feat(ci): use replay mode, setup ollama if specific label exists on PR (#2955)

This PR makes setting up Ollama optional for CI. By default, we use
`replay` mode for inference requests and use the stored results from the
`tests/integration/recordings/` directory.

Every so often, users will update tests which will need us to re-record.
To do this, we check for the existence of a label `re-record-tests` on
the PR. If detected,
- ollama is spun up
- inference mode is set to record
- after the tests are done, if any new changes are detected, they are
pushed back to the PR

## Test Plan

This is GitHub CI. Gotta test it live.
This commit is contained in:
Ashwin Bharambe 2025-07-29 16:50:26 -07:00 committed by GitHub
parent 0ac503ec0d
commit b237df8f18
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
11 changed files with 1519 additions and 13 deletions

View file

@ -7,6 +7,7 @@ on:
branches: [ main ] branches: [ main ]
pull_request: pull_request:
branches: [ main ] branches: [ main ]
types: [opened, synchronize, reopened, labeled, unlabeled]
paths: paths:
- 'llama_stack/**' - 'llama_stack/**'
- 'tests/**' - 'tests/**'
@ -39,6 +40,8 @@ jobs:
runs-on: ubuntu-latest runs-on: ubuntu-latest
outputs: outputs:
test-type: ${{ steps.generate-matrix.outputs.test-type }} test-type: ${{ steps.generate-matrix.outputs.test-type }}
rerecord-tests: ${{ steps.check-rerecord-tests.outputs.rerecord-tests }}
steps: steps:
- name: Checkout repository - name: Checkout repository
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2 uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
@ -52,10 +55,30 @@ jobs:
sort | jq -R -s -c 'split("\n")[:-1]') sort | jq -R -s -c 'split("\n")[:-1]')
echo "test-type=$TEST_TYPES" >> $GITHUB_OUTPUT echo "test-type=$TEST_TYPES" >> $GITHUB_OUTPUT
- name: Check if re-record-tests label exists
id: check-rerecord-tests
run: |
if [[ "${{ contains(github.event.pull_request.labels.*.name, 're-record-tests') }}" == "true" ]]; then
echo "rerecord-tests=true" >> $GITHUB_OUTPUT
else
echo "rerecord-tests=false" >> $GITHUB_OUTPUT
fi
test-matrix: test-matrix:
needs: discover-tests needs: discover-tests
runs-on: ubuntu-latest runs-on: ubuntu-latest
permissions:
# Set write permissions since we might need to commit recordings
contents: write
pull-requests: write
env:
# Create reusable variable for the re-record tests condition
SHOULD_RECORD: ${{ needs.discover-tests.outputs.rerecord-tests == 'true' }}
# TODO: set up another var to track whether we need ollama or not
# not every matrix type needs ollama
strategy: strategy:
fail-fast: false fail-fast: false
matrix: matrix:
@ -74,6 +97,16 @@ jobs:
test-type: tool_runtime test-type: tool_runtime
steps: steps:
- name: Debug
run: |
echo "test-type: ${{ matrix.test-type }}"
echo "client-type: ${{ matrix.client-type }}"
echo "provider: ${{ matrix.provider }}"
echo "python-version: ${{ matrix.python-version }}"
echo "client-version: ${{ matrix.client-version }}"
echo "SHOULD_RECORD: ${{ env.SHOULD_RECORD }}"
echo "rerecord-tests: ${{ needs.discover-tests.outputs.rerecord-tests }}"
- name: Checkout repository - name: Checkout repository
uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2 uses: actions/checkout@11bd71901bbe5b1630ceea73d27597364c9af683 # v4.2.2
@ -84,7 +117,7 @@ jobs:
client-version: ${{ matrix.client-version }} client-version: ${{ matrix.client-version }}
