Let the user inject a message into a running chain instead of only being
able to abort it. While a chain streams, typing + Enter sends the text to
a new /api/chat/steer endpoint; it is drained at the next iteration
boundary, wrapped with a hint so the model actively classifies it
("complements the task -> keep working" vs. "changes course -> adjust"),
and stored as a Type="steer" user message so it survives reload.
Shared infrastructure (provider-agnostic):
- SteeringQueue: out-of-band queue keyed by sessionId, mirrored from
StreamingTracker (Enqueue/Drain/Clear).
- Program.cs registers it as a singleton and passes it to AnthropicService.
- ChatEndpoint: POST /api/chat/steer enqueues only while IsStreaming,
Clear() in the finally.
- ChatService.BuildHistoryFromDb groups Type="steer" so no two
consecutive user turns are produced on re-chat.
- Frontend api.js/chat.js/bubbles.js/history.js + chat.css render the
optimistic steer bubble and the steer_injected SSE event; Enter during
a stream sends a steer instead of being blocked.
Anthropic API path:
- Drain point B (tool boundary, merged into the tool_result user turn)
and C (turn end -> inject + continue instead of finalize).
Claude CLI path (kill-and-restart):
- The agentic loop runs inside the claude child, so true mid-turn inject
is impossible. On a pending steer the child is killed at the next tool
boundary, progress is rebuilt from the DB as a <work_in_progress>
transcript, and the CLI is restarted with the steer appended.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
337 lines
16 KiB
C#
337 lines
16 KiB
C#
using System;
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using System.Collections.Generic;
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using System.Linq;
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using System.Text.Json;
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using System.Threading;
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using System.Threading.Tasks;
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using Gott.Extensions;
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using Gott.Models;
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using Gott.Services;
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using Microsoft.AspNetCore.Builder;
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using Microsoft.AspNetCore.Http;
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using Microsoft.AspNetCore.Routing;
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namespace Gott.Endpoints;
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public static class ChatEndpoint
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{
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public static void MapChatEndpoint(this IEndpointRouteBuilder app)
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{
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app.MapPost("/api/chat", HandleChat);
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app.MapPost("/api/chat/stop", HandleStop);
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app.MapPost("/api/chat/steer", HandleSteer);
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}
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private static async Task HandleChat(HttpRequest req, HttpResponse res, ServerSettingsService settings, ChatService chatService, DatabaseService db, StreamingTracker streamingTracker, SteeringQueue steeringQueue, AnthropicService anthropic, OpenAiService openAi, RemoteConnectionManager remoteMgr, EmbeddingBackgroundService embeddingBg, CancellationToken cancellationToken)
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{
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var body = await JsonSerializer.DeserializeAsync<ChatRequest>(req.Body);
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if (body == null)
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{
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res.StatusCode = 400;
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await res.WriteAsJsonAsync(new { error = "body required" });
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return;
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}
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var sessionId = body.SessionId;
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if (string.IsNullOrEmpty(sessionId))
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{
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res.StatusCode = 400;
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await res.WriteAsJsonAsync(new { error = "sessionId required" });
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return;
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}
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// Prüfe ob dies eine Choice-Antwort ist (ask_user_choice response)
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var isChoiceResponse = !string.IsNullOrEmpty(body.ChoiceToolCallId) && !string.IsNullOrEmpty(body.ChoiceResult);
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if (!isChoiceResponse && body.Content.ValueKind == JsonValueKind.Undefined)
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{
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res.StatusCode = 400;
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await res.WriteAsJsonAsync(new { error = "content required" });
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return;
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}
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var userId = req.HttpContext.GetUserId();
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var maxIterations = settings.GetInt("MaxIterations", 100);
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var remoteConn = remoteMgr.GetBySessionId(sessionId);
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var hasRemote = remoteConn != null;
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var ctx = await chatService.PrepareContext(sessionId, userId, maxIterations, planMode: body.PlanMode, hasRemoteConnection: hasRemote, remoteOs: remoteConn?.OsVersion);
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if (ctx == null)
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{
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res.StatusCode = 400;
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await res.WriteAsJsonAsync(new { error = "Session/Agent nicht gefunden oder kein Agent ausgewählt" });
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return;
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}
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// API-Key des Users für diesen Agent auflösen (kann null sein)
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var userApiKey = await db.GetAgentApiKeyRecord(userId, ctx.AgentId);
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if (isChoiceResponse)
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{
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// Choice-Antwort: tool_result in die VORHERIGE Chain speichern (wo der tool_use liegt)
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// Damit BuildHistoryFromDb die tool_use + tool_result korrekt zusammenbauen kann.
