Feat: Implement NLG Engine base structure

backend/app/services/nlg/nlg_engine.py

@@ -0,0 +1,45 @@
+import json
+from abc import ABC, abstractmethod
+
+class NLGEngine(ABC):
+    """
+    Base class for Natural Language Generation (NLG) engines.
+    Defines the interface for generating text sections and full reports,
+    with a structure prepared for plugging in various LLM providers.
+    """
+
+    @abstractmethod
+    def generate_section_text(self, section_id: str, raw_data: dict) -> str:
+        """
+        Generates natural language text for a specific report section based on raw data.
+
+        Args:
+            section_id (str): The identifier for the report section (e.g., "executive_summary", "market_trends").
+            raw_data (dict): The raw data pertinent to the section, used as context for generation.
+
+        Returns:
+            str: A JSON-formatted string containing the generated text and metadata.
+                  Example: `return self._format_output({"section_id": "executive_summary", "text": "Generated summary text."})`
+        """
+        pass
+
+    @abstractmethod
+    def generate_full_report(self, data: dict) -> str:
+        """
+        Generates a complete natural language report based on a comprehensive data structure.
+
+        Args:
+            data (dict): A dictionary containing all necessary data for generating the full report.
+
+        Returns:
+            str: A JSON-formatted string representing the full generated report,
+                  structured with sections and their respective texts.
+                  Example: `return self._format_output({"report_title": "...", "sections": [{"section_id": "...", "text": "..."}]})`
+        """
+        pass
+
+    def _format_output(self, content: dict) -> str:
+        """
+        Helper method to ensure all outputs are structured as JSON.
+        """
+        return json.dumps(content)