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remove tests/integration/inference/test_vision_inference.py

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Matthew Farrellee 2025-01-09 03:04:05 -05:00
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tests/integration/inference/test_vision_inference.py
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@ -1,206 +0,0 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import base64
import pathlib
from pathlib import Path
import pytest
THIS_DIR = Path(__file__).parent
@pytest.fixture
def image_path():
return pathlib.Path(__file__).parent / "dog.png"
@pytest.fixture
def base64_image_data(image_path):
# Convert the image to base64
return base64.b64encode(image_path.read_bytes()).decode("utf-8")
def test_image_chat_completion_non_streaming(client_with_models, vision_model_id):
message = {
"role": "user",
"content": [
{
"type": "image",
"image": {
"url": {
"uri": "https://raw.githubusercontent.com/meta-llama/llama-stack/main/tests/integration/inference/dog.png"
},
},
},
{
"type": "text",
"text": "Describe what is in this image.",
},
],
}
response = client_with_models.inference.chat_completion(
model_id=vision_model_id,
messages=[message],
stream=False,
)
message_content = response.completion_message.content.lower().strip()
assert len(message_content) > 0
assert any(expected in message_content for expected in {"dog", "puppy", "pup"})
@pytest.fixture
def multi_image_data():
files = [
THIS_DIR / "vision_test_1.jpg",
THIS_DIR / "vision_test_2.jpg",
THIS_DIR / "vision_test_3.jpg",
]
encoded_files = []
for file in files:
with open(file, "rb") as image_file:
base64_data = base64.b64encode(image_file.read()).decode("utf-8")
encoded_files.append(base64_data)
return encoded_files
@pytest.mark.parametrize("stream", [True, False])
def test_image_chat_completion_multiple_images(client_with_models, vision_model_id, multi_image_data, stream):
supported_models = ["llama-4", "gpt-4o", "llama4"]
if not any(model in vision_model_id.lower() for model in supported_models):
pytest.skip(
f"Skip since multi-image tests are only supported for {supported_models}, not for {vision_model_id}"
)
messages = [
{
"role": "user",
"content": [
{
"type": "image",
"image": {
"data": multi_image_data[0],
},
},
{
"type": "image",
"image": {
"data": multi_image_data[1],
},
},
{
"type": "text",
"text": "What are the differences between these images? Where would you assume they would be located?",
},
],
},
]
response = client_with_models.inference.chat_completion(
model_id=vision_model_id,
messages=messages,
stream=stream,
)
if stream:
message_content = ""
for chunk in response:
message_content += chunk.event.delta.text
else:
message_content = response.completion_message.content
assert len(message_content) > 0
assert any(expected in message_content.lower().strip() for expected in {"bedroom"}), message_content
messages.append(
{
"role": "assistant",
"content": [{"type": "text", "text": message_content}],
"stop_reason": "end_of_turn",
}
)
messages.append(
{
"role": "user",
"content": [
{
"type": "image",
"image": {
"data": multi_image_data[2],
},
},
{"type": "text", "text": "How about this one?"},
],
},
)
response = client_with_models.inference.chat_completion(
model_id=vision_model_id,
messages=messages,
stream=stream,
)
if stream:
message_content = ""
for chunk in response:
message_content += chunk.event.delta.text
else:
message_content = response.completion_message.content
assert len(message_content) > 0
assert any(expected in message_content.lower().strip() for expected in {"sword", "shield"}), message_content
def test_image_chat_completion_streaming(client_with_models, vision_model_id):
message = {
"role": "user",
"content": [
{
"type": "image",
"image": {
"url": {
"uri": "https://raw.githubusercontent.com/meta-llama/llama-stack/main/tests/integration/inference/dog.png"
},
},
},
{
"type": "text",
"text": "Describe what is in this image.",
},
],
}
response = client_with_models.inference.chat_completion(
model_id=vision_model_id,
messages=[message],
stream=True,
)
streamed_content = ""
for chunk in response:
streamed_content += chunk.event.delta.text.lower()
assert len(streamed_content) > 0
assert any(expected in streamed_content for expected in {"dog", "puppy", "pup"})
def test_image_chat_completion_base64(client_with_models, vision_model_id, base64_image_data):
image_spec = {
"type": "image",
"image": {
"data": base64_image_data,
},
}
message = {
"role": "user",
"content": [
image_spec,
{
"type": "text",
"text": "Describe what is in this image.",
},
],
}
response = client_with_models.inference.chat_completion(
model_id=vision_model_id,
messages=[message],
stream=False,
)
message_content = response.completion_message.content.lower().strip()
assert len(message_content) > 0