {
+        foreach (string name in new[] { ".gpu-rent-meta.json", "meta.json" })
+        {
+            string path = Path.Combine(bookDir, name);
+            if (!File.Exists(path))
+            {
+                continue;
+            }
+            try
+            {
+                JObject meta = JObject.Parse(File.ReadAllText(path, Encoding.UTF8));
+                string sha = meta["content_sha"]?.ToString()?.Trim();
+                if (!string.IsNullOrWhiteSpace(sha))
+                {
+                    return sha;
+                }
+            }
+            catch
+            {
+                // ignore
+            }
+        }
+        string jsonl = Path.Combine(bookDir, "search.jsonl");
+        if (File.Exists(jsonl))
+        {
+            return FileFingerprint(jsonl);
+        }
+        return null;
+    }
+
+    /// <summary>Reindex changed books from disk. Returns total row count.</summary>
+    public int EnsureBooksIndex()
+    {
+        string root = BooksRoot();
+        if (!Directory.Exists(root))
+        {
+            return BookRowCount();
+        }
+        int total = 0;
+        foreach (string bookDir in Directory.GetDirectories(root).OrderBy(d => d, StringComparer.OrdinalIgnoreCase))
+        {
+            string bookId = Path.GetFileName(bookDir);
+            if (string.IsNullOrWhiteSpace(bookId))
+            {
+                continue;
+            }
+            string jsonl = Path.Combine(bookDir, "search.jsonl");
+            if (!File.Exists(jsonl))
+            {
+                continue;
+            }
+            string fp = ReadBookContentSha(bookDir) ?? FileFingerprint(jsonl);
+            lock (_lock)
+            {
+                EnsureOpen();
+                EnsureBooksSchema();
+                string metaKey = BooksMetaPrefix + bookId;
+                if (string.Equals(GetMeta(metaKey), fp, StringComparison.Ordinal))
+                {
+                    continue;
+                }
+            }
+            int n = IndexBookJsonl(bookId, jsonl, fp);
+            total += n;
+        }
+        if (total > 0)
+        {
+            Logs.Info($"AssistentMemory: indexed {total} book rows under {root}");
+        }
+        return BookRowCount();
+    }
+
+    int IndexBookJsonl(string bookId, string jsonlPath, string fingerprint)
+    {
+        List<(string id, string title, string tags, string text, string body, string rating, string metaJson, string blob)> rows = [];
+        foreach (string line in File.ReadLines(jsonlPath, Encoding.UTF8))
+        {
+            if (string.IsNullOrWhiteSpace(line))
+            {
+                continue;
+            }
+            JObject o;
+            try
+            {
+                o = JObject.Parse(line);
+            }
+            catch
+            {
+                continue;
+            }
+            string id = o["id"]?.ToString()?.Trim();
+            if (string.IsNullOrWhiteSpace(id))
+            {
+                id = $"{bookId}:{rows.Count + 1}";
+            }
+            string title = o["title"]?.ToString() ?? "";
+            string tagsJoined = "";
+            if (o["tags"] is JArray tagArr)
+            {
+                tagsJoined = string.Join(", ", tagArr.Select(t => t?.ToString()?.Trim()).Where(t => !string.IsNullOrWhiteSpace(t)));
+            }
+            string text = o["text"]?.ToString() ?? "";
+            string body = o["body"]?.ToString() ?? text;
+            if (string.IsNullOrWhiteSpace(text) && string.IsNullOrWhiteSpace(body))
+            {
+                continue;
+            }
+            string rating = o["rating"]?.ToString() ?? "";
+            string metaJson = (o["meta"] as JObject)?.ToString(Newtonsoft.Json.Formatting.None) ?? "{}";
+            string blob = $"{title}\n{tagsJoined}\n{text}\n{body}\n{rating}";
+            rows.Add((id, title, tagsJoined, text, body, rating, metaJson, blob));
+        }
+
+        lock (_lock)
+        {
+            EnsureOpen();
+            EnsureBooksSchema();
+            using SqliteTransaction tx = _conn.BeginTransaction();
+            using (SqliteCommand del = _conn.CreateCommand())
+            {
+                del.Transaction = tx;
+                del.CommandText = "DELETE FROM books_rows WHERE book_id = $b";
+                del.Parameters.AddWithValue("$b", bookId);
+                del.ExecuteNonQuery();
+            }
+            using (SqliteCommand ins = _conn.CreateCommand())
+            {
+                ins.Transaction = tx;
+                ins.CommandText =
+                    """
+                    INSERT OR REPLACE INTO books_rows(
+                      id, book_id, title, tags, text, body, rating, meta_json, search_blob)
+                    VALUES($id,$b,$t,$tg,$tx,$bd,$r,$mj,$bl)
+                    """;
+                var pid = ins.Parameters.Add("$id", SqliteType.Text);
+                var pb = ins.Parameters.Add("$b", SqliteType.Text);
+                var pt = ins.Parameters.Add("$t", SqliteType.Text);
+                var ptg = ins.Parameters.Add("$tg", SqliteType.Text);
+                var ptx = ins.Parameters.Add("$tx", SqliteType.Text);
+                var pbd = ins.Parameters.Add("$bd", SqliteType.Text);
+                var pr = ins.Parameters.Add("$r", SqliteType.Text);
+                var pmj = ins.Parameters.Add("$mj", SqliteType.Text);
+                var pbl = ins.Parameters.Add("$bl", SqliteType.Text);
+                foreach (var row in rows)
+                {
+                    pid.Value = row.id;
+                    pb.Value = bookId;
+                    pt.Value = row.title;
+                    ptg.Value = row.tags;
+                    ptx.Value = row.text;
+                    pbd.Value = row.body;
+                    pr.Value = row.rating;
+                    pmj.Value = row.metaJson;
+                    pbl.Value = row.blob;
+                    ins.ExecuteNonQuery();
+                }
+            }
+            tx.Commit();
+            SetMeta(BooksMetaPrefix + bookId, fingerprint);
+            Logs.Info($"AssistentMemory: indexed book {bookId} ({rows.Count} rows)");
+            return rows.Count;
+        }
+    }
+
+    public int BookRowCount()
+    {
+        lock (_lock)
+        {
+            EnsureOpen();
+            if (!TableExists("books_rows"))
+            {
+                return 0;
+            }
+            using SqliteCommand c = _conn.CreateCommand();
+            c.CommandText = "SELECT COUNT(*) FROM books_rows";
+            return Convert.ToInt32(c.ExecuteScalar());
+        }
+    }
+
+    public JArray ListBooksOnDisk()
+    {
+        JArray list = [];
+        string root = BooksRoot();
+        if (!Directory.Exists(root))
+        {
+            return list;
+        }
+        foreach (string bookDir in Directory.GetDirectories(root).OrderBy(d => d, StringComparer.OrdinalIgnoreCase))
+        {
+            string id = Path.GetFileName(bookDir);
+            if (string.IsNullOrWhiteSpace(id))
+            {
+                continue;
+            }
+            JObject spec = new() { ["id"] = id };
+            string yaml = Path.Combine(bookDir, "book.yaml");
+            if (File.Exists(yaml))
+            {
+                foreach (string rawLine in File.ReadAllLines(yaml, Encoding.UTF8))
+                {
+                    string line = rawLine.Trim();
+                    if (string.IsNullOrWhiteSpace(line) || line.StartsWith('#'))
+                    {
+                        continue;
+                    }
+                    int colon = line.IndexOf(':');
+                    if (colon <= 0)
+                    {
+                        continue;
+                    }
+                    string key = line[..colon].Trim();
+                    string val = line[(colon + 1)..].Trim().Trim('"', '\'');
+                    if (key is "title" or "description" or "content_kind" or "language")
+                    {
+                        spec[key] = val;
+                    }
+                }
+            }
+            string jsonl = Path.Combine(bookDir, "search.jsonl");
+            spec["indexed"] = File.Exists(jsonl);
+            spec["content_sha"] = ReadBookContentSha(bookDir) ?? "";
+            list.Add(spec);
+        }
+        return list;
+    }
+
+    /// <summary>FTS lookup over attached books (filter by book_id list when provided).</summary>
+    public JArray LookupBooks(string query, int limit = 8, IEnumerable<string> bookIds = null, string rating = null)
+    {
+        query = (query ?? "").Trim();
+        if (query.Length < 1)
+        {
+            return [];
+        }
+        TryIndexBooks();
+        int cap = Math.Clamp(limit, 1, 30);
+        HashSet<string> bookFilter = null;
+        if (bookIds is not null)
+        {
+            bookFilter = bookIds
+                .Select(b => (b ?? "").Trim())
+                .Where(b => !string.IsNullOrWhiteSpace(b))
+                .ToHashSet(StringComparer.OrdinalIgnoreCase);
+            if (bookFilter.Count == 0)
+            {
+                return [];
+            }
+        }
+        string ratingFilter = string.IsNullOrWhiteSpace(rating) ? null : rating.Trim().ToLowerInvariant();
+        List<JObject> hits = [];
+        HashSet<string> seen = [];
+
+        void Add(SqliteDataReader reader)
+        {
+            string id = reader.GetString(0);
+            if (!seen.Add(id))
+            {
+                return;
+            }
+            string bookId = reader.IsDBNull(1) ? "" : reader.GetString(1);
+            if (bookFilter is not null && !bookFilter.Contains(bookId))
+            {
+                seen.Remove(id);
+                return;
+            }
+            string title = reader.IsDBNull(2) ? "" : reader.GetString(2);
+            string tags = reader.IsDBNull(3) ? "" : reader.GetString(3);
+            string text = reader.IsDBNull(4) ? "" : reader.GetString(4);
+            string body = reader.IsDBNull(5) ? "" : reader.GetString(5);
+            string rowRating = reader.IsDBNull(6) ? "" : reader.GetString(6);
+            JToken metaTok = new JObject();
+            if (!reader.IsDBNull(7))
+            {
+                try { metaTok = JToken.Parse(reader.GetString(7)); } catch { metaTok = new JObject(); }
+            }
+            hits.Add(new JObject
+            {
+                ["id"] = id,
+                ["book"] = bookId,
+                ["source"] = "book",
+                ["title"] = title,
+                ["tags"] = tags,
+                ["text"] = text.Length > 600 ? text[..600] + "…" : text,
+                ["body"] = body.Length > 1200 ? body[..1200] + "…" : body,
+                ["rating"] = rowRating,
+                ["meta"] = metaTok,
+                ["note"] = "BOOK reference — remix style/ideas, do not paste long verbatim",
+            });
+        }
+
+        lock (_lock)
+        {
+            EnsureOpen();
+            if (!TableExists("books_rows"))
+            {
+                return [];
+            }
+
+            string match = BuildFtsMatch(query);
+            if (!string.IsNullOrWhiteSpace(match) && TableExists("books_fts"))
+            {
+                try
+                {
+                    using SqliteCommand cmd = _conn.CreateCommand();
+                    string sql =
+                        """
+                        SELECT b.id, b.book_id, b.title, b.tags, b.text, b.body, b.rating, b.meta_json
+                        FROM books_rows b
+                        WHERE b.rowid IN (SELECT rowid FROM books_fts WHERE books_fts MATCH $q)
+                        """;
+                    if (ratingFilter is not null)
+                    {
+                        sql += " AND lower(b.rating) = $r";
+                    }
+                    sql += " LIMIT $lim";
+                    cmd.CommandText = sql;
+                    cmd.Parameters.AddWithValue("$q", match);
+                    if (ratingFilter is not null)
+                    {
+                        cmd.Parameters.AddWithValue("$r", ratingFilter);
+                    }
+                    cmd.Parameters.AddWithValue("$lim", cap);
+                    using SqliteDataReader reader = cmd.ExecuteReader();
+                    while (reader.Read() && hits.Count < cap)
+                    {
+                        Add(reader);
+                    }
+                }
+                catch (Exception ex)
+                {
+                    Logs.Debug($"AssistentMemory books FTS: {ex.Message}");
+                }
+            }
+
+            if (hits.Count < cap)
+            {
+                try
+                {
+                    using SqliteCommand cmd = _conn.CreateCommand();
+                    string sql =
+                        """
+                        SELECT id, book_id, title, tags, text, body, rating, meta_json
+                        FROM books_rows
+                        WHERE (title LIKE $p ESCAPE '\' OR tags LIKE $p ESCAPE '\' OR text LIKE $p ESCAPE '\' OR body LIKE $p ESCAPE '\' OR search_blob LIKE $p ESCAPE '\')
+                        """;
+                    if (ratingFilter is not null)
+                    {
+                        sql += " AND lower(rating) = $r";
+                    }
+                    sql += " LIMIT $lim";
+                    cmd.CommandText = sql;
+                    cmd.Parameters.AddWithValue("$p", "%" + EscapeLike(query) + "%");
+                    if (ratingFilter is not null)
+                    {
+                        cmd.Parameters.AddWithValue("$r", ratingFilter);
+                    }
+                    cmd.Parameters.AddWithValue("$lim", cap);
+                    using SqliteDataReader reader = cmd.ExecuteReader();
+                    while (reader.Read() && hits.Count < cap)
+                    {
+                        Add(reader);
+                    }
+                }
+                catch (Exception ex)
+                {
+                    Logs.Debug($"AssistentMemory books LIKE: {ex.Message}");
+                }
+            }
+        }
+
+        return new JArray(hits.Take(cap));
+    }
+}

AssistentMemory.Heard.cs

@@ -44,47 +44,10 @@ public sealed partial class AssistentMemory
 
     public void SetTrainSampleAgentLinked(string id, bool linked)
     {
-        if (string.IsNullOrWhiteSpace(id))
+        // Training UI removed — no-op.
-        {
-            return;
-        }
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            if (!HasColumn("train_samples", "agent_linked"))
-            {
-                return;
-            }
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText = "UPDATE train_samples SET agent_linked = $v, updated_at = $u WHERE id = $id";
-            cmd.Parameters.AddWithValue("$v", linked ? 1 : 0);
-            cmd.Parameters.AddWithValue("$u", DateTimeOffset.UtcNow.ToUnixTimeMilliseconds());
-            cmd.Parameters.AddWithValue("$id", id.Trim());
-            cmd.ExecuteNonQuery();
-        }
     }
 
-    public int CountAgentLinkedTrainSamples()
+    public int CountAgentLinkedTrainSamples() => 0;
-    {
-        lock (_lock)
-        {
-            try
-            {
-                EnsureTrainingReady();
-            }
-            catch
-            {
-                return 0;
-            }
-            if (!HasColumn("train_samples", "agent_linked"))
-            {
-                return 0;
-            }
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText = "SELECT COUNT(*) FROM train_samples WHERE agent_linked = 1";
-            return Convert.ToInt32(cmd.ExecuteScalar());
-        }
-    }
 
     public async Task<bool> LinkTrainSampleToAgentAsync(string baseUrl, JObject sample, string embedModel)
     {

