fix(openai): ask_user_choice-Intercept, Interleaved Thinking in History, MiniMax-Debug-Log
OpenAI-kompatible Provider (MiniMax, DeepSeek-R1, QwQ, Kimi K2, etc.) verloren bei
jeder neuen Iteration ihre eigene Chain-of-Thought, weil thinking-Messages aus der
DB-History rausgefiltert wurden. Folge: Modell kündigt Action an, ruft Tool aber
nicht auf → Stream endet mit finish_reason:stop ohne Tool-Call. Zusätzlich fehlte
der ask_user_choice-Intercept (Tool wurde als unbekannt abgelehnt) und es gab keine
Diagnose-Möglichkeit für unerwartete Stop-Verhalten.
- ChatService.BuildHistoryFromDb(includeThinking): neuer Parameter, fügt
thinking-Messages als {type:"thinking"}-Block in die Assistant-Message ein.
Text/Tool-Use derselben Iteration werden via AppendToLastMessage angehängt
→ ein Assistant-Block enthält [thinking, text, tool_use…].
- OpenAiService.ConvertMessage + StreamChat + ChatNonStreaming: Thinking als
<think>...</think>-Prefix dem Assistant-Content voranstellen (Per-Iteration und
beim DB-History-Aufbau). Konvention von MiniMax-Docs, wird auch von DeepSeek-R1,
QwQ, Kimi K2 verstanden.
- ChatEndpoint, SessionEndpoint, CronjobService, TelegramService, ToolService:
includeThinking je nach Provider durchgereicht. Anthropic-Pfad bleibt aus
(lehnt thinking-Blöcke ohne Signature ab).
- OpenAiService: ask_user_choice-Intercept im Streaming-Pfad (analog
AnthropicService.Streaming) – Tool nicht ausführen, SSE user_choice rausschicken,
mit stopReason awaiting_user_choice finalisieren und return.
- OpenAiService: MiniMax-SSE-Debug-Log in data/openai-debug/ (JSONL: Header +
Roh-data-Zeilen + Summary mit promptTokens/completionTokens/finishReason/
toolCalls/duration) – nur für provider=="minimax", nicht-blockierend.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
MelekiandClaude Opus 4.7 committed
1 parent
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commit
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7 files changed
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@@ -185,8 +185,13 @@ public static class ChatEndpoint
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} // !skipPreparer
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}
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// History für den Session-Agent: OHNE Sub-Agent-Messages (saubere History)
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var messages = await chatService.BuildHistoryFromDb(sessionId, promptBlocks: ctx.PromptBlocks);
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// History für den Session-Agent: OHNE Sub-Agent-Messages (saubere History).
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// includeThinking=true für OpenAI-kompatible Provider → Thinking wird als
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// <think>...</think>-Prefix dem Assistant-Text vorangestellt (laut MiniMax-Docs essentiell
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// für Tool-Calling-Reliability / Interleaved Thinking). Anthropic-Pfad braucht das nicht,
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// weil dort thinking-Blöcke nur mit Signatur akzeptiert werden (die wir nicht persistieren).
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var includeThinkingForProvider = !string.IsNullOrEmpty(ctx.Provider);
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var messages = await chatService.BuildHistoryFromDb(sessionId, promptBlocks: ctx.PromptBlocks, includeThinking: includeThinkingForProvider);
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// Bei Choice-Response: toolChoice auf "auto" setzen, damit Claude frei antworten kann
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var effectiveToolChoice = isChoiceResponse ? "auto" : ctx.ToolChoice;
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@@ -287,8 +287,9 @@ public static class SessionEndpoint
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// Model
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var modelId = ChatService.ResolveModelId(agent.Model);
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// Messages aus der DB (exakt wie beim Chat)
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var messages = await chatService.BuildHistoryFromDb(session.SessionId, promptBlocks: promptBlocks);
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// Messages aus der DB (exakt wie beim Chat) – includeThinking je nach Provider
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var previewProvider = OpenAiService.IsOpenAiProvider(modelId);
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var messages = await chatService.BuildHistoryFromDb(session.SessionId, promptBlocks: promptBlocks, includeThinking: previewProvider);
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// Tools (exakt wie AddToolsToPayload es machen würde)
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var hasWorkspace = !string.IsNullOrEmpty(workspace);
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+26
-6
@@ -232,7 +232,7 @@ Für welche Plattform soll die App entwickelt werden? Web, Mobile oder Desktop?
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/// includeTag: Wenn gesetzt, werden Messages mit diesem Tag NICHT ausgefiltert
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/// (z.B. "preparer" damit der Preparer seine eigenen vorherigen Messages sieht).
