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https://github.com/blakeblackshear/frigate.git
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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
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@@ -1,6 +1,7 @@
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"""llama.cpp Provider for Frigate AI."""
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import base64
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import json
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import logging
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from typing import Any, Optional
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@@ -99,3 +100,132 @@ class LlamaCppClient(GenAIClient):
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def get_context_size(self) -> int:
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"""Get the context window size for llama.cpp."""
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return self.genai_config.provider_options.get("context_size", 4096)
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def chat_with_tools(
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self,
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messages: list[dict[str, Any]],
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tools: Optional[list[dict[str, Any]]] = None,
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tool_choice: Optional[str] = "auto",
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) -> dict[str, Any]:
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"""
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Send chat messages to llama.cpp server with optional tool definitions.
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Uses the OpenAI-compatible endpoint but passes through all native llama.cpp
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parameters (like slot_id, temperature, etc.) via provider_options.
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"""
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if self.provider is None:
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logger.warning(
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"llama.cpp provider has not been initialized. Check your llama.cpp configuration."
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)
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return {
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"content": None,
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"tool_calls": None,
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"finish_reason": "error",
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}
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try:
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openai_tool_choice = None
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if tool_choice:
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if tool_choice == "none":
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openai_tool_choice = "none"
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elif tool_choice == "auto":
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openai_tool_choice = "auto"
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elif tool_choice == "required":
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openai_tool_choice = "required"
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payload = {
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"messages": messages,
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}
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if tools:
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payload["tools"] = tools
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if openai_tool_choice is not None:
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payload["tool_choice"] = openai_tool_choice
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provider_opts = {
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k: v for k, v in self.provider_options.items() if k != "context_size"
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}
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payload.update(provider_opts)
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response = requests.post(
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f"{self.provider}/v1/chat/completions",
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json=payload,
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timeout=self.timeout,
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)
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response.raise_for_status()
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result = response.json()
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if result is None or "choices" not in result or len(result["choices"]) == 0:
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return {
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"content": None,
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"tool_calls": None,
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"finish_reason": "error",
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}
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choice = result["choices"][0]
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message = choice.get("message", {})
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content = message.get("content")
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if content:
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content = content.strip()
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else:
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content = None
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tool_calls = None
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if "tool_calls" in message and message["tool_calls"]:
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tool_calls = []
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for tool_call in message["tool_calls"]:
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try:
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function_data = tool_call.get("function", {})
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arguments_str = function_data.get("arguments", "{}")
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arguments = json.loads(arguments_str)
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except (json.JSONDecodeError, KeyError, TypeError) as e:
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logger.warning(
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f"Failed to parse tool call arguments: {e}, "
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f"tool: {function_data.get('name', 'unknown')}"
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)
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arguments = {}
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tool_calls.append(
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{
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"id": tool_call.get("id", ""),
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"name": function_data.get("name", ""),
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"arguments": arguments,
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}
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)
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finish_reason = "error"
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if "finish_reason" in choice and choice["finish_reason"]:
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finish_reason = choice["finish_reason"]
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elif tool_calls:
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finish_reason = "tool_calls"
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elif content:
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finish_reason = "stop"
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return {
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"content": content,
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"tool_calls": tool_calls,
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"finish_reason": finish_reason,
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}
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except requests.exceptions.Timeout as e:
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logger.warning("llama.cpp request timed out: %s", str(e))
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return {
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"content": None,
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"tool_calls": None,
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"finish_reason": "error",
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}
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except requests.exceptions.RequestException as e:
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logger.warning("llama.cpp returned an error: %s", str(e))
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return {
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"content": None,
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"tool_calls": None,
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"finish_reason": "error",
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}
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except Exception as e:
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logger.warning("Unexpected error in llama.cpp chat_with_tools: %s", str(e))
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return {
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"content": None,
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"tool_calls": None,
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"finish_reason": "error",
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}
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