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9 Commits

Author SHA1 Message Date
Matt Aitchison
de8d28909c ci: test all 4 Python versions on PRs
Run 3.10, 3.11, 3.12, 3.13 on every PR — we need to catch
version-specific breakage before merge. Removes the configure
job since the matrix is now static. Still 16 jobs (4×4) vs 32.
2026-02-25 16:33:19 -06:00
Matt Aitchison
19b9b9da23 ci: drop artifact approach, use setup-uv caching directly
tar czf on the venv was taking too long (gzip is single-threaded).
Simpler approach: each test job installs with setup-uv's built-in
cache. With warm cache, uv sync --frozen takes ~10-15s which is
faster than tar + upload + download + extract.
2026-02-25 16:23:45 -06:00
Matt Aitchison
2327fd04a3 ci: quote github.base_ref in shell to prevent injection 2026-02-25 16:15:37 -06:00
Matt Aitchison
0bdc5a093e ci: optimize test workflows — reduce jobs, share venv via artifact
- Restructure tests.yml: install once per Python version, share .venv
  via artifact instead of 32 independent installs
- Reduce test groups from 8 to 4 (tests only take ~60s per group)
- Only test Python 3.12+3.13 on PRs; full matrix on push to main
- Switch all workflows from manual actions/cache to setup-uv built-in
  caching, eliminating cache race conditions
- Add --frozen flag to uv sync for deterministic CI installs
- Re-enable duration-based test splitting with least_duration algorithm
  (was disabled due to a bug in the path filter)
- Fix update-test-durations path filter (tests/**/*.py never matched
  actual test dirs under lib/)
- Add concurrency group with cancel-in-progress for PR runs
- Add gate jobs to satisfy existing branch protection required checks
2026-02-25 16:14:38 -06:00
dependabot[bot]
017189db78 chore(deps): bump nltk in the security-updates group across 1 directory (#4598)
Bumps the security-updates group with 1 update in the / directory: [nltk](https://github.com/nltk/nltk).


Updates `nltk` from 3.9.2 to 3.9.3
- [Changelog](https://github.com/nltk/nltk/blob/develop/ChangeLog)
- [Commits](https://github.com/nltk/nltk/compare/3.9.2...3.9.3)

---
updated-dependencies:
- dependency-name: nltk
  dependency-version: 3.9.3
  dependency-type: indirect
  dependency-group: security-updates
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-02-25 15:37:21 -06:00
dependabot[bot]
02d911494f chore(deps): bump cryptography (#4506)
Bumps the security-updates group with 1 update in the / directory: [cryptography](https://github.com/pyca/cryptography).


Updates `cryptography` from 46.0.4 to 46.0.5
- [Changelog](https://github.com/pyca/cryptography/blob/main/CHANGELOG.rst)
- [Commits](https://github.com/pyca/cryptography/compare/46.0.4...46.0.5)

---
updated-dependencies:
- dependency-name: cryptography
  dependency-version: 46.0.5
  dependency-type: indirect
  dependency-group: security-updates
...

Signed-off-by: dependabot[bot] <support@github.com>
Co-authored-by: dependabot[bot] <49699333+dependabot[bot]@users.noreply.github.com>
2026-02-25 15:04:07 -06:00
João Moura
8102d0a6ca feat: enhance JSON argument parsing and validation in CrewAgentExecutor and BaseTool
* feat: enhance JSON argument parsing and validation in CrewAgentExecutor and BaseTool

- Added error handling for malformed JSON tool arguments in CrewAgentExecutor, providing descriptive error messages.
- Implemented schema validation for tool arguments in BaseTool, ensuring that invalid arguments raise appropriate exceptions.
- Introduced tests to verify correct behavior for both valid and invalid JSON inputs, enhancing robustness of tool execution.

* refactor: improve argument validation in BaseTool

- Introduced a new private method  to handle argument validation for tools, enhancing code clarity and reusability.
- Updated the  method to utilize the new validation method, ensuring consistent error handling for invalid arguments.
- Enhanced exception handling to specifically catch , providing clearer error messages for tool argument validation failures.

* feat: introduce parse_tool_call_args for improved argument parsing

- Added a new utility function, parse_tool_call_args, to handle parsing of tool call arguments from JSON strings or dictionaries, enhancing error handling for malformed JSON inputs.
- Updated CrewAgentExecutor and AgentExecutor to utilize the new parsing function, streamlining argument validation and improving clarity in error reporting.
- Introduced unit tests for parse_tool_call_args to ensure robust functionality and correct handling of various input scenarios.

* feat: add keyword argument validation in BaseTool and Tool classes

- Introduced a new method `_validate_kwargs` in BaseTool to validate keyword arguments against the defined schema, ensuring proper argument handling.
- Updated the `run` and `arun` methods in both BaseTool and Tool classes to utilize the new validation method, improving error handling and robustness.
- Added comprehensive tests for asynchronous execution in `TestBaseToolArunValidation` to verify correct behavior for valid and invalid keyword arguments.

* Potential fix for pull request finding 'Syntax error'

Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>

---------

Co-authored-by: lorenzejay <lorenzejaytech@gmail.com>
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
Co-authored-by: Greyson LaLonde <greyson.r.lalonde@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>
2026-02-25 13:13:31 -05:00
Greyson LaLonde
ee374d01de chore: add versioning logic for devtools 2026-02-25 12:13:00 -05:00
Greyson LaLonde
9914e51199 feat: add versioned docs
starting with 1.10.0
2026-02-25 11:05:31 -05:00
24 changed files with 2085 additions and 2019 deletions

View File

@@ -25,24 +25,12 @@ jobs:
- name: Checkout repository
uses: actions/checkout@v4
- name: Install uv
- name: Install uv and populate cache
uses: astral-sh/setup-uv@v6
with:
version: "0.8.4"
python-version: ${{ matrix.python-version }}
enable-cache: false
enable-cache: true
- name: Install dependencies and populate cache
run: |
echo "Building global UV cache for Python ${{ matrix.python-version }}..."
uv sync --all-groups --all-extras --no-install-project
echo "Cache populated successfully"
- name: Save uv caches
uses: actions/cache/save@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
- name: Install dependencies
run: uv sync --all-groups --all-extras --frozen --no-install-project

View File

@@ -18,27 +18,15 @@ jobs:
- name: Fetch Target Branch
run: git fetch origin $TARGET_BRANCH --depth=1
- name: Restore global uv cache
id: cache-restore
uses: actions/cache/restore@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py3.11-${{ hashFiles('uv.lock') }}
restore-keys: |
uv-main-py3.11-
- name: Install uv
uses: astral-sh/setup-uv@v6
with:
version: "0.8.4"
python-version: "3.11"
enable-cache: false
enable-cache: true
- name: Install dependencies
run: uv sync --all-groups --all-extras --no-install-project
run: uv sync --all-groups --all-extras --frozen --no-install-project
- name: Get Changed Python Files
id: changed-files
@@ -57,13 +45,3 @@ jobs:
| grep -v 'src/crewai/cli/templates/' \
| grep -v '/tests/' \
| xargs -I{} uv run ruff check "{}"
- name: Save uv caches
if: steps.cache-restore.outputs.cache-hit != 'true'
uses: actions/cache/save@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py3.11-${{ hashFiles('uv.lock') }}

View File

@@ -1,8 +1,6 @@
name: Publish to PyPI
on:
repository_dispatch:
types: [deployment-tests-passed]
workflow_dispatch:
inputs:
release_tag:
@@ -20,11 +18,8 @@ jobs:
- name: Determine release tag
id: release
run: |
# Priority: workflow_dispatch input > repository_dispatch payload > default branch
if [ -n "${{ inputs.release_tag }}" ]; then
echo "tag=${{ inputs.release_tag }}" >> $GITHUB_OUTPUT
elif [ -n "${{ github.event.client_payload.release_tag }}" ]; then
echo "tag=${{ github.event.client_payload.release_tag }}" >> $GITHUB_OUTPUT
else
echo "tag=" >> $GITHUB_OUTPUT
fi

