25213f2004
- 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
79 lines
3.7 KiB
Python
79 lines
3.7 KiB
Python
from pydantic import BaseModel, Field
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from typing import Any, Dict, List, Optional, Type, Union
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def flatten_pydantic_model(model: BaseModel, merge_strategy: Dict[str, str] = {}) -> Dict[str, Any]:
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"""
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Flattens a nested Pydantic model by bringing all attributes to the highest level.
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:param model: Pydantic model instance to be flattened.
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:param merge_strategy: Dictionary defining how to handle duplicate attributes.
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:return: Flattened dictionary representation of the model.
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"""
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flat_dict = {}
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def recursive_flatten(obj: BaseModel, parent_key=""):
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for field_name, value in obj.model_dump(exclude_unset=True, by_alias=True).items():
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new_key = field_name # Maintain original field names
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if isinstance(value, BaseModel):
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# Recursively flatten nested models
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recursive_flatten(value, new_key)
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elif isinstance(value, list) and all(isinstance(i, BaseModel) for i in value):
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# If it's a list of Pydantic models, flatten each element
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for item in value:
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recursive_flatten(item, new_key)
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else:
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if new_key in flat_dict and new_key in merge_strategy:
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# Apply merge strategy
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if merge_strategy[new_key] == "add":
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if isinstance(flat_dict[new_key], list) and isinstance(value, list):
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flat_dict[new_key] += value # Concatenate lists
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elif isinstance(flat_dict[new_key], (int, float)) and isinstance(value, (int, float)):
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flat_dict[new_key] += value # Sum numbers
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elif isinstance(flat_dict[new_key], str) and isinstance(value, str):
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flat_dict[new_key] += "\n" + value # Concatenate strings
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elif merge_strategy[new_key] == "first":
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pass # Keep the first occurrence
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elif merge_strategy[new_key] == "last":
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flat_dict[new_key] = value
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else:
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flat_dict[new_key] = value
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recursive_flatten(model)
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return flat_dict
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def merge_dicts(base_dict: Dict[str, Any], new_data: Union[Dict[str, Any], BaseModel], merge_strategy: Dict[str, str]) \
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-> Dict[str, Any]:
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"""
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Merges a Pydantic model (or dictionary) into an existing dictionary based on a merge strategy.
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:param base_dict: The base dictionary to merge into.
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:param new_data: The new Pydantic model or dictionary to merge.
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:param merge_strategy: Dict defining how to merge duplicate attributes.
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:return: Updated dictionary after merging.
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"""
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if isinstance(new_data, BaseModel):
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new_data = flatten_pydantic_model(new_data) # Convert Pydantic model to dict
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for key, value in new_data.items():
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if key in base_dict and key in merge_strategy:
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strategy = merge_strategy[key]
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if strategy == "add":
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if isinstance(base_dict[key], list) and isinstance(value, list):
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base_dict[key] += value # Concatenate lists
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elif isinstance(base_dict[key], (int, float)) and isinstance(value, (int, float)):
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base_dict[key] += value # Sum numbers
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elif isinstance(base_dict[key], str) and isinstance(value, str):
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base_dict[key] += " " + value # Concatenate strings
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elif strategy == "first":
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pass # Keep the first occurrence (do nothing)
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elif strategy == "last":
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base_dict[key] = value # Always overwrite with latest value
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else:
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base_dict[key] = value # Add new field
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return base_dict
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