코드 탭 컨텍스트 영속화와 Auto budget 복구 적용

- AxAgentExecutionEngine에서 시스템 프롬프트 중복을 제거하고 structured tool_use/tool_result 전사본을 conversation.Messages로 동기화해 다음 턴과 저장 이력에서도 코드 작업 컨텍스트가 유지되도록 수정
- AgentQueryContextBuilder와 ContextCondenser에 post-compact tool snippet 복원, recent window 확대, tool result 보존 강화 로직을 추가해 장기 코드 실행 중 빌드/파일 근거 손실을 줄임
- MaxContextTokens=0 Auto 모드를 AppSettings, SettingsService 마이그레이션, 설정 UI, 오버레이 UI, 컨텍스트 사용량 표시, LLM 요청 본문에 연결하고 Auto 모드에서는 provider output cap 강제 주입을 제거
- 관련 회귀 테스트와 문서 README/DEVELOPMENT/CODE_CONTEXT_RELIABILITY_PLAN을 갱신하고 깨진 진단 문자열 기대값을 영어 기준으로 정리

검증:
- dotnet build src/AxCopilot/AxCopilot.csproj -c Release -v minimal -p:OutputPath=bin\\verify_context_reliability_followup\\ -p:IntermediateOutputPath=obj\\verify_context_reliability_followup\\
- dotnet test src/AxCopilot.Tests/AxCopilot.Tests.csproj -c Release -v minimal --filter "AxAgentExecutionEngineTests|AgentQueryContextBuilderTests|ContextCondenserTests|SettingsServiceTests|AgentLoopDiagnosticsFormatterTests" -p:OutputPath=bin\\verify_context_reliability_followup_tests\\ -p:IntermediateOutputPath=obj\\verify_context_reliability_followup_tests\\
- dotnet test src/AxCopilot.Tests/AxCopilot.Tests.csproj -c Release -v minimal --filter "AgentLoopQueryAssemblyServiceTests|AgentLoopPreLlmStageServiceTests|AgentLoopLlmRequestPreparationServiceTests|AgentMessageInvariantHelperTests|CodeTaskWorkingSetServiceTests|AgentLoopE2ETests" -p:OutputPath=bin\\verify_context_reliability_followup_tests2\\ -p:IntermediateOutputPath=obj\\verify_context_reliability_followup_tests2\\
- dotnet build src/AxCopilot/AxCopilot.csproj -c Release -v minimal -p:OutputPath=bin\\verify_context_reliability_final\\ -p:IntermediateOutputPath=obj\\verify_context_reliability_final\\

src/AxCopilot/Services/LlmService.cs

@@ -301,14 +301,25 @@ public partial class LlmService : ILlmService
         return llm.Model;
     }
 
-    private int ResolveOpenAiCompatibleMaxTokens()
+    private int? ResolveConfiguredMaxOutputTokens()
     {
         var llm = _settings.Settings.Llm;
-        var requested = Math.Clamp(llm.MaxContextTokens, 1, 1_000_000);
+        return llm.MaxContextTokens > 0
+            ? Math.Clamp(llm.MaxContextTokens, 1, 1_000_000)
+            : null;
+    }
+
+    private int? ResolveOpenAiCompatibleMaxTokens()
+    {
+        var llm = _settings.Settings.Llm;
+        var requested = ResolveConfiguredMaxOutputTokens();
+        if (!requested.HasValue)
+            return null;
+
         var service = NormalizeServiceName(llm.Service);
 
         if (service == "vllm")
-            return Math.Min(requested, 8192);
+            return Math.Min(requested.Value, 8192);
 
         return requested;
     }
@@ -469,16 +480,19 @@ public partial class LlmService : ILlmService
         var temperature = ResolveTemperature();
         var maxTokens = ResolveOpenAiCompatibleMaxTokens();
         IbmDiagDebug($"[IBM진단] BuildIbmDeploymentBody 완료: finalMessages={msgs.Count}건, temp={temperature}, maxTokens={maxTokens}");
-        return new
+        var parameters = new Dictionary<string, object?>
         {
-            messages = msgs,
-            parameters = new
-            {
-                temperature,
-                max_new_tokens = maxTokens
-            },
-            // Qwen3.5 thinking 모드 비활성화: 활성화되면 content=null, reasoning_content에만 출력됨
-            chat_template_kwargs = new { enable_thinking = false },
+            ["temperature"] = temperature,
+        };
+        if (maxTokens.HasValue)
+            parameters["max_new_tokens"] = maxTokens.Value;
+
+        return new Dictionary<string, object?>
+        {
+            ["messages"] = msgs,
+            ["parameters"] = parameters,
+            // Qwen3.5 thinking mode is disabled to keep content in the normal response field.
+            ["chat_template_kwargs"] = new { enable_thinking = false },
         };
     }
 
