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549 Commits
1.0.0.a1
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gl/feat/wo
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|
|
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|
|
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|
|
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|
|
54e4554f49 |
2
.github/workflows/build-uv-cache.yml
vendored
2
.github/workflows/build-uv-cache.yml
vendored
@@ -33,7 +33,7 @@ jobs:
|
||||
- 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
|
||||
uv sync --all-groups --all-extras
|
||||
echo "Cache populated successfully"
|
||||
|
||||
- name: Save uv caches
|
||||
|
||||
4
.github/workflows/codeql.yml
vendored
4
.github/workflows/codeql.yml
vendored
@@ -15,11 +15,11 @@ on:
|
||||
push:
|
||||
branches: [ "main" ]
|
||||
paths-ignore:
|
||||
- "lib/crewai/src/crewai/cli/templates/**"
|
||||
- "src/crewai/cli/templates/**"
|
||||
pull_request:
|
||||
branches: [ "main" ]
|
||||
paths-ignore:
|
||||
- "lib/crewai/src/crewai/cli/templates/**"
|
||||
- "src/crewai/cli/templates/**"
|
||||
|
||||
jobs:
|
||||
analyze:
|
||||
|
||||
10
.github/workflows/linter.yml
vendored
10
.github/workflows/linter.yml
vendored
@@ -38,7 +38,7 @@ jobs:
|
||||
enable-cache: false
|
||||
|
||||
- name: Install dependencies
|
||||
run: uv sync --all-groups --all-extras --no-install-project
|
||||
run: uv sync --all-packages --all-extras --no-install-project
|
||||
|
||||
- name: Get Changed Python Files
|
||||
id: changed-files
|
||||
@@ -52,10 +52,10 @@ jobs:
|
||||
- name: Run Ruff on Changed Files
|
||||
if: ${{ steps.changed-files.outputs.files != '' }}
|
||||
run: |
|
||||
echo "${{ steps.changed-files.outputs.files }}" \
|
||||
| tr ' ' '\n' \
|
||||
| grep -v 'src/crewai/cli/templates/' \
|
||||
| xargs -I{} uv run ruff check "{}"
|
||||
echo "${{ steps.changed-files.outputs.files }}" \
|
||||
| tr ' ' '\n' \
|
||||
| grep -v 'src/crewai/cli/templates/' \
|
||||
| xargs -I{} uv run ruff check "{}"
|
||||
|
||||
- name: Save uv caches
|
||||
if: steps.cache-restore.outputs.cache-hit != 'true'
|
||||
|
||||
71
.github/workflows/publish.yml
vendored
71
.github/workflows/publish.yml
vendored
@@ -1,71 +0,0 @@
|
||||
name: Publish to PyPI
|
||||
|
||||
on:
|
||||
release:
|
||||
types: [ published ]
|
||||
workflow_dispatch:
|
||||
|
||||
jobs:
|
||||
build:
|
||||
if: github.event.release.prerelease == true
|
||||
name: Build packages
|
||||
runs-on: ubuntu-latest
|
||||
permissions:
|
||||
contents: read
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Set up Python
|
||||
uses: actions/setup-python@v5
|
||||
with:
|
||||
python-version: "3.12"
|
||||
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v4
|
||||
|
||||
- name: Build packages
|
||||
run: |
|
||||
uv build --all-packages
|
||||
rm dist/.gitignore
|
||||
|
||||
- name: Upload artifacts
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: dist
|
||||
path: dist/
|
||||
|
||||
publish:
|
||||
if: github.event.release.prerelease == true
|
||||
name: Publish to PyPI
|
||||
needs: build
|
||||
runs-on: ubuntu-latest
|
||||
environment:
|
||||
name: pypi
|
||||
url: https://pypi.org/p/crewai
|
||||
permissions:
|
||||
id-token: write
|
||||
contents: read
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v6
|
||||
with:
|
||||
version: "0.8.4"
|
||||
python-version: "3.12"
|
||||
enable-cache: false
|
||||
|
||||
- name: Download artifacts
|
||||
uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: dist
|
||||
path: dist
|
||||
|
||||
- name: Publish to PyPI
|
||||
env:
|
||||
UV_PUBLISH_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
|
||||
run: |
|
||||
for package in dist/*; do
|
||||
echo "Publishing $package"
|
||||
uv publish "$package"
|
||||
done
|
||||
80
.github/workflows/tests.yml
vendored
80
.github/workflows/tests.yml
vendored
@@ -8,14 +8,6 @@ permissions:
|
||||
env:
|
||||
OPENAI_API_KEY: fake-api-key
|
||||
PYTHONUNBUFFERED: 1
|
||||
BRAVE_API_KEY: fake-brave-key
|
||||
SNOWFLAKE_USER: fake-snowflake-user
|
||||
SNOWFLAKE_PASSWORD: fake-snowflake-password
|
||||
SNOWFLAKE_ACCOUNT: fake-snowflake-account
|
||||
SNOWFLAKE_WAREHOUSE: fake-snowflake-warehouse
|
||||
SNOWFLAKE_DATABASE: fake-snowflake-database
|
||||
SNOWFLAKE_SCHEMA: fake-snowflake-schema
|
||||
EMBEDCHAIN_DB_URI: sqlite:///test.db
|
||||
|
||||
jobs:
|
||||
tests:
|
||||
@@ -33,17 +25,17 @@ 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${{ matrix.python-version }}-
|
||||
# - name: Restore global uv cache
|
||||
# id: cache-restore
|
||||
# uses: actions/cache/restore@v4
|
||||
# with:
|
||||
# path: |
|
||||
# ~/.cache/uv
|
||||
# ~/.local/share/uv
|
||||
# .venv
|
||||
# key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
|
||||
# restore-keys: |
|
||||
# uv-main-py${{ matrix.python-version }}-
|
||||
|
||||
- name: Install uv
|
||||
uses: astral-sh/setup-uv@v6
|
||||
@@ -53,18 +45,18 @@ jobs:
|
||||
enable-cache: false
|
||||
|
||||
- name: Install the project
|
||||
run: uv sync --all-groups --all-extras
|
||||
run: uv sync --all-packages --all-extras
|
||||
|
||||
- name: Restore test durations
|
||||
uses: actions/cache/restore@v4
|
||||
with:
|
||||
path: .test_durations_py*
|
||||
key: test-durations-py${{ matrix.python-version }}
|
||||
# - name: Restore test durations
|
||||
# uses: actions/cache/restore@v4
|
||||
# with:
|
||||
# path: .test_durations_py*
|
||||
# key: test-durations-py${{ matrix.python-version }}
|
||||
|
||||
- name: Run tests (group ${{ matrix.group }} of 8)
|
||||
run: |
|
||||
PYTHON_VERSION_SAFE=$(echo "${{ matrix.python-version }}" | tr '.' '_')
|
||||
DURATION_FILE="../../.test_durations_py${PYTHON_VERSION_SAFE}"
|
||||
DURATION_FILE=".test_durations_py${PYTHON_VERSION_SAFE}"
|
||||
|
||||
# Temporarily always skip cached durations to fix test splitting
|
||||
# When durations don't match, pytest-split runs duplicate tests instead of splitting
|
||||
@@ -83,7 +75,7 @@ jobs:
|
||||