AssistentMemory.Training.cs

@@ -1,385 +0,0 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using Microsoft.Data.Sqlite;
-using Newtonsoft.Json.Linq;
-using SwarmUI.Utils;
-
-namespace Mrleo1nid.SwarmAssistent;
-
-/// <summary>Training datasets, samples, and job metadata in assistent.sqlite.</summary>
-public sealed partial class AssistentMemory
-{
-    public const string KvHfDatasetCache = "hf_dataset_cache";
-
-    void EnsureTrainingSchema()
-    {
-        Exec(
-            """
-            CREATE TABLE IF NOT EXISTS train_datasets (
-              id TEXT PRIMARY KEY,
-              title TEXT NOT NULL DEFAULT '',
-              created_at INTEGER NOT NULL,
-              updated_at INTEGER NOT NULL,
-              meta_json TEXT
-            );
-            CREATE TABLE IF NOT EXISTS train_samples (
-              id TEXT PRIMARY KEY,
-              dataset_id TEXT NOT NULL DEFAULT 'default',
-              source TEXT NOT NULL DEFAULT 'manual',
-              chat_id TEXT,
-              persona TEXT,
-              pack TEXT,
-              hf_repo TEXT,
-              messages_json TEXT NOT NULL DEFAULT '[]',
-              status TEXT NOT NULL DEFAULT 'draft',
-              created_at INTEGER NOT NULL,
-              updated_at INTEGER NOT NULL,
-              FOREIGN KEY(dataset_id) REFERENCES train_datasets(id) ON DELETE CASCADE
-            );
-            CREATE INDEX IF NOT EXISTS idx_train_samples_status ON train_samples(status);
-            CREATE INDEX IF NOT EXISTS idx_train_samples_dataset ON train_samples(dataset_id);
-            CREATE TABLE IF NOT EXISTS train_jobs (
-              id TEXT PRIMARY KEY,
-              kind TEXT NOT NULL,
-              status TEXT NOT NULL DEFAULT 'pending',
-              config_json TEXT,
-              base_model TEXT,
-              output_name TEXT,
-              log_path TEXT,
-              progress_json TEXT,
-              created_at INTEGER NOT NULL,
-              updated_at INTEGER NOT NULL,
-              finished_at INTEGER
-            );
-            CREATE INDEX IF NOT EXISTS idx_train_jobs_status ON train_jobs(status);
-            """);
-        if (!HasColumn("train_samples", "agent_linked"))
-        {
-            Exec("ALTER TABLE train_samples ADD COLUMN agent_linked INTEGER NOT NULL DEFAULT 0");
-        }
-        using SqliteCommand cmd = _conn.CreateCommand();
-        cmd.CommandText = "INSERT OR IGNORE INTO train_datasets(id, title, created_at, updated_at) VALUES('default', 'Default', $u, $u)";
-        cmd.Parameters.AddWithValue("$u", DateTimeOffset.UtcNow.ToUnixTimeMilliseconds());
-        cmd.ExecuteNonQuery();
-    }
-
-    public List<JObject> ListTrainSamples(string status = null, string persona = null, string datasetId = null, int limit = 200)
-    {
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            int take = Math.Clamp(limit, 1, 2000);
-            List<string> where = [];
-            if (!string.IsNullOrWhiteSpace(status) && !string.Equals(status, "all", StringComparison.OrdinalIgnoreCase))
-            {
-                where.Add("status = $status");
-            }
-            if (!string.IsNullOrWhiteSpace(persona) && !string.Equals(persona, "all", StringComparison.OrdinalIgnoreCase))
-            {
-                where.Add("persona = $persona");
-            }
-            if (!string.IsNullOrWhiteSpace(datasetId))
-            {
-                where.Add("dataset_id = $ds");
-            }
-            bool hasAgentLinked = HasColumn("train_samples", "agent_linked");
-            string sql = hasAgentLinked
-                ? "SELECT id, dataset_id, source, chat_id, persona, pack, hf_repo, messages_json, status, created_at, updated_at, agent_linked FROM train_samples"
-                : "SELECT id, dataset_id, source, chat_id, persona, pack, hf_repo, messages_json, status, created_at, updated_at FROM train_samples";
-            if (where.Count > 0)
-            {
-                sql += " WHERE " + string.Join(" AND ", where);
-            }
-            sql += " ORDER BY updated_at DESC LIMIT $lim";
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText = sql;
-            if (where.Any(w => w.Contains("$status")))
-            {
-                cmd.Parameters.AddWithValue("$status", status.Trim());
-            }
-            if (where.Any(w => w.Contains("$persona")))
-            {
-                cmd.Parameters.AddWithValue("$persona", persona.Trim());
-            }
-            if (where.Any(w => w.Contains("$ds")))
-            {
-                cmd.Parameters.AddWithValue("$ds", datasetId.Trim());
-            }
-            cmd.Parameters.AddWithValue("$lim", take);
-            List<JObject> list = [];
-            using SqliteDataReader r = cmd.ExecuteReader();
-            while (r.Read())
-            {
-                list.Add(ReadTrainSampleRow(r));
-            }
-            return list;
-        }
-    }
-
-    static JObject ReadTrainSampleRow(SqliteDataReader r)
-    {
-        JArray messages = [];
-        try
-        {
-            messages = JArray.Parse(r.GetString(7));
-        }
-        catch
-        {
-            // ignore
-        }
-        bool hasAgentLinked = r.FieldCount > 11;
-        return new JObject
-        {
-            ["id"] = r.GetString(0),
-            ["dataset_id"] = r.GetString(1),
-            ["source"] = r.GetString(2),
-            ["chat_id"] = r.IsDBNull(3) ? null : r.GetString(3),
-            ["persona"] = r.IsDBNull(4) ? null : r.GetString(4),
-            ["pack"] = r.IsDBNull(5) ? null : r.GetString(5),
-            ["hf_repo"] = r.IsDBNull(6) ? null : r.GetString(6),
-            ["messages"] = messages,
-            ["status"] = r.GetString(8),
-            ["createdAt"] = r.GetInt64(9),
-            ["updatedAt"] = r.GetInt64(10),
-            ["agent_linked"] = hasAgentLinked && !r.IsDBNull(11) && r.GetInt64(11) != 0,
-        };
-    }
-
-    public JObject GetTrainSample(string id)
-    {
-        if (string.IsNullOrWhiteSpace(id))
-        {
-            return null;
-        }
-        lock (_lock)
-        {
-            EnsureOpen();
-            bool hasAgentLinked = HasColumn("train_samples", "agent_linked");
-            string sql = hasAgentLinked
-                ? "SELECT id, dataset_id, source, chat_id, persona, pack, hf_repo, messages_json, status, created_at, updated_at, agent_linked FROM train_samples WHERE id = $id LIMIT 1"
-                : "SELECT id, dataset_id, source, chat_id, persona, pack, hf_repo, messages_json, status, created_at, updated_at FROM train_samples WHERE id = $id LIMIT 1";
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText = sql;
-            cmd.Parameters.AddWithValue("$id", id.Trim());
-            using SqliteDataReader r = cmd.ExecuteReader();
-            return r.Read() ? ReadTrainSampleRow(r) : null;
-        }
-    }
-
-    public int ImportTrainSamplesBatch(IEnumerable<JObject> samples)
-    {
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            int imported = 0;
-            using SqliteTransaction tx = _conn.BeginTransaction();
-            foreach (JObject sample in samples)
-            {
-                if (sample is null)
-                {
-                    continue;
-                }
-                UpsertTrainSampleCore(sample, tx);
-                imported++;
-            }
-            tx.Commit();
-            return imported;
-        }
-    }
-
-    public JObject UpsertTrainSample(JObject sample)
-    {
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            return UpsertTrainSampleCore(sample, null);
-        }
-    }
-
-    JObject UpsertTrainSampleCore(JObject sample, SqliteTransaction tx)
-    {
-        long now = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
-        string id = sample["id"]?.ToString()?.Trim();
-        if (string.IsNullOrWhiteSpace(id))
-        {
-            id = $"ts_{now}_{Guid.NewGuid():N}"[..24];
-        }
-        string datasetId = sample["dataset_id"]?.ToString()?.Trim() ?? "default";
-        JArray messages = sample["messages"] as JArray ?? [];
-        using SqliteCommand cmd = _conn.CreateCommand();
-        if (tx is not null)
-        {
-            cmd.Transaction = tx;
-        }
-        cmd.CommandText =
-            """
-            INSERT INTO train_samples(id, dataset_id, source, chat_id, persona, pack, hf_repo, messages_json, status, created_at, updated_at)
-            VALUES($id, $ds, $src, $chat, $persona, $pack, $hf, $msg, $status, $c, $u)
-            ON CONFLICT(id) DO UPDATE SET
-              dataset_id = excluded.dataset_id,
-              source = excluded.source,
-              chat_id = excluded.chat_id,
-              persona = excluded.persona,
-              pack = excluded.pack,
-              hf_repo = excluded.hf_repo,
-              messages_json = excluded.messages_json,
-              status = excluded.status,
-              updated_at = excluded.updated_at
-            """;
-        cmd.Parameters.AddWithValue("$id", id);
-        cmd.Parameters.AddWithValue("$ds", datasetId);
-        cmd.Parameters.AddWithValue("$src", sample["source"]?.ToString() ?? "manual");
-        cmd.Parameters.AddWithValue("$chat", (object)sample["chat_id"]?.ToString() ?? DBNull.Value);
-        cmd.Parameters.AddWithValue("$persona", (object)sample["persona"]?.ToString() ?? DBNull.Value);
-        cmd.Parameters.AddWithValue("$pack", (object)sample["pack"]?.ToString() ?? DBNull.Value);
-        cmd.Parameters.AddWithValue("$hf", (object)sample["hf_repo"]?.ToString() ?? DBNull.Value);
-        cmd.Parameters.AddWithValue("$msg", messages.ToString(Newtonsoft.Json.Formatting.None));
-        cmd.Parameters.AddWithValue("$status", sample["status"]?.ToString() ?? "draft");
-        long created = sample["createdAt"]?.Value<long?>() ?? now;
-        cmd.Parameters.AddWithValue("$c", created);
-        cmd.Parameters.AddWithValue("$u", now);
-        cmd.ExecuteNonQuery();
-        return new JObject { ["id"] = id, ["updatedAt"] = now };
-    }
-
-    public bool DeleteTrainSample(string id)
-    {
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText = "DELETE FROM train_samples WHERE id = $id";
-            cmd.Parameters.AddWithValue("$id", id ?? "");
-            return cmd.ExecuteNonQuery() > 0;
-        }
-    }
-
-    public int CountTrainSamples(string status = null)
-    {
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            using SqliteCommand cmd = _conn.CreateCommand();
-            if (string.IsNullOrWhiteSpace(status) || string.Equals(status, "all", StringComparison.OrdinalIgnoreCase))
-            {
-                cmd.CommandText = "SELECT COUNT(*) FROM train_samples";
-            }
-            else
-            {
-                cmd.CommandText = "SELECT COUNT(*) FROM train_samples WHERE status = $s";
-                cmd.Parameters.AddWithValue("$s", status.Trim());
-            }
-            return Convert.ToInt32(cmd.ExecuteScalar());
-        }
-    }
-
-    public JObject SaveTrainJob(JObject job)
-    {
-        lock (_lock)
-        {
-            EnsureOpen();
-            long now = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
-            string id = job["id"]?.ToString()?.Trim();
-            if (string.IsNullOrWhiteSpace(id))
-            {
-                id = $"tj_{now}_{Guid.NewGuid():N}"[..24];
-            }
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText =
-                """
-                INSERT INTO train_jobs(id, kind, status, config_json, base_model, output_name, log_path, progress_json, created_at, updated_at, finished_at)
-                VALUES($id, $kind, $status, $cfg, $base, $out, $log, $prog, $c, $u, $f)
-                ON CONFLICT(id) DO UPDATE SET
-                  status = excluded.status,
-                  config_json = excluded.config_json,
-                  log_path = excluded.log_path,
-                  progress_json = excluded.progress_json,
-                  updated_at = excluded.updated_at,
-                  finished_at = excluded.finished_at
-                """;
-            cmd.Parameters.AddWithValue("$id", id);
-            cmd.Parameters.AddWithValue("$kind", job["kind"]?.ToString() ?? "qlora");
-            cmd.Parameters.AddWithValue("$status", job["status"]?.ToString() ?? "pending");
-            cmd.Parameters.AddWithValue("$cfg", job["config"]?.ToString(Newtonsoft.Json.Formatting.None) ?? job["config_json"]?.ToString() ?? "{}");
-            cmd.Parameters.AddWithValue("$base", (object)job["base_model"]?.ToString() ?? DBNull.Value);
-            cmd.Parameters.AddWithValue("$out", (object)job["output_name"]?.ToString() ?? DBNull.Value);
-            cmd.Parameters.AddWithValue("$log", (object)job["log_path"]?.ToString() ?? DBNull.Value);
-            cmd.Parameters.AddWithValue("$prog", (object)(job["progress"]?.ToString(Newtonsoft.Json.Formatting.None) ?? job["progress_json"]?.ToString()) ?? DBNull.Value);
-            cmd.Parameters.AddWithValue("$c", job["created_at"]?.Value<long?>() ?? job["createdAt"]?.Value<long?>() ?? now);
-            cmd.Parameters.AddWithValue("$u", now);
-            cmd.Parameters.AddWithValue("$f", (object)(job["finished_at"]?.Value<long?>() ?? job["finishedAt"]?.Value<long?>()) ?? DBNull.Value);
-            cmd.ExecuteNonQuery();
-            return new JObject { ["id"] = id };
-        }
-    }
-
-    public JObject GetTrainJob(string id)
-    {
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText = "SELECT id, kind, status, config_json, base_model, output_name, log_path, progress_json, created_at, updated_at, finished_at FROM train_jobs WHERE id = $id";
-            cmd.Parameters.AddWithValue("$id", id ?? "");
-            using SqliteDataReader r = cmd.ExecuteReader();
-            if (!r.Read())
-            {
-                return null;
-            }
-            return ReadTrainJobRow(r);
-        }
-    }
-
-    public JObject GetLastTrainJob()
-    {
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText =
-                "SELECT id, kind, status, config_json, base_model, output_name, log_path, progress_json, created_at, updated_at, finished_at "
-                + "FROM train_jobs ORDER BY updated_at DESC LIMIT 1";
-            using SqliteDataReader r = cmd.ExecuteReader();
-            if (!r.Read())
-            {
-                return null;
-            }
-            return ReadTrainJobRow(r);
-        }
-    }
-
-    static JObject ReadTrainJobRow(SqliteDataReader r)
-    {
-        return new JObject
-        {
-            ["id"] = r.GetString(0),
-            ["kind"] = r.GetString(1),
-            ["status"] = r.GetString(2),
-            ["config_json"] = r.IsDBNull(3) ? null : r.GetString(3),
-            ["base_model"] = r.IsDBNull(4) ? null : r.GetString(4),
-            ["output_name"] = r.IsDBNull(5) ? null : r.GetString(5),
-            ["log_path"] = r.IsDBNull(6) ? null : r.GetString(6),
-            ["progress_json"] = r.IsDBNull(7) ? null : r.GetString(7),
-            ["created_at"] = r.GetInt64(8),
-            ["updated_at"] = r.GetInt64(9),
-            ["finished_at"] = r.IsDBNull(10) ? null : r.GetInt64(10),
-        };
-    }
-
-    public JObject GetActiveTrainJob()
-    {
-        lock (_lock)
-        {
-            EnsureTrainingReady();
-            using SqliteCommand cmd = _conn.CreateCommand();
-            cmd.CommandText = "SELECT id, kind, status, config_json, base_model, output_name, log_path, progress_json, created_at, updated_at, finished_at FROM train_jobs WHERE status IN ('pending','running') ORDER BY updated_at DESC LIMIT 1";
-            using SqliteDataReader r = cmd.ExecuteReader();
-            if (!r.Read())
-            {
-                return null;
-            }
-            return ReadTrainJobRow(r);
-        }
-    }
-}

AssistentMemory.cs

@@ -144,14 +144,6 @@ public sealed partial class AssistentMemory : IDisposable
             Logs.Debug($"AssistentMemory store schema: {ex.Message}");
         }
         try
-        {
-            EnsureTrainingSchema();
-        }
-        catch (Exception ex)
-        {
-            Logs.Error($"AssistentMemory training schema failed: {ex.Message}");
-        }
-        try
         {
             EnsureUserPrefsSchema();
         }
@@ -193,17 +185,8 @@ public sealed partial class AssistentMemory : IDisposable
 
     internal void EnsureTrainingReady()
     {
+        // Training UI removed in 0.16 — heard examples live in memories only.
         EnsureOpen();
-        if (!HasTable("train_samples"))
-        {
-            EnsureTrainingSchema();
-        }
-        if (!HasTable("train_samples"))
-        {
-            throw new InvalidOperationException(
-                "Assistent training database unavailable (train_samples). "
-                + "Run gpu-rent seed-extensions and restart SwarmUI (≥0.15.6).");
-        }
     }
 
     void MigratePersonaColumn()
@@ -443,6 +426,7 @@ public sealed partial class AssistentMemory : IDisposable
         {
             TryIndexTags();
             TryIndexExamples();
+            TryIndexBooks();
             return;
         }
 
@@ -478,6 +462,7 @@ public sealed partial class AssistentMemory : IDisposable
             Logs.Debug($"AssistentMemory seed defer (embed unavailable): {ex.Message}");
             TryIndexTags();
             TryIndexExamples();
+            TryIndexBooks();
             return;
         }
 

AssistentOllama.cs

@@ -339,7 +339,7 @@ public partial class SwarmAssistentExtension
         string embedModel = raw?["embed_model"]?.ToString() ?? Config.LoadSettings()["embed_model"]?.ToString();
         try
         {
-            (string reply, JObject parsed, JArray civitai, int systemChars, JObject systemLayers) = await RunChatWithHops(
+            (string reply, JObject parsed, JArray civitai, JObject knowledge, int systemChars, JObject systemLayers) = await RunChatWithHops(
                 session, root, modelName, packName, includeBase, contextJson, userMessages, personaId: persona, skillIds: skills, embedModel: embedModel);
             JObject result = new()
             {
@@ -350,6 +350,7 @@ public partial class SwarmAssistentExtension
                 ["persona"] = persona,
                 ["raw"] = parsed,
                 ["civitai_results"] = civitai,
+                ["knowledge"] = knowledge,
                 ["system_chars"] = systemChars,
                 ["system_layers"] = systemLayers,
             };
@@ -409,7 +410,7 @@ public partial class SwarmAssistentExtension
                     }, API.WebsocketTimeout);
                 }
             }
-            (string reply, JObject parsed, JArray civitai, int systemChars, JObject systemLayers) = await RunChatWithHops(
+            (string reply, JObject parsed, JArray civitai, JObject knowledge, int systemChars, JObject systemLayers) = await RunChatWithHops(
                 session, root, modelName, packName, includeBase, contextJson, userMessages, OnDelta, OnHopStart, persona, skills, embedModel);
             JObject done = new()
             {
@@ -421,6 +422,7 @@ public partial class SwarmAssistentExtension
                 ["persona"] = persona,
                 ["raw"] = parsed,
                 ["civitai_results"] = civitai,
+                ["knowledge"] = knowledge,
                 ["system_chars"] = systemChars,
                 ["system_layers"] = systemLayers,
             };

AssistentPatch.cs

@@ -313,6 +313,10 @@ public partial class SwarmAssistentExtension
         {
             return "ask_inventory";
         }
+        if ((AskContains(patch, "knowledge") || ActionsContain(patch, "lookup_knowledge")) && !Skip("ask_knowledge"))
+        {
+            return "ask_knowledge";
+        }
         if ((AskContains(patch, "examples") || ActionsContain(patch, "lookup_examples")) && !Skip("ask_examples"))
         {
             return "ask_examples";

AssistentTraining.Agent.cs

@@ -1,181 +0,0 @@
-using System;
-using System.Collections.Generic;
-using System.Linq;
-using System.Threading.Tasks;
-using Newtonsoft.Json.Linq;
-using SwarmUI.Accounts;
-using SwarmUI.Utils;
-
-namespace Mrleo1nid.SwarmAssistent;
-
-/// <summary>Link training dataset samples to the live agent as retrievable &quot;heard&quot; examples.</summary>
-public partial class SwarmAssistentExtension
-{
-    string MemoryEmbedForTraining(string personaId = null)
-    {
-        string pid = AssistentConfig.SafeId(personaId) ?? Config.DefaultPersonaId();
-        return Config.LoadSettings()["embed_model"]?.ToString()
-            ?? Config.LoadAssistant(pid)["embed_model"]?.ToString()
-            ?? "nomic-embed-text";
-    }
-
-    string MemoryBaseForTraining(JObject raw = null)
-        => MemoryBaseUrl(raw?["base_url"]?.ToString());
-
-    public async Task<JObject> AssistentGetDatasetAgentSettings(Session session)
-    {
-        await Task.CompletedTask;
-        try
-        {
-            JObject settings = Config.LoadTrainingAgent();
-            return new JObject
-            {
-                ["success"] = true,
-                ["settings"] = settings,
-                ["linked"] = Memory.CountAgentLinkedTrainSamples(),
-                ["approved"] = Memory.CountTrainSamples("approved"),
-            };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = ex.Message };
-        }
-    }
-
-    public async Task<JObject> AssistentSaveDatasetAgentSettings(Session session, JObject settings)
-    {
-        await Task.CompletedTask;
-        if (settings is null)
-        {
-            return new JObject { ["error"] = "settings required" };
-        }
-        Config.SaveTrainingAgent(settings);
-        return new JObject { ["success"] = true, ["settings"] = Config.LoadTrainingAgent() };
-    }
-
-    public async Task<JObject> AssistentLinkTrainSampleToAgent(Session session, string id, JObject raw = null)
-    {
-        if (string.IsNullOrWhiteSpace(id))
-        {
-            return new JObject { ["error"] = "id required" };
-        }
-        JObject sample = Memory.GetTrainSample(id.Trim());
-        if (sample is null)
-        {
-            return new JObject { ["error"] = "sample not found" };
-        }
-        if (!string.Equals(sample["status"]?.ToString(), "approved", StringComparison.OrdinalIgnoreCase))
-        {
-            return new JObject { ["error"] = "only approved samples can be linked to the agent" };
-        }
-        try
-        {
-            string embed = MemoryEmbedForTraining(sample["persona"]?.ToString());
-            bool ok = await Memory.LinkTrainSampleToAgentAsync(MemoryBaseForTraining(raw), sample, embed);
-            return new JObject { ["success"] = ok, ["linked"] = Memory.CountAgentLinkedTrainSamples() };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = ex.Message };
-        }
-    }
-
-    public async Task<JObject> AssistentUnlinkTrainSampleFromAgent(Session session, string id)
-    {
-        await Task.CompletedTask;
-        if (string.IsNullOrWhiteSpace(id))
-        {
-            return new JObject { ["error"] = "id required" };
-        }
-        JObject sample = Memory.GetTrainSample(id.Trim());
-        if (sample is null)
-        {
-            return new JObject { ["error"] = "sample not found" };
-        }
-        Memory.UnlinkTrainSampleFromAgent(sample);
-        return new JObject { ["success"] = true, ["linked"] = Memory.CountAgentLinkedTrainSamples() };
-    }
-
-    public async Task<JObject> AssistentSyncDatasetToAgent(Session session, JObject raw = null)
-    {
-        bool approvedOnly = raw?["approved_only"]?.Value<bool?>() ?? true;
-        bool relink = raw?["relink"]?.Value<bool?>() ?? false;
-        string persona = raw?["persona"]?.ToString();
-        string status = approvedOnly ? "approved" : "all";
-        List<JObject> samples = Memory.ListTrainSamples(status, persona, null, 2000);
-        string baseUrl = MemoryBaseForTraining(raw);
-        int linked = 0;
-        int skipped = 0;
-        List<string> errors = [];
-        foreach (JObject sample in samples)
-        {
-            bool already = sample["agent_linked"]?.Value<bool?>() ?? false;
-            if (already && !relink)
-            {
-                skipped++;
-                continue;
-            }
-            if (!string.Equals(sample["status"]?.ToString(), "approved", StringComparison.OrdinalIgnoreCase))
-            {
-                skipped++;
-                continue;
-            }
-            try
-            {
-                string embed = MemoryEmbedForTraining(sample["persona"]?.ToString());
-                if (await Memory.LinkTrainSampleToAgentAsync(baseUrl, sample, embed))
-                {
-                    linked++;
-                }
-                else
-                {
-                    skipped++;
-                }
-            }
-            catch (Exception ex)
-            {
-                errors.Add($"{sample["id"]}: {ex.Message}");
-            }
-        }
-        return new JObject
-        {
-            ["success"] = true,
-            ["linked_now"] = linked,
-            ["skipped"] = skipped,
-            ["total_linked"] = Memory.CountAgentLinkedTrainSamples(),
-            ["errors"] = new JArray(errors.Take(8)),
-        };
-    }
-
-    async Task TryAutoLinkTrainSample(Session session, JObject sample, JObject raw = null)
-    {
-        if (sample is null || Memory is null)
-        {
-            return;
-        }
-        JObject agent = Config.LoadTrainingAgent();
-        if (agent["enabled"]?.Value<bool?>() == false)
-        {
-            return;
-        }
-        if (agent["auto_link_on_approve"]?.Value<bool?>() == false)
-        {
-            return;
-        }
-        string status = sample["status"]?.ToString() ?? "";
-        if (!string.Equals(status, "approved", StringComparison.OrdinalIgnoreCase))
-        {
-            Memory.UnlinkTrainSampleFromAgent(sample);
-            return;
-        }
-        try
-        {
-            string embed = MemoryEmbedForTraining(sample["persona"]?.ToString());
-            await Memory.LinkTrainSampleToAgentAsync(MemoryBaseForTraining(raw), sample, embed);
-        }
-        catch (Exception ex)
-        {
-            Logs.Debug($"TryAutoLinkTrainSample: {ex.Message}");
-        }
-    }
-}

