Files
AutoGPT/autogpt_platform/backend/backend/data/understanding.py
Ubbe 995dd1b5f3 feat(platform): replace suggestion pills with themed prompt categories (#12515)
## Summary

<img width="700" height="575" alt="Screenshot 2026-03-23 at 21 40 07"
src="https://github.com/user-attachments/assets/f6138c63-dd5e-4bde-a2e4-7434d0d3ec72"
/>

Re-applies #12452 which was reverted as collateral in #12485 (invite
system revert).

Replaces the flat list of suggestion pills in the CoPilot empty session
with themed prompt categories (Learn, Create, Automate, Organize), each
shown as a popover with contextual prompts.

- **Backend**: Adds `suggested_prompts` as a themed `dict[str,
list[str]]` keyed by category. Updates Tally extraction LLM prompt to
generate prompts per theme, and the `/suggested-prompts` API to return
grouped themes. Legacy `list[str]` rows are preserved under a
`"General"` key for backward compatibility.
- **Frontend**: Replaces inline pill buttons with a `SuggestionThemes`
popover component. Each theme button (with icon) opens a dropdown of 5
relevant prompts. Falls back to hardcoded defaults when the API has no
personalized prompts. Normalizes partial API responses by padding
missing themes with defaults. Legacy `"General"` prompts are distributed
round-robin across themes.

### Changes 🏗️

- `backend/data/understanding.py`: `suggested_prompts` field added as
`dict[str, list[str]]`; legacy list rows preserved under `"General"` key
via `_json_to_themed_prompts`
- `backend/data/tally.py`: LLM prompt updated to generate themed
prompts; validation now per-theme with blank-string rejection
- `backend/api/features/chat/routes.py`: New `SuggestedTheme` model;
endpoint returns `themes[]`
- `frontend/copilot/components/EmptySession/EmptySession.tsx`: Uses
generated API hooks for suggested prompts
- `frontend/copilot/components/EmptySession/helpers.ts`:
`DEFAULT_THEMES` replaces `DEFAULT_QUICK_ACTIONS`; `getSuggestionThemes`
normalizes partial API responses
-
`frontend/copilot/components/EmptySession/components/SuggestionThemes/`:
New popover component with theme icons and loading states

### Checklist 📋

- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  - [x] Verify themed suggestion buttons render on CoPilot empty session
  - [x] Click each theme button and confirm popover opens with prompts
  - [x] Click a prompt and confirm it sends the message
- [x] Verify fallback to default themes when API returns no custom
prompts
- [x] Verify legacy users' personalized prompts are preserved and
visible

🤖 Generated with [Claude Code](https://claude.com/claude-code)