@@ -1155,7 +1169,6 @@ public partial class LlmService : ILlmService
 
     private object BuildOpenAiBody(List<ChatMessage> messages, bool stream)
     {
-        var llm = _settings.Settings.Llm;
         var msgs = BuildMessageList(messages, openAiVision: true);
         var body = new Dictionary<string, object?>
         {
@@ -1163,8 +1176,10 @@ public partial class LlmService : ILlmService
             ["messages"] = msgs,
             ["stream"] = stream,
             ["temperature"] = ResolveTemperature(),
-            ["max_tokens"] = ResolveOpenAiCompatibleMaxTokens()
         };
+        var maxTokens = ResolveOpenAiCompatibleMaxTokens();
+        if (maxTokens.HasValue)
+            body["max_tokens"] = maxTokens.Value;
         // 스트리밍 시 마지막 청크에 토큰 사용량을 포함하도록 요청 (vLLM/OpenAI 호환)
         if (stream)
             body["stream_options"] = new { include_usage = true };
@@ -1298,19 +1313,23 @@ public partial class LlmService : ILlmService
             });
         }
 
-        if (systemInstruction != null)
-            return new
-            {
-                systemInstruction,
-                contents,
-                generationConfig = new { temperature = ResolveTemperature(), maxOutputTokens = llm.MaxContextTokens }
-            };
-
-        return new
+        var generationConfig = new Dictionary<string, object?>
         {
-            contents,
-            generationConfig = new { temperature = ResolveTemperature(), maxOutputTokens = llm.MaxContextTokens }
+            ["temperature"] = ResolveTemperature(),
         };
+        var maxOutputTokens = ResolveConfiguredMaxOutputTokens();
+        if (maxOutputTokens.HasValue)
+            generationConfig["maxOutputTokens"] = maxOutputTokens.Value;
+
+        var body = new Dictionary<string, object?>
+        {
+            ["contents"] = contents,
+            ["generationConfig"] = generationConfig,
+        };
+        if (systemInstruction != null)
+            body["systemInstruction"] = systemInstruction;
+
+        return body;
     }
 
     // ═══════════════════════════════════════════════════════════════════════
@@ -1422,7 +1441,6 @@ public partial class LlmService : ILlmService
 
     private object BuildSigmoidBody(List<ChatMessage> messages, bool stream)
     {
-        var llm = _settings.Settings.Llm;
         var msgs = new List<object>();
 
         foreach (var m in messages)
@@ -1444,27 +1462,32 @@ public partial class LlmService : ILlmService
         }
 
         var activeModel = ResolveModel();
+        var maxTokens = ResolveConfiguredMaxOutputTokens();
         if (!string.IsNullOrEmpty(_systemPrompt))
         {
-            return new
+            var body = new Dictionary<string, object?>
             {
-                model = activeModel,
-                max_tokens = llm.MaxContextTokens,
-                temperature = ResolveTemperature(),
-                system = _systemPrompt,
-                messages = msgs,
-                stream
+                ["model"] = activeModel,
+                ["temperature"] = ResolveTemperature(),
+                ["system"] = _systemPrompt,
+                ["messages"] = msgs,
+                ["stream"] = stream,
             };
+            if (maxTokens.HasValue)
+                body["max_tokens"] = maxTokens.Value;
+            return body;
         }
 
-        return new
+        var fallbackBody = new Dictionary<string, object?>
         {
-            model = activeModel,
-            max_tokens = llm.MaxContextTokens,
-            temperature = ResolveTemperature(),
-            messages = msgs,
-            stream
+            ["model"] = activeModel,
+            ["temperature"] = ResolveTemperature(),
+            ["messages"] = msgs,
+            ["stream"] = stream,
         };
+        if (maxTokens.HasValue)
+            fallbackBody["max_tokens"] = maxTokens.Value;
+        return fallbackBody;
     }
 
     // ─── 공용 헬퍼 ─────────────────────────────────────────────────────────