- Introduction of PARTNER_RAG retriever, PARTNER_RAG_SPECIALIST and linked Agent and Task, to support documentation inquiries in the management app (eveai_app)

- Addition of a tenant_partner_services view to show partner services from the viewpoint of a tenant
- Addition of domain model diagrams
- Addition of license_periods views and form

config/agents/evie_partner/PARTNER_RAG_AGENT/1.0.0.yaml

@@ -0,0 +1,26 @@
+version: "1.0.0"
+name: "Partner Rag Agent"
+role: >
+  You are a virtual assistant responsible for answering user questions about the Evie platform (Ask Eve AI) and products 
+  developed by partners on top of it. You are reliable point of contact for end-users seeking help, clarification, or 
+  deeper understanding of features, capabilities, integrations, or workflows related to these AI-powered solutions.
+goal: >
+  Your primary goal is to:
+  	•	Provide clear, relevant, and accurate responses to user questions.
+  	•	Reduce friction in user onboarding and daily usage.
+  	•	Increase user confidence and adoption of both the platform and partner-developed products.
+  	•	Act as a bridge between documentation and practical application, enabling users to help themselves through intelligent guidance.
+backstory: >
+  You have availability Evie’s own documentation, partner product manuals, and real user interactions. You are designed 
+  to replace passive documentation with active, contextual assistance. 
+  You have evolved beyond a support bot: you combine knowledge, reasoning, and a friendly tone to act as a product 
+  companion that grows with the ecosystem. As partner products expand, the agent updates its knowledge and learns to 
+  distinguish between general platform capabilities and product-specific nuances, offering a personalised experience 
+  each time.
+full_model_name: "mistral.mistral-medium-latest"
+temperature: 0.3
+metadata:
+  author: "Josako"
+  date_added: "2025-07-16"
+  description: "An Agent that does RAG based on a user's question, RAG content & history"
+  changes: "Initial version"

config/partner_services/globals/KNOWLEDGE_SERVICE/1.0.0.yaml

@@ -0,0 +1,9 @@
+version: "1.0.0"
+name: "Knowledge Service"
+configuration: {}
+permissions: {}
+metadata:
+  author: "Josako"
+  date_added: "2025-04-02"
+  changes: "Initial version"
+  description: "Partner providing catalog content"

config/retrievers/evie_partner/PARTNER_RAG/1.0.0.yaml

@@ -0,0 +1,21 @@
+version: "1.0.0"
+name: "Standard RAG Retriever"
+configuration:
+  es_k:
+    name: "es_k"
+    type: "integer"
+    description: "K-value to retrieve embeddings (max embeddings retrieved)"
+    required: true
+    default: 8
+  es_similarity_threshold:
+    name: "es_similarity_threshold"
+    type: "float"
+    description: "Similarity threshold for retrieving embeddings"
+    required: true
+    default: 0.3
+arguments: {}
+metadata:
+  author: "Josako"
+  date_added: "2025-01-24"
+  changes: "Initial version"
+  description: "Retrieving all embeddings conform the query"

config/specialists/evie_partner/PARTNER_RAG_SPECIALIST/1.0.0.yaml

@@ -0,0 +1,34 @@
+version: "1.0.0"
+name: "Partner RAG Specialist"
+framework: "crewai"
+chat: true
+configuration: {}
+arguments: {}
+results:
+  rag_output:
+    answer:
+      name: "answer"
+      type: "str"
+      description: "Answer to the query"
+      required: true
+    citations:
+      name: "citations"
+      type: "List[str]"
+      description: "List of citations"
+      required: false
+    insufficient_info:
+      name: "insufficient_info"
+      type: "bool"
+      description: "Whether or not the query is insufficient info"
+      required: true
+agents:
+  - type: "PARTNER_RAG_AGENT"
+    version: "1.0"
+tasks:
+  - type: "PARTNER_RAG_TASK"
+    version: "1.0"
+metadata:
+  author: "Josako"
+  date_added: "2025-07-16"
+  changes: "Initial version"
+  description: "Q&A through Partner RAG Specialist (for documentation purposes)"

config/specialists/globals/RAG_SPECIALIST/1.1.0.yaml

@@ -1,4 +1,4 @@
-version: "1.0.0"
+version: "1.1.0"
 name: "RAG Specialist"
 framework: "crewai"
 chat: true

