mirror of
https://github.com/Significant-Gravitas/AutoGPT.git
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Merge remote-tracking branch 'origin/dev' into lluisagusti/secrt-1926-agent-generation-completes-but-ui-does-not-update-refresh
This commit is contained in:
Lluis Agusti
@@ -2,7 +2,7 @@ import asyncio
|
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import logging
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import uuid
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from datetime import UTC, datetime
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from typing import Any
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from typing import Any, cast
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from weakref import WeakValueDictionary
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|
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from openai.types.chat import (
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@@ -104,6 +104,26 @@ class ChatSession(BaseModel):
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successful_agent_runs: dict[str, int] = {}
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successful_agent_schedules: dict[str, int] = {}
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def add_tool_call_to_current_turn(self, tool_call: dict) -> None:
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"""Attach a tool_call to the current turn's assistant message.
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Searches backwards for the most recent assistant message (stopping at
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any user message boundary). If found, appends the tool_call to it.
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Otherwise creates a new assistant message with the tool_call.
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"""
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for msg in reversed(self.messages):
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if msg.role == "user":
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break
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if msg.role == "assistant":
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if not msg.tool_calls:
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msg.tool_calls = []
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msg.tool_calls.append(tool_call)
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return
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self.messages.append(
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ChatMessage(role="assistant", content="", tool_calls=[tool_call])
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)
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@staticmethod
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def new(user_id: str) -> "ChatSession":
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return ChatSession(
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@@ -172,6 +192,47 @@ class ChatSession(BaseModel):
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successful_agent_schedules=successful_agent_schedules,
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)
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@staticmethod
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def _merge_consecutive_assistant_messages(
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messages: list[ChatCompletionMessageParam],
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) -> list[ChatCompletionMessageParam]:
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"""Merge consecutive assistant messages into single messages.
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Long-running tool flows can create split assistant messages: one with
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text content and another with tool_calls. Anthropic's API requires
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tool_result blocks to reference a tool_use in the immediately preceding
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assistant message, so these splits cause 400 errors via OpenRouter.
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"""
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if len(messages) < 2:
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return messages
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result: list[ChatCompletionMessageParam] = [messages[0]]
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for msg in messages[1:]:
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prev = result[-1]
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if prev.get("role") != "assistant" or msg.get("role") != "assistant":
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result.append(msg)
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continue
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prev = cast(ChatCompletionAssistantMessageParam, prev)
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curr = cast(ChatCompletionAssistantMessageParam, msg)
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curr_content = curr.get("content") or ""
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if curr_content:
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prev_content = prev.get("content") or ""
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prev["content"] = (
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f"{prev_content}\n{curr_content}" if prev_content else curr_content
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)
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curr_tool_calls = curr.get("tool_calls")
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if curr_tool_calls:
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prev_tool_calls = prev.get("tool_calls")
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prev["tool_calls"] = (
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list(prev_tool_calls) + list(curr_tool_calls)
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if prev_tool_calls
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else list(curr_tool_calls)
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)
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return result
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|
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def to_openai_messages(self) -> list[ChatCompletionMessageParam]:
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messages = []
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for message in self.messages:
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@@ -258,7 +319,7 @@ class ChatSession(BaseModel):
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name=message.name or "",
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)
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)
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return messages
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return self._merge_consecutive_assistant_messages(messages)
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async def _get_session_from_cache(session_id: str) -> ChatSession | None:
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@@ -1,4 +1,16 @@
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from typing import cast
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import pytest
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from openai.types.chat import (
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ChatCompletionAssistantMessageParam,
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ChatCompletionMessageParam,
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ChatCompletionToolMessageParam,
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ChatCompletionUserMessageParam,
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)
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from openai.types.chat.chat_completion_message_tool_call_param import (
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ChatCompletionMessageToolCallParam,
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Function,
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)
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from .model import (
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ChatMessage,
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@@ -117,3 +129,205 @@ async def test_chatsession_db_storage(setup_test_user, test_user_id):
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loaded.tool_calls is not None
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), f"Tool calls missing for {orig.role} message"
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assert len(orig.tool_calls) == len(loaded.tool_calls)
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|
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# --------------------------------------------------------------------------- #
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# _merge_consecutive_assistant_messages #
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# --------------------------------------------------------------------------- #
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_tc = ChatCompletionMessageToolCallParam(
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id="tc1", type="function", function=Function(name="do_stuff", arguments="{}")
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)
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_tc2 = ChatCompletionMessageToolCallParam(
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id="tc2", type="function", function=Function(name="other", arguments="{}")
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)
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def test_merge_noop_when_no_consecutive_assistants():
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"""Messages without consecutive assistants are returned unchanged."""
