feat: LLM-based fact extraction + robust entity parsing

Entity extraction fixes:
- clean_llm_response() strips <think> tags, markdown fences, extracts JSON
- Handle array responses (wrap in {"entities": [...]})
- EntityType custom Deserialize: unknown variants map to Unknown (not crash)
- Increase timeout to 90s for reasoning models
- Increase max_tokens to 1500 for reasoning model overhead

Fact extraction (new):
- LlmFactExtractor: LLM-based relationship extraction between entities
- Validates source/target against known entity list (no hallucinated edges)
- Same clean_llm_response() for reasoning model + Ollama compatibility
- Graceful fallback: returns empty on LLM error (no pipeline crash)
- IngestWorker uses LlmFactExtractor when LLM_ENDPOINT set

K8s deployment:
- Add LLM_ENDPOINT, LLM_API_BASE, LLM_MODEL env vars
- Points to in-cluster reasoning-predictor service

Tested E2E with local Ollama (qwen2.5:3b):
- 12 entities extracted (person, tool, concept, organization)
- 5 edges with meaningful relationships and facts
- 781 tests pass

crates/mem-cli/src/ingest_worker.rs

@@ -3,7 +3,7 @@ use mem_store::{MemoryL1, VectorStore, ChunkL0, EntityRepoOps, EdgeRepoOps};
 use mem_llm::EmbeddingsClient;
 use mem_ingest::ingest_pipeline::{IngestPipeline, Episode};
 use mem_ingest::entity_extractor::{WikiLinkFallbackExtractor, LlmEntityExtractor};
-use mem_ingest::fact_extractor::SimpleFactExtractor;
+use mem_ingest::fact_extractor::{SimpleFactExtractor, LlmFactExtractor};
 use mem_ingest::contradiction_detector::ContradictionHandler;
 use sqlx::PgPool;
 use uuid::Uuid;
@@ -37,7 +37,14 @@ impl IngestWorker {
                 Arc::new(WikiLinkFallbackExtractor)
             };
         let fact_extractor: Arc<dyn mem_ingest::fact_extractor::FactExtractor> = 
-            Arc::new(SimpleFactExtractor);
+            if std::env::var("LLM_ENDPOINT").is_ok() {
+                let model = std::env::var("LLM_MODEL").unwrap_or_else(|_| "qwen2.5:3b-instruct".to_string());
+                tracing::info!("Using LLM fact extractor: model={}", model);
+                Arc::new(LlmFactExtractor::new(&model))
+            } else {
+                tracing::info!("LLM_ENDPOINT not set, using simple pattern fact extractor");
+                Arc::new(SimpleFactExtractor)
+            };
         let contradiction_detector = Arc::new(ContradictionHandler::default());
         let pipeline = Arc::new(IngestPipeline::new(
             entity_extractor,