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/// </summary>
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public async Task<List<object>> BuildHistoryFromDb(string sessionId, string includeTag = null, List<PromptBlock> promptBlocks = null)
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public async Task<List<object>> BuildHistoryFromDb(string sessionId, string includeTag = null, List<PromptBlock> promptBlocks = null, bool includeThinking = false)
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{
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var chainsList = (await _db.GetActiveChains(sessionId)).ToList();
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// chronologisch sortieren (älteste zuerst)
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@@ -359,15 +359,35 @@ Für welche Plattform soll die App entwickelt werden? Web, Mobile oder Desktop?
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if (content.Count > 0)
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history.Add(new Dictionary<string, object> { ["role"] = "user", ["content"] = content });
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}
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else if (msg.Role == "assistant" && msg.Type == "thinking" && includeThinking)
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{
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// Thinking-Inhalt für OpenAI-kompatible Provider mitführen.
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// Wird in OpenAiService.ConvertMessage als <think>...</think>
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// dem Assistant-Text vorangestellt (laut MiniMax-Docs: "the content field
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// will contain <think> tag content, which must be preserved completely"
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// → essential für Interleaved Thinking, Tool-Calling-Reliability,
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// siehe https://www.minimax.io/news/why-is-interleaved-thinking-important-for-m2).
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// Anthropic-Pfad: includeThinking=false → Block wird übersprungen,
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// weil Anthropic-API thinking-Blöcke ohne Signature ablehnt.
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if (!string.IsNullOrEmpty(msg.Content))
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{
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// NEUE assistant message starten; text/tool_use derselben Iteration
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// werden via AppendToLastMessage angehängt → ein assistant-Block enthält
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// dann [thinking, text, tool_use…].
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history.Add(new Dictionary<string, object>
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{
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["role"] = "assistant",
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["content"] = new List<object> { new { type = "thinking", thinking = msg.Content } }
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});
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}
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}
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else if (msg.Role == "assistant" && msg.Type == "text")
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{
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if (!string.IsNullOrEmpty(msg.Content))
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{
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history.Add(new Dictionary<string, object>
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{
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["role"] = "assistant",
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["content"] = new List<object> { new { type = "text", text = msg.Content } }
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});
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// Wenn die letzte Message bereits assistant ist (z.B. mit Thinking-Block
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// aus derselben Iteration), Text dort anhängen statt neue Message zu starten.
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AppendToLastMessage(history, "assistant", new { type = "text", text = msg.Content });
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}
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}
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else if (msg.Role == "assistant" && msg.Type == "tool_use")
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@@ -95,8 +95,9 @@ public class CronjobService : BackgroundService
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throw new Exception($"Kein API-Key für Agent {ctx.AgentId} zugewiesen (User {job.UserId})");
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ctx.ApiToken = userApiKey.ApiKey;
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// History aus DB laden
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var history = await _chatService.BuildHistoryFromDb(job.SessionId, promptBlocks: ctx.PromptBlocks);
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// History aus DB laden. includeThinking=true für OpenAI-kompatible Provider →
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// <think>...</think>-Prefix wird dem Assistant-Text vorangestellt.
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var history = await _chatService.BuildHistoryFromDb(job.SessionId, promptBlocks: ctx.PromptBlocks, includeThinking: !string.IsNullOrEmpty(ctx.Provider));
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// User-Nachricht hinzufügen
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var userContent = new List<object> { new { type = "text", text = job.Prompt } };
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+181
-6
@@ -387,6 +387,41 @@ public class OpenAiService
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using var stream = await httpResp.Content.ReadAsStreamAsync(workCt);
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using var reader = new System.IO.StreamReader(stream);
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// Diagnose-Logging für MiniMax: jede SSE-data-Line + Header + Summary in JSONL.