AssistentTraining.cs

@@ -1,456 +0,0 @@
-using System;
-using System.Collections.Generic;
-using System.IO;
-using System.Linq;
-using System.Net.Http;
-using System.Text;
-using System.Threading.Tasks;
-using Newtonsoft.Json.Linq;
-using SwarmUI.Accounts;
-using SwarmUI.Utils;
-
-namespace Mrleo1nid.SwarmAssistent;
-
-/// <summary>Training samples, dataset import/export, Ollama Modelfile builder.</summary>
-public partial class SwarmAssistentExtension
-{
-    static string TrainingRoot()
-    {
-        string root = Path.Combine(DataRoot(), "Assistent", "training");
-        Directory.CreateDirectory(root);
-        Directory.CreateDirectory(Path.Combine(root, "datasets"));
-        Directory.CreateDirectory(Path.Combine(root, "jobs"));
-        Directory.CreateDirectory(Path.Combine(root, "adapters"));
-        return root;
-    }
-
-    public async Task<JObject> AssistentListTrainSamples(Session session, string status = null, string persona = null, int limit = 200)
-    {
-        await Task.CompletedTask;
-        try
-        {
-            List<JObject> list = Memory.ListTrainSamples(status, persona, null, limit);
-            return new JObject
-            {
-                ["success"] = true,
-                ["samples"] = new JArray(list),
-                ["approved"] = Memory.CountTrainSamples("approved"),
-                ["draft"] = Memory.CountTrainSamples("draft"),
-                ["total"] = Memory.CountTrainSamples(null),
-            };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = ex.Message };
-        }
-    }
-
-    public async Task<JObject> AssistentUpsertTrainSample(Session session, JObject raw)
-    {
-        await Task.CompletedTask;
-        if (raw is null)
-        {
-            return new JObject { ["error"] = "body required" };
-        }
-        try
-        {
-            JObject saved = Memory.UpsertTrainSample(raw);
-            JObject full = Memory.GetTrainSample(saved["id"]?.ToString()) ?? raw;
-            await TryAutoLinkTrainSample(session, full, raw);
-            return new JObject { ["success"] = true, ["sample"] = full };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = ex.Message };
-        }
-    }
-
-    public async Task<JObject> AssistentDeleteTrainSample(Session session, string id)
-    {
-        await Task.CompletedTask;
-        if (string.IsNullOrWhiteSpace(id))
-        {
-            return new JObject { ["error"] = "id required" };
-        }
-        JObject sample = Memory.GetTrainSample(id.Trim());
-        bool ok = Memory.DeleteTrainSample(id.Trim());
-        if (ok && sample is not null)
-        {
-            Memory.UnlinkTrainSampleFromAgent(sample);
-        }
-        return new JObject { ["success"] = true, ["deleted"] = ok };
-    }
-
-    public async Task<JObject> AssistentBuildDatasetFromChats(Session session, bool approved_only = false)
-    {
-        await Task.CompletedTask;
-        try
-        {
-            List<JObject> chats = Memory.ListChats(withMessages: true, limit: AssistentMemory.MaxChatsStored);
-            int added = 0;
-            foreach (JObject chat in chats)
-            {
-                JArray messages = chat["messages"] as JArray ?? [];
-                for (int i = 0; i < messages.Count - 1; i++)
-                {
-                    if (messages[i] is not JObject u || messages[i + 1] is not JObject a)
-                    {
-                        continue;
-                    }
-                    if (!string.Equals(u["role"]?.ToString(), "user", StringComparison.OrdinalIgnoreCase))
-                    {
-                        continue;
-                    }
-                    if (!string.Equals(a["role"]?.ToString(), "assistant", StringComparison.OrdinalIgnoreCase))
-                    {
-                        continue;
-                    }
-                    Memory.UpsertTrainSample(new JObject
-                    {
-                        ["source"] = "chat",
-                        ["chat_id"] = chat["id"],
-                        ["persona"] = a["persona"] ?? u["persona"],
-                        ["pack"] = a["pack"] ?? u["pack"],
-                        ["status"] = approved_only ? "approved" : "draft",
-                        ["messages"] = new JArray { u.DeepClone(), a.DeepClone() },
-                    });
-                    added++;
-                }
-            }
-            return new JObject { ["success"] = true, ["added"] = added };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = ex.Message };
-        }
-    }
-
-    public async Task<JObject> AssistentImportDataset(Session session, JObject raw)
-    {
-        await Task.CompletedTask;
-        string content = raw?["content"]?.ToString();
-        string format = raw?["format"]?.ToString() ?? "auto";
-        if (string.IsNullOrWhiteSpace(content))
-        {
-            return new JObject { ["error"] = "content required" };
-        }
-        try
-        {
-            int imported = 0;
-            string fmt = (format ?? "auto").Trim().ToLowerInvariant();
-            List<JObject> records = ParseDatasetContent(content, fmt);
-            foreach (JObject rec in records)
-            {
-                JArray messages = rec["messages"] as JArray;
-                if (messages is null || messages.Count == 0)
-                {
-                    continue;
-                }
-                Memory.UpsertTrainSample(new JObject
-                {
-                    ["source"] = "import",
-                    ["messages"] = messages,
-                    ["status"] = "draft",
-                });
-                imported++;
-            }
-            return new JObject { ["success"] = true, ["imported"] = imported };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = ex.Message };
-        }
-    }
-
-    static List<JObject> ParseDatasetContent(string content, string format)
-    {
-        List<JObject> list = [];
-        string trimmed = content.Trim();
-        if (trimmed.StartsWith('['))
-        {
-            JArray arr = JArray.Parse(trimmed);
-            foreach (JToken t in arr)
-            {
-                if (t is JObject o)
-                {
-                    JArray msgs = ExtractMessagesFromRecord(o);
-                    if (msgs != null)
-                    {
-                        list.Add(new JObject { ["messages"] = msgs });
-                    }
-                }
-            }
-            return list;
-        }
-        if (format == "csv" || LooksLikeCsv(trimmed))
-        {
-            return ParseCsvDataset(trimmed);
-        }
-        foreach (string line in trimmed.Split('\n'))
-        {
-            string ln = line.Trim();
-            if (string.IsNullOrWhiteSpace(ln))
-            {
-                continue;
-            }
-            try
-            {
-                JObject o = JObject.Parse(ln);
-                JArray msgs = ExtractMessagesFromRecord(o);
-                if (msgs != null)
-                {
-                    list.Add(new JObject { ["messages"] = msgs });
-                }
-            }
-            catch
-            {
-                // skip bad line
-            }
-        }
-        return list;
-    }
-
-    static bool LooksLikeCsv(string s) => s.Contains(',') && s.Contains('\n') && !s.TrimStart().StartsWith('{');
-
-    static List<JObject> ParseCsvDataset(string csv)
-    {
-        List<JObject> list = [];
-        string[] lines = csv.Split('\n').Select(l => l.Trim()).Where(l => l.Length > 0).ToArray();
-        if (lines.Length < 2)
-        {
-            return list;
-        }
-        string[] headers = lines[0].Split(',').Select(h => h.Trim().Trim('"')).ToArray();
-        int promptIdx = Array.FindIndex(headers, h => h.Equals("prompt", StringComparison.OrdinalIgnoreCase) || h.Equals("question", StringComparison.OrdinalIgnoreCase) || h.Equals("instruction", StringComparison.OrdinalIgnoreCase));
-        int respIdx = Array.FindIndex(headers, h => h.Equals("response", StringComparison.OrdinalIgnoreCase) || h.Equals("answer", StringComparison.OrdinalIgnoreCase) || h.Equals("output", StringComparison.OrdinalIgnoreCase) || h.Equals("completion", StringComparison.OrdinalIgnoreCase));
-        if (promptIdx < 0 || respIdx < 0)
-        {
-            return list;
-        }
-        for (int i = 1; i < lines.Length; i++)
-        {
-            string[] cols = SplitCsvLine(lines[i]);
-            if (cols.Length <= Math.Max(promptIdx, respIdx))
-            {
-                continue;
-            }
-            list.Add(new JObject
-            {
-                ["messages"] = new JArray
-                {
-                    new JObject { ["role"] = "user", ["content"] = cols[promptIdx] },
-                    new JObject { ["role"] = "assistant", ["content"] = cols[respIdx] },
-                },
-            });
-        }
-        return list;
-    }
-
-    static string[] SplitCsvLine(string line)
-    {
-        List<string> parts = [];
-        StringBuilder cur = new();
-        bool inQ = false;
-        foreach (char c in line)
-        {
-            if (c == '"')
-            {
-                inQ = !inQ;
-                continue;
-            }
-            if (c == ',' && !inQ)
-            {
-                parts.Add(cur.ToString().Trim());
-                cur.Clear();
-                continue;
-            }
-            cur.Append(c);
-        }
-        parts.Add(cur.ToString().Trim());
-        return parts.ToArray();
-    }
-
-    static JArray ExtractMessagesFromRecord(JObject o)
-    {
-        if (o["messages"] is JArray msgs)
-        {
-            return NormalizeMessagesArray(msgs);
-        }
-        if (o["conversations"] is JArray conv)
-        {
-            return ConvertHfRowToMessages(new JObject { ["conversations"] = conv }, new JObject { ["kind"] = "conversations" }, null);
-        }
-        if (o["instruction"] != null && o["output"] != null)
-        {
-            return ConvertHfRowToMessages(o, new JObject { ["kind"] = "alpaca" }, null);
-        }
-        if (o["prompt"] != null && (o["response"] != null || o["completion"] != null))
-        {
-            return ConvertHfRowToMessages(o, new JObject { ["kind"] = "prompt_response", ["response_col"] = o["response"] != null ? "response" : "completion" }, null);
-        }
-        return null;
-    }
-
-    public async Task<JObject> AssistentExportDataset(Session session, string status = "approved", string format = "jsonl")
-    {
-        await Task.CompletedTask;
-        try
-        {
-            List<JObject> samples = Memory.ListTrainSamples(status, null, null, 5000);
-            StringBuilder sb = new();
-            int exported = 0;
-            foreach (JObject s in samples)
-            {
-                JArray messages = s["messages"] as JArray ?? [];
-                if (messages.Count == 0)
-                {
-                    continue;
-                }
-                exported++;
-                if (string.Equals(format, "sharegpt", StringComparison.OrdinalIgnoreCase))
-                {
-                    JArray conv = [];
-                    foreach (JToken m in messages)
-                    {
-                        if (m is not JObject mo)
-                        {
-                            continue;
-                        }
-                        string role = mo["role"]?.ToString() ?? "user";
-                        conv.Add(new JObject
-                        {
-                            ["from"] = role == "assistant" ? "gpt" : "human",
-                            ["value"] = mo["content"]?.ToString() ?? "",
-                        });
-                    }
-                    sb.AppendLine(new JObject { ["conversations"] = conv }.ToString(Newtonsoft.Json.Formatting.None));
-                }
-                else
-                {
-                    sb.AppendLine(new JObject { ["messages"] = messages }.ToString(Newtonsoft.Json.Formatting.None));
-                }
-            }
-            string path = Path.Combine(TrainingRoot(), "datasets", $"export_{DateTimeOffset.UtcNow.ToUnixTimeMilliseconds()}.jsonl");
-            await File.WriteAllTextAsync(path, sb.ToString(), Encoding.UTF8);
-            return new JObject { ["success"] = true, ["path"] = path, ["count"] = exported, ["content"] = sb.ToString() };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = ex.Message };
-        }
-    }
-
-    public async Task<JObject> AssistentCreateOllamaModel(Session session, JObject raw)
-    {
-        if (raw is null)
-        {
-            return new JObject { ["error"] = "body required" };
-        }
-        string baseUrl = NormalizeBaseUrl(raw["base_url"]?.ToString());
-        string baseModel = raw["base_model"]?.ToString()?.Trim();
-        string name = raw["name"]?.ToString()?.Trim();
-        string system = raw["system"]?.ToString() ?? "";
-        int shots = raw["shots"]?.Value<int?>() ?? 8;
-        if (string.IsNullOrWhiteSpace(baseModel) || string.IsNullOrWhiteSpace(name))
-        {
-            return new JObject { ["error"] = "base_model and name required" };
-        }
-        if (string.IsNullOrWhiteSpace(system))
-        {
-            string persona = AssistentConfig.SafeId(raw["persona"]?.ToString()) ?? Config.DefaultPersonaId();
-            system = Config.LoadCorePrompt(persona) + "\n\n" + Config.RenderIdentityBlock(persona, includeAllShelves: true);
-        }
-        StringBuilder mf = new();
-        mf.AppendLine($"FROM {baseModel}");
-        mf.AppendLine($"SYSTEM \"\"\"{system}\"\"\"");
-        List<JObject> samples = Memory.ListTrainSamples("approved", null, null, Math.Clamp(shots, 0, 32));
-        foreach (JObject s in samples.Take(shots))
-        {
-            JArray messages = s["messages"] as JArray ?? [];
-            foreach (JToken m in messages)
-            {
-                if (m is not JObject mo)
-                {
-                    continue;
-                }
-                string role = mo["role"]?.ToString() ?? "user";
-                string content = mo["content"]?.ToString() ?? "";
-                if (string.IsNullOrWhiteSpace(content))
-                {
-                    continue;
-                }
-                mf.AppendLine($"MESSAGE {role} \"\"\"{content.Replace("\"\"\"", "\"\"\"\"\"\"\"")}\"\"\"");
-            }
-        }
-        if (raw["num_ctx"] != null)
-        {
-            mf.AppendLine($"PARAMETER num_ctx {raw["num_ctx"]}");
-        }
-        if (raw["temperature"] != null)
-        {
-            mf.AppendLine($"PARAMETER temperature {raw["temperature"]}");
-        }
-        string modelfilePath = Path.Combine(TrainingRoot(), "jobs", $"modelfile_{DateTimeOffset.UtcNow.ToUnixTimeMilliseconds()}.Modelfile");
-        Directory.CreateDirectory(Path.GetDirectoryName(modelfilePath)!);
-        await File.WriteAllTextAsync(modelfilePath, mf.ToString(), Encoding.UTF8);
-        try
-        {
-            JObject payload = new()
-            {
-                ["name"] = name,
-                ["modelfile"] = mf.ToString(),
-                ["stream"] = false,
-            };
-            using StringContent content = new(payload.ToString(Newtonsoft.Json.Formatting.None), Encoding.UTF8, "application/json");
-            using HttpResponseMessage resp = await HttpClient.PostAsync($"{baseUrl}/api/create", content);
-            string body = await resp.Content.ReadAsStringAsync();
-            if (!resp.IsSuccessStatusCode)
-            {
-                return new JObject { ["error"] = $"Ollama create HTTP {(int)resp.StatusCode}: {Clip(body, 400)}", ["modelfile_path"] = modelfilePath };
-            }
-            return new JObject { ["success"] = true, ["name"] = name, ["modelfile_path"] = modelfilePath, ["ollama"] = body };
-        }
-        catch (Exception ex)
-        {
-            return new JObject { ["error"] = ex.Message, ["modelfile_path"] = modelfilePath };
-        }
-    }
-
-    public async Task<JObject> AssistentGetTrainJob(Session session, string id = null)
-    {
-        await Task.CompletedTask;
-        JObject job = string.IsNullOrWhiteSpace(id) ? Memory.GetActiveTrainJob() : Memory.GetTrainJob(id);
-        JObject lastJob = Memory.GetLastTrainJob();
-        if (job is not null && TrainingJobManager.IsRunning && string.Equals(job["id"]?.ToString(), TrainingJobManager.CurrentJobId, StringComparison.OrdinalIgnoreCase))
-        {
-            JObject live = TrainingJobManager.GetProgress();
-            job["progress_json"] = live.ToString(Newtonsoft.Json.Formatting.None);
-            job["status"] = live["status"]?.ToString() ?? job["status"];
-        }
-        return new JObject
-        {
-            ["success"] = true,
-            ["job"] = job,
-            ["last_job"] = lastJob,
-            ["training_active"] = TrainingJobManager.IsRunning,
-            ["progress"] = TrainingJobManager.IsRunning ? TrainingJobManager.GetProgress() : null,
-        };
-    }
-
-    public async Task<JObject> AssistentSaveRunnerSettings(Session session, JObject settings)
-    {
-        await Task.CompletedTask;
-        if (settings is null)
-        {
-            return new JObject { ["error"] = "settings required" };
-        }
-        Config.SaveTrainingRunner(settings);
-        return new JObject { ["success"] = true };
-    }
-
-    public async Task<JObject> AssistentGetRunnerSettings(Session session)
-    {
-        await Task.CompletedTask;
-        return new JObject { ["success"] = true, ["settings"] = Config.LoadTrainingRunner() };
-    }
-}

