acontinue_run().
continue_from.py
"""Time-travel a team run via `continue_from`.
``continue_from`` chooses the message boundary to resume from. Three forms:
- ``continue_from="end"`` full transcript (default)
- ``continue_from="last_user"`` just after the latest user message
- ``continue_from=K`` (int) exact message-index boundary
For a COMPLETED team run, /continue auto-forks into a new sibling run so the
source run remains a durable record of the completed model loop.
Related variants:
- Pair with ``fork=True`` to make the fork explicit (see ``02_fork_run.py``)
- Use ``regenerate=True`` to drop the last assistant turn only (see ``../24_regenerate/01_regenerate.py``)
"""
import asyncio
import time
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openai import OpenAIResponses
from agno.team import Team
DB_FILE = f"tmp/team_time_travel_{int(time.time())}.db"
def get_population(city: str) -> str:
data = {"Paris": "2.1M", "Tokyo": "13.9M"}
return data.get(city, "unknown")
async def main() -> None:
pop_agent = Agent(
name="pop-agent",
role="Answers population questions.",
model=OpenAIResponses(id="gpt-5.4"),
tools=[get_population],
db=SqliteDb(session_table="team_time_travel", db_file=DB_FILE),
)
team = Team(
name="pop-team",
model=OpenAIResponses(id="gpt-5.4"),
members=[pop_agent],
db=SqliteDb(session_table="team_time_travel", db_file=DB_FILE),
instructions="Delegate population questions and summarize the answer.",
)
original = await team.arun(
input="What's the population of Paris?",
session_id="team-sess-tt",
)
print(f"Original: {original.run_id} msgs={len(original.messages or [])}")
print(f" content: {original.content}")
print()
# Continue from the end: this is the default. The source is preserved and
# the follow-up becomes a new sibling because the original run completed.
follow_up = await team.acontinue_run(
run_id=original.run_id,
session_id="team-sess-tt",
continue_from="end",
input="Now compare that with Tokyo.",
)
print(f"Follow-up: {follow_up.run_id}")
print(f" forked_from_run_id: {follow_up.forked_from_run_id}")
print(f" content: {follow_up.content}")
print()
# Resume from the last user message and re-ask a different city.
# Completed runs auto-fork, so the Paris path is preserved.
rewound = await team.acontinue_run(
run_id=original.run_id,
session_id="team-sess-tt",
continue_from="last_user",
input="Actually, tell me about Tokyo instead.",
)
print(f"Rewound: {rewound.run_id}")
print(f" forked_from_run_id: {rewound.forked_from_run_id}")
print(f" content: {rewound.content}")
print()
# Numeric form: pick an exact message index. Useful when the symbolic
# boundaries don't land where you want — e.g. dropping more than just
# the last assistant reply.
print("Original team-run messages:")
for i, m in enumerate(original.messages or [], start=1):
preview = (m.content or "")[:60].replace("\n", " ")
print(f" [{i}] {m.role}: {preview}")
print()
rewound_to_index = await team.acontinue_run(
run_id=original.run_id,
session_id="team-sess-tt",
continue_from=1,
input="Tell me about Lagos instead.",
)
print(f"Rewound to index 1: {rewound_to_index.run_id}")
print(f" forked_from_message_index: {rewound_to_index.forked_from_message_index}")
print(f" content: {rewound_to_index.content}")
print()
# Inspect the session - all team runs coexist.
session = team.db.get_session(session_id="team-sess-tt", session_type="team")
team_runs = [r for r in (session.runs or []) if hasattr(r, "member_responses")]
print(f"Session has {len(team_runs)} team row(s) (source preserved, forks added)")
if __name__ == "__main__":
asyncio.run(main())
Run the Example
1
Set up your virtual environment
uv venv --python 3.12
source .venv/bin/activate
uv venv --python 3.12
.venv\Scripts\activate
2
Install dependencies
uv pip install -U agno openai sqlalchemy
3
Export your OpenAI API key
export OPENAI_API_KEY="your_openai_api_key_here"
$Env:OPENAI_API_KEY="your_openai_api_key_here"
4
Run the example
Save the code above as
continue_from.py, then run:python continue_from.py