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* refactor: extract shared utils to break harness→app cross-layer imports Move _validate_skill_frontmatter to src/skills/validation.py and CONVERTIBLE_EXTENSIONS + convert_file_to_markdown to src/utils/file_conversion.py. This eliminates the two reverse dependencies from client.py (harness layer) into gateway/routers/ (app layer), preparing for the harness/app package split. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * refactor: split backend/src into harness (deerflow.*) and app (app.*) Physically split the monolithic backend/src/ package into two layers: - **Harness** (`packages/harness/deerflow/`): publishable agent framework package with import prefix `deerflow.*`. Contains agents, sandbox, tools, models, MCP, skills, config, and all core infrastructure. - **App** (`app/`): unpublished application code with import prefix `app.*`. Contains gateway (FastAPI REST API) and channels (IM integrations). Key changes: - Move 13 harness modules to packages/harness/deerflow/ via git mv - Move gateway + channels to app/ via git mv - Rename all imports: src.* → deerflow.* (harness) / app.* (app layer) - Set up uv workspace with deerflow-harness as workspace member - Update langgraph.json, config.example.yaml, all scripts, Docker files - Add build-system (hatchling) to harness pyproject.toml - Add PYTHONPATH=. to gateway startup commands for app.* resolution - Update ruff.toml with known-first-party for import sorting - Update all documentation to reflect new directory structure Boundary rule enforced: harness code never imports from app. All 429 tests pass. Lint clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * chore: add harness→app boundary check test and update docs Add test_harness_boundary.py that scans all Python files in packages/harness/deerflow/ and fails if any `from app.*` or `import app.*` statement is found. This enforces the architectural rule that the harness layer never depends on the app layer. Update CLAUDE.md to document the harness/app split architecture, import conventions, and the boundary enforcement test. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * feat: add config versioning with auto-upgrade on startup When config.example.yaml schema changes, developers' local config.yaml files can silently become outdated. This adds a config_version field and auto-upgrade mechanism so breaking changes (like src.* → deerflow.* renames) are applied automatically before services start. - Add config_version: 1 to config.example.yaml - Add startup version check warning in AppConfig.from_file() - Add scripts/config-upgrade.sh with migration registry for value replacements - Add `make config-upgrade` target - Auto-run config-upgrade in serve.sh and start-daemon.sh before starting services - Add config error hints in service failure messages Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix comments * fix: update src.* import in test_sandbox_tools_security to deerflow.* Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: handle empty config and search parent dirs for config.example.yaml Address Copilot review comments on PR #1131: - Guard against yaml.safe_load() returning None for empty config files - Search parent directories for config.example.yaml instead of only looking next to config.yaml, fixing detection in common setups Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: correct skills root path depth and config_version type coercion - loader.py: fix get_skills_root_path() to use 5 parent levels (was 3) after harness split, file lives at packages/harness/deerflow/skills/ so parent×3 resolved to backend/packages/harness/ instead of backend/ - app_config.py: coerce config_version to int() before comparison in _check_config_version() to prevent TypeError when YAML stores value as string (e.g. config_version: "1") - tests: add regression tests for both fixes Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * fix: update test imports from src.* to deerflow.*/app.* after harness refactor Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
123 lines
4.5 KiB
Python
123 lines
4.5 KiB
Python
"""Tests for memory prompt injection formatting."""