- name: Setup ollama - name: Setup ollama
if: ${{ matrix.provider == 'ollama' }} if: ${{ matrix.provider == 'ollama' && env.SHOULD_RECORD == 'true' }}
uses: ./.github/actions/setup-ollama uses: ./.github/actions/setup-ollama
- name: Setup vllm - name: Setup vllm
@ -116,6 +149,14 @@ jobs:
fi fi
EXCLUDE_TESTS="builtin_tool or safety_with_image or code_interpreter or test_rag" EXCLUDE_TESTS="builtin_tool or safety_with_image or code_interpreter or test_rag"
export LLAMA_STACK_TEST_RECORDING_DIR="tests/integration/recordings"
if [ "$SHOULD_RECORD" == "true" ]; then
export LLAMA_STACK_TEST_INFERENCE_MODE="record"
else
export LLAMA_STACK_TEST_INFERENCE_MODE="replay"
fi
if [ "${{ matrix.provider }}" == "ollama" ]; then if [ "${{ matrix.provider }}" == "ollama" ]; then
export OLLAMA_URL="http://0.0.0.0:11434" export OLLAMA_URL="http://0.0.0.0:11434"
export TEXT_MODEL=ollama/llama3.2:3b-instruct-fp16 export TEXT_MODEL=ollama/llama3.2:3b-instruct-fp16
@ -129,7 +170,6 @@ jobs:
EXCLUDE_TESTS="${EXCLUDE_TESTS} or test_inference_store_tool_calls" EXCLUDE_TESTS="${EXCLUDE_TESTS} or test_inference_store_tool_calls"
fi fi
uv run pytest -s -v tests/integration/${{ matrix.test-type }} --stack-config=${stack_config} \ uv run pytest -s -v tests/integration/${{ matrix.test-type }} --stack-config=${stack_config} \
-k "not( ${EXCLUDE_TESTS} )" \ -k "not( ${EXCLUDE_TESTS} )" \
--text-model=$TEXT_MODEL \ --text-model=$TEXT_MODEL \
@ -137,6 +177,20 @@ jobs:
--color=yes ${EXTRA_PARAMS} \ --color=yes ${EXTRA_PARAMS} \
--capture=tee-sys | tee pytest-${{ matrix.test-type }}.log --capture=tee-sys | tee pytest-${{ matrix.test-type }}.log
- name: Update the PR if tests/integration/recordings/ has changed
if: ${{ env.SHOULD_RECORD == 'true' }}
run: |
if ! git diff --quiet tests/integration/recordings/; then
echo "Updating PR with updated recordings"
git config --local user.email "github-actions[bot]@users.noreply.github.com"
git config --local user.name "github-actions[bot]"
git add tests/integration/recordings/
git commit -m "Update recordings from integration tests"
git push origin HEAD:${{ github.head_ref }}
else
echo "No changes to recordings detected"
fi
- name: Check Storage and Memory Available After Tests - name: Check Storage and Memory Available After Tests
if: ${{ always() }} if: ${{ always() }}
run: | run: |
@ -144,13 +198,13 @@ jobs:
df -h df -h
- name: Write inference logs to file - name: Write inference logs to file
if: ${{ always() }} if: ${{ env.SHOULD_RECORD == 'true' }}
run: | run: |
sudo docker logs ollama > ollama.log || true sudo docker logs ollama > ollama.log || true
sudo docker logs vllm > vllm.log || true sudo docker logs vllm > vllm.log || true
- name: Upload all logs to artifacts - name: Upload all logs to artifacts
if: ${{ always() }} if: ${{ env.SHOULD_RECORD == 'true' }}
uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2 uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2
with: with:
name: logs-${{ github.run_id }}-${{ github.run_attempt }}-${{ matrix.provider }}-${{ matrix.client-type }}-${{ matrix.test-type }}-${{ matrix.python-version }}-${{ matrix.client-version }} name: logs-${{ github.run_id }}-${{ github.run_attempt }}-${{ matrix.provider }}-${{ matrix.client-type }}-${{ matrix.test-type }}-${{ matrix.python-version }}-${{ matrix.client-version }}

