flyteplugins-agents-mistral

Run Mistral Agents (the Conversations API, mistralai 2.x) on Flyte. You keep writing Mistral agents; Flyte is the runtime underneath.

pip install flyteplugins-agents-mistral

import flyte
from flyteplugins.agents.mistral import tool, run_agent

env = flyte.TaskEnvironment(
    "mistral-agent",
    secrets=[flyte.Secret(key="mistral_api_key", as_env_var="MISTRAL_API_KEY")],
)

@tool
@env.task(cache="auto", retries=3)
async def get_weather(city: str) -> str:
    """Get the current weather for a city."""
    return f"The weather in {city} is sunny, 22°C."

@env.task(report=True, retries=3)
async def city_agent(question: str) -> str:
    return await run_agent(question, tools=[get_weather], model="mistral-large-latest")

How it maps to Flyte

The SDK owns the loop — we don't reimplement it. Mistral's own runner (conversations.run_async + RunContext) drives the agent loop and executes the tools; we just register Flyte-task-backed tools with it. tool produces the Python function the runner calls, and its body dispatches to task.aio(), so each tool call is a durable Flyte child action.
Both per-turn and per-tool durability. The runner makes each model turn by calling start_async/append_async (in-process HTTP), so with durable=True we wrap those two methods — the seam below the loop — and record each turn via flyte.trace (the ConversationResponse round-trips through pydantic JSON). On a crash/retry, completed turns replay and completed tool calls are cache hits — all while the SDK still owns the loop. (Same idea as swapping OpenAI's ModelProvider: trace the model-call seam, not the loop.)
Observability: the turns, tool calls and final answer render into the task report.

The API key is read from the environment. Wire it as a Flyte secret.

Memory

Pass memory_key (a user/thread id) for cross-run memory — the agent continues the same conversation across separate runs:

await run_agent(message, model="mistral-large-latest", memory_key="user-alice")

Mistral keeps the transcript server-side, so Flyte durably persists the thread's conversation_id (in a keyed MemoryStore) and continues that conversation when the key recurs.

Examples

See examples/:

mistral_durable_agent.py — a single durable agent: tools as Flyte tasks, per-turn traced conversation, agent timeline in the report.
mistral_crash_resume.py — crash & resume: the task crashes on its first attempt after doing real work; on retry the completed conversation turns replay from their flyte.trace records and the tool calls are cache hits. Run on a backend to see the replay.
mistral_multi_agent.py — multi-agent orchestration: a planner agent decomposes a topic, researcher agents fan out in parallel, an editor agent synthesizes — each agent its own durable action.
mistral_agent_id.py — drive a pre-created server-side agent by agent_id (instead of an inline model) while its tool calls still run as durable Flyte actions.
mistral_memory.py — cross-run memory: two separate runs share a memory_key; the agent learns a fact in run 1 and recalls it in run 2.
mistral_handoffs.py — native handoffs: a triage agent hands the conversation off to a billing or technical-support agent (by id), the whole multi-agent run durable on Flyte. The specialist can pause on a Flyte condition (flyte.new_condition) to have a human share a detail, then resume with it.

Conformance

This adapter passes the shared flyteplugins.agents.core.testing.assert_adapter_conforms check — the same one every adapter runs — so it follows the common format despite a server-side, conversation-based SDK shape very different from OpenAI's or Claude's.

Metadata

Release files for flyteplugins-agents-mistral 2.12.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for flyteplugins-agents-mistral 2.12.0
File	Interpreter	ABI	Platform	Reset
flyteplugins_agents_mistral-2.12.0-py3-none-any.whl 7.9 kB Oct 19, 2026 Without provenance	Python 3	none	any	Details

Release files / flyteplugins_agents_mistral-2.12.0-py3-none-any.whl

Download URL	flyteplugins_agents_mistral-2.12.0-py3-none-any.whl
Size	7.9 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`211667cc9d4beb404839cc9c66f7710f0cef08c75979824ed15d169c1b631d49`
BLAKE2b-256 checksum How to use checksums	`5d84c3d3a4c0f9727166b33c84e96818dbbda5de78a2228186d644d6bad6d8ab`
Upload date	Oct 19, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/7.0.0 CPython/3.13.16`

Security for flyteplugins-agents-mistral 2.12.0

Report project as malware

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.