# DURATIONS_ARG="--durations-path=${DURATION_FILE}"
|
||||
# fi
|
||||
|
||||
cd lib/crewai && uv run pytest \
|
||||
uv run pytest lib/crewai \
|
||||
--block-network \
|
||||
--timeout=30 \
|
||||
-vv \
|
||||
@@ -92,27 +84,15 @@ jobs:
|
||||
$DURATIONS_ARG \
|
||||
--durations=10 \
|
||||
-n auto \
|
||||
--maxfail=3
|
||||
--maxfail=3 \
|
||||
-m "not requires_local_services"
|
||||
|
||||
- name: Run tool tests (group ${{ matrix.group }} of 8)
|
||||
run: |
|
||||
cd lib/crewai-tools && uv run pytest \
|
||||
--block-network \
|
||||
--timeout=30 \
|
||||
-vv \
|
||||
--splits 8 \
|
||||
--group ${{ matrix.group }} \
|
||||
--durations=10 \
|
||||
-n auto \
|
||||
--maxfail=3
|
||||
|
||||
|
||||
- name: Save uv caches
|
||||
if: steps.cache-restore.outputs.cache-hit != 'true'
|
||||
uses: actions/cache/save@v4
|
||||
with:
|
||||
path: |
|
||||
~/.cache/uv
|
||||
~/.local/share/uv
|
||||
.venv
|
||||
key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
|
||||
# - name: Save uv caches
|
||||
# if: steps.cache-restore.outputs.cache-hit != 'true'
|
||||
# uses: actions/cache/save@v4
|
||||
# with:
|
||||
# path: |
|
||||
# ~/.cache/uv
|
||||
# ~/.local/share/uv
|
||||
# .venv
|
||||
# key: uv-main-py${{ matrix.python-version }}-${{ hashFiles('uv.lock') }}
|
||||
|
||||
2
.github/workflows/type-checker.yml
vendored
2
.github/workflows/type-checker.yml
vendored
@@ -40,7 +40,7 @@ jobs:
|
||||
enable-cache: false
|
||||
|
||||
- name: Install dependencies
|
||||
run: uv sync --all-groups --all-extras
|
||||
run: uv sync --all-packages --all-extras
|
||||
|
||||
- name: Get changed Python files
|
||||
id: changed-files
|
||||
|
||||
@@ -6,16 +6,19 @@ repos:
|
||||
entry: uv run ruff check
|
||||
language: system
|
||||
types: [python]
|
||||
files: ^lib/crewai/src/
|
||||
exclude: ^lib/crewai/
|
||||
- id: ruff-format
|
||||
name: ruff-format
|
||||
entry: uv run ruff format
|
||||
language: system
|
||||
types: [python]
|
||||
files: ^lib/crewai/src/
|
||||
exclude: ^lib/crewai/
|
||||
- id: mypy
|
||||
name: mypy
|
||||
entry: uv run mypy
|
||||
language: system
|
||||
types: [python]
|
||||
files: ^lib/crewai/src/
|
||||
exclude: ^lib/crewai/
|
||||
|
||||
BIN
assets/crew_only_logo.png
Normal file
BIN
assets/crew_only_logo.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 14 KiB |
BIN
assets/crewai_logo.png
Normal file
BIN
assets/crewai_logo.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 14 KiB |
@@ -1,335 +0,0 @@
|
||||
## Building CrewAI Tools
|
||||
|
||||
This guide shows you how to build high‑quality CrewAI tools that match the patterns in this repository and are ready to be merged. It focuses on: architecture, conventions, environment variables, dependencies, testing, documentation, and a complete example.
|
||||
|
||||
### Who this is for
|
||||
- Contributors creating new tools under `crewai_tools/tools/*`
|
||||
- Maintainers reviewing PRs for consistency and DX
|
||||
|
||||
---
|
||||
|
||||
## Quick‑start checklist
|
||||
1. Create a new folder under `crewai_tools/tools/<your_tool_name>/` with a `README.md` and a `<your_tool_name>.py`.
|
||||
2. Implement a class that ends with `Tool` and subclasses `BaseTool` (or `RagTool` when appropriate).
|
||||
3. Define a Pydantic `args_schema` with explicit field descriptions and validation.
|
||||
4. Declare `env_vars` and `package_dependencies` in the class when needed.
|
||||
5. Lazily initialize clients in `__init__` or `_run` and handle missing credentials with clear errors.
|
||||
6. Implement `_run(...) -> str | dict` and, if needed, `_arun(...)`.
|
||||
7. Add tests under `tests/tools/` (unit, no real network calls; mock or record safely).
|
||||
8. Add a concise tool `README.md` with usage and required env vars.
|
||||
9. If you add optional dependencies, register them in `pyproject.toml` under `[project.optional-dependencies]` and reference that extra in your tool docs.
|
||||
10. Run `uv run pytest` and `pre-commit run -a` locally; ensure green.
|
||||
|
||||
---
|
||||
|
||||
## Tool anatomy and conventions
|
||||
|
||||
### BaseTool pattern
|
||||
All tools follow this structure:
|
||||
|
||||
```python
|
||||
from typing import Any, List, Optional, Type
|
||||
|
||||
import os
|
||||
from pydantic import BaseModel, Field
|
||||
from crewai.tools import BaseTool, EnvVar
|
||||
|
||||
|
||||
class MyToolInput(BaseModel):
|
||||
"""Input schema for MyTool."""
|
||||
query: str = Field(..., description="Your input description here")
|
||||
limit: int = Field(5, ge=1, le=50, description="Max items to return")
|
||||
|
||||
|
||||
class MyTool(BaseTool):
|
||||
name: str = "My Tool"
|
||||
description: str = "Explain succinctly what this tool does and when to use it."
|
||||
args_schema: Type[BaseModel] = MyToolInput
|
||||
|
||||
# Only include when applicable
|
||||
env_vars: List[EnvVar] = [
|
||||
EnvVar(name="MY_API_KEY", description="API key for My service", required=True),
|
||||
]
|
||||
package_dependencies: List[str] = ["my-sdk"]
|
||||
|
||||
def __init__(self, **kwargs: Any) -> None:
|
||||
super().__init__(**kwargs)
|
||||
# Lazy import to keep base install light
|
||||
try:
|
||||
import my_sdk # noqa: F401
|
||||
except Exception as exc:
|
||||
raise ImportError(
|
||||
"Missing optional dependency 'my-sdk'. Install with: \n"
|
||||
" uv add crewai-tools --extra my-sdk\n"
|
||||
"or\n"
|
||||
" pip install my-sdk\n"
|
||||
) from exc
|
||||
|
||||
if "MY_API_KEY" not in os.environ:
|
||||
raise ValueError("Environment variable MY_API_KEY is required for MyTool")
|
||||
|
||||
def _run(self, query: str, limit: int = 5, **_: Any) -> str:
|
||||
"""Synchronous execution. Return a concise string or JSON string."""
|
||||
# Implement your logic here; do not print. Return the content.
|
||||
# Handle errors gracefully, return clear messages.
|
||||
return f"Processed {query} with limit={limit}"
|
||||
|
||||
async def _arun(self, *args: Any, **kwargs: Any) -> str:
|
||||
"""Optional async counterpart if your client supports it."""
