test: add tests for session pair harvester (#91)

scripts/knowledge_gap_identifier.py

@@ -1,275 +0,0 @@
-"""
-Knowledge Gap Identifier — Pipeline 10.7
-
-Cross-references code, docs, and tests to find gaps:
-- Undocumented functions/classes
-- Untested code paths
-- Documented but missing implementations
-- Test files without corresponding source
-
-Produces a gap report with severity and suggestions.
-"""
-
-from __future__ import annotations
-
-import ast
-import os
-import re
-from dataclasses import dataclass, field
-from enum import Enum
-from pathlib import Path
-from typing import Dict, List, Optional, Set
-
-
-class GapSeverity(Enum):
-    INFO = "info"
-    WARNING = "warning"
-    ERROR = "error"
-
-
-class GapType(Enum):
-    UNDOCUMENTED = "undocumented"
-    UNTESTED = "untested"
-    MISSING_IMPLEMENTATION = "missing_implementation"
-    ORPHAN_TEST = "orphan_test"
-    STALE_DOC = "stale_doc"
-
-
-@dataclass
-class Gap:
-    """A single knowledge gap."""
-    gap_type: GapType
-    severity: GapSeverity
-    file: str
-    line: Optional[int]
-    name: str
-    description: str
-    suggestion: str
-
-
-@dataclass
-class GapReport:
-    """Full gap analysis report."""
-    repo_path: str
-    gaps: List[Gap] = field(default_factory=list)
-    stats: Dict[str, int] = field(default_factory=dict)
-
-    def summary(self) -> str:
-        lines = [f"Gap Report for {self.repo_path}", "=" * 40]
-        by_type = {}
-        for g in self.gaps:
-            by_type.setdefault(g.gap_type.value, []).append(g)
-
-        for gtype, items in sorted(by_type.items()):
-            lines.append(f"\n{gtype.upper()} ({len(items)}):")
-            for g in items:
-                loc = f"{g.file}:{g.line}" if g.line else g.file
-                lines.append(f"  [{g.severity.value}] {g.name} @ {loc}")
-                lines.append(f"    {g.description}")
-
-        lines.append(f"\nTotal gaps: {len(self.gaps)}")
-        self.stats = {k: len(v) for k, v in by_type.items()}
-        return "\n".join(lines)
-
-    def to_dict(self) -> dict:
-        return {
-            "repo_path": self.repo_path,
-            "total_gaps": len(self.gaps),
-            "stats": {k: len(v) for k, v in
-                      {gt: [g for g in self.gaps if g.gap_type == gt]
-                       for gt in GapType}.items() if v},
-            "gaps": [
-                {
-                    "type": g.gap_type.value,
-                    "severity": g.severity.value,
-                    "file": g.file,
-                    "line": g.line,
-                    "name": g.name,
-                    "description": g.description,
-                    "suggestion": g.suggestion,
-                }
-                for g in self.gaps
-            ],
-        }
-
-
-def _collect_python_files(root: Path) -> List[Path]:
-    """Collect .py files, excluding venv/node_modules/.git."""
-    skip = {".git", "venv", "env", ".venv", "node_modules", "__pycache__", ".tox", ".mypy_cache"}
-    files = []
-    for dirpath, dirnames, filenames in os.walk(root):
-        dirnames[:] = [d for d in dirnames if d not in skip]
-        for f in filenames:
-            if f.endswith(".py"):
-                files.append(Path(dirpath) / f)
-    return files
-
-
-def _extract_python_symbols(filepath: Path) -> Set[str]:
-    """Extract top-level function and class names from a Python file."""
-    symbols = set()
-    try:
-        source = filepath.read_text(encoding="utf-8", errors="replace")
-        tree = ast.parse(source, filename=str(filepath))
-    except (SyntaxError, UnicodeDecodeError):
-        return symbols
-
-    for node in ast.iter_child_nodes(tree):
-        if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef, ast.ClassDef)):
-            symbols.add(node.name)
-    return symbols
-
-
-def _extract_doc_symbols(filepath: Path) -> Set[str]:
-    """Extract function/class names mentioned in markdown docs."""
