feat(ai-session): add FlowPilot AI-powered troubleshooting sessions

Implements Phase 1 of the FlowPilot-First pivot — the core AI session
experience where engineers describe a problem and FlowPilot guides them
through structured diagnosis with selectable options, free-text escape
hatches, and auto-generated documentation on resolution.

Backend: AISession + AISessionStep models, FlowPilot Engine (LLM
orchestration with structured JSON output), Flow Matching Engine v1
(semantic + keyword + recency scoring), 8 API endpoints with auth,
rate limiting, and AI quota enforcement.

Frontend: Intake screen, conversational session view with sidebar,
step cards with options/actions/resolution suggestions, resolve/escalate
modals, documentation view with rating, session history integration,
and /pilot route with sidebar navigation.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
2026-03-18 14:27:36 +00:00
parent 44eb48e457
commit 5494816b06
29 changed files with 3647 additions and 5 deletions

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@@ -36,6 +36,8 @@ from .survey_response import SurveyResponse
from .survey_invite import SurveyInvite
from .kb_import import KBImport, KBImportNode
from .script_template import ScriptCategory, ScriptTemplate, ScriptGeneration
from .ai_session import AISession
from .ai_session_step import AISessionStep
from .psa_connection import PsaConnection
from .psa_post_log import PsaPostLog
from .psa_member_mapping import PsaMemberMapping
@@ -90,6 +92,8 @@ __all__ = [
"ScriptCategory",
"ScriptTemplate",
"ScriptGeneration",
"AISession",
"AISessionStep",
"PsaConnection",
"PsaPostLog",
"PsaMemberMapping",

