Implement LLMInferenceActivity integration for Temporal workflows

Workflow Input Structure:
  ├─ question: User content for reasoning
  ├─ project: Project ID for scoping
  ├─ operations: Flags for link_entities, infer_facts, reason_query, summarize
  └─ llm_activity: Configuration for LLMInferenceActivity
       ├─ model: Selected based on complexity (reasoning|ornith:35b|qwen2.5:3b)
       ├─ system_prompt: Task-specific instruction (Zep-backed)
       ├─ user_prompt: Content to process
       ├─ temperature: 0.7 (reasoning) or 0.5 (validation)
       └─ max_tokens: 2048 (reasoning) or 512 (validation)

Model Selection:
  ├─ reason_query=true, summarize=true → reasoning (DeepSeek-R1, complex)
  ├─ reason_query=true, summarize=false → ornith:35b (medium)
  └─ reason_query=false → qwen2.5:3b (fast, <100ms)

System Prompts (handlers/llm_prompts.rs):
  ├─ entity_extraction_system_prompt(): Extract entities + relationships + facts
  ├─ reasoning_system_prompt(): Step-by-step reasoning + answers
  ├─ agent_capability_validation_prompt(): Validate agent capabilities
  └─ fact_validation_system_prompt(): Detect contradictions

Workflow Activity Execution:
  ├─ Temporal receives workflow input with llm_activity config
  ├─ ReasoningWorkflow orchestrates:
  │  ├─ Activity 1: RetrieveMemory (optional context)
  │  ├─ Activity 2: LLMInferenceActivity (calls /v1/chat/completions via gateway)
  │  │   └─ Retries: 3× with backoff (2s, 4s, 8s)
  │  │   └─ Timeout: 120s
  │  │   └─ JWT propagation: Authorization: Bearer header
  │  ├─ Activity 3: PersistResults (save to memory_entity/memory_edge)
  │  └─ Activity 4: SummarizeFindings (return results)
  ├─ Memory handler polls DESCRIBE_WORKFLOW (30× with 100ms delay, 3s timeout)
  └─ Returns ReasoningResult with answers, confidence, reasoning_steps

Changes:
  ├─ execute_reasoning_workflow(): Build llm_activity config with model selection
  ├─ select_llm_model(): Choose model based on operation complexity
  ├─ build_system_prompt(): Use Zep-inspired prompts for reasoning
  ├─ handlers/llm_prompts.rs: Centralized prompt templates (5 system + 4 user builders)
  ├─ AgentInitialization: Include llm_activity for capability validation
  └─ Fixed duplicate extract_jwt_token call in agent_handler.rs

Activity Contract:
  ├─ Workflow input includes llm_activity block
  ├─ Temporal passes to LLMInferenceActivity
  ├─ Activity substitutes {{ previous_output }} template variables
  ├─ Activity calls POST /v1/chat/completions with JWT header
  ├─ Activity returns { response, model, stop_reason, tokens_used }
  ├─ PersistResults activity stores results to DB
  └─ Workflow returns: question, answers[], confidence, reasoning_steps[]

Tests Added:
  + 14 new tests in llm_prompts.rs (prompt validation, user prompt builders)

Compilation: ✅

crates/mem-cli/src/handlers/agent_handler.rs

@@ -97,17 +97,27 @@ pub async fn register_agent_handler(
     //   1. Persist agent state to temporal_workflow_links table
     //   2. Execute LLMInferenceActivity (call LLM via api.riotpiao.com/v1/chat/completions)
     //   3. Store reasoning traces to memory_entity/memory_edge
-    if let Some(jwt) = crate::handlers::crate::handlers::extract_jwt_token(&req) {
+    if let Some(jwt) = crate::handlers::extract_jwt_token(&req) {
         let client = SynthesisClient::new(
             "https://api.riotpiao.com".to_string(),
             jwt,
         );
         
         // Start Temporal workflow for agent initialization
+        // Include LLMInferenceActivity configuration for capability verification
         let workflow_input = serde_json::json!({
             "agent_id": body.agent_id,
             "capabilities": body.capabilities,
-            "project_id": body.project_id
+            "project_id": body.project_id,
+            
+            // LLMInferenceActivity inputs for agent capability reasoning
+            "llm_activity": {
+                "model": "ornith:13b",
+                "system_prompt": "You are an agent capability validator. Verify that the requested capabilities are valid for the memory system. Return JSON with 'valid' boolean and 'reason' string.",
+                "user_prompt": format!("Validate agent capabilities: {:?}", body.capabilities),
+                "temperature": 0.5,
+                "max_tokens": 512
+            }
         });
 
         let workflow_req = crate::handlers::WorkflowBuilder::new("AgentInitialization")