feat: Return nested tool returns (#5305)
* Adapt to support multiple tool returns * remove unused create_tool_return_message * Add explanation to otid index * Simplify explicit tool returns * Simplify function return to only return single object
This commit is contained in:
Matthew Zhou
committed by
Caren Thomas
Caren Thomas
parent
207ef28fd9
commit
b06619c290
@@ -328,7 +328,7 @@ class Message(BaseMessage):
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),
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)
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elif self.role == MessageRole.tool:
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messages.extend(self._convert_tool_return_message())
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messages.append(self._convert_tool_return_message())
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elif self.role == MessageRole.user:
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messages.append(self._convert_user_message())
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elif self.role == MessageRole.system:
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@@ -629,7 +629,7 @@ class Message(BaseMessage):
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return messages
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def _convert_tool_return_message(self) -> List[ToolReturnMessage]:
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def _convert_tool_return_message(self) -> ToolReturnMessage:
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"""Convert tool role message to ToolReturnMessage.
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The tool return is packaged as follows:
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@@ -640,7 +640,7 @@ class Message(BaseMessage):
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}
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Returns:
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List[ToolReturnMessage]: Converted tool return messages
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ToolReturnMessage: Converted tool return message
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Raises:
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ValueError: If message role is not 'tool', parsing fails, or no valid content exists
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@@ -660,27 +660,49 @@ class Message(BaseMessage):
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return self._convert_legacy_tool_return()
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def _convert_explicit_tool_returns(self) -> List[ToolReturnMessage]:
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"""Convert explicit tool returns to ToolReturnMessage list."""
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tool_returns = []
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def _convert_explicit_tool_returns(self) -> ToolReturnMessage:
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"""Convert explicit tool returns to a single ToolReturnMessage."""
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from letta.schemas.letta_message import ToolReturn as ToolReturnSchema
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for index, tool_return in enumerate(self.tool_returns):
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# build list of all tool return objects
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all_tool_returns = []
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for tool_return in self.tool_returns:
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parsed_data = self._parse_tool_response(tool_return.func_response)
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tool_returns.append(
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self._create_tool_return_message(
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message_text=parsed_data["message"],
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status=parsed_data["status"],
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tool_call_id=tool_return.tool_call_id,
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stdout=tool_return.stdout,
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stderr=tool_return.stderr,
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otid_index=index,
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)
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tool_return_obj = ToolReturnSchema(
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tool_return=parsed_data["message"],
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status=parsed_data["status"],
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tool_call_id=tool_return.tool_call_id,
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stdout=tool_return.stdout,
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stderr=tool_return.stderr,
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)
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all_tool_returns.append(tool_return_obj)
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return tool_returns
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if not all_tool_returns:
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# this should not happen if tool_returns is non-empty, but handle gracefully
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raise ValueError("No tool returns to convert")
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def _convert_legacy_tool_return(self) -> List[ToolReturnMessage]:
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first_tool_return = all_tool_returns[0]
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return ToolReturnMessage(
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id=self.id,
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date=self.created_at,
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# deprecated top-level fields populated from first tool return
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tool_return=first_tool_return.tool_return,
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status=first_tool_return.status,
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tool_call_id=first_tool_return.tool_call_id,
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stdout=first_tool_return.stdout,
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stderr=first_tool_return.stderr,
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tool_returns=all_tool_returns,
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name=self.name,
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otid=Message.generate_otid_from_id(self.id, 0),
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sender_id=self.sender_id,
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step_id=self.step_id,
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is_err=self.is_err,
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run_id=self.run_id,
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)
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def _convert_legacy_tool_return(self) -> ToolReturnMessage:
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"""Convert legacy single text content to ToolReturnMessage."""
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if not self._has_single_text_content():
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raise ValueError(f"No valid tool returns to convert: {self}")
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@@ -688,16 +710,14 @@ class Message(BaseMessage):
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text_content = self.content[0].text
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parsed_data = self._parse_tool_response(text_content)
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return [
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self._create_tool_return_message(
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message_text=parsed_data["message"],
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status=parsed_data["status"],
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tool_call_id=self.tool_call_id,
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stdout=None,
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stderr=None,
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otid_index=0,
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)
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]
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return self._create_tool_return_message(
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message_text=parsed_data["message"],
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status=parsed_data["status"],
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tool_call_id=self.tool_call_id,
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stdout=None,
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stderr=None,
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otid_index=0,
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)
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def _has_single_text_content(self) -> bool:
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"""Check if message has exactly one text content item."""
