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102 lines
3.6 KiB
Python
102 lines
3.6 KiB
Python
# ========= Copyright 2023-2026 @ CAMEL-AI.org. All Rights Reserved. =========
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ========= Copyright 2023-2026 @ CAMEL-AI.org. All Rights Reserved. =========
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import re
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import textwrap
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from typing import Type
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from pydantic import BaseModel
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from camel.messages import OpenAIMessage
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def extract_thinking_from_content(
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content: str,
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reasoning_content: str | None = None,
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) -> tuple[str, str | None]:
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r"""Extract ``<think>`` tags from content into reasoning_content.
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Used for both pre-processing (stripping ``<think>`` tags from
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input messages before sending to the model) and post-processing
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(extracting ``<think>`` tags from model output into the
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``reasoning_content`` field).
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If the content contains ``<think>...</think>`` tags and
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``reasoning_content`` is not already set, extracts the thinking
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content and returns cleaned content with the reasoning.
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Args:
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content (str): The response content that may contain
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``<think>`` tags.
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reasoning_content (str | None): Existing reasoning content.
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If already set, no extraction is performed.
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(default: :obj:`None`)
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Returns:
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tuple[str, str | None]: A tuple of (cleaned_content,
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reasoning_content). If no extraction was needed, returns
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the original values unchanged.
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"""
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if reasoning_content is not None:
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return content, reasoning_content
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if '<think>' not in content or '</think>' not in content:
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return content, reasoning_content
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think_match = re.search(r'<think>(.*?)</think>', content, flags=re.DOTALL)
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if think_match:
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extracted = think_match.group(1).strip()
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# Only set reasoning_content if there's actual content
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if extracted:
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reasoning_content = extracted
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content = re.sub(
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r'<think>.*?</think>', '', content, flags=re.DOTALL
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).strip()
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return content, reasoning_content
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def try_modify_message_with_format(
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message: OpenAIMessage,
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response_format: Type[BaseModel] | None,
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) -> None:
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r"""Modifies the content of the message to include the instruction of using
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the response format.
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The message will not be modified in the following cases:
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- response_format is None
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- message content is not a string
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- message role is assistant
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Args:
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response_format (Type[BaseModel] | None): The Pydantic model class.
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message (OpenAIMessage): The message to be modified.
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"""
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if response_format is None:
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return
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if not isinstance(message["content"], str):
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return
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if message["role"] == "assistant":
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return
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json_schema = response_format.model_json_schema()
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updated_prompt = textwrap.dedent(
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f"""\
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{message["content"]}
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Please generate a JSON response adhering to the following JSON schema:
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{json_schema}
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Make sure the JSON response is valid and matches the EXACT structure defined in the schema. Your result should ONLY be a valid json object, WITHOUT ANY OTHER TEXT OR COMMENTS.
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""" # noqa: E501
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)
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message["content"] = updated_prompt
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