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
2026-03-25 15:32:49 +08:00

474 lines
16 KiB
Python

"""Data models and access layer for user business understanding."""
import logging
from datetime import datetime
from typing import Any, Optional, cast
import pydantic
from prisma.models import CoPilotUnderstanding
from backend.data.redis_client import get_redis_async
from backend.util.json import SafeJson
logger = logging.getLogger(__name__)
# Cache configuration
CACHE_KEY_PREFIX = "understanding"
CACHE_TTL_SECONDS = 48 * 60 * 60 # 48 hours
def _cache_key(user_id: str) -> str:
"""Generate cache key for user business understanding."""
return f"{CACHE_KEY_PREFIX}:{user_id}"
def _json_to_list(value: Any) -> list[str]:
"""Convert Json field to list[str], handling None.
Also handles legacy dict-format rows (e.g. ``{"Learn": [...], "Create": [...]}``
from the reverted themed-prompts feature) by flattening all values into a single
list so existing personalised data isn't silently lost.
"""
if value is None:
return []
if isinstance(value, list):
return cast(list[str], value)
if isinstance(value, dict):
# Legacy themed-prompt format: flatten all string values from all categories.
logger.debug(
"_json_to_list: flattening legacy dict-format value (keys=%s)",
list(value.keys()),
)
return [
item
for vals in value.values()
if isinstance(vals, list)
for item in vals
if isinstance(item, str)
]
return []
def _json_to_themed_prompts(value: Any) -> dict[str, list[str]]:
"""Convert Json field to themed prompts dict.
Handles both the new ``dict[str, list[str]]`` format and the legacy
``list[str]`` format. Legacy rows are placed under a ``"General"`` key so
existing personalised prompts remain readable until a backfill regenerates
them into the proper themed shape.
"""
if isinstance(value, dict):
return {
k: [i for i in v if isinstance(i, str)]
for k, v in value.items()
if isinstance(k, str) and isinstance(v, list)
}
if isinstance(value, list) and value:
return {"General": [str(p) for p in value if isinstance(p, str)]}
return {}
class BusinessUnderstandingInput(pydantic.BaseModel):
"""Input model for updating business understanding - all fields optional for incremental updates."""
# User info
user_name: Optional[str] = pydantic.Field(None, description="The user's name")
job_title: Optional[str] = pydantic.Field(None, description="The user's job title")
# Business basics
business_name: Optional[str] = pydantic.Field(
None, description="Name of the user's business"
)
industry: Optional[str] = pydantic.Field(None, description="Industry or sector")
business_size: Optional[str] = pydantic.Field(
None, description="Company size (e.g., '1-10', '11-50')"
)
user_role: Optional[str] = pydantic.Field(
None,
description="User's role in the organization (e.g., 'decision maker', 'implementer')",
)
# Processes & activities
key_workflows: Optional[list[str]] = pydantic.Field(
None, description="Key business workflows"
)
daily_activities: Optional[list[str]] = pydantic.Field(
None, description="Daily activities performed"
)
# Pain points & goals
pain_points: Optional[list[str]] = pydantic.Field(
None, description="Current pain points"
)
bottlenecks: Optional[list[str]] = pydantic.Field(
None, description="Process bottlenecks"
)
manual_tasks: Optional[list[str]] = pydantic.Field(
None, description="Manual/repetitive tasks"
)
automation_goals: Optional[list[str]] = pydantic.Field(
None, description="Desired automation goals"
)
# Current tools
current_software: Optional[list[str]] = pydantic.Field(
None, description="Software/tools currently used"
)
existing_automation: Optional[list[str]] = pydantic.Field(
None, description="Existing automations"
)
# Additional context
additional_notes: Optional[str] = pydantic.Field(
None, description="Any additional context"
)
# Suggested prompts (UI-only, not included in system prompt)
suggested_prompts: Optional[dict[str, list[str]]] = pydantic.Field(
None, description="LLM-generated suggested prompts grouped by theme"
)
class BusinessUnderstanding(pydantic.BaseModel):
"""Full business understanding model returned from database."""
id: str
user_id: str
created_at: datetime
updated_at: datetime
# User info
user_name: Optional[str] = None
job_title: Optional[str] = None
# Business basics
business_name: Optional[str] = None
industry: Optional[str] = None
business_size: Optional[str] = None
user_role: Optional[str] = None
# Processes & activities
key_workflows: list[str] = pydantic.Field(default_factory=list)
daily_activities: list[str] = pydantic.Field(default_factory=list)
# Pain points & goals
pain_points: list[str] = pydantic.Field(default_factory=list)
bottlenecks: list[str] = pydantic.Field(default_factory=list)
manual_tasks: list[str] = pydantic.Field(default_factory=list)
