feat: add ResolutionOutputGenerator with three-output generation

Adds ResolutionOutputGenerator service that generates PSA ticket notes,
knowledge base article draft, and client summary on session resolve, plus
integration tests for generate_all and edit_output.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
chihlasm
2026-03-24 08:46:29 +00:00
parent 9d2a8332aa
commit 5f3169bad4
2 changed files with 195 additions and 0 deletions

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"""Resolution output generator — three deliverables on session resolve."""
import logging
from typing import Any
from uuid import UUID
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.models.ai_session import AISession
from app.models.session_resolution_output import SessionResolutionOutput
from app.services.assistant_chat_service import _call_ai
logger = logging.getLogger(__name__)
RESOLUTION_MODEL = "claude-sonnet-4-6"
class ResolutionOutputGenerator:
def __init__(self, db: AsyncSession):
self.db = db
async def generate_all(self, session_id: UUID) -> list[SessionResolutionOutput]:
result = await self.db.execute(
select(AISession).where(AISession.id == session_id)
)
session = result.scalar_one_or_none()
if not session:
raise ValueError(f"Session {session_id} not found")
context = self._build_session_context(session)
outputs = []
for output_type, prompt in [
("psa_ticket_notes", self._psa_notes_prompt(context)),
("knowledge_base", self._kb_article_prompt(context)),
("client_summary", self._client_summary_prompt(context)),
]:
content, _, _ = await _call_ai(
system_base="You are a technical documentation assistant for MSP teams.",
rag_context="",
history=[],
new_message=prompt,
max_tokens=2048,
)
output = SessionResolutionOutput(
session_id=session_id,
output_type=output_type,
generated_content=content,
status="draft",
generated_by_model=RESOLUTION_MODEL,
)
self.db.add(output)
outputs.append(output)
await self.db.flush()
return outputs
async def edit_output(self, output_id: UUID, edited_content: str) -> SessionResolutionOutput:
result = await self.db.execute(
select(SessionResolutionOutput).where(SessionResolutionOutput.id == output_id)
)
output = result.scalar_one_or_none()
if not output:
raise ValueError(f"Output {output_id} not found")
output.edited_content = edited_content
await self.db.flush()
return output
async def push_output(self, output_id: UUID, destination: str) -> SessionResolutionOutput:
result = await self.db.execute(
select(SessionResolutionOutput).where(SessionResolutionOutput.id == output_id)
)
output = result.scalar_one_or_none()
if not output:
raise ValueError(f"Output {output_id} not found")
from datetime import datetime, timezone
output.status = "pushed"
output.pushed_to = destination
output.pushed_at = datetime.now(timezone.utc)
await self.db.flush()
return output
def _build_session_context(self, session: AISession) -> str:
parts = [
f"Problem: {session.problem_summary or 'Unknown'}",
f"Domain: {session.problem_domain or 'Unknown'}",
f"Resolution: {session.resolution_summary or 'Not specified'}",
f"Steps taken: {session.step_count}",
]
msgs = session.conversation_messages or []
if msgs:
parts.append("\nConversation highlights:")
for msg in msgs[-10:]:
role = msg.get("role", "unknown")
content = msg.get("content", "")[:200]
parts.append(f" [{role}]: {content}")
return "\n".join(parts)
def _psa_notes_prompt(self, context: str) -> str:
return (
f"Generate professional PSA ticket notes for this resolved troubleshooting session.\n"
f"Format as structured markdown with: Problem, Diagnostic Steps, Resolution, Recommendations.\n\n{context}"
)
def _kb_article_prompt(self, context: str) -> str:
return (
f"Generate a knowledge base article draft from this resolved session.\n"
f"Include: Symptoms, Root Cause, Resolution Steps, Things to Rule Out First.\n\n{context}"
)
def _client_summary_prompt(self, context: str) -> str:
return (
f"Generate a non-technical summary for the end user/client.\n"
f"Explain what was wrong and what was done to fix it in plain language.\n"
f"No jargon. 2-3 paragraphs max.\n\n{context}"
)

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"""Integration tests for ResolutionOutputGenerator."""
import pytest
from unittest.mock import AsyncMock, patch
from httpx import AsyncClient
from app.models.ai_session import AISession
from app.models.session_resolution_output import SessionResolutionOutput
@pytest.mark.asyncio
@patch("app.services.resolution_output_generator._call_ai")
async def test_generate_all_creates_three_outputs(
mock_call_ai, client: AsyncClient, test_user, auth_headers, test_db
):
"""generate_all creates PSA notes, KB article, and client summary."""
mock_call_ai.return_value = ("Generated content here", 100, 50)
session = AISession(
user_id=test_user["user_data"]["id"],
account_id=test_user["user_data"]["account_id"],
session_type="guided",
intake_type="free_text",
intake_content={"text": "test"},
status="resolved",
confidence_tier="guided",
conversation_messages=[
{"role": "user", "content": "DNS not working"},
{"role": "assistant", "content": "Fixed by flushing DNS cache"},
],
resolution_summary="Flushed DNS cache",
)
test_db.add(session)
await test_db.flush()
from app.services.resolution_output_generator import ResolutionOutputGenerator
gen = ResolutionOutputGenerator(test_db)
outputs = await gen.generate_all(session.id)
assert len(outputs) == 3
types = {o.output_type for o in outputs}
assert types == {"psa_ticket_notes", "knowledge_base", "client_summary"}
assert all(o.status == "draft" for o in outputs)
assert mock_call_ai.call_count == 3
@pytest.mark.asyncio
async def test_edit_output(client: AsyncClient, test_user, auth_headers, test_db):
"""Editing an output stores edited_content."""
session = AISession(
user_id=test_user["user_data"]["id"],
account_id=test_user["user_data"]["account_id"],
session_type="guided",
intake_type="free_text",
intake_content={"text": "test"},
status="resolved",
confidence_tier="guided",
conversation_messages=[],
resolution_summary="Fixed it",
)
test_db.add(session)
await test_db.flush()
output = SessionResolutionOutput(
session_id=session.id,
output_type="psa_ticket_notes",
generated_content="Original notes",
status="draft",
generated_by_model="claude-sonnet-4-6",
)
test_db.add(output)
await test_db.flush()
from app.services.resolution_output_generator import ResolutionOutputGenerator
gen = ResolutionOutputGenerator(test_db)
edited = await gen.edit_output(output.id, "My edited notes")
assert edited.edited_content == "My edited notes"