|
||||
# Prefer delegating to _run when the client is thread-safe
|
||||
return self._run(*args, **kwargs)
|
||||
```
|
||||
|
||||
Key points:
|
||||
- Class name must end with `Tool` to be auto‑discovered by our tooling.
|
||||
- Use `args_schema` for inputs; always include `description` and validation.
|
||||
- Validate env vars early and fail with actionable errors.
|
||||
- Keep outputs deterministic and compact; favor `str` (possibly JSON‑encoded) or small dicts converted to strings.
|
||||
- Avoid printing; return the final string.
|
||||
|
||||
### Error handling
|
||||
- Wrap network and I/O with try/except and return a helpful message. See `BraveSearchTool` and others for patterns.
|
||||
- Validate required inputs and environment configuration with clear messages.
|
||||
- Keep exceptions user‑friendly; do not leak stack traces.
|
||||
|
||||
### Rate limiting and retries
|
||||
- If the upstream API enforces request pacing, implement minimal rate limiting (see `BraveSearchTool`).
|
||||
- Consider idempotency and backoff for transient errors where appropriate.
|
||||
|
||||
### Async support
|
||||
- Implement `_arun` only if your library has a true async client or your sync calls are thread‑safe.
|
||||
- Otherwise, delegate `_arun` to `_run` as in multiple existing tools.
|
||||
|
||||
### Returning values
|
||||
- Return a string (or JSON string) that’s ready to display in an agent transcript.
|
||||
- If returning structured data, keep it small and human‑readable. Use stable keys and ordering.
|
||||
|
||||
---
|
||||
|
||||
## RAG tools and adapters
|
||||
|
||||
If your tool is a knowledge source, consider extending `RagTool` and/or creating an adapter.
|
||||
|
||||
- `RagTool` exposes `add(...)` and a `query(question: str) -> str` contract through an `Adapter`.
|
||||
- See `crewai_tools/tools/rag/rag_tool.py` and adapters like `embedchain_adapter.py` and `lancedb_adapter.py`.
|
||||
|
||||
Minimal adapter example:
|
||||
|
||||
```python
|
||||
from typing import Any
|
||||
from pydantic import BaseModel
|
||||
from crewai_tools.tools.rag.rag_tool import Adapter, RagTool
|
||||
|
||||
|
||||
class MemoryAdapter(Adapter):
|
||||
store: list[str] = []
|
||||
|
||||
def add(self, text: str, **_: Any) -> None:
|
||||
self.store.append(text)
|
||||
|
||||
def query(self, question: str) -> str:
|
||||
# naive demo: return all text containing any word from the question
|
||||
tokens = set(question.lower().split())
|
||||
hits = [t for t in self.store if tokens & set(t.lower().split())]
|
||||
return "\n".join(hits) if hits else "No relevant content found."
|
||||
|
||||
|
||||
class MemoryRagTool(RagTool):
|
||||
name: str = "In‑memory RAG"
|
||||
description: str = "Toy RAG that stores text in memory and returns matches."
|
||||
adapter: Adapter = MemoryAdapter()
|
||||
```
|
||||
|
||||
When using external vector DBs (MongoDB, Qdrant, Weaviate), study the existing tools to follow indexing, embedding, and query configuration patterns closely.
|
||||
|
||||
---
|
||||
|
||||
## Toolkits (multiple related tools)
|
||||
|
||||
Some integrations expose a toolkit (a group of tools) rather than a single class. See Bedrock `browser_toolkit.py` and `code_interpreter_toolkit.py`.
|
||||
|
||||
Guidelines:
|
||||
- Provide small, focused `BaseTool` classes for each operation (e.g., `navigate`, `click`, `extract_text`).
|
||||
- Offer a helper `create_<name>_toolkit(...) -> Tuple[ToolkitClass, List[BaseTool]]` to create tools and manage resources.
|
||||
- If you open external resources (browsers, interpreters), support cleanup methods and optionally context manager usage.
|
||||
|
||||
---
|
||||
|
||||
## Environment variables and dependencies
|
||||
|
||||
### env_vars
|
||||
- Declare as `env_vars: List[EnvVar]` with `name`, `description`, `required`, and optional `default`.
|
||||
- Validate presence in `__init__` or on first `_run` call.
|
||||
|
||||
### Dependencies
|
||||
- List runtime packages in `package_dependencies` on the class.
|
||||
- If they are genuinely optional, add an extra under `[project.optional-dependencies]` in `pyproject.toml` (e.g., `tavily-python`, `serpapi`, `scrapfly-sdk`).
|
||||
- Use lazy imports to avoid hard deps for users who don’t need the tool.
|
||||
|
||||
---
|
||||
|
||||
## Testing
|
||||
|
||||
Place tests under `tests/tools/` and follow these rules:
|
||||
- Do not hit real external services in CI. Use mocks, fakes, or recorded fixtures where allowed.
|
||||
- Validate input validation, env var handling, error messages, and happy path output formatting.
|
||||
- Keep tests fast and deterministic.
|
||||
|
||||
Example skeleton (`tests/tools/my_tool_test.py`):
|
||||
|
||||
```python
|
||||
import os
|
||||
import pytest
|
||||
from crewai_tools.tools.my_tool.my_tool import MyTool
|
||||
|
||||
|
||||
def test_requires_env_var(monkeypatch):
|
||||
monkeypatch.delenv("MY_API_KEY", raising=False)
|
||||
with pytest.raises(ValueError):
|
||||
MyTool()
|
||||
|
||||
|
||||
def test_happy_path(monkeypatch):
|
||||
monkeypatch.setenv("MY_API_KEY", "test")
|
||||
tool = MyTool()
|
||||
result = tool.run(query="hello", limit=2)
|
||||
assert "hello" in result
|
||||
```
|
||||
|
||||
Run locally:
|
||||
|
||||
```bash
|
||||
uv run pytest
|
||||
pre-commit run -a
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Documentation
|
||||
|
||||
Each tool must include a `README.md` in its folder with:
|
||||
- What it does and when to use it
|
||||
- Required env vars and optional extras (with install snippet)
|
||||
- Minimal usage example
|
||||
|
||||
Update the root `README.md` only if the tool introduces a new category or notable capability.
|
||||
|
||||
---
|
||||
|
||||
## Discovery and specs
|
||||
|
||||
Our internal tooling discovers classes whose names end with `Tool`. Keep your class exported from the module path under `crewai_tools/tools/...` to be picked up by scripts like `generate_tool_specs.py`.
|
||||
|
||||
---
|
||||
|
||||
## Full example: “Weather Search Tool”
|
||||
|
||||
This example demonstrates: `args_schema`, `env_vars`, `package_dependencies`, lazy imports, validation, and robust error handling.
|
||||
|
||||
```python
|
||||
# file: crewai_tools/tools/weather_tool/weather_tool.py
|
||||
from typing import Any, List, Optional, Type
|
||||
import os
|
||||
import requests
|
||||
from pydantic import BaseModel, Field
|
||||
from crewai.tools import BaseTool, EnvVar
|
||||
|
||||
|
||||
class WeatherToolInput(BaseModel):
|
||||
"""Input schema for WeatherTool."""