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@@ -1,7 +1,7 @@
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{
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"agents": [
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{
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"name": "test_export_import_fb3c857d-b25b-4666-9197-3966a2458cb0",
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"name": "test_export_import_57426498-f708-4228-a331-5efc0087b895",
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"memory_blocks": [],
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"tools": [],
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"tool_ids": [
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@@ -20,23 +20,23 @@
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"block-2"
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],
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"tool_rules": [
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{
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"tool_name": "memory_replace",
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"type": "continue_loop",
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"prompt_template": null
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},
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{
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"tool_name": "send_message",
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"type": "exit_loop",
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"prompt_template": null
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},
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{
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"tool_name": "conversation_search",
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"tool_name": "memory_insert",
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"type": "continue_loop",
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"prompt_template": null
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},
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{
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"tool_name": "memory_insert",
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"tool_name": "memory_replace",
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"type": "continue_loop",
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"prompt_template": null
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},
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{
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"tool_name": "conversation_search",
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"type": "continue_loop",
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"prompt_template": null
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}
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@@ -129,7 +129,8 @@
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"content": [
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{
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"type": "text",
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"text": "You are a helpful assistant specializing in data analysis and mathematical computations.\n\n<memory_blocks>\nThe following memory blocks are currently engaged in your core memory unit:\n\n<persona>\n<description>\nThe persona block: Stores details about your current persona, guiding how you behave and respond. This helps you to maintain consistency and personality in your interactions.\n</description>\n<metadata>\n- chars_current=195\n- chars_limit=8000\n</metadata>\n<value>\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: You are Alex, a data analyst and mathematician who helps users with calculations and insights. You have extensive experience in statistical analysis and prefer to provide clear, accurate results.\n</value>\n</persona>\n\n<human>\n<description>\nThe human block: Stores key details about the person you are conversing with, allowing for more personalized and friend-like conversation.\n</description>\n<metadata>\n- chars_current=175\n- chars_limit=4000\n</metadata>\n<value>\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: username: sarah_researcher\nLine 2: occupation: data scientist\nLine 3: interests: machine learning, statistics, fibonacci sequences\nLine 4: preferred_communication: detailed explanations with examples\n</value>\n</human>\n\n<project_context>\n<description>\n\n</description>\n<metadata>\n- chars_current=210\n- chars_limit=6000\n</metadata>\n<value>\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: Current project: Building predictive models for financial markets. Sarah is working on sequence analysis and pattern recognition. Recently interested in mathematical sequences like Fibonacci for trend analysis.\n</value>\n</project_context>\n\n</memory_blocks>\n\n<tool_usage_rules>\nThe following constraints define rules for tool usage and guide desired behavior. These rules must be followed to ensure proper tool execution and workflow. A single response may contain multiple tool calls.\n\n<tool_rule>\nmemory_replace requires continuing your response when called\n</tool_rule>\n<tool_rule>\nconversation_search requires continuing your response when called\n</tool_rule>\n<tool_rule>\nmemory_insert requires continuing your response when called\n</tool_rule>\n<tool_rule>\nsend_message ends your response (yields control) when called\n</tool_rule>\n</tool_usage_rules>\n\n<memory_metadata>\n- The current system date is: September 26, 2025\n- Memory blocks were last modified: 2025-09-26 05:01:19 AM UTC+0000\n- -1 previous messages between you and the user are stored in recall memory (use tools to access them)\n- 2 total memories you created are stored in archival memory (use tools to access them)\n</memory_metadata>"
