- Bug fixes

- TRAICIE_KO_INTERVIEW_DEFINITION spacialist updated to new version
- Edit Document Version now includes Catalog Tagging Fields
- eveai_ordered_list_editor no longer includes Expand Button & Add Row doesn't submit
- Active Period was not correctly returned in some cases in the license_period_services.py
- Partner menu removed if not Super User

common/services/entitlements/license_period_services.py

@@ -71,6 +71,8 @@ class LicensePeriodServices:
                             delta = abs(current_date - license_period.period_start)
                             if delta > timedelta(days=current_app.config.get('ENTITLEMENTS_MAX_PENDING_DAYS', 5)):
                                 raise EveAIPendingLicensePeriod()
+                            else:
+                                return license_period
                     case PeriodStatus.ACTIVE:
                         return license_period
             else:

config/type_defs/processor_types.py

@@ -10,11 +10,6 @@ PROCESSOR_TYPES = {
         "description": "A Processor for PDF files",
         "file_types": "pdf",
     },
-    "AUDIO_PROCESSOR": {
-        "name": "AUDIO Processor",
-        "description": "A Processor for audio files",
-        "file_types": "mp3, mp4, ogg",
-    },
     "MARKDOWN_PROCESSOR": {
         "name": "Markdown Processor",
         "description": "A Processor for markdown files",

content/changelog/1.0/1.0.0.md

@@ -5,7 +5,19 @@ All notable changes to EveAI will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [2.3.12]
+## [3.0.0-beta]
+
+### Added
+- Mobile Support for the chat client.
+- Additional visual clues for chatbot and human messages in the chat client
+
+### Changed
+- Additional visual clues for chatbot and human messages in the chat client
+- Adaptation (new version) of TRAICIE_SELECTION_SPECIALIST to further humanise interactions with end users. (Introduction of an additional interview phase to allow divergence from the interview scenario for normal questions, and convergence to the interview scenario.
+- Humanisation of cached interaction messages (random choice)
+- Adding specialist configuration information to be added as arguments for retrievers
+
+## [2.3.12-alfa]
 
 ### Added
 - Modal display of privacy statement and terms & conditions documents in eveai_Chat_client

eveai_app/templates/eveai_ordered_list_editor.html

@@ -79,8 +79,10 @@ window.EveAI.OrderedListEditors = {
             // Add row button
             const addRowBtn = document.createElement('button');
             addRowBtn.className = 'btn btn-sm btn-primary mt-2';
+            addRowBtn.type = 'button'; // Deze regel toevoegen om submit te voorkomen
             addRowBtn.innerHTML = 'Add Row';
-            addRowBtn.addEventListener('click', () => {
+            addRowBtn.addEventListener('click', (e) => {
+                e.preventDefault(); // Extra veiligheid om submit te voorkomen
                 const newRow = {};
                 // Create empty row with default values
                 Object.entries(listTypeConfig).forEach(([key, field]) => {
@@ -93,27 +95,9 @@ window.EveAI.OrderedListEditors = {
                 table.addRow(newRow);
                 this._updateTextarea(containerId, table);
             });
+
             container.parentNode.insertBefore(addRowBtn, container.nextSibling);
 
-            // Add explode button for fullscreen mode
-            const explodeBtn = document.createElement('button');
-            explodeBtn.className = 'btn btn-sm btn-secondary mt-2 ms-2';
-            explodeBtn.innerHTML = '<i class="material-icons">fullscreen</i> Expand';
-            explodeBtn.addEventListener('click', () => {
-                container.classList.toggle('fullscreen-mode');
-
-                // Update button text based on current state
-                if (container.classList.contains('fullscreen-mode')) {
-                    explodeBtn.innerHTML = '<i class="material-icons">fullscreen_exit</i> Collapse';
-                } else {
-                    explodeBtn.innerHTML = '<i class="material-icons">fullscreen</i> Expand';
-                }
-
-                // Redraw table to adjust to new size
-                table.redraw(true);
-            });
-            container.parentNode.insertBefore(explodeBtn, addRowBtn.nextSibling);
-
             // Store instance
             this.instances[containerId] = {
                 table: table,

