155 lines
6.0 KiB
Python
155 lines
6.0 KiB
Python
"""
|
|
Copyright 2024-2026 ReplyPier
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License");
|
|
you may not use this file except in compliance with the License.
|
|
You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software
|
|
distributed under the License is distributed on an "AS IS" BASIS,
|
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
See the License for the specific language governing permissions and
|
|
limitations under the License.
|
|
"""
|
|
|
|
from typing import List, Optional
|
|
|
|
from pydantic import BaseModel, Field
|
|
|
|
|
|
class TriageResult(BaseModel):
|
|
"""Structured output of the AI triage pass over a new ticket."""
|
|
# Rewritten, clearer title. The original is preserved on the ticket.
|
|
title: str = Field(max_length=500)
|
|
priority: str = Field(description="urgent, high, medium or low")
|
|
severity: Optional[int] = Field(default=None, ge=1, le=3)
|
|
# Short intent classification, e.g. "billing_issue", "bug_report",
|
|
# "feature_request", "account_access", "outage".
|
|
intent: str = Field(max_length=100)
|
|
# 1-3 sentence internal summary of the issue.
|
|
summary: str = Field(max_length=2000)
|
|
# ["payments", "ledger"] — up to two short lowercase topic tags.
|
|
tags: List[str] = Field(default_factory=list, max_length=3)
|
|
confidence: float = Field(ge=0.0, le=1.0)
|
|
|
|
|
|
class HypothesisSpec(BaseModel):
|
|
"""One proposed root-cause hypothesis, before testing."""
|
|
title: str = Field(max_length=300)
|
|
rationale: str = Field(max_length=2000)
|
|
|
|
|
|
class HypothesisPlan(BaseModel):
|
|
"""Output of the hypothesis-generation step (H1..Hn, most likely first)."""
|
|
hypotheses: List[HypothesisSpec] = Field(min_length=1, max_length=5)
|
|
|
|
|
|
class HypothesisVerdict(BaseModel):
|
|
"""Outcome of testing a single hypothesis with bounded tool calls."""
|
|
status: str = Field(description="validated, invalidated or inconclusive")
|
|
confidence: float = Field(ge=0.0, le=1.0)
|
|
# What the evidence showed, citing the queries/results that decided it.
|
|
conclusion: str = Field(max_length=4000)
|
|
|
|
|
|
class RCATimelineEntry(BaseModel):
|
|
time: str = Field(max_length=100)
|
|
event: str = Field(max_length=500)
|
|
|
|
|
|
class RCAResult(BaseModel):
|
|
"""Structured root-cause analysis synthesized from the tested hypotheses
|
|
and captured evidence."""
|
|
summary: str = Field(max_length=4000)
|
|
impact: Optional[str] = Field(default=None, max_length=4000)
|
|
timeline: List[RCATimelineEntry] = Field(default_factory=list, max_length=20)
|
|
investigation_log: Optional[str] = Field(default=None, max_length=6000)
|
|
contributing_factors: List[str] = Field(default_factory=list, max_length=10)
|
|
# Must cite hypotheses inline, e.g. "[H1 · 0.92]".
|
|
conclusion: str = Field(max_length=6000)
|
|
remediation: Optional[str] = Field(default=None, max_length=4000)
|
|
prevention: Optional[str] = Field(default=None, max_length=4000)
|
|
# Plain-language section a human reviews and sends to the customer.
|
|
customer_summary: str = Field(max_length=4000)
|
|
confidence: float = Field(ge=0.0, le=1.0)
|
|
|
|
|
|
TRIAGE_JSON_TOOL_SCHEMA = {
|
|
"type": "object",
|
|
"properties": {
|
|
"title": {"type": "string", "description": "Clear, specific rewritten title."},
|
|
"priority": {"type": "string", "enum": ["urgent", "high", "medium", "low"]},
|
|
"severity": {"type": "integer", "minimum": 1, "maximum": 3},
|
|
"intent": {"type": "string", "description": "Short intent slug, e.g. bug_report."},
|
|
"summary": {"type": "string", "description": "1-3 sentence internal summary."},
|
|
"tags": {"type": "array", "items": {"type": "string"}, "description": "Up to two short lowercase topic tags."},
|
|
"confidence": {"type": "number", "minimum": 0, "maximum": 1},
|
|
},
|
|
"required": ["title", "priority", "intent", "summary", "confidence"],
|
|
"additionalProperties": False,
|
|
}
|
|
|
|
|
|
HYPOTHESES_JSON_TOOL_SCHEMA = {
|
|
"type": "object",
|
|
"properties": {
|
|
"hypotheses": {
|
|
"type": "array",
|
|
"minItems": 1,
|
|
"maxItems": 5,
|
|
"items": {
|
|
"type": "object",
|
|
"properties": {
|
|
"title": {"type": "string", "description": "Short testable hypothesis."},
|
|
"rationale": {"type": "string", "description": "Why this is suspected and what evidence would confirm it."},
|
|
},
|
|
"required": ["title", "rationale"],
|
|
"additionalProperties": False,
|
|
},
|
|
},
|
|
},
|
|
"required": ["hypotheses"],
|
|
"additionalProperties": False,
|
|
}
|
|
|
|
|
|
VERDICT_JSON_TOOL_SCHEMA = {
|
|
"type": "object",
|
|
"properties": {
|
|
"status": {"type": "string", "enum": ["validated", "invalidated", "inconclusive"]},
|
|
"confidence": {"type": "number", "minimum": 0, "maximum": 1},
|
|
"conclusion": {"type": "string", "description": "What the evidence showed, citing queries/results."},
|
|
},
|
|
"required": ["status", "confidence", "conclusion"],
|
|
"additionalProperties": False,
|
|
}
|
|
|
|
|
|
RCA_JSON_TOOL_SCHEMA = {
|
|
"type": "object",
|
|
"properties": {
|
|
"summary": {"type": "string"},
|
|
"impact": {"type": "string"},
|
|
"timeline": {
|
|
"type": "array",
|
|
"items": {
|
|
"type": "object",
|
|
"properties": {"time": {"type": "string"}, "event": {"type": "string"}},
|
|
"required": ["time", "event"],
|
|
"additionalProperties": False,
|
|
},
|
|
},
|
|
"investigation_log": {"type": "string"},
|
|
"contributing_factors": {"type": "array", "items": {"type": "string"}},
|
|
"conclusion": {"type": "string", "description": "Cites hypotheses inline, e.g. [H1 · 0.92]."},
|
|
"remediation": {"type": "string"},
|
|
"prevention": {"type": "string"},
|
|
"customer_summary": {"type": "string", "description": "Plain language for the customer."},
|
|
"confidence": {"type": "number", "minimum": 0, "maximum": 1},
|
|
},
|
|
"required": ["summary", "conclusion", "customer_summary", "confidence"],
|
|
"additionalProperties": False,
|
|
}
|