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4 commits

Author SHA1 Message Date
Francisco Arceo
e7d21e1ee3
feat: Add support for Conversations in Responses API (#3743)
# What does this PR do?
This PR adds support for Conversations in Responses.

<!-- If resolving an issue, uncomment and update the line below -->
<!-- Closes #[issue-number] -->

## Test Plan
Unit tests
Integration tests

<Details>
<Summary>Manual testing with this script: (click to expand)</Summary>

```python
from openai import OpenAI

client = OpenAI()
client = OpenAI(base_url="http://localhost:8321/v1/", api_key="none")

def test_conversation_create():
    print("Testing conversation create...")
    conversation = client.conversations.create(
        metadata={"topic": "demo"},
        items=[
            {"type": "message", "role": "user", "content": "Hello!"}
        ]
    )
    print(f"Created: {conversation}")
    return conversation

def test_conversation_retrieve(conv_id):
    print(f"Testing conversation retrieve for {conv_id}...")
    retrieved = client.conversations.retrieve(conv_id)
    print(f"Retrieved: {retrieved}")
    return retrieved

def test_conversation_update(conv_id):
    print(f"Testing conversation update for {conv_id}...")
    updated = client.conversations.update(
        conv_id,
        metadata={"topic": "project-x"}
    )
    print(f"Updated: {updated}")
    return updated

def test_conversation_delete(conv_id):
    print(f"Testing conversation delete for {conv_id}...")
    deleted = client.conversations.delete(conv_id)
    print(f"Deleted: {deleted}")
    return deleted

def test_conversation_items_create(conv_id):
    print(f"Testing conversation items create for {conv_id}...")
    items = client.conversations.items.create(
        conv_id,
        items=[
            {
                "type": "message",
                "role": "user",
                "content": [{"type": "input_text", "text": "Hello!"}]
            },
            {
                "type": "message",
                "role": "user",
                "content": [{"type": "input_text", "text": "How are you?"}]
            }
        ]
    )
    print(f"Items created: {items}")
    return items

def test_conversation_items_list(conv_id):
    print(f"Testing conversation items list for {conv_id}...")
    items = client.conversations.items.list(conv_id, limit=10)
    print(f"Items list: {items}")
    return items

def test_conversation_item_retrieve(conv_id, item_id):
    print(f"Testing conversation item retrieve for {conv_id}/{item_id}...")
    item = client.conversations.items.retrieve(conversation_id=conv_id, item_id=item_id)
    print(f"Item retrieved: {item}")
    return item

def test_conversation_item_delete(conv_id, item_id):
    print(f"Testing conversation item delete for {conv_id}/{item_id}...")
    deleted = client.conversations.items.delete(conversation_id=conv_id, item_id=item_id)
    print(f"Item deleted: {deleted}")
    return deleted

def test_conversation_responses_create():
    print("\nTesting conversation create for a responses example...")
    conversation = client.conversations.create()
    print(f"Created: {conversation}")

    response = client.responses.create(
      model="gpt-4.1",
      input=[{"role": "user", "content": "What are the 5 Ds of dodgeball?"}],
      conversation=conversation.id,
    )
    print(f"Created response: {response} for conversation {conversation.id}")

    return response, conversation

def test_conversations_responses_create_followup(
        conversation,
        content="Repeat what you just said but add 'this is my second time saying this'",
    ):
    print(f"Using: {conversation.id}")

    response = client.responses.create(
      model="gpt-4.1",
      input=[{"role": "user", "content": content}],
      conversation=conversation.id,
    )
    print(f"Created response: {response} for conversation {conversation.id}")

    conv_items = client.conversations.items.list(conversation.id)
    print(f"\nRetrieving list of items for conversation {conversation.id}:")
    print(conv_items.model_dump_json(indent=2))

def test_response_with_fake_conv_id():
    fake_conv_id = "conv_zzzzzzzzz5dc81908289d62779d2ac510a2b0b602ef00a44"
    print(f"Using {fake_conv_id}")
    try:
        response = client.responses.create(
          model="gpt-4.1",
          input=[{"role": "user", "content": "say hello"}],
          conversation=fake_conv_id,
        )
        print(f"Created response: {response} for conversation {fake_conv_id}")
    except Exception as e:
        print(f"failed to create response for conversation {fake_conv_id} with error {e}")


def main():
    print("Testing OpenAI Conversations API...")

    # Create conversation
    conversation = test_conversation_create()
    conv_id = conversation.id

    # Retrieve conversation
    test_conversation_retrieve(conv_id)

    # Update conversation
    test_conversation_update(conv_id)

    # Create items
    items = test_conversation_items_create(conv_id)

    # List items
    items_list = test_conversation_items_list(conv_id)

    # Retrieve specific item
    if items_list.data:
        item_id = items_list.data[0].id
        test_conversation_item_retrieve(conv_id, item_id)

        # Delete item
        test_conversation_item_delete(conv_id, item_id)

    # Delete conversation
    test_conversation_delete(conv_id)

    response, conversation2 = test_conversation_responses_create()
    print('\ntesting reseponse retrieval')
    test_conversation_retrieve(conversation2.id)

    print('\ntesting responses follow up')
    test_conversations_responses_create_followup(conversation2)

    print('\ntesting responses follow up x2!')

    test_conversations_responses_create_followup(
        conversation2,
        content="Repeat what you just said but add 'this is my third time saying this'",
    )

    test_response_with_fake_conv_id()

    print("All tests completed!")


if __name__ == "__main__":
    main()
```
</Details>