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var previousChainId = await chatService.FindChainWithToolCall(sessionId, body.ChoiceToolCallId);
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if (previousChainId != null)
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{
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await db.SaveMessage(new MessageRecord
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{
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ChainId = previousChainId,
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Iteration = 999, // Hohe Iteration damit es nach dem tool_use kommt
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Role = "user",
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Type = "tool_result",
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ToolCallId = body.ChoiceToolCallId,
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Content = body.ChoiceResult
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});
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}
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else
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{
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// Fallback: In aktuelle Chain speichern
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await db.SaveMessage(new MessageRecord
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{
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ChainId = ctx.ChainId,
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Iteration = 0,
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Role = "user",
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Type = "tool_result",
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ToolCallId = body.ChoiceToolCallId,
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Content = body.ChoiceResult
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});
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}
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}
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else
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{
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// Normale User-Message aufbereiten und speichern
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var userMessage = new ChatMessage { Role = "user", Content = body.Content };
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var textContent = userMessage.GetTextContent();
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var attachmentBlocks = userMessage.GetAttachmentBlocks();
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var attachmentRecords = attachmentBlocks.Select(b => new AttachmentRecord
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{
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Type = b.Type,
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MediaType = b.MediaType,
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FileName = b.FileName,
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Data = b.Data
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}).ToList();
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var userMsgId = await db.SaveMessageWithAttachments(new MessageRecord
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{
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ChainId = ctx.ChainId,
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Iteration = 0,
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Role = "user",
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Type = "text",
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Content = textContent
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}, attachmentRecords);
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embeddingBg?.Enqueue(userMsgId, ctx.ChainId, ctx.SessionId, ctx.AgentId, "user", textContent ?? "");
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}
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res.Headers["Content-Type"] = "text/event-stream";
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res.Headers["Cache-Control"] = "no-cache";
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res.Headers["Connection"] = "keep-alive";
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// Response-Buffering deaktivieren – wichtig für SSE unter Windows
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var bufferingFeature = res.HttpContext.Features.Get<Microsoft.AspNetCore.Http.Features.IHttpResponseBodyFeature>();
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bufferingFeature?.DisableBuffering();
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// Kestrel MinResponseDataRate deaktivieren für diesen SSE-Stream.
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// Ohne dies killt Kestrel die Verbindung wenn bei langen Tool-Ausführungen
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// keine Daten fließen (Default: 240 bytes/s, 5s Grace → "client_disconnected").
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var minRateFeature = res.HttpContext.Features.Get<Microsoft.AspNetCore.Server.Kestrel.Core.Features.IHttpMinResponseDataRateFeature>();
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if (minRateFeature != null)
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minRateFeature.MinDataRate = null;
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// ── Preparer-Agent Phase (vor dem Worker) ──
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if (ctx.Preparer != null && !isChoiceResponse)
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{
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var preparerApiToken = userApiKey?.ApiKey;
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// Kein Key und kein CLI → Preparer überspringen (main agent wird auch CLI nutzen oder fehlermelden)
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bool skipPreparer = string.IsNullOrEmpty(ctx.Preparer.Provider)
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&& string.IsNullOrEmpty(preparerApiToken)
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&& !anthropic.IsCliAvailable;
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if (!skipPreparer)
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{
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// Preparer bekommt History MIT seinen eigenen vorherigen Messages (Tag "preparer"),
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// damit er den Kontext seiner Rückfragen kennt
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var preparerHistory = await chatService.BuildHistoryFromDb(sessionId, includeTag: "preparer", promptBlocks: ctx.PromptBlocks);
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var preparerResult = await anthropic.RunPreparer(
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res, ctx.Preparer, preparerHistory, ctx.ChainId, ctx.Workspace, sessionId, preparerApiToken, cancellationToken);
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if (!preparerResult.ShouldForward)
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{
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// Preparer hat eine Rückfrage → Antwort als Text streamen, Flow beenden
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// Preparer-Antwort wird schon in RunAgentChat in DB gespeichert