|
||||
city: str = Field(..., description="City name, e.g., 'Berlin'")
|
||||
country: Optional[str] = Field(None, description="ISO country code, e.g., 'DE'")
|
||||
units: str = Field(
|
||||
default="metric",
|
||||
description="Units system: 'metric' or 'imperial'",
|
||||
pattern=r"^(metric|imperial)$",
|
||||
)
|
||||
|
||||
|
||||
class WeatherTool(BaseTool):
|
||||
name: str = "Weather Search"
|
||||
description: str = (
|
||||
"Look up current weather for a city using a public weather API."
|
||||
)
|
||||
args_schema: Type[BaseModel] = WeatherToolInput
|
||||
|
||||
env_vars: List[EnvVar] = [
|
||||
EnvVar(
|
||||
name="WEATHER_API_KEY",
|
||||
description="API key for the weather service",
|
||||
required=True,
|
||||
),
|
||||
]
|
||||
package_dependencies: List[str] = ["requests"]
|
||||
|
||||
base_url: str = "https://api.openweathermap.org/data/2.5/weather"
|
||||
|
||||
def __init__(self, **kwargs: Any) -> None:
|
||||
super().__init__(**kwargs)
|
||||
if "WEATHER_API_KEY" not in os.environ:
|
||||
raise ValueError("WEATHER_API_KEY is required for WeatherTool")
|
||||
|
||||
def _run(self, city: str, country: Optional[str] = None, units: str = "metric") -> str:
|
||||
try:
|
||||
q = f"{city},{country}" if country else city
|
||||
params = {
|
||||
"q": q,
|
||||
"units": units,
|
||||
"appid": os.environ["WEATHER_API_KEY"],
|
||||
}
|
||||
resp = requests.get(self.base_url, params=params, timeout=10)
|
||||
resp.raise_for_status()
|
||||
data = resp.json()
|
||||
|
||||
main = data.get("weather", [{}])[0].get("main", "Unknown")
|
||||
desc = data.get("weather", [{}])[0].get("description", "")
|
||||
temp = data.get("main", {}).get("temp")
|
||||
feels = data.get("main", {}).get("feels_like")
|
||||
city_name = data.get("name", city)
|
||||
|
||||
return (
|
||||
f"Weather in {city_name}: {main} ({desc}). "
|
||||
f"Temperature: {temp}°, feels like {feels}°."
|
||||
)
|
||||
except requests.Timeout:
|
||||
return "Weather service timed out. Please try again later."
|
||||
except requests.HTTPError as e:
|
||||
return f"Weather service error: {e.response.status_code} {e.response.text[:120]}"
|
||||
except Exception as e:
|
||||
return f"Unexpected error fetching weather: {e}"
|
||||
```
|
||||
|
||||
Folder layout:
|
||||
|
||||
```
|
||||
crewai_tools/tools/weather_tool/
|
||||
├─ weather_tool.py
|
||||
└─ README.md
|
||||
```
|
||||
|
||||
And `README.md` should document env vars and usage.
|
||||
|
||||
---
|
||||
|
||||
## PR checklist
|
||||
- [ ] Tool lives under `crewai_tools/tools/<name>/`
|
||||
- [ ] Class ends with `Tool` and subclasses `BaseTool` (or `RagTool`)
|
||||
- [ ] Precise `args_schema` with descriptions and validation
|
||||
- [ ] `env_vars` declared (if any) and validated
|
||||
- [ ] `package_dependencies` and optional extras added in `pyproject.toml` (if any)
|
||||
- [ ] Clear error handling; no prints
|
||||
- [ ] Unit tests added (`tests/tools/`), fast and deterministic
|
||||
- [ ] Tool `README.md` with usage and env vars
|
||||
- [ ] `pre-commit` and `pytest` pass locally
|
||||
|
||||
---
|
||||
|
||||
## Tips for great DX
|
||||
- Keep responses short and useful—agents quote your tool output directly.
|
||||
- Validate early; fail fast with actionable guidance.
|
||||
- Prefer lazy imports; minimize default install surface.
|
||||
- Mirror patterns from similar tools in this repo for a consistent developer experience.
|
||||
|
||||
Happy building!
|
||||
|
||||
|
||||
@@ -1,155 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
|
||||
import inspect
|
||||
import json
|
||||
from pathlib import Path
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from crewai.tools.base_tool import BaseTool, EnvVar
|
||||
from crewai_tools import tools
|
||||
from pydantic.json_schema import GenerateJsonSchema
|
||||
from pydantic_core import PydanticOmit
|
||||
|
||||
|
||||
class SchemaGenerator(GenerateJsonSchema):
|
||||
def handle_invalid_for_json_schema(self, schema, error_info):
|
||||
raise PydanticOmit
|
||||
|
||||
|
||||
class ToolSpecExtractor:
|
||||
def __init__(self) -> None:
|
||||
self.tools_spec: List[Dict[str, Any]] = []
|
||||
self.processed_tools: set[str] = set()
|
||||
|
||||
def extract_all_tools(self) -> List[Dict[str, Any]]:
|
||||
for name in dir(tools):
|
||||
if name.endswith("Tool") and name not in self.processed_tools:
|
||||
obj = getattr(tools, name, None)
|
||||
if inspect.isclass(obj):
|
||||
self.extract_tool_info(obj)
|
||||
self.processed_tools.add(name)
|
||||
return self.tools_spec
|
||||
|
||||
def extract_tool_info(self, tool_class: BaseTool) -> None:
|
||||
try:
|
||||
core_schema = tool_class.__pydantic_core_schema__
|
||||
if not core_schema:
|
||||
return
|
||||
|
||||
schema = self._unwrap_schema(core_schema)
|
||||
fields = schema.get("schema", {}).get("fields", {})
|
||||
|
||||
tool_info = {
|
||||
"name": tool_class.__name__,
|
||||
"humanized_name": self._extract_field_default(
|
||||
fields.get("name"), fallback=tool_class.__name__
|
||||
),
|
||||
"description": self._extract_field_default(
|
||||
fields.get("description")
|
||||
).strip(),
|
||||
"run_params_schema": self._extract_params(fields.get("args_schema")),
|
||||
"init_params_schema": self._extract_init_params(tool_class),
|
||||
"env_vars": self._extract_env_vars(fields.get("env_vars")),
|
||||
"package_dependencies": self._extract_field_default(
|
||||
fields.get("package_dependencies"), fallback=[]
|
||||
),
|
||||
}
|
||||
|
||||
self.tools_spec.append(tool_info)
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error extracting {tool_class.__name__}: {e}")
|
||||
|
||||
def _unwrap_schema(self, schema: Dict) -> Dict:
|
||||
while (
|
||||
schema.get("type") in {"function-after", "default"} and "schema" in schema
|
||||
):
|
||||
schema = schema["schema"]
|
||||
return schema
|
||||
|
||||
def _extract_field_default(self, field: Optional[Dict], fallback: str = "") -> str:
|
||||
if not field:
|
||||
return fallback
|
||||
|
||||
schema = field.get("schema", {})
|
||||
default = schema.get("default")