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"text": "You are a helpful assistant specializing in data analysis and mathematical computations.\n\n<memory_blocks>\nThe following memory blocks are currently engaged in your core memory unit:\n\n<project_context>\n<description>\n\n</description>\n<metadata>\n- chars_current=210\n- chars_limit=6000\n</metadata>\n<value>\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: Current project: Building predictive models for financial markets. Sarah is working on sequence analysis and pattern recognition. Recently interested in mathematical sequences like Fibonacci for trend analysis.\n</value>\n</project_context>\n\n<human>\n<description>\nThe human block: Stores key details about the person you are conversing with, allowing for more personalized and friend-like conversation.\n</description>\n<metadata>\n- chars_current=175\n- chars_limit=4000\n</metadata>\n<value>\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: username: sarah_researcher\nLine 2: occupation: data scientist\nLine 3: interests: machine learning, statistics, fibonacci sequences\nLine 4: preferred_communication: detailed explanations with examples\n</value>\n</human>\n\n<persona>\n<description>\nThe persona block: Stores details about your current persona, guiding how you behave and respond. This helps you to maintain consistency and personality in your interactions.\n</description>\n<metadata>\n- chars_current=195\n- chars_limit=8000\n</metadata>\n<value>\n# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\nLine 1: You are Alex, a data analyst and mathematician who helps users with calculations and insights. You have extensive experience in statistical analysis and prefer to provide clear, accurate results.\n</value>\n</persona>\n\n</memory_blocks>\n\n<tool_usage_rules>\nThe following constraints define rules for tool usage and guide desired behavior. These rules must be followed to ensure proper tool execution and workflow. A single response may contain multiple tool calls.\n\n<tool_rule>\nmemory_insert requires continuing your response when called\n</tool_rule>\n<tool_rule>\nmemory_replace requires continuing your response when called\n</tool_rule>\n<tool_rule>\nconversation_search requires continuing your response when called\n</tool_rule>\n<tool_rule>\nsend_message ends your response (yields control) when called\n</tool_rule>\n</tool_usage_rules>\n\n<memory_metadata>\n- The current system date is: October 10, 2025\n- Memory blocks were last modified: 2025-10-10 12:21:30 AM UTC+0000\n- -1 previous messages between you and the user are stored in recall memory (use tools to access them)\n- 2 total memories you created are stored in archival memory (use tools to access them)\n</memory_metadata>",
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"signature": null
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}
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],
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"name": null,
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@@ -143,7 +144,10 @@
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"tool_calls": null,
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"tool_call_id": null,
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"tool_returns": [],
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"created_at": "2025-09-26T05:01:17.251536+00:00"
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"created_at": "2025-10-10T00:21:29.139951+00:00",
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"approve": null,
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"approval_request_id": null,
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"denial_reason": null
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},
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{
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"type": "message",
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@@ -151,7 +155,8 @@
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"content": [
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{
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"type": "text",
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"text": "Bootup sequence complete. Persona activated. Testing messaging functionality."
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"text": "Bootup sequence complete. Persona activated. Testing messaging functionality.",
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"signature": null
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}
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],
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"name": null,
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@@ -164,7 +169,7 @@
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"agent_id": "agent-0",
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"tool_calls": [
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{
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"id": "d734f768-4f38-4dfb-993f-3b7220e3466c",
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"id": "9b3e8290-a336-4e3b-851e-2472ccd6fe91",
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"function": {
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"arguments": "{\n \"message\": \"More human than human is our motto.\"\n}",
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"name": "send_message"
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@@ -174,7 +179,10 @@
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],
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"tool_call_id": null,
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"tool_returns": [],
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"created_at": "2025-09-26T05:01:17.251576+00:00"
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"created_at": "2025-10-10T00:21:29.139990+00:00",
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"approve": null,
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"approval_request_id": null,
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"denial_reason": null
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},
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{
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"type": "message",
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@@ -182,7 +190,8 @@
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"content": [
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{
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"type": "text",