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@@ -0,0 +1,204 @@
"""AI-powered troubleshooting session model.
Represents a complete FlowPilot interaction from intake to resolution/escalation.
This is the central entity of the FlowPilot-First pivot.
"""
import uuid
from datetime import datetime, timezone
from typing import Optional, Any, TYPE_CHECKING
from sqlalchemy import String, Text, DateTime, ForeignKey, Boolean, Integer, Float, CheckConstraint
import sqlalchemy as sa
from sqlalchemy.orm import Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID, JSONB
from app.core.database import Base
if TYPE_CHECKING:
from app.models.user import User
from app.models.team import Team
from app.models.account import Account
from app.models.tree import Tree
from app.models.psa_connection import PsaConnection
class AISession(Base):
"""A FlowPilot-guided troubleshooting session.
Lifecycle: active → resolved | escalated | abandoned
Sessions may be paused and resumed (e.g., escalation handoff).
"""
__tablename__ = "ai_sessions"
__table_args__ = (
CheckConstraint(
"intake_type IN ('free_text', 'psa_ticket', 'screenshot', 'log_paste', 'combined')",
name="ck_ai_sessions_intake_type",
),
CheckConstraint(
"status IN ('active', 'paused', 'resolved', 'escalated', 'abandoned')",
name="ck_ai_sessions_status",
),
CheckConstraint(
"confidence_tier IN ('guided', 'exploring', 'discovery')",
name="ck_ai_sessions_confidence_tier",
),
)
id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
)
user_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("users.id", ondelete="CASCADE"),
nullable=False,
index=True,
)
account_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("accounts.id", ondelete="CASCADE"),
nullable=False,
index=True,
)
team_id: Mapped[Optional[uuid.UUID]] = mapped_column(
UUID(as_uuid=True),
ForeignKey("teams.id", ondelete="SET NULL"),
nullable=True,
index=True,
)
# ── Intake ──
intake_type: Mapped[str] = mapped_column(
String(20), nullable=False, default="free_text"
)
intake_content: Mapped[dict[str, Any]] = mapped_column(
JSONB, nullable=False, default=dict,
comment="Original intake data: {text, image_urls, log_content, ticket_data}",
)
problem_summary: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="AI-generated one-line problem summary from intake",
)
problem_domain: Mapped[Optional[str]] = mapped_column(
String(100), nullable=True,
comment="Classified domain: active_directory, networking, m365, hardware, etc.",
)
# ── Session state ──
status: Mapped[str] = mapped_column(
String(20), nullable=False, default="active", index=True,
)
confidence_tier: Mapped[str] = mapped_column(
String(20), nullable=False, default="discovery",
comment="Current AI confidence: guided (>80%), exploring (40-80%), discovery (<40%)",
)
confidence_score: Mapped[float] = mapped_column(
Float, nullable=False, default=0.0,
comment="Numeric confidence 0.0-1.0 for internal tracking",
)
# ── Flow matching ──
matched_flow_id: Mapped[Optional[uuid.UUID]] = mapped_column(
UUID(as_uuid=True),
ForeignKey("trees.id", ondelete="SET NULL"),
nullable=True,
comment="If following an existing flow, which one",
)
match_score: Mapped[Optional[float]] = mapped_column(
Float, nullable=True,
comment="Similarity score of the matched flow (0.0-1.0)",
)
# ── PSA link ──
psa_ticket_id: Mapped[Optional[str]] = mapped_column(
String(100), nullable=True,
comment="External PSA ticket ID if session was started from a ticket",
)
psa_connection_id: Mapped[Optional[uuid.UUID]] = mapped_column(
UUID(as_uuid=True),
ForeignKey("psa_connections.id", ondelete="SET NULL"),
nullable=True,
)
ticket_data: Mapped[Optional[dict[str, Any]]] = mapped_column(
JSONB, nullable=True,
comment="Snapshot of PSA ticket data at session start",
)
# ── Resolution / Escalation ──
resolution_summary: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="What fixed the issue (set on resolution)",
)
resolution_action: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="The specific action/step that resolved the issue",
)
escalation_reason: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="Why escalated (set on escalation)",
)
escalation_package: Mapped[Optional[dict[str, Any]]] = mapped_column(
JSONB, nullable=True,
comment="Context package for receiving engineer: steps_tried, hypotheses, suggestions",
)
escalated_to_id: Mapped[Optional[uuid.UUID]] = mapped_column(
UUID(as_uuid=True),
ForeignKey("users.id", ondelete="SET NULL"),
nullable=True,
)
# ── Feedback ──
session_rating: Mapped[Optional[int]] = mapped_column(
Integer, nullable=True,
comment="1-5 engineer feedback rating",
)
session_feedback: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="Optional feedback text from engineer",
)
# ── AI tracking ──
total_input_tokens: Mapped[int] = mapped_column(
Integer, nullable=False, default=0,
)
total_output_tokens: Mapped[int] = mapped_column(
Integer, nullable=False, default=0,
)
step_count: Mapped[int] = mapped_column(
Integer, nullable=False, default=0,
)
# ── Timestamps ──
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)
updated_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True),
default=lambda: datetime.now(timezone.utc),
onupdate=lambda: datetime.now(timezone.utc),
)
resolved_at: Mapped[Optional[datetime]] = mapped_column(
DateTime(timezone=True), nullable=True,
)
# ── LLM conversation context ──
system_prompt_snapshot: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="Snapshot of the system prompt used (for debugging/training)",
)
conversation_messages: Mapped[list[dict[str, Any]]] = mapped_column(
JSONB, nullable=False, default=list,
comment="Full LLM message history for context continuity",
)
# ── Relationships ──
user: Mapped["User"] = relationship("User", foreign_keys=[user_id])
account: Mapped["Account"] = relationship("Account")
team: Mapped[Optional["Team"]] = relationship("Team")
matched_flow: Mapped[Optional["Tree"]] = relationship("Tree", foreign_keys=[matched_flow_id])
escalated_to: Mapped[Optional["User"]] = relationship("User", foreign_keys=[escalated_to_id])
psa_connection: Mapped[Optional["PsaConnection"]] = relationship("PsaConnection")
steps: Mapped[list["AISessionStep"]] = relationship(
"AISessionStep", back_populates="session",
cascade="all, delete-orphan",
order_by="AISessionStep.step_order",
)