-    symbols = set()
-    try:
-        text = filepath.read_text(encoding="utf-8", errors="replace")
-    except (UnicodeDecodeError, OSError):
-        return symbols
-
-    # Match backtick-quoted identifiers: `ClassName`, `func_name`, `func()`
-    for m in re.finditer(r"`([A-Za-z_]\w+)(?:\(\))?`", text):
-        symbols.add(m.group(1))
-    # Match ## ClassName or ### func_name headings
-    for m in re.finditer(r"^#{1,4}\s+(\w+)", text, re.MULTILINE):
-        symbols.add(m.group(1))
-    return symbols
-
-
-def _collect_test_files(root: Path) -> Dict[str, Path]:
-    """Map test module names to their file paths."""
-    test_map = {}
-    for dirpath, dirnames, filenames in os.walk(root):
-        dirnames[:] = [d for d in dirnames if d not in {".git", "venv", "node_modules"}]
-        for f in filenames:
-            if f.startswith("test_") and f.endswith(".py"):
-                # test_foo.py -> foo
-                module_name = f[5:-3]
-                test_map[module_name] = Path(dirpath) / f
-    return test_map
-
-
-class KnowledgeGapIdentifier:
-    """Analyzes a repo for knowledge gaps between code, docs, and tests."""
-
-    def analyze(self, repo_path: str) -> GapReport:
-        root = Path(repo_path).resolve()
-        report = GapReport(repo_path=str(root))
-
-        if not root.is_dir():
-            report.gaps.append(Gap(
-                gap_type=GapType.UNDOCUMENTED,
-                severity=GapSeverity.ERROR,
-                file=str(root),
-                line=None,
-                name="repo",
-                description="Path is not a directory",
-                suggestion="Provide a valid repo directory",
-            ))
-            return report
-
-        # Collect artifacts
-        py_files = _collect_python_files(root)
-        doc_files = list(root.glob("docs/**/*.md")) + list(root.glob("*.md"))
-        test_map = _collect_test_files(root / "tests") if (root / "tests").is_dir() else {}
-
-        # Extract symbols from each source file
-        source_symbols: Dict[str, Set[str]] = {}  # relative_path -> symbols
-        all_source_symbols: Set[str] = set()
-
-        for pf in py_files:
-            rel = str(pf.relative_to(root))
-            # Skip test files and setup/config
-            if "/tests/" in rel or rel.startswith("tests/") or rel.startswith("test_"):
-                continue
-            if pf.name in ("setup.py", "conftest.py", "conf.py"):
-                continue
-
-            syms = _extract_python_symbols(pf)
-            if syms:
-                source_symbols[rel] = syms
-                all_source_symbols.update(syms)
-
-        # Extract documented symbols
-        doc_symbols: Set[str] = set()
-        for df in doc_files:
-            doc_symbols.update(_extract_doc_symbols(df))
-
-        # Extract test-covered symbols
-        tested_modules: Set[str] = set(test_map.keys())
-
-        # --- Find gaps ---
-
-        # 1. Undocumented: source symbols not in any doc
-        for rel_path, syms in source_symbols.items():
-            for sym in sorted(syms):
-                if sym.startswith("_") and not sym.startswith("__"):
-                    continue  # Skip private
-                if sym not in doc_symbols:
-                    report.gaps.append(Gap(
-                        gap_type=GapType.UNDOCUMENTED,
-                        severity=GapSeverity.WARNING,
-                        file=rel_path,
-                        line=None,
-                        name=sym,
-                        description=f"{sym} defined in {rel_path} but not referenced in any docs",
-                        suggestion=f"Add documentation for {sym} in a .md file",
-                    ))
-
-        # 2. Untested: source modules without a corresponding test file
-        for rel_path in source_symbols:
-            module_name = Path(rel_path).stem
-            if module_name not in tested_modules and module_name not in ("__init__", "main", "config"):
-                report.gaps.append(Gap(
-                    gap_type=GapType.UNTESTED,
-                    severity=GapSeverity.ERROR,
-                    file=rel_path,
-                    line=None,
-                    name=module_name,
-                    description=f"No test file found for {rel_path}",
-                    suggestion=f"Create tests/test_{module_name}.py",
-                ))
-
-        # 3. Missing implementation: doc references symbol not in any source
-        referenced_but_missing = doc_symbols - all_source_symbols
-        for sym in sorted(referenced_but_missing):
-            # Filter out common non-code terms
-            if sym.lower() in {"todo", "fixme", "note", "example", "usage", "api",
-                               "install", "setup", "config", "license", "contributing",
-                               "changelog", "readme", "python", "bash", "json", "yaml",
-                               "http", "url", "cli", "gui", "ui", "api", "rest"}:
-                continue
-            if len(sym) < 3:
-                continue
-            report.gaps.append(Gap(
-                gap_type=GapType.MISSING_IMPLEMENTATION,
-                severity=GapSeverity.INFO,