View File

@@ -1,47 +1,42 @@
name: Run Tests
on: [pull_request]
on:
pull_request:
push:
branches: [main]
permissions:
contents: read
concurrency:
group: tests-${{ github.head_ref || github.run_id }}
cancel-in-progress: true
jobs:
tests:
name: tests (${{ matrix.python-version }})
name: tests (${{ matrix.python-version }}, ${{ matrix.group }}/4)
runs-on: ubuntu-latest
timeout-minutes: 15
timeout-minutes: 10
strategy:
fail-fast: true
matrix:
python-version: ['3.10', '3.11', '3.12', '3.13']
group: [1, 2, 3, 4, 5, 6, 7, 8]
group: [1, 2, 3, 4]
steps:
- name: Checkout code
uses: actions/checkout@v4
with:
fetch-depth: 0 # Fetch all history for proper diff
- name: Restore global uv cache
id: cache-restore
uses: actions/cache/restore@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
restore-keys: |
uv-main-py${{ matrix.python-version }}-
fetch-depth: 0
- name: Install uv
uses: astral-sh/setup-uv@v6
with:
version: "0.8.4"
python-version: ${{ matrix.python-version }}
enable-cache: false
enable-cache: true
- name: Install the project
run: uv sync --all-groups --all-extras
run: uv sync --all-groups --all-extras --frozen
- name: Restore test durations
uses: actions/cache/restore@v4
@@ -49,52 +44,56 @@ jobs:
path: .test_durations_py*
key: test-durations-py${{ matrix.python-version }}
- name: Run tests (group ${{ matrix.group }} of 8)
- name: Run tests (group ${{ matrix.group }} of 4)
run: |
PYTHON_VERSION_SAFE=$(echo "${{ matrix.python-version }}" | tr '.' '_')
DURATION_FILE="../../.test_durations_py${PYTHON_VERSION_SAFE}"
# Temporarily always skip cached durations to fix test splitting
# When durations don't match, pytest-split runs duplicate tests instead of splitting
echo "Using even test splitting (duration cache disabled until fix merged)"
DURATIONS_ARG=""
if [ -f "$DURATION_FILE" ]; then
if git diff "origin/${{ github.base_ref }}...HEAD" --name-only 2>/dev/null | grep -q "^lib/.*/tests/.*\.py$"; then
echo "::notice::Test files changed — using even splitting"
else
echo "::notice::Using cached test durations for optimal splitting"
DURATIONS_ARG="--durations-path=${DURATION_FILE}"
fi
else
echo "::notice::No cached durations — using even splitting"
fi
# Original logic (disabled temporarily):
# if [ ! -f "$DURATION_FILE" ]; then
# echo "No cached durations found, tests will be split evenly"
# DURATIONS_ARG=""
# elif git diff origin/${{ github.base_ref }}...HEAD --name-only 2>/dev/null | grep -q "^tests/.*\.py$"; then
# echo "Test files have changed, skipping cached durations to avoid mismatches"
# DURATIONS_ARG=""
# else
# echo "No test changes detected, using cached test durations for optimal splitting"
# DURATIONS_ARG="--durations-path=${DURATION_FILE}"
# fi
cd lib/crewai && uv run pytest \
cd lib/crewai && uv run --frozen pytest \
-vv \
--splits 8 \
--splits 4 \
--group ${{ matrix.group }} \
$DURATIONS_ARG \
--splitting-algorithm least_duration \
--durations=10 \
--maxfail=3
- name: Run tool tests (group ${{ matrix.group }} of 8)
- name: Run tool tests (group ${{ matrix.group }} of 4)
run: |
cd lib/crewai-tools && uv run pytest \
cd lib/crewai-tools && uv run --frozen pytest \
-vv \
--splits 8 \
--splits 4 \
--group ${{ matrix.group }} \
--durations=10 \
--maxfail=3
- name: Save uv caches
if: steps.cache-restore.outputs.cache-hit != 'true'
uses: actions/cache/save@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
# Gate jobs matching required status checks in branch protection
tests-gate:
name: tests (${{ matrix.python-version }})
needs: [tests]
if: always()
runs-on: ubuntu-latest
strategy:
matrix:
python-version: ['3.10', '3.11', '3.12', '3.13']
steps:
- name: Check test results
run: |
if [ "${{ needs.tests.result }}" = "success" ]; then
echo "All tests passed"
else
echo "Tests failed: ${{ needs.tests.result }}"
exit 1
fi

View File

@@ -1,18 +0,0 @@
name: Trigger Deployment Tests
on:
release:
types: [published]
jobs:
trigger:
name: Trigger deployment tests
runs-on: ubuntu-latest
steps:
- name: Trigger deployment tests
uses: peter-evans/repository-dispatch@v3
with:
token: ${{ secrets.CREWAI_DEPLOYMENTS_PAT }}
repository: ${{ secrets.CREWAI_DEPLOYMENTS_REPOSITORY }}
event-type: crewai-release
client-payload: '{"release_tag": "${{ github.event.release.tag_name }}", "release_name": "${{ github.event.release.name }}"}'

View File

@@ -20,27 +20,15 @@ jobs:
with:
fetch-depth: 0 # Fetch all history for proper diff
- name: Restore global uv cache
id: cache-restore
uses: actions/cache/restore@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
restore-keys: |
uv-main-py${{ matrix.python-version }}-
- name: Install uv
uses: astral-sh/setup-uv@v6
with:
version: "0.8.4"
python-version: ${{ matrix.python-version }}
enable-cache: false
enable-cache: true
- name: Install dependencies
run: uv sync --all-groups --all-extras
run: uv sync --all-groups --all-extras --frozen
- name: Get changed Python files
id: changed-files
@@ -74,16 +62,6 @@ jobs:
if: steps.changed-files.outputs.has_changes == 'false'
run: echo "No Python files in src/ were modified - skipping type checks"
- name: Save uv caches
if: steps.cache-restore.outputs.cache-hit != 'true'
uses: actions/cache/save@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
# Summary job to provide single status for branch protection
type-checker:
name: type-checker
@@ -94,8 +72,8 @@ jobs:
- name: Check matrix results
run: |
if [ "${{ needs.type-checker-matrix.result }}" == "success" ] || [ "${{ needs.type-checker-matrix.result }}" == "skipped" ]; then
echo "All type checks passed"
echo "All type checks passed"
else
echo "Type checks failed"
echo "Type checks failed"
exit 1
fi

View File

@@ -5,7 +5,9 @@ on:
branches:
- main
paths:
- 'tests/**/*.py'
- 'lib/crewai/tests/**/*.py'
- 'lib/crewai-tools/tests/**/*.py'
- 'lib/crewai-files/tests/**/*.py'
workflow_dispatch:
permissions:
@@ -20,37 +22,25 @@ jobs:
env:
OPENAI_API_KEY: fake-api-key
PYTHONUNBUFFERED: 1
steps:
- name: Checkout repository
uses: actions/checkout@v4
- name: Restore global uv cache
id: cache-restore
uses: actions/cache/restore@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
restore-keys: |
uv-main-py${{ matrix.python-version }}-
- name: Install uv
uses: astral-sh/setup-uv@v6
with:
version: "0.8.4"
python-version: ${{ matrix.python-version }}
enable-cache: false
enable-cache: true
- name: Install the project
run: uv sync --all-groups --all-extras
run: uv sync --all-groups --all-extras --frozen
- name: Run all tests and store durations
run: |
PYTHON_VERSION_SAFE=$(echo "${{ matrix.python-version }}" | tr '.' '_')
uv run pytest --store-durations --durations-path=.test_durations_py${PYTHON_VERSION_SAFE} -n auto
uv run --frozen pytest --store-durations --durations-path=.test_durations_py${PYTHON_VERSION_SAFE} -n auto
continue-on-error: true
- name: Save durations to cache
@@ -59,13 +49,3 @@ jobs:
with:
path: .test_durations_py*
key: test-durations-py${{ matrix.python-version }}
- name: Save uv caches
if: steps.cache-restore.outputs.cache-hit != 'true'
uses: actions/cache/save@v4
with:
path: |
~/.cache/uv
~/.local/share/uv
.venv
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}

