feat: multi-agent architecture with Conversations API and persistent state

Mistral Agents + Conversations API integration:
- Orchestrator agent created on startup with Sol's personality + tools
- ConversationRegistry routes messages through persistent conversations
- Per-room conversation state (room_id → conversation_id + token counts)
- Function call handling within conversation responses
- Configurable via [agents] section in sol.toml (use_conversations_api flag)

Multimodal support:
- m.image detection and Matrix media download (mxc:// → base64 data URI)
- ContentPart-based messages sent to Mistral vision models
- Archive stores media_urls for image messages

System prompt rewrite:
- 687 → 150 lines — dense, few-shot examples, hard rules
- {room_context_rules} placeholder for group vs DM behavior
- Sender prefixing (<@user:server>) for multi-user turns in group rooms

SQLite persistence (/data/sol.db):
- Conversation mappings and agent IDs survive reboots
- WAL mode for concurrent reads
- Falls back to in-memory on failure (sneezes into all rooms to signal)
- PVC already mounted at /data alongside Matrix SDK state store

New modules:
- src/persistence.rs — SQLite state store
- src/conversations.rs — ConversationRegistry + message merging
- src/agents/{mod,definitions,registry}.rs — agent lifecycle
- src/agent_ux.rs — reaction + thread progress UX
- src/tools/bridge.rs — tool dispatch for domain agents

102 tests passing.

src/memory/extractor.rs

@@ -64,7 +64,8 @@ pub async fn extract_and_store(
     };
 
     let response = chat_blocking(mistral, model, messages, params).await?;
-    let text = response.choices[0].message.content.trim();
+    let text = response.choices[0].message.content.text();
+    let text = text.trim();
 
     let extraction: ExtractionResponse = match serde_json::from_str(text) {
         Ok(e) => e,