eveai_app/templates/navbar.html

@@ -78,7 +78,7 @@
                                     {'name': 'Users', 'url': '/user/view_users', 'roles': ['Super User', 'Partner Admin', 'Tenant Admin']},
                                 ]) }}
                             {% endif %}
-                            {% if current_user.is_authenticated %}
+                            {% if current_user.is_authenticated and current_user.has_roles('Super User') %}
                                 {% set partner_menu_items = [
                                     {'name': 'Partners', 'url': '/partner/partners', 'roles': ['Super User']},
                                     {'name': 'Partner Services', 'url': '/partner/partner_services', 'roles': ['Super User']}

eveai_app/views/document_views.py

@@ -15,8 +15,8 @@ from common.models.document import Document, DocumentVersion, Catalog, Retriever
 from common.extensions import db, cache_manager, minio_client
 from common.models.interaction import Specialist, SpecialistRetriever
 from common.utils.document_utils import create_document_stack, start_embedding_task, process_url, \
-    edit_document, \
-    edit_document_version, refresh_document, clean_url, is_file_type_supported_by_catalog
+    edit_document as util_edit_document, edit_document_version as util_edit_document_version, refresh_document, \
+    clean_url, is_file_type_supported_by_catalog
 from common.utils.dynamic_field_utils import create_default_config_from_type_config
 from common.utils.eveai_exceptions import EveAIException
 from .document_forms import AddDocumentForm, AddURLForm, EditDocumentForm, EditDocumentVersionForm, \
@@ -553,7 +553,7 @@ def edit_document(document_id):
         form.valid_to.data = doc.valid_to
 
     if form.validate_on_submit():
-        updated_doc, error = edit_document(
+        updated_doc, error = util_edit_document(
             session.get('tenant').get('id', 0),
             document_id,
             form.name.data,
@@ -581,19 +581,18 @@ def edit_document_version(document_version_id):
     catalog_id = doc_vers.document.catalog_id
 
     catalog = Catalog.query.get_or_404(catalog_id)
+    current_app.logger.debug(f"Catalog Configuration: {catalog.configuration}")
     if catalog.configuration and len(catalog.configuration) > 0:
-        full_config = cache_manager.catalogs_config_cache.get_config(catalog.type)
-        document_version_configurations = full_config['document_version_configurations']
-        for config in document_version_configurations:
-            form.add_dynamic_fields(config, full_config, doc_vers.catalog_properties[config])
+        current_app.logger.debug(f"Document Version Catalog Properties: {doc_vers.catalog_properties}")
+        form.add_dynamic_fields("tagging_fields", catalog.configuration, doc_vers.catalog_properties["tagging_fields"])
 
     if form.validate_on_submit():
         catalog_properties = {}
         # Use the full_config variable we already defined
-        for config in document_version_configurations:
-            catalog_properties[config] = form.get_dynamic_data(config)
+        catalog_properties = {"tagging_fields": form.get_dynamic_data("tagging_fields")}
+        current_app.logger.debug(f"New Document Version Catalog Properties: {catalog_properties}")
 
-        updated_version, error = edit_document_version(
+        updated_version, error = util_edit_document_version(
             session.get('tenant').get('id', 0),
             document_version_id,
             form.user_context.data,
@@ -601,7 +600,7 @@ def edit_document_version(document_version_id):
         )
         if updated_version:
             flash(f'Document Version {updated_version.id} updated successfully', 'success')
-            return redirect(prefixed_url_for('document_bp.document_versions', document_id=updated_version.doc_id))
+            return redirect(prefixed_url_for('document_bp.documents', document_id=updated_version.doc_id))
         else:
             flash(f'Error updating document version: {error}', 'danger')
     else:

eveai_app/views/dynamic_form_base.py

@@ -404,6 +404,7 @@ class DynamicFormBase(FlaskForm):
             # Prepare field data
             field_data = None
             if initial_data and field_name in initial_data:
+                current_app.logger.debug(f"Using initial data for field '{field_name}': {initial_data[field_name]}")
                 field_data = initial_data[field_name]
                 if field_type in ['tagging_fields', 'tagging_fields_filter', 'dynamic_arguments'] and isinstance(
                         field_data, dict):

eveai_chat_workers/specialists/traicie/TRAICIE_KO_INTERVIEW_DEFINITION_SPECIALIST/1_1.py