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View File

@@ -98,11 +98,6 @@ from crewai_tools.tools.mongodb_vector_search_tool.vector_search import (
MongoDBVectorSearchTool,
)
from crewai_tools.tools.multion_tool.multion_tool import MultiOnTool
from crewai_tools.tools.oceanbase_vector_search_tool.oceanbase_vector_search_tool import (
OceanBaseToolSchema,
OceanBaseVectorSearchConfig,
OceanBaseVectorSearchTool,
)
from crewai_tools.tools.mysql_search_tool.mysql_search_tool import MySQLSearchTool
from crewai_tools.tools.nl2sql.nl2sql_tool import NL2SQLTool
from crewai_tools.tools.ocr_tool.ocr_tool import OCRTool
@@ -248,9 +243,6 @@ __all__ = [
"MongoDBVectorSearchTool",
"MultiOnTool",
"MySQLSearchTool",
"OceanBaseToolSchema",
"OceanBaseVectorSearchConfig",
"OceanBaseVectorSearchTool",
"NL2SQLTool",
"OCRTool",
"OxylabsAmazonProductScraperTool",

View File

@@ -87,11 +87,6 @@ from crewai_tools.tools.mongodb_vector_search_tool import (
MongoDBVectorSearchConfig,
MongoDBVectorSearchTool,
)
from crewai_tools.tools.oceanbase_vector_search_tool import (
OceanBaseToolSchema,
OceanBaseVectorSearchConfig,
OceanBaseVectorSearchTool,
)
from crewai_tools.tools.multion_tool.multion_tool import MultiOnTool
from crewai_tools.tools.mysql_search_tool.mysql_search_tool import MySQLSearchTool
from crewai_tools.tools.nl2sql.nl2sql_tool import NL2SQLTool
@@ -231,9 +226,6 @@ __all__ = [
"MongoDBVectorSearchConfig",
"MongoDBVectorSearchTool",
"MultiOnTool",
"OceanBaseToolSchema",
"OceanBaseVectorSearchConfig",
"OceanBaseVectorSearchTool",
"MySQLSearchTool",
"NL2SQLTool",
"OCRTool",

View File

@@ -1,144 +0,0 @@
# OceanBaseVectorSearchTool
## Description
This tool is designed for performing vector similarity searches within an OceanBase database. OceanBase is a distributed relational database developed by Ant Group that supports native vector indexing and search capabilities using HNSW (Hierarchical Navigable Small World) algorithm.
Use this tool to find semantically similar documents to a given query by leveraging OceanBase's vector search functionality.
For more information about OceanBase vector capabilities, see:
https://en.oceanbase.com/docs/common-oceanbase-database-10000000001976351
## Installation
Install the crewai_tools package with OceanBase support by executing the following command in your terminal:
```shell
pip install crewai-tools[oceanbase]
```
or
```shell
uv add crewai-tools --extra oceanbase
```
## Example
### Basic Usage
```python
from crewai_tools import OceanBaseVectorSearchTool
tool = OceanBaseVectorSearchTool(
connection_uri="127.0.0.1:2881",
user="root@test",
password="",
db_name="test",
table_name="documents",
)
```
### With Custom Configuration
```python
from crewai_tools import OceanBaseVectorSearchConfig, OceanBaseVectorSearchTool
query_config = OceanBaseVectorSearchConfig(
limit=10,
distance_func="cosine",
distance_threshold=0.5,
)
tool = OceanBaseVectorSearchTool(
connection_uri="127.0.0.1:2881",
user="root@test",
password="your_password",
db_name="my_database",
table_name="my_documents",
vector_column_name="embedding",
text_column_name="content",
metadata_column_name="metadata",
query_config=query_config,
embedding_model="text-embedding-3-large",
dimensions=3072,
)
```
### Adding the Tool to an Agent
```python
from crewai import Agent
from crewai_tools import OceanBaseVectorSearchTool
tool = OceanBaseVectorSearchTool(
connection_uri="127.0.0.1:2881",
user="root@test",
db_name="test",
table_name="documents",
)
rag_agent = Agent(
name="rag_agent",
role="You are a helpful assistant that can answer questions using the OceanBaseVectorSearchTool.",
goal="Answer user questions by searching relevant documents",
backstory="You have access to a knowledge base stored in OceanBase",
llm="gpt-4o-mini",
tools=[tool],
)
```
### Preloading Documents
```python
from crewai_tools import OceanBaseVectorSearchTool
import os
tool = OceanBaseVectorSearchTool(
connection_uri="127.0.0.1:2881",
user="root@test",
db_name="test",
table_name="documents",
)
texts = []
metadatas = []
for filename in os.listdir("knowledge"):
with open(os.path.join("knowledge", filename), "r") as f:
texts.append(f.read())
metadatas.append({"source": filename})
tool.add_texts(texts, metadatas=metadatas)
```
## Configuration Options
### OceanBaseVectorSearchConfig
| Parameter | Type | Default | Description |
|-----------|------|---------|-------------|
| `limit` | int | 4 | Number of documents to return |
| `distance_func` | str | "l2" | Distance function: "l2", "cosine", or "inner_product" |
| `distance_threshold` | float | None | Only return results with distance <= threshold |
| `include_embeddings` | bool | False | Whether to include embedding vectors in results |
### OceanBaseVectorSearchTool
| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `connection_uri` | str | Yes | OceanBase connection URI (e.g., "127.0.0.1:2881") |
| `user` | str | Yes | Username for connection (e.g., "root@test") |
| `password` | str | No | Password for connection |
| `db_name` | str | No | Database name (default: "test") |
| `table_name` | str | Yes | Table containing vector data |
| `vector_column_name` | str | No | Column with embeddings (default: "embedding") |
| `text_column_name` | str | No | Column with text content (default: "text") |
| `metadata_column_name` | str | No | Column with metadata (default: "metadata") |
| `embedding_model` | str | No | OpenAI model for embeddings (default: "text-embedding-3-large") |
| `dimensions` | int | No | Embedding dimensions (default: 1536) |
| `query_config` | OceanBaseVectorSearchConfig | No | Search configuration |
## Environment Variables
- `OPENAI_API_KEY`: Required for generating embeddings
- `AZURE_OPENAI_ENDPOINT`: Optional, for Azure OpenAI support

View File

@@ -1,12 +0,0 @@
from crewai_tools.tools.oceanbase_vector_search_tool.oceanbase_vector_search_tool import (
OceanBaseToolSchema,
OceanBaseVectorSearchConfig,
OceanBaseVectorSearchTool,
)
__all__ = [
"OceanBaseToolSchema",
"OceanBaseVectorSearchConfig",
"OceanBaseVectorSearchTool",
]

