Add GenAI Backend Streaming and Chat (#22152)

* Add basic chat page with entry

* Add chat history

* processing

* Add markdown

* Improvements

* Adjust timing format

* Reduce fields in response

* More time parsing improvements

* Show tool calls separately from message

* Add title

* Improve UI handling

* Support streaming

* Full streaming support

* Fix tool calling

* Add copy button

* Improvements to UI

* Improve default behavior

* Implement message editing

* Add sub label to event tool filtering

* Cleanup

* Cleanup UI and prompt

* Cleanup UI bubbles

* Fix loading

* Add support for markdown tables

* Add thumbnail images to object results

* Add a starting state for chat

* Clenaup

frigate/genai/utils.py

@@ -0,0 +1,70 @@
+"""Shared helpers for GenAI providers and chat (OpenAI-style messages, tool call parsing)."""
+
+import json
+import logging
+from typing import Any, List, Optional
+
+logger = logging.getLogger(__name__)
+
+
+def parse_tool_calls_from_message(
+    message: dict[str, Any],
+) -> Optional[list[dict[str, Any]]]:
+    """
+    Parse tool_calls from an OpenAI-style message dict.
+
+    Message may have "tool_calls" as a list of:
+      {"id": str, "function": {"name": str, "arguments": str}, ...}
+
+    Returns a list of {"id", "name", "arguments"} with arguments parsed as dict,
+    or None if no tool_calls. Used by Ollama and LlamaCpp (non-stream) responses.
+    """
+    raw = message.get("tool_calls")
+    if not raw or not isinstance(raw, list):
+        return None
+    result = []
+    for tool_call in raw:
+        function_data = tool_call.get("function") or {}
+        try:
+            arguments_str = function_data.get("arguments") or "{}"
+            arguments = json.loads(arguments_str)
+        except (json.JSONDecodeError, KeyError, TypeError) as e:
+            logger.warning(
+                "Failed to parse tool call arguments: %s, tool: %s",
+                e,
+                function_data.get("name", "unknown"),
+            )
+            arguments = {}
+        result.append(
+            {
+                "id": tool_call.get("id", ""),
+                "name": function_data.get("name", ""),
+                "arguments": arguments,
+            }
+        )
+    return result if result else None
+
+
+def build_assistant_message_for_conversation(
+    content: Any,
+    tool_calls_raw: Optional[List[dict[str, Any]]],
+) -> dict[str, Any]:
+    """
+    Build the assistant message dict in OpenAI format for appending to a conversation.
+
+    tool_calls_raw: list of {"id", "name", "arguments"} (arguments as dict), or None.
+    """
+    msg: dict[str, Any] = {"role": "assistant", "content": content}
+    if tool_calls_raw:
+        msg["tool_calls"] = [
+            {
+                "id": tc["id"],
+                "type": "function",
+                "function": {
+                    "name": tc["name"],
+                    "arguments": json.dumps(tc.get("arguments") or {}),
+                },
+            }
+            for tc in tool_calls_raw
+        ]
+    return msg