View file

@ -0,0 +1,167 @@
{
"request": {
"method": "POST",
"url": "http://localhost:11434/api/generate",
"headers": {},
"body": {
"model": "llama3.2:3b-instruct-fp16",
"raw": true,
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"options": {
"temperature": 0.0
},
"stream": true
},
"endpoint": "/api/generate",
"model": "llama3.2:3b-instruct-fp16"
},
"response": {
"body": [
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"__data__": {
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}
},
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{
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},
{
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"done": true,
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}
}
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"is_streaming": true
}
}

View file

@ -0,0 +1,185 @@
{
"request": {
"method": "POST",
"url": "http://localhost:11434/api/generate",
"headers": {},
"body": {
"model": "llama3.2:3b-instruct-fp16",
"raw": true,
"prompt": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant. You have access to functions, but you should only use them if they are required.\nYou are an expert in composing functions. You are given a question and a set of possible functions.\nBased on the question, you may or may not need to make one function/tool call to achieve the purpose.\n\nIf you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]\nIf you decide to invoke a function, you SHOULD NOT include any other text in the response. besides the function call in the above format.\nFor a boolean parameter, be sure to use `True` or `False` (capitalized) for the value.\n\n\nHere is a list of functions in JSON format that you can invoke.\n\n[\n {\n \"name\": \"greet_everyone\",\n \"description\": \"\",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"url\"],\n \"properties\": {\n \"url\": {\n \"type\": \"string\",\n \"description\": \"\"\n }\n }\n }\n },\n {\n \"name\": \"get_boiling_point\",\n \"description\": \"\nReturns the boiling point of a liquid in Celsius or Fahrenheit.\n\n:param liquid_name: The name of the liquid\n:param celsius: Whether to return the boiling point in Celsius\n:return: The boiling point of the liquid in Celcius or Fahrenheit\n\",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"liquid_name\", \"celsius\"],\n \"properties\": {\n \"liquid_name\": {\n \"type\": \"string\",\n \"description\": \"\"\n },\n \"celsius\": {\n \"type\": \"boolean\",\n \"description\": \"\"\n }\n }\n }\n }\n]\n\nYou can answer general questions or invoke tools when necessary.\nIn addition to tool calls, you should also augment your responses by using the tool outputs.\nYou are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nSay hi to the world. Use tools to do so.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
"options": {
"temperature": 0.0
},
"stream": true
},
"endpoint": "/api/generate",
"model": "llama3.2:3b-instruct-fp16"
},
"response": {
"body": [
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},
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},
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}
}

View file

@ -14,7 +14,7 @@
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@ -0,0 +1,347 @@
{
"request": {
"method": "POST",
"url": "http://localhost:11434/api/generate",
"headers": {},
"body": {
"model": "llama3.2:3b-instruct-fp16",
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}
},
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}
},
{
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}
},
{
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},
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"done": true,
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"is_streaming": true
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}

View file

@ -0,0 +1,185 @@
{
"request": {
"method": "POST",
"url": "http://localhost:11434/api/generate",
"headers": {},
"body": {
"model": "llama3.2:3b-instruct-fp16",
"raw": true,
"prompt": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant. You have access to functions, but you should only use them if they are required.\nYou are an expert in composing functions. You are given a question and a set of possible functions.\nBased on the question, you may or may not need to make one function/tool call to achieve the purpose.\n\nIf you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]\nIf you decide to invoke a function, you SHOULD NOT include any other text in the response. besides the function call in the above format.\nFor a boolean parameter, be sure to use `True` or `False` (capitalized) for the value.\n\n\nHere is a list of functions in JSON format that you can invoke.\n\n[\n {\n \"name\": \"greet_everyone\",\n \"description\": \"\",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"url\"],\n \"properties\": {\n \"url\": {\n \"type\": \"string\",\n \"description\": \"\"\n }\n }\n }\n },\n {\n \"name\": \"get_boiling_point\",\n \"description\": \"\n Returns the boiling point of a liquid in Celsius or Fahrenheit.\n\n :param liquid_name: The name of the liquid\n :param celsius: Whether to return the boiling point in Celsius\n :return: The boiling point of the liquid in Celcius or Fahrenheit\n \",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"liquid_name\", \"celsius\"],\n \"properties\": {\n \"liquid_name\": {\n \"type\": \"string\",\n \"description\": \"\"\n },\n \"celsius\": {\n \"type\": \"boolean\",\n \"description\": \"\"\n }\n }\n }\n }\n]\n\nYou can answer general questions or invoke tools when necessary.\nIn addition to tool calls, you should also augment your responses by using the tool outputs.\nYou are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nSay hi to the world. Use tools to do so.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
"options": {
"temperature": 0.0
},
"stream": true
},
"endpoint": "/api/generate",
"model": "llama3.2:3b-instruct-fp16"
},
"response": {
"body": [
{
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}
},
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}
},
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"response": "=\"",
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}
},
{
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"response": "world",
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}
},
{
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"response": "\")]",
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}
},
{
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"done": true,
"done_reason": "stop",
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}
}
],
"is_streaming": true
}
}