|
||||
return default if isinstance(default, (list, str, int)) else fallback
|
||||
|
||||
def _extract_params(
|
||||
self, args_schema_field: Optional[Dict]
|
||||
) -> List[Dict[str, str]]:
|
||||
if not args_schema_field:
|
||||
return {}
|
||||
|
||||
args_schema_class = args_schema_field.get("schema", {}).get("default")
|
||||
if not (
|
||||
inspect.isclass(args_schema_class)
|
||||
and hasattr(args_schema_class, "__pydantic_core_schema__")
|
||||
):
|
||||
return {}
|
||||
|
||||
try:
|
||||
return args_schema_class.model_json_schema(
|
||||
schema_generator=SchemaGenerator, mode="validation"
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"Error extracting params from {args_schema_class}: {e}")
|
||||
return {}
|
||||
|
||||
def _extract_env_vars(self, env_vars_field: Optional[Dict]) -> List[Dict[str, str]]:
|
||||
if not env_vars_field:
|
||||
return []
|
||||
|
||||
env_vars = []
|
||||
for env_var in env_vars_field.get("schema", {}).get("default", []):
|
||||
if isinstance(env_var, EnvVar):
|
||||
env_vars.append(
|
||||
{
|
||||
"name": env_var.name,
|
||||
"description": env_var.description,
|
||||
"required": env_var.required,
|
||||
"default": env_var.default,
|
||||
}
|
||||
)
|
||||
return env_vars
|
||||
|
||||
def _extract_init_params(self, tool_class: BaseTool) -> dict:
|
||||
ignored_init_params = [
|
||||
"name",
|
||||
"description",
|
||||
"env_vars",
|
||||
"args_schema",
|
||||
"description_updated",
|
||||
"cache_function",
|
||||
"result_as_answer",
|
||||
"max_usage_count",
|
||||
"current_usage_count",
|
||||
"package_dependencies",
|
||||
]
|
||||
|
||||
json_schema = tool_class.model_json_schema(
|
||||
schema_generator=SchemaGenerator, mode="serialization"
|
||||
)
|
||||
|
||||
properties = {}
|
||||
for key, value in json_schema["properties"].items():
|
||||
if key not in ignored_init_params:
|
||||
properties[key] = value
|
||||
|
||||
json_schema["properties"] = properties
|
||||
return json_schema
|
||||
|
||||
def save_to_json(self, output_path: str) -> None:
|
||||
with open(output_path, "w", encoding="utf-8") as f:
|
||||
json.dump({"tools": self.tools_spec}, f, indent=2, sort_keys=True)
|
||||
print(f"Saved tool specs to {output_path}")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
output_file = Path(__file__).parent / "tool.specs.json"
|
||||
extractor = ToolSpecExtractor()
|
||||
|
||||
specs = extractor.extract_all_tools()
|
||||
extractor.save_to_json(str(output_file))
|
||||
|
||||
print(f"Extracted {len(specs)} tool classes.")
|
||||
@@ -1,7 +0,0 @@
|
||||
from .code_interpreter_toolkit import (
|
||||
CodeInterpreterToolkit,
|
||||
create_code_interpreter_toolkit,
|
||||
)
|
||||
|
||||
|
||||
__all__ = ["CodeInterpreterToolkit", "create_code_interpreter_toolkit"]
|
||||
@@ -1,68 +0,0 @@
|
||||
from typing import List, Optional
|
||||
|
||||
from crewai_tools.rag.chunkers.base_chunker import BaseChunker
|
||||
|
||||
|
||||
class CsvChunker(BaseChunker):
|
||||
def __init__(
|
||||
self,
|
||||
chunk_size: int = 1200,
|
||||
chunk_overlap: int = 100,
|
||||
separators: Optional[List[str]] = None,
|
||||
keep_separator: bool = True,
|
||||
):
|
||||
if separators is None:
|
||||
separators = [
|
||||
"\nRow ", # Row boundaries (from CSVLoader format)
|
||||
"\n", # Line breaks
|
||||
" | ", # Column separators
|
||||
", ", # Comma separators
|
||||
" ", # Word breaks
|
||||
"", # Character level
|
||||
]
|
||||
super().__init__(chunk_size, chunk_overlap, separators, keep_separator)
|
||||
|
||||
|
||||
class JsonChunker(BaseChunker):
|
||||
def __init__(
|
||||
self,
|
||||
chunk_size: int = 2000,
|
||||
chunk_overlap: int = 200,
|
||||
separators: Optional[List[str]] = None,
|
||||
keep_separator: bool = True,
|
||||
):
|
||||
if separators is None:
|
||||
separators = [
|
||||
"\n\n", # Object/array boundaries
|
||||
"\n", # Line breaks
|
||||
"},", # Object endings
|
||||
"],", # Array endings
|
||||
", ", # Property separators
|
||||
": ", # Key-value separators
|
||||
" ", # Word breaks
|
||||
"", # Character level
|
||||
]
|
||||
super().__init__(chunk_size, chunk_overlap, separators, keep_separator)
|
||||
|
||||
|
||||
class XmlChunker(BaseChunker):
|
||||
def __init__(
|
||||
self,
|
||||
chunk_size: int = 2500,
|
||||
chunk_overlap: int = 250,
|
||||
separators: Optional[List[str]] = None,
|
||||
keep_separator: bool = True,
|
||||
):
|
||||
if separators is None:
|
||||
separators = [
|
||||
"\n\n", # Element boundaries
|
||||
"\n", # Line breaks
|
||||
">", # Tag endings
|
||||
". ", # Sentence endings (for text content)
|
||||
"! ", # Exclamation endings
|
||||
"? ", # Question endings
|
||||
", ", # Comma separators
|
||||
" ", # Word breaks
|
||||
"", # Character level
|
||||
]
|
||||
super().__init__(chunk_size, chunk_overlap, separators, keep_separator)
|
||||
@@ -1,78 +0,0 @@
|
||||
from typing import List, Optional
|
||||
|
||||
from crewai_tools.rag.chunkers.base_chunker import BaseChunker
|
||||
|
||||
|
||||
class TextChunker(BaseChunker):
|
||||
def __init__(
|
||||
self,
|
||||
chunk_size: int = 1500,
|
||||
chunk_overlap: int = 150,
|
||||
separators: Optional[List[str]] = None,
|
||||
keep_separator: bool = True,
|
||||
):
|
||||
if separators is None:
|
||||
separators = [
|
||||
"\n\n\n", # Multiple line breaks (sections)
|
||||
"\n\n", # Paragraph breaks
|
||||
"\n", # Line breaks
|
||||
". ", # Sentence endings
|
||||
"! ", # Exclamation endings
|
||||
"? ", # Question endings
|
||||
"; ", # Semicolon breaks
|
||||
", ", # Comma breaks
|
||||
" ", # Word breaks
|
||||
"", # Character level
|
||||
]
|
||||
super().__init__(chunk_size, chunk_overlap, separators, keep_separator)
|
||||
|
||||
|
||||
class DocxChunker(BaseChunker):
|
||||
def __init__(
|
||||
self,
|
||||
chunk_size: int = 2500,
|
||||
chunk_overlap: int = 250,
|
||||
separators: Optional[List[str]] = None,
|
||||
keep_separator: bool = True,
|
||||
):
|
||||
if separators is None:
|
||||
separators = [
|
||||
"\n\n\n", # Multiple line breaks (major sections)
|
||||