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msgs = [
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ChatCompletionUserMessageParam(role="user", content="hi"),
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ChatCompletionAssistantMessageParam(role="assistant", content="hello"),
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ChatCompletionUserMessageParam(role="user", content="bye"),
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]
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merged = ChatSession._merge_consecutive_assistant_messages(msgs)
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assert len(merged) == 3
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assert [m["role"] for m in merged] == ["user", "assistant", "user"]
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def test_merge_splits_text_and_tool_calls():
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"""The exact bug scenario: text-only assistant followed by tool_calls-only assistant."""
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msgs = [
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ChatCompletionUserMessageParam(role="user", content="build agent"),
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ChatCompletionAssistantMessageParam(
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role="assistant", content="Let me build that"
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),
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ChatCompletionAssistantMessageParam(
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role="assistant", content="", tool_calls=[_tc]
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),
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ChatCompletionToolMessageParam(role="tool", content="ok", tool_call_id="tc1"),
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]
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merged = ChatSession._merge_consecutive_assistant_messages(msgs)
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assert len(merged) == 3
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assert merged[0]["role"] == "user"
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assert merged[2]["role"] == "tool"
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a = cast(ChatCompletionAssistantMessageParam, merged[1])
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assert a["role"] == "assistant"
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assert a.get("content") == "Let me build that"
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assert a.get("tool_calls") == [_tc]
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def test_merge_combines_tool_calls_from_both():
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"""Both consecutive assistants have tool_calls — they get merged."""
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msgs: list[ChatCompletionAssistantMessageParam] = [
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ChatCompletionAssistantMessageParam(
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role="assistant", content="text", tool_calls=[_tc]
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),
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ChatCompletionAssistantMessageParam(
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role="assistant", content="", tool_calls=[_tc2]
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),
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]
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merged = ChatSession._merge_consecutive_assistant_messages(msgs) # type: ignore[arg-type]
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assert len(merged) == 1
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a = cast(ChatCompletionAssistantMessageParam, merged[0])
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assert a.get("tool_calls") == [_tc, _tc2]
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assert a.get("content") == "text"
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def test_merge_three_consecutive_assistants():
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"""Three consecutive assistants collapse into one."""
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msgs: list[ChatCompletionAssistantMessageParam] = [
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ChatCompletionAssistantMessageParam(role="assistant", content="a"),
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ChatCompletionAssistantMessageParam(role="assistant", content="b"),
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ChatCompletionAssistantMessageParam(
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role="assistant", content="", tool_calls=[_tc]
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),
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]
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merged = ChatSession._merge_consecutive_assistant_messages(msgs) # type: ignore[arg-type]
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assert len(merged) == 1
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a = cast(ChatCompletionAssistantMessageParam, merged[0])
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assert a.get("content") == "a\nb"
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assert a.get("tool_calls") == [_tc]
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def test_merge_empty_and_single_message():
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"""Edge cases: empty list and single message."""
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assert ChatSession._merge_consecutive_assistant_messages([]) == []
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|
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single: list[ChatCompletionMessageParam] = [
|
||||
ChatCompletionUserMessageParam(role="user", content="hi")
|
||||
]
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assert ChatSession._merge_consecutive_assistant_messages(single) == single
|
||||
|
||||
|
||||
# --------------------------------------------------------------------------- #
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# add_tool_call_to_current_turn #
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# --------------------------------------------------------------------------- #
|
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|
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_raw_tc = {
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"id": "tc1",
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"type": "function",
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"function": {"name": "f", "arguments": "{}"},
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}
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_raw_tc2 = {
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"id": "tc2",
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"type": "function",
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"function": {"name": "g", "arguments": "{}"},
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}
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|
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|
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def test_add_tool_call_appends_to_existing_assistant():
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"""When the last assistant is from the current turn, tool_call is added to it."""
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session = ChatSession.new(user_id="u")
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session.messages = [
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ChatMessage(role="user", content="hi"),
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ChatMessage(role="assistant", content="working on it"),
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]
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session.add_tool_call_to_current_turn(_raw_tc)
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assert len(session.messages) == 2 # no new message created
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assert session.messages[1].tool_calls == [_raw_tc]
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|
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|
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def test_add_tool_call_creates_assistant_when_none_exists():
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"""When there's no current-turn assistant, a new one is created."""