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@@ -0,0 +1,133 @@
"""AI session step model.
Every interaction within an AI session is captured as a step.
Steps are the raw material that becomes flow nodes in the Knowledge Flywheel.
"""
import uuid
from datetime import datetime, timezone
from typing import Optional, Any, TYPE_CHECKING
from sqlalchemy import String, Text, DateTime, ForeignKey, Integer, Float, CheckConstraint
from sqlalchemy.orm import Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID, JSONB
from app.core.database import Base
if TYPE_CHECKING:
from app.models.ai_session import AISession
from app.models.script_template import ScriptGeneration
class AISessionStep(Base):
"""A single interaction step within a FlowPilot session.
Step types:
- question: FlowPilot asks a diagnostic question with options
- action: FlowPilot suggests an action for the engineer to perform
- script_generation: FlowPilot invokes the Script Generator
- verification: FlowPilot asks engineer to verify a condition
- info_request: FlowPilot asks engineer to gather specific data
- note: Engineer or FlowPilot adds a contextual note
- intake_analysis: Initial analysis of the intake content
"""
__tablename__ = "ai_session_steps"
__table_args__ = (
CheckConstraint(
"step_type IN ('question', 'action', 'script_generation', 'verification', "
"'info_request', 'note', 'intake_analysis')",
name="ck_ai_session_steps_step_type",
),
)
id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True), primary_key=True, default=uuid.uuid4
)
session_id: Mapped[uuid.UUID] = mapped_column(
UUID(as_uuid=True),
ForeignKey("ai_sessions.id", ondelete="CASCADE"),
nullable=False,
index=True,
)
step_order: Mapped[int] = mapped_column(
Integer, nullable=False,
comment="Sequential position in the session (0-indexed)",
)
step_type: Mapped[str] = mapped_column(
String(30), nullable=False,
)
# ── Content presented to engineer ──
content: Mapped[dict[str, Any]] = mapped_column(
JSONB, nullable=False, default=dict,
comment="The question/action content rendered in the session UI",
)
context_message: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="Why FlowPilot is asking this (shown above the question)",
)
# ── Options (for question steps) ──
options_presented: Mapped[Optional[list[dict[str, Any]]]] = mapped_column(
JSONB, nullable=True,
comment="Array of {label, value, followup_hint} options shown to engineer",
)
# ── Engineer response ──
selected_option: Mapped[Optional[str]] = mapped_column(
String(500), nullable=True,
comment="Which option the engineer selected (value field)",
)
free_text_input: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="If engineer typed a custom response instead of selecting an option",
)
was_free_text: Mapped[bool] = mapped_column(
default=False,
comment="True if the engineer used the free-text escape hatch",
)
was_skipped: Mapped[bool] = mapped_column(
default=False,
comment="True if engineer selected 'I don't know / Can't check'",
)
# ── Action results ──
action_result: Mapped[Optional[dict[str, Any]]] = mapped_column(
JSONB, nullable=True,
comment="Outcome of action step: {success: bool, details: str, next_hint: str}",
)
# ── Script generation link ──
script_generation_id: Mapped[Optional[uuid.UUID]] = mapped_column(
UUID(as_uuid=True),
ForeignKey("script_generations.id", ondelete="SET NULL"),
nullable=True,
)
# ── AI internals ──
confidence_at_step: Mapped[float] = mapped_column(
Float, nullable=False, default=0.0,
comment="FlowPilot confidence level at this point (0.0-1.0)",
)
ai_reasoning: Mapped[Optional[str]] = mapped_column(
Text, nullable=True,
comment="Why FlowPilot chose this step (internal, for debugging/training)",
)
input_tokens: Mapped[int] = mapped_column(
Integer, nullable=False, default=0,
)
output_tokens: Mapped[int] = mapped_column(
Integer, nullable=False, default=0,
)
# ── Timestamps ──
created_at: Mapped[datetime] = mapped_column(
DateTime(timezone=True), default=lambda: datetime.now(timezone.utc)
)
responded_at: Mapped[Optional[datetime]] = mapped_column(
DateTime(timezone=True), nullable=True,
comment="When the engineer responded to this step",
)
# ── Relationships ──
session: Mapped["AISession"] = relationship("AISession", back_populates="steps")
script_generation: Mapped[Optional["ScriptGeneration"]] = relationship("ScriptGeneration")

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@@ -1,7 +1,7 @@
import uuid
from datetime import datetime, timezone
from typing import Optional, Any, TYPE_CHECKING
from sqlalchemy import String, Text, DateTime, ForeignKey, Boolean, Integer, Index, CheckConstraint
from sqlalchemy import String, Text, DateTime, ForeignKey, Boolean, Integer, Float, Index, CheckConstraint
from sqlalchemy.orm import Mapped, mapped_column, relationship
from sqlalchemy.dialects.postgresql import UUID, JSONB
from app.core.database import Base
@@ -161,6 +161,25 @@ class Tree(Base):
comment="Provenance metadata from .rfflow file import"
)
# Flow matching (FlowPilot AI sessions)
origin: Mapped[Optional[str]] = mapped_column(
String(20), nullable=True,
comment="manual | ai_generated | ai_enhanced"
)
source_session_id: Mapped[Optional[uuid.UUID]] = mapped_column(
UUID(as_uuid=True), nullable=True,
)
match_keywords: Mapped[Optional[list[Any]]] = mapped_column(
JSONB, nullable=True,
comment="Keywords for FlowPilot flow matching"
)
success_rate: Mapped[Optional[float]] = mapped_column(
Float, nullable=True,
)
last_matched_at: Mapped[Optional[datetime]] = mapped_column(
DateTime(timezone=True), nullable=True,
)
# Relationships
author: Mapped[Optional["User"]] = relationship("User", foreign_keys=[author_id], back_populates="trees")
team: Mapped[Optional["Team"]] = relationship("Team", back_populates="trees")