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import math
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from deerflow.agents.memory.prompt import _coerce_confidence, format_memory_for_injection
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def test_format_memory_includes_facts_section() -> None:
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memory_data = {
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"user": {},
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"history": {},
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"facts": [
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{"content": "User uses PostgreSQL", "category": "knowledge", "confidence": 0.9},
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{"content": "User prefers SQLAlchemy", "category": "preference", "confidence": 0.8},
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],
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}
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result = format_memory_for_injection(memory_data, max_tokens=2000)
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assert "Facts:" in result
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assert "User uses PostgreSQL" in result
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assert "User prefers SQLAlchemy" in result
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def test_format_memory_sorts_facts_by_confidence_desc() -> None:
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memory_data = {
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"user": {},
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"history": {},
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"facts": [
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{"content": "Low confidence fact", "category": "context", "confidence": 0.4},
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{"content": "High confidence fact", "category": "knowledge", "confidence": 0.95},
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],
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}
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result = format_memory_for_injection(memory_data, max_tokens=2000)
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assert result.index("High confidence fact") < result.index("Low confidence fact")
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def test_format_memory_respects_budget_when_adding_facts(monkeypatch) -> None:
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# Make token counting deterministic for this test by counting characters.
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monkeypatch.setattr("deerflow.agents.memory.prompt._count_tokens", lambda text, encoding_name="cl100k_base": len(text))
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memory_data = {
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"user": {},
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"history": {},
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"facts": [
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{"content": "First fact should fit", "category": "knowledge", "confidence": 0.95},
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{"content": "Second fact should not fit in tiny budget", "category": "knowledge", "confidence": 0.90},
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],
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}
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first_fact_only_memory_data = {
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"user": {},
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"history": {},
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"facts": [
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{"content": "First fact should fit", "category": "knowledge", "confidence": 0.95},
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],
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}
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one_fact_result = format_memory_for_injection(first_fact_only_memory_data, max_tokens=2000)
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two_facts_result = format_memory_for_injection(memory_data, max_tokens=2000)
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# Choose a budget that can include exactly one fact section line.
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max_tokens = (len(one_fact_result) + len(two_facts_result)) // 2
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first_only_result = format_memory_for_injection(memory_data, max_tokens=max_tokens)
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assert "First fact should fit" in first_only_result
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assert "Second fact should not fit in tiny budget" not in first_only_result
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def test_coerce_confidence_nan_falls_back_to_default() -> None:
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"""NaN should not be treated as a valid confidence value."""
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result = _coerce_confidence(math.nan, default=0.5)
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assert result == 0.5
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def test_coerce_confidence_inf_falls_back_to_default() -> None:
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"""Infinite values should fall back to default rather than clamping to 1.0."""
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assert _coerce_confidence(math.inf, default=0.3) == 0.3
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assert _coerce_confidence(-math.inf, default=0.3) == 0.3
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def test_coerce_confidence_valid_values_are_clamped() -> None:
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"""Valid floats outside [0, 1] are clamped; values inside are preserved."""
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assert _coerce_confidence(1.5) == 1.0
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assert _coerce_confidence(-0.5) == 0.0
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assert abs(_coerce_confidence(0.75) - 0.75) < 1e-9
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def test_format_memory_skips_none_content_facts() -> None:
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"""Facts with content=None must not produce a 'None' line in the output."""
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memory_data = {
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"facts": [
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{"content": None, "category": "knowledge", "confidence": 0.9},
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{"content": "Real fact", "category": "knowledge", "confidence": 0.8},
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],
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}
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result = format_memory_for_injection(memory_data, max_tokens=2000)
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assert "None" not in result
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assert "Real fact" in result
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def test_format_memory_skips_non_string_content_facts() -> None:
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"""Facts with non-string content (e.g. int/list) must be ignored."""
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memory_data = {
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"facts": [
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{"content": 42, "category": "knowledge", "confidence": 0.9},
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{"content": ["list"], "category": "knowledge", "confidence": 0.85},
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{"content": "Valid fact", "category": "knowledge", "confidence": 0.7},
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],
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}
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result = format_memory_for_injection(memory_data, max_tokens=2000)
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# The formatted line for an integer content would be "- [knowledge | 0.90] 42".
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assert "| 0.90] 42" not in result
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# The formatted line for a list content would be "- [knowledge | 0.85] ['list']".
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assert "| 0.85]" not in result
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assert "Valid fact" in result
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