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Prefer Service.ThinkingConfig over raw ThinkingConfig class names in Anthropic and Google services and examples

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This commit is contained in:
Paul Kompfner
2026-03-11 12:34:10 -04:00
parent 6b168d6bbb
commit 51a8a28a99
6 changed files with 23 additions and 17 deletions
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4
examples/foundational/49a-thinking-anthropic.py
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@@ -22,7 +22,7 @@ from pipecat.processors.aggregators.llm_response_universal import (
)
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicThinkingConfig
from pipecat.services.anthropic.llm import AnthropicLLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.transports.base_transport import BaseTransport, TransportParams
@@ -64,7 +64,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm = AnthropicLLMService(
api_key=os.getenv("ANTHROPIC_API_KEY"),
settings=AnthropicLLMService.Settings(
thinking=AnthropicThinkingConfig(
thinking=AnthropicLLMService.ThinkingConfig(
type="enabled",
budget_tokens=2048,
),

4
examples/foundational/49b-thinking-google.py
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@@ -24,7 +24,7 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.google.llm import GoogleLLMService, GoogleThinkingConfig
from pipecat.services.google.llm import GoogleLLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
@@ -65,7 +65,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
api_key=os.getenv("GOOGLE_API_KEY"),
# model="gemini-3-pro-preview", # A more powerful reasoning model, but slower
settings=GoogleLLMService.Settings(
thinking=GoogleThinkingConfig(
thinking=GoogleLLMService.ThinkingConfig(
thinking_budget=-1, # Dynamic thinking
include_thoughts=True,
),

4
examples/foundational/49c-thinking-functions-anthropic.py
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@@ -23,7 +23,7 @@ from pipecat.processors.aggregators.llm_response_universal import (
)
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.anthropic.llm import AnthropicLLMService, AnthropicThinkingConfig
from pipecat.services.anthropic.llm import AnthropicLLMService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.llm_service import FunctionCallParams
@@ -85,7 +85,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
llm = AnthropicLLMService(
api_key=os.getenv("ANTHROPIC_API_KEY"),
settings=AnthropicLLMService.Settings(
thinking=AnthropicThinkingConfig(
thinking=AnthropicLLMService.ThinkingConfig(
type="enabled",
budget_tokens=2048,
),

4
examples/foundational/49d-thinking-functions-google.py
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@@ -25,7 +25,7 @@ from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.google.llm import GoogleLLMService, GoogleThinkingConfig
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
@@ -86,7 +86,7 @@ async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
api_key=os.getenv("GOOGLE_API_KEY"),
# model="gemini-3-pro-preview", # A more powerful reasoning model, but slower
settings=GoogleLLMService.Settings(
thinking=GoogleThinkingConfig(
thinking=GoogleLLMService.ThinkingConfig(
thinking_budget=-1, # Dynamic thinking
include_thoughts=True,
),

12
src/pipecat/services/anthropic/llm.py
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@@ -98,18 +98,20 @@ class AnthropicLLMSettings(LLMSettings):
"""
enable_prompt_caching: bool | _NotGiven = field(default_factory=lambda: _NOT_GIVEN)
thinking: AnthropicThinkingConfig | _NotGiven = field(default_factory=lambda: _NOT_GIVEN)
thinking: Union["AnthropicLLMService.ThinkingConfig", _NotGiven] = field(
default_factory=lambda: _NOT_GIVEN
)
@classmethod
def from_mapping(cls, settings):
"""Convert a plain dict to settings, coercing thinking dicts.
For backward compatibility, a ``thinking`` value that is a plain dict
is converted to a :class:`AnthropicThinkingConfig`.
is converted to a :class:`AnthropicLLMService.ThinkingConfig`.
"""
instance = super().from_mapping(settings)
if is_given(instance.thinking) and isinstance(instance.thinking, dict):
instance.thinking = AnthropicThinkingConfig(**instance.thinking)
instance.thinking = AnthropicLLMService.ThinkingConfig(**instance.thinking)
return instance
@@ -199,7 +201,9 @@ class AnthropicLLMService(LLMService):
temperature: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
top_k: Optional[int] = Field(default_factory=lambda: NOT_GIVEN, ge=0)
top_p: Optional[float] = Field(default_factory=lambda: NOT_GIVEN, ge=0.0, le=1.0)
thinking: Optional[AnthropicThinkingConfig] = Field(default_factory=lambda: NOT_GIVEN)
thinking: Optional["AnthropicLLMService.ThinkingConfig"] = Field(
default_factory=lambda: NOT_GIVEN
)
extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
def model_post_init(self, __context):

12
src/pipecat/services/google/llm.py
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@@ -16,7 +16,7 @@ import json
import os
import uuid
from dataclasses import dataclass, field
from typing import Any, AsyncIterator, Dict, List, Literal, Optional
from typing import Any, AsyncIterator, Dict, List, Literal, Optional, Union
from loguru import logger
from PIL import Image
@@ -719,18 +719,20 @@ class GoogleLLMSettings(LLMSettings):
thinking: Thinking configuration.
"""
thinking: GoogleThinkingConfig | _NotGiven = field(default_factory=lambda: NOT_GIVEN)
thinking: Union["GoogleLLMService.ThinkingConfig", _NotGiven] = field(
default_factory=lambda: NOT_GIVEN
)
@classmethod
def from_mapping(cls, settings):
"""Convert a plain dict to settings, coercing thinking dicts.
For backward compatibility, a ``thinking`` value that is a plain dict
is converted to a :class:`GoogleThinkingConfig`.
is converted to a :class:`GoogleLLMService.ThinkingConfig`.
"""
instance = super().from_mapping(settings)
if is_given(instance.thinking) and isinstance(instance.thinking, dict):
instance.thinking = GoogleThinkingConfig(**instance.thinking)
instance.thinking = GoogleLLMService.ThinkingConfig(**instance.thinking)
return instance
@@ -775,7 +777,7 @@ class GoogleLLMService(LLMService):
temperature: Optional[float] = Field(default=None, ge=0.0, le=2.0)
top_k: Optional[int] = Field(default=None, ge=0)
top_p: Optional[float] = Field(default=None, ge=0.0, le=1.0)
thinking: Optional[GoogleThinkingConfig] = Field(default=None)
thinking: Optional["GoogleLLMService.ThinkingConfig"] = Field(default=None)
extra: Optional[Dict[str, Any]] = Field(default_factory=dict)
def __init__(