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"text": "{\n \"status\": \"OK\",\n \"message\": null,\n \"time\": \"2025-09-26 05:01:17 AM UTC+0000\"\n}"
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"text": "{\n \"status\": \"OK\",\n \"message\": null,\n \"time\": \"2025-10-10 12:21:29 AM UTC+0000\"\n}",
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"signature": null
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}
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],
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"name": "send_message",
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@@ -194,9 +203,12 @@
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"model": "gpt-4.1-mini",
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"agent_id": "agent-0",
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"tool_calls": null,
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"tool_call_id": "d734f768-4f38-4dfb-993f-3b7220e3466c",
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"tool_call_id": "9b3e8290-a336-4e3b-851e-2472ccd6fe91",
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"tool_returns": [],
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"created_at": "2025-09-26T05:01:17.251607+00:00"
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"created_at": "2025-10-10T00:21:29.140013+00:00",
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"approve": null,
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"approval_request_id": null,
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"denial_reason": null
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},
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{
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"type": "message",
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@@ -204,7 +216,8 @@
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"content": [
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{
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"type": "text",
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"text": "{\n \"type\": \"login\",\n \"last_login\": \"Never (first login)\",\n \"time\": \"2025-09-26 05:01:17 AM UTC+0000\"\n}"
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"text": "{\n \"type\": \"login\",\n \"last_login\": \"Never (first login)\",\n \"time\": \"2025-10-10 12:21:29 AM UTC+0000\"\n}",
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"signature": null
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}
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],
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"name": null,
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@@ -218,7 +231,10 @@
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"tool_calls": null,
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"tool_call_id": null,
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"tool_returns": [],
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"created_at": "2025-09-26T05:01:17.251623+00:00"
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"created_at": "2025-10-10T00:21:29.140024+00:00",
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"approve": null,
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"approval_request_id": null,
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"denial_reason": null
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},
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{
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"type": "message",
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@@ -226,7 +242,8 @@
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"content": [
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{
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"type": "text",
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"text": "Test message for export"
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"text": "Test message for export",
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"signature": null
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}
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],
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"name": null,
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@@ -240,7 +257,10 @@
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"tool_calls": null,
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"tool_call_id": null,
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"tool_returns": [],
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"created_at": "2025-09-26T05:01:18.840105+00:00"
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"created_at": "2025-10-10T00:21:30.360611+00:00",
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"approve": null,
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"approval_request_id": null,
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"denial_reason": null
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},
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{
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"type": "message",
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@@ -248,7 +268,8 @@
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"content": [
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{
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"type": "text",
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"text": "Confirming receipt of test message from user."
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"text": "Responding to test message for export.",
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"signature": null
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}
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],
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"name": null,
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@@ -261,17 +282,20 @@
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"agent_id": "agent-0",
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"tool_calls": [
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{
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"id": "call_ktYL78z2mTh3w1t6pWixMHqA",