View file

@ -0,0 +1,59 @@
{
"request": {
"method": "POST",
"url": "http://localhost:11434/api/generate",
"headers": {},
"body": {
"model": "llama3.2:1b",
"raw": true,
"prompt": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant. You have access to functions, but you should only use them if they are required.\nYou are an expert in composing functions. You are given a question and a set of possible functions.\nBased on the question, you may or may not need to make one function/tool call to achieve the purpose.\n\nIf you decide to invoke any of the function(s), you MUST put it in the format of [func_name1(params_name1=params_value1, params_name2=params_value2...), func_name2(params)]\nIf you decide to invoke a function, you SHOULD NOT include any other text in the response. besides the function call in the above format.\nFor a boolean parameter, be sure to use `True` or `False` (capitalized) for the value.\n\n\nHere is a list of functions in JSON format that you can invoke.\n\n[\n {\n \"name\": \"greet_everyone\",\n \"description\": \"\",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"url\"],\n \"properties\": {\n \"url\": {\n \"type\": \"string\",\n \"description\": \"\"\n }\n }\n }\n },\n {\n \"name\": \"get_boiling_point\",\n \"description\": \"\nReturns the boiling point of a liquid in Celsius or Fahrenheit.\n\n:param liquid_name: The name of the liquid\n:param celsius: Whether to return the boiling point in Celsius\n:return: The boiling point of the liquid in Celcius or Fahrenheit\n\",\n \"parameters\": {\n \"type\": \"dict\",\n \"required\": [\"liquid_name\", \"celsius\"],\n \"properties\": {\n \"liquid_name\": {\n \"type\": \"string\",\n \"description\": \"\"\n },\n \"celsius\": {\n \"type\": \"boolean\",\n \"description\": \"\"\n }\n }\n }\n }\n]\n\nYou can answer general questions or invoke tools when necessary.\nIn addition to tool calls, you should also augment your responses by using the tool outputs.\nYou are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nSay hi to the world. Use tools to do so.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
"options": {
"temperature": 0.0
},
"stream": true
},
"endpoint": "/api/generate",
"model": "llama3.2:1b"
},
"response": {
"body": [
{
"__type__": "ollama._types.GenerateResponse",
"__data__": {
"model": "llama3.2:1b",
"created_at": "2025-07-29T23:23:09.553247Z",
"done": false,
"done_reason": null,
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"eval_count": null,
"eval_duration": null,
"response": "Hi",
"thinking": null,
"context": null
}
},
{
"__type__": "ollama._types.GenerateResponse",
"__data__": {
"model": "llama3.2:1b",
"created_at": "2025-07-29T23:23:09.564069Z",
"done": true,
"done_reason": "stop",
"total_duration": 2125493250,
"load_duration": 1610279708,
"prompt_eval_count": 448,
"prompt_eval_duration": 502413125,
"eval_count": 2,
"eval_duration": 11573709,
"response": "",
"thinking": null,
"context": null
}
}
],
"is_streaming": true
}
}

View file

@ -10,7 +10,6 @@ import pytest
from llama_stack_client import Agent from llama_stack_client import Agent
from llama_stack import LlamaStackAsLibraryClient from llama_stack import LlamaStackAsLibraryClient
from llama_stack.apis.models import ModelType
from llama_stack.distribution.datatypes import AuthenticationRequiredError from llama_stack.distribution.datatypes import AuthenticationRequiredError
AUTH_TOKEN = "test-token" AUTH_TOKEN = "test-token"
@ -24,7 +23,7 @@ def mcp_server():
yield mcp_server_info yield mcp_server_info
def test_mcp_invocation(llama_stack_client, mcp_server): def test_mcp_invocation(llama_stack_client, text_model_id, mcp_server):
if not isinstance(llama_stack_client, LlamaStackAsLibraryClient): if not isinstance(llama_stack_client, LlamaStackAsLibraryClient):
pytest.skip("The local MCP server only reliably reachable from library client.") pytest.skip("The local MCP server only reliably reachable from library client.")
@ -69,14 +68,10 @@ def test_mcp_invocation(llama_stack_client, mcp_server):
assert content[0].type == "text" assert content[0].type == "text"
assert content[0].text == "Hello, world!" assert content[0].text == "Hello, world!"
models = [ print(f"Using model: {text_model_id}")
m for m in llama_stack_client.models.list() if m.model_type == ModelType.llm and "guard" not in m.identifier
]
model_id = models[0].identifier
print(f"Using model: {model_id}")
agent = Agent( agent = Agent(
client=llama_stack_client, client=llama_stack_client,
model=model_id, model=text_model_id,
instructions="You are a helpful assistant.", instructions="You are a helpful assistant.",
tools=[test_toolgroup_id], tools=[test_toolgroup_id],
) )