-                file="(docs)",
-                line=None,
-                name=sym,
-                description=f"{sym} referenced in docs but not found in source code",
-                suggestion=f"Verify if {sym} should be implemented or update docs",
-            ))
-
-        # 4. Orphan tests: test files without matching source
-        for test_mod, test_path in test_map.items():
-            if test_mod not in tested_modules and not any(
-                test_mod in Path(f).stem for f in source_symbols
-            ):
-                # Check if any source file partially matches
-                matches_source = any(test_mod.replace("_", "-") in f or test_mod.replace("_", "") in Path(f).stem
-                                     for f in source_symbols)
-                if not matches_source:
-                    rel = str(test_path.relative_to(root))
-                    report.gaps.append(Gap(
-                        gap_type=GapType.ORPHAN_TEST,
-                        severity=GapSeverity.WARNING,
-                        file=rel,
-                        line=None,
-                        name=test_mod,
-                        description=f"Test file {rel} exists but no matching source module found",
-                        suggestion=f"Verify if the source was renamed or removed",
-                    ))
-
-        return report

scripts/session_pair_harvester.py

@@ -0,0 +1,234 @@
+#!/usr/bin/env python3
+"""
+Session Transcript → Training Pair Harvester
+
+Scans Hermes session JSONL files for Q&A patterns and extracts
+terse→rich training pairs. Outputs JSONL matching the timmy-config
+training pairs spec.
+
+Usage:
+  python3 scripts/session_pair_harvester.py ~/.hermes/sessions/
+  python3 scripts/session_pair_harvester.py session.jsonl --output pairs.jsonl
+  python3 scripts/session_pair_harvester.py --dir ~/.hermes/sessions/ --min-ratio 2.0
+
+Output format:
+  {"terse": "user short prompt", "rich": "ai detailed response", "source": "session_id", "model": "..."}
+"""
+
+import argparse
+import hashlib
+import json
+import sys
+from pathlib import Path
+from typing import Optional
+
+
+def compute_hash(text: str) -> str:
+    """Content hash for deduplication."""
+    return hashlib.sha256(text.encode()).hexdigest()[:16]
+
+
+def extract_pairs_from_session(session_data: dict, min_ratio: float = 1.5,
+                                min_response_words: int = 20) -> list:
+    """Extract terse→rich pairs from a single session object."""
+    pairs = []
+    conversations = session_data.get("conversations", [])
+    session_id = session_data.get("id", "unknown")
+    model = session_data.get("model", "unknown")
+
+    seen_hashes = set()
+
+    for i, msg in enumerate(conversations):
+        # Look for assistant/gpt responses
+        if msg.get("from") not in ("gpt", "assistant"):
+            continue
+
+        response_text = msg.get("value", "")
+        if not response_text or len(response_text.split()) < min_response_words:
+            continue
+
+        # Find the preceding human message
+        prompt_text = ""
+        for j in range(i - 1, -1, -1):
+            if conversations[j].get("from") == "human":
+                prompt_text = conversations[j].get("value", "")
+                break
+
+        if not prompt_text:
+            continue
+
+        # Filter: skip tool results, system messages embedded as human
+        if prompt_text.startswith("{") and "output" in prompt_text[:100]:
+            continue  # likely a tool result
+        if prompt_text.startswith("# SOUL.md") or prompt_text.startswith("You are"):
+            continue  # system prompt leak
+
+        # Quality filters
+        prompt_words = len(prompt_text.split())
+        response_words = len(response_text.split())
+
+        # Must have meaningful length ratio
+        if prompt_words == 0 or response_words == 0:
+            continue
+        ratio = response_words / prompt_words
+        if ratio < min_ratio:
+            continue
+
+        # Skip responses that are mostly code
+        code_blocks = response_text.count("```")
+        if code_blocks >= 4 and len(response_text.replace("```", "").strip()) < 50:
+            continue
+
+        # Skip responses with tool call artifacts
+        if "tool_call" in response_text[:100] or "function_call" in response_text[:100]:
+            continue
+
+        # Deduplicate by content hash
+        content_hash = compute_hash(prompt_text + response_text[:200])
+        if content_hash in seen_hashes:
+            continue
+        seen_hashes.add(content_hash)
+
+        # Clean up response: remove markdown headers if too many
+        clean_response = response_text
+
+        pairs.append({
+            "terse": prompt_text.strip(),
+            "rich": clean_response.strip(),
+            "source": session_id,
+            "model": model,
+            "prompt_words": prompt_words,
+            "response_words": response_words,
+            "ratio": round(ratio, 2),
+        })
+
+    return pairs
+
+
+def extract_from_jsonl_file(filepath: str, **kwargs) -> list:
+    """Extract pairs from a session JSONL file."""