AssistentTrainingJobs.cs

@@ -1,607 +0,0 @@
-using System;
-using System.Collections.Generic;
-using System.Diagnostics;
-using System.IO;
-using System.Linq;
-using System.Net.Http;
-using System.Net.WebSockets;
-using System.Text;
-using System.Text.RegularExpressions;
-using System.Threading;
-using System.Threading.Tasks;
-using Newtonsoft.Json.Linq;
-using SwarmUI.Accounts;
-using SwarmUI.Utils;
-using SwarmUI.WebAPI;
-
-namespace Mrleo1nid.SwarmAssistent;
-
-/// <summary>QLoRA training job runner with VRAM lock and progress streaming.</summary>
-public partial class SwarmAssistentExtension
-{
-    static readonly TrainingJobManager TrainingJobManager = new();
-
-    public async Task<JObject> AssistentStartTrainJob(Session session, JObject raw)
-    {
-        if (raw is null)
-        {
-            return new JObject { ["error"] = "body required" };
-        }
-        if (TrainingJobManager.IsRunning)
-        {
-            return new JObject { ["error"] = "Тренировка уже идёт" };
-        }
-        string hfBase = raw["base_model"]?.ToString()?.Trim();
-        string outputName = raw["output_name"]?.ToString()?.Trim();
-        if (string.IsNullOrWhiteSpace(hfBase) || string.IsNullOrWhiteSpace(outputName))
-        {
-            return new JObject { ["error"] = "base_model and output_name required" };
-        }
-        string hfDataset = null;
-        JObject hfCheck = null;
-        JObject hfMapping = raw["hf_mapping"] as JObject;
-        if (!string.IsNullOrWhiteSpace(raw["hf_dataset"]?.ToString()))
-        {
-            hfDataset = NormalizeHfDatasetId(raw["hf_dataset"]?.ToString());
-            if (hfDataset is null)
-            {
-                return new JObject { ["error"] = "invalid hf_dataset id" };
-            }
-            hfCheck = await CheckHfDatasetInternal(session, hfDataset, useCache: true);
-            if (hfCheck["gate"]?.ToString() == "rejected")
-            {
-                return new JObject { ["error"] = hfCheck["reason"]?.ToString() ?? "hf dataset rejected" };
-            }
-            hfMapping = ResolveHfMapping(hfCheck, hfMapping);
-            if (MappingRequired(hfCheck, hfMapping))
-            {
-                return new JObject { ["error"] = "Нужен маппинг колонок для HF набора", ["check"] = hfCheck };
-            }
-        }
-        JObject runner = Config.LoadTrainingRunner();
-        string kind = runner["kind"]?.ToString()?.Trim();
-        if (string.IsNullOrWhiteSpace(kind))
-        {
-            kind = "builtin";
-        }
-        string baseUrl = NormalizeBaseUrl(raw["base_url"]?.ToString());
-        string chatModel = raw["chat_model"]?.ToString()?.Trim();
-        if (!string.IsNullOrWhiteSpace(chatModel))
-        {
-            await AssistentParkLlm(session, baseUrl, chatModel);
-        }
-        string datasetPath = null;
-        int exportCount = 0;
-        if (string.IsNullOrWhiteSpace(hfDataset))
-        {
-            JObject export = await AssistentExportDataset(session, "approved", "jsonl");
-            datasetPath = export["path"]?.ToString();
-            exportCount = export["count"]?.Value<int?>() ?? 0;
-            if (string.IsNullOrWhiteSpace(datasetPath) || !File.Exists(datasetPath) || exportCount <= 0)
-            {
-                return new JObject { ["error"] = "Нет одобренных примеров для тренировки (или укажи hf_dataset)" };
-            }
-        }
-        else
-        {
-            JObject export = await AssistentExportDataset(session, "approved", "jsonl");
-            exportCount = export["count"]?.Value<int?>() ?? 0;
-            if (exportCount > 0 && File.Exists(export["path"]?.ToString() ?? ""))
-            {
-                datasetPath = export["path"]?.ToString();
-            }
-        }
-        long now = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
-        string jobId = $"tj_{now}";
-        string jobDir = Path.Combine(TrainingRoot(), "jobs", jobId);
-        Directory.CreateDirectory(jobDir);
-        string configPath = Path.Combine(jobDir, "config.json");
-        string logPath = Path.Combine(jobDir, "log.txt");
-        string adapterDir = Path.Combine(TrainingRoot(), "adapters", SanitizeAdapterName(outputName));
-        Directory.CreateDirectory(adapterDir);
-        JObject jobConfig = new()
-        {
-            ["base_model"] = hfBase,
-            ["output_name"] = outputName,
-            ["ollama_base"] = raw["ollama_base"]?.ToString()?.Trim(),
-            ["gguf_base_path"] = raw["gguf_base_path"]?.ToString()?.Trim() ?? runner["gguf_base_path"]?.ToString()?.Trim(),
-            ["dataset_path"] = datasetPath,
-            ["hf_dataset"] = hfDataset,
-            ["hf_mapping"] = hfMapping,
-            ["hf_schema"] = hfCheck?["schema"],
-            ["max_samples"] = raw["max_samples"] ?? 0,
-            ["rank"] = raw["rank"] ?? 16,
-            ["alpha"] = raw["alpha"] ?? 32,
-            ["lr"] = raw["lr"] ?? 0.0002,
-            ["epochs"] = raw["epochs"] ?? 3,
-            ["seq_len"] = raw["seq_len"] ?? 2048,
-            ["four_bit"] = raw["four_bit"] ?? true,
-            ["batch_size"] = raw["batch_size"] ?? 1,
-            ["gradient_accumulation_steps"] = raw["gradient_accumulation_steps"] ?? 4,
-            ["adapter_dir"] = adapterDir,
-            ["local_export_count"] = exportCount,
-        };
-        await File.WriteAllTextAsync(configPath, jobConfig.ToString(Newtonsoft.Json.Formatting.Indented), Encoding.UTF8);
-        Memory.SaveTrainJob(new JObject
-        {
-            ["id"] = jobId,
-            ["kind"] = "qlora",
-            ["status"] = "running",
-            ["config"] = jobConfig,
-            ["base_model"] = hfBase,
-            ["output_name"] = outputName,
-            ["log_path"] = logPath,
-            ["created_at"] = now,
-        });
-        string cmdLine = BuildRunnerCommand(runner, configPath, logPath, jobDir);
-        bool started = TrainingJobManager.Start(this, session, jobId, cmdLine, logPath, baseUrl, chatModel, GetHfToken(session));
-        if (!started)
-        {
-            Memory.SaveTrainJob(new JObject { ["id"] = jobId, ["status"] = "failed", ["progress"] = new JObject { ["error"] = "process start failed" } });
-            return new JObject { ["error"] = "Не удалось запустить процесс тренировки" };
-        }
-        return new JObject { ["success"] = true, ["job_id"] = jobId, ["log_path"] = logPath };
-    }
-
-    static string SanitizeAdapterName(string name)
-    {
-        if (string.IsNullOrWhiteSpace(name))
-        {
-            return "adapter";
-        }
-        char[] bad = Path.GetInvalidFileNameChars();
-        StringBuilder sb = new();
-        foreach (char c in name)
-        {
-            sb.Append(Array.IndexOf(bad, c) >= 0 ? '_' : c);
-        }
-        return sb.ToString().Trim();
-    }
-
-    string BuildRunnerCommand(JObject runner, string configPath, string logPath, string workDir)
-    {
-        string python = runner["python"]?.ToString()?.Trim();
-        if (string.IsNullOrWhiteSpace(python))
-        {
-            python = "python";
-        }
-        string kind = runner["kind"]?.ToString()?.Trim() ?? "builtin";
-        string custom = runner["cmd"]?.ToString()?.Trim();
-        string scriptPath = Path.Combine(FilePath, "scripts", "train_qlora.py");
-        if (string.Equals(kind, "custom", StringComparison.OrdinalIgnoreCase) && !string.IsNullOrWhiteSpace(custom))
-        {
-            return custom
-                .Replace("{python}", python, StringComparison.OrdinalIgnoreCase)
-                .Replace("{config}", configPath, StringComparison.OrdinalIgnoreCase)
-                .Replace("{log}", logPath, StringComparison.OrdinalIgnoreCase)
-                .Replace("{workdir}", workDir, StringComparison.OrdinalIgnoreCase);
-        }
-        return $"\"{python}\" \"{scriptPath}\" --config \"{configPath}\" --log \"{logPath}\"";
-    }
-
-    public async Task<JObject> AssistentCancelTrainJob(Session session, string id = null)
-    {
-        await Task.CompletedTask;
-        TrainingJobManager.Cancel();
-        string jobId = id ?? TrainingJobManager.CurrentJobId;
-        if (!string.IsNullOrWhiteSpace(jobId))
-        {
-            Memory.SaveTrainJob(new JObject
-            {
-                ["id"] = jobId,
-                ["status"] = "cancelled",
-                ["finished_at"] = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds(),
-            });
-        }
-        return new JObject { ["success"] = true, ["cancelled"] = true };
-    }
-
-    public async Task<JObject> AssistentTrainWS(Session session, WebSocket ws, JObject raw)
-    {
-        await Task.CompletedTask;
-        try
-        {
-            while (TrainingJobManager.IsRunning && ws.State == System.Net.WebSockets.WebSocketState.Open)
-            {
-                JObject progress = TrainingJobManager.GetProgress();
-                string msg = progress.ToString(Newtonsoft.Json.Formatting.None);
-                await ws.SendAsync(Encoding.UTF8.GetBytes(msg), System.Net.WebSockets.WebSocketMessageType.Text, true, CancellationToken.None);
-                await Task.Delay(800);
-            }
-            JObject final = TrainingJobManager.GetProgress();
-            final["done"] = true;
-            await ws.SendAsync(Encoding.UTF8.GetBytes(final.ToString(Newtonsoft.Json.Formatting.None)), System.Net.WebSockets.WebSocketMessageType.Text, true, CancellationToken.None);
-        }
-        catch (Exception ex)
-        {
-            Logs.Debug($"AssistentTrainWS: {ex.Message}");
-        }
-        return new JObject { ["success"] = true };
-    }
-
-    internal async Task FinishTrainJobAsync(
-        string jobId,
-        bool success,
-        string logPath,
-        Session session,
-        string baseUrl,
-        string chatModel,
-        JObject jobConfig,
-        JObject runner)
-    {
-        long now = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
-        string adapterDir = jobConfig?["adapter_dir"]?.ToString() ?? "";
-        string outputName = jobConfig?["output_name"]?.ToString() ?? "";
-        JObject progress = TrainingJobManager.GetProgress();
-        string finalStatus = success ? "completed" : "failed";
-        if (success && Directory.Exists(adapterDir))
-        {
-            JObject reg = await RegisterAdapterPipeline(session, baseUrl, outputName, adapterDir, jobConfig, runner);
-            progress["ollama"] = reg;
-            if (reg["success"]?.Value<bool?>() != true && reg["skipped"]?.Value<bool?>() != true)
-            {
-                finalStatus = "completed_with_warnings";
-            }
-        }
-        progress["status"] = finalStatus;
-        Memory.SaveTrainJob(new JObject
-        {
-            ["id"] = jobId,
-            ["status"] = finalStatus,
-            ["finished_at"] = now,
-            ["progress"] = progress,
-        });
-        if (!string.IsNullOrWhiteSpace(chatModel))
-        {
-            await AssistentWarmLlm(session, baseUrl, chatModel);
-        }
-        TrainingJobManager.ClearRunning();
-    }
-
-    async Task<JObject> RegisterAdapterPipeline(Session session, string baseUrl, string outputName, string adapterDir, JObject jobConfig, JObject runner)
-    {
-        string safetensors = Directory.GetFiles(adapterDir, "adapter_model.safetensors").FirstOrDefault();
-        if (string.IsNullOrWhiteSpace(safetensors))
-        {
-            return new JObject { ["success"] = false, ["error"] = "adapter_model.safetensors not found" };
-        }
-        string ggufPath = Directory.GetFiles(adapterDir, "*.gguf").FirstOrDefault();
-        string ggufScript = runner?["gguf_script"]?.ToString()?.Trim();
-        string ggufBase = jobConfig?["gguf_base_path"]?.ToString()?.Trim() ?? runner?["gguf_base_path"]?.ToString()?.Trim();
-        string python = runner?["python"]?.ToString()?.Trim();
-        if (string.IsNullOrWhiteSpace(python))
-        {
-            python = "python";
-        }
-        if (string.IsNullOrWhiteSpace(ggufPath) && !string.IsNullOrWhiteSpace(ggufScript) && File.Exists(ggufScript))
-        {
-            if (string.IsNullOrWhiteSpace(ggufBase) || !File.Exists(ggufBase))
-            {
-                return new JObject
-                {
-                    ["success"] = false,
-                    ["skipped"] = true,
-                    ["error"] = "gguf_base_path не задан или файл не найден — адаптер сохранён как safetensors",
-                    ["adapter_dir"] = adapterDir,
-                };
-            }
-            ggufPath = Path.Combine(adapterDir, "adapter.gguf");
-            string ggufCmd = runner?["gguf_cmd"]?.ToString()?.Trim();
-            if (string.IsNullOrWhiteSpace(ggufCmd))
-            {
-                ggufCmd = "\"{python}\" \"{script}\" \"{base}\" \"{lora}\" \"{out}\"";
-            }
-            string cmd = ggufCmd
-                .Replace("{python}", python, StringComparison.OrdinalIgnoreCase)
-                .Replace("{script}", ggufScript, StringComparison.OrdinalIgnoreCase)
-                .Replace("{base}", ggufBase, StringComparison.OrdinalIgnoreCase)
-                .Replace("{lora}", adapterDir, StringComparison.OrdinalIgnoreCase)
-                .Replace("{out}", ggufPath, StringComparison.OrdinalIgnoreCase);
-            int code = await RunShellCommandAsync(cmd, adapterDir);
-            if (code != 0 || !File.Exists(ggufPath))
-            {
-                return new JObject
-                {
-                    ["success"] = false,
-                    ["error"] = $"GGUF convert failed exit={code}",
-                    ["adapter_dir"] = adapterDir,
-                };
-            }
-        }
-        if (string.IsNullOrWhiteSpace(ggufPath) || !File.Exists(ggufPath))
-        {
-            return new JObject
-            {
-                ["success"] = false,
-                ["skipped"] = true,
-                ["note"] = "Настрой convert_lora_to_gguf.py и gguf_base_path для регистрации в Ollama",
-                ["adapter_dir"] = adapterDir,
-            };
-        }
-        string ollamaBase = jobConfig?["ollama_base"]?.ToString()?.Trim();
-        if (string.IsNullOrWhiteSpace(ollamaBase))
-        {
-            return new JObject
-            {
-                ["success"] = false,
-                ["skipped"] = true,
-                ["error"] = "ollama_base не задан — укажи базовую Ollama-модель на форме QLoRA",
-                ["adapter_dir"] = adapterDir,
-                ["gguf"] = ggufPath,
-            };
-        }
-        return await RegisterAdapterInOllama(baseUrl, outputName, ollamaBase, ggufPath);
-    }
-
-    static async Task<int> RunShellCommandAsync(string commandLine, string workDir)
-    {
-        try
-        {
-            ProcessStartInfo psi = new()
-            {
-                FileName = "cmd.exe",
-                Arguments = $"/c {commandLine}",
-                UseShellExecute = false,
-                RedirectStandardOutput = true,
-                RedirectStandardError = true,
-                CreateNoWindow = true,
-                WorkingDirectory = workDir ?? Environment.CurrentDirectory,
-            };
-            using Process proc = Process.Start(psi);
-            if (proc is null)
-            {
-                return -1;
-            }
-            await proc.WaitForExitAsync();
-            return proc.ExitCode;
-        }
-        catch (Exception ex)
-        {
-            Logs.Debug($"RunShellCommand: {ex.Message}");
-            return -1;
-        }
-    }
-
-    async Task<JObject> RegisterAdapterInOllama(string baseUrl, string outputName, string ollamaBase, string adapterGguf)
-    {
-        StringBuilder mf = new();
-        mf.AppendLine($"FROM {ollamaBase}");
-        mf.AppendLine($"ADAPTER {adapterGguf.Replace("\\", "/")}");
-        JObject payload = new()
-        {
-            ["name"] = outputName,
-            ["modelfile"] = mf.ToString(),
-            ["stream"] = false,
-        };
-        using StringContent content = new(payload.ToString(Newtonsoft.Json.Formatting.None), Encoding.UTF8, "application/json");
-        using HttpResponseMessage resp = await HttpClient.PostAsync($"{NormalizeBaseUrl(baseUrl)}/api/create", content);
-        string body = await resp.Content.ReadAsStringAsync();
-        if (!resp.IsSuccessStatusCode)
-        {
-            return new JObject
-            {
-                ["success"] = false,
-                ["error"] = $"ollama create HTTP {(int)resp.StatusCode}: {Clip(body, 400)}",
-                ["modelfile"] = mf.ToString(),
-            };
-        }
-        return new JObject
-        {
-            ["success"] = true,
-            ["name"] = outputName,
-            ["ollama_base"] = ollamaBase,
-            ["adapter"] = adapterGguf,
-            ["response"] = body,
-        };
-    }
-}
-
-sealed class TrainingJobManager
-{
-    static readonly Regex LossRe = new(@"loss[:\s]+([0-9.]+)", RegexOptions.IgnoreCase | RegexOptions.Compiled);
-    static readonly Regex StepRe = new(@"step\s+(\d+)\s*/\s*(\d+)", RegexOptions.IgnoreCase | RegexOptions.Compiled);
-
-    Process _process;
-    readonly object _lock = new();
-    JObject _progress = new() { ["status"] = "idle" };
-    string _logPath;
-    SwarmAssistentExtension _ext;
-    Session _session;
-    string _jobId;
-    string _baseUrl;
-    string _chatModel;
-    long _lastProgressSaveMs;
-    int _lastSavedStep = -1;
-
-    public bool IsRunning { get; private set; }
-    public string CurrentJobId => _jobId;
-
-    public bool Start(SwarmAssistentExtension ext, Session session, string jobId, string commandLine, string logPath, string baseUrl, string chatModel, string hfToken)
-    {
-        lock (_lock)
-        {
-            if (IsRunning)
-            {
-                return false;
-            }
-            _ext = ext;
-            _session = session;
-            _jobId = jobId;
-            _logPath = logPath;
-            _baseUrl = baseUrl;
-            _chatModel = chatModel;
-            _lastProgressSaveMs = 0;
-            _lastSavedStep = -1;
-            _progress = new JObject { ["status"] = "running", ["step"] = 0, ["loss"] = null, ["log"] = "" };
-            try
-            {
-                ProcessStartInfo psi = new()
-                {
-                    FileName = "cmd.exe",
-                    Arguments = $"/c {commandLine}",
-                    UseShellExecute = false,
-                    RedirectStandardOutput = true,
-                    RedirectStandardError = true,
-                    CreateNoWindow = true,
-                    WorkingDirectory = Path.GetDirectoryName(logPath) ?? Environment.CurrentDirectory,
-                };
-                if (!string.IsNullOrWhiteSpace(hfToken))
-                {
-                    psi.Environment["HF_TOKEN"] = hfToken;
-                    psi.Environment["HUGGING_FACE_HUB_TOKEN"] = hfToken;
-                }
-                _process = new Process { StartInfo = psi, EnableRaisingEvents = true };
-                _process.OutputDataReceived += (_, e) => AppendLog(e.Data);
-                _process.ErrorDataReceived += (_, e) => AppendLog(e.Data);
-                _process.Exited += async (_, _) => await OnExited();
-                _process.Start();
-                _process.BeginOutputReadLine();
-                _process.BeginErrorReadLine();
-                IsRunning = true;
-                return true;
-            }
-            catch (Exception ex)
-            {
-                _progress["error"] = ex.Message;
-                IsRunning = false;
-                return false;
-            }
-        }
-    }
-
-    void AppendLog(string line)
-    {
-        if (string.IsNullOrWhiteSpace(line))
-        {
-            return;
-        }
-        lock (_lock)
-        {
-            try
-            {
-                File.AppendAllText(_logPath, line + Environment.NewLine);
-            }
-            catch
-            {
-                // ignore
-            }
-            string prev = _progress["log"]?.ToString() ?? "";
-            string combined = prev + line + "\n";
-            if (combined.Length > 12000)
-            {
-                combined = combined[^12000..];
-            }
-            _progress["log"] = combined;
-            Match lossM = LossRe.Match(line);
-            if (lossM.Success)
-            {
-                _progress["loss"] = lossM.Groups[1].Value;
-            }
-            Match stepM = StepRe.Match(line);
-            if (stepM.Success)
-            {
-                int step = int.Parse(stepM.Groups[1].Value);
-                int total = int.Parse(stepM.Groups[2].Value);
-                _progress["step"] = step;
-                _progress["total_steps"] = total;
-                _progress["percent"] = total > 0 ? (int)(100.0 * step / total) : 0;
-            }
-            MaybeSaveProgress(stepM.Success ? int.Parse(stepM.Groups[1].Value) : -1);
-        }
-    }
-
-    void MaybeSaveProgress(int step)
-    {
-        long now = DateTimeOffset.UtcNow.ToUnixTimeMilliseconds();
-        bool stepChanged = step >= 0 && step != _lastSavedStep;
-        if (!stepChanged && now - _lastProgressSaveMs < 2500)
-        {
-            return;
-        }
-        _lastProgressSaveMs = now;
-        if (step >= 0)
-        {
-            _lastSavedStep = step;
-        }
-        try
-        {
-            _ext?.Memory?.SaveTrainJob(new JObject
-            {
-                ["id"] = _jobId,
-                ["status"] = "running",
-                ["progress"] = _progress,
-            });
-        }
-        catch
-        {
-            // ignore
-        }
-    }
-
-    async Task OnExited()
-    {
-        bool ok = false;
-        JObject jobConfig = new();
-        lock (_lock)
-        {
-            ok = _process?.ExitCode == 0;
-            IsRunning = false;
-            _progress["status"] = ok ? "completed" : "failed";
-            _progress["exit_code"] = _process?.ExitCode;
-        }
-        if (_ext != null)
-        {
-            JObject job = _ext.Memory.GetTrainJob(_jobId);
-            try
-            {
-                string cfgRaw = job?["config_json"]?.ToString();
-                if (!string.IsNullOrWhiteSpace(cfgRaw))
-                {
-                    jobConfig = JObject.Parse(cfgRaw);
-                }
-            }
-            catch
-            {
-                // ignore
-            }
-            JObject runner = _ext.Config.LoadTrainingRunner();
-            await _ext.FinishTrainJobAsync(_jobId, ok, _logPath, _session, _baseUrl, _chatModel, jobConfig, runner);
-        }
-    }
-
-    public void Cancel()
-    {
-        lock (_lock)
-        {
-            try
-            {
-                if (_process != null && !_process.HasExited)
-                {
-                    _process.Kill(entireProcessTree: true);
-                }
-            }
-            catch
-            {
-                // ignore
-            }
-            IsRunning = false;
-            _progress["status"] = "cancelled";
-        }
-    }
-
-    public JObject GetProgress()
-    {
-        lock (_lock)
-        {
-            return (JObject)_progress.DeepClone();
-        }
-    }
-
-    public void ClearRunning()
-    {
-        lock (_lock)
-        {
-            IsRunning = false;
-        }
-    }
-}