"\n\n", # Paragraph breaks
|
||||
"\n", # Line breaks
|
||||
". ", # Sentence endings
|
||||
"! ", # Exclamation endings
|
||||
"? ", # Question endings
|
||||
"; ", # Semicolon breaks
|
||||
", ", # Comma breaks
|
||||
" ", # Word breaks
|
||||
"", # Character level
|
||||
]
|
||||
super().__init__(chunk_size, chunk_overlap, separators, keep_separator)
|
||||
|
||||
|
||||
class MdxChunker(BaseChunker):
|
||||
def __init__(
|
||||
self,
|
||||
chunk_size: int = 3000,
|
||||
chunk_overlap: int = 300,
|
||||
separators: Optional[List[str]] = None,
|
||||
keep_separator: bool = True,
|
||||
):
|
||||
if separators is None:
|
||||
separators = [
|
||||
"\n## ", # H2 headers (major sections)
|
||||
"\n### ", # H3 headers (subsections)
|
||||
"\n#### ", # H4 headers (sub-subsections)
|
||||
"\n\n", # Paragraph breaks
|
||||
"\n```", # Code block boundaries
|
||||
"\n", # Line breaks
|
||||
". ", # Sentence endings
|
||||
"! ", # Exclamation endings
|
||||
"? ", # Question endings
|
||||
"; ", # Semicolon breaks
|
||||
", ", # Comma breaks
|
||||
" ", # Word breaks
|
||||
"", # Character level
|
||||
]
|
||||
super().__init__(chunk_size, chunk_overlap, separators, keep_separator)
|
||||
@@ -1,27 +0,0 @@
|
||||
from typing import List, Optional
|
||||
|
||||
from crewai_tools.rag.chunkers.base_chunker import BaseChunker
|
||||
|
||||
|
||||
class WebsiteChunker(BaseChunker):
|
||||
def __init__(
|
||||
self,
|
||||
chunk_size: int = 2500,
|
||||
chunk_overlap: int = 250,
|
||||
separators: Optional[List[str]] = None,
|
||||
keep_separator: bool = True,
|
||||
):
|
||||
if separators is None:
|
||||
separators = [
|
||||
"\n\n\n", # Major section breaks
|
||||
"\n\n", # Paragraph breaks
|
||||
"\n", # Line breaks
|
||||
". ", # Sentence endings
|
||||
"! ", # Exclamation endings
|
||||
"? ", # Question endings
|
||||
"; ", # Semicolon breaks
|
||||
", ", # Comma breaks
|
||||
" ", # Word breaks
|
||||
"", # Character level
|
||||
]
|
||||
super().__init__(chunk_size, chunk_overlap, separators, keep_separator)
|
||||
@@ -1,135 +0,0 @@
|
||||
import os
|
||||
import tarfile
|
||||
from typing import Optional, Type
|
||||
import zipfile
|
||||
|
||||
from crewai.tools import BaseTool
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
class FileCompressorToolInput(BaseModel):
|
||||
"""Input schema for FileCompressorTool."""
|
||||
|
||||
input_path: str = Field(
|
||||
..., description="Path to the file or directory to compress."
|
||||
)
|
||||
output_path: Optional[str] = Field(
|
||||
default=None, description="Optional output archive filename."
|
||||
)
|
||||
overwrite: bool = Field(
|
||||
default=False,
|
||||
description="Whether to overwrite the archive if it already exists.",
|
||||
)
|
||||
format: str = Field(
|
||||
default="zip",
|
||||
description="Compression format ('zip', 'tar', 'tar.gz', 'tar.bz2', 'tar.xz').",
|
||||
)
|
||||
|
||||
|
||||
class FileCompressorTool(BaseTool):
|
||||
name: str = "File Compressor Tool"
|
||||
description: str = (
|
||||
"Compresses a file or directory into an archive (.zip currently supported). "
|
||||
"Useful for archiving logs, documents, or backups."
|
||||
)
|
||||
args_schema: Type[BaseModel] = FileCompressorToolInput
|
||||
|
||||
def _run(
|
||||
self,
|
||||
input_path: str,
|
||||
output_path: Optional[str] = None,
|
||||
overwrite: bool = False,
|
||||
format: str = "zip",
|
||||
) -> str:
|
||||
if not os.path.exists(input_path):
|
||||
return f"Input path '{input_path}' does not exist."
|
||||
|
||||
if not output_path:
|
||||
output_path = self._generate_output_path(input_path, format)
|
||||
|
||||
FORMAT_EXTENSION = {
|
||||
"zip": ".zip",
|
||||
"tar": ".tar",
|
||||
"tar.gz": ".tar.gz",
|
||||
"tar.bz2": ".tar.bz2",
|
||||
"tar.xz": ".tar.xz",
|
||||
}
|
||||
|
||||
if format not in FORMAT_EXTENSION:
|
||||
return f"Compression format '{format}' is not supported. Allowed formats: {', '.join(FORMAT_EXTENSION.keys())}"
|
||||
if not output_path.endswith(FORMAT_EXTENSION[format]):
|
||||
return f"Error: If '{format}' format is chosen, output file must have a '{FORMAT_EXTENSION[format]}' extension."
|
||||
if not self._prepare_output(output_path, overwrite):
|
||||
return (
|
||||
f"Output '{output_path}' already exists and overwrite is set to False."
|
||||
)
|
||||
|
||||
try:
|
||||
format_compression = {
|
||||
"zip": self._compress_zip,
|
||||
"tar": self._compress_tar,
|
||||
"tar.gz": self._compress_tar,
|
||||
"tar.bz2": self._compress_tar,
|
||||
"tar.xz": self._compress_tar,
|
||||
}
|
||||
if format == "zip":
|
||||
format_compression[format](input_path, output_path)
|
||||
else:
|
||||
format_compression[format](input_path, output_path, format)
|
||||
|
||||
return f"Successfully compressed '{input_path}' into '{output_path}'"
|
||||
except FileNotFoundError:
|
||||
return f"Error: File not found at path: {input_path}"
|
||||
except PermissionError:
|
||||
return f"Error: Permission denied when accessing '{input_path}' or writing '{output_path}'"
|
||||
except Exception as e:
|
||||
return f"An unexpected error occurred during compression: {e!s}"
|
||||
|
||||
def _generate_output_path(self, input_path: str, format: str) -> str:
|
||||
"""Generates output path based on input path and format."""
|
||||
if os.path.isfile(input_path):
|
||||
base_name = os.path.splitext(os.path.basename(input_path))[
|
||||
0
|
||||
] # Remove extension
|
||||
else:
|
||||
base_name = os.path.basename(os.path.normpath(input_path)) # Directory name
|
||||
return os.path.join(os.getcwd(), f"{base_name}.{format}")
|
||||
|
||||
def _prepare_output(self, output_path: str, overwrite: bool) -> bool:
|
||||
"""Ensures output path is ready for writing."""
|
||||
output_dir = os.path.dirname(output_path)
|
||||
if output_dir and not os.path.exists(output_dir):
|
||||
os.makedirs(output_dir)
|
||||
if os.path.exists(output_path) and not overwrite:
|
||||
return False
|
||||
return True
|
||||
|
||||
def _compress_zip(self, input_path: str, output_path: str):
|
||||
"""Compresses input into a zip archive."""