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"id": "call_mNAOnZ212k0eehF005T5s6Wn",
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"function": {
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"arguments": "{\"message\": \"Received your test message for export successfully. Let me know if you need any calculations or data analysis.\", \"request_heartbeat\": false}",
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"arguments": "{\"message\": \"Received your test message for export. Everything is working fine on my end. How can I assist you further today?\", \"request_heartbeat\": false}",
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"name": "send_message"
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},
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"type": "function"
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}
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],
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"tool_call_id": "call_ktYL78z2mTh3w1t6pWixMHqA",
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"tool_call_id": "call_mNAOnZ212k0eehF005T5s6Wn",
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"tool_returns": [],
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"created_at": "2025-09-26T05:01:20.466363+00:00"
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"created_at": "2025-10-10T00:21:31.900813+00:00",
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"approve": null,
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"approval_request_id": null,
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"denial_reason": null
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},
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{
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"type": "message",
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@@ -279,7 +303,8 @@
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"content": [
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{
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"type": "text",
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"text": "{\n \"status\": \"OK\",\n \"message\": \"Sent message successfully.\",\n \"time\": \"2025-09-26 05:01:20 AM UTC+0000\"\n}"
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"text": "{\n \"status\": \"OK\",\n \"message\": \"Sent message successfully.\",\n \"time\": \"2025-10-10 12:21:31 AM UTC+0000\"\n}",
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"signature": null
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}
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],
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"name": "send_message",
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@@ -291,15 +316,20 @@
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"model": "gpt-4.1-mini",
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"agent_id": "agent-0",
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"tool_calls": null,
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"tool_call_id": "call_ktYL78z2mTh3w1t6pWixMHqA",
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"tool_call_id": "call_mNAOnZ212k0eehF005T5s6Wn",
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"tool_returns": [
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{
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"tool_call_id": "call_mNAOnZ212k0eehF005T5s6Wn",
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"status": "success",
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"stdout": null,
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"stderr": null
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"stderr": null,
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"func_response": "{\n \"status\": \"OK\",\n \"message\": \"Sent message successfully.\",\n \"time\": \"2025-10-10 12:21:31 AM UTC+0000\"\n}"
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}
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],
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"created_at": "2025-09-26T05:01:20.466485+00:00"
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"created_at": "2025-10-10T00:21:31.900994+00:00",
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"approve": null,
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"approval_request_id": null,
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"denial_reason": null
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}
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],
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"files_agents": [],
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@@ -367,7 +397,7 @@
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"sources": [],
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"tools": [
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{
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"id": "tool-1",
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"id": "tool-2",
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"tool_type": "custom",
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"description": "Analyze data and provide insights.",
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"source_type": "json",
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@@ -411,7 +441,7 @@
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"metadata_": {}
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},
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{
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"id": "tool-6",
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"id": "tool-3",
|
||||
"tool_type": "custom",
|
||||
"description": "Calculate the nth Fibonacci number.",
|
||||
"source_type": "json",
|
||||
@@ -449,7 +479,7 @@
|
||||
{
|
||||
"id": "tool-4",
|
||||
"tool_type": "letta_core",
|
||||
