feat(iit): Complete CRA Agent V3.0 P1 - ChatOrchestrator with LLM Function Calling

P1 Architecture: Lightweight ReAct (Function Calling loop, max 3 rounds)

Core changes:
- Add ToolDefinition/ToolCall types to LLM adapters (DeepSeek + CloseAI + Claude)
- Replace 6 old tools with 4 semantic tools: read_report, look_up_data, check_quality, search_knowledge
- Create ChatOrchestrator (~160 lines) replacing ChatService (1,442 lines)
- Wire WechatCallbackController to ChatOrchestrator, deprecate ChatService
- Fix nullable content (string | null) across 12+ LLM consumer files

E2E test results: 8/8 scenarios passed (100%)
- QC report query, critical issues, patient data, trend, on-demand QC
- Knowledge base search, project overview, data modification refusal

Net code reduction: ~1,100 lines
Tested: E2E P1 chat test 8/8 passed with DeepSeek API

Made-with: Cursor

backend/src/modules/ssa/services/IntentRouterService.ts

@@ -189,7 +189,7 @@ class IntentRouterService {
       maxTokens: 100,
     });
 
-    return this.parseLLMResponse(response.content);
+    return this.parseLLMResponse(response.content ?? '');
   }
 
   private parseLLMResponse(text: string): IntentResult {

backend/src/modules/ssa/services/PicoInferenceService.ts

@@ -67,7 +67,7 @@ export class PicoInferenceService {
             maxTokens: rendered.modelConfig?.maxTokens ?? 1024,
           });
 
-          const raw = this.robustJsonParse(response.content);
+          const raw = this.robustJsonParse(response.content ?? '');
           const validated = PicoInferenceSchema.parse({
             ...raw,
             status: 'ai_inferred',

backend/src/modules/ssa/services/QueryService.ts

@@ -122,7 +122,7 @@ export class QueryService {
         });
 
         // 4. 三层 JSON 解析
-        const raw = this.robustJsonParse(response.content);
+        const raw = this.robustJsonParse(response.content ?? '');
 
         // 5. Zod 校验（动态防幻觉）
         const validColumns = profile?.columns.map(c => c.name) ?? [];

backend/src/modules/ssa/services/ReflectionService.ts

@@ -104,7 +104,7 @@ export class ReflectionService {
         maxTokens: LLM_MAX_TOKENS,
       });
 
-      const rawOutput = response.content;
+      const rawOutput = response.content ?? '';
       logger.info('[SSA:Reflection] LLM response received', {
         contentLength: rawOutput.length,
         usage: response.usage,