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// Verzeichnis: data/openai-debug/{provider}-{ts}-{chainId8}.jsonl
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System.IO.StreamWriter debugWriter = null;
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string debugLogPath = null;
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long debugLineCount = 0;
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string lastFinishReason = null;
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if (provider == "minimax")
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{
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try
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{
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var dataDir = System.IO.Path.Combine(AppContext.BaseDirectory, "data", "openai-debug");
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System.IO.Directory.CreateDirectory(dataDir);
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var ts = DateTime.UtcNow.ToString("yyyyMMdd-HHmmss-fff");
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var chainShort = chainId.Length >= 8 ? chainId.Substring(0, 8) : chainId;
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debugLogPath = System.IO.Path.Combine(dataDir, $"{provider}-{ts}-{chainShort}.jsonl");
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debugWriter = new System.IO.StreamWriter(
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new System.IO.FileStream(debugLogPath, System.IO.FileMode.Create, System.IO.FileAccess.Write, System.IO.FileShare.Read),
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new UTF8Encoding(false))
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{ AutoFlush = true };
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var header = JsonSerializer.Serialize(new
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{
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meta = true,
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provider,
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model = modelId,
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chainId,
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iteration,
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promptMessages = apiMessages.Count,
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maxTokens,
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started = DateTime.UtcNow.ToString("o")
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});
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await debugWriter.WriteLineAsync(header);
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}
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catch { debugWriter = null; debugLogPath = null; }
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}
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var fullText = new StringBuilder();
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var thinkingText = new StringBuilder();
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// Tool-Call Akkumulatoren: id → (name, arguments)
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@@ -409,6 +444,19 @@ public class OpenAiService
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if (!line.StartsWith("data:")) continue;
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var data = line[5..].Trim();
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// Diagnose-Log: rohe data-Zeile als JSONL-Record
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if (debugWriter != null)
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{
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try
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{
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var rec = JsonSerializer.Serialize(new { t = DateTime.UtcNow.ToString("o"), raw = data });
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await debugWriter.WriteLineAsync(rec);
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debugLineCount++;
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}
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catch { /* Debug-Log darf den Stream nicht killen */ }
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}
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if (data == "[DONE]") break;
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JsonElement parsed;
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@@ -425,6 +473,7 @@ public class OpenAiService
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if (choice.TryGetProperty("finish_reason", out var finishProp) && finishProp.ValueKind != JsonValueKind.Null)
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{
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var fr = (finishProp.GetString() ?? "").ToLowerInvariant();
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lastFinishReason = fr;
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if (fr == "tool_calls" || fr == "function_call") stopReason = "tool_use";
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else if (fr == "stop") stopReason = "end_turn";
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else if (fr == "length") { stopReason = "max_tokens"; gotLengthFinish = true; }
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@@ -655,6 +704,41 @@ public class OpenAiService
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catch (InvalidOperationException) { /* Unerwartetes JSON-Format von Provider – Zeile überspringen */ }
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}
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// Diagnose-Log: Summary am Ende des Streams
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if (debugWriter != null)
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{
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try
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{
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var toolCallSummaries = new List<object>();
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foreach (var (idx, (tcId, tcName, tcArgs, _)) in toolCallAccumulators)
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{
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toolCallSummaries.Add(new { idx, id = tcId, name = tcName, argsLen = tcArgs.Length });
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}
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var summary = JsonSerializer.Serialize(new
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{
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summary = true,
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chainId,
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iteration,
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promptTokens = usage.InputTokens,
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completionTokens = usage.OutputTokens,
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finishReason = lastFinishReason,
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stopReason,
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toolCalls = toolCallSummaries,
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toolCallCount = toolCallAccumulators.Count,
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textLen = fullText.Length,
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thinkingLen = thinkingText.Length,
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sseLines = debugLineCount,
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durationMs = sw.ElapsedMilliseconds,
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ended = DateTime.UtcNow.ToString("o")
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});
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await debugWriter.WriteLineAsync(summary);
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await debugWriter.FlushAsync();
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debugWriter.Dispose();
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}
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catch { try { debugWriter?.Dispose(); } catch { } }
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debugWriter = null;
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}
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// Inline-Think-Buffer-Rest flushen (falls Stream mit partiellem Tag-Fragment endete)
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if (inlineThinkBuf.Length > 0)
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{
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@@ -769,17 +853,62 @@ public class OpenAiService
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});
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}
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// Thinking als <think>...</think>-Prefix dem finalText voranstellen, damit
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// das Modell in nachfolgenden Iterationen seine eigene Chain-of-Thought sieht
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// (essential für MiniMax-M2, DeepSeek-R1, QwQ, Kimi K2 etc. – sonst bricht
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// Tool-Calling-Reliability ein, siehe MiniMax-Doku zu Interleaved Thinking).
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var historyContent = string.IsNullOrEmpty(finalText) ? "" : finalText;
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if (!string.IsNullOrEmpty(finalThinking))
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historyContent = $"<think>\n{finalThinking}\n</think>\n\n{historyContent}";
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apiMessages.Add(new
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{
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role = "assistant",
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content = string.IsNullOrEmpty(finalText) ? "" : finalText,
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content = historyContent,
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tool_calls = toolCallsForHistory
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});
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// Tool-Results sammeln
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var toolResults = new List<object>();
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bool awaitingChoice = false;
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foreach (var (_, (tcId, tcName, tcArgs, _)) in toolCallAccumulators)
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{
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// ask_user_choice: NICHT ausführen, sondern als SSE-Event an Client senden.