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await SseHelper.WriteSseEvent(res, "done", new
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{
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chainId = ctx.ChainId,
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stopReason = "preparer_query",
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planMode = ctx.PlanMode
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}, cancellationToken);
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return;
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}
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// Preparer ist zufrieden → aufbereiteten Prompt in DB speichern
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if (!string.IsNullOrWhiteSpace(preparerResult.ForwardedPrompt))
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{
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await db.SaveMessage(new MessageRecord
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{
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ChainId = ctx.ChainId,
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Iteration = 0,
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Role = "user",
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Type = "text",
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Content = $"[Vorbereitet von {ctx.Preparer.Agent?.Name ?? "Vorbereiter-Agent"}]:\n{preparerResult.ForwardedPrompt}"
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});
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}
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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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// 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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// Drei separate CancellationTokens:
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// - workCt: Nur Stop-Button (graceful) → für Anthropic API-Calls, Tool-Ausführungen, DB-Writes
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// Agent-Arbeit läuft bei Client-Disconnect weiter (Client pollt ja)
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// - hardCt: Hard-Stop (Doppel-Klick) → sofortiger Abbruch aus while-Loop
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// - sseCt: Stop-Button + Client-Disconnect → für SSE-Writes an den Browser
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// Bei Client-Disconnect werden SSE-Writes zu stillen No-Ops
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var tokens = streamingTracker.Start(sessionId, ctx.ChainId);
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var workCt = tokens.StopToken;
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var hardCt = tokens.HardToken;
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using var sseLinkCts = CancellationTokenSource.CreateLinkedTokenSource(cancellationToken, tokens.StopToken);
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var sseCt = sseLinkCts.Token;
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// SSE-Heartbeat: Alle 15s ein Kommentar senden, damit die Verbindung
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// bei langen Tool-Ausführungen nicht von Browser/Netzwerk getrennt wird.
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var heartbeatTask = Task.Run(async () =>
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{
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try
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{
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while (!sseCt.IsCancellationRequested)
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{
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await Task.Delay(15000, sseCt);
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await res.WriteAsync(": heartbeat\n\n", sseCt);
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await res.Body.FlushAsync(sseCt);
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}
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}
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catch (OperationCanceledException) { }
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catch { }
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}, sseCt);
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try
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{
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if (!string.IsNullOrEmpty(ctx.Provider))
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{
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// OpenAI-kompatibler Provider – Key des Users für diesen Agent verwenden
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string openAiKeyOverride = userApiKey?.ApiKey;
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// OpenAI-Provider braucht zwingend einen Key
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if (ctx.Provider == "openai" && string.IsNullOrEmpty(openAiKeyOverride))
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{
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await SseHelper.TryWriteSse(res, "error", new { error = "Kein API-Key für diesen Agent zugewiesen. Bitte einen OpenAI-Key zuweisen." }, sseCt);
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await SseHelper.TryWriteSse(res, "done", new { chainId = ctx.ChainId }, sseCt);
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return;
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}
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await openAi.StreamChat(res, ctx.ModelId, ctx.SystemPromptText, messages, ctx.ChainId, workspace: ctx.Workspace, sessionId: sessionId, agentId: ctx.AgentId, maxIterations: ctx.MaxIterations, apiKeyOverride: openAiKeyOverride, useAutoContext: ctx.Agent?.UseAutoContext ?? true, workCt: workCt, sseCt: sseCt);
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}
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else
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{
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// Standard: Anthropic
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var anthropicToken = userApiKey?.ApiKey;
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// Kein API-Key → Claude CLI als Fallback verwenden
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if (string.IsNullOrEmpty(anthropicToken))
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{
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// CLI-Berechtigung prüfen
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var chatUser = await db.GetUser(userId);
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if (chatUser != null && !chatUser.CanUseCli && !chatUser.IsAdmin)
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{
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await SseHelper.TryWriteSse(res, "error", new { error = "Kein API-Key zugewiesen und keine CLI-Berechtigung. Bitte einen Key zuweisen." }, sseCt);
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await SseHelper.TryWriteSse(res, "done", new { chainId = ctx.ChainId }, sseCt);
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return;
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}
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if (anthropic.IsCliAvailable)