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session = ChatSession.new(user_id="u")
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session.messages = [
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ChatMessage(role="user", content="hi"),
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]
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session.add_tool_call_to_current_turn(_raw_tc)
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|
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assert len(session.messages) == 2
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assert session.messages[1].role == "assistant"
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assert session.messages[1].tool_calls == [_raw_tc]
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|
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|
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def test_add_tool_call_does_not_cross_user_boundary():
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"""A user message acts as a boundary — previous assistant is not modified."""
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session = ChatSession.new(user_id="u")
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session.messages = [
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ChatMessage(role="assistant", content="old turn"),
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ChatMessage(role="user", content="new message"),
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]
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session.add_tool_call_to_current_turn(_raw_tc)
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|
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assert len(session.messages) == 3 # new assistant was created
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assert session.messages[0].tool_calls is None # old assistant untouched
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assert session.messages[2].role == "assistant"
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assert session.messages[2].tool_calls == [_raw_tc]
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|
||||
|
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def test_add_tool_call_multiple_times():
|
||||
"""Multiple long-running tool calls accumulate on the same assistant."""
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session = ChatSession.new(user_id="u")
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session.messages = [
|
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ChatMessage(role="user", content="hi"),
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ChatMessage(role="assistant", content="doing stuff"),
|
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]
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session.add_tool_call_to_current_turn(_raw_tc)
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# Simulate a pending tool result in between (like _yield_tool_call does)
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session.messages.append(
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ChatMessage(role="tool", content="pending", tool_call_id="tc1")
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)
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session.add_tool_call_to_current_turn(_raw_tc2)
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|
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assert len(session.messages) == 3 # user, assistant, tool — no extra assistant
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assert session.messages[1].tool_calls == [_raw_tc, _raw_tc2]
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|
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|
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def test_to_openai_messages_merges_split_assistants():
|
||||
"""End-to-end: session with split assistants produces valid OpenAI messages."""
|
||||
session = ChatSession.new(user_id="u")
|
||||
session.messages = [
|
||||
ChatMessage(role="user", content="build agent"),
|
||||
ChatMessage(role="assistant", content="Let me build that"),
|
||||
ChatMessage(
|
||||
role="assistant",
|
||||
content="",
|
||||
tool_calls=[
|
||||
{
|
||||
"id": "tc1",
|
||||
"type": "function",
|
||||
"function": {"name": "create_agent", "arguments": "{}"},
|
||||
}
|
||||
],
|
||||
),
|
||||
ChatMessage(role="tool", content="done", tool_call_id="tc1"),
|
||||
ChatMessage(role="assistant", content="Saved!"),
|
||||
ChatMessage(role="user", content="show me an example run"),
|
||||
]
|
||||
openai_msgs = session.to_openai_messages()
|
||||
|
||||
# The two consecutive assistants at index 1,2 should be merged
|
||||
roles = [m["role"] for m in openai_msgs]
|
||||
assert roles == ["user", "assistant", "tool", "assistant", "user"]
|
||||
|
||||
# The merged assistant should have both content and tool_calls
|
||||
merged = cast(ChatCompletionAssistantMessageParam, openai_msgs[1])
|
||||
assert merged.get("content") == "Let me build that"
|
||||
tc_list = merged.get("tool_calls")
|
||||
assert tc_list is not None and len(list(tc_list)) == 1
|
||||
assert list(tc_list)[0]["id"] == "tc1"
|
||||
|
||||
@@ -800,9 +800,13 @@ async def stream_chat_completion(
|
||||
# Build the messages list in the correct order
|
||||
messages_to_save: list[ChatMessage] = []
