Files
gott/Endpoints/ChatEndpoint.cs
T
MelekiandClaude Opus 4.8 f2fd493e5f Add live steering injection into running chains
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>
2026-06-02 06:49:58 +02:00

337 lines
16 KiB
C#
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using System;
using System.Collections.Generic;
using System.Linq;
using System.Text.Json;
using System.Threading;
using System.Threading.Tasks;
using Gott.Extensions;
using Gott.Models;
using Gott.Services;
using Microsoft.AspNetCore.Builder;
using Microsoft.AspNetCore.Http;
using Microsoft.AspNetCore.Routing;
namespace Gott.Endpoints;
public static class ChatEndpoint
{
public static void MapChatEndpoint(this IEndpointRouteBuilder app)
{
app.MapPost("/api/chat", HandleChat);
app.MapPost("/api/chat/stop", HandleStop);
app.MapPost("/api/chat/steer", HandleSteer);
}
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)
{
var body = await JsonSerializer.DeserializeAsync<ChatRequest>(req.Body);
if (body == null)
{
res.StatusCode = 400;
await res.WriteAsJsonAsync(new { error = "body required" });
return;
}
var sessionId = body.SessionId;
if (string.IsNullOrEmpty(sessionId))
{
res.StatusCode = 400;
await res.WriteAsJsonAsync(new { error = "sessionId required" });
return;
}
// Prüfe ob dies eine Choice-Antwort ist (ask_user_choice response)
var isChoiceResponse = !string.IsNullOrEmpty(body.ChoiceToolCallId) && !string.IsNullOrEmpty(body.ChoiceResult);
if (!isChoiceResponse && body.Content.ValueKind == JsonValueKind.Undefined)
{
res.StatusCode = 400;
await res.WriteAsJsonAsync(new { error = "content required" });
return;
}
var userId = req.HttpContext.GetUserId();
var maxIterations = settings.GetInt("MaxIterations", 100);
var remoteConn = remoteMgr.GetBySessionId(sessionId);
var hasRemote = remoteConn != null;
var ctx = await chatService.PrepareContext(sessionId, userId, maxIterations, planMode: body.PlanMode, hasRemoteConnection: hasRemote, remoteOs: remoteConn?.OsVersion);
if (ctx == null)
{
res.StatusCode = 400;
await res.WriteAsJsonAsync(new { error = "Session/Agent nicht gefunden oder kein Agent ausgewählt" });
return;
}
// API-Key des Users für diesen Agent auflösen (kann null sein)
var userApiKey = await db.GetAgentApiKeyRecord(userId, ctx.AgentId);
if (isChoiceResponse)
{
// Choice-Antwort: tool_result in die VORHERIGE Chain speichern (wo der tool_use liegt)
// Damit BuildHistoryFromDb die tool_use + tool_result korrekt zusammenbauen kann.
var previousChainId = await chatService.FindChainWithToolCall(sessionId, body.ChoiceToolCallId);
if (previousChainId != null)
{
await db.SaveMessage(new MessageRecord
{
ChainId = previousChainId,
Iteration = 999, // Hohe Iteration damit es nach dem tool_use kommt
Role = "user",
Type = "tool_result",
ToolCallId = body.ChoiceToolCallId,
Content = body.ChoiceResult
});
}
else
{
// Fallback: In aktuelle Chain speichern
await db.SaveMessage(new MessageRecord
{
ChainId = ctx.ChainId,
Iteration = 0,
Role = "user",
Type = "tool_result",
ToolCallId = body.ChoiceToolCallId,
Content = body.ChoiceResult
});
}
}
else
{
// Normale User-Message aufbereiten und speichern
var userMessage = new ChatMessage { Role = "user", Content = body.Content };
var textContent = userMessage.GetTextContent();
var attachmentBlocks = userMessage.GetAttachmentBlocks();
var attachmentRecords = attachmentBlocks.Select(b => new AttachmentRecord
{
Type = b.Type,
MediaType = b.MediaType,
FileName = b.FileName,
Data = b.Data
}).ToList();
var userMsgId = await db.SaveMessageWithAttachments(new MessageRecord
{
ChainId = ctx.ChainId,
Iteration = 0,
Role = "user",
Type = "text",
Content = textContent
}, attachmentRecords);
embeddingBg?.Enqueue(userMsgId, ctx.ChainId, ctx.SessionId, ctx.AgentId, "user", textContent ?? "");
}
res.Headers["Content-Type"] = "text/event-stream";
res.Headers["Cache-Control"] = "no-cache";
res.Headers["Connection"] = "keep-alive";
// Response-Buffering deaktivieren – wichtig für SSE unter Windows
var bufferingFeature = res.HttpContext.Features.Get<Microsoft.AspNetCore.Http.Features.IHttpResponseBodyFeature>();
bufferingFeature?.DisableBuffering();
// Kestrel MinResponseDataRate deaktivieren für diesen SSE-Stream.
