- Verbeterde versie Selectie Specialist - voor demo (1.2)

This commit is contained in:
Josako
2025-06-16 11:06:20 +02:00
parent dbea41451a
commit 71adf64668
5 changed files with 111 additions and 24 deletions

View File

@@ -102,18 +102,11 @@ class SpecialistResult(BaseModel):
}
# Structural optional fields available for all specialists
answer: Optional[str] = Field(
None,
description="Optional textual answer from the specialist"
)
detailed_query: Optional[str] = Field(
None,
description="Optional detailed query for the specialist"
)
form_request: Optional[Dict[str, Any]] = Field(
None,
description="Optional form definition to request user input"
)
answer: Optional[str] = Field(None, description="Optional textual answer from the specialist")
detailed_query: Optional[str] = Field(None, description="Optional detailed query for the specialist")
form_request: Optional[Dict[str, Any]] = Field(None, description="Optional form definition to request user input")
phase: Optional[str] = Field(None, description="Phase of the specialist's workflow")
citations: Optional[Dict[str, Any]] = Field(None, description="Citations for the specialist's answer")
@model_validator(mode='after')
def validate_required_results(self) -> 'SpecialistResult':

View File

@@ -95,16 +95,63 @@ class SpecialistExecutor(CrewAIBaseSpecialistExecutor):
sleep(1)
self.ept.send_update(self.task_id, "Traicie Selection Specialist Processing", {"name": f"Processing Iteration {i}"})
# flow_results = asyncio.run(self.flow.kickoff_async(inputs=arguments.model_dump()))
# flow_state = self.flow.state
# results = RoleDefinitionSpecialistResult.create_for_type(self.type, self.type_version)
contact_form = cache_manager.specialist_forms_config_cache.get_config("PERSONAL_CONTACT_FORM", "1.0")
current_app.logger.debug(f"Contact form: {contact_form}")
results = SpecialistResult.create_for_type(self.type, self.type_version,
answer=f"Antwoord op uw vraag: {arguments.question}",
form_request=contact_form)
if not self._cached_session.interactions:
specialist_phase = "initial"
else:
specialist_phase = self._cached_session.interactions[-1].specialist_results.get('phase', 'initial')
self.log_tuning(f"Traicie Selection Specialist execution ended", {"Results": results.model_dump()})
results = None
match specialist_phase:
case "initial":
ko_form = form_definition = {
"type": "KO_CRITERIA_FORM",
"version": "1.0.0",
"name": "KO Criteria Form",
"icon": "verified",
"fields": {
"weekend_werk": {
"name": "Weekend Werk",
"description": "Werken in het weekend",
"context": "Ben je bereid om in het weekend te werken?",
"type": "options",
"required": True,
"allowed_values": ["Ja, geen probleem", "Nee, liever niet"]
},
"fysisch_werk": {
"name": "Fysische Activiteit",
"description": "Fysisch werken",
"context": "In onze winkels is het belangrijk dat je 8u kan rechtstaan in een iets koeler omgeving. Is dit voor jou haalbaar?",
"type": "options",
"required": True,
"allowed_values": ["Ja, prima haalbaar", "Neen, mogelijks een probleem"]
},
"nabijheid_werk": {
"name": "Nabijheid Werk",
"description": "Afstand Woon-Werk",
"context": "We hebben gemerkt dat tevreden collegas in de buurt van de winkel wonen. Hoe ver wil jij je verplaatsen?",
"type": "options",
"required": True,
"allowed_values": ["Meer dan 15 km", "Minder dan 15 km"]
},
}
}
results = SpecialistResult.create_for_type(self.type, self.type_version,
answer=f"We starten met een aantal KO Criteria vragen",
form_request=ko_form,
phase="ko_questions")
case "ko_questions":
contact_form = cache_manager.specialist_forms_config_cache.get_config("PERSONAL_CONTACT_FORM", "1.0")
results = SpecialistResult.create_for_type(self.type, self.type_version,
answer=f"We hebben de antwoorden op de KO criteria verwerkt. Je bent een geschikte kandidaat. Kan je je contactegevens doorgeven?",
form_request=contact_form,
phase="personal_contact_data")
case "personal_contact_data":
results = SpecialistResult.create_for_type(self.type, self.type_version,
answer=f"We hebben de contactgegevens verwerkt. We nemen zo snel mogelijk contact met je op.",
phase="candidate_selected")
self.log_tuning(f"Traicie Selection Specialist execution ended", {"Results": results.model_dump() if results else "No info"})
return results