"description": "Search prior conversation history using hybrid search (text + semantic similarity).\n\nExamples:\n # Search all messages\n conversation_search(query=\"project updates\")\n\n # Search only assistant messages\n conversation_search(query=\"error handling\", roles=[\"assistant\"])\n\n # Search with date range (inclusive of both dates)\n conversation_search(query=\"meetings\", start_date=\"2024-01-15\", end_date=\"2024-01-20\")\n # This includes all messages from Jan 15 00:00:00 through Jan 20 23:59:59\n\n # Search messages from a specific day (inclusive)\n conversation_search(query=\"bug reports\", start_date=\"2024-09-04\", end_date=\"2024-09-04\")\n # This includes ALL messages from September 4, 2024\n\n # Search with specific time boundaries\n conversation_search(query=\"deployment\", start_date=\"2024-01-15T09:00\", end_date=\"2024-01-15T17:30\")\n # This includes messages from 9 AM to 5:30 PM on Jan 15\n\n # Search with limit\n conversation_search(query=\"debugging\", limit=10)",
|
||||
"description": "Search prior conversation history using hybrid search (text + semantic similarity).\n\nExamples:\n # Search all messages\n conversation_search(query=\"project updates\")\n\n # Search only assistant messages\n conversation_search(query=\"error handling\", roles=[\"assistant\"])\n\n # Search with date range (inclusive of both dates)\n conversation_search(query=\"meetings\", start_date=\"2024-01-15\", end_date=\"2024-01-20\")\n # This includes all messages from Jan 15 00:00:00 through Jan 20 23:59:59\n\n # Search messages from a specific day (inclusive)\n conversation_search(query=\"bug reports\", start_date=\"2024-09-04\", end_date=\"2024-09-04\")\n # This includes ALL messages from September 4, 2024\n\n # Search with specific time boundaries\n conversation_search(query=\"deployment\", start_date=\"2024-01-15T09:00\", end_date=\"2024-01-15T17:30\")\n # This includes messages from 9 AM to 5:30 PM on Jan 15\n\n # Search with limit\n conversation_search(query=\"debugging\", limit=10)\n\n Returns:\n str: Query result string containing matching messages with timestamps and content.",
|
||||
"source_type": "python",
|
||||
"name": "conversation_search",
|
||||
"tags": [
|
||||
@@ -458,7 +488,7 @@
|
||||
"source_code": null,
|
||||
"json_schema": {
|
||||
"name": "conversation_search",
|
||||
"description": "Search prior conversation history using hybrid search (text + semantic similarity).\n\nExamples:\n # Search all messages\n conversation_search(query=\"project updates\")\n\n # Search only assistant messages\n conversation_search(query=\"error handling\", roles=[\"assistant\"])\n\n # Search with date range (inclusive of both dates)\n conversation_search(query=\"meetings\", start_date=\"2024-01-15\", end_date=\"2024-01-20\")\n # This includes all messages from Jan 15 00:00:00 through Jan 20 23:59:59\n\n # Search messages from a specific day (inclusive)\n conversation_search(query=\"bug reports\", start_date=\"2024-09-04\", end_date=\"2024-09-04\")\n # This includes ALL messages from September 4, 2024\n\n # Search with specific time boundaries\n conversation_search(query=\"deployment\", start_date=\"2024-01-15T09:00\", end_date=\"2024-01-15T17:30\")\n # This includes messages from 9 AM to 5:30 PM on Jan 15\n\n # Search with limit\n conversation_search(query=\"debugging\", limit=10)",
|
||||
"description": "Search prior conversation history using hybrid search (text + semantic similarity).\n\nExamples:\n # Search all messages\n conversation_search(query=\"project updates\")\n\n # Search only assistant messages\n conversation_search(query=\"error handling\", roles=[\"assistant\"])\n\n # Search with date range (inclusive of both dates)\n conversation_search(query=\"meetings\", start_date=\"2024-01-15\", end_date=\"2024-01-20\")\n # This includes all messages from Jan 15 00:00:00 through Jan 20 23:59:59\n\n # Search messages from a specific day (inclusive)\n conversation_search(query=\"bug reports\", start_date=\"2024-09-04\", end_date=\"2024-09-04\")\n # This includes ALL messages from September 4, 2024\n\n # Search with specific time boundaries\n conversation_search(query=\"deployment\", start_date=\"2024-01-15T09:00\", end_date=\"2024-01-15T17:30\")\n # This includes messages from 9 AM to 5:30 PM on Jan 15\n\n # Search with limit\n conversation_search(query=\"debugging\", limit=10)\n\n Returns:\n str: Query result string containing matching messages with timestamps and content.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
@@ -506,7 +536,7 @@
|
||||
"metadata_": {}
|
||||
},
|
||||
{
|
||||
"id": "tool-3",
|
||||
"id": "tool-1",
|
||||
"tool_type": "custom",
|
||||
"description": "Get user preferences for a specific category.",
|
||||
"source_type": "json",
|
||||
@@ -542,9 +572,9 @@
|
||||
"metadata_": {}
|
||||
},
|
||||
{
|
||||
"id": "tool-5",
|
||||
"id": "tool-0",
|
||||
"tool_type": "letta_sleeptime_core",
|
||||
"description": "The memory_insert command allows you to insert text at a specific location in a memory block.\n\nExamples:\n # Update a block containing information about the user (append to the end of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\")\n\n # Update a block containing information about the user (insert at the beginning of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\", insert_line=0)",
|
||||
"description": "The memory_insert command allows you to insert text at a specific location in a memory block.\n\nExamples:\n # Update a block containing information about the user (append to the end of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\")\n\n # Update a block containing information about the user (insert at the beginning of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\", insert_line=0)\n\n Returns:\n Optional[str]: None is always returned as this function does not produce a response.",
|
||||
"source_type": "python",
|
||||
"name": "memory_insert",
|
||||
"tags": [
|
||||
@@ -553,7 +583,7 @@
|
||||
"source_code": null,
|
||||
"json_schema": {
|
||||
"name": "memory_insert",
|
||||
"description": "The memory_insert command allows you to insert text at a specific location in a memory block.\n\nExamples:\n # Update a block containing information about the user (append to the end of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\")\n\n # Update a block containing information about the user (insert at the beginning of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\", insert_line=0)",
|
||||