// Ohne dies killt Kestrel die Verbindung wenn bei langen Tool-Ausführungen
// keine Daten fließen (Default: 240 bytes/s, 5s Grace → "client_disconnected").
var minRateFeature = res.HttpContext.Features.Get<Microsoft.AspNetCore.Server.Kestrel.Core.Features.IHttpMinResponseDataRateFeature>();
if (minRateFeature != null)
minRateFeature.MinDataRate = null;
// ── Preparer-Agent Phase (vor dem Worker) ──
if (ctx.Preparer != null && !isChoiceResponse)
{
var preparerApiToken = userApiKey?.ApiKey;
// Kein Key und kein CLI → Preparer überspringen (main agent wird auch CLI nutzen oder fehlermelden)
bool skipPreparer = string.IsNullOrEmpty(ctx.Preparer.Provider)
&& string.IsNullOrEmpty(preparerApiToken)
&& !anthropic.IsCliAvailable;
if (!skipPreparer)
{
// Preparer bekommt History MIT seinen eigenen vorherigen Messages (Tag "preparer"),
// damit er den Kontext seiner Rückfragen kennt
var preparerHistory = await chatService.BuildHistoryFromDb(sessionId, includeTag: "preparer", promptBlocks: ctx.PromptBlocks);
var preparerResult = await anthropic.RunPreparer(
res, ctx.Preparer, preparerHistory, ctx.ChainId, ctx.Workspace, sessionId, preparerApiToken, cancellationToken);
if (!preparerResult.ShouldForward)
{
// Preparer hat eine Rückfrage → Antwort als Text streamen, Flow beenden
// Preparer-Antwort wird schon in RunAgentChat in DB gespeichert
await SseHelper.WriteSseEvent(res, "done", new
{
chainId = ctx.ChainId,
stopReason = "preparer_query",
planMode = ctx.PlanMode
}, cancellationToken);
return;
}
// Preparer ist zufrieden → aufbereiteten Prompt in DB speichern
if (!string.IsNullOrWhiteSpace(preparerResult.ForwardedPrompt))
{
await db.SaveMessage(new MessageRecord
{
ChainId = ctx.ChainId,
Iteration = 0,
Role = "user",
Type = "text",
Content = $"[Vorbereitet von {ctx.Preparer.Agent?.Name ?? "Vorbereiter-Agent"}]:\n{preparerResult.ForwardedPrompt}"
});
}
} // !skipPreparer
}
// History für den Session-Agent: OHNE Sub-Agent-Messages (saubere History).
// includeThinking=true für OpenAI-kompatible Provider → Thinking wird als
// <think>...</think>-Prefix dem Assistant-Text vorangestellt (laut MiniMax-Docs essentiell
// für Tool-Calling-Reliability / Interleaved Thinking). Anthropic-Pfad braucht das nicht,
// weil dort thinking-Blöcke nur mit Signatur akzeptiert werden (die wir nicht persistieren).
var includeThinkingForProvider = !string.IsNullOrEmpty(ctx.Provider);
var messages = await chatService.BuildHistoryFromDb(sessionId, promptBlocks: ctx.PromptBlocks, includeThinking: includeThinkingForProvider);
// Bei Choice-Response: toolChoice auf "auto" setzen, damit Claude frei antworten kann
var effectiveToolChoice = isChoiceResponse ? "auto" : ctx.ToolChoice;
// Drei separate CancellationTokens:
// - workCt: Nur Stop-Button (graceful) → für Anthropic API-Calls, Tool-Ausführungen, DB-Writes
// Agent-Arbeit läuft bei Client-Disconnect weiter (Client pollt ja)
// - hardCt: Hard-Stop (Doppel-Klick) → sofortiger Abbruch aus while-Loop
// - sseCt: Stop-Button + Client-Disconnect → für SSE-Writes an den Browser
// Bei Client-Disconnect werden SSE-Writes zu stillen No-Ops
var tokens = streamingTracker.Start(sessionId, ctx.ChainId);
var workCt = tokens.StopToken;
var hardCt = tokens.HardToken;
using var sseLinkCts = CancellationTokenSource.CreateLinkedTokenSource(cancellationToken, tokens.StopToken);
var sseCt = sseLinkCts.Token;
// SSE-Heartbeat: Alle 15s ein Kommentar senden, damit die Verbindung
// bei langen Tool-Ausführungen nicht von Browser/Netzwerk getrennt wird.