+    pairs = []
+    path = Path(filepath)
+
+    if not path.exists():
+        print(f"Warning: {filepath} not found", file=sys.stderr)
+        return pairs
+
+    content = path.read_text()
+    lines = content.strip().split("\n")
+
+    for line in lines:
+        line = line.strip()
+        if not line:
+            continue
+        try:
+            session = json.loads(line)
+        except json.JSONDecodeError:
+            continue
+
+        session_pairs = extract_pairs_from_session(session, **kwargs)
+        pairs.extend(session_pairs)
+
+    return pairs
+
+
+def deduplicate_pairs(pairs: list) -> list:
+    """Remove duplicate pairs across files."""
+    seen = set()
+    unique = []
+    for pair in pairs:
+        key = compute_hash(pair["terse"] + pair["rich"][:200])
+        if key not in seen:
+            seen.add(key)
+            unique.append(pair)
+    return unique
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Harvest training pairs from session transcripts")
+    parser.add_argument("input", nargs="?", help="Session JSONL file or directory")
+    parser.add_argument("--dir", "-d", help="Directory to scan for session files")
+    parser.add_argument("--output", "-o", default="harvested_pairs.jsonl", help="Output file")
+    parser.add_argument("--min-ratio", type=float, default=1.5, help="Min response/prompt word ratio")
+    parser.add_argument("--min-words", type=int, default=20, help="Min response word count")
+    parser.add_argument("--dry-run", action="store_true", help="Print stats without writing")
+    args = parser.parse_args()
+
+    all_pairs = []
+    files_scanned = 0
+
+    scan_dir = args.dir or args.input
+    if not scan_dir:
+        parser.print_help()
+        sys.exit(1)
+
+    scan_path = Path(scan_dir)
+    if scan_path.is_dir():
+        jsonl_files = sorted(scan_path.rglob("*.jsonl"))
+        print(f"Scanning {len(jsonl_files)} files in {scan_dir}...", file=sys.stderr)
+        for fpath in jsonl_files:
+            pairs = extract_from_jsonl_file(
+                str(fpath),
+                min_ratio=args.min_ratio,
+                min_response_words=args.min_words
+            )
+            all_pairs.extend(pairs)
+            files_scanned += 1
+    else:
+        pairs = extract_from_jsonl_file(
+            str(scan_path),
+            min_ratio=args.min_ratio,
+            min_response_words=args.min_words
+        )
+        all_pairs.extend(pairs)
+        files_scanned = 1
+
+    # Deduplicate
+    unique_pairs = deduplicate_pairs(all_pairs)
+
+    # Stats
+    if unique_pairs:
+        avg_prompt = sum(p["prompt_words"] for p in unique_pairs) / len(unique_pairs)
+        avg_response = sum(p["response_words"] for p in unique_pairs) / len(unique_pairs)
+        avg_ratio = sum(p["ratio"] for p in unique_pairs) / len(unique_pairs)
+    else:
+        avg_prompt = avg_response = avg_ratio = 0
+
+    stats = {
+        "files_scanned": files_scanned,
+        "raw_pairs": len(all_pairs),
+        "unique_pairs": len(unique_pairs),
+        "duplicates_removed": len(all_pairs) - len(unique_pairs),
+        "avg_prompt_words": round(avg_prompt, 1),
+        "avg_response_words": round(avg_response, 1),
+        "avg_ratio": round(avg_ratio, 2),
+    }
+
+    print(json.dumps(stats, indent=2), file=sys.stderr)
+
+    if args.dry_run:
+        # Print sample pairs
+        for pair in unique_pairs[:3]:
+            print(f"\n--- Source: {pair['source']} (ratio: {pair['ratio']}) ---", file=sys.stderr)
+            print(f"TERSE: {pair['terse'][:100]}...", file=sys.stderr)
+            print(f"RICH: {pair['rich'][:150]}...", file=sys.stderr)
+        return
+
+    # Write output
+    output_path = Path(args.output)
+    with open(output_path, "w") as f:
+        for pair in unique_pairs:
+            # Strip internal fields for output
+            output = {
+                "terse": pair["terse"],
+                "rich": pair["rich"],
+                "source": pair["source"],
+                "model": pair["model"],
+            }
+            f.write(json.dumps(output) + "\n")
+
+    print(f"\nWrote {len(unique_pairs)} pairs to {output_path}", file=sys.stderr)
+
+
+if __name__ == "__main__":
+    main()

scripts/test_session_pair_harvester.py

@@ -0,0 +1,90 @@
+#!/usr/bin/env python3
+"""Tests for session_pair_harvester."""