Config/_base/patch-keys.json

@@ -8,6 +8,6 @@
     "snapshot_generate", "select_slot", "aspect", "images", "batch", "vary", "lock_seed",
     "creativity", "intensity", "complexity", "movement",
     "clear_prompt_images", "slot_to_prompt_image", "pack", "persona", "controls",
-    "inventory_query", "variants"
+    "inventory_query", "knowledge_query", "example_query", "knowledge_rating", "example_rating", "variants"
   ]
 }

Config/_base/skills/knowledge.json

@@ -0,0 +1,6 @@
+{
+  "id": "knowledge",
+  "title": "Books + knowledge search",
+  "default": false,
+  "prompt_file": "knowledge.md"
+}

Config/_base/skills/knowledge.md

@@ -0,0 +1,22 @@
+# Knowledge skill
+
+Attached **books** are read-only FTS corpora (Civitai prompts, RU fic style, …). They are **not** mutable memory.
+
+## When to search
+
+- User asks for reference prompts, scene wording, style/tone, or «как на Civitai».
+- You need concrete tag/prompt patterns before generating.
+
+## How to search (server hop)
+
+```json
+{ "ask": ["knowledge"], "knowledge_query": "redhead stockings cinematic window light" }
+```
+
+Optional: `knowledge_rating` (`pg`, `pg13`, …). Legacy `ask:["examples"]` + `example_query` still works for Civitai-only.
+
+## Rules
+
+- **Remix** — never paste long verbatim from books.
+- Pure chat / opinions: **prose only**, no JSON.
+- Do **not** emit `generate:true` on knowledge Q&A turns.

Config/_base/skills/memory.md

@@ -6,7 +6,7 @@ You have five memory tools:
 2. **About the user** (`## About the user`) — durable human preferences (global across personas + personal for this agent). Tunable weight in settings. Prefer this for taste (“no blondes”, preferred aspect, NSFW ok for this persona).
 3. **Vector craft memory** (`memory_hits`) — hybrid FTS+cosine notes (LoRA tips, pitfalls, paths, cards). Shared + this persona; personal overwrites shared on the same `kind`+`key`.
 4. **Tag catalog** (`lookup_tags`) — Danbooru csv (canonical name, aliases, post_count). **Not** RAG. Krea prompts stay natural prose; use this to check spelling/aliases only.
-5. **Civitai examples** (`ask: examples` / `lookup_examples`) — popular Krea 2 prompts indexed with FTS (no embeddings). Use when you want a **reference** for how others phrased a scene — remix, do not copy 1:1.
+5. **Civitai / knowledge books** (`ask: knowledge` / `ask: examples`) — FTS over attached books (gpu-rent seeded) and legacy Civitai examples. Remix, do not copy 1:1.
 
 ## Priority
 

Config/_base/training-qlora.json

@@ -1,49 +0,0 @@
-{
-  "hf_models": [
-    {
-      "id": "qwen2.5-7b-instruct",
-      "title": "Qwen2.5 7B Instruct",
-      "hf_id": "Qwen/Qwen2.5-7B-Instruct",
-      "ollama_hint": "qwen2.5:7b-instruct",
-      "default_output": "assistent-qwen25-7b:v1",
-      "rank": 16,
-      "seq_len": 2048
-    },
-    {
-      "id": "qwen2.5-3b-instruct",
-      "title": "Qwen2.5 3B Instruct",
-      "hf_id": "Qwen/Qwen2.5-3B-Instruct",
-      "ollama_hint": "qwen2.5:3b-instruct",
-      "default_output": "assistent-qwen25-3b:v1",
-      "rank": 16,
-      "seq_len": 2048
-    },
-    {
-      "id": "llama-3.2-3b-instruct",
-      "title": "Llama 3.2 3B Instruct",
-      "hf_id": "meta-llama/Llama-3.2-3B-Instruct",
-      "ollama_hint": "llama3.2:3b-instruct",
-      "default_output": "assistent-llama32-3b:v1",
-      "rank": 16,
-      "seq_len": 2048
-    },
-    {
-      "id": "llama-3.1-8b-instruct",
-      "title": "Llama 3.1 8B Instruct",
-      "hf_id": "meta-llama/Llama-3.1-8B-Instruct",
-      "ollama_hint": "llama3.1:8b-instruct",
-      "default_output": "assistent-llama31-8b:v1",
-      "rank": 16,
-      "seq_len": 2048
-    },
-    {
-      "id": "phi-3-mini-instruct",
-      "title": "Phi-3 Mini 4K Instruct",
-      "hf_id": "microsoft/Phi-3-mini-4k-instruct",
-      "ollama_hint": "phi3:mini",
-      "default_output": "assistent-phi3-mini:v1",
-      "rank": 16,
-      "seq_len": 2048
-    }
-  ]
-}

SwarmAssistentExtension.cs

@@ -33,8 +33,8 @@ public partial class SwarmAssistentExtension : Extension
         ExtensionAuthor = "mrleo1nid";
         Description = "Collaborative Krea 2 assistant: Ollama chat, persona presets, vector memory, model cards, Generate loop.";
         License = "MIT";
-        Version = "0.15.17";
+        Version = "0.16.0";
-        Tags = ["tabs", "ui", "llm", "ollama", "krea", "inpaint", "memory", "training", "heard", "qlora"];
+        Tags = ["tabs", "ui", "llm", "ollama", "krea", "inpaint", "memory", "knowledge", "heard", "books"];
     }
 
     public override void OnInit()
@@ -64,6 +64,10 @@ public partial class SwarmAssistentExtension : Extension
         API.RegisterAPICall(AssistentGetMemory, false, PermUse);
         API.RegisterAPICall(AssistentLookupTags, false, PermUse);
         API.RegisterAPICall(AssistentLookupExamples, false, PermUse);
+        API.RegisterAPICall(AssistentListKnowledgeCatalog, false, PermUse);
+        API.RegisterAPICall(AssistentSearchKnowledge, false, PermUse);
+        API.RegisterAPICall(AssistentGetKnowledgeAttach, false, PermUse);
+        API.RegisterAPICall(AssistentSaveKnowledgeAttach, true, PermUse);
         API.RegisterAPICall(AssistentSaveControls, true, PermUse);
         API.RegisterAPICall(AssistentGetPersonaShelves, false, PermUse);
         API.RegisterAPICall(AssistentClonePersona, true, PermUse);
@@ -77,29 +81,7 @@ public partial class SwarmAssistentExtension : Extension
         API.RegisterAPICall(AssistentForgetUserPref, true, PermUse);
         API.RegisterAPICall(AssistentClearUserPrefs, true, PermUse);
         API.RegisterAPICall(AssistentClearMemory, true, PermUse);
-        API.RegisterAPICall(AssistentListTrainSamples, false, PermUse);
+        Logs.Init("Swarm Assistent extension loaded (0.16.0 knowledge books hub)");
-        API.RegisterAPICall(AssistentUpsertTrainSample, true, PermUse);
-        API.RegisterAPICall(AssistentDeleteTrainSample, true, PermUse);
-        API.RegisterAPICall(AssistentBuildDatasetFromChats, false, PermUse);
-        API.RegisterAPICall(AssistentImportDataset, true, PermUse);
-        API.RegisterAPICall(AssistentExportDataset, false, PermUse);
-        API.RegisterAPICall(AssistentCreateOllamaModel, true, PermUse);
-        API.RegisterAPICall(AssistentSearchHfDatasets, false, PermUse);
-        API.RegisterAPICall(AssistentCheckHfDataset, false, PermUse);
-        API.RegisterAPICall(AssistentPreviewHfDataset, false, PermUse);
-        API.RegisterAPICall(AssistentImportHfDataset, true, PermUse);
-        API.RegisterAPICall(AssistentStartTrainJob, true, PermUse);
-        API.RegisterAPICall(AssistentCancelTrainJob, true, PermUse);
-        API.RegisterAPICall(AssistentGetTrainJob, false, PermUse);
-        API.RegisterAPICall(AssistentTrainWS, true, PermUse);
-        API.RegisterAPICall(AssistentSaveRunnerSettings, true, PermUse);
-        API.RegisterAPICall(AssistentGetRunnerSettings, false, PermUse);
-        API.RegisterAPICall(AssistentGetDatasetAgentSettings, false, PermUse);
-        API.RegisterAPICall(AssistentSaveDatasetAgentSettings, true, PermUse);
-        API.RegisterAPICall(AssistentLinkTrainSampleToAgent, true, PermUse);
-        API.RegisterAPICall(AssistentUnlinkTrainSampleFromAgent, true, PermUse);
-        API.RegisterAPICall(AssistentSyncDatasetToAgent, true, PermUse);
-        Logs.Init("Swarm Assistent extension loaded (0.15.0 persona packs / dreamer)");
     }
 
     int CfgInt(string key, int fallback)

Tabs/Text2Image/Assistent.html

@@ -10,13 +10,8 @@
         </div>
         <div class="sa-app-tabs" role="tablist" aria-label="Разделы Assistent">
             <button type="button" class="sa-app-tab sa-app-tab-active" data-view="chat" id="sa_tab_chat" role="tab" aria-selected="true">Чат</button>
-            <button type="button" class="sa-app-tab" data-view="train" id="sa_tab_train" role="tab" aria-selected="false">Обучение</button>
             <button type="button" class="sa-app-tab" data-view="settings" id="sa_tab_settings" role="tab" aria-selected="false">Настройки</button>
         </div>
-        <div class="sa-train-banner" id="sa_train_banner" hidden role="status">
-            <span class="sa-spinner" aria-hidden="true"></span>
-            <span id="sa_train_banner_text">Идёт тренировка…</span>
-        </div>
     </header>
     <div class="sa-views" id="sa_views">
         <div class="sa-view" id="sa_view_chat">
@@ -161,140 +156,6 @@
             </div>
         </div>
 
-        <div class="sa-view" id="sa_view_train" hidden>
-            <div class="sa-training" id="sa_training">
-                <div class="sa-training-tabs" role="tablist" aria-label="Разделы обучения">
-                    <button type="button" class="sa-ttab sa-ttab-active" data-ttab="dataset" role="tab" aria-selected="true">Датасет</button>
-                    <button type="button" class="sa-ttab" data-ttab="train" role="tab" aria-selected="false">Тренировка</button>
-                    <button type="button" class="sa-ttab" data-ttab="models" role="tab" aria-selected="false">Модели</button>
-                </div>
-                <span class="sa-status sa-train-global-status" id="sa_train_status" role="status"></span>
-                <div class="sa-training-panes">
-                    <div class="sa-tpane" data-tpane="dataset">
-                        <div class="sa-train-toolbar">
-                            <span class="sa-train-stats" id="sa_train_stats">Одобрено: —</span>
-                            <select id="sa_train_filter_status" class="sa-select" title="Статус">
-                                <option value="all">Все статусы</option>
-                                <option value="approved">Одобренные</option>
-                                <option value="draft">Черновики</option>
-                                <option value="rejected">Отклонённые</option>
-                            </select>
-                            <select id="sa_train_filter_persona" class="sa-select" title="Личность"><option value="all">Все личности</option></select>
-                            <button type="button" class="basic-button" id="sa_btn_train_from_chats">Из чатов</button>
-                            <button type="button" class="basic-button" id="sa_btn_train_import_file">Импорт файла…</button>
-                            <input type="file" id="sa_train_import_file" accept=".jsonl,.json,.csv,text/csv,application/json" hidden />
-                            <button type="button" class="basic-button" id="sa_btn_train_export">Экспорт JSONL</button>
-                        </div>
-                        <div class="sa-agent-heard-panel" id="sa_agent_heard_panel">
-                            <div class="sa-agent-heard-head">
-                                <strong>Услышанное → агент</strong>
-                                <span class="sa-agent-heard-stats" id="sa_agent_heard_stats">Подключено: —</span>
-                            </div>
-                            <p class="sa-agent-heard-hint">Одобренные примеры сразу попадают в RAG агента (без QLoRA). Агент видит их как <code>heard_examples</code> и может запросить через <code>heard_search</code>.</p>
-                            <div class="sa-agent-heard-controls">
-                                <label class="sa-check"><input type="checkbox" id="sa_agent_heard_enabled" checked /> Включено для чата</label>
-                                <label class="sa-check"><input type="checkbox" id="sa_agent_auto_link" checked /> Авто-подключение при одобрении</label>
-                                <label>Примеров в контексте <input type="number" id="sa_agent_heard_quota" min="0" max="8" value="3" /></label>
-                                <button type="button" class="basic-button sa-primary" id="sa_btn_agent_sync">Подключить все одобренные</button>
-                            </div>
-                        </div>
-                        <div class="sa-hf-panel">
-                            <div class="sa-hf-head"><strong>Hugging Face</strong></div>
-                            <div class="sa-hf-search-row">
-                                <input type="search" id="sa_hf_search" class="sa-hf-search" placeholder="Поиск датасетов…" autocomplete="off" />
-                                <button type="button" class="basic-button" id="sa_btn_hf_search">Найти</button>
-                                <label class="sa-check sa-hf-show-all"><input type="checkbox" id="sa_hf_show_all" /> Показать все</label>
-                            </div>
-                            <div class="sa-hf-link-row">
-                                <input type="text" id="sa_hf_link" class="sa-hf-link" placeholder="owner/name или https://huggingface.co/datasets/…" />
-                                <button type="button" class="basic-button" id="sa_btn_hf_check">Проверить</button>
-                            </div>
-                            <div class="sa-hf-status" id="sa_hf_status" role="status"></div>
-                            <div class="sa-hf-list" id="sa_hf_list"></div>
-                            <div class="sa-hf-preview" id="sa_hf_preview" hidden></div>
-                            <div class="sa-hf-mapping-row" id="sa_hf_mapping_row" hidden>
-                                <span class="sa-settings-hint">Маппинг колонок:</span>
-                                <label>Preset
-                                    <select id="sa_hf_mapping_preset" class="sa-select">
-                                        <option value="">— вручную —</option>
-                                        <option value="fiction_tags_text">Fiction: title/tags → text</option>
-                                    </select>
-                                </label>
-                                <label>User col <select id="sa_hf_user_col" class="sa-select"></select></label>
-                                <label>Assistant col <select id="sa_hf_asst_col" class="sa-select"></select></label>
-                            </div>
-                            <div class="sa-hf-import-row" id="sa_hf_import_row" hidden>
-                                <label>Лимит строк <input type="number" id="sa_hf_import_limit" min="1" max="5000" value="200" /></label>
-                                <label>Соотношение внешних:своих <input type="number" id="sa_hf_mix_ratio" min="0" max="20" step="0.5" value="3" title="Сколько внешних примеров на один свой" /></label>
-                                <button type="button" class="basic-button sa-primary" id="sa_btn_hf_import">Импортировать</button>
-                            </div>
-                        </div>
-                        <div class="sa-train-samples" id="sa_train_samples"></div>
-                    </div>
-                    <div class="sa-tpane" data-tpane="train" hidden>
-                        <div class="sa-train-modes">
-                            <label class="sa-check"><input type="radio" name="sa_train_mode" value="modelfile" checked /> Быстро: Ollama Modelfile</label>
-                            <label class="sa-check"><input type="radio" name="sa_train_mode" value="qlora" /> QLoRA (нужен python-раннер)</label>
-                        </div>
-                        <div class="sa-train-form" id="sa_train_form_modelfile">
-                            <label>Базовая модель (Ollama)
-                                <select id="sa_modelfile_base" class="sa-select"><option value="">—</option></select>
-                            </label>
-                            <label>Имя результата <input type="text" id="sa_modelfile_name" placeholder="assistent-neutral:v1" /></label>
-                            <label>Персона для SYSTEM
-                                <select id="sa_modelfile_persona" class="sa-select"><option value="neutral">neutral</option></select>
-                            </label>
-                            <label>Few-shot примеров <input type="number" id="sa_modelfile_shots" min="0" max="32" value="8" /></label>
-                            <label>SYSTEM (редактируемый) <textarea id="sa_modelfile_system" rows="8" spellcheck="false"></textarea></label>
-                            <div class="sa-settings-row sa-knob-row">
-                                <label>num_ctx <input type="number" id="sa_modelfile_num_ctx" min="2048" max="131072" step="1024" value="16384" /></label>
-                                <label>temperature <input type="number" id="sa_modelfile_temp" min="0" max="2" step="0.05" value="0.7" /></label>
-                            </div>
-                            <button type="button" class="basic-button sa-primary" id="sa_btn_modelfile_create">Создать модель</button>
-                        </div>
-                        <div class="sa-train-form" id="sa_train_form_qlora" hidden>
-                            <p class="sa-settings-hint">Base model — HF id (safetensors). Тренер скачает веса сам (нужен HF_TOKEN в User Settings).</p>
-                            <label>HF base model
-                                <select id="sa_qlora_base" class="sa-select"><option value="">— выберите модель —</option></select>
-                            </label>
-                            <label id="sa_qlora_base_custom_row" hidden>Другая модель (HF id)
-                                <input type="text" id="sa_qlora_base_custom" placeholder="org/model-name" />
-                            </label>
-                            <label>Ollama base (FROM для ADAPTER)
-                                <select id="sa_qlora_ollama_base" class="sa-select"><option value="">—</option></select>
-                            </label>
-                            <label>Имя модели в Ollama <input type="text" id="sa_qlora_name" placeholder="my-lora:v1" /></label>
-                            <div class="sa-settings-row sa-knob-row">
-                                <label>rank <input type="number" id="sa_qlora_rank" min="4" max="128" value="16" /></label>
-                                <label>alpha <input type="number" id="sa_qlora_alpha" min="4" max="256" value="32" /></label>
-                                <label>LR <input type="number" id="sa_qlora_lr" min="0.000001" max="0.01" step="0.00001" value="0.0002" /></label>
-                                <label>epochs <input type="number" id="sa_qlora_epochs" min="1" max="20" value="3" /></label>
-                                <label>seq_len <input type="number" id="sa_qlora_seq" min="512" max="8192" step="256" value="2048" /></label>
-                                <label>max_samples <input type="number" id="sa_qlora_max_samples" min="0" max="50000" value="0" title="0 = все строки" /></label>
-                            </div>
-                            <label class="sa-check"><input type="checkbox" id="sa_qlora_4bit" checked /> 4-bit QLoRA</label>
-                            <label>HF датасет (опционально, без локального датасета) <input type="text" id="sa_qlora_hf_dataset" placeholder="krplt/ru-fictext-nsfw" /></label>
-                            <p class="sa-settings-hint">После обучения: safetensors → GGUF (convert script) → ollama create. Настрой пути в Настройки → Модели.</p>
-                            <button type="button" class="basic-button sa-primary" id="sa_btn_qlora_start">Запустить QLoRA</button>
-                            <button type="button" class="basic-button" id="sa_btn_qlora_cancel" hidden>Отменить</button>
-                        </div>
-                        <div class="sa-train-progress" id="sa_train_progress" hidden>
-                            <div class="sa-train-progress-bar"><div class="sa-train-progress-fill" id="sa_train_progress_fill"></div></div>
-                            <pre class="sa-train-log" id="sa_train_log"></pre>
-                        </div>
-                    </div>
-                    <div class="sa-tpane" data-tpane="models" hidden>
-                        <p class="sa-settings-hint">После QLoRA/Modelfile — итог здесь и в списке Ollama. Выбери модель в шапке Assistent или ⚙ → Модели.</p>
-                        <div class="sa-train-last-job" id="sa_train_last_job" hidden></div>
-                        <div class="sa-train-models-list" id="sa_train_models_list"></div>
-                        <div class="sa-settings-row">
-                            <button type="button" class="basic-button" id="sa_btn_train_models_refresh">Обновить</button>
-                        </div>
-                    </div>
-                </div>
-            </div>
-        </div>
-
         <div class="sa-view" id="sa_view_settings" hidden>
             <div class="sa-settings" id="sa_settings">
                 <div class="sa-settings-tabs" role="tablist" aria-label="Разделы настроек">
@@ -330,24 +191,10 @@
                                 <option value="nomic-embed-text">nomic-embed-text</option>
                             </select>
                         </label>
-                        <div class="sa-skills-label">QLoRA-раннер</div>
-                        <label>Python <input type="text" id="sa_runner_python" placeholder="python или полный путь" /></label>
-                        <label>Тип тренера
-                            <select id="sa_runner_kind" class="sa-select">
-                                <option value="builtin" selected>Встроенный (train_qlora.py)</option>
-                                <option value="custom">Custom command</option>
-                            </select>
-                        </label>
-                        <label>GGUF base model (.gguf) <input type="text" id="sa_runner_gguf_base" placeholder="C:/models/base.gguf" title="Базовая GGUF для convert_lora_to_gguf" /></label>
-                        <label>Рабочая директория <input type="text" id="sa_runner_workdir" placeholder="Assistent/training/runner" /></label>
-                        <label>Custom command <input type="text" id="sa_runner_cmd" placeholder="{python} train.py --config {config}" /></label>
-                        <label>convert_lora_to_gguf.py <input type="text" id="sa_runner_gguf_script" placeholder="C:/llama.cpp/convert_lora_to_gguf.py" /></label>
-                        <label>GGUF cmd template <input type="text" id="sa_runner_gguf_cmd" placeholder='"{python}" "{script}" "{base}" "{lora}" "{out}"' /></label>
                         <div class="sa-settings-row">
                             <button type="button" class="basic-button" id="sa_btn_refresh_models">Обновить модели</button>
                             <button type="button" class="basic-button" id="sa_btn_refresh_inventory">Обновить inventory</button>
                             <button type="button" class="basic-button" id="sa_btn_settings_health">Проверить Ollama</button>
-                            <button type="button" class="basic-button" id="sa_btn_save_runner">Сохранить раннер</button>
                         </div>
                         <div class="sa-settings-health" id="sa_settings_health_line">Ollama · …</div>
                     </div>
@@ -358,6 +205,14 @@
                             <div class="sa-persona-preview" id="sa_persona_preview">
                                 <div class="sa-mem-empty">Выбери личность слева</div>
                             </div>
+                            <div class="sa-knowledge-panel" id="sa_knowledge_panel" hidden>
+                                <div class="sa-mem-head"><span class="sa-skills-label">Знания (books)</span></div>
+                                <p class="sa-settings-hint" id="sa_knowledge_hint">FTS-корпуса для ask:knowledge. Bundled/pack — только просмотр; overlay — редактируемо.</p>
+                                <div class="sa-knowledge-list" id="sa_knowledge_list"></div>
+                                <div class="sa-settings-row">
+                                    <button type="button" class="basic-button sa-primary" id="sa_btn_knowledge_save" hidden>Сохранить attach</button>
+                                </div>
+                            </div>
                         </div>
                         <div class="sa-settings-row">
                             <button type="button" class="basic-button" id="sa_btn_persona_export">Экспорт</button>

