feat: 对齐df的注入模式

backend/packages/harness/deerflow/agents/memory/thread_prompt.py

@@ -6,7 +6,7 @@ import json
 import re
 from typing import Any
 
-from deerflow.agents.memory.prompt import _coerce_confidence, _count_tokens, format_conversation_for_update
+from deerflow.agents.memory.prompt import format_conversation_for_update, format_memory_for_injection
 
 THREAD_MEMORY_UPDATE_PROMPT = """You are a user profile memory system.
 
@@ -100,65 +100,7 @@ def _infer_preferred_memory_language(messages: list[Any]) -> str:
 
 
 def format_thread_memory_for_injection(memory_data: dict[str, Any], max_tokens: int = 2000) -> str:
-    if not memory_data:
+    return format_memory_for_injection(memory_data, max_tokens=max_tokens)
-        return ""
-
-    user = memory_data.get("user") or {}
-    history = memory_data.get("history") or {}
-    facts = memory_data.get("facts") or []
-
-    user_lines: list[str] = []
-    for key, label in (("workContext", "Work Context"), ("personalContext", "Personal Context"), ("topOfMind", "Top Of Mind")):
-        section = user.get(key) if isinstance(user, dict) else None
-        if isinstance(section, dict):
-            summary = section.get("summary")
-            if isinstance(summary, str) and summary.strip():
-                user_lines.append(f"- {label}: {summary.strip()}")
-
-    history_lines: list[str] = []
-    for key, label in (("recentMonths", "Recent Months"), ("earlierContext", "Earlier Context"), ("longTermBackground", "Long-Term Background")):
-        section = history.get(key) if isinstance(history, dict) else None
-        if isinstance(section, dict):
-            summary = section.get("summary")
-            if isinstance(summary, str) and summary.strip():
-                history_lines.append(f"- {label}: {summary.strip()}")
-
-    sections: list[str] = []
-    if user_lines:
-        sections.append("User:\n" + "\n".join(user_lines))
-    if history_lines:
-        sections.append("History:\n" + "\n".join(history_lines))
-
-    # Facts are lowest priority: include by confidence/recency and trim by token budget.
-    ranked_facts = sorted(
-        (
-            f
-            for f in facts
-            if isinstance(f, dict) and isinstance(f.get("content"), str) and f.get("content", "").strip()
-        ),
-        key=lambda f: (_coerce_confidence(f.get("confidence"), default=0.0), str(f.get("createdAt", ""))),
-        reverse=True,
-    )
-    base = "\n\n".join(sections)
-    running = _count_tokens(base) if base else 0
-    fact_lines: list[str] = []
-    if ranked_facts:
-        running += _count_tokens("\n\nFacts:\n" if base else "Facts:\n")
-    for fact in ranked_facts:
-        line = (
-            f"- [{str(fact.get('category', 'context')).strip() or 'context'} | "
-            f"{_coerce_confidence(fact.get('confidence'), default=0.0):.2f}] {fact.get('content').strip()}"
-        )
-        candidate = ("\n" + line) if fact_lines else line
-        cost = _count_tokens(candidate)
-        if running + cost > max_tokens:
-            break
-        fact_lines.append(line)
-        running += cost
-    if fact_lines:
-        sections.append("Facts:\n" + "\n".join(fact_lines))
-
-    return "\n\n".join(sections)
 
 
 def build_thread_memory_prompt(existing_memory: dict[str, Any], messages: list[Any]) -> str:

backend/tests/test_thread_memory_prompt.py

@@ -4,7 +4,7 @@ from deerflow.agents.memory.thread_prompt import build_thread_memory_prompt, for
 
 
 def test_thread_memory_injection_keeps_profile_and_preferences_under_small_budget(monkeypatch):
-    monkeypatch.setattr("deerflow.agents.memory.thread_prompt._count_tokens", lambda text, encoding_name="cl100k_base": len(text))
+    monkeypatch.setattr("deerflow.agents.memory.prompt._count_tokens", lambda text, encoding_name="cl100k_base": len(text))
     memory = {
         "user": {
             "workContext": {"summary": "Building APIs", "updatedAt": "2026-05-08T00:00:00Z"},
@@ -23,7 +23,7 @@ def test_thread_memory_injection_keeps_profile_and_preferences_under_small_budge
     }
 
     result = format_thread_memory_for_injection(memory, max_tokens=140)
-    assert "User:" in result
+    assert "User Context:" in result
     assert "History:" in result