Implement LLM Chat API with tool calling support (#21731)

* Implement initial tools definiton APIs

* Add initial chat completion API with tool support

* Implement other providers

* Cleanup

frigate/api/defs/request/chat_body.py

@@ -0,0 +1,34 @@
+"""Chat API request models."""
+
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class ChatMessage(BaseModel):
+    """A single message in a chat conversation."""
+
+    role: str = Field(
+        description="Message role: 'user', 'assistant', 'system', or 'tool'"
+    )
+    content: str = Field(description="Message content")
+    tool_call_id: Optional[str] = Field(
+        default=None, description="For tool messages, the ID of the tool call"
+    )
+    name: Optional[str] = Field(
+        default=None, description="For tool messages, the tool name"
+    )
+
+
+class ChatCompletionRequest(BaseModel):
+    """Request for chat completion with tool calling."""
+
+    messages: list[ChatMessage] = Field(
+        description="List of messages in the conversation"
+    )
+    max_tool_iterations: int = Field(
+        default=5,
+        ge=1,
+        le=10,
+        description="Maximum number of tool call iterations (default: 5)",
+    )

frigate/api/defs/response/chat_response.py

@@ -0,0 +1,37 @@
+"""Chat API response models."""
+
+from typing import Any, Optional
+
+from pydantic import BaseModel, Field
+
+
+class ToolCall(BaseModel):
+    """A tool call from the LLM."""
+
+    id: str = Field(description="Unique identifier for this tool call")
+    name: str = Field(description="Tool name to call")
+    arguments: dict[str, Any] = Field(description="Arguments for the tool call")
+
+
+class ChatMessageResponse(BaseModel):
+    """A message in the chat response."""
+
+    role: str = Field(description="Message role")
+    content: Optional[str] = Field(
+        default=None, description="Message content (None if tool calls present)"
+    )
+    tool_calls: Optional[list[ToolCall]] = Field(
+        default=None, description="Tool calls if LLM wants to call tools"
+    )
+
+
+class ChatCompletionResponse(BaseModel):
+    """Response from chat completion."""
+
+    message: ChatMessageResponse = Field(description="The assistant's message")
+    finish_reason: str = Field(
+        description="Reason generation stopped: 'stop', 'tool_calls', 'length', 'error'"
+    )
+    tool_iterations: int = Field(
+        default=0, description="Number of tool call iterations performed"
+    )

frigate/api/defs/tags.py

@@ -5,6 +5,7 @@ class Tags(Enum):
     app = "App"
     auth = "Auth"
     camera = "Camera"
+    chat = "Chat"
     events = "Events"
     export = "Export"
     classification = "Classification"