View File

@@ -1,267 +0,0 @@
from __future__ import annotations
import json
from logging import getLogger
import os
from typing import Any
from crewai.tools import BaseTool, EnvVar
from pydantic import BaseModel, Field
try:
import pyobvector # noqa: F401
PYOBVECTOR_AVAILABLE = True
except ImportError:
PYOBVECTOR_AVAILABLE = False
logger = getLogger(__name__)
class OceanBaseToolSchema(BaseModel):
"""Input schema for OceanBase vector search tool."""
query: str = Field(
...,
description="The query to search for relevant information in the OceanBase database.",
)
class OceanBaseVectorSearchConfig(BaseModel):
"""Configuration for OceanBase vector search queries."""
limit: int = Field(
default=4,
description="Number of documents to return.",
)
distance_threshold: float | None = Field(
default=None,
description="Only return results where distance is less than or equal to this threshold.",
)
distance_func: str = Field(
default="l2",
description="Distance function to use for similarity search. Options: 'l2', 'cosine', 'inner_product'.",
)
include_embeddings: bool = Field(
default=False,
description="Whether to include the embedding vector of each result.",
)
class OceanBaseVectorSearchTool(BaseTool):
"""Tool to perform vector search on OceanBase database."""
name: str = "OceanBaseVectorSearchTool"
description: str = (
"A tool to perform vector similarity search on an OceanBase database "
"for retrieving relevant information from stored documents."
)
args_schema: type[BaseModel] = OceanBaseToolSchema
query_config: OceanBaseVectorSearchConfig | None = Field(
default=None,
description="OceanBase vector search query configuration.",
)
embedding_model: str = Field(
default="text-embedding-3-large",
description="OpenAI embedding model to use for generating query embeddings.",
)
dimensions: int = Field(
default=1536,
description="Number of dimensions in the embedding vector.",
)
connection_uri: str = Field(
...,
description="Connection URI for OceanBase (e.g., '127.0.0.1:2881').",
)
user: str = Field(
...,
description="Username for OceanBase connection (e.g., 'root@test').",
)
password: str = Field(
default="",
description="Password for OceanBase connection.",
)
db_name: str = Field(
default="test",
description="Database name in OceanBase.",
)
table_name: str = Field(
...,
description="Name of the table containing vector data.",
)
vector_column_name: str = Field(
default="embedding",
description="Name of the column containing vector embeddings.",
)
text_column_name: str = Field(
default="text",
description="Name of the column containing text content.",
)
metadata_column_name: str | None = Field(
default="metadata",
description="Name of the column containing metadata (optional).",
)
env_vars: list[EnvVar] = Field(
default_factory=lambda: [
EnvVar(
name="OPENAI_API_KEY",
description="API key for OpenAI embeddings",
required=True,
),
]
)
package_dependencies: list[str] = Field(default_factory=lambda: ["pyobvector"])
_client: Any = None
_openai_client: Any = None
def __init__(self, **kwargs: Any) -> None:
super().__init__(**kwargs)
if not PYOBVECTOR_AVAILABLE:
import click
if click.confirm(
"You are missing the 'pyobvector' package. Would you like to install it?"
):
import subprocess
subprocess.run(["uv", "add", "pyobvector"], check=True) # noqa: S607
else:
raise ImportError(
"The 'pyobvector' package is required for OceanBaseVectorSearchTool."
)
if "AZURE_OPENAI_ENDPOINT" in os.environ:
from openai import AzureOpenAI
self._openai_client = AzureOpenAI()
elif "OPENAI_API_KEY" in os.environ:
from openai import Client
self._openai_client = Client()
else:
raise ValueError(
"OPENAI_API_KEY environment variable is required for OceanBaseVectorSearchTool."
)
from pyobvector import ObVecClient
self._client = ObVecClient(
uri=self.connection_uri,
user=self.user,
password=self.password,
db_name=self.db_name,
)
def _embed_text(self, text: str) -> list[float]:
"""Generate embedding for the given text using OpenAI."""
response = self._openai_client.embeddings.create(
input=[text],
model=self.embedding_model,
dimensions=self.dimensions,
)
return response.data[0].embedding
def _get_distance_func(self) -> Any:
"""Get the appropriate distance function from pyobvector."""
import pyobvector
config = self.query_config or OceanBaseVectorSearchConfig()
valid_distance_funcs = {
"l2": "l2_distance",
"cosine": "cosine_distance",
"inner_product": "inner_product",
}
func_name = valid_distance_funcs.get(config.distance_func, "l2_distance")
return getattr(pyobvector, func_name)
def _run(self, query: str) -> str:
"""Execute vector search on OceanBase."""
try:
config = self.query_config or OceanBaseVectorSearchConfig()
query_vector = self._embed_text(query)
output_columns = [self.text_column_name]
if self.metadata_column_name:
output_columns.append(self.metadata_column_name)
results = self._client.ann_search(
table_name=self.table_name,
vec_data=query_vector,
vec_column_name=self.vector_column_name,
distance_func=self._get_distance_func(),
with_dist=True,
topk=config.limit,
output_column_names=output_columns,
distance_threshold=config.distance_threshold,
)
formatted_results = []
for row in results:
result_dict: dict[str, Any] = {}
if len(row) >= 1:
result_dict["text"] = row[0]
if self.metadata_column_name and len(row) >= 2:
result_dict["metadata"] = row[1]
if len(row) > len(output_columns):
result_dict["distance"] = row[-1]
formatted_results.append(result_dict)
return json.dumps(formatted_results, indent=2, default=str)
except Exception as e:
logger.error(f"Error during OceanBase vector search: {e}")
return json.dumps({"error": str(e)})
def add_texts(
self,
texts: list[str],
metadatas: list[dict[str, Any]] | None = None,
ids: list[str] | None = None,
) -> list[str]:
"""Add texts with embeddings to the OceanBase table.
Args:
texts: List of text strings to add.
metadatas: Optional list of metadata dictionaries for each text.
ids: Optional list of unique IDs for each text.
Returns:
List of IDs for the added texts.
"""
import uuid
if ids is None:
ids = [str(uuid.uuid4()) for _ in texts]
if metadatas is None:
metadatas = [{} for _ in texts]
data = []
for text, metadata, doc_id in zip(texts, metadatas, ids, strict=False):
embedding = self._embed_text(text)
row = {
"id": doc_id,
self.text_column_name: text,
self.vector_column_name: embedding,
}
if self.metadata_column_name:
row[self.metadata_column_name] = metadata
data.append(row)
self._client.insert(self.table_name, data=data)
return ids
def __del__(self) -> None:
"""Cleanup clients on deletion."""
try:
if hasattr(self, "_openai_client") and self._openai_client:
self._openai_client.close()
except Exception as e:
logger.error(f"Error closing OpenAI client: {e}")

View File

@@ -1,208 +0,0 @@
import json
import sys
from unittest.mock import MagicMock, patch
import pytest
from crewai_tools import OceanBaseVectorSearchConfig
mock_pyobvector = MagicMock()
mock_pyobvector.ObVecClient = MagicMock()
mock_pyobvector.l2_distance = MagicMock(return_value="l2_func")
mock_pyobvector.cosine_distance = MagicMock(return_value="cosine_func")
mock_pyobvector.inner_product = MagicMock(return_value="ip_func")
sys.modules["pyobvector"] = mock_pyobvector
@pytest.fixture
def mock_openai_client():
"""Create a mock OpenAI client."""
mock_client = MagicMock()
mock_embedding = MagicMock()
mock_embedding.embedding = [0.1] * 1536
mock_response = MagicMock()
mock_response.data = [mock_embedding]
mock_client.embeddings.create.return_value = mock_response
return mock_client
@pytest.fixture
def mock_obvec_client():
"""Create a mock OceanBase vector client."""
mock_client = MagicMock()
return mock_client
@pytest.fixture
def oceanbase_vector_search_tool(mock_openai_client, mock_obvec_client):
"""Create an OceanBaseVectorSearchTool with mocked clients."""
from crewai_tools import OceanBaseVectorSearchTool
with patch.dict("os.environ", {"OPENAI_API_KEY": "test-key"}):
with patch(
"crewai_tools.tools.oceanbase_vector_search_tool.oceanbase_vector_search_tool.PYOBVECTOR_AVAILABLE",
True,
):
mock_pyobvector.ObVecClient.return_value = mock_obvec_client
with patch("openai.Client") as mock_openai_class:
mock_openai_class.return_value = mock_openai_client
tool = OceanBaseVectorSearchTool(
connection_uri="127.0.0.1:2881",
user="root@test",
password="",
db_name="test",
table_name="test_table",
)
tool._openai_client = mock_openai_client
tool._client = mock_obvec_client
yield tool
def test_successful_query_execution(oceanbase_vector_search_tool, mock_obvec_client):
"""Test successful vector search query execution."""
mock_obvec_client.ann_search.return_value = [
("test document content", {"source": "test.txt"}, 0.1),
("another document", {"source": "test2.txt"}, 0.2),
]
results = json.loads(oceanbase_vector_search_tool._run(query="test query"))
assert len(results) == 2
assert results[0]["text"] == "test document content"
assert results[0]["metadata"] == {"source": "test.txt"}
assert results[0]["distance"] == 0.1
def test_query_with_custom_config(mock_openai_client, mock_obvec_client):
"""Test vector search with custom configuration."""
from crewai_tools import OceanBaseVectorSearchTool
query_config = OceanBaseVectorSearchConfig(
limit=10,
distance_func="cosine",
distance_threshold=0.5,
)
with patch.dict("os.environ", {"OPENAI_API_KEY": "test-key"}):
with patch(
"crewai_tools.tools.oceanbase_vector_search_tool.oceanbase_vector_search_tool.PYOBVECTOR_AVAILABLE",
True,
):
mock_pyobvector.ObVecClient.return_value = mock_obvec_client
with patch("openai.Client") as mock_openai_class:
mock_openai_class.return_value = mock_openai_client
tool = OceanBaseVectorSearchTool(
connection_uri="127.0.0.1:2881",
user="root@test",
db_name="test",
table_name="test_table",
query_config=query_config,
)
tool._openai_client = mock_openai_client
tool._client = mock_obvec_client
mock_obvec_client.ann_search.return_value = [("doc", {}, 0.3)]
tool._run(query="test")
call_kwargs = mock_obvec_client.ann_search.call_args.kwargs
assert call_kwargs["topk"] == 10
assert call_kwargs["distance_threshold"] == 0.5
def test_add_texts(oceanbase_vector_search_tool, mock_obvec_client):
"""Test adding texts to the OceanBase table."""
texts = ["document 1", "document 2"]
metadatas = [{"source": "file1.txt"}, {"source": "file2.txt"}]
result_ids = oceanbase_vector_search_tool.add_texts(texts, metadatas=metadatas)
assert len(result_ids) == 2
mock_obvec_client.insert.assert_called_once()
call_args = mock_obvec_client.insert.call_args
assert call_args[0][0] == "test_table"
assert len(call_args[1]["data"]) == 2
def test_add_texts_without_metadata(oceanbase_vector_search_tool, mock_obvec_client):
"""Test adding texts without metadata."""
texts = ["document 1", "document 2"]
result_ids = oceanbase_vector_search_tool.add_texts(texts)
assert len(result_ids) == 2
mock_obvec_client.insert.assert_called_once()
def test_error_handling(oceanbase_vector_search_tool, mock_obvec_client):
"""Test error handling during search."""
mock_obvec_client.ann_search.side_effect = Exception("Database connection error")
result = json.loads(oceanbase_vector_search_tool._run(query="test"))
assert "error" in result
assert "Database connection error" in result["error"]
def test_config_defaults():
"""Test OceanBaseVectorSearchConfig default values."""
config = OceanBaseVectorSearchConfig()
assert config.limit == 4
assert config.distance_func == "l2"
assert config.distance_threshold is None
assert config.include_embeddings is False
def test_config_custom_values():
"""Test OceanBaseVectorSearchConfig with custom values."""
config = OceanBaseVectorSearchConfig(
limit=20,
distance_func="cosine",
distance_threshold=0.8,
include_embeddings=True,
)
assert config.limit == 20
assert config.distance_func == "cosine"
assert config.distance_threshold == 0.8
assert config.include_embeddings is True
def test_tool_schema():
"""Test OceanBaseToolSchema validation."""
from crewai_tools import OceanBaseToolSchema
schema = OceanBaseToolSchema(query="test query")
assert schema.query == "test query"
def test_tool_schema_requires_query():
"""Test that OceanBaseToolSchema requires a query."""
from crewai_tools import OceanBaseToolSchema
from pydantic import ValidationError
with pytest.raises(ValidationError):
OceanBaseToolSchema()
def test_distance_function_selection(oceanbase_vector_search_tool):
"""Test that the correct distance function is selected."""
oceanbase_vector_search_tool.query_config = OceanBaseVectorSearchConfig(
distance_func="l2"
)
func = oceanbase_vector_search_tool._get_distance_func()
assert func == mock_pyobvector.l2_distance
oceanbase_vector_search_tool.query_config = OceanBaseVectorSearchConfig(
distance_func="cosine"
)
func = oceanbase_vector_search_tool._get_distance_func()
assert func == mock_pyobvector.cosine_distance
oceanbase_vector_search_tool.query_config = OceanBaseVectorSearchConfig(
distance_func="inner_product"
)
func = oceanbase_vector_search_tool._get_distance_func()
assert func == mock_pyobvector.inner_product

