Hacktoberfest 2026: le issue che i maintainer hanno segnato per ottobre, aperte e adatte ai principianti. Sfoglia le issue Hacktoberfest

Python: [Bug]: UserMessage/AgentMessage return different shapes from WorkflowState and DeclarativeWorkflowState

Aperta
  • Qualcosa non va?
#9,041 1 commento 0 reazioni 1 assegnatario Vedi su GitHub

I maintainer di solito rispondono entro 1 giorno

@eavanvalkenburg ci sta già lavorando.

Dal 5/10/2026.

  • #9101 di @he-yufeng — aperta

Valutazione

Difficoltà
4/5
Tempo stimato
3-5 giorni
Idoneità per principianti
48/100
Tipo di issue
Bug
Chiarezza
Abbastanza chiara
Stato di attività
Attiva
Stack tecnologico
python
Ambito
backend-api-design

Direzione di ricerca

Compare the two evaluation paths in _powerfx_functions.py and _declarative_base.py, then trace how each MessageText implementation reads messages. The issue leaves the canonical shape to a maintainer, so get that direction before changing code. Done means both evaluation paths produce the agreed shape and both MessageText implementations read it consistently.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

python vnext
Language

Python

What happened?

The same declarative formula produces two different message shapes depending on which public state class evaluates it:

from agent_framework_declarative._workflows._state import WorkflowState

WorkflowState().eval('=UserMessage("hi")')
# {'role': 'user', 'content': 'hi'}

WorkflowState (standalone) routes to _powerfx_functions.user_message, which returns a flat content key (python/packages/declarative/agent_framework_declarative/_workflows/_powerfx_functions.py:107, same for assistant_message / agent_message / system_message).

DeclarativeWorkflowState (what factory-created workflows use) routes to _eval_custom_function, which returns a flat text key for UserMessage / AgentMessage:

return {"role": "user", "text": str(text) if text else ""}  # _declarative_base.py:755

The two MessageText implementations each read only their own side's shape, so a message that crosses paths silently extracts nothing:

  • _declarative_base._eval_and_replace_message_text reads text first, then a contents list; it never reads content (_declarative_base.py:858-885). A content-shaped message yields "".
  • _powerfx_functions.message_text reads content, so on a text-shaped message it returns "":
from agent_framework_declarative._workflows._powerfx_functions import message_text

message_text([{"role": "user", "text": "hi"}])     # ''
message_text([{"role": "user", "content": "hi"}])  # 'hi'

The agent-side consumer is more tolerant (_executors_agents.py:716 reads content then text), which papers over the split for agent invocations but not for MessageText.

For reference, the .NET canonical shape is a structured record (dotnet/src/Microsoft.Agents.AI.Workflows.Declarative/PowerFx/Functions/MessageFunction.cs): {__type__, Role, Content: [{Type: "Text", Value: ...}]}, i.e. neither flat Python shape. Feeding that shape to the fallback message_text today stringifies the content table:

message_text([{"role": "user", "content": [{"type": "text", "value": "hi"}]}])
# "[{'type': 'text', 'value': 'hi'}]"

Verified on current main (e9857bd75a21843803431a2e7dfa41ee9b017ac7) with agent-framework-declarative installed from source; the .NET shape was read from the in-repo dotnet sources.

What should happen?

One canonical message shape for the Python package, with both eval paths producing it and both MessageText implementations reading it. Which key wins (flat text, flat content, or the structured .NET-style content list) looks like a maintainer call; happy to send the PR once there is a direction.

Lingua principale
Python
Stelle
14k
Fork
2.5k
Merge medio
2g 2h
PR unite (30g)
389

Preparare l'ambiente

Apri in Codespaces

Avvia il container di sviluppo del progetto nel browser, con il tuo account GitHub.

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Altre issue di microsoft/agent-framework

Tutte le issue di microsoft/agent-framework

Issue simili

Altre issue su Python

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.