src/app.js

@@ -5996,70 +5996,16 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
         scrollMessagesToBottom();
     }
 
-    function mountCurateButtons(msgEl, meta) {
+    function mountCurateButtons() {
-        if (!msgEl || msgEl.querySelector('.sa-msg-curate')) {
+        // Training dataset curation removed in 0.16.
-            return;
-        }
-        const wrap = document.createElement('div');
-        wrap.className = 'sa-msg-curate';
-        const ok = document.createElement('button');
-        ok.type = 'button';
-        ok.className = 'basic-button';
-        ok.title = 'В датасет (одобрить)';
-        ok.textContent = '+ датасет';
-        ok.addEventListener('click', () => curateAssistantMessage(msgEl, 'approved'));
-        const bad = document.createElement('button');
-        bad.type = 'button';
-        bad.className = 'basic-button';
-        bad.title = 'Отклонить для датасета';
-        bad.textContent = 'брак';
-        bad.addEventListener('click', () => curateAssistantMessage(msgEl, 'rejected'));
-        wrap.appendChild(ok);
-        wrap.appendChild(bad);
-        msgEl.appendChild(wrap);
     }
 
-    function curateAssistantMessage(msgEl, status) {
+    function curateAssistantMessage() {
-        const hist = state.history || [];
+        setStatus('Обучение снято — используй books/knowledge');
-        let asstText = msgEl.querySelector('.sa-msg-body')?.textContent?.trim() || msgEl.textContent?.trim() || '';
-        let userText = '';
-        for (let i = hist.length - 1; i >= 0; i--) {
-            if (hist[i]?.role === 'assistant' && (hist[i].content || '').trim() === asstText.trim()) {
-                for (let j = i - 1; j >= 0; j--) {
-                    if (hist[j]?.role === 'user') {
-                        userText = hist[j].content || '';
-                        break;
-                    }
-                }
-                break;
-            }
-        }
-        if (!userText) {
-            for (let i = hist.length - 1; i >= 0; i--) {
-                if (hist[i]?.role === 'user') {
-                    userText = hist[i].content || '';
-                    break;
-                }
-            }
-        }
-        const messages = [
-            { role: 'user', content: userText },
-            { role: 'assistant', content: asstText },
-        ];
-        window.SA?.training?.curateFromChat?.(messages, {
-            chatId: state.activeChatId,
-            persona: $('sa_persona')?.value || 'neutral',
-            pack: $('sa_pack')?.value || defaultPackId(),
-            status,
-        })?.then?.((ok) => {
-            if (ok) {
-                setStatus(status === 'approved' ? 'Пример добавлен в датасет' : 'Пример отмечен как брак');
-            }
-        });
     }
 
     function isTrainingLocked() {
-        return !!state.trainingLock || document.getElementById('swarm_assistent_root')?.classList.contains('sa-root-training-lock');
+        return false;
     }
 
     function wantsAutoVision() {
@@ -6308,7 +6254,7 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
             document.documentElement.style.setProperty('--sa-image-width', paneW);
         }
         if (view === 'cards') { view = 'chat'; }
-        if (view === 'chat' || view === 'settings' || view === 'train') {
+        if (view === 'chat' || view === 'settings') {
             state.view = view;
         }
         const drawer = localStorage.getItem(LS_CHATS_DRAWER);
@@ -6375,7 +6321,7 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
         fill(LS_PERSONA, ui.persona, (v) => { if ($('sa_persona')) { $('sa_persona').value = v; } });
         fill(LS_PANE_WIDTH, ui.pane_width, (v) => document.documentElement.style.setProperty('--sa-image-width', v));
         if (ui.view === 'cards') { ui.view = 'chat'; }
-        if (ui.view === 'chat' || ui.view === 'settings' || ui.view === 'train') {
+        if (ui.view === 'chat' || ui.view === 'settings') {
             fill(LS_VIEW, ui.view, (v) => { state.view = v; });
         }
         if (ui.board_tab === 'refs' || ui.board_tab === 'generate') {
@@ -6457,9 +6403,6 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
             ? { ...state.config.control_values }
             : null;
         state.config = data;
-        if (window.SA?.training?.onConfig) {
-            window.SA.training.onConfig(data);
-        }
         if (window.SA?.applyConfigPatchKeys) {
             window.SA.applyConfigPatchKeys(data);
         }
@@ -7561,10 +7504,14 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
 
     function loadPersonaPreview(id) {
         const box = $('sa_persona_preview');
+        const knowPanel = $('sa_knowledge_panel');
         if (!box || typeof genericRequest !== 'function') {
             return;
         }
         box.innerHTML = '<div class="sa-mem-empty">Загрузка…</div>';
+        if (knowPanel) {
+            knowPanel.hidden = true;
+        }
         genericRequest(
             'AssistentGetPersonaShelves',
             { persona: id },
@@ -7573,6 +7520,7 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
                 const src = data?.source || '';
                 box.textContent = `${id} · ${personaSourceLabel(src)}\n\n${summary || '(пусто)'}`;
                 syncPersonaPanelActions();
+                loadPersonaKnowledge(id);
             },
             0,
             (err) => {
@@ -7581,6 +7529,75 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
         );
     }
 
+    function loadPersonaKnowledge(personaId) {
+        const panel = $('sa_knowledge_panel');
+        const list = $('sa_knowledge_list');
+        const saveBtn = $('sa_btn_knowledge_save');
+        const hint = $('sa_knowledge_hint');
+        if (!panel || !list || typeof genericRequest !== 'function') {
+            return;
+        }
+        list.innerHTML = '<div class="sa-mem-empty">Загрузка книг…</div>';
+        panel.hidden = false;
+        genericRequest(
+            'AssistentListKnowledgeCatalog',
+            { persona: personaId },
+            (data) => {
+                const cat = data?.knowledge || {};
+                const attach = new Set((cat.attach || []).map(String));
+                const books = cat.books || [];
+                const editable = !!data?.editable;
+                if (hint) {
+                    hint.textContent = editable
+                        ? 'Отметь книги для FTS-поиска (ask:knowledge). Сохраняется в overlay knowledge.json.'
+                        : 'Bundled/pack — attach задан по умолчанию или assistent-pack.yaml. Клонируй в overlay для правок.';
+                }
+                if (saveBtn) {
+                    saveBtn.hidden = !editable;
+                }
+                list.innerHTML = '';
+                if (!books.length) {
+                    list.innerHTML = '<div class="sa-mem-empty">Книги не найдены на диске. gpu-rent seed-books + up.</div>';
+                    return;
+                }
+                for (const b of books) {
+                    const row = document.createElement('label');
+                    row.className = 'sa-check sa-knowledge-row';
+                    const cb = document.createElement('input');
+                    cb.type = 'checkbox';
+                    cb.value = b.id;
+                    cb.checked = attach.has(String(b.id));
+                    cb.disabled = !editable;
+                    row.appendChild(cb);
+                    const title = b.title || b.id;
+                    const kind = b.content_kind ? ` · ${b.content_kind}` : '';
+                    const idx = b.indexed ? '' : ' · нет search.jsonl';
+                    row.appendChild(document.createTextNode(` ${title} (${b.id})${kind}${idx}`));
+                    list.appendChild(row);
+                }
+                if (saveBtn && editable) {
+                    saveBtn.onclick = () => {
+                        const picked = [...list.querySelectorAll('input[type=checkbox]:checked')].map((el) => el.value);
+                        genericRequest(
+                            'AssistentSaveKnowledgeAttach',
+                            { persona: personaId, attach: picked },
+                            () => {
+                                setStatus('Knowledge attach сохранён');
+                                loadPersonaKnowledge(personaId);
+                            },
+                            0,
+                            (err) => setStatus(String(err || 'save failed')),
+                        );
+                    };
+                }
+            },
+            0,
+            (err) => {
+                list.innerHTML = `<div class="sa-mem-empty">${escapeHtml(String(err || 'ошибка'))}</div>`;
+            },
+        );
+    }
+
     function exportSelectedPersona() {
         const id = state.settingsPersonaId || $('sa_persona')?.value;
         if (!id || typeof genericRequest !== 'function') {
@@ -7927,23 +7944,17 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
         }
         if (view === 'settings') {
             state.view = 'settings';
-        } else if (view === 'train') {
-            state.view = 'train';
         } else {
             state.view = 'chat';
         }
         const chat = $('sa_view_chat');
         const settings = $('sa_view_settings');
-        const train = $('sa_view_train');
         if (chat) {
             chat.hidden = state.view !== 'chat';
         }
         if (settings) {
             settings.hidden = state.view !== 'settings';
         }
-        if (train) {
-            train.hidden = state.view !== 'train';
-        }
         const tabActive = (id, on) => {
             $(id)?.classList.toggle('sa-subtab-active', on);
             $(id)?.classList.toggle('sa-app-tab-active', on);
@@ -7951,12 +7962,9 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
         };
         tabActive('sa_tab_chat', state.view === 'chat');
         tabActive('sa_tab_settings', state.view === 'settings');
-        tabActive('sa_tab_train', state.view === 'train');
         saveSettings();
         if (state.view === 'settings') {
             setSettingsTab(state.settingsTab || 'behavior');
-        } else if (state.view === 'train') {
-            window.SA?.training?.render?.();
         } else if ((state.llmParked || state.expectColdLoad) && !state.generating) {
             // Back in the chat — bring the model home (Krea may have evicted it).
             warmLlm({ force: true });
@@ -9222,6 +9230,14 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
                         });
                     }
                 }
+                if (meta.knowledge?.hops?.length) {
+                    const hopLabels = meta.knowledge.hops.map((h) => `${h.tool || 'hop'}:${h.count ?? '?'}`).slice(0, 6);
+                    activityDone('knowledge', {
+                        kind: 'ask',
+                        label: 'knowledge hops',
+                        detail: hopLabels.join(' · '),
+                    });
+                }
                 captureActivityTrace();
                 state.history.push({
                     role: 'assistant',
@@ -9339,6 +9355,7 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
                             system_chars: data.system_chars,
                             system_layers: data.system_layers,
                             prompt_eval_count: data.prompt_eval_count ?? data.raw?.prompt_eval_count,
+                            knowledge: data.knowledge,
                         });
                     }
                 },
@@ -9371,6 +9388,7 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
                                 system_chars: data.system_chars,
                                 system_layers: data.system_layers,
                                 prompt_eval_count: data.prompt_eval_count ?? data.raw?.prompt_eval_count,
+                                knowledge: data.knowledge,
                             });
                         },
                         0,
@@ -9398,6 +9416,7 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
                     system_chars: data.system_chars,
                     system_layers: data.system_layers,
                     prompt_eval_count: data.prompt_eval_count ?? data.raw?.prompt_eval_count,
+                    knowledge: data.knowledge,
                 });
             },
             0,
@@ -9600,7 +9619,6 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
         window.__swarmAssistentWired = true;
         loadSettings();
         setView(state.view || 'chat');
-        void window.SA?.training?.resumePolling?.();
         updateGate();
         ensureBoard();
         setBoardTab(state.boardTab || 'generate', { persist: false });
@@ -9699,7 +9717,6 @@ import { DEFAULT_ASPECT_TABLE, applyAspectTableFromObject as mergeAspectTable }
 
         $('sa_tab_chat')?.addEventListener('click', () => setView('chat'));
 