automation_goals: list[str] = pydantic.Field(default_factory=list)
# Current tools
current_software: list[str] = pydantic.Field(default_factory=list)
existing_automation: list[str] = pydantic.Field(default_factory=list)
# Additional context
additional_notes: Optional[str] = None
# Suggested prompts (UI-only, not included in system prompt)
suggested_prompts: dict[str, list[str]] = pydantic.Field(default_factory=dict)
@classmethod
def from_db(cls, db_record: CoPilotUnderstanding) -> "BusinessUnderstanding":
"""Convert database record to Pydantic model."""
data = db_record.data if isinstance(db_record.data, dict) else {}
business = (
data.get("business", {}) if isinstance(data.get("business"), dict) else {}
)
return cls(
id=db_record.id,
user_id=db_record.userId,
created_at=db_record.createdAt,
updated_at=db_record.updatedAt,
user_name=data.get("name"),
job_title=business.get("job_title"),
business_name=business.get("business_name"),
industry=business.get("industry"),
business_size=business.get("business_size"),
user_role=business.get("user_role"),
key_workflows=_json_to_list(business.get("key_workflows")),
daily_activities=_json_to_list(business.get("daily_activities")),
pain_points=_json_to_list(business.get("pain_points")),
bottlenecks=_json_to_list(business.get("bottlenecks")),
manual_tasks=_json_to_list(business.get("manual_tasks")),
automation_goals=_json_to_list(business.get("automation_goals")),
current_software=_json_to_list(business.get("current_software")),
existing_automation=_json_to_list(business.get("existing_automation")),
additional_notes=business.get("additional_notes"),
suggested_prompts=_json_to_themed_prompts(data.get("suggested_prompts")),
)
def _merge_lists(existing: list | None, new: list | None) -> list | None:
"""Merge two lists, removing duplicates while preserving order."""
if new is None:
return existing
if existing is None:
return new
# Preserve order, add new items that don't exist
merged = list(existing)
for item in new:
if item not in merged:
merged.append(item)
return merged
async def _get_from_cache(user_id: str) -> Optional[BusinessUnderstanding]:
"""Get business understanding from Redis cache."""
try:
redis = await get_redis_async()
cached_data = await redis.get(_cache_key(user_id))
if cached_data:
return BusinessUnderstanding.model_validate_json(cached_data)
except Exception as e:
logger.warning(f"Failed to get understanding from cache: {e}")
return None
async def _set_cache(user_id: str, understanding: BusinessUnderstanding) -> None:
"""Set business understanding in Redis cache with TTL."""
try:
redis = await get_redis_async()
await redis.setex(
_cache_key(user_id),
CACHE_TTL_SECONDS,
understanding.model_dump_json(),
)
except Exception as e:
logger.warning(f"Failed to set understanding in cache: {e}")
async def _delete_cache(user_id: str) -> None:
"""Delete business understanding from Redis cache."""
try:
redis = await get_redis_async()
await redis.delete(_cache_key(user_id))
except Exception as e:
logger.warning(f"Failed to delete understanding from cache: {e}")
async def get_business_understanding(
user_id: str,
) -> Optional[BusinessUnderstanding]:
"""Get the business understanding for a user.
Checks cache first, falls back to database if not cached.
Results are cached for 48 hours.
"""
# Try cache first
cached = await _get_from_cache(user_id)
if cached:
logger.debug(f"Business understanding cache hit for user {user_id}")
return cached
# Cache miss - load from database
logger.debug(f"Business understanding cache miss for user {user_id}")
record = await CoPilotUnderstanding.prisma().find_unique(where={"userId": user_id})
if record is None:
return None
understanding = BusinessUnderstanding.from_db(record)
# Store in cache for next time
await _set_cache(user_id, understanding)
return understanding
def merge_business_understanding_data(
existing_data: dict[str, Any],
input_data: BusinessUnderstandingInput,
) -> dict[str, Any]:
"""Merge new input into existing data dict using incremental strategy.
- String fields: new value overwrites if provided (not None)
- List fields: new items are appended to existing (deduplicated)
- suggested_prompts: fully replaced if provided (not None)
Returns the merged data dict (mutates and returns *existing_data*).
"""
existing_business: dict[str, Any] = {}
if isinstance(existing_data.get("business"), dict):
existing_business = dict(existing_data["business"])
business_string_fields = [
"job_title",
"business_name",
"industry",
"business_size",
"user_role",
"additional_notes",
]
business_list_fields = [
"key_workflows",
"daily_activities",
"pain_points",
"bottlenecks",
"manual_tasks",
"automation_goals",
"current_software",
"existing_automation",
]
# Handle top-level name field
if input_data.user_name is not None:
existing_data["name"] = input_data.user_name
# Business string fields - overwrite if provided
for field in business_string_fields:
value = getattr(input_data, field)
if value is not None:
existing_business[field] = value
# Business list fields - merge with existing
for field in business_list_fields:
value = getattr(input_data, field)
if value is not None:
existing_list = _json_to_list(existing_business.get(field))
merged = _merge_lists(existing_list, value)
existing_business[field] = merged
# Suggested prompts - fully replace if provided
if input_data.suggested_prompts is not None:
existing_data["suggested_prompts"] = input_data.suggested_prompts
# Set version and nest business data
existing_business["version"] = 1
existing_data["business"] = existing_business
return existing_data
async def upsert_business_understanding(
user_id: str,
input_data: BusinessUnderstandingInput,
) -> BusinessUnderstanding:
"""
Create or update business understanding with incremental merge strategy.
- String fields: new value overwrites if provided (not None)
- List fields: new items are appended to existing (deduplicated)
- suggested_prompts: fully replaced if provided (not None)
Data is stored as: {name: ..., business: {version: 1, ...}}
"""
# Get existing record for merge
existing = await CoPilotUnderstanding.prisma().find_unique(
where={"userId": user_id}
)
# Get existing data structure or start fresh
existing_data: dict[str, Any] = {}
if existing and isinstance(existing.data, dict):
existing_data = dict(existing.data)
merged_data = merge_business_understanding_data(existing_data, input_data)
# Upsert with the merged data
record = await CoPilotUnderstanding.prisma().upsert(
where={"userId": user_id},
data={
"create": {"userId": user_id, "data": SafeJson(merged_data)},
"update": {"data": SafeJson(merged_data)},
},
)
understanding = BusinessUnderstanding.from_db(record)
# Update cache with new understanding
await _set_cache(user_id, understanding)
return understanding
async def clear_business_understanding(user_id: str) -> bool:
"""Clear/delete business understanding for a user from both DB and cache."""
# Delete from cache first
await _delete_cache(user_id)
try:
await CoPilotUnderstanding.prisma().delete(where={"userId": user_id})
return True
except Exception:
# Record might not exist
return False
def format_understanding_for_prompt(understanding: BusinessUnderstanding) -> str:
"""Format business understanding as text for system prompt injection."""
if not understanding:
return ""
sections = []
# User info section
user_info = []
if understanding.user_name:
user_info.append(f"Name: {understanding.user_name}")
if understanding.job_title:
user_info.append(f"Job Title: {understanding.job_title}")
if user_info:
sections.append("## User\n" + "\n".join(user_info))
# Business section
business_info = []
if understanding.business_name:
business_info.append(f"Company: {understanding.business_name}")
if understanding.industry:
business_info.append(f"Industry: {understanding.industry}")
if understanding.business_size:
business_info.append(f"Size: {understanding.business_size}")
if understanding.user_role:
business_info.append(f"Role Context: {understanding.user_role}")
if business_info:
sections.append("## Business\n" + "\n".join(business_info))
# Processes section
processes = []
if understanding.key_workflows:
processes.append(f"Key Workflows: {', '.join(understanding.key_workflows)}")
if understanding.daily_activities:
processes.append(
f"Daily Activities: {', '.join(understanding.daily_activities)}"
)
if processes:
sections.append("## Processes\n" + "\n".join(processes))
# Pain points section
pain_points = []
if understanding.pain_points:
pain_points.append(f"Pain Points: {', '.join(understanding.pain_points)}")
if understanding.bottlenecks:
pain_points.append(f"Bottlenecks: {', '.join(understanding.bottlenecks)}")
if understanding.manual_tasks:
pain_points.append(f"Manual Tasks: {', '.join(understanding.manual_tasks)}")
if pain_points:
sections.append("## Pain Points\n" + "\n".join(pain_points))
# Goals section
if understanding.automation_goals:
sections.append(
"## Automation Goals\n"
+ "\n".join(f"- {goal}" for goal in understanding.automation_goals)
)
# Current tools section
tools_info = []
if understanding.current_software:
tools_info.append(
f"Current Software: {', '.join(understanding.current_software)}"
)
if understanding.existing_automation:
tools_info.append(
f"Existing Automation: {', '.join(understanding.existing_automation)}"
)
if tools_info:
sections.append("## Current Tools\n" + "\n".join(tools_info))
# Additional notes
if understanding.additional_notes:
sections.append(f"## Additional Context\n{understanding.additional_notes}")
if not sections:
return ""
return "# User Business Context\n\n" + "\n\n".join(sections)