var heartbeatTask = Task.Run(async () =>
{
try
{
while (!sseCt.IsCancellationRequested)
{
await Task.Delay(15000, sseCt);
await res.WriteAsync(": heartbeat\n\n", sseCt);
await res.Body.FlushAsync(sseCt);
}
}
catch (OperationCanceledException) { }
catch { }
}, sseCt);
try
{
if (!string.IsNullOrEmpty(ctx.Provider))
{
// OpenAI-kompatibler Provider – Key des Users für diesen Agent verwenden
string openAiKeyOverride = userApiKey?.ApiKey;
// OpenAI-Provider braucht zwingend einen Key
if (ctx.Provider == "openai" && string.IsNullOrEmpty(openAiKeyOverride))
{
await SseHelper.TryWriteSse(res, "error", new { error = "Kein API-Key für diesen Agent zugewiesen. Bitte einen OpenAI-Key zuweisen." }, sseCt);
await SseHelper.TryWriteSse(res, "done", new { chainId = ctx.ChainId }, sseCt);
return;
}
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);
}
else
{
// Standard: Anthropic
var anthropicToken = userApiKey?.ApiKey;
// Kein API-Key → Claude CLI als Fallback verwenden
if (string.IsNullOrEmpty(anthropicToken))
{
// CLI-Berechtigung prüfen
var chatUser = await db.GetUser(userId);
if (chatUser != null && !chatUser.CanUseCli && !chatUser.IsAdmin)
{
await SseHelper.TryWriteSse(res, "error", new { error = "Kein API-Key zugewiesen und keine CLI-Berechtigung. Bitte einen Key zuweisen." }, sseCt);
await SseHelper.TryWriteSse(res, "done", new { chainId = ctx.ChainId }, sseCt);
return;
}
if (anthropic.IsCliAvailable)
{
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);
}
else
{
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);
await SseHelper.TryWriteSse(res, "done", new { chainId = ctx.ChainId }, sseCt);
}
return;
}
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);
}
}
finally
{
streamingTracker.Stop(sessionId);
// Nach Stop ist IsStreaming(sessionId) false → /api/chat/steer enqueued nichts mehr.
// Etwaige nicht gedrainte Einwürfe verwerfen (kein Leak in die nächste Chain).
steeringQueue.Clear(sessionId);
// Heartbeat-Task beenden (sseLinkCts wird disposed → Token cancelled)
}
}
private static async Task HandleStop(HttpRequest req, HttpResponse res, StreamingTracker streamingTracker)
{
var body = await JsonSerializer.DeserializeAsync<JsonElement>(req.Body);
var sessionId = body.TryGetProperty("sessionId", out var sid) ? sid.GetString() : null;
if (string.IsNullOrEmpty(sessionId))
{
res.StatusCode = 400;
await res.WriteAsJsonAsync(new { error = "sessionId required" });
return;
}
// Erster Klick = "graceful" (laufende Iteration fertig), zweiter = "hard" (sofort)
var stopLevel = streamingTracker.Cancel(sessionId);
await res.WriteAsJsonAsync(new { stopped = stopLevel != null, level = stopLevel ?? "none" });
}
/// <summary>
/// "Steering": Reiht eine Nachricht out-of-band in die laufende Chain ein.
/// Sie wird an der nächsten Iterations-Grenze als User-Message injiziert.
/// Anthropic-API-Pfad: Injektion zwischen den messages.create-Calls.
/// Claude-CLI-Pfad: Kill-and-Restart am nächsten Tool-Boundary (der Agentic-Loop
/// läuft im claude-Child, daher kein echtes Mid-Turn-Inject möglich).
/// </summary>
private static async Task HandleSteer(HttpRequest req, HttpResponse res, StreamingTracker streamingTracker, SteeringQueue steeringQueue)
{
var body = await JsonSerializer.DeserializeAsync<JsonElement>(req.Body);
var sessionId = body.TryGetProperty("sessionId", out var sid) ? sid.GetString() : null;
var text = body.TryGetProperty("text", out var txt) ? txt.GetString() : null;
if (string.IsNullOrEmpty(sessionId) || string.IsNullOrWhiteSpace(text))
{
res.StatusCode = 400;
await res.WriteAsJsonAsync(new { error = "sessionId and text required" });
return;
}
// Nur einreihen wenn tatsächlich gerade eine Chain läuft – sonst würde der
// Einwurf nie gedraint (kein laufender Loop) und bis zur nächsten Chain liegen bleiben.
if (!streamingTracker.IsStreaming(sessionId))
{
await res.WriteAsJsonAsync(new { injected = false, reason = "not_streaming" });
return;
}
steeringQueue.Enqueue(sessionId, text.Trim());
await res.WriteAsJsonAsync(new { injected = true });
}
}