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// Analog zum Anthropic-Pfad (AnthropicService.Streaming.cs:546-576).
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// tool_result kommt asynchron vom Client via ChatEndpoint (ChoiceToolCallId+ChoiceResult).
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if (tcName == ToolService.AskUserChoiceToolName)
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{
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JsonElement choiceInput;
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try { choiceInput = JsonSerializer.Deserialize<JsonElement>(tcArgs.ToString()); }
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catch { choiceInput = JsonSerializer.Deserialize<JsonElement>("{}"); }
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var question = choiceInput.TryGetProperty("question", out var qProp) ? qProp.GetString() ?? "" : "";
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var choices = new List<string>();
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if (choiceInput.TryGetProperty("choices", out var cProp))
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{
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if (cProp.ValueKind == JsonValueKind.Array)
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{
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foreach (var ch in cProp.EnumerateArray())
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choices.Add(ch.GetString() ?? "");
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}
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else if (cProp.ValueKind == JsonValueKind.String)
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{
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// Fallback: Modell hat einen einzelnen String statt Array gesendet
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choices.Add(cProp.GetString() ?? "");
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}
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}
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await SseHelper.TryWriteSse(response, "user_choice", new
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{
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toolCallId = tcId,
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question,
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choices
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}, sseCt);
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awaitingChoice = true;
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continue; // Kein Execute, kein tool_result Save
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}
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// Tool-Start SSE
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await SseHelper.TryWriteSse(response, "tool_start", new { name = tcName, id = tcId }, sseCt);
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@@ -818,6 +947,24 @@ public class OpenAiService
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});
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}
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// Wenn ask_user_choice aufgerufen wurde → finalize mit awaiting_user_choice und return.
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// Die Choice-Antwort kommt async vom Client und triggert eine neue Chain.
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if (awaitingChoice)
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{
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await FinalizeChain(chain, usage, iteration, "awaiting_user_choice", sw);
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await SseHelper.TryWriteSse(response, "done", new
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{
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model = modelString,
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inputTokens = usage.InputTokens,
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outputTokens = usage.OutputTokens,
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iterations = iteration,
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chainId,
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durationMs = sw.ElapsedMilliseconds,
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stopReason = "awaiting_user_choice"
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}, sseCt);
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return;
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}
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// Tool-Results in History einfügen
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foreach (var tr in toolResults)
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apiMessages.Add(tr);
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@@ -945,11 +1092,13 @@ public class OpenAiService
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var finishReason = choice.TryGetProperty("finish_reason", out var frProp) ? frProp.GetString() ?? "" : "";
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// Reasoning/Thinking extrahieren (Nvidia Thinking-Modelle)
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string iterationThinking = null;
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if (message.TryGetProperty("reasoning", out var reasoningProp) && reasoningProp.ValueKind == JsonValueKind.String)
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{
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var reasoning = reasoningProp.GetString() ?? "";
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if (!string.IsNullOrEmpty(reasoning))
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{
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iterationThinking = reasoning;
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await _db.SaveMessage(new MessageRecord
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{
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ChainId = ctx.ChainId, Iteration = iterations,
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@@ -982,12 +1131,18 @@ public class OpenAiService
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break;
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}
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// Assistant-Message mit tool_calls in History
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// Assistant-Message mit tool_calls in History.
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// Thinking als <think>...</think>-Prefix dem content voranstellen, damit das Modell
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// in nachfolgenden Iterationen seine eigene Chain-of-Thought sieht.
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var assistantMsg = JsonSerializer.Deserialize<JsonElement>(message.GetRawText());
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var iterContent = message.TryGetProperty("content", out var c) && c.ValueKind == JsonValueKind.String ? c.GetString() ?? "" : "";
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if (!string.IsNullOrEmpty(iterationThinking))
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iterContent = $"<think>\n{iterationThinking}\n</think>\n\n{iterContent}";
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apiMessages.Add(new
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{
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role = "assistant",
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content = message.TryGetProperty("content", out var c) && c.ValueKind == JsonValueKind.String ? c.GetString() ?? "" : "",
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content = iterContent,
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tool_calls = JsonSerializer.Deserialize<List<object>>(toolCallsProp.GetRawText())
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});
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@@ -1073,6 +1228,7 @@ public class OpenAiService
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if (contentProp.ValueKind == JsonValueKind.Array)
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{
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var textParts = new StringBuilder();
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var thinkingParts = new StringBuilder();
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var toolCalls = new List<object>();
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var toolResults = new List<object>();
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@@ -1081,7 +1237,15 @@ public class OpenAiService
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if (!block.TryGetProperty("type", out var typeProp)) continue;
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var blockType = typeProp.GetString() ?? "";
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if (blockType == "text" && block.TryGetProperty("text", out var textProp))
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if (blockType == "thinking" && block.TryGetProperty("thinking", out var thinkingProp))
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{
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// Thinking-Inhalt sammeln; wird unten als <think>...</think>-Prefix dem
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// Assistant-Text vorangestellt. So bekommen Thinking-Modelle (MiniMax-M2,
|
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// DeepSeek-R1, QwQ, Kimi K2 etc.) ihre eigene Chain-of-Thought zurück, was
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// laut Provider-Docs entscheidend für Tool-Calling-Reliability ist.