@@ -0,0 +1,288 @@
+from datetime import datetime as dt, timezone as tz
+from typing import Optional, List, Dict
+
+import json
+import yaml
+from crewai.flow.flow import start, listen
+from flask import current_app
+from pydantic import BaseModel, Field
+
+from common.extensions import db, minio_client
+from common.models.interaction import Specialist, EveAIAsset
+from common.utils.minio_utils import MIB_CONVERTOR
+from common.utils.eveai_exceptions import EveAISpecialistExecutionError
+from common.utils.model_logging_utils import set_logging_information
+from eveai_chat_workers.definitions.language_level.language_level_v1_0 import LANGUAGE_LEVEL
+from eveai_chat_workers.definitions.tone_of_voice.tone_of_voice_v1_0 import TONE_OF_VOICE
+from eveai_chat_workers.outputs.traicie.knockout_questions.knockout_questions_v1_0 import KOQuestions, KOQuestion
+from eveai_chat_workers.specialists.crewai_base_classes import EveAICrewAICrew, EveAICrewAIFlow, EveAIFlowState
+from eveai_chat_workers.specialists.crewai_base_specialist import CrewAIBaseSpecialistExecutor
+from eveai_chat_workers.specialists.specialist_typing import SpecialistResult, SpecialistArguments
+
+
+class SpecialistExecutor(CrewAIBaseSpecialistExecutor):
+    """
+    type: TRAICIE_KO_INTERVIEW_DEFINITION_SPECIALIST
+    type_version: 1.0
+    Traicie Selection Specialist Executor class
+    """
+
+    def __init__(self, tenant_id, specialist_id, session_id, task_id, **kwargs):
+        self.ko_def_crew = None
+
+        super().__init__(tenant_id, specialist_id, session_id, task_id)
+
+
+    @property
+    def type(self) -> str:
+        return "TRAICIE_KO_INTERVIEW_DEFINITION_SPECIALIST"
+
+    @property
+    def type_version(self) -> str:
+        return "1.1"
+
+    def _config_task_agents(self):
+        self._add_task_agent("traicie_ko_criteria_interview_definition_task", "traicie_hr_bp_agent")
+
+    def _config_pydantic_outputs(self):
+        self._add_pydantic_output("traicie_ko_criteria_interview_definition_task", KOQuestions, "ko_questions")
+
+    def _config_state_result_relations(self):
+        self._add_state_result_relation("ko_questions")
+
+    def _instantiate_specialist(self):
+        verbose = self.tuning
+
+        ko_def_agents = [self.traicie_hr_bp_agent]
+        ko_def_tasks = [self.traicie_ko_criteria_interview_definition_task]
+        self.ko_def_crew = EveAICrewAICrew(
+            self,
+            "KO Criteria Interview Definition Crew",
+            agents=ko_def_agents,
+            tasks=ko_def_tasks,
+            verbose=verbose,
+        )
+
+        self.flow = KOFlow(
+            self,
+            self.ko_def_crew
+        )
+
+    def execute(self, arguments: SpecialistArguments, formatted_context, citations) -> SpecialistResult:
+        self.log_tuning("Traicie KO Criteria Interview Definition Specialist execution started", {})
+
+        if not self._cached_session.interactions:
+            specialist_phase = "initial"
+        else:
+            specialist_phase = self._cached_session.interactions[-1].specialist_results.get('phase', 'initial')
+
+        results = None
+
+        match specialist_phase:
+            case "initial":
+                results = self.execute_initial_state(arguments, formatted_context, citations)
+
+        self.log_tuning(f"Traicie KO Criteria Interview Definition Specialist execution ended",
+                        {"Results": results.model_dump() if results else "No info"})
+
+        return results
+
+
+    def execute_initial_state(self, arguments: SpecialistArguments, formatted_context, citations) -> SpecialistResult:
+        self.log_tuning("Traicie KO Criteria Interview Definition Specialist initial_state_execution started", {})
+
+        selection_specialist = Specialist.query.get(arguments.specialist_id)
+        if not selection_specialist:
+            raise EveAISpecialistExecutionError(self.tenant_id, self.specialist_id, self.session_id,
+                                                "No selection specialist found")
+        if selection_specialist.type != "TRAICIE_SELECTION_SPECIALIST":
+            raise EveAISpecialistExecutionError(self.tenant_id, self.specialist_id, self.session_id,
+                                                "Specialist is no Selection Specialist")
+
+        ko_competencies = []
+        for competency in selection_specialist.configuration.get("competencies", []):