View File

@@ -50,6 +50,7 @@ from crewai.utilities.agent_utils import (
handle_unknown_error,
has_reached_max_iterations,
is_context_length_exceeded,
parse_tool_call_args,
process_llm_response,
track_delegation_if_needed,
)
@@ -894,13 +895,9 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
ToolUsageStartedEvent,
)
if isinstance(func_args, str):
try:
args_dict = json.loads(func_args)
except json.JSONDecodeError:
args_dict = {}
else:
args_dict = func_args
args_dict, parse_error = parse_tool_call_args(func_args, func_name, call_id, original_tool)
if parse_error is not None:
return parse_error
if original_tool is None:
for tool in self.original_tools or []:

View File

@@ -66,6 +66,7 @@ from crewai.utilities.agent_utils import (
has_reached_max_iterations,
is_context_length_exceeded,
is_inside_event_loop,
parse_tool_call_args,
process_llm_response,
track_delegation_if_needed,
)
@@ -848,13 +849,9 @@ class AgentExecutor(Flow[AgentReActState], CrewAgentExecutorMixin):
call_id, func_name, func_args = info
# Parse arguments
if isinstance(func_args, str):
try:
args_dict = json.loads(func_args)
except json.JSONDecodeError:
args_dict = {}
else:
args_dict = func_args
args_dict, parse_error = parse_tool_call_args(func_args, func_name, call_id)
if parse_error is not None:
return parse_error
# Get agent_key for event tracking
agent_key = getattr(self.agent, "key", "unknown") if self.agent else "unknown"

View File

@@ -18,6 +18,7 @@ from pydantic import (
BaseModel as PydanticBaseModel,
ConfigDict,
Field,
ValidationError,
create_model,
field_validator,
)
@@ -150,14 +151,37 @@ class BaseTool(BaseModel, ABC):
super().model_post_init(__context)
def _validate_kwargs(self, kwargs: dict[str, Any]) -> dict[str, Any]:
"""Validate keyword arguments against args_schema if present.
Args:
kwargs: The keyword arguments to validate.
Returns:
Validated (and possibly coerced) keyword arguments.
Raises:
ValueError: If validation against args_schema fails.
"""
if kwargs and self.args_schema is not None and self.args_schema.model_fields:
try:
validated = self.args_schema.model_validate(kwargs)
return validated.model_dump()
except Exception as e:
raise ValueError(
f"Tool '{self.name}' arguments validation failed: {e}"
) from e
return kwargs
def run(
self,
*args: Any,
**kwargs: Any,
) -> Any:
kwargs = self._validate_kwargs(kwargs)
result = self._run(*args, **kwargs)
# If _run is async, we safely run it
if asyncio.iscoroutine(result):
result = asyncio.run(result)
@@ -179,6 +203,7 @@ class BaseTool(BaseModel, ABC):
Returns:
The result of the tool execution.
"""
kwargs = self._validate_kwargs(kwargs)
result = await self._arun(*args, **kwargs)
self.current_usage_count += 1
return result
@@ -331,6 +356,8 @@ class Tool(BaseTool, Generic[P, R]):
Returns:
The result of the tool execution.
"""
kwargs = self._validate_kwargs(kwargs)
result = self.func(*args, **kwargs)
if asyncio.iscoroutine(result):
@@ -361,6 +388,7 @@ class Tool(BaseTool, Generic[P, R]):
Returns:
The result of the tool execution.
"""
kwargs = self._validate_kwargs(kwargs)
result = await self._arun(*args, **kwargs)
self.current_usage_count += 1
return result

View File

@@ -1146,6 +1146,36 @@ def extract_tool_call_info(
return None
def parse_tool_call_args(
func_args: dict[str, Any] | str,
func_name: str,
call_id: str,
original_tool: Any = None,
) -> tuple[dict[str, Any], None] | tuple[None, dict[str, Any]]:
"""Parse tool call arguments from a JSON string or dict.
Returns:
``(args_dict, None)`` on success, or ``(None, error_result)`` on
JSON parse failure where ``error_result`` is a ready-to-return dict
with the same shape as ``_execute_single_native_tool_call`` return values.
"""
if isinstance(func_args, str):
try:
return json.loads(func_args), None
except json.JSONDecodeError as e:
return None, {
"call_id": call_id,
"func_name": func_name,
"result": (
f"Error: Failed to parse tool arguments as JSON: {e}. "
f"Please provide valid JSON arguments for the '{func_name}' tool."
),
"from_cache": False,
"original_tool": original_tool,
}
return func_args, None
def _setup_before_llm_call_hooks(
executor_context: CrewAgentExecutor | AgentExecutor | LiteAgent | None,
printer: Printer,

