Add multi-model panel with Fusion mode

Panel agents answer the user prompt in parallel (read-only, non-streaming);
their responses are merged into the worker's last user message as a
<panel_responses> block, and the session agent synthesizes one final
streamed answer. The RunPanel engine is built layer-ready for future MoA.

- New session fields: multi_model_mode (off/fusion), panel_agent_ids (CSV)
  with idempotent column migration
- New partial Services/AnthropicService.Panel.cs holding the RunPanel engine
- Provider-agnostic members: Anthropic RunNonStreamingToolLoop / OpenAI
  CompleteText / CLI plan-mode; all forced read-only, persisted with Tag=panel
- SSE events: panel_start, panel_member_start, panel_member_done, panel_done
- Frontend: multi-agent picker, live panel bubbles, history rendering
- Graceful degradation: panel errors fall back to worker-only

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

Services/OpenAiService.cs

@@ -1087,6 +1087,56 @@ public class OpenAiService
     /// Non-Streaming Chat für Telegram, Cronjobs und send_to_session.
     /// Gibt den finalen Antworttext zurück. Unterstützt Tool-Calling (agentic loop).
     /// </summary>
+    /// <summary>
+    /// Minimaler Single-Shot-Completion-Call: KEINE Tools, KEINE Persistenz, KEINE Chain.
+    /// Für Panel-Member (Fusion) – liefert nur den Antworttext zurück. So leckt nichts
+    /// ungetaggt in die Worker-History und es entstehen keine Seiteneffekte (Schreiben/Chains).
+    /// </summary>
+    public async Task<string> CompleteText(string modelId, string systemPromptText, List<object> messages, string apiToken)
+    {
+        var resolved = ResolveProviderConfig(modelId, apiToken);
+        if (resolved == null)
+            throw new Exception($"Unbekannter Provider: '{ParseModelString(modelId).provider}'");
+        var (provider, resolvedModelId, providerConfig) = resolved.Value;
+
+        var apiMessages = BuildApiMessages(systemPromptText, messages);
+        var client = CreateClient(providerConfig.ApiKey);
+        var maxTokens = provider == "minimax" ? 32768 : 16384;
+
+        var payload = new Dictionary<string, object>
+        {
+            ["model"] = resolvedModelId,
+            ["messages"] = apiMessages,
+            ["stream"] = false,
+            ["max_tokens"] = maxTokens
+        };
+        if (provider == "nvidia" && IsNvidiaThinkingModel(resolvedModelId))
+            payload["chat_template_kwargs"] = new { thinking = true };
+        if (provider == "minimax")
+        {
+            payload["temperature"] = 1.0;
+            payload["top_p"] = 0.95;
+        }
+
+        var jsonPayload = JsonSerializer.Serialize(payload);
+        var httpContent = new StringContent(jsonPayload, Encoding.UTF8, "application/json");
+        using var httpResp = await client.SendAsync(
+            new HttpRequestMessage(HttpMethod.Post, $"{providerConfig.BaseUrl}/chat/completions") { Content = httpContent });
+        var respBody = await httpResp.Content.ReadAsStringAsync();
+        if (!httpResp.IsSuccessStatusCode)
+            throw new Exception($"OpenAI API {(int)httpResp.StatusCode}: {respBody}");
+
+        var resp = JsonSerializer.Deserialize<JsonElement>(respBody);
+        if (!resp.TryGetProperty("choices", out var choices) || choices.ValueKind != JsonValueKind.Array || choices.GetArrayLength() == 0)
+            return "";
+        var choice = choices[0];
+        if (!choice.TryGetProperty("message", out var message) || message.ValueKind != JsonValueKind.Object)
+            return "";
+        if (message.TryGetProperty("content", out var contentProp) && contentProp.ValueKind == JsonValueKind.String)
+            return contentProp.GetString() ?? "";
+        return "";
+    }
+
     public async Task<string> ChatNonStreaming(
         ChatContext ctx,
         List<object> messages,