|
||||
with zipfile.ZipFile(output_path, "w", zipfile.ZIP_DEFLATED) as zipf:
|
||||
if os.path.isfile(input_path):
|
||||
zipf.write(input_path, os.path.basename(input_path))
|
||||
else:
|
||||
for root, _, files in os.walk(input_path):
|
||||
for file in files:
|
||||
full_path = os.path.join(root, file)
|
||||
arcname = os.path.relpath(full_path, start=input_path)
|
||||
zipf.write(full_path, arcname)
|
||||
|
||||
def _compress_tar(self, input_path: str, output_path: str, format: str):
|
||||
"""Compresses input into a tar archive with the given format."""
|
||||
format_mode = {
|
||||
"tar": "w",
|
||||
"tar.gz": "w:gz",
|
||||
"tar.bz2": "w:bz2",
|
||||
"tar.xz": "w:xz",
|
||||
}
|
||||
|
||||
if format not in format_mode:
|
||||
raise ValueError(f"Unsupported tar format: {format}")
|
||||
|
||||
mode = format_mode[format]
|
||||
|
||||
with tarfile.open(output_path, mode) as tarf:
|
||||
arcname = os.path.basename(input_path)
|
||||
tarf.add(input_path, arcname=arcname)
|
||||
File diff suppressed because it is too large
Load Diff
1
lib/crewai/.python-version
Normal file
1
lib/crewai/.python-version
Normal file
@@ -0,0 +1 @@
|
||||
3.13
|
||||
@@ -1,777 +0,0 @@
|
||||
<p align="center">
|
||||
<a href="https://github.com/crewAIInc/crewAI">
|
||||
<img src="docs/images/crewai_logo.png" width="600px" alt="Open source Multi-AI Agent orchestration framework">
|
||||
</a>
|
||||
</p>
|
||||
<p align="center" style="display: flex; justify-content: center; gap: 20px; align-items: center;">
|
||||
<a href="https://trendshift.io/repositories/11239" target="_blank">
|
||||
<img src="https://trendshift.io/api/badge/repositories/11239" alt="crewAIInc%2FcrewAI | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/>
|
||||
</a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://crewai.com">Homepage</a>
|
||||
·
|
||||
<a href="https://docs.crewai.com">Docs</a>
|
||||
·
|
||||
<a href="https://app.crewai.com">Start Cloud Trial</a>
|
||||
·
|
||||
<a href="https://blog.crewai.com">Blog</a>
|
||||
·
|
||||
<a href="https://community.crewai.com">Forum</a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://github.com/crewAIInc/crewAI">
|
||||
<img src="https://img.shields.io/github/stars/crewAIInc/crewAI" alt="GitHub Repo stars">
|
||||
</a>
|
||||
<a href="https://github.com/crewAIInc/crewAI/network/members">
|
||||
<img src="https://img.shields.io/github/forks/crewAIInc/crewAI" alt="GitHub forks">
|
||||
</a>
|
||||
<a href="https://github.com/crewAIInc/crewAI/issues">
|
||||
<img src="https://img.shields.io/github/issues/crewAIInc/crewAI" alt="GitHub issues">
|
||||
</a>
|
||||
<a href="https://github.com/crewAIInc/crewAI/pulls">
|
||||
<img src="https://img.shields.io/github/issues-pr/crewAIInc/crewAI" alt="GitHub pull requests">
|
||||
</a>
|
||||
<a href="https://opensource.org/licenses/MIT">
|
||||
<img src="https://img.shields.io/badge/License-MIT-green.svg" alt="License: MIT">
|
||||
</a>
|
||||
</p>
|
||||
|
||||
<p align="center">
|
||||
<a href="https://pypi.org/project/crewai/">
|
||||
<img src="https://img.shields.io/pypi/v/crewai" alt="PyPI version">
|
||||
</a>
|
||||
<a href="https://pypi.org/project/crewai/">
|
||||
<img src="https://img.shields.io/pypi/dm/crewai" alt="PyPI downloads">
|
||||
</a>
|
||||
<a href="https://twitter.com/crewAIInc">
|
||||
<img src="https://img.shields.io/twitter/follow/crewAIInc?style=social" alt="Twitter Follow">
|
||||
</a>
|
||||
</p>
|
||||
|
||||
### Fast and Flexible Multi-Agent Automation Framework
|
||||
|
||||
> CrewAI is a lean, lightning-fast Python framework built entirely from scratch—completely **independent of LangChain or other agent frameworks**.
|
||||
> It empowers developers with both high-level simplicity and precise low-level control, ideal for creating autonomous AI agents tailored to any scenario.
|
||||
|
||||
- **CrewAI Crews**: Optimize for autonomy and collaborative intelligence.
|
||||
- **CrewAI Flows**: Enable granular, event-driven control, single LLM calls for precise task orchestration and supports Crews natively
|
||||
|
||||
With over 100,000 developers certified through our community courses at [learn.crewai.com](https://learn.crewai.com), CrewAI is rapidly becoming the
|
||||
standard for enterprise-ready AI automation.
|
||||
|
||||
# CrewAI Enterprise Suite
|
||||
|
||||
CrewAI Enterprise Suite is a comprehensive bundle tailored for organizations that require secure, scalable, and easy-to-manage agent-driven automation.
|
||||
|
||||
You can try one part of the suite the [Crew Control Plane for free](https://app.crewai.com)
|
||||
|
||||
## Crew Control Plane Key Features:
|
||||
|
||||
- **Tracing & Observability**: Monitor and track your AI agents and workflows in real-time, including metrics, logs, and traces.
|
||||
- **Unified Control Plane**: A centralized platform for managing, monitoring, and scaling your AI agents and workflows.
|
||||
- **Seamless Integrations**: Easily connect with existing enterprise systems, data sources, and cloud infrastructure.
|
||||
- **Advanced Security**: Built-in robust security and compliance measures ensuring safe deployment and management.
|
||||
- **Actionable Insights**: Real-time analytics and reporting to optimize performance and decision-making.
|
||||
- **24/7 Support**: Dedicated enterprise support to ensure uninterrupted operation and quick resolution of issues.
|
||||
- **On-premise and Cloud Deployment Options**: Deploy CrewAI Enterprise on-premise or in the cloud, depending on your security and compliance requirements.
|
||||
|
||||
CrewAI Enterprise is designed for enterprises seeking a powerful, reliable solution to transform complex business processes into efficient,
|
||||
intelligent automations.
