Revert "Early 0.18 work (#22138)" (#22142)

This reverts commit d24b96d3bb.

frigate/genai/__init__.py

@@ -69,7 +69,7 @@ class GenAIClient:
                 return "\n- (No objects detected)"
 
         context_prompt = f"""
-Your task is to analyze a sequence of images taken in chronological order from a security camera.
+Your task is to analyze the sequence of images ({len(thumbnails)} total) taken in chronological order from the perspective of the {review_data["camera"]} security camera.
 
 ## Normal Activity Patterns for This Property
 
@@ -108,8 +108,7 @@ Your response MUST be a flat JSON object with:
 
 ## Sequence Details
 
-- Camera: {review_data["camera"]}
-- Total frames: {len(thumbnails)} (Frame 1 = earliest, Frame {len(thumbnails)} = latest)
+- Frame 1 = earliest, Frame {len(thumbnails)} = latest
 - Activity started at {review_data["start"]} and lasted {review_data["duration"]} seconds
 - Zones involved: {", ".join(review_data["zones"]) if review_data["zones"] else "None"}
 
@@ -293,64 +292,6 @@ Guidelines:
         """Get the context window size for this provider in tokens."""
         return 4096
 
-    def chat_with_tools(
-        self,
-        messages: list[dict[str, Any]],
-        tools: Optional[list[dict[str, Any]]] = None,
-        tool_choice: Optional[str] = "auto",
-    ) -> dict[str, Any]:
-        """
-        Send chat messages to LLM with optional tool definitions.
-
-        This method handles conversation-style interactions with the LLM,
-        including function calling/tool usage capabilities.
-
-        Args:
-            messages: List of message dictionaries. Each message should have:
-                - 'role': str - One of 'user', 'assistant', 'system', or 'tool'
-                - 'content': str - The message content
-                - 'tool_call_id': Optional[str] - For tool responses, the ID of the tool call
-                - 'name': Optional[str] - For tool messages, the tool name
-            tools: Optional list of tool definitions in OpenAI-compatible format.
-                   Each tool should have 'type': 'function' and 'function' with:
-                   - 'name': str - Tool name
-                   - 'description': str - Tool description
-                   - 'parameters': dict - JSON schema for parameters
-            tool_choice: How the model should handle tools:
-                - 'auto': Model decides whether to call tools
-                - 'none': Model must not call tools
-                - 'required': Model must call at least one tool
-                - Or a dict specifying a specific tool to call
-            **kwargs: Additional provider-specific parameters.
-
-        Returns:
-            Dictionary with:
-            - 'content': Optional[str] - The text response from the LLM, None if tool calls
-            - 'tool_calls': Optional[List[Dict]] - List of tool calls if LLM wants to call tools.
-              Each tool call dict has:
-                - 'id': str - Unique identifier for this tool call
-                - 'name': str - Tool name to call
-                - 'arguments': dict - Arguments for the tool call (parsed JSON)
-            - 'finish_reason': str - Reason generation stopped:
-                - 'stop': Normal completion
-                - 'tool_calls': LLM wants to call tools
-                - 'length': Hit token limit
-                - 'error': An error occurred
-
-        Raises:
-            NotImplementedError: If the provider doesn't implement this method.
-        """
-        # Base implementation - each provider should override this
-        logger.warning(
-            f"{self.__class__.__name__} does not support chat_with_tools. "
-            "This method should be overridden by the provider implementation."
-        )
-        return {
-            "content": None,
-            "tool_calls": None,
-            "finish_reason": "error",
-        }
-
 
 def get_genai_client(config: FrigateConfig) -> Optional[GenAIClient]:
     """Get the GenAI client."""