- Implementation of specialist execution api, including SSE protocol

- eveai_chat becomes deprecated and should be replaced with SSE
- Adaptation of STANDARD_RAG specialist
- Base class definition allowing to realise specialists with crewai framework
- Implementation of SPIN_SPECIALIST
- Implementation of test app for testing specialists (test_specialist_client). Also serves as an example for future SSE-based client
- Improvements to startup scripts to better handle and scale multiple connections
- Small improvements to the interaction forms and views
- Caching implementation improved and augmented with additional caches

common/utils/pydantic_utils.py

@@ -0,0 +1,78 @@
+from pydantic import BaseModel, Field
+from typing import Any, Dict, List, Optional, Type, Union
+
+
+def flatten_pydantic_model(model: BaseModel, merge_strategy: Dict[str, str] = {}) -> Dict[str, Any]:
+    """
+    Flattens a nested Pydantic model by bringing all attributes to the highest level.
+
+    :param model: Pydantic model instance to be flattened.
+    :param merge_strategy: Dictionary defining how to handle duplicate attributes.
+    :return: Flattened dictionary representation of the model.
+    """
+    flat_dict = {}
+
+    def recursive_flatten(obj: BaseModel, parent_key=""):
+        for field_name, value in obj.model_dump(exclude_unset=True, by_alias=True).items():
+            new_key = field_name  # Maintain original field names
+
+            if isinstance(value, BaseModel):
+                # Recursively flatten nested models
+                recursive_flatten(value, new_key)
+            elif isinstance(value, list) and all(isinstance(i, BaseModel) for i in value):
+                # If it's a list of Pydantic models, flatten each element
+                for item in value:
+                    recursive_flatten(item, new_key)
+            else:
+                if new_key in flat_dict and new_key in merge_strategy:
+                    # Apply merge strategy
+                    if merge_strategy[new_key] == "add":
+                        if isinstance(flat_dict[new_key], list) and isinstance(value, list):
+                            flat_dict[new_key] += value  # Concatenate lists
+                        elif isinstance(flat_dict[new_key], (int, float)) and isinstance(value, (int, float)):
+                            flat_dict[new_key] += value  # Sum numbers
+                        elif isinstance(flat_dict[new_key], str) and isinstance(value, str):
+                            flat_dict[new_key] += "\n" + value  # Concatenate strings
+                    elif merge_strategy[new_key] == "first":
+                        pass  # Keep the first occurrence
+                    elif merge_strategy[new_key] == "last":
+                        flat_dict[new_key] = value
+                else:
+                    flat_dict[new_key] = value
+
+    recursive_flatten(model)
+    return flat_dict
+
+
+def merge_dicts(base_dict: Dict[str, Any], new_data: Union[Dict[str, Any], BaseModel], merge_strategy: Dict[str, str]) \
+        -> Dict[str, Any]:
+    """
+    Merges a Pydantic model (or dictionary) into an existing dictionary based on a merge strategy.
+
+    :param base_dict: The base dictionary to merge into.
+    :param new_data: The new Pydantic model or dictionary to merge.
+    :param merge_strategy: Dict defining how to merge duplicate attributes.
+    :return: Updated dictionary after merging.
+    """
+    if isinstance(new_data, BaseModel):
+        new_data = flatten_pydantic_model(new_data)  # Convert Pydantic model to dict
+
+    for key, value in new_data.items():
+        if key in base_dict and key in merge_strategy:
+            strategy = merge_strategy[key]
+
+            if strategy == "add":
+                if isinstance(base_dict[key], list) and isinstance(value, list):
+                    base_dict[key] += value  # Concatenate lists
+                elif isinstance(base_dict[key], (int, float)) and isinstance(value, (int, float)):
+                    base_dict[key] += value  # Sum numbers
+                elif isinstance(base_dict[key], str) and isinstance(value, str):
+                    base_dict[key] += " " + value  # Concatenate strings
+            elif strategy == "first":
+                pass  # Keep the first occurrence (do nothing)
+            elif strategy == "last":
+                base_dict[key] = value  # Always overwrite with latest value
+        else:
+            base_dict[key] = value  # Add new field
+
+    return base_dict