|
||||
|
||||
# Add assistant message with tool_calls if any
|
||||
# Add assistant message with tool_calls if any.
|
||||
# Use extend (not assign) to preserve tool_calls already added by
|
||||
# _yield_tool_call for long-running tools.
|
||||
if accumulated_tool_calls:
|
||||
assistant_response.tool_calls = accumulated_tool_calls
|
||||
if not assistant_response.tool_calls:
|
||||
assistant_response.tool_calls = []
|
||||
assistant_response.tool_calls.extend(accumulated_tool_calls)
|
||||
logger.info(
|
||||
f"Added {len(accumulated_tool_calls)} tool calls to assistant message"
|
||||
)
|
||||
@@ -1404,13 +1408,9 @@ async def _yield_tool_call(
|
||||
operation_id=operation_id,
|
||||
)
|
||||
|
||||
# Save assistant message with tool_call FIRST (required by LLM)
|
||||
assistant_message = ChatMessage(
|
||||
role="assistant",
|
||||
content="",
|
||||
tool_calls=[tool_calls[yield_idx]],
|
||||
)
|
||||
session.messages.append(assistant_message)
|
||||
# Attach the tool_call to the current turn's assistant message
|
||||
# (or create one if this is a tool-only response with no text).
|
||||
session.add_tool_call_to_current_turn(tool_calls[yield_idx])
|
||||
|
||||
# Then save pending tool result
|
||||
pending_message = ChatMessage(
|
||||
|
||||
@@ -21,43 +21,71 @@ logger = logging.getLogger(__name__)
|
||||
|
||||
class HumanInTheLoopBlock(Block):
|
||||
"""
|
||||
This block pauses execution and waits for human approval or modification of the data.
|
||||
Pauses execution and waits for human approval or rejection of the data.
|
||||
|
||||
When executed, it creates a pending review entry and sets the node execution status
|
||||
to REVIEW. The execution will remain paused until a human user either:
|
||||
- Approves the data (with or without modifications)
|
||||
- Rejects the data
|
||||
When executed, this block creates a pending review entry and sets the node execution
|
||||
status to REVIEW. The execution remains paused until a human user either approves
|
||||
or rejects the data.
|
||||
|
||||
This is useful for workflows that require human validation or intervention before
|
||||
proceeding to the next steps.
|
||||
**How it works:**
|
||||
- The input data is presented to a human reviewer
|
||||
- The reviewer can approve or reject (and optionally modify the data if editable)
|
||||
- On approval: the data flows out through the `approved_data` output pin
|
||||
- On rejection: the data flows out through the `rejected_data` output pin
|
||||
|
||||
**Important:** The output pins yield the actual data itself, NOT status strings.
|
||||
The approval/rejection decision determines WHICH output pin fires, not the value.
|
||||
You do NOT need to compare the output to "APPROVED" or "REJECTED" - simply connect
|
||||
downstream blocks to the appropriate output pin for each case.
|
||||
|
||||
**Example usage:**
|
||||
- Connect `approved_data` → next step in your workflow (data was approved)
|
||||
- Connect `rejected_data` → error handling or notification (data was rejected)
|
||||
"""
|
||||
|
||||
class Input(BlockSchemaInput):
|
||||
data: Any = SchemaField(description="The data to be reviewed by a human user")
|
||||
data: Any = SchemaField(
|
||||
description="The data to be reviewed by a human user. "
|
||||
"This exact data will be passed through to either approved_data or "
|
||||
"rejected_data output based on the reviewer's decision."
|
||||
)
|
||||
name: str = SchemaField(
|
||||
description="A descriptive name for what this data represents",
|
||||
description="A descriptive name for what this data represents. "
|
||||
"This helps the reviewer understand what they are reviewing.",
|
||||
)
|
||||
editable: bool = SchemaField(
|
||||
description="Whether the human reviewer can edit the data",
|
||||
description="Whether the human reviewer can edit the data before "
|
||||
"approving or rejecting it",
|
||||
default=True,
|
||||
advanced=True,
|
||||
)
|
||||
|
||||
class Output(BlockSchemaOutput):
|
||||
approved_data: Any = SchemaField(
|
||||
description="The data when approved (may be modified by reviewer)"
|
||||
description="Outputs the input data when the reviewer APPROVES it. "
|
||||
"The value is the actual data itself (not a status string like 'APPROVED'). "
|
||||
"If the reviewer edited the data, this contains the modified version. "
|
||||
"Connect downstream blocks here for the 'approved' workflow path."
|
||||
)
|
||||
rejected_data: Any = SchemaField(
|
||||
description="The data when rejected (may be modified by reviewer)"
|
||||
description="Outputs the input data when the reviewer REJECTS it. "
|
||||
"The value is the actual data itself (not a status string like 'REJECTED'). "
|
||||
"If the reviewer edited the data, this contains the modified version. "
|
||||
"Connect downstream blocks here for the 'rejected' workflow path."
