Initial commit: BLIGHT: CUE

Webhook listener that monitors Gitea repos for BLIGHT: triggers in
markdown files, processes them via Gemini 2.5 Flash-Lite, and writes
results back in-place.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ai/__init__.py

@@ -0,0 +1,4 @@
+from .base import AIProvider
+from .gemini import GeminiProvider
+
+__all__ = ["AIProvider", "GeminiProvider"]

ai/base.py

@@ -0,0 +1,21 @@
+from abc import ABC, abstractmethod
+
+
+class AIProvider(ABC):
+    """Base class for all AI provider implementations.
+
+    To add a new provider, subclass this and implement `complete`, then
+    instantiate your provider in `processor.py` instead of GeminiProvider.
+    """
+
+    @abstractmethod
+    def complete(self, document: str, instruction: str) -> str:
+        """Process an instruction in the context of a full document.
+
+        Args:
+            document: The full markdown document text (for context).
+            instruction: The BLIGHT instruction extracted from the trigger line.
+
+        Returns:
+            The text to insert in place of the trigger line.
+        """

ai/gemini.py

@@ -0,0 +1,29 @@
+import google.generativeai as genai
+import config
+from .base import AIProvider
+
+_SYSTEM_PROMPT = (
+    "You are an inline document assistant. "
+    "The user will provide a markdown document and a specific instruction. "
+    "Your response must contain ONLY the text to be inserted into the document — "
+    "no preamble, no explanation, no meta-commentary, no markdown code fences unless "
+    "the instruction specifically asks for them. "
+    "Respond as if your output will be dropped directly into the middle of a document."
+)
+
+
+class GeminiProvider(AIProvider):
+    def __init__(self) -> None:
+        genai.configure(api_key=config.GEMINI_API_KEY)
+        self._model = genai.GenerativeModel(
+            model_name="gemini-2.5-flash-lite",
+            system_instruction=_SYSTEM_PROMPT,
+        )
+
+    def complete(self, document: str, instruction: str) -> str:
+        prompt = (
+            f"DOCUMENT:\n\n{document}\n\n"
+            f"INSTRUCTION: {instruction}"
+        )
+        response = self._model.generate_content(prompt)
+        return response.text.strip()