"""Contract tests for AI Functions Provider.
Phase 2 — Verifies AI Functions interface compatibility.
These tests ensure chunking and filtering behaviors work correctly.
Dependencies:
- P2-A1: AI_Functions Provider interface design
- P2-A2: AIChunkingProvider implementation
- P2-A3: AIFilterProvider implementation
"""
import pytest
from typing import Protocol
from core.models import RequestContext
class TestAIChunkingProvider:
"""Verify AIChunkingProvider interface and behavior.
AI chunking splits long content into semantic chunks based on
meaning boundaries rather than arbitrary character limits.
"""
def test_ai_chunking_has_chunk_method(self):
"""AIChunkingProvider must have a chunk(content, max_size) method.
TODO: Enable when P2-A1 (AI_Functions Provider interface) is DONE.
"""
pytest.skip("Waiting for P2-A1: AI_Functions Provider interface design")
def test_chunk_returns_semantic_chunks(self):
"""chunk() should split content at semantic boundaries.
Bad: Mid-sentence cuts
Good: Paragraph, section, or topic boundaries
Example input:
"User prefers coffee. User hates tea. User loves juice."
Expected chunks (max_size=50 chars):
["User prefers coffee.", "User hates tea.", "User loves juice."]
TODO: Implement when P2-A2 (AIChunkingProvider) is DONE.
"""
pytest.skip("Waiting for P2-A2: AIChunkingProvider implementation")
def test_chunk_respects_max_size(self):
"""No chunk should exceed max_size characters.
Soft limit: May slightly exceed if needed for semantic boundary.
Hard limit: Never exceed max_size * 1.2
TODO: Implement when P2-A2 (AIChunkingProvider) is DONE.
"""
pytest.skip("Waiting for P2-A2: AIChunkingProvider implementation")
def test_chunk_preserves_context_overlap(self):
"""Chunks should have slight overlap for context continuity.
Recommended: 10-20% overlap between consecutive chunks.
Helps retrieval maintain coherence across chunk boundaries.
TODO: Implement when P2-A2 (AIChunkingProvider) is DONE.
"""
pytest.skip("Waiting for P2-A2: AIChunkingProvider implementation")
def test_chunk_handles_code_blocks(self):
"""Code blocks should not be split in the middle.
Chunking should recognize ```fenced code blocks``` and
preserve their integrity.
TODO: Implement when P2-A2 (AIChunkingProvider) is DONE.
"""
pytest.skip("Waiting for P2-A2: AIChunkingProvider implementation")
def test_chunk_returns_empty_for_empty_input(self):
"""Empty content should return empty list, not error.
TODO: Implement when P2-A2 (AIChunkingProvider) is DONE.
"""
pytest.skip("Waiting for P2-A2: AIChunkingProvider implementation")
def test_chunk_handles_markdown_structure(self):
"""Markdown headers (# ## ###) should inform chunk boundaries.
Prefer to split at headers rather than mid-section.
TODO: Implement when P2-A2 (AIChunkingProvider) is DONE.
"""
pytest.skip("Waiting for P2-A2: AIChunkingProvider implementation")
class TestAIFilterProvider:
"""Verify AIFilterProvider interface and behavior.
AI filtering removes low-quality or irrelevant memories before
they are persisted to the knowledge base.
"""
def test_ai_filter_has_filter_method(self):
"""AIFilterProvider must have a filter(candidates) method.
TODO: Enable when P2-A1 (AI_Functions Provider interface) is DONE.
"""
pytest.skip("Waiting for P2-A1: AI_Functions Provider interface design")
def test_filter_returns_subset(self):
"""filter() should return a subset (not superset) of input candidates.
May remove low-quality items, but never add new ones.
Input: 10 candidates
Output: ≤ 10 candidates
TODO: Implement when P2-A3 (AIFilterProvider) is DONE.
"""
pytest.skip("Waiting for P2-A3: AIFilterProvider implementation")
def test_filter_removes_low_confidence(self):
"""Candidates with confidence < threshold should be removed.
Default threshold: 0.5 (configurable)
Below threshold: Skip (don't persist)
At or above: Keep
TODO: Implement when P2-A3 (AIFilterProvider) is DONE.
