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255670b
update
fengju0213 Sep 30, 2025
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Update chat_agent.py
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Merge branch 'master' into enhance_update_memory
Wendong-Fan Oct 2, 2025
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Wendong-Fan Oct 5, 2025
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minor enhance
Wendong-Fan Oct 5, 2025
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Merge branch 'master' into enhance_update_memory
fengju0213 Oct 5, 2025
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Update chat_agent.py
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fengju0213 Oct 14, 2025
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Update chat_agent.py
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Update chat_agent.py
fengju0213 Oct 21, 2025
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Update chat_agent.py
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Update chat_agent.py
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Update test_chat_agent.py
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Update test_chat_agent.py
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fengju0213 Oct 24, 2025
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Merge branch 'master' into enhance_update_memory
Wendong-Fan Oct 25, 2025
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Update chat_agent.py
fengju0213 Oct 28, 2025
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update
fengju0213 Oct 28, 2025
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Update handle_token_limit.py
fengju0213 Oct 28, 2025
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Merge branch 'master' into enhance_update_memory
fengju0213 Oct 28, 2025
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update
fengju0213 Oct 29, 2025
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Update chat_agent.py
fengju0213 Oct 29, 2025
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Update chat_agent.py
fengju0213 Oct 30, 2025
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38 changes: 38 additions & 0 deletions camel/agents/_utils.py
Original file line number Diff line number Diff line change
Expand Up @@ -25,6 +25,44 @@
logger = logging.getLogger(__name__)


def build_default_summary_prompt(conversation_text: str) -> str:
r"""Create the default prompt used for conversation summarization.

Args:
conversation_text (str): The conversation to be summarized.

Returns:
str: A formatted prompt instructing the model to produce a structured
markdown summary.
"""
template = textwrap.dedent(
"""\
Summarize the conversation below.
Produce markdown that strictly follows this outline and numbering:

Summary:
1. **Primary Request and Intent**:
2. **Key Concepts**:
3. **Errors and Fixes**:
4. **Problem Solving**:
5. **Pending Tasks**:
6. **Current Work**:
7. **Optional Next Step**:

Requirements:
- Use bullet lists under each section (`- item`). If a section has no
information, output `- None noted`.
- Keep the ordering, headings, and formatting as written above.
- Focus on concrete actions, findings, and decisions.
- Do not invent details that are not supported by the conversation.

Conversation:
{conversation_text}
"""
)
return template.format(conversation_text=conversation_text)


def generate_tool_prompt(tool_schema_list: List[Dict[str, Any]]) -> str:
r"""Generates a tool prompt based on the provided tool schema list.

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