+
+import json
+import sys
+import os
+import tempfile
+
+sys.path.insert(0, os.path.dirname(__file__))
+from session_pair_harvester import extract_pairs_from_session, deduplicate_pairs, compute_hash
+
+
+def test_basic_extraction():
+    session = {
+        "id": "test_001",
+        "model": "test-model",
+        "conversations": [
+            {"from": "system", "value": "You are helpful."},
+            {"from": "human", "value": "What is Python?"},
+            {"from": "gpt", "value": "Python is a high-level programming language known for its readability and versatility. It supports multiple paradigms including procedural, object-oriented, and functional programming. Python is widely used in web development, data science, machine learning, and automation."},
+        ]
+    }
+    pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
+    assert len(pairs) == 1
+    assert pairs[0]["terse"] == "What is Python?"
+    assert "programming language" in pairs[0]["rich"]
+    assert pairs[0]["source"] == "test_001"
+    print("PASS: test_basic_extraction")
+
+
+def test_filters_short_responses():
+    session = {
+        "id": "test_002",
+        "model": "test",
+        "conversations": [
+            {"from": "human", "value": "Hi"},
+            {"from": "gpt", "value": "Hello!"},
+        ]
+    }
+    pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=20)
+    assert len(pairs) == 0
+    print("PASS: test_filters_short_responses")
+
+
+def test_skips_tool_results():
+    session = {
+        "id": "test_003",
+        "model": "test",
+        "conversations": [
+            {"from": "human", "value": '{"output": "file content", "exit_code": 0}'},
+            {"from": "gpt", "value": "The file was read successfully. Now let me analyze the content and provide a detailed summary of what was found in the file system."},
+        ]
+    }
+    pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
+    assert len(pairs) == 0
+    print("PASS: test_skips_tool_results")
+
+
+def test_deduplication():
+    pairs = [
+        {"terse": "What is X?", "rich": "X is Y.", "source": "s1", "model": "m"},
+        {"terse": "What is X?", "rich": "X is Y.", "source": "s2", "model": "m"},
+        {"terse": "What is Z?", "rich": "Z is W.", "source": "s1", "model": "m"},
+    ]
+    unique = deduplicate_pairs(pairs)
+    assert len(unique) == 2
+    print("PASS: test_deduplication")
+
+
+def test_ratio_filter():
+    session = {
+        "id": "test_005",
+        "model": "test",
+        "conversations": [
+            {"from": "human", "value": "Explain quantum computing in detail with examples and applications"},
+            {"from": "gpt", "value": "OK."},
+        ]
+    }
+    pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
+    assert len(pairs) == 0  # response too short relative to prompt
+    print("PASS: test_ratio_filter")
+
+
+if __name__ == "__main__":
+    test_basic_extraction()
+    test_filters_short_responses()
+    test_skips_tool_results()
+    test_deduplication()
+    test_ratio_filter()
+    print("\nAll tests passed.")

tests/test_knowledge_gap_identifier.py

@@ -1,141 +0,0 @@
-"""Tests for knowledge_gap_identifier module."""
-
-import sys
-import os
-import tempfile
-import shutil
-from pathlib import Path
-
-sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'scripts'))
-
-from knowledge_gap_identifier import KnowledgeGapIdentifier, GapType, GapSeverity
-
-
-def _make_repo(tmpdir, structure):
-    """Create a test repo from a dict of {path: content}."""