View File

@@ -11,7 +11,7 @@ import os
import threading
import time
from collections import Counter
from unittest.mock import patch
from unittest.mock import Mock, patch
import pytest
from pydantic import BaseModel, Field
@@ -1129,3 +1129,150 @@ class TestMaxUsageCountWithNativeToolCalling:
# Verify the requested calls occurred while keeping usage bounded.
assert tool.current_usage_count >= 2
assert tool.current_usage_count <= tool.max_usage_count
# =============================================================================
# JSON Parse Error Handling Tests
# =============================================================================
class TestNativeToolCallingJsonParseError:
"""Tests that malformed JSON tool arguments produce clear errors
instead of silently dropping all arguments."""
def _make_executor(self, tools: list[BaseTool]) -> "CrewAgentExecutor":
"""Create a minimal CrewAgentExecutor with mocked dependencies."""
from crewai.agents.crew_agent_executor import CrewAgentExecutor
from crewai.tools.base_tool import to_langchain
structured_tools = to_langchain(tools)
mock_agent = Mock()
mock_agent.key = "test_agent"
mock_agent.role = "tester"
mock_agent.verbose = False
mock_agent.fingerprint = None
mock_agent.tools_results = []
mock_task = Mock()
mock_task.name = "test"
mock_task.description = "test"
mock_task.id = "test-id"
executor = object.__new__(CrewAgentExecutor)
executor.agent = mock_agent
executor.task = mock_task
executor.crew = Mock()
executor.tools = structured_tools
executor.original_tools = tools
executor.tools_handler = None
executor._printer = Mock()
executor.messages = []
return executor
def test_malformed_json_returns_parse_error(self) -> None:
"""Malformed JSON args must return a descriptive error, not silently become {}."""
class CodeTool(BaseTool):
name: str = "execute_code"
description: str = "Run code"
def _run(self, code: str) -> str:
return f"ran: {code}"
tool = CodeTool()
executor = self._make_executor([tool])
from crewai.utilities.agent_utils import convert_tools_to_openai_schema
_, available_functions = convert_tools_to_openai_schema([tool])
malformed_json = '{"code": "print("hello")"}'
result = executor._execute_single_native_tool_call(
call_id="call_123",
func_name="execute_code",
func_args=malformed_json,
available_functions=available_functions,
)
assert "Failed to parse tool arguments as JSON" in result["result"]
assert tool.current_usage_count == 0
def test_valid_json_still_executes_normally(self) -> None:
"""Valid JSON args should execute the tool as before."""
class CodeTool(BaseTool):
name: str = "execute_code"
description: str = "Run code"
def _run(self, code: str) -> str:
return f"ran: {code}"
tool = CodeTool()
executor = self._make_executor([tool])
from crewai.utilities.agent_utils import convert_tools_to_openai_schema
_, available_functions = convert_tools_to_openai_schema([tool])
valid_json = '{"code": "print(1)"}'
result = executor._execute_single_native_tool_call(
call_id="call_456",
func_name="execute_code",
func_args=valid_json,
available_functions=available_functions,
)
assert result["result"] == "ran: print(1)"
def test_dict_args_bypass_json_parsing(self) -> None:
"""When func_args is already a dict, no JSON parsing occurs."""
class CodeTool(BaseTool):
name: str = "execute_code"
description: str = "Run code"
def _run(self, code: str) -> str:
return f"ran: {code}"
tool = CodeTool()
executor = self._make_executor([tool])
from crewai.utilities.agent_utils import convert_tools_to_openai_schema
_, available_functions = convert_tools_to_openai_schema([tool])
result = executor._execute_single_native_tool_call(
call_id="call_789",
func_name="execute_code",
func_args={"code": "x = 42"},
available_functions=available_functions,
)
assert result["result"] == "ran: x = 42"
def test_schema_validation_catches_missing_args_on_native_path(self) -> None:
"""The native function calling path should now enforce args_schema,
catching missing required fields before _run is called."""
class StrictTool(BaseTool):
name: str = "strict_tool"
description: str = "A tool with required args"
def _run(self, code: str, language: str) -> str:
return f"{language}: {code}"
tool = StrictTool()
executor = self._make_executor([tool])
from crewai.utilities.agent_utils import convert_tools_to_openai_schema
_, available_functions = convert_tools_to_openai_schema([tool])
result = executor._execute_single_native_tool_call(
call_id="call_schema",
func_name="strict_tool",
func_args={"code": "print(1)"},
available_functions=available_functions,
)
assert "Error" in result["result"]
assert "validation failed" in result["result"].lower() or "missing" in result["result"].lower()

View File

@@ -3,6 +3,8 @@ from typing import Callable
from unittest.mock import patch
import pytest
from pydantic import BaseModel, Field
from crewai.agent import Agent
from crewai.crew import Crew
from crewai.task import Task
@@ -230,3 +232,204 @@ def test_max_usage_count_is_respected():
crew.kickoff()
assert tool.max_usage_count == 5
assert tool.current_usage_count == 5
# =============================================================================
# Schema Validation in run() Tests
# =============================================================================
class CodeExecutorInput(BaseModel):
code: str = Field(description="The code to execute")
language: str = Field(default="python", description="Programming language")
class CodeExecutorTool(BaseTool):
name: str = "code_executor"
description: str = "Execute code snippets"
args_schema: type[BaseModel] = CodeExecutorInput
def _run(self, code: str, language: str = "python") -> str:
return f"Executed {language}: {code}"
class TestBaseToolRunValidation:
"""Tests for args_schema validation in BaseTool.run()."""
def test_run_with_valid_kwargs_passes_validation(self) -> None:
"""Valid keyword arguments should pass schema validation and execute."""
t = CodeExecutorTool()
result = t.run(code="print('hello')")
assert result == "Executed python: print('hello')"
def test_run_with_all_kwargs_passes_validation(self) -> None:
"""All keyword arguments including optional ones should pass."""
t = CodeExecutorTool()
result = t.run(code="console.log('hi')", language="javascript")
assert result == "Executed javascript: console.log('hi')"
def test_run_with_missing_required_kwarg_raises(self) -> None:
"""Missing required kwargs should raise ValueError from schema validation."""
t = CodeExecutorTool()
with pytest.raises(ValueError, match="validation failed"):
t.run(language="python")
def test_run_with_wrong_field_name_raises(self) -> None:
"""Kwargs not matching any schema field should trigger validation error
for missing required fields."""
t = CodeExecutorTool()
with pytest.raises(ValueError, match="validation failed"):
t.run(wrong_arg="value")
def test_run_with_positional_args_skips_validation(self) -> None:
"""Positional-arg calls should bypass schema validation (backwards compat)."""
class SimpleTool(BaseTool):
name: str = "simple"
description: str = "A simple tool"
def _run(self, question: str) -> str:
return question
t = SimpleTool()
result = t.run("What is life?")
assert result == "What is life?"
def test_run_strips_extra_kwargs_from_llm(self) -> None:
"""Extra kwargs not in the schema should be silently stripped,
preventing unexpected-keyword crashes in _run."""
t = CodeExecutorTool()
result = t.run(code="1+1", extra_hallucinated_field="junk")
assert result == "Executed python: 1+1"
def test_run_increments_usage_after_validation(self) -> None:
"""Usage count should still increment after validated execution."""
t = CodeExecutorTool()
assert t.current_usage_count == 0
t.run(code="x = 1")
assert t.current_usage_count == 1
def test_run_does_not_increment_usage_on_validation_error(self) -> None:
"""Usage count should NOT increment when validation fails."""
t = CodeExecutorTool()
assert t.current_usage_count == 0
with pytest.raises(ValueError):
t.run(wrong="bad")
assert t.current_usage_count == 0
class TestToolDecoratorRunValidation:
"""Tests for args_schema validation in Tool.run() (decorator-based tools)."""
def test_decorator_tool_run_validates_kwargs(self) -> None:
"""Decorator-created tools should also validate kwargs against schema."""
@tool("execute_code")
def execute_code(code: str, language: str = "python") -> str:
"""Execute a code snippet."""
return f"Executed {language}: {code}"
result = execute_code.run(code="x = 1")
assert result == "Executed python: x = 1"
def test_decorator_tool_run_rejects_missing_required(self) -> None:
"""Decorator tools should reject missing required args via validation."""
@tool("execute_code")
def execute_code(code: str) -> str:
"""Execute a code snippet."""
return f"Executed: {code}"
with pytest.raises(ValueError, match="validation failed"):
execute_code.run(wrong_arg="value")
def test_decorator_tool_positional_args_still_work(self) -> None:
"""Positional args to decorator tools should bypass validation."""
@tool("greet")
def greet(name: str) -> str:
"""Greet someone."""
return f"Hello, {name}!"
result = greet.run("World")
assert result == "Hello, World!"
# =============================================================================
# Async arun() Schema Validation Tests
# =============================================================================
class AsyncCodeExecutorTool(BaseTool):
name: str = "async_code_executor"
description: str = "Execute code snippets asynchronously"
args_schema: type[BaseModel] = CodeExecutorInput
async def _arun(self, code: str, language: str = "python") -> str:
return f"Async executed {language}: {code}"
def _run(self, code: str, language: str = "python") -> str:
return f"Executed {language}: {code}"
class TestBaseToolArunValidation:
"""Tests for args_schema validation in BaseTool.arun()."""
@pytest.mark.asyncio
async def test_arun_with_valid_kwargs_passes_validation(self) -> None:
"""Valid keyword arguments should pass schema validation in arun."""
t = AsyncCodeExecutorTool()
result = await t.arun(code="print('hello')")
assert result == "Async executed python: print('hello')"
@pytest.mark.asyncio
async def test_arun_with_missing_required_kwarg_raises(self) -> None:
"""Missing required kwargs should raise ValueError in arun."""
t = AsyncCodeExecutorTool()
with pytest.raises(ValueError, match="validation failed"):
await t.arun(language="python")
@pytest.mark.asyncio
async def test_arun_with_wrong_field_name_raises(self) -> None:
"""Kwargs not matching schema fields should trigger validation error in arun."""
t = AsyncCodeExecutorTool()
with pytest.raises(ValueError, match="validation failed"):
await t.arun(wrong_arg="value")
@pytest.mark.asyncio
async def test_arun_strips_extra_kwargs(self) -> None:
"""Extra kwargs not in the schema should be stripped in arun."""
t = AsyncCodeExecutorTool()
result = await t.arun(code="1+1", extra_field="junk")
assert result == "Async executed python: 1+1"
@pytest.mark.asyncio
async def test_arun_does_not_increment_usage_on_validation_error(self) -> None:
"""Usage count should NOT increment when arun validation fails."""
t = AsyncCodeExecutorTool()
assert t.current_usage_count == 0
with pytest.raises(ValueError):
await t.arun(wrong="bad")
assert t.current_usage_count == 0
class TestToolDecoratorArunValidation:
"""Tests for args_schema validation in Tool.arun() (decorator-based async tools)."""
@pytest.mark.asyncio
async def test_async_decorator_tool_arun_validates_kwargs(self) -> None:
"""Async decorator tools should validate kwargs in arun."""
@tool("async_execute")
async def async_execute(code: str, language: str = "python") -> str:
"""Execute code asynchronously."""
return f"Async {language}: {code}"
result = await async_execute.arun(code="x = 1")
assert result == "Async python: x = 1"
@pytest.mark.asyncio
async def test_async_decorator_tool_arun_rejects_missing_required(self) -> None:
"""Async decorator tools should reject missing required args in arun."""
@tool("async_execute")
async def async_execute(code: str) -> str:
"""Execute code asynchronously."""
return f"Async: {code}"
with pytest.raises(ValueError, match="validation failed"):
await async_execute.arun(wrong_arg="value")