-        $('sa_tab_train')?.addEventListener('click', () => setView('train'));
         $('sa_tab_settings')?.addEventListener('click', () => openSettings(state.settingsTab || 'behavior'));
         $('sa_board_tab_gen')?.addEventListener('click', () => setBoardTab('generate'));
         $('sa_board_tab_refs')?.addEventListener('click', () => setBoardTab('refs'));

src/main.js

@@ -29,6 +29,3 @@ window.SA.applyConfigPatchKeys = function (config) {
 };
 
 import './app.js';
-import { attachTraining } from './training.js';
-
-attachTraining(window.SA);

src/training.js

@@ -1,942 +0,0 @@
-/** Swarm Assistent — training tab (dataset, Modelfile, QLoRA). */
-
-const $ = (id) => document.getElementById(id);
-
-function escapeHtml(s) {
-  return String(s ?? '')
-    .replace(/&/g, '&')
-    .replace(/</g, '&lt;')
-    .replace(/>/g, '&gt;')
-    .replace(/"/g, '&quot;');
-}
-
-const QLORA_HF_CUSTOM = '__custom__';
-
-export function attachTraining(SA) {
-  const state = {
-    ttab: 'dataset',
-    samples: [],
-    hfResults: [],
-    hfSelected: null,
-    hfCheck: null,
-    hfMapping: null,
-    trainWs: null,
-    polling: null,
-    qloraTraining: null,
-    agentSettings: { enabled: true, auto_link_on_approve: true, heard_quota: 3 },
-    agentLinked: 0,
-  };
-
-  function setAgentHeardStats(linked) {
-    const el = $('sa_agent_heard_stats');
-    if (el) {
-      el.textContent = `Подключено: ${linked ?? state.agentLinked ?? '—'}`;
-    }
-  }
-
-  async function loadAgentHeardSettings() {
-    try {
-      const data = await SA.request('AssistentGetDatasetAgentSettings', {});
-      const s = data?.settings || {};
-      state.agentSettings = {
-        enabled: s.enabled !== false,
-        auto_link_on_approve: s.auto_link_on_approve !== false,
-        heard_quota: s.heard_quota ?? 3,
-      };
-      state.agentLinked = data?.linked ?? 0;
-      if ($('sa_agent_heard_enabled')) $('sa_agent_heard_enabled').checked = state.agentSettings.enabled;
-      if ($('sa_agent_auto_link')) $('sa_agent_auto_link').checked = state.agentSettings.auto_link_on_approve;
-      if ($('sa_agent_heard_quota')) $('sa_agent_heard_quota').value = String(state.agentSettings.heard_quota);
-      setAgentHeardStats(state.agentLinked);
-    } catch (e) {
-      const msg = String(e.message || e);
-      setTrainStatus(formatTrainError(msg));
-      console.warn('loadAgentHeardSettings', e);
-    }
-  }
-
-  async function saveAgentHeardSettings() {
-    const settings = {
-      enabled: !!$('sa_agent_heard_enabled')?.checked,
-      auto_link_on_approve: !!$('sa_agent_auto_link')?.checked,
-      heard_quota: Math.max(0, Math.min(8, parseInt($('sa_agent_heard_quota')?.value, 10) || 3)),
-    };
-    try {
-      const data = await SA.request('AssistentSaveDatasetAgentSettings', { settings });
-      state.agentSettings = data?.settings || settings;
-      setTrainStatus('Настройки «услышанного» сохранены');
-    } catch (e) {
-      setTrainStatus(formatTrainError(e.message || e));
-    }
-  }
-
-  async function syncAllToAgent() {
-    setTrainStatus('Подключение к агенту…');
-    try {
-      await saveAgentHeardSettings();
-      const data = await SA.request('AssistentSyncDatasetToAgent', { approved_only: true, relink: false });
-      state.agentLinked = data?.total_linked ?? state.agentLinked;
-      setAgentHeardStats(state.agentLinked);
-      setTrainStatus(`Подключено: +${data?.linked_now ?? 0}, всего ${data?.total_linked ?? '—'}`);
-      await refreshSamples();
-    } catch (e) {
-      setTrainStatus(formatTrainError(e.message || e));
-    }
-  }
-
-  function setTrainStatus(msg) {
-    const el = $('sa_train_status');
-    if (el) el.textContent = msg || '';
-  }
-
-  function isSqliteError(msg) {
-    const s = String(msg || '').toLowerCase();
-    return s.includes('sqlite')
-      || s.includes('sqlconnection')
-      || s.includes('train_samples')
-      || s.includes('training database unavailable');
-  }
-
-  function isGenericServerError(msg) {
-    return /internal error occurred/i.test(String(msg || ''));
-  }
-
-  function formatTrainError(msg) {
-    const s = String(msg || '');
-    if (isSqliteError(s)) {
-      return `${s} — ${sqliteHint()}`;
-    }
-    if (isGenericServerError(s)) {
-      return `${s} — часто SQLite/импорт HF: gpu-rent seed-extensions, restart SwarmUI, HF token для gated.`;
-    }
-    return s;
-  }
-
-  function sqliteHint() {
-    return 'База Assistent (SQLite) недоступна — gpu-rent seed-extensions + restart SwarmUI (≥0.15.6).';
-  }
-
-  function parseJobProgress(job) {
-    if (!job) return null;
-    const raw = job.progress_json;
-    if (!raw) return null;
-    try {
-      return typeof raw === 'string' ? JSON.parse(raw) : raw;
-    } catch {
-      return null;
-    }
-  }
-
-  function renderLastTrainJob(job) {
-    const box = $('sa_train_last_job');
-    if (!box) return;
-    if (!job) {
-      box.hidden = true;
-      box.innerHTML = '';
-      return;
-    }
-    const prog = parseJobProgress(job);
-    const status = job.status || prog?.status || '—';
-    const out = job.output_name || prog?.ollama?.name || '—';
-    const base = job.base_model || '—';
-    const ollama = prog?.ollama;
-    let ollamaLine = '';
-    if (ollama?.success) {
-      ollamaLine = `<div class="sa-train-last-ok">Ollama: <strong>${escapeHtml(ollama.name || out)}</strong> — выбери в шапке чата</div>`;
-    } else if (ollama?.error) {
-      ollamaLine = `<div class="sa-train-last-warn">Ollama: ${escapeHtml(ollama.error)}</div>`;
-    } else if (ollama?.skipped) {
-      ollamaLine = `<div class="sa-train-last-warn">${escapeHtml(ollama.note || 'Адаптер на диске, ollama create вручную')}</div>`;
-    }
-    box.hidden = false;
-    box.innerHTML = `
-      <div class="sa-train-last-head">Последняя тренировка · ${escapeHtml(job.kind || 'qlora')} · <span class="sa-hf-badge sa-hf-badge-${status === 'completed' ? 'ok' : status === 'failed' ? 'no' : 'map'}">${escapeHtml(status)}</span></div>
-      <div>HF base: <code>${escapeHtml(base)}</code> → имя: <code>${escapeHtml(out)}</code></div>
-      ${ollamaLine}
-      ${prog?.log ? `<pre class="sa-train-log sa-train-last-log">${escapeHtml(String(prog.log).slice(-4000))}</pre>` : ''}`;
-  }
-
-  function setTrainingTab(id) {
-    state.ttab = id || 'dataset';
-    document.querySelectorAll('#sa_training .sa-ttab').forEach((btn) => {
-      const on = btn.getAttribute('data-ttab') === state.ttab;
-      btn.classList.toggle('sa-ttab-active', on);
-      btn.setAttribute('aria-selected', on ? 'true' : 'false');
-    });
-    document.querySelectorAll('#sa_training .sa-tpane').forEach((pane) => {
-      pane.hidden = pane.getAttribute('data-tpane') !== state.ttab;
-    });
-    if (state.ttab === 'dataset') {
-      refreshSamples();
-      loadAgentHeardSettings();
-    }
-    if (state.ttab === 'train') {
-      syncModelfileModels();
-      syncQloraModels();
-      void resumeTrainJobPolling();
-    }
-    if (state.ttab === 'models') refreshTrainModels();
-  }
-
-  async function refreshSamples() {
-    try {
-      const status = $('sa_train_filter_status')?.value || 'all';
-      const persona = $('sa_train_filter_persona')?.value || 'all';
-      const data = await SA.request('AssistentListTrainSamples', { status, persona, limit: 300 });
-      if (data?.error) {
-        const msg = data.error;
-        setTrainStatus(formatTrainError(msg));
-        const stats = $('sa_train_stats');
-        if (stats) stats.textContent = 'Датасет недоступен (SQLite)';
-        state.samples = [];
-        renderSamples();
-        return;
-      }
-      state.samples = data?.samples || [];
-      const stats = $('sa_train_stats');
-      if (stats) {
-        const appr = data?.approved ?? '—';
-        const draft = data?.draft ?? '—';
-        const total = data?.total ?? '—';
-        stats.textContent = `Одобрено: ${appr} · черновики: ${draft} · всего: ${total}`;
-      }
-      const personaSel = $('sa_train_filter_persona');
-      if (personaSel && $('sa_persona')) {
-        const cur = personaSel.value || 'all';
-        personaSel.innerHTML = '<option value="all">Все личности</option>';
-        for (const opt of $('sa_persona').options) {
-          const o = document.createElement('option');
-          o.value = opt.value;
-          o.textContent = opt.textContent;
-          personaSel.appendChild(o);
-        }
-        personaSel.value = cur;
-      }
-      renderSamples();
-    } catch (e) {
-      setTrainStatus(formatTrainError(e.message || e));
-    }
-  }
-
-  function renderSamples() {
-    const root = $('sa_train_samples');
-    if (!root) return;
-    const filter = $('sa_train_filter_status')?.value || 'all';
-    if (!state.samples.length) {
-      const hint = filter === 'approved'
-        ? 'Под фильтром «Одобренные» пусто. HF-импорт создаёт <strong>черновики</strong> — переключи на «Черновики» или «Все статусы».'
-        : filter === 'draft'
-          ? 'Нет черновиков. Импортируй HF или отметь примеры в чате.'
-          : 'Нет примеров. Отметь ответы в чате или импортируй датасет (HF / файл).';
-      root.innerHTML = `<div class="sa-mem-empty">${hint}</div>`;
-      return;
-    }
-    root.innerHTML = '';
-    for (const s of state.samples) {
-      const div = document.createElement('div');
-      div.className = 'sa-train-sample';
-      div.dataset.id = s.id;
-      const msgs = s.messages || [];
-      const preview = msgs.map((m) => `${m.role}: ${(m.content || '').slice(0, 120)}`).join('\n');
-      const linked = s.agent_linked ? ' · 🔗 агент' : '';
-      div.innerHTML = `
-        <div class="sa-train-sample-head">
-          <span class="sa-hf-badge sa-hf-badge-${s.status === 'approved' ? 'ok' : s.status === 'rejected' ? 'no' : 'map'}">${escapeHtml(s.status)}</span>
-          <span>${escapeHtml(s.source)} · ${escapeHtml(s.persona || '—')} · ${escapeHtml(s.pack || '—')}${linked}</span>
-          <button type="button" class="basic-button" data-approve="1">✓</button>
-          <button type="button" class="basic-button" data-reject="1">✕</button>
-          <button type="button" class="basic-button" data-link="1" title="Подключить к агенту">🔗</button>
-          <button type="button" class="basic-button" data-unlink="1" title="Отключить от агента">⛓</button>
-          <button type="button" class="basic-button sa-danger-btn" data-del="1">Удалить</button>
-        </div>
-        <textarea spellcheck="false">${escapeHtml(preview)}</textarea>`;
-      root.appendChild(div);
-    }
-  }
-
-  async function upsertSample(patch) {
-    await SA.request('AssistentUpsertTrainSample', patch);
-    await refreshSamples();
-  }
-
-  function hfStringColumns(check) {
-    const cols = check?.schema?.columns;
-    if (Array.isArray(cols) && cols.length) return cols;
-    const feats = check?.features;
-    if (Array.isArray(feats)) {
-      return feats.map((f) => f?.name).filter(Boolean);
-    }
-    if (feats && typeof feats === 'object') return Object.keys(feats);
-    return [];
-  }
-
-  function renderHfMappingUI(check) {
-    const row = $('sa_hf_mapping_row');
-    if (!row) return;
-    const gate = check?.gate;
-    const schemaKind = check?.schema?.kind;
-    const needsMapping = gate === 'mapping' || schemaKind === 'fiction_tags_text';
-    row.hidden = !needsMapping;
-    if (!needsMapping) {
-      state.hfMapping = null;
-      return;
-    }
-    const cols = hfStringColumns(check);
-    const userSel = $('sa_hf_user_col');
-    const asstSel = $('sa_hf_asst_col');
-    const presetSel = $('sa_hf_mapping_preset');
-    if (userSel) {
-      userSel.innerHTML = cols.map((c) => `<option value="${escapeHtml(c)}">${escapeHtml(c)}</option>`).join('');
-      if (cols.includes('tags')) userSel.value = 'tags';
-      else if (cols.includes('title')) userSel.value = 'title';
-    }
-    if (asstSel) {
-      asstSel.innerHTML = cols.map((c) => `<option value="${escapeHtml(c)}">${escapeHtml(c)}</option>`).join('');
-      if (cols.includes('text')) asstSel.value = 'text';
-      else if (cols.includes('output')) asstSel.value = 'output';
-    }
-    if (schemaKind === 'fiction_tags_text' && presetSel) {
-      presetSel.value = 'fiction_tags_text';
-      state.hfMapping = { kind: 'fiction_tags_text', preset: 'fiction_tags_text' };
-    }
-  }
-
-  function buildHfMappingPayload() {
-    const preset = $('sa_hf_mapping_preset')?.value;
-    if (preset === 'fiction_tags_text') {
-      return { kind: 'fiction_tags_text', preset: 'fiction_tags_text' };
-    }
-    const userCol = $('sa_hf_user_col')?.value;
-    const asstCol = $('sa_hf_asst_col')?.value;
-    if (userCol && asstCol) {
-      return { kind: 'custom', user_col: userCol, assistant_col: asstCol };
-    }
-    return state.hfMapping;
-  }
-
-  function getQloraHfBase() {
-    const sel = $('sa_qlora_base');
-    if (!sel) return '';
-    if (sel.value === QLORA_HF_CUSTOM) {
-      return ($('sa_qlora_base_custom')?.value || '').trim();
-    }
-    return (sel.value || '').trim();
-  }
-
-  function applyQloraPresetFromSelect({ fillName = true } = {}) {
-    const sel = $('sa_qlora_base');
-    const customRow = $('sa_qlora_base_custom_row');
-    if (!sel) return;
-    if (sel.value === QLORA_HF_CUSTOM) {
-      if (customRow) customRow.hidden = false;
-      return;
-    }
-    if (customRow) customRow.hidden = true;
-    const presetJson = sel.selectedOptions[0]?.dataset?.preset;
-    if (!presetJson) return;
-    let preset;
-    try {
-      preset = JSON.parse(presetJson);
-    } catch {
-      return;
-    }
-    const nameEl = $('sa_qlora_name');
-    if (fillName && nameEl && !nameEl.value.trim() && preset.default_output) {
-      nameEl.value = preset.default_output;
-    }
-    const ollamaSel = $('sa_qlora_ollama_base');
-    if (ollamaSel && preset.ollama_hint) {
-      const hint = preset.ollama_hint;
-      if ([...ollamaSel.options].some((o) => o.value === hint)) {
-        ollamaSel.value = hint;
-      }
-    }
-    if (preset.rank != null && $('sa_qlora_rank')) {
-      $('sa_qlora_rank').value = preset.rank;
-    }
-    if (preset.seq_len != null && $('sa_qlora_seq')) {
-      $('sa_qlora_seq').value = preset.seq_len;
-    }
-  }
-
-  function populateQloraHfPresets(training) {
-    const sel = $('sa_qlora_base');
-    if (!sel) return;
-    const prevBase = getQloraHfBase();
-    const models = Array.isArray(training?.hf_models) ? training.hf_models : [];
-    sel.innerHTML = '<option value="">— выберите модель —</option>';
-    for (const m of models) {
-      const hfId = (m.hf_id || m.id || '').trim();
-      if (!hfId) continue;
-      const opt = document.createElement('option');
-      opt.value = hfId;
-      opt.textContent = m.title ? `${m.title} (${hfId})` : hfId;
-      opt.dataset.preset = JSON.stringify(m);
-      sel.appendChild(opt);
-    }
-    const customOpt = document.createElement('option');
-    customOpt.value = QLORA_HF_CUSTOM;
-    customOpt.textContent = 'Другая (ввести HF id…)';
-    sel.appendChild(customOpt);
-    if (prevBase && [...sel.options].some((o) => o.value === prevBase)) {
-      sel.value = prevBase;
-    } else if (prevBase) {
-      sel.value = QLORA_HF_CUSTOM;
-      const custom = $('sa_qlora_base_custom');
-      if (custom) custom.value = prevBase;
-    } else if (models.length) {
-      sel.value = (models[0].hf_id || models[0].id || '').trim();
-    }
-    applyQloraPresetFromSelect({ fillName: !prevBase });
-  }
-
-  async function ensureTrainingQloraConfig(force = false) {
-    if (!force && state.qloraTraining) {
-      return state.qloraTraining;
-    }
-    try {
-      const persona = $('sa_persona')?.value || '';
-      const data = await SA.request('AssistentGetConfig', { persona });
-      state.qloraTraining = data?.training && typeof data.training === 'object'
-        ? data.training
-        : { hf_models: [] };
-      return state.qloraTraining;
-    } catch {
-      state.qloraTraining = state.qloraTraining || { hf_models: [] };
-      return state.qloraTraining;
-    }
-  }
-
-  async function syncQloraModels() {
-    try {
-      const training = await ensureTrainingQloraConfig();
-      populateQloraHfPresets(training);
-      const baseUrl = $('sa_base_url')?.value || localStorage.getItem('swarm_assistent_base_url') || '';
-      const data = await SA.request('AssistentListModels', { baseUrl });
-      const models = data?.models || [];
-      const sel = $('sa_qlora_ollama_base');
-      if (!sel) return;
-      const cur = sel.value;
-      sel.innerHTML = '<option value="">—</option>';
-      for (const m of models) {
-        const opt = document.createElement('option');
-        opt.value = m;
-        opt.textContent = m;
-        sel.appendChild(opt);
-      }
-      if (cur) sel.value = cur;
-      else if ($('sa_model')?.value) sel.value = $('sa_model').value;
-      applyQloraPresetFromSelect({ fillName: false });
-    } catch (e) { /* ignore */ }
-  }
-
-  function renderHfList() {
-    const root = $('sa_hf_list');
-    if (!root) return;
-    root.innerHTML = '';
-    const showAll = !!$('sa_hf_show_all')?.checked;
-    for (const r of state.hfResults) {
-      if (!showAll && r.gate === 'rejected') continue;
-      const row = document.createElement('div');
-      row.className = 'sa-hf-row' + (state.hfSelected === r.id ? ' sa-hf-row-active' : '') + (r.gate === 'rejected' ? ' sa-hf-rejected' : '');
-      row.dataset.id = r.id;
-      const badge = r.gate === 'ok' ? 'ok' : r.gate === 'mapping' ? 'map' : 'no';
-      row.innerHTML = `<span class="sa-hf-badge sa-hf-badge-${badge}">${escapeHtml(r.gate)}</span><strong>${escapeHtml(r.id)}</strong><span>${escapeHtml(r.reason || '')}</span>`;
-      root.appendChild(row);
-    }
-  }
-
-  async function searchHf() {
-    const q = ($('sa_hf_search')?.value || '').trim();
-    setTrainStatus('Поиск…');
-    try {
-      const data = await SA.request('AssistentSearchHfDatasets', {
-        q,
-        limit: 24,
-        show_all: !!$('sa_hf_show_all')?.checked,
-      });
-      state.hfResults = data?.results || [];
-      renderHfList();
-      setTrainStatus(`Найдено: ${state.hfResults.length}`);
-    } catch (e) {
-      setTrainStatus(formatTrainError(e.message || e));
-    }
-  }
-
-  async function checkHfLink() {
-    const link = ($('sa_hf_link')?.value || '').trim();
-    const status = $('sa_hf_status');
-    if (!link) return;
-    if (status) status.textContent = 'Проверяю…';
-    try {
-      const data = await SA.request('AssistentCheckHfDataset', { dataset: link });
-      state.hfCheck = data;
-      state.hfSelected = data.id;
-      if (status) {
-        status.textContent = data.gate === 'rejected'
-          ? `Отклонено: ${data.reason}`
-          : `${data.gate}: ${data.reason || 'OK'}`;
-      }
-      const preview = $('sa_hf_preview');
-      if (preview) {
-        preview.hidden = false;