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thinkingParts.Append(thinkingProp.GetString());
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}
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else if (blockType == "text" && block.TryGetProperty("text", out var textProp))
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{
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textParts.Append(textProp.GetString());
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}
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@@ -1122,14 +1286,25 @@ public class OpenAiService
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}
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}
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// Thinking als <think>...</think>-Prefix dem Text voranstellen (MiniMax-Konvention,
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// wird auch von DeepSeek-R1, QwQ, Kimi K2 etc. verstanden).
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var thinkingStr = thinkingParts.ToString();
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string PrependThinking(string baseText)
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{
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if (string.IsNullOrEmpty(thinkingStr)) return baseText;
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var prefix = $"<think>\n{thinkingStr}\n</think>\n\n";
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return string.IsNullOrEmpty(baseText) ? prefix : prefix + baseText;
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}
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// Assistant-Message mit tool_calls
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if (toolCalls.Count > 0)
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{
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var text = textParts.ToString().Trim();
|
||||
var combinedTc = PrependThinking(text);
|
||||
return new
|
||||
{
|
||||
role = "assistant",
|
||||
content = string.IsNullOrEmpty(text) ? "" : text,
|
||||
content = string.IsNullOrEmpty(combinedTc) ? "" : combinedTc,
|
||||
tool_calls = toolCalls
|
||||
};
|
||||
}
|
||||
@@ -1138,7 +1313,7 @@ public class OpenAiService
|
||||
if (toolResults.Count > 0)
|
||||
return toolResults; // List<object> wird im Aufrufer per OfType<List<object>> erkannt
|
||||
|
||||
var combined = textParts.ToString().Trim();
|
||||
var combined = PrependThinking(textParts.ToString().Trim());
|
||||
if (string.IsNullOrEmpty(combined)) return null;
|
||||
return new { role, content = combined };
|
||||
}
|
||||
|
||||
@@ -184,7 +184,9 @@ public class TelegramService
|
||||
|
||||
try
|
||||
{
|
||||
var history = await _chatService.BuildHistoryFromDb(session.SessionId, promptBlocks: ctx.PromptBlocks);
|
||||
// includeThinking=true für OpenAI-kompatible Provider → <think>...</think>-Prefix
|
||||
// im Assistant-Text (essential für MiniMax/DeepSeek/QwQ Tool-Calling-Reliability).
|
||||
var history = await _chatService.BuildHistoryFromDb(session.SessionId, promptBlocks: ctx.PromptBlocks, includeThinking: !string.IsNullOrEmpty(ctx.Provider));
|
||||
history.Add(new Dictionary<string, object>
|
||||
{
|
||||
["role"] = "user",
|
||||
|
||||
@@ -814,7 +814,9 @@ public class ToolService
|
||||
|
||||
// History aufbauen – User-Message NICHT in DB speichern (wie Cronjob)
|
||||
// Stattdessen als kontextualisierte Nachricht in die History injizieren
|
||||
var history = await ctx.ChatService.BuildHistoryFromDb(targetSessionId, promptBlocks: targetCtx.PromptBlocks);
|
||||
// includeThinking=true für OpenAI-kompatible Provider → <think>...</think>-Prefix
|
||||
// im Assistant-Text. Anthropic ignoriert das (lehnt Blöcke ohne Signatur ab).
|
||||
var history = await ctx.ChatService.BuildHistoryFromDb(targetSessionId, promptBlocks: targetCtx.PromptBlocks, includeThinking: !string.IsNullOrEmpty(targetCtx.Provider));
|
||||
var senderAgent = ctx.AgentId != null ? await ctx.Db.GetAgent(ctx.AgentId) : null;
|
||||
var senderName = senderAgent?.Name ?? ctx.AgentId ?? "Unbekannter Agent";
|
||||
var senderInfo = $"[Nachricht von Agent \"{senderName}\"]: {message}";
|
||||
|
||||
Reference in new issue
Block a user