mirror of
https://github.com/blakeblackshear/frigate.git
synced 2026-08-02 17:12:16 +03:00
Early 0.18 work (#22138)
* Update version * Create scaffolding for case management (#21293) * implement case management for export apis (#21295) * refactor vainfo to search for first GPU (#21296) use existing LibvaGpuSelector to pick appropritate libva device * Case management UI (#21299) * Refactor export cards to match existing cards in other UI pages * Show cases separately from exports * Add proper filtering and display of cases * Add ability to edit and select cases for exports * Cleanup typing * Hide if no unassigned * Cleanup hiding logic * fix scrolling * Improve layout * Camera connection quality indicator (#21297) * add camera connection quality metrics and indicator * formatting * move stall calcs to watchdog * clean up * change watchdog to 1s and separately track time for ffmpeg retry_interval * implement status caching to reduce message volume * Export filter UI (#21322) * Get started on export filters * implement basic filter * Implement filtering and adjust api * Improve filter handling * Improve navigation * Cleanup * handle scrolling * Refactor temperature reporting for detectors and implement Hailo temp reading (#21395) * Add Hailo temperature retrieval * Refactor `get_hailo_temps()` to use ctxmanager * Show Hailo temps in system UI * Move hailo_platform import to get_hailo_temps * Refactor temperatures calculations to use within detector block * Adjust webUI to handle new location --------- Co-authored-by: tigattack <10629864+tigattack@users.noreply.github.com> * Camera-specific hwaccel settings for timelapse exports (correct base) (#21386) * added hwaccel_args to camera.record.export config struct * populate camera.record.export.hwaccel_args with a cascade up to camera then global if 'auto' * use new hwaccel args in export * added documentation for camera-specific hwaccel export * fix c/p error * missed an import * fleshed out the docs and comments a bit * ruff lint * separated out the tips in the doc * fix documentation * fix and simplify reference config doc * Add support for GPU and NPU temperatures (#21495) * Add rockchip temps * Add support for GPU and NPU temperatures in the frontend * Add support for Nvidia temperature * Improve separation * Adjust graph scaling * Exports Improvements (#21521) * Add images to case folder view * Add ability to select case in export dialog * Add to mobile review too * Add API to handle deleting recordings (#21520) * Add recording delete API * Re-organize recordings apis * Fix import * Consolidate query types * Add media sync API endpoint (#21526) * add media cleanup functions * add endpoint * remove scheduled sync recordings from cleanup * move to utils dir * tweak import * remove sync_recordings and add config migrator * remove sync_recordings * docs * remove key * clean up docs * docs fix * docs tweak * Media sync API refactor and UI (#21542) * generic job infrastructure * types and dispatcher changes for jobs * save data in memory only for completed jobs * implement media sync job and endpoints * change logs to debug * websocket hook and types * frontend * i18n * docs tweaks * endpoint descriptions * tweak docs * use same logging pattern in sync_recordings as the other sync functions (#21625) * Fix incorrect counting in sync_recordings (#21626) * Update go2rtc to v1.9.13 (#21648) Co-authored-by: Eugeny Tulupov <eugeny.tulupov@spirent.com> * Refactor Time-Lapse Export (#21668) * refactor time lapse creation to be a separate API call with ability to pass arbitrary ffmpeg args * Add CPU fallback * Optimize empty directory cleanup for recordings (#21695) The previous empty directory cleanup did a full recursive directory walk, which can be extremely slow. This new implementation only removes directories which have a chance of being empty due to a recent file deletion. * Implement llama.cpp GenAI Provider (#21690) * Implement llama.cpp GenAI Provider * Add docs * Update links * Fix broken mqtt links * Fix more broken anchors * Remove parents in remove_empty_directories (#21726) The original implementation did a full directory tree walk to find and remove empty directories, so this implementation should remove the parents as well, like the original did. * 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 * Offline preview image (#21752) * use latest preview frame for latest image when camera is offline * remove frame extraction logic * tests * frontend * add description to api endpoint * Update to ROCm 7.2.0 (#21753) * Update to ROCm 7.2.0 * ROCm now works properly with JinaV1 * Arcface has compilation error * Add live context tool to LLM (#21754) * Add live context tool * Improve handling of images in request * Improve prompt caching * Add networking options for configuring listening ports (#21779) * feat: add X-Frame-Time when returning snapshot (#21932) Co-authored-by: Florent MORICONI <170678386+fmcloudconsulting@users.noreply.github.com> * Improve jsmpeg player websocket handling (#21943) * improve jsmpeg player websocket handling prevent websocket console messages from appearing when player is destroyed * reformat files after ruff upgrade * Allow API Events to be Detections or Alerts, depending on the Event Label (#21923) * - API created events will be alerts OR detections, depending on the event label, defaulting to alerts - Indefinite API events will extend the recording segment until those events are ended - API event start time is the actual start time, instead of having a pre-buffer of record.event_pre_capture * Instead of checking for indefinite events on a camera before deciding if we should end the segment, only update last_detection_time and last_alert_time if frame_time is greater, which should have the same effect * Add the ability to set a pre_capture number of seconds when creating a manual event via the API. Default behavior unchanged * Remove unnecessary _publish_segment_start() call * Formatting * handle last_alert_time or last_detection_time being None when checking them against the frame_time * comment manual_info["label"].split(": ")[0] for clarity * ffmpeg Preview Segment Optimization for "high" and "very_high" (#21996) * Introduce qmax parameter for ffmpeg preview encoding Added PREVIEW_QMAX_PARAM to control ffmpeg encoding quality. * formatting * Fix spacing in qmax parameters for preview quality * Adapt to new Gemini format * Fix frame time access * Remove exceptions * Cleanup --------- Co-authored-by: Josh Hawkins <32435876+hawkeye217@users.noreply.github.com> Co-authored-by: tigattack <10629864+tigattack@users.noreply.github.com> Co-authored-by: Andrew Roberts <adroberts@gmail.com> Co-authored-by: Eugeny Tulupov <zhekka3@gmail.com> Co-authored-by: Eugeny Tulupov <eugeny.tulupov@spirent.com> Co-authored-by: John Shaw <1753078+johnshaw@users.noreply.github.com> Co-authored-by: Eric Work <work.eric@gmail.com> Co-authored-by: FL42 <46161216+fl42@users.noreply.github.com> Co-authored-by: Florent MORICONI <170678386+fmcloudconsulting@users.noreply.github.com> Co-authored-by: nulledy <254504350+nulledy@users.noreply.github.com>
This commit is contained in:
co-authored by
Josh Hawkins
tigattack
Andrew Roberts
Eugeny Tulupov
Eugeny Tulupov
John Shaw
Eric Work
FL42
Florent MORICONI
nulledy
parent
7df3622243
commit
d24b96d3bb
+198
-1
@@ -1,7 +1,7 @@
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"""Gemini Provider for Frigate AI."""