View File

@@ -17,6 +17,7 @@ from crewai.utilities.agent_utils import (
_format_messages_for_summary,
_split_messages_into_chunks,
convert_tools_to_openai_schema,
parse_tool_call_args,
summarize_messages,
)
@@ -922,3 +923,56 @@ class TestParallelSummarizationVCR:
assert summary_msg["role"] == "user"
assert "files" in summary_msg
assert "report.pdf" in summary_msg["files"]
class TestParseToolCallArgs:
"""Unit tests for parse_tool_call_args."""
def test_valid_json_string_returns_dict(self) -> None:
args_dict, error = parse_tool_call_args('{"code": "print(1)"}', "run_code", "call_1")
assert error is None
assert args_dict == {"code": "print(1)"}
def test_malformed_json_returns_error_dict(self) -> None:
args_dict, error = parse_tool_call_args('{"code": "print("hi")"}', "run_code", "call_1")
assert args_dict is None
assert error is not None
assert error["call_id"] == "call_1"
assert error["func_name"] == "run_code"
assert error["from_cache"] is False
assert "Failed to parse tool arguments as JSON" in error["result"]
assert "run_code" in error["result"]
def test_malformed_json_preserves_original_tool(self) -> None:
mock_tool = object()
_, error = parse_tool_call_args("{bad}", "my_tool", "call_2", original_tool=mock_tool)
assert error is not None
assert error["original_tool"] is mock_tool
def test_malformed_json_original_tool_defaults_to_none(self) -> None:
_, error = parse_tool_call_args("{bad}", "my_tool", "call_3")
assert error is not None
assert error["original_tool"] is None
def test_dict_input_returned_directly(self) -> None:
func_args = {"code": "x = 42"}
args_dict, error = parse_tool_call_args(func_args, "run_code", "call_4")
assert error is None
assert args_dict == {"code": "x = 42"}
def test_empty_dict_input_returned_directly(self) -> None:
args_dict, error = parse_tool_call_args({}, "run_code", "call_5")
assert error is None
assert args_dict == {}
def test_valid_json_with_nested_values(self) -> None:
args_dict, error = parse_tool_call_args(
'{"query": "hello", "options": {"limit": 10}}', "search", "call_6"
)
assert error is None
assert args_dict == {"query": "hello", "options": {"limit": 10}}
def test_error_result_has_correct_keys(self) -> None:
_, error = parse_tool_call_args("{bad json}", "tool", "call_7")
assert error is not None
assert set(error.keys()) == {"call_id", "func_name", "result", "from_cache", "original_tool"}