+            if competency["is_knockout"] is True and competency["assess"] is True:
+                ko_competencies.append({"title": competency["title"], "description": competency["description"]})
+
+        tone_of_voice = selection_specialist.configuration.get('tone_of_voice', 'Professional & Neutral')
+        selected_tone_of_voice = next(
+            (item for item in TONE_OF_VOICE if item["name"] == tone_of_voice),
+            None  # fallback indien niet gevonden
+        )
+        tone_of_voice_context = f"{selected_tone_of_voice["description"]}"
+
+        language_level = selection_specialist.configuration.get('language_level', 'Standard')
+        selected_language_level = next(
+            (item for item in LANGUAGE_LEVEL if item["name"] == language_level),
+            None
+        )
+        language_level_context = (f"{selected_language_level['description']}, "
+                                  f"corresponding to CEFR level {selected_language_level['cefr_level']}")
+
+        flow_inputs = {
+            'name': "Evie",
+            'tone_of_voice': tone_of_voice,
+            'tone_of_voice_context': tone_of_voice_context,
+            'language_level': language_level,
+            'language_level_context': language_level_context,
+            'ko_criteria': ko_competencies,
+        }
+
+        flow_results = self.flow.kickoff(inputs=flow_inputs)
+
+        new_type = "TRAICIE_KO_CRITERIA_QUESTIONS"
+
+        # Controleer of we een KOQuestions object hebben of een lijst van KOQuestion objecten
+        if hasattr(self.flow.state.ko_questions, 'to_json'):
+            # Het is een KOQuestions object
+            json_str = self.flow.state.ko_questions.to_json()
+        elif isinstance(self.flow.state.ko_questions, list):
+            # Het is een lijst van KOQuestion objecten
+            # Maak een KOQuestions object en gebruik to_json daarop
+            ko_questions_obj = KOQuestions.from_question_list(self.flow.state.ko_questions)
+            json_str = ko_questions_obj.to_json()
+        else:
+            # Fallback voor het geval het een onverwacht type is
+            current_app.logger.warning(f"Unexpected type for ko_questions: {type(self.flow.state.ko_questions)}")
+            ko_questions_data = [q.model_dump() for q in self.flow.state.ko_questions]
+            json_str = json.dumps(ko_questions_data, ensure_ascii=False, indent=2)
+
+        try:
+            asset = db.session.query(EveAIAsset).filter(
+                EveAIAsset.type == new_type,
+                EveAIAsset.type_version == "1.0.0",
+                EveAIAsset.configuration.is_not(None),
+                EveAIAsset.configuration.has_key('specialist_id'),
+                EveAIAsset.configuration['specialist_id'].astext.cast(db.Integer) == selection_specialist.id
+            ).first()
+        except (ValueError, TypeError) as e:
+            current_app.logger.warning(f"Error casting specialist_id in asset configuration: {str(e)}")
+            asset = None
+
+        if not asset:
+            asset = EveAIAsset(
+                name=f"KO Criteria Form for specialist {selection_specialist.id}",
+                type=new_type,
+                type_version="1.0.0",
+                system_metadata={
+                    "Creator Specialist Type": self.type,
+                    "Creator Specialist Type Version": self.type_version,
+                    "Creator Specialist ID": self.specialist_id
+                },
+                configuration={
+                    "specialist_id": selection_specialist.id,
+                },
+            )
+            set_logging_information(asset, dt.now(tz=tz.utc))
+            asset.last_used_at = asset.created_at
+        else:
+            asset.last_used_at = dt.now(tz=tz.utc)
+
+        try:
+            # Stap 1: Asset aanmaken maar nog niet committen
+            db.session.add(asset)
+            db.session.flush()  # Geeft ons het ID zonder te committen
+
+            # Stap 2: Upload naar MinIO (kan falen zonder database impact)
+            bucket_name, object_name, file_size = minio_client.upload_asset_file(
+                tenant_id=self.tenant_id,
+                asset_id=asset.id,
+                asset_type=new_type,
+                file_type="json",
+                file_data=json_str
+            )
+
