init commit

llm_core.py

@@ -0,0 +1,44 @@
+# [DEF:llm_core:Module]
+import os
+import logging
+from typing import Type, TypeVar
+from pydantic import BaseModel
+
+# Pylance often fails to resolve dynamic exports in google-generativeai
+import google.generativeai as genai # type: ignore
+
+logger = logging.getLogger("LLM_Core")
+T = TypeVar("T", bound=BaseModel)
+
+class GeminiProcessor:
+    def __init__(self, model_name: str = "gemini-1.5-flash"):
+        api_key = os.getenv("GOOGLE_API_KEY")
+        if not api_key:
+            raise ValueError("[FATAL] GOOGLE_API_KEY not found.")
+        
+        # Explicit type ignore for Pylance strict mode
+        genai.configure(api_key=api_key) # type: ignore
+        self.model = genai.GenerativeModel(model_name) # type: ignore
+
+    def generate_structured(self, prompt: str, content: str, schema: Type[T]) -> T:
+        logger.info(f"[GeminiProcessor] Structured generation for {schema.__name__}")
+        full_prompt = f"{prompt}\n\nINPUT TEXT:\n{content}"
+        
+        response = self.model.generate_content(
+            full_prompt,
+            generation_config=genai.GenerationConfig( # type: ignore
+                response_mime_type="application/json",
+                response_schema=schema
+            )
+        )
+        return schema.model_validate_json(response.text)
+
+    def generate_text(self, system_instruction: str, user_content: str) -> str:
+        # Re-instantiate model with system instruction
+        model_w_sys = genai.GenerativeModel( # type: ignore
+            self.model.model_name,
+            system_instruction=system_instruction
+        )
+        response = model_w_sys.generate_content(user_content)
+        return response.text
+# [/DEF:llm_core]