|
||||
)
|
||||
review_message: str = SchemaField(
|
||||
description="Any message provided by the reviewer", default=""
|
||||
description="Optional message provided by the reviewer explaining their "
|
||||
"decision. Only outputs when the reviewer provides a message; "
|
||||
"this pin does not fire if no message was given.",
|
||||
default="",
|
||||
)
|
||||
|
||||
def __init__(self):
|
||||
super().__init__(
|
||||
id="8b2a7b3c-6e9d-4a5f-8c1b-2e3f4a5b6c7d",
|
||||
description="Pause execution and wait for human approval or modification of data",
|
||||
description="Pause execution for human review. Data flows through "
|
||||
"approved_data or rejected_data output based on the reviewer's decision. "
|
||||
"Outputs contain the actual data, not status strings.",
|
||||
categories={BlockCategory.BASIC},
|
||||
input_schema=HumanInTheLoopBlock.Input,
|
||||
output_schema=HumanInTheLoopBlock.Output,
|
||||
|
||||
@@ -61,7 +61,7 @@ Below is a comprehensive list of all available blocks, categorized by their prim
|
||||
| [Get List Item](block-integrations/basic.md#get-list-item) | Returns the element at the given index |
|
||||
| [Get Store Agent Details](block-integrations/system/store_operations.md#get-store-agent-details) | Get detailed information about an agent from the store |
|
||||
| [Get Weather Information](block-integrations/basic.md#get-weather-information) | Retrieves weather information for a specified location using OpenWeatherMap API |
|
||||
| [Human In The Loop](block-integrations/basic.md#human-in-the-loop) | Pause execution and wait for human approval or modification of data |
|
||||
| [Human In The Loop](block-integrations/basic.md#human-in-the-loop) | Pause execution for human review |
|
||||
| [List Is Empty](block-integrations/basic.md#list-is-empty) | Checks if a list is empty |
|
||||
| [List Library Agents](block-integrations/system/library_operations.md#list-library-agents) | List all agents in your personal library |
|
||||
| [Note](block-integrations/basic.md#note) | A visual annotation block that displays a sticky note in the workflow editor for documentation and organization purposes |
|
||||
|
||||
@@ -975,7 +975,7 @@ A travel planning application could use this block to provide users with current
|
||||
## Human In The Loop
|
||||
|
||||
### What it is
|
||||
Pause execution and wait for human approval or modification of data
|
||||
Pause execution for human review. Data flows through approved_data or rejected_data output based on the reviewer's decision. Outputs contain the actual data, not status strings.
|
||||
|
||||
### How it works
|
||||
<!-- MANUAL: how_it_works -->
|
||||
@@ -988,18 +988,18 @@ This enables human oversight at critical points in automated workflows, ensuring
|
||||
|
||||
| Input | Description | Type | Required |
|
||||
|-------|-------------|------|----------|
|
||||
| data | The data to be reviewed by a human user | Data | Yes |
|
||||
| name | A descriptive name for what this data represents | str | Yes |
|
||||
| editable | Whether the human reviewer can edit the data | bool | No |
|
||||
| data | The data to be reviewed by a human user. This exact data will be passed through to either approved_data or rejected_data output based on the reviewer's decision. | Data | Yes |
|
||||
| name | A descriptive name for what this data represents. This helps the reviewer understand what they are reviewing. | str | Yes |
|
||||
| editable | Whether the human reviewer can edit the data before approving or rejecting it | bool | No |
|
||||
|
||||
### Outputs
|
||||
|
||||
| Output | Description | Type |
|
||||
|--------|-------------|------|
|
||||
| error | Error message if the operation failed | str |
|
||||
| approved_data | The data when approved (may be modified by reviewer) | Approved Data |
|
||||
| rejected_data | The data when rejected (may be modified by reviewer) | Rejected Data |
|
||||
| review_message | Any message provided by the reviewer | str |
|
||||
| approved_data | Outputs the input data when the reviewer APPROVES it. The value is the actual data itself (not a status string like 'APPROVED'). If the reviewer edited the data, this contains the modified version. Connect downstream blocks here for the 'approved' workflow path. | Approved Data |
|
||||
| rejected_data | Outputs the input data when the reviewer REJECTS it. The value is the actual data itself (not a status string like 'REJECTED'). If the reviewer edited the data, this contains the modified version. Connect downstream blocks here for the 'rejected' workflow path. | Rejected Data |
|
||||
| review_message | Optional message provided by the reviewer explaining their decision. Only outputs when the reviewer provides a message; this pin does not fire if no message was given. | str |
|
||||
|
||||
### Possible use case
|
||||
<!-- MANUAL: use_case -->
|
||||
|
||||
Reference in New Issue
Block a user