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import logging
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from typing import Optional
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from typing import Any, Optional
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from google import genai
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from google.genai import errors, types
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@@ -76,3 +76,200 @@ class GeminiClient(GenAIClient):
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"""Get the context window size for Gemini."""
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# Gemini Pro Vision has a 1M token context window
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return 1000000
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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 Gemini with optional tool definitions.
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Implements function calling/tool usage for Gemini models.
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"""
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try:
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# Convert messages to Gemini format
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gemini_messages = []
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for msg in messages:
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role = msg.get("role", "user")
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content = msg.get("content", "")
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# Map roles to Gemini format
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if role == "system":
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# Gemini doesn't have system role, prepend to first user message
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if gemini_messages and gemini_messages[0].role == "user":
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gemini_messages[0].parts[
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0
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].text = f"{content}\n\n{gemini_messages[0].parts[0].text}"
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else:
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gemini_messages.append(
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types.Content(
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role="user", parts=[types.Part.from_text(text=content)]
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)
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)
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elif role == "assistant":
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gemini_messages.append(
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types.Content(
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role="model", parts=[types.Part.from_text(text=content)]
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)
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)
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elif role == "tool":
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# Handle tool response
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function_response = {
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"name": msg.get("name", ""),
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"response": content,
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}
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gemini_messages.append(
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types.Content(
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role="function",
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parts=[
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types.Part.from_function_response(function_response)
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],
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)
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)
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else: # user
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gemini_messages.append(
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types.Content(
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role="user", parts=[types.Part.from_text(text=content)]
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)
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)
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# Convert tools to Gemini format
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gemini_tools = None
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if tools:
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gemini_tools = []
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for tool in tools:
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if tool.get("type") == "function":
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func = tool.get("function", {})
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gemini_tools.append(
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types.Tool(
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function_declarations=[
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types.FunctionDeclaration(
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name=func.get("name", ""),
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description=func.get("description", ""),
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parameters=func.get("parameters", {}),
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)
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]
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)
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)
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# Configure tool choice
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tool_config = None
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if tool_choice:
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if tool_choice == "none":
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tool_config = types.ToolConfig(
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function_calling_config=types.FunctionCallingConfig(mode="NONE")
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)
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elif tool_choice == "auto":
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tool_config = types.ToolConfig(
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function_calling_config=types.FunctionCallingConfig(mode="AUTO")
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)
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elif tool_choice == "required":
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tool_config = types.ToolConfig(
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function_calling_config=types.FunctionCallingConfig(mode="ANY")
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)
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# Build request config
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config_params = {"candidate_count": 1}
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if gemini_tools:
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config_params["tools"] = gemini_tools
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if tool_config:
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config_params["tool_config"] = tool_config
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# Merge runtime_options
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if isinstance(self.genai_config.runtime_options, dict):
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config_params.update(self.genai_config.runtime_options)
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response = self.provider.models.generate_content(
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model=self.genai_config.model,
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contents=gemini_messages,
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config=types.GenerateContentConfig(**config_params),
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)
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# Check if response is valid
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if not response or not response.candidates:
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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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candidate = response.candidates[0]
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content = None
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tool_calls = None
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# Extract content and tool calls from response
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if candidate.content and candidate.content.parts:
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for part in candidate.content.parts:
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if part.text:
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content = part.text.strip()
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elif part.function_call:
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# Handle function call
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if tool_calls is None:
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tool_calls = []
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try:
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arguments = (
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dict(part.function_call.args)
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if part.function_call.args
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else {}
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)
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except Exception:
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arguments = {}
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tool_calls.append(
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{
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"id": part.function_call.name or "",
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"name": part.function_call.name or "",
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"arguments": arguments,
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}
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)
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# Determine finish reason
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finish_reason = "error"
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if hasattr(candidate, "finish_reason") and candidate.finish_reason:
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from google.genai.types import FinishReason
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if candidate.finish_reason == FinishReason.STOP:
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finish_reason = "stop"
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elif candidate.finish_reason == FinishReason.MAX_TOKENS:
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finish_reason = "length"
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elif candidate.finish_reason in [
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FinishReason.SAFETY,
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FinishReason.RECITATION,
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]:
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finish_reason = "error"
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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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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 errors.APIError as e:
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logger.warning("Gemini API error during 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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except Exception as e:
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logger.warning(
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"Gemini returned an error during chat_with_tools: %s", str(e)
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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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