config/specialists/globals/STANDARD_RAG_SPECIALIST/1.0.0.yaml

@@ -1,53 +0,0 @@
-version: 1.0.0
-name: "Standard RAG Specialist"
-framework: "langchain"
-chat: true
-configuration:
-  specialist_context:
-    name: "Specialist Context"
-    type: "text"
-    description: "The context to be used by the specialist."
-    required: false
-  temperature:
-    name: "Temperature"
-    type: "number"
-    description: "The inference temperature to be used by the specialist."
-    required: false
-    default: 0.3
-arguments:
-  language:
-    name: "Language"
-    type: "str"
-    description: "Language code to be used for receiving questions and giving answers"
-    required: true
-  query:
-    name: "query"
-    type: "str"
-    description: "Query to answer"
-    required: true
-results:
-  detailed_query:
-    name: "detailed_query"
-    type: "str"
-    description: "The query detailed with the Chat Session History."
-    required: true
-  answer:
-    name: "answer"
-    type: "str"
-    description: "Answer to the query"
-    required: true
-  citations:
-    name: "citations"
-    type: "List[str]"
-    description: "List of citations"
-    required: false
-  insufficient_info:
-    name: "insufficient_info"
-    type: "bool"
-    description: "Whether or not the query is insufficient info"
-    required: true
-metadata:
-  author: "Josako"
-  date_added: "2025-01-08"
-  changes: "Initial version"
-  description: "A Specialist that performs standard Q&A"

config/tasks/evie_partner/PARTNER_RAG_TASK/1.0.0.yaml

@@ -0,0 +1,22 @@
+version: "1.0.0"
+name: "RAG Task"
+task_description: >
+  Answer the question based on the following context, and taking into account the history of the discussion. Try not to
+  repeat answers already given in the recent history,  unless confirmation is required or repetition is essential to 
+  give a coherent answer.
+  Answer the end user in the language used in his/her question.
+  If the question cannot be answered using the given context, answer "I have insufficient information to answer this 
+  question."
+  Context (in between triple $):
+    $$${context}$$$
+  History (in between triple €):
+    €€€{history}€€€
+  Question (in between triple £):
+    £££{question}£££
+expected_output: >
+  Your answer.
+metadata:
+  author: "Josako"
+  date_added: "2025-07-16"
+  description: "A Task that gives RAG-based answers"
+  changes: "Initial version"

config/type_defs/partner_service_types.py

@@ -1,9 +1,5 @@
 # config/type_defs/partner_service_types.py
 PARTNER_SERVICE_TYPES = {
-    "REFERRAL_SERVICE": {
-        "name": "Referral Service",
-        "description": "Partner referring new customers",
-    },
     "KNOWLEDGE_SERVICE": {
         "name": "Knowledge Service",
         "description": "Partner providing catalog content",

config/type_defs/retriever_types.py

@@ -4,6 +4,11 @@ RETRIEVER_TYPES = {
         "name": "Standard RAG Retriever",
         "description": "Retrieving all embeddings from the catalog conform the query",
     },
+    "PARTNER_RAG": {
+        "name": "Partner RAG Retriever",
+        "description": "RAG intended for partner documentation",
+        "partner": "evie_partner"
+    },
     "TRAICIE_ROLE_DEFINITION_BY_ROLE_IDENTIFICATION": {
         "name": "Traicie Role Definition Retriever by Role Identification",
         "description": "Retrieves relevant role information for a given role",

config/type_defs/specialist_types.py

@@ -1,13 +1,14 @@
 # Specialist Types
 SPECIALIST_TYPES = {
-    "STANDARD_RAG_SPECIALIST": {
-        "name": "Standard RAG Specialist",
-        "description": "Standard Q&A through RAG Specialist",
-    },
     "RAG_SPECIALIST": {
         "name": "RAG Specialist",
         "description": "Q&A through RAG Specialist",
     },
+    "PARTNER_RAG_SPECIALIST": {
+        "name": "Partner RAG Specialist",
+        "description": "Q&A through Partner RAG Specialist (for documentation purposes)",
+        "partner": "evie_partner"
+    },
     "SPIN_SPECIALIST": {
         "name": "Spin Sales Specialist",
         "description": "A specialist that allows to answer user queries, try to get SPIN-information and Identification",