-        preview.textContent = JSON.stringify(data.sample_rows || data.features || data, null, 2).slice(0, 8000);
-      }
-      const importRow = $('sa_hf_import_row');
-      if (importRow) importRow.hidden = data.gate === 'rejected';
-      renderHfMappingUI(data);
-    } catch (e) {
-      if (status) status.textContent = String(e.message || e);
-    }
-  }
-
-  async function importHf() {
-    const link = ($('sa_hf_link')?.value || '').trim();
-    if (!state.hfCheck?.id && link) {
-      await checkHfLink();
-    }
-    if (!state.hfSelected && !state.hfCheck?.id) {
-      setTrainStatus('Сначала проверь набор');
-      const hfSt = $('sa_hf_status');
-      if (hfSt) hfSt.textContent = 'Вставь ссылку и нажми «Проверить»';
-      return;
-    }
-    const id = state.hfSelected || state.hfCheck.id;
-    const limit = Number($('sa_hf_import_limit')?.value) || 200;
-    const mapping = buildHfMappingPayload();
-    const btn = $('sa_btn_hf_import');
-    const hfSt = $('sa_hf_status');
-    const busy = limit > 400
-      ? `Импортирую до ${limit} строк… (1–2 мин)`
-      : `Импортирую до ${limit}…`;
-    setTrainStatus(busy);
-    if (hfSt) {
-      hfSt.textContent = busy;
-      hfSt.classList.add('sa-hf-busy');
-    }
-    if (btn) {
-      btn.disabled = true;
-      btn.dataset.label = btn.textContent;
-      btn.textContent = '…';
-    }
-    try {
-      const data = await SA.request('AssistentImportHfDataset', { dataset: id, limit, mapping });
-      const n = Number(data?.imported) || 0;
-      let msg;
-      if (data?.runner_only) {
-        msg = `Runner-only: ${data.note || id} (в sqlite не импортировали)`;
-      } else if (n > 0) {
-        const filt = $('sa_train_filter_status');
-        if (filt && filt.value === 'approved') {
-          filt.value = 'draft';
-        }
-        msg = `Импортировано: ${n} черновик(ов) — список ниже (фильтр → черновики)`;
-      } else {
-        msg = 'Импортировано: 0 — HF token в User Settings, маппинг или gated-набор';
-      }
-      setTrainStatus(msg);
-      if (hfSt) hfSt.textContent = msg;
-      await refreshSamples();
-      $('sa_train_samples')?.scrollIntoView({ behavior: 'smooth', block: 'nearest' });
-    } catch (e) {
-      const err = String(e.message || e);
-      const show = formatTrainError(err);
-      setTrainStatus(show);
-      if (hfSt) hfSt.textContent = show;
-    } finally {
-      if (hfSt) hfSt.classList.remove('sa-hf-busy');
-      if (btn) {
-        btn.disabled = false;
-        btn.textContent = btn.dataset.label || 'Импортировать';
-      }
-    }
-  }
-
-  async function syncModelfileModels() {
-    try {
-      const baseUrl = $('sa_base_url')?.value || localStorage.getItem('swarm_assistent_base_url') || '';
-      const data = await SA.request('AssistentListModels', { baseUrl });
-      const models = data?.models || [];
-      for (const selId of ['sa_modelfile_base']) {
-        const sel = $(selId);
-        if (!sel) continue;
-        const cur = sel.value;
-        sel.innerHTML = '<option value="">—</option>';
-        for (const m of models) {
-          const opt = document.createElement('option');
-          opt.value = m;
-          opt.textContent = m;
-          sel.appendChild(opt);
-        }
-        if (cur) sel.value = cur;
-      }
-      const personaSel = $('sa_modelfile_persona');
-      if (personaSel && $('sa_persona')) {
-        personaSel.innerHTML = $('sa_persona').innerHTML;
-        personaSel.value = $('sa_persona').value || 'neutral';
-      }
-    } catch (e) { /* ignore */ }
-  }
-
-  async function createModelfile() {
-    const btn = $('sa_btn_modelfile_create');
-    btn?.setAttribute('disabled', 'disabled');
-    setTrainStatus('Создаю Modelfile в Ollama…');
-    try {
-      const data = await SA.request('AssistentCreateOllamaModel', {
-        base_url: $('sa_base_url')?.value,
-        base_model: $('sa_modelfile_base')?.value,
-        name: $('sa_modelfile_name')?.value,
-        persona: $('sa_modelfile_persona')?.value,
-        system: $('sa_modelfile_system')?.value,
-        shots: Number($('sa_modelfile_shots')?.value) || 8,
-        num_ctx: Number($('sa_modelfile_num_ctx')?.value) || 16384,
-        temperature: Number($('sa_modelfile_temp')?.value) || 0.7,
-      });
-      setTrainStatus(`Готово: ${data.name}`);
-      SA.app?.refreshModels?.();
-    } catch (e) {
-      setTrainStatus(formatTrainError(e.message || e));
-    } finally {
-      btn?.removeAttribute('disabled');
-    }
-  }
-
-  function setTrainMode(mode) {
-    $('sa_train_form_modelfile').hidden = mode !== 'modelfile';
-    $('sa_train_form_qlora').hidden = mode !== 'qlora';
-    const radio = document.querySelector(`input[name="sa_train_mode"][value="${mode}"]`);
-    if (radio) radio.checked = true;
-  }
-
-  function setTrainingLock(on, text) {
-    const root = $('swarm_assistent_root');
-    const banner = $('sa_train_banner');
-    if (root) root.classList.toggle('sa-root-training-lock', !!on);
-    if (banner) {
-      banner.hidden = !on;
-      const t = $('sa_train_banner_text');
-      if (t && text) t.textContent = text;
-    }
-    SA.app?.setTrainingLock?.(!!on);
-  }
-
-  async function pollTrainJob() {
-    try {
-      const data = await SA.request('AssistentGetTrainJob', {});
-      const prog = data?.progress || (data?.job?.progress_json ? JSON.parse(data.job.progress_json) : null);
-      const active = data?.training_active || data?.job?.status === 'running';
-      const status = data?.job?.status || prog?.status;
-      const pct = prog?.percent;
-      const bannerText = active && pct != null
-        ? `QLoRA · ${pct}%`
-        : active
-          ? 'Идёт QLoRA…'
-          : 'Идёт тренировка…';
-      setTrainingLock(active, bannerText);
-      const logEl = $('sa_train_log');
-      const bar = $('sa_train_progress_fill');
-      const box = $('sa_train_progress');
-      if (prog) {
-        if (box) box.hidden = false;
-        if (bar && pct != null) bar.style.width = `${pct}%`;
-        if (logEl && prog.log) logEl.textContent = prog.log;
-      }
-      if (active) {
-        setTrainStatus(pct != null
-          ? `QLoRA · ${pct}% — полный лог на вкладке «Тренировка»`
-          : 'QLoRA запущена — полный лог на вкладке «Тренировка»');
-      }
-      if (!active) {
-        clearInterval(state.polling);
-        state.polling = null;
-        $('sa_btn_qlora_cancel').hidden = true;
-        setTrainingLock(false);
-        if (status === 'completed' || status === 'completed_with_warnings') {
-          const ollama = prog?.ollama;
-          if (ollama?.success) {
-            setTrainStatus(`Готово: модель ${ollama.name} в Ollama — вкладка «Модели»`);
-            SA.app?.refreshModels?.();
-          } else if (ollama?.skipped) {
-            setTrainStatus(ollama.note || ollama.error || 'Адаптер сохранён — см. вкладку «Модели»');
-          } else if (ollama?.error) {
-            setTrainStatus(`Обучение OK, Ollama: ${ollama.error}`);
-          } else if (status === 'completed_with_warnings') {
-            setTrainStatus('Завершено с предупреждениями — лог на «Модели»');
-          } else {
-            setTrainStatus('QLoRA завершено — вкладка «Модели»');
-          }
-          setTrainingTab('models');
-          await refreshTrainModels();
-        } else if (status === 'failed') {
-          setTrainStatus(`Ошибка тренировки (exit ${prog?.exit_code ?? '?'})`);
-        }
-      }
-    } catch (e) { /* ignore */ }
-  }
-
-  async function resumeTrainJobPolling() {
-    try {
-      const data = await SA.request('AssistentGetTrainJob', {});
-      const active = data?.training_active || data?.job?.status === 'running';
-      await pollTrainJob();
-      if (!active) return;
-      setTrainMode('qlora');
-      $('sa_btn_qlora_cancel').hidden = false;
-      if (state.polling) clearInterval(state.polling);
-      state.polling = setInterval(pollTrainJob, 1500);
-    } catch (e) { /* ignore */ }
-  }
-
-  async function startQlora() {
-    const baseModel = getQloraHfBase();
-    const outputName = ($('sa_qlora_name')?.value || '').trim();
-    if (!baseModel) {
-      setTrainStatus('Выберите HF base model из списка или укажите свой HF id');
-      $('sa_qlora_base')?.focus();
-      return;
-    }
-    if (!outputName) {
-      setTrainStatus('Укажите имя модели в Ollama (например my-lora:v1)');
-      $('sa_qlora_name')?.focus();
-      return;
-    }
-    setTrainStatus('Запуск…');
-    try {
-      const hfDs = ($('sa_qlora_hf_dataset')?.value || '').trim();
-      const mapping = hfDs ? buildHfMappingPayload() : undefined;
-      await SA.request('AssistentStartTrainJob', {
-        base_url: $('sa_base_url')?.value,
-        chat_model: $('sa_model')?.value,
-        base_model: baseModel,
-        ollama_base: $('sa_qlora_ollama_base')?.value,
-        output_name: outputName,
-        rank: Number($('sa_qlora_rank')?.value) || 16,
-        alpha: Number($('sa_qlora_alpha')?.value) || 32,
-        lr: Number($('sa_qlora_lr')?.value) || 0.0002,
-        epochs: Number($('sa_qlora_epochs')?.value) || 3,
-        seq_len: Number($('sa_qlora_seq')?.value) || 2048,
-        max_samples: Number($('sa_qlora_max_samples')?.value) || 0,
-        four_bit: !!$('sa_qlora_4bit')?.checked,
-        hf_dataset: hfDs || undefined,
-        hf_mapping: mapping,
-      });
-      $('sa_btn_qlora_cancel').hidden = false;
-      setTrainingLock(true, 'Идёт тренировка…');
-      if (state.polling) clearInterval(state.polling);
-      state.polling = setInterval(pollTrainJob, 1500);
-      pollTrainJob();
-      setTrainMode('qlora');
-      setTrainingTab('train');
-      setTrainStatus('QLoRA запущена — прогресс ниже');
-    } catch (e) {
-      setTrainStatus(formatTrainError(e.message || e));
-    }
-  }
-
-  async function cancelQlora() {
-    try {
-      await SA.request('AssistentCancelTrainJob', {});
-      setTrainingLock(false);
-      setTrainStatus('Отменено');
-    } catch (e) {
-      setTrainStatus(formatTrainError(e.message || e));
-    }
-  }
-
-  async function refreshTrainModels() {
-    const root = $('sa_train_models_list');
-    if (!root) return;
-    try {
-      const jobData = await SA.request('AssistentGetTrainJob', {});
-      renderLastTrainJob(jobData?.last_job || jobData?.job);
-      const data = await SA.request('AssistentListModels', { baseUrl: $('sa_base_url')?.value });
-      const models = data?.models || [];
-      const lastOut = jobData?.last_job?.output_name;
-      root.innerHTML = models.length
-        ? models.map((m) => {
-          const hit = lastOut && String(m).includes(String(lastOut).split(':')[0]);
-          return `<div class="sa-hf-row${hit ? ' sa-train-model-new' : ''}"><strong>${escapeHtml(m)}</strong>${hit ? ' · последняя тренировка' : ''}</div>`;
-        }).join('')
-        : '<div class="sa-mem-empty">Нет моделей в Ollama — после QLoRA нажми «Обновить» или проверь лог тренировки</div>';
-    } catch (e) {
-      const msg = String(e.message || e);
-      root.innerHTML = `<div class="sa-mem-empty">${escapeHtml(isSqliteError(msg) ? sqliteHint() : msg)}</div>`;
-    }
-  }
-
-  async function saveRunner() {
-    try {
-      await SA.request('AssistentSaveRunnerSettings', {
-        python: $('sa_runner_python')?.value,
-        kind: $('sa_runner_kind')?.value || 'builtin',
-        workdir: $('sa_runner_workdir')?.value,
-        cmd: $('sa_runner_cmd')?.value,
-        gguf_script: $('sa_runner_gguf_script')?.value,
-        gguf_base_path: $('sa_runner_gguf_base')?.value,
-        gguf_cmd: $('sa_runner_gguf_cmd')?.value,
-      });
-      setTrainStatus('Раннер сохранён');
-    } catch (e) {
-      setTrainStatus(formatTrainError(e.message || e));
-    }
-  }
-
-  async function loadRunner() {
-    try {
-      const data = await SA.request('AssistentGetRunnerSettings', {});
-      const s = data?.settings || {};
-      if ($('sa_runner_python') && s.python) $('sa_runner_python').value = s.python;
-      if ($('sa_runner_kind')) $('sa_runner_kind').value = s.kind || 'builtin';
-      if ($('sa_runner_workdir') && s.workdir) $('sa_runner_workdir').value = s.workdir;
-      if ($('sa_runner_cmd') && s.cmd) $('sa_runner_cmd').value = s.cmd;
-      if ($('sa_runner_gguf_script') && s.gguf_script) $('sa_runner_gguf_script').value = s.gguf_script;
-      if ($('sa_runner_gguf_base') && s.gguf_base_path) $('sa_runner_gguf_base').value = s.gguf_base_path;
-      if ($('sa_runner_gguf_cmd') && s.gguf_cmd) $('sa_runner_gguf_cmd').value = s.gguf_cmd;
-    } catch (e) { /* ignore */ }
-  }
-
-  function wireTraining() {
-    if (window.__saTrainingWired) return;
-    window.__saTrainingWired = true;
-    document.querySelectorAll('#sa_training .sa-ttab').forEach((btn) => {
-      btn.addEventListener('click', () => setTrainingTab(btn.getAttribute('data-ttab')));
-    });
-    $('sa_btn_agent_sync')?.addEventListener('click', syncAllToAgent);
-    $('sa_agent_heard_enabled')?.addEventListener('change', saveAgentHeardSettings);
-    $('sa_agent_auto_link')?.addEventListener('change', saveAgentHeardSettings);
-    $('sa_agent_heard_quota')?.addEventListener('change', saveAgentHeardSettings);
-    loadAgentHeardSettings();
-    $('sa_btn_train_from_chats')?.addEventListener('click', async () => {
-      try {
-        const data = await SA.request('AssistentBuildDatasetFromChats', {});
-        setTrainStatus(`Из чатов: +${data.added}`);
-        await refreshSamples();
-      } catch (e) { setTrainStatus(String(e.message || e)); }
-    });
-    $('sa_btn_train_import_file')?.addEventListener('click', () => $('sa_train_import_file')?.click());
-    $('sa_train_import_file')?.addEventListener('change', async (e) => {
-      const file = e.target?.files?.[0];
-      if (!file) return;
-      const text = await file.text();
-      try {
-        const data = await SA.request('AssistentImportDataset', { format: 'auto', content: text });
-        setTrainStatus(`Импорт: ${data.imported}`);
-        await refreshSamples();
-      } catch (err) { setTrainStatus(formatTrainError(err.message || err)); }
-      e.target.value = '';
-    });
-    $('sa_btn_train_export')?.addEventListener('click', async () => {
-      try {
-        const data = await SA.request('AssistentExportDataset', { status: 'approved' });
-        if (data.content) {
-          const blob = new Blob([data.content], { type: 'application/jsonl' });
-          const a = document.createElement('a');
-          a.href = URL.createObjectURL(blob);
-          a.download = 'assistent-dataset.jsonl';
-          a.click();
-        }
-        setTrainStatus(`Экспорт: ${data.count} примеров`);
-      } catch (e) { setTrainStatus(String(e.message || e)); }
-    });
-    $('sa_train_filter_status')?.addEventListener('change', refreshSamples);
-    $('sa_train_filter_persona')?.addEventListener('change', refreshSamples);
-    $('sa_train_samples')?.addEventListener('click', async (e) => {
-      const row = e.target.closest('.sa-train-sample');
-      if (!row) return;
-      const id = row.dataset.id;
-      const sample = state.samples.find((s) => s.id === id);
-      if (!sample) return;
-      if (e.target.closest('[data-approve]')) {
-        await upsertSample({ ...sample, status: 'approved' });
-        await loadAgentHeardSettings();
-      } else if (e.target.closest('[data-reject]')) {
-        await upsertSample({ ...sample, status: 'rejected' });
-        await loadAgentHeardSettings();
-      } else if (e.target.closest('[data-link]')) {
-        try {
-          const data = await SA.request('AssistentLinkTrainSampleToAgent', { id });
-          state.agentLinked = data?.linked ?? state.agentLinked;
-          setAgentHeardStats(state.agentLinked);
-          setTrainStatus('Пример подключён к агенту');
-          await refreshSamples();
-        } catch (err) { setTrainStatus(formatTrainError(err.message || err)); }
-      } else if (e.target.closest('[data-unlink]')) {
-        try {
-          const data = await SA.request('AssistentUnlinkTrainSampleFromAgent', { id });
-          state.agentLinked = data?.linked ?? state.agentLinked;
-          setAgentHeardStats(state.agentLinked);
-          setTrainStatus('Пример отключён от агента');
-          await refreshSamples();
-        } catch (err) { setTrainStatus(formatTrainError(err.message || err)); }
-      } else if (e.target.closest('[data-del]')) {
-        if (window.confirm('Удалить пример?')) {
-          await SA.request('AssistentDeleteTrainSample', { id });
-          await refreshSamples();
-        }
-      }
-    });
-    $('sa_btn_hf_search')?.addEventListener('click', searchHf);
-    $('sa_hf_show_all')?.addEventListener('change', () => { renderHfList(); });
-    $('sa_hf_list')?.addEventListener('click', async (e) => {
-      const row = e.target.closest('.sa-hf-row');
-      if (!row || row.classList.contains('sa-hf-rejected')) return;
-      state.hfSelected = row.dataset.id;
-      $('sa_hf_link').value = row.dataset.id;
-      renderHfList();
-      await checkHfLink();
-    });
-    $('sa_btn_hf_check')?.addEventListener('click', checkHfLink);
-    $('sa_hf_mapping_preset')?.addEventListener('change', () => {
-      state.hfMapping = buildHfMappingPayload();
-    });
-    $('sa_btn_hf_import')?.addEventListener('click', importHf);
-    document.querySelectorAll('input[name="sa_train_mode"]').forEach((r) => {
-      r.addEventListener('change', () => setTrainMode(r.value));
-    });
-    $('sa_btn_modelfile_create')?.addEventListener('click', createModelfile);
-    $('sa_qlora_base')?.addEventListener('change', () => applyQloraPresetFromSelect());
-    $('sa_btn_qlora_start')?.addEventListener('click', startQlora);
-    $('sa_btn_qlora_cancel')?.addEventListener('click', cancelQlora);
-    $('sa_btn_train_models_refresh')?.addEventListener('click', refreshTrainModels);
-    $('sa_btn_save_runner')?.addEventListener('click', saveRunner);
-    loadRunner();
-    setTrainMode('modelfile');
-    void resumeTrainJobPolling();
-  }
-
-  SA.training = {
-    render() {
-      wireTraining();
-      setTrainingTab(state.ttab);
-    },
-    onConfig(data) {
-      if (data?.training && typeof data.training === 'object') {
-        state.qloraTraining = data.training;
-        if (state.ttab === 'train') {
-          populateQloraHfPresets(state.qloraTraining);
-          applyQloraPresetFromSelect({ fillName: false });
-        }
-      }
-    },
-    resumePolling: resumeTrainJobPolling,
-    async curateFromChat(messages, meta) {
-      try {
-        await SA.request('AssistentUpsertTrainSample', {
-          source: 'chat',
-          chat_id: meta?.chatId,
-          persona: meta?.persona,
-          pack: meta?.pack,
-          status: meta?.status || 'approved',
-          messages,
-        });
-        return true;
-      } catch (e) {
-        console.warn('curateFromChat', e);
-        return false;
-      }
-    },
-    setTrainingLock,
-    pollTrainJob,
-  };
-}