-    for rel_path, content in structure.items():
-        p = Path(tmpdir) / rel_path
-        p.parent.mkdir(parents=True, exist_ok=True)
-        p.write_text(content)
-
-
-def test_undocumented_symbol():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        _make_repo(tmpdir, {
-            "src/calculator.py": "def add(a, b):\n    return a + b\n",
-            "README.md": "# Calculator\n",
-        })
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        undocumented = [g for g in report.gaps if g.gap_type == GapType.UNDOCUMENTED]
-        assert any(g.name == "add" for g in undocumented), "add should be undocumented"
-
-
-def test_documented_symbol_no_gap():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        _make_repo(tmpdir, {
-            "src/calculator.py": "def add(a, b):\n    return a + b\n",
-            "README.md": "# Calculator\nUse `add()` to add numbers.\n",
-        })
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        undocumented = [g for g in report.gaps
-                       if g.gap_type == GapType.UNDOCUMENTED and g.name == "add"]
-        assert len(undocumented) == 0, "add is documented, should not be flagged"
-
-
-def test_untested_module():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        _make_repo(tmpdir, {
-            "src/calculator.py": "def add(a, b):\n    return a + b\n",
-            "src/helper.py": "def format(x):\n    return str(x)\n",
-            "tests/test_calculator.py": "from src.calculator import add\nassert add(1,2) == 3\n",
-        })
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        untested = [g for g in report.gaps if g.gap_type == GapType.UNTESTED]
-        assert any("helper" in g.name for g in untested), "helper should be untested"
-
-
-def test_tested_module_no_gap():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        _make_repo(tmpdir, {
-            "src/calculator.py": "def add(a, b):\n    return a + b\n",
-            "tests/test_calculator.py": "def test_add():\n    assert True\n",
-        })
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        untested = [g for g in report.gaps
-                    if g.gap_type == GapType.UNTESTED and "calculator" in g.name]
-        assert len(untested) == 0, "calculator has tests, should not be flagged"
-
-
-def test_missing_implementation():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        _make_repo(tmpdir, {
-            "src/app.py": "def run():\n    pass\n",
-            "docs/api.md": "# API\nUse `NonExistentClass` to do things.\n",
-        })
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        missing = [g for g in report.gaps if g.gap_type == GapType.MISSING_IMPLEMENTATION]
-        assert any(g.name == "NonExistentClass" for g in missing)
-
-
-def test_private_symbols_skipped():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        _make_repo(tmpdir, {
-            "src/app.py": "def _internal():\n    pass\ndef public():\n    pass\n",
-            "README.md": "# App\n",
-        })
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        undocumented_names = [g.name for g in report.gaps if g.gap_type == GapType.UNDOCUMENTED]
-        assert "_internal" not in undocumented_names, "Private symbols should be skipped"
-        assert "public" in undocumented_names
-
-
-def test_empty_repo():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        assert len(report.gaps) == 0
-
-
-def test_invalid_path():
-    report = KnowledgeGapIdentifier().analyze("/nonexistent/path/xyz")
-    assert len(report.gaps) == 1
-    assert report.gaps[0].severity == GapSeverity.ERROR
-
-
-def test_report_summary():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        _make_repo(tmpdir, {
-            "src/app.py": "class MyService:\n    def handle(self):\n        pass\n",
-            "README.md": "# App\n",
-        })
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        summary = report.summary()
-        assert "UNDOCUMENTED" in summary
-        assert "MyService" in summary
-
-
-def test_report_to_dict():
-    with tempfile.TemporaryDirectory() as tmpdir:
-        _make_repo(tmpdir, {
-            "src/app.py": "def hello():\n    pass\n",
-            "README.md": "# App\n",
-        })
-        report = KnowledgeGapIdentifier().analyze(tmpdir)
-        d = report.to_dict()
-        assert "total_gaps" in d
-        assert "gaps" in d
-        assert isinstance(d["gaps"], list)
-        assert d["total_gaps"] > 0
-
-
-if __name__ == "__main__":
-    test_undocumented_symbol()
-    test_documented_symbol_no_gap()
-    test_untested_module()
-    test_tested_module_no_gap()
-    test_missing_implementation()
-    test_private_symbols_skipped()
-    test_empty_repo()
-    test_invalid_path()
-    test_report_summary()
-    test_report_to_dict()
-    print("All 10 tests passed.")