"""
pytest.skip("Waiting for P2-A3: AIFilterProvider implementation")
def test_filter_removes_duplicates(self):
"""Semantically similar candidates should be deduplicated.
Example: "User likes coffee" and "User prefers coffee"
should be recognized as duplicates and one removed.
TODO: Implement when P2-A3 (AIFilterProvider) is DONE.
"""
pytest.skip("Waiting for P2-A3: AIFilterProvider implementation")
def test_filter_removes_vague_content(self):
"""Candidates with vague or generic content should be removed.
Examples to filter:
- "User said something"
- "User mentioned a topic"
- "User talked about stuff"
Examples to keep:
- "User prefers dark roast coffee over light roast"
- "User is allergic to peanuts"
TODO: Implement when P2-A3 (AIFilterProvider) is DONE.
"""
pytest.skip("Waiting for P2-A3: AIFilterProvider implementation")
def test_filter_preserves_high_quality(self):
"""High-quality candidates should never be filtered out.
Quality indicators:
- Specific details (names, dates, quantities)
- Clear relationship (user's X, agent learned Y)
- Actionable information
- Confidence ≥ 0.8
TODO: Implement when P2-A3 (AIFilterProvider) is DONE.
"""
pytest.skip("Waiting for P2-A3: AIFilterProvider implementation")
def test_filter_empty_list_returns_empty(self):
"""Empty input should return empty list, not error.
TODO: Implement when P2-A3 (AIFilterProvider) is DONE.
"""
pytest.skip("Waiting for P2-A3: AIFilterProvider implementation")
class TestAIFunctionsProviderProtocol:
"""Verify AI Functions satisfy Provider Protocol patterns."""
def test_ai_chunking_is_llm_dependent(self):
"""AIChunkingProvider should use LLM for semantic understanding.
May implement fallback to rule-based chunking if LLM unavailable.
TODO: Implement when P2-A2 (AIChunkingProvider) is DONE.
"""
pytest.skip("Waiting for P2-A2: AIChunkingProvider implementation")
def test_ai_filter_is_llm_dependent(self):
"""AIFilterProvider should use LLM for quality assessment.
May implement fallback to rule-based filtering if LLM unavailable.
TODO: Implement when P2-A3 (AIFilterProvider) is DONE.
"""
pytest.skip("Waiting for P2-A3: AIFilterProvider implementation")
def test_ai_functions_timeout_protection(self):
"""AI Functions should have timeout protection.
LLM calls may hang; implement timeout (default: 30s).
On timeout: Return gracefully, don't block pipeline.
TODO: Implement when P2-A2 and P2-A3 are DONE.
"""
pytest.skip("Waiting for AI Functions implementations")
class TestAIFunctionsIntegration:
"""Integration tests with extraction pipeline."""
def test_extractor_uses_ai_chunking(self):
"""Extractors should use AIChunkingProvider for large content.
When extracted content exceeds size threshold, use AI chunking
to split into semantic chunks before persisting.
TODO: Implement when P2-A4 (extractor integration) is DONE.
"""
pytest.skip("Waiting for P2-A4: Extractor integration with AIChunkingProvider")
def test_extractor_uses_ai_filter(self):
"""Extractors should use AIFilterProvider before merging.
Apply AI filtering to CandidateMemory list before calling
MergePolicy.
TODO: Implement when P2-A4 (extractor integration) is DONE.
"""
pytest.skip("Waiting for P2-A4: Extractor integration with AIFilterProvider")
def test_chunked_content_creates_multiple_nodes(self):
"""AI chunking should result in multiple ContextNodes.
Each chunk becomes a separate node with same URI + chunk index.
Example:
content.md (original, 5000 chars)
→ chunk_0.md (2000 chars)
→ chunk_1.md (2000 chars)
→ chunk_2.md (1000 chars)
TODO: Implement when P2-A4 (extractor integration) is DONE.
"""
pytest.skip("Waiting for P2-A4: Extractor integration with AIChunkingProvider")
def test_filtered_candidates_skip_merge_policy(self):
"""Filtered-out candidates should skip MergePolicy entirely.
They should not generate WritePlan entries.
TODO: Implement when P2-A4 (extractor integration) is DONE.
"""
pytest.skip("Waiting for P2-A4: Extractor integration with AIFilterProvider")
