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2.0.0

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Co-Authored-By: Quentin Torroba <quentin.torroba@mistral.ai>
Co-Authored-By: Michel Thomazo <michel.thomazo@mistral.ai>
Co-Authored-By: Clément Drouin <clement.drouin@mistral.ai>
Co-Authored-By: Vincent Guilloux <vincent.guilloux@mistral.ai>
Co-Authored-By: Clément Siriex <clement.sirieix@mistral.ai>
Co-Authored-By: Kim-Adeline Miguel <kimadeline.miguel@mistral.ai>
Co-Authored-By: Thaddee Tyl <thaddee.tyl@gmail.com>
Co-Authored-By: David Brochart <david.brochart@gmail.com>
Co-Authored-By: Joseph Guhlin <joseph.guhlin@gmail.com>
Co-Authored-By: Thomas Kenbeek <thomaskenbeek@gmail.com>
Co-Authored-By: Remenby31 <baptiste.cruvellier31@gmail.com>
This commit is contained in:
Mathias Gesbert 2026-01-27 16:39:30 +01:00 • committed by Mathias Gesbert
parent 79f215d91c
commit d33db9fff8
217 changed files with 16911 additions and 4305 deletions
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28
vibe/core/programmatic.py
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@ -2,9 +2,9 @@ from __future__ import annotations
import asyncio
from vibe.core.agent import Agent
from vibe.core.agent_loop import AgentLoop
from vibe.core.agents.models import BuiltinAgentName
from vibe.core.config import VibeConfig
from vibe.core.modes import AgentMode
from vibe.core.output_formatters import create_formatter
from vibe.core.types import AssistantEvent, LLMMessage, OutputFormat, Role
from vibe.core.utils import ConversationLimitException, logger
@ -17,27 +17,13 @@ def run_programmatic(
max_price: float | None = None,
output_format: OutputFormat = OutputFormat.TEXT,
previous_messages: list[LLMMessage] | None = None,
mode: AgentMode = AgentMode.AUTO_APPROVE,
agent_name: str = BuiltinAgentName.AUTO_APPROVE,
) -> str | None:
"""Run in programmatic mode: execute prompt and return the assistant response.
Args:
config: Configuration for the Vibe agent
prompt: The user prompt to process
max_turns: Maximum number of assistant turns (LLM calls) to allow
max_price: Maximum cost in dollars before stopping
output_format: Format for the output
previous_messages: Optional messages from a previous session to continue
mode: Operational mode (defaults to AUTO_APPROVE for programmatic use)
Returns:
The final assistant response text, or None if no response
"""
formatter = create_formatter(output_format)
agent = Agent(
agent_loop = AgentLoop(
config,
mode=mode,
agent_name=agent_name,
message_observer=formatter.on_message_added,
max_turns=max_turns,
max_price=max_price,
@ -50,12 +36,12 @@ def run_programmatic(
non_system_messages = [
msg for msg in previous_messages if not (msg.role == Role.system)
]
agent.messages.extend(non_system_messages)
agent_loop.messages.extend(non_system_messages)
logger.info(
"Loaded %d messages from previous session", len(non_system_messages)
)
async for event in agent.act(prompt):
async for event in agent_loop.act(prompt):
formatter.on_event(event)
if isinstance(event, AssistantEvent) and event.stopped_by_middleware:
raise ConversationLimitException(event.content)