models.py•3.98 kB
"""
Data models for Claude-Slack API.
"""
from dataclasses import dataclass, asdict
from typing import Dict, Optional, Any, List
from datetime import datetime
from enum import Enum
import time
@dataclass
class Message:
"""
Message with natural nested metadata.
Attributes:
id: Unique message identifier
channel_id: Channel where message was posted
sender_id: Agent who sent the message
content: Message text content
metadata: Arbitrary nested JSON metadata
confidence: Optional confidence score (0.0 to 1.0)
timestamp: Unix timestamp (seconds since epoch)
score: Search relevance score (set during search operations)
"""
id: int
channel_id: str
sender_id: str
content: str
metadata: Dict[str, Any] = None
confidence: Optional[float] = None
timestamp: Optional[float] = None
score: Optional[float] = None
search_scores: Optional[Dict[str, Any]] = None
def __post_init__(self):
"""Initialize defaults."""
if self.metadata is None:
self.metadata = {}
if self.timestamp is None:
self.timestamp = time.time()
def to_dict(self) -> Dict[str, Any]:
"""Export as dictionary."""
return asdict(self)
def get_nested(self, path: str, default=None) -> Any:
"""
Get value from nested metadata using dot notation.
Args:
path: Dot-separated path (e.g., "breadcrumbs.task")
default: Default value if path not found
Returns:
Value at path or default
"""
keys = path.split('.')
value = self.metadata
for key in keys:
if isinstance(value, dict):
value = value.get(key)
if value is None:
return default
else:
return default
return value
@dataclass
class SearchResult:
"""
Search result with scoring information.
Attributes:
message: The message object
similarity_score: Vector similarity score (0.0 to 1.0)
final_score: Combined score after ranking
scores: Detailed scoring breakdown
"""
message: Message
similarity_score: float
final_score: float
scores: Optional[Dict[str, float]] = None
def __post_init__(self):
"""Set message score."""
self.message.score = self.final_score
@dataclass
class AggregationResult:
"""
Aggregation result for grouped data.
Attributes:
value: The grouped value
count: Number of items in group
metrics: Additional computed metrics
"""
value: Any
count: int
metrics: Dict[str, Any] = None
def __post_init__(self):
"""Initialize defaults."""
if self.metrics is None:
self.metrics = {}
def to_dict(self) -> Dict[str, Any]:
"""Export as dictionary."""
return {
"value": self.value,
"count": self.count,
**self.metrics
}
@dataclass
class AgentInfo:
"""Agent information"""
name: str
project_id: Optional[str]
description: Optional[str]
status: str
dm_policy: str
discoverable: str
project_name: Optional[str] = None
dm_availability: Optional[str] = None
has_existing_dm: bool = False
class DMPolicy(Enum):
"""DM policy options for agents"""
OPEN = 'open' # Accept DMs from anyone
RESTRICTED = 'restricted' # Only from allowlist
CLOSED = 'closed' # No DMs allowed
class Discoverability(Enum):
"""Agent discoverability settings"""
PUBLIC = 'public' # Visible to all
PROJECT = 'project' # Visible in linked projects
PRIVATE = 'private' # Not discoverable
class DMPermission(Enum):
"""DM permission types"""
ALLOW = 'allow'
BLOCK = 'block'