"description": "The memory_insert command allows you to insert text at a specific location in a memory block.\n\nExamples:\n # Update a block containing information about the user (append to the end of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\")\n\n # Update a block containing information about the user (insert at the beginning of the block)\n memory_insert(label=\"customer\", new_str=\"The customer's ticket number is 12345\", insert_line=0)\n\n Returns:\n Optional[str]: None is always returned as this function does not produce a response.",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
@@ -586,9 +616,9 @@
|
||||
"metadata_": {}
|
||||
},
|
||||
{
|
||||
"id": "tool-2",
|
||||
"id": "tool-5",
|
||||
"tool_type": "letta_sleeptime_core",
|
||||
"description": "The memory_replace command allows you to replace a specific string in a memory block with a new string. This is used for making precise edits.\n\nExamples:\n # Update a block containing information about the user\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"Their name is Bob\")\n\n # Update a block containing a todo list\n memory_replace(label=\"todos\", old_str=\"- [ ] Step 5: Search the web\", new_str=\"- [x] Step 5: Search the web\")\n\n # Pass an empty string to\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"\")\n\n # Bad example - do NOT add (view-only) line numbers to the args\n memory_replace(label=\"human\", old_str=\"Line 1: Their name is Alice\", new_str=\"Line 1: Their name is Bob\")\n\n # Bad example - do NOT include the number number warning either\n memory_replace(label=\"human\", old_str=\"# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\\nLine 1: Their name is Alice\", new_str=\"Line 1: Their name is Bob\")\n\n # Good example - no line numbers or line number warning (they are view-only), just the text\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"Their name is Bob\")",
|
||||
"description": "The memory_replace command allows you to replace a specific string in a memory block with a new string. This is used for making precise edits.\n\nExamples:\n # Update a block containing information about the user\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"Their name is Bob\")\n\n # Update a block containing a todo list\n memory_replace(label=\"todos\", old_str=\"- [ ] Step 5: Search the web\", new_str=\"- [x] Step 5: Search the web\")\n\n # Pass an empty string to\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"\")\n\n # Bad example - do NOT add (view-only) line numbers to the args\n memory_replace(label=\"human\", old_str=\"Line 1: Their name is Alice\", new_str=\"Line 1: Their name is Bob\")\n\n # Bad example - do NOT include the number number warning either\n memory_replace(label=\"human\", old_str=\"# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\\nLine 1: Their name is Alice\", new_str=\"Line 1: Their name is Bob\")\n\n # Good example - no line numbers or line number warning (they are view-only), just the text\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"Their name is Bob\")\n\n Returns:\n str: The success message",
|
||||
"source_type": "python",
|
||||
"name": "memory_replace",
|
||||
"tags": [
|
||||
@@ -597,7 +627,7 @@
|
||||
"source_code": null,
|
||||
"json_schema": {
|
||||
"name": "memory_replace",
|
||||
"description": "The memory_replace command allows you to replace a specific string in a memory block with a new string. This is used for making precise edits.\n\nExamples:\n # Update a block containing information about the user\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"Their name is Bob\")\n\n # Update a block containing a todo list\n memory_replace(label=\"todos\", old_str=\"- [ ] Step 5: Search the web\", new_str=\"- [x] Step 5: Search the web\")\n\n # Pass an empty string to\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"\")\n\n # Bad example - do NOT add (view-only) line numbers to the args\n memory_replace(label=\"human\", old_str=\"Line 1: Their name is Alice\", new_str=\"Line 1: Their name is Bob\")\n\n # Bad example - do NOT include the number number warning either\n memory_replace(label=\"human\", old_str=\"# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\\nLine 1: Their name is Alice\", new_str=\"Line 1: Their name is Bob\")\n\n # Good example - no line numbers or line number warning (they are view-only), just the text\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"Their name is Bob\")",
|
||||
"description": "The memory_replace command allows you to replace a specific string in a memory block with a new string. This is used for making precise edits.\n\nExamples:\n # Update a block containing information about the user\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"Their name is Bob\")\n\n # Update a block containing a todo list\n memory_replace(label=\"todos\", old_str=\"- [ ] Step 5: Search the web\", new_str=\"- [x] Step 5: Search the web\")\n\n # Pass an empty string to\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"\")\n\n # Bad example - do NOT add (view-only) line numbers to the args\n memory_replace(label=\"human\", old_str=\"Line 1: Their name is Alice\", new_str=\"Line 1: Their name is Bob\")\n\n # Bad example - do NOT include the number number warning either\n memory_replace(label=\"human\", old_str=\"# NOTE: Line numbers shown below are to help during editing. Do NOT include line number prefixes in your memory edit tool calls.\\nLine 1: Their name is Alice\", new_str=\"Line 1: Their name is Bob\")\n\n # Good example - no line numbers or line number warning (they are view-only), just the text\n memory_replace(label=\"human\", old_str=\"Their name is Alice\", new_str=\"Their name is Bob\")\n\n Returns:\n str: The success message",
|
||||
"parameters": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
@@ -631,7 +661,7 @@
|
||||
"metadata_": {}
|
||||
},
|
||||
{
|
||||
"id": "tool-0",
|
||||
"id": "tool-6",
|
||||
"tool_type": "letta_core",
|
||||
"description": "Sends a message to the human user.",
|
||||
"source_type": "python",
|
||||
@@ -668,7 +698,7 @@
|
||||
],
|
||||
"mcp_servers": [],
|
||||
"metadata": {
|
||||
"revision_id": "567e9fe06270"
|
||||
"revision_id": "c734cfc0d595"
|
||||
},
|
||||
"created_at": "2025-09-26T05:01:21.039802+00:00"
|
||||
"created_at": "2025-10-10T00:21:32.284067+00:00"
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user