OpenAI Operational Error - Vector IDs Missing

Question

OpenAI Operational Error - Vector IDs Missing

ROLAND LATTERY 0

When running the agent, I get a the error "invalid_payload required: Required properties ["vector_store_ids"] are not present"

Because of this error, I cannot get responses to my queries loaded in the chat window.

Sridhar M 5,340 Reputation points Microsoft External Staff Moderator

2026-03-04T15:44:16.0233333+00:00
Hi ROLAND LATTERY

vector‐indexing pipeline never actually got a vector_store_ids property in its payload—so the service can’t know which vector store entry to update. When you use Azure Cognitive Search’s “integrated vectorization” feature (i.e. the Text Split + AzureOpenAIEmbedding skills), you must:

Add a field named (or aliased as) vector_store_ids to your target Search index • Type: Collection(Edm.String) • Attributes: filterable/searchable/retrievable as needed

In your skillset, make sure your embedding skill is outputting “vectorStoreIds” and that it’s mapped (via the skill’s OutputFieldMappings) to that vector_store_ids index field

If you built a custom skill, ensure your JSON enrichment output includes something like: { “vector_store_ids”: [ “” ] … }

Once those pieces line up, the indexer will push embeddings AND the vector IDs into your index, and the “invalid_payload…vector_store_ids not present” error will go away.

Thank you.
Sridhar M 5,340 Reputation points Microsoft External Staff Moderator

2026-03-05T12:20:40.26+00:00

Hi ROLAND LATTERY

Did you get any chance to review the above response.

Thank you!
Manas Mohanty 16,190 Reputation points Microsoft External Staff Moderator

2026-03-23T17:52:13.02+00:00

Hi ROLAND LATTERY

Could you confirm if the usage of vector store id in SDK or recreating vector store in foundry UI resolve the issue.

Thank you

1 answer

Your answer

Sridhar M 5,340 Reputation points Microsoft External Staff Moderator

2026-03-04T15:44:16.0233333+00:00

Hi ROLAND LATTERY

vector‐indexing pipeline never actually got a vector_store_ids property in its payload—so the service can’t know which vector store entry to update. When you use Azure Cognitive Search’s “integrated vectorization” feature (i.e. the Text Split + AzureOpenAIEmbedding skills), you must:

Add a field named (or aliased as) vector_store_ids to your target Search index • Type: Collection(Edm.String) • Attributes: filterable/searchable/retrievable as needed

In your skillset, make sure your embedding skill is outputting “vectorStoreIds” and that it’s mapped (via the skill’s OutputFieldMappings) to that vector_store_ids index field

If you built a custom skill, ensure your JSON enrichment output includes something like: { “vector_store_ids”: [ “” ] … }

Once those pieces line up, the indexer will push embeddings AND the vector IDs into your index, and the “invalid_payload…vector_store_ids not present” error will go away.

Thank you.
Sridhar M 5,340 Reputation points Microsoft External Staff Moderator

2026-03-05T12:20:40.26+00:00

Hi ROLAND LATTERY

Did you get any chance to review the above response.

Thank you!
Manas Mohanty 16,190 Reputation points Microsoft External Staff Moderator

2026-03-23T17:52:13.02+00:00

Hi ROLAND LATTERY

Could you confirm if the usage of vector store id in SDK or recreating vector store in foundry UI resolve the issue.

Thank you

Answer 1

Hi ROLAND LATTERY

Good day. Sorry for delay in follow up from support side.

It looks like the issue might be originating on SDK.

From SDK perspective

You might be missing "vector store id "while running thread from file search mode.

Please share your sample SDK if SDK


file_search = FileSearchTool(vector_store_ids=[vector_store.id])

from azure.ai.projects import AIProjectClient
from azure.identity import DefaultAzureCredential
from azure.ai.agents.models import ListSortOrder, FileSearchTool

project = AIProjectClient(
    endpoint="https://your-foundry-resource-name.ai.azure.com/api/projects/project-name",
    credential=DefaultAzureCredential(),
)

# Upload file and create vector store
file = project.agents.files.upload(file_path="./product_info_1.md", purpose=FilePurpose.AGENTS)
vector_store = project.agents.vector_stores.create_and_poll(file_ids=[file.id], name="my_vectorstore")

# Create file search tool and agent
file_search = FileSearchTool(vector_store_ids=[vector_store.id])
agent = project.agents.create_agent(
    model="gpt-4o",
    name="my-assistant",
    instructions="You are a helpful assistant and can search information from uploaded files",
    tools=file_search.definitions,
    tool_resources=file_search.resources,
)



# Create thread and process user message
thread = project.agents.threads.create()
project.agents.messages.create(thread_id=thread.id, role="user", content="Hello, what Contoso products do you know?")
run = project.agents.runs.create_and_process(thread_id=thread.id, agent_id=agent.id)

# Handle run status
if run.status == "failed":
    print(f"Run failed: {run.last_error}")

# Print thread messages
messages = project.agents.messages.list(thread_id=thread.id, order=ListSortOrder.ASCENDING)
for message in messages:
    if message.run_id == run.id and message.text_messages:
        print(f"{message.role}: {message.text_messages[-1].text.value}")

# Cleanup resources
project.agents.vector_stores.delete(vector_store.id)
project.agents.files.delete(file_id=file.id)
project.agents.delete_agent(agent.id)

From Foundry UI

Respective Vector store is corrupt or not usable. Please re-create the vector store with same files

Follow up query

SDK code if you are using SDK
Model in usage
Foundry type
Screenshot from Foundry UI if operating from portal UI
Attached Foundry New SDK and migration guide for reference too.

Have reached via private message for support ticket creation if the issue does not resolve with above pointers.

Thank you

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OpenAI Operational Error - Vector IDs Missing

1 answer

Your answer