Refactor imports and standardize file naming: update module imports for consistency, align filenames with snake_case convention, and extract DynamicResponse to a dedicated module.

This commit is contained in:
Yûki VACHOT 2025-11-29 02:27:58 +01:00
parent 126d04ab0f
commit bf5d1b890a
22 changed files with 160 additions and 145 deletions

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"""
Handles schema versioning, storage, and updates for API endpoints.
The module provides functionality to detect and manage changes in API response
schemas, maintain history of schema versions, and persist schema data to disk.
It supports use cases such as tracking endpoint availability, generating schema
summaries, and providing dynamic endpoint descriptions.
Classes:
SchemaRegistry
"""
import json
import logging
from datetime import UTC, datetime
from pathlib import Path
from typing import Any, Optional
from .endpoint_schema import EndpointSchema
from .schema_detector import SchemaDetector
from ...config import settings
logger = logging.getLogger(__name__)
class SchemaRegistry:
"""
Manages schema storage, versioning, and change detection.
Schemas are persisted to disk and loaded on startup, allowing the system
to track changes over time and adapt automatically.
"""
def __init__(self, cache_dir: Optional[str] = None):
self.cache_dir = Path(cache_dir or settings.SCHEMA_CACHE_DIR)
self.cache_dir.mkdir(parents=True, exist_ok=True)
self.schemas: dict[str, EndpointSchema] = {}
self.schema_history: dict[str, list[EndpointSchema]] = {}
self.detector = SchemaDetector()
self._load_cached_schemas()
def _get_schema_file(self) -> Path:
"""Get the path to the schema cache file."""
return self.cache_dir / "schemas.json"
def _get_history_file(self) -> Path:
"""Get the path to the schema history file."""
return self.cache_dir / "schema_history.json"
def _load_cached_schemas(self) -> None:
"""Load schemas from disk cache."""
schema_file = self._get_schema_file()
if schema_file.exists():
try:
with open(schema_file) as f:
data = json.load(f)
for endpoint, schema_data in data.items():
self.schemas[endpoint] = EndpointSchema.from_dict(schema_data)
logger.info(f"Loaded {len(self.schemas)} cached schemas")
except Exception as e:
logger.warning(f"Failed to load cached schemas: {e}")
history_file = self._get_history_file()
if history_file.exists():
try:
with open(history_file) as f:
data = json.load(f)
for endpoint, history in data.items():
self.schema_history[endpoint] = [
EndpointSchema.from_dict(h) for h in history
]
except Exception as e:
logger.warning(f"Failed to load schema history: {e}")
def _save_schemas(self) -> None:
"""Save schemas to disk cache."""
try:
with open(self._get_schema_file(), "w") as f:
json.dump(
{ep: schema.to_dict() for ep, schema in self.schemas.items()}, f, indent=2
)
with open(self._get_history_file(), "w") as f:
json.dump(
{
ep: [h.to_dict() for h in history[-10:]] # Keep last 10 versions
for ep, history in self.schema_history.items()
},
f,
indent=2,
)
except Exception as e:
logger.error(f"Failed to save schemas: {e}")
def update_schema(
self, endpoint: str, response_data: Any, response_code: int = 200, method: str = "GET"
) -> tuple[EndpointSchema, bool]:
"""
Update schema for an endpoint based on response data.
Args:
endpoint: The API endpoint
response_data: The JSON response data
response_code: HTTP response code
method: HTTP method
Returns:
Tuple of (updated schema, whether schema changed)
"""
fields = self.detector.analyze_response(response_data)
new_hash = self.detector.compute_schema_hash(fields)
existing_schema = self.schemas.get(endpoint)
schema_changed = existing_schema is None or existing_schema.schema_hash != new_hash
new_schema = EndpointSchema(
endpoint=endpoint,
method=method,
fields=fields,
last_updated=datetime.now(UTC),
schema_hash=new_hash,
response_code=response_code,
is_available=True,
sample_response=self._truncate_sample(response_data),
)
if schema_changed:
if endpoint not in self.schema_history:
self.schema_history[endpoint] = []
if existing_schema:
self.schema_history[endpoint].append(existing_schema)
logger.info(f"Schema changed for {endpoint}: {new_hash}")
self.schemas[endpoint] = new_schema
self._save_schemas()
return new_schema, schema_changed
def mark_unavailable(self, endpoint: str, error_message: str, response_code: int = 0) -> None:
"""Mark an endpoint as unavailable."""
if endpoint in self.schemas:
self.schemas[endpoint].is_available = False
self.schemas[endpoint].error_message = error_message
self.schemas[endpoint].response_code = response_code
self.schemas[endpoint].last_updated = datetime.now(UTC)
else:
self.schemas[endpoint] = EndpointSchema(
endpoint=endpoint,
method="GET",
is_available=False,
error_message=error_message,
response_code=response_code,
)
self._save_schemas()
def get_schema(self, endpoint: str) -> Optional[EndpointSchema]:
"""Get the current schema for an endpoint."""
return self.schemas.get(endpoint)
def get_all_schemas(self) -> dict[str, EndpointSchema]:
"""Get all registered schemas."""
return self.schemas.copy()
def get_available_endpoints(self) -> list[str]:
"""Get list of currently available endpoints."""
return [ep for ep, schema in self.schemas.items() if schema.is_available]
def get_schema_summary(self) -> dict:
"""Get a summary of all schemas for LLM context."""
return {
"total_endpoints": len(self.schemas),
"available_endpoints": len(self.get_available_endpoints()),
"endpoints": {
endpoint: {
"available": schema.is_available,
"last_updated": schema.last_updated.isoformat(),
"field_count": len(schema.fields),
"fields": list(schema.fields.keys())[:20], # Limit for context
"response_code": schema.response_code,
}
for endpoint, schema in self.schemas.items()
},
}
def generate_dynamic_description(self, endpoint: str) -> str:
"""
Generate a dynamic description of an endpoint's response format.
This is used to provide context to the LLM about what data is available.
"""
schema = self.get_schema(endpoint)
if not schema:
return f"No schema information available for {endpoint}"
if not schema.is_available:
return f"Endpoint {endpoint} is currently unavailable: {schema.error_message}"
lines = [
f"Endpoint: {endpoint}",
f"Method: {schema.method}",
f"Last Updated: {schema.last_updated.isoformat()}",
f"Status: {'Available' if schema.is_available else 'Unavailable'}",
"",
"Response Fields:",
]
for name, item in sorted(schema.fields.items()):
nullable_str = " (nullable)" if item.nullable else ""
lines.append(f" - {name}: {item.field_type}{nullable_str}")
if item.nested_schema:
lines.append(f" Nested fields: {list(item.nested_schema.keys())}")
return "\n".join(lines)
@staticmethod
def _truncate_sample(data: Any, max_items: int = 3) -> Any:
"""Truncate sample response for storage."""
if isinstance(data, dict):
return {
k: SchemaRegistry._truncate_sample(v, max_items) for k, v in list(data.items())[:20]
}
if isinstance(data, list):
return [SchemaRegistry._truncate_sample(item, max_items) for item in data[:max_items]]
if isinstance(data, str) and len(data) > 200:
return data[:200] + "..."
return data
# Global registry instance
schema_registry = SchemaRegistry()