+            # Stap 3: Storage metadata toevoegen
+            asset.bucket_name = bucket_name
+            asset.object_name = object_name
+            asset.file_size = file_size / MIB_CONVERTOR
+            asset.file_type = "json"
+
+            # Stap 4: Token usage toevoegen
+            asset.prompt_tokens = self.ko_def_crew.usage_metrics.prompt_tokens
+            asset.completion_tokens = self.ko_def_crew.usage_metrics.completion_tokens
+
+            # Alles in één keer committen
+            db.session.commit()
+
+        except Exception as e:
+            current_app.logger.error(f"Error creating asset: {str(e)}")
+            db.session.rollback()
+            # Probeer MinIO cleanup als upload is gelukt maar database commit faalde
+            try:
+                if 'bucket_name' in locals() and 'object_name' in locals():
+                    minio_client.delete_object(bucket_name, object_name)
+            except:
+                pass  # Log maar ga door met originele exception
+            raise EveAISpecialistExecutionError(self.tenant_id, self.specialist_id, self.session_id,
+                                                f"Failed to create asset: {str(e)}")
+
+        results = SpecialistResult.create_for_type(self.type, self.type_version,
+                                                   answer=f"asset {asset.id} created for specialist {selection_specialist.id}",
+                                                   phase="finished",
+                                                   asset_id=asset.id,
+                                                   )
+
+
+        return results
+
+
+class KODefInput(BaseModel):
+    name: Optional[str] = Field(None, alias="name")
+    tone_of_voice: Optional[str] = Field(None, alias="tone_of_voice")
+    tone_of_voice_context: Optional[str] = Field(None, alias="tone_of_voice_context")
+    language_level: Optional[str] = Field(None, alias="language_level")
+    language_level_context: Optional[str] = Field(None, alias="language_level_context")
+    ko_criteria: Optional[List[Dict[str, str]]] = Field(None, alias="ko_criteria")
+
+
+class KODefResult(SpecialistResult):
+    asset_id: Optional[int] = Field(None, alias="asset_id")
+
+
+class KOFlowState(EveAIFlowState):
+    """Flow state for Traicie Role Definition specialist that automatically updates from task outputs"""
+    input: Optional[KODefInput] = None
+    ko_questions: Optional[List[KOQuestion]] = Field(None, alias="ko_questions")
+    phase: Optional[str] = Field(None, alias="phase")
+
+
+class KOFlow(EveAICrewAIFlow[KOFlowState]):
+    def __init__(self,
+                 specialist_executor: CrewAIBaseSpecialistExecutor,
+                 ko_def_crew: EveAICrewAICrew,
+                 **kwargs):
+        super().__init__(specialist_executor, "Traicie KO Interview Definiton Specialist Flow", **kwargs)
+        self.specialist_executor = specialist_executor
+        self.ko_def_crew = ko_def_crew
+        self.exception_raised = False
+
+    @start()
+    def process_inputs(self):
+        return ""
+
+    @listen(process_inputs)
+    async def execute_ko_def_definition(self):
+        inputs = self.state.input.model_dump()
+        try:
+            crew_output = await self.ko_def_crew.kickoff_async(inputs=inputs)
+            # Unfortunately, crew_output will only contain the output of the latest task.
+            # As we will only take into account the flow state, we need to ensure both competencies and criteria
+            # are copies to the flow state.
+            update = {}
+            for task in self.ko_def_crew.tasks:
+                if task.name == "traicie_ko_criteria_interview_definition_task":
+                    # update["competencies"] = task.output.pydantic.competencies
+                    self.state.ko_questions = task.output.pydantic.ko_questions
+            # crew_output.pydantic = crew_output.pydantic.model_copy(update=update)
+            self.state.phase = "personal_contact_data"
+            return crew_output
+        except Exception as e:
+            current_app.logger.error(f"CREW execute_ko_def Kickoff Error: {str(e)}")
+            self.exception_raised = True
+            raise e
+
+    async def kickoff_async(self, inputs=None):
+        self.state.input = KODefInput.model_validate(inputs)
+        result = await super().kickoff_async(inputs)
+        return self.state