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{
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await anthropic.StreamChatViaCli(res, ctx.ModelId, ctx.SystemPrompt, messages, ctx.ChainId, workspace: ctx.Workspace, allowUserChoice: ctx.Agent?.AllowUserChoice ?? true, planMode: body.PlanMode, webSearch: !string.IsNullOrEmpty(ctx.WebSearchVersion), sessionId: sessionId, agentId: ctx.AgentId, remoteMgr: remoteMgr, unityMcpUrl: ctx.Session?.UnityMcpUrl, unityMcpToken: ctx.Session?.UnityMcpToken, useAutoContext: ctx.Agent?.UseAutoContext ?? true, effort: ctx.Effort, workCt: workCt, sseCt: sseCt);
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}
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else
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{
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await SseHelper.TryWriteSse(res, "error", new { error = "Kein API-Key zugewiesen und Claude CLI nicht verfügbar. Bitte einen Key zuweisen oder 'claude login' ausführen." }, sseCt);
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await SseHelper.TryWriteSse(res, "done", new { chainId = ctx.ChainId }, sseCt);
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}
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return;
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}
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await anthropic.StreamChat(res, ctx.ModelId, ctx.SystemPrompt, messages, ctx.ChainId, ctx.Workspace, apiToken: anthropicToken, sessionId: sessionId, agentId: ctx.AgentId, userId: userId, useMemory: ctx.UseMemory, webSearchVersion: ctx.WebSearchVersion, maxIterations: ctx.MaxIterations, toolChoice: effectiveToolChoice, review: ctx.Review, finalizer: ctx.Finalizer, allowUserChoice: ctx.Agent?.AllowUserChoice ?? true, planMode: ctx.PlanMode, useAutoContext: ctx.Agent?.UseAutoContext ?? true, useGitHubSearch: ctx.Agent?.UseGitHubSearch ?? false, useSerperSearch: ctx.Agent?.UseSerperSearch ?? false, effort: ctx.Effort, workCt: workCt, hardCt: hardCt, sseCt: sseCt, remoteMgr: remoteMgr);
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}
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}
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finally
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{
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streamingTracker.Stop(sessionId);
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// Nach Stop ist IsStreaming(sessionId) false → /api/chat/steer enqueued nichts mehr.
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// Etwaige nicht gedrainte Einwürfe verwerfen (kein Leak in die nächste Chain).
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steeringQueue.Clear(sessionId);
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// Heartbeat-Task beenden (sseLinkCts wird disposed → Token cancelled)
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}
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}
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private static async Task HandleStop(HttpRequest req, HttpResponse res, StreamingTracker streamingTracker)
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{
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var body = await JsonSerializer.DeserializeAsync<JsonElement>(req.Body);
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var sessionId = body.TryGetProperty("sessionId", out var sid) ? sid.GetString() : null;
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if (string.IsNullOrEmpty(sessionId))
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{
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res.StatusCode = 400;
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await res.WriteAsJsonAsync(new { error = "sessionId required" });
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return;
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}
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// Erster Klick = "graceful" (laufende Iteration fertig), zweiter = "hard" (sofort)
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var stopLevel = streamingTracker.Cancel(sessionId);
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await res.WriteAsJsonAsync(new { stopped = stopLevel != null, level = stopLevel ?? "none" });
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}
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/// <summary>
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/// "Steering": Reiht eine Nachricht out-of-band in die laufende Chain ein.
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/// Sie wird an der nächsten Iterations-Grenze als User-Message injiziert.
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/// Anthropic-API-Pfad: Injektion zwischen den messages.create-Calls.
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/// Claude-CLI-Pfad: Kill-and-Restart am nächsten Tool-Boundary (der Agentic-Loop
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/// läuft im claude-Child, daher kein echtes Mid-Turn-Inject möglich).
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/// </summary>
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private static async Task HandleSteer(HttpRequest req, HttpResponse res, StreamingTracker streamingTracker, SteeringQueue steeringQueue)
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{
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var body = await JsonSerializer.DeserializeAsync<JsonElement>(req.Body);
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var sessionId = body.TryGetProperty("sessionId", out var sid) ? sid.GetString() : null;
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var text = body.TryGetProperty("text", out var txt) ? txt.GetString() : null;
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if (string.IsNullOrEmpty(sessionId) || string.IsNullOrWhiteSpace(text))
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{
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res.StatusCode = 400;
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await res.WriteAsJsonAsync(new { error = "sessionId and text required" });
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return;
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}
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// Nur einreihen wenn tatsächlich gerade eine Chain läuft – sonst würde der
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// Einwurf nie gedraint (kein laufender Loop) und bis zur nächsten Chain liegen bleiben.
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if (!streamingTracker.IsStreaming(sessionId))
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{
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await res.WriteAsJsonAsync(new { injected = false, reason = "not_streaming" });
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return;
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}
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steeringQueue.Enqueue(sessionId, text.Trim());
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await res.WriteAsJsonAsync(new { injected = true });
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}
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}
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