View File

@@ -14,7 +14,7 @@ from rich.markdown import Markdown
from rich.panel import Panel
from rich.prompt import Confirm
from crewai_devtools.prompts import RELEASE_NOTES_PROMPT
from crewai_devtools.prompts import RELEASE_NOTES_PROMPT, TRANSLATE_RELEASE_NOTES_PROMPT
load_dotenv()
@@ -191,6 +191,248 @@ def update_pyproject_dependencies(file_path: Path, new_version: str) -> bool:
return False
def add_docs_version(docs_json_path: Path, version: str) -> bool:
"""Add a new version to the Mintlify docs.json versioning config.
Copies the current default version's tabs into a new version entry,
sets the new version as default, and marks the previous default as
non-default. Operates on all languages.
Args:
docs_json_path: Path to docs/docs.json.
version: Version string (e.g., "1.10.0").
Returns:
True if docs.json was updated, False otherwise.
"""
import json
if not docs_json_path.exists():
return False
data = json.loads(docs_json_path.read_text())
version_label = f"v{version}"
updated = False
for lang in data.get("navigation", {}).get("languages", []):
versions = lang.get("versions", [])
if not versions:
continue
# Skip if this version already exists for this language
if any(v.get("version") == version_label for v in versions):
continue
# Find the current default and copy its tabs
default_version = next(
(v for v in versions if v.get("default")),
versions[0],
)
new_version = {
"version": version_label,
"default": True,
"tabs": default_version.get("tabs", []),
}
# Remove default flag from old default
default_version.pop("default", None)
# Insert new version at the beginning
versions.insert(0, new_version)
updated = True
if not updated:
return False
docs_json_path.write_text(json.dumps(data, indent=2, ensure_ascii=False) + "\n")
return True
_PT_BR_MONTHS = {
1: "jan",
2: "fev",
3: "mar",
4: "abr",
5: "mai",
6: "jun",
7: "jul",
8: "ago",
9: "set",
10: "out",
11: "nov",
12: "dez",
}
_CHANGELOG_LOCALES: dict[str, dict[str, str]] = {
"en": {
"link_text": "View release on GitHub",
"language_name": "English",
},
"pt-BR": {
"link_text": "Ver release no GitHub",
"language_name": "Brazilian Portuguese",
},
"ko": {
"link_text": "GitHub 릴리스 보기",
"language_name": "Korean",
},
}
def translate_release_notes(
release_notes: str,
lang: str,
client: OpenAI,
) -> str:
"""Translate release notes into the target language using OpenAI.
Args:
release_notes: English release notes markdown.
lang: Language code (e.g., "pt-BR", "ko").
client: OpenAI client instance.
Returns:
Translated release notes, or original on failure.
"""
locale_cfg = _CHANGELOG_LOCALES.get(lang)
if not locale_cfg:
return release_notes
language_name = locale_cfg["language_name"]
prompt = TRANSLATE_RELEASE_NOTES_PROMPT.substitute(
language=language_name,
release_notes=release_notes,
)
try:
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{
"role": "system",
"content": f"You are a professional translator. Translate technical documentation into {language_name}.",
},
{"role": "user", "content": prompt},
],
temperature=0.3,
)
return response.choices[0].message.content or release_notes
except Exception as e:
console.print(
f"[yellow]Warning:[/yellow] Could not translate to {language_name}: {e}"
)
return release_notes
def _format_changelog_date(lang: str) -> str:
"""Format today's date for a changelog entry in the given language."""
from datetime import datetime
now = datetime.now()
if lang == "ko":
return f"{now.year}{now.month}{now.day}"
if lang == "pt-BR":
return f"{now.day:02d} {_PT_BR_MONTHS[now.month]} {now.year}"
return now.strftime("%b %d, %Y")
def update_changelog(
changelog_path: Path,
version: str,
release_notes: str,
lang: str = "en",
) -> bool:
"""Prepend a new release entry to a docs changelog file.
Args:
changelog_path: Path to the changelog.mdx file.
version: Version string (e.g., "1.9.3").
release_notes: Markdown release notes content.
lang: Language code for localized date/link text.
Returns:
True if changelog was updated, False otherwise.
"""
if not changelog_path.exists():
return False
locale_cfg = _CHANGELOG_LOCALES.get(lang, _CHANGELOG_LOCALES["en"])
date_label = _format_changelog_date(lang)
link_text = locale_cfg["link_text"]
# Indent each non-empty line with 2 spaces to match <Update> block format
indented_lines = []
for line in release_notes.splitlines():
if line.strip():
indented_lines.append(f" {line}")
else:
indented_lines.append("")
indented_notes = "\n".join(indented_lines)
entry = (
f'<Update label="{date_label}">\n'
f" ## v{version}\n"
f"\n"
f" [{link_text}]"
f"(https://github.com/crewAIInc/crewAI/releases/tag/{version})\n"
f"\n"
f"{indented_notes}\n"
f"\n"
f"</Update>"
)
content = changelog_path.read_text()
# Insert after the frontmatter closing ---
parts = content.split("---", 2)
if len(parts) >= 3:
new_content = (
parts[0]
+ "---"
+ parts[1]
+ "---\n"
+ entry
+ "\n\n"
+ parts[2].lstrip("\n")
)
else:
new_content = entry + "\n\n" + content
changelog_path.write_text(new_content)
return True
def update_template_dependencies(templates_dir: Path, new_version: str) -> list[Path]:
"""Update crewai dependency versions in CLI template pyproject.toml files.
Handles both pinned (==) and minimum (>=) version specifiers,
as well as extras like [tools].
Args:
templates_dir: Path to the CLI templates directory.
new_version: New version string.
Returns:
List of paths that were updated.
"""
import re
updated = []
for pyproject in templates_dir.rglob("pyproject.toml"):
content = pyproject.read_text()
new_content = re.sub(
r'"crewai(\[tools\])?(==|>=)[^"]*"',
lambda m: f'"crewai{(m.group(1) or "")!s}=={new_version}"',
content,
)
if new_content != content:
pyproject.write_text(new_content)
updated.append(pyproject)
return updated
def find_version_files(base_path: Path) -> list[Path]:
"""Find all __init__.py files that contain __version__.
@@ -394,6 +636,22 @@ def bump(version: str, dry_run: bool, no_push: bool, no_commit: bool) -> None:
"[yellow]Warning:[/yellow] No __version__ attributes found to update"
)
# Update CLI template pyproject.toml files
templates_dir = lib_dir / "crewai" / "src" / "crewai" / "cli" / "templates"
if templates_dir.exists():
if dry_run:
for tpl in templates_dir.rglob("pyproject.toml"):
console.print(
f"[dim][DRY RUN][/dim] Would update template: {tpl.relative_to(cwd)}"
)
else:
tpl_updated = update_template_dependencies(templates_dir, version)
for tpl in tpl_updated:
console.print(
f"[green]✓[/green] Updated template: {tpl.relative_to(cwd)}"
)
updated_files.append(tpl)
if not dry_run:
console.print("\nSyncing workspace...")
run_command(["uv", "sync"])
@@ -575,9 +833,9 @@ def tag(dry_run: bool, no_edit: bool) -> None:
github_contributors = get_github_contributors(commit_range)
if commits.strip():
client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
if commits.strip():
contributors_section = ""
if github_contributors:
contributors_section = f"\n\n## Contributors\n\n{', '.join([f'@{u}' for u in github_contributors])}"
@@ -588,7 +846,7 @@ def tag(dry_run: bool, no_edit: bool) -> None:
contributors_section=contributors_section,
)
response = client.chat.completions.create(
response = openai_client.chat.completions.create(
model="gpt-4o-mini",
messages=[
{
@@ -643,6 +901,77 @@ def tag(dry_run: bool, no_edit: bool) -> None:
"\n[green]✓[/green] Using generated release notes without editing"
)
is_prerelease = any(
indicator in version.lower()
for indicator in ["a", "b", "rc", "alpha", "beta", "dev"]
)
# Update docs: changelogs + version switcher
docs_json_path = cwd / "docs" / "docs.json"
changelog_langs = ["en", "pt-BR", "ko"]
if not dry_run:
docs_files_staged = []
for lang in changelog_langs:
cl_path = cwd / "docs" / lang / "changelog.mdx"
if lang == "en":
notes_for_lang = release_notes
else:
console.print(f"[dim]Translating release notes to {lang}...[/dim]")
notes_for_lang = translate_release_notes(
release_notes, lang, openai_client
)
if update_changelog(cl_path, version, notes_for_lang, lang=lang):
console.print(
f"[green]✓[/green] Updated {cl_path.relative_to(cwd)}"
)
docs_files_staged.append(str(cl_path))
else:
console.print(
f"[yellow]Warning:[/yellow] Changelog not found at {cl_path.relative_to(cwd)}"
)
if not is_prerelease:
if add_docs_version(docs_json_path, version):
console.print(
f"[green]✓[/green] Added v{version} to docs version switcher"
)
docs_files_staged.append(str(docs_json_path))
else:
console.print(
f"[yellow]Warning:[/yellow] docs.json not found at {docs_json_path.relative_to(cwd)}"
)
if docs_files_staged:
for f in docs_files_staged:
run_command(["git", "add", f])
run_command(
[
"git",
"commit",
"-m",
f"docs: update changelog and version for v{version}",
]
)
console.print("[green]✓[/green] Committed docs updates")
run_command(["git", "push"])
console.print("[green]✓[/green] Pushed docs updates")
else:
for lang in changelog_langs:
cl_path = cwd / "docs" / lang / "changelog.mdx"
translated = " (translated)" if lang != "en" else ""
console.print(
f"[dim][DRY RUN][/dim] Would update {cl_path.relative_to(cwd)}{translated}"
)
if not is_prerelease:
console.print(
f"[dim][DRY RUN][/dim] Would add v{version} to docs version switcher"
)
else:
console.print(
"[dim][DRY RUN][/dim] Skipping docs version (pre-release)"
)
if not dry_run:
with console.status(f"[cyan]Creating tag {tag_name}..."):
try:
@@ -660,11 +989,6 @@ def tag(dry_run: bool, no_edit: bool) -> None:
sys.exit(1)
console.print(f"[green]✓[/green] Pushed tag {tag_name}")
is_prerelease = any(
indicator in version.lower()
for indicator in ["a", "b", "rc", "alpha", "beta", "dev"]
)
with console.status("[cyan]Creating GitHub Release..."):
try:
gh_cmd = [

View File

@@ -43,3 +43,18 @@ Instructions:
Keep it professional and clear."""
)
TRANSLATE_RELEASE_NOTES_PROMPT = Template(
"""Translate the following release notes into $language.
$release_notes
Instructions:
- Translate all section headers and descriptions naturally
- Keep markdown formatting (##, ###, -, etc.) exactly as-is
- Keep all proper nouns, code identifiers, class names, and technical terms unchanged
(e.g. "CrewAI", "LiteAgent", "ChromaDB", "MCP", "@username")
- Keep the ## Contributors section and GitHub usernames unchanged
- Do not add or remove any content, only translate"""
)

78
uv.lock generated
View File

@@ -1471,48 +1471,48 @@ provides-extras = ["apify", "beautifulsoup4", "bedrock", "browserbase", "composi
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version = "46.0.5"
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{ name = "cffi", marker = "platform_python_implementation != 'PyPy'" },
{ name = "typing-extensions", marker = "python_full_version < '3.11'" },
]
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