PHASE 3 — relational tier (Mem0g-light)

app/core/deep_agent.py

@@ -55,6 +55,22 @@ def _language_instruction(context: dict[str, Any]) -> str:
         f"All your output text must be written in {lang}."
     )
 
+def _relational_memory_injection(context: dict[str, Any]) -> str:
+    """Return a system-prompt paragraph listing known people/projects from relational memory.
+
+    Returns empty string when no relational rows or tier is Free.
+    Capped at 800 chars to control token spend.
+    """
+    relations: list[str] = context.get("relational_memory") or []
+    if not relations:
+        return ""
+    body = "\n".join(f"- {r}" for r in relations)
+    section = f"\n\nKnown people & projects:\n{body}"
+    if len(section) > 800:
+        section = section[:797] + "..."
+    return section
+
+
 _HOME_SYSTEM_PROMPT = (
     "You are the home assistant with direct access to all tools: tasks, projects, notes, timelines, and memory tools. "
     "Always use tools for factual data retrieval before answering. "
@@ -904,6 +920,7 @@ async def run_home(user_id: str, message: str, context: dict[str, Any]) -> str:
     system_prompt, langfuse_prompt = get_prompt_or_fallback(
         "home_system", _HOME_SYSTEM_PROMPT
     )
+    system_prompt += _relational_memory_injection(context)
     system_prompt += _language_instruction(context)
     response = await _run_single_agent(
         user_id=user_id,
@@ -922,6 +939,7 @@ async def run_floating(user_id: str, message: str, context: dict[str, Any]) -> t
     system_prompt, langfuse_prompt = get_prompt_or_fallback(
         "floating_system", _FLOATING_SYSTEM_PROMPT
     )
+    system_prompt += _relational_memory_injection(context)
     system_prompt += _language_instruction(context)
     response = await _run_single_agent(
         user_id=user_id,
@@ -946,6 +964,7 @@ async def run_home_stream(
     system_prompt, langfuse_prompt = get_prompt_or_fallback(
         "home_system", _HOME_SYSTEM_PROMPT
     )
+    system_prompt += _relational_memory_injection(context)
     system_prompt += _language_instruction(context)
     text_chunks: list[str] = []
     async for event in _run_single_agent_stream(
@@ -979,6 +998,7 @@ async def run_floating_stream(
     system_prompt, langfuse_prompt = get_prompt_or_fallback(
         "floating_system", _FLOATING_SYSTEM_PROMPT
     )
+    system_prompt += _relational_memory_injection(context)
     system_prompt += _language_instruction(context)
     sanitizer = _FloatingStreamSanitizer()
     emitted_sanitized = False