deer-flow/backend/docs/MEMORY_IMPROVEMENTS_SUMMARY.md

# Memory System Improvements - Summary

## Sync Note (2026-03-10)

This summary is synchronized with the `main` branch implementation.
TF-IDF/context-aware retrieval is **planned**, not merged yet.

## Implemented

- Accurate token counting with `tiktoken` in memory injection.
- Facts are injected into `<memory>` prompt content.
- Facts are ordered by confidence and bounded by `max_injection_tokens`.

## Planned (Not Yet Merged)

- TF-IDF cosine similarity recall based on recent conversation context.
- `current_context` parameter for `format_memory_for_injection`.
- Weighted ranking (`similarity` + `confidence`).
- Runtime extraction/injection flow for context-aware fact selection.

## Why This Sync Was Needed

Earlier docs described TF-IDF behavior as already implemented, which did not match code in `main`.
This mismatch is tracked in issue `#1059`.

## Current API Shape

```python
def format_memory_for_injection(memory_data: dict[str, Any], max_tokens: int = 2000) -> str:
```

No `current_context` argument is currently available in `main`.

## Verification Pointers

- Implementation: `backend/src/agents/memory/prompt.py`
- Prompt assembly: `backend/src/agents/lead_agent/prompt.py`
- Regression tests: `backend/tests/test_memory_prompt_injection.py`