---------

Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
2025-10-10 11:57:40 -07:00
Ashwin Bharambe
42414a1a1b
fix(logging): disable console telemetry sink by default (#3623)
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The current span processing dumps so much junk on the console that it
makes actual understanding of what is going on in the server impossible.
I am killing the console sink as a default. If you want, you are always
free to change your run.yaml to add it.

Before: 
<img width="1877" height="1107" alt="image"
src="https://github.com/user-attachments/assets/3a7ad261-e2ba-4d40-9820-fcc282c8df37"
/>

After:
<img width="1919" height="470" alt="image"
src="https://github.com/user-attachments/assets/bc7cf763-fba9-4e95-a4b5-f65f6d1c5332"
/>
2025-09-30 14:58:05 -07:00
slekkala1
efdb5558b8
fix: Remove bfcl scoring function as not supported (#3281)
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# What does this PR do?
BFCL scoring function is not supported, removing it. 

Also minor fixes as the llama stack run is broken for open-benchmark for
test plan verification
1. Correct the model paths for supported models
2. Fix another issue as there is no `provider_id` for DatasetInput but
logger assumes it exists.
``` 
File "/Users/swapna942/llama-stack/llama_stack/core/stack.py", line 332, in construct_stack
    await register_resources(run_config, impls)
  File "/Users/swapna942/llama-stack/llama_stack/core/stack.py", line 108, in register_resources
    logger.debug(f"registering {rsrc.capitalize()} {obj} for provider {obj.provider_id}")
                                                                       ^^^^^^^^^^^^^^^
  File "/Users/swapna942/llama-stack/.venv/lib/python3.13/site-packages/pydantic/main.py", line 991, in __getattr__
    raise AttributeError(f'{type(self).__name__!r} object has no attribute {item!r}')
AttributeError: 'DatasetInput' object has no attribute 'provider_id'
```

## Test Plan
```llama stack build --distro open-benchmark --image-type venv``` and run the server succeeds


Issue Link: https://github.com/llamastack/llama-stack/issues/3282
2025-08-29 11:03:52 -07:00
Ashwin Bharambe
cc87995e2b
chore: rename templates to distributions (#3035)
As the title says. Distributions is in, Templates is out.

`llama stack build --template` --> `llama stack build --distro`. For
backward compatibility, the previous option is kept but results in a
warning.

Updated `server.py` to remove the "config_or_template" backward
compatibility since it has been a couple releases since that change.
2025-08-04 11:34:17 -07:00