|
||||
|
||||
## Table of contents
|
||||
|
||||
- [Why CrewAI?](#why-crewai)
|
||||
- [Getting Started](#getting-started)
|
||||
- [Key Features](#key-features)
|
||||
- [Understanding Flows and Crews](#understanding-flows-and-crews)
|
||||
- [CrewAI vs LangGraph](#how-crewai-compares)
|
||||
- [Examples](#examples)
|
||||
- [Quick Tutorial](#quick-tutorial)
|
||||
- [Write Job Descriptions](#write-job-descriptions)
|
||||
- [Trip Planner](#trip-planner)
|
||||
- [Stock Analysis](#stock-analysis)
|
||||
- [Using Crews and Flows Together](#using-crews-and-flows-together)
|
||||
- [Connecting Your Crew to a Model](#connecting-your-crew-to-a-model)
|
||||
- [How CrewAI Compares](#how-crewai-compares)
|
||||
- [Frequently Asked Questions (FAQ)](#frequently-asked-questions-faq)
|
||||
- [Contribution](#contribution)
|
||||
- [Telemetry](#telemetry)
|
||||
- [License](#license)
|
||||
|
||||
## Why CrewAI?
|
||||
|
||||
<div align="center" style="margin-bottom: 30px;">
|
||||
<img src="docs/images/asset.png" alt="CrewAI Logo" width="100%">
|
||||
</div>
|
||||
|
||||
CrewAI unlocks the true potential of multi-agent automation, delivering the best-in-class combination of speed, flexibility, and control with either Crews of AI Agents or Flows of Events:
|
||||
|
||||
- **Standalone Framework**: Built from scratch, independent of LangChain or any other agent framework.
|
||||
- **High Performance**: Optimized for speed and minimal resource usage, enabling faster execution.
|
||||
- **Flexible Low Level Customization**: Complete freedom to customize at both high and low levels - from overall workflows and system architecture to granular agent behaviors, internal prompts, and execution logic.
|
||||
- **Ideal for Every Use Case**: Proven effective for both simple tasks and highly complex, real-world, enterprise-grade scenarios.
|
||||
- **Robust Community**: Backed by a rapidly growing community of over **100,000 certified** developers offering comprehensive support and resources.
|
||||
|
||||
CrewAI empowers developers and enterprises to confidently build intelligent automations, bridging the gap between simplicity, flexibility, and performance.
|
||||
|
||||
## Getting Started
|
||||
|
||||
Setup and run your first CrewAI agents by following this tutorial.
|
||||
|
||||
[](https://www.youtube.com/watch?v=-kSOTtYzgEw "CrewAI Getting Started Tutorial")
|
||||
|
||||
###
|
||||
Learning Resources
|
||||
|
||||
Learn CrewAI through our comprehensive courses:
|
||||
|
||||
- [Multi AI Agent Systems with CrewAI](https://www.deeplearning.ai/short-courses/multi-ai-agent-systems-with-crewai/) - Master the fundamentals of multi-agent systems
|
||||
- [Practical Multi AI Agents and Advanced Use Cases](https://www.deeplearning.ai/short-courses/practical-multi-ai-agents-and-advanced-use-cases-with-crewai/) - Deep dive into advanced implementations
|
||||
|
||||
### Understanding Flows and Crews
|
||||
|
||||
CrewAI offers two powerful, complementary approaches that work seamlessly together to build sophisticated AI applications:
|
||||
|
||||
1. **Crews**: Teams of AI agents with true autonomy and agency, working together to accomplish complex tasks through role-based collaboration. Crews enable:
|
||||
|
||||
- Natural, autonomous decision-making between agents
|
||||
- Dynamic task delegation and collaboration
|
||||
- Specialized roles with defined goals and expertise
|
||||
- Flexible problem-solving approaches
|
||||
2. **Flows**: Production-ready, event-driven workflows that deliver precise control over complex automations. Flows provide:
|
||||
|
||||
- Fine-grained control over execution paths for real-world scenarios
|
||||
- Secure, consistent state management between tasks
|
||||
- Clean integration of AI agents with production Python code
|
||||
- Conditional branching for complex business logic
|
||||
|
||||
The true power of CrewAI emerges when combining Crews and Flows. This synergy allows you to:
|
||||
|
||||
- Build complex, production-grade applications
|
||||
- Balance autonomy with precise control
|
||||
- Handle sophisticated real-world scenarios
|
||||
- Maintain clean, maintainable code structure
|
||||
|
||||
### Getting Started with Installation
|
||||
|
||||
To get started with CrewAI, follow these simple steps:
|
||||
|
||||
### 1. Installation
|
||||
|
||||
Ensure you have Python >=3.10 <3.14 installed on your system. CrewAI uses [UV](https://docs.astral.sh/uv/) for dependency management and package handling, offering a seamless setup and execution experience.
|
||||
|
||||
First, install CrewAI:
|
||||
|
||||
```shell
|
||||
pip install crewai
|
||||
```
|
||||
|
||||
If you want to install the 'crewai' package along with its optional features that include additional tools for agents, you can do so by using the following command:
|
||||
|
||||
```shell
|
||||
pip install 'crewai[tools]'
|
||||
```
|
||||
|
||||
The command above installs the basic package and also adds extra components which require more dependencies to function.
|
||||
|
||||
### Troubleshooting Dependencies
|
||||
|
||||
If you encounter issues during installation or usage, here are some common solutions:
|
||||
|
||||
#### Common Issues
|
||||
|
||||
1. **ModuleNotFoundError: No module named 'tiktoken'**
|
||||
|
||||
- Install tiktoken explicitly: `pip install 'crewai[embeddings]'`
|
||||
- If using embedchain or other tools: `pip install 'crewai[tools]'`
|
||||
2. **Failed building wheel for tiktoken**
|
||||
|
||||
- Ensure Rust compiler is installed (see installation steps above)
|
||||
- For Windows: Verify Visual C++ Build Tools are installed
|
||||
- Try upgrading pip: `pip install --upgrade pip`
|
||||
- If issues persist, use a pre-built wheel: `pip install tiktoken --prefer-binary`
|
||||
|
||||
### 2. Setting Up Your Crew with the YAML Configuration
|
||||
|
||||
To create a new CrewAI project, run the following CLI (Command Line Interface) command:
|
||||
|
||||
```shell
|
||||
crewai create crew <project_name>
|
||||
```
|
||||
|
||||
This command creates a new project folder with the following structure:
|
||||
|
||||
```
|
||||
my_project/
|
||||
├── .gitignore
|
||||
├── pyproject.toml
|
||||
├── README.md
|
||||
├── .env
|
||||
└── src/
|
||||
└── my_project/
|
||||
├── __init__.py
|
||||
├── main.py
|
||||
├── crew.py
|
||||
├── tools/
|
||||
│ ├── custom_tool.py
|
||||
│ └── __init__.py
|
||||
└── config/
|
||||
├── agents.yaml
|
||||
└── tasks.yaml
|
||||
```
|
||||
|
||||
You can now start developing your crew by editing the files in the `src/my_project` folder. The `main.py` file is the entry point of the project, the `crew.py` file is where you define your crew, the `agents.yaml` file is where you define your agents, and the `tasks.yaml` file is where you define your tasks.
|
||||
|
||||
#### To customize your project, you can:
|
||||
|
||||
- Modify `src/my_project/config/agents.yaml` to define your agents.
|
||||
- Modify `src/my_project/config/tasks.yaml` to define your tasks.
|
||||
- Modify `src/my_project/crew.py` to add your own logic, tools, and specific arguments.
|
||||
- Modify `src/my_project/main.py` to add custom inputs for your agents and tasks.
|
||||
- Add your environment variables into the `.env` file.
|
||||
|
||||
#### Example of a simple crew with a sequential process:
|
||||
|
||||
Instantiate your crew:
|
||||
|
||||
```shell
|
||||
crewai create crew latest-ai-development
|
||||
```
|
||||
|
||||
Modify the files as needed to fit your use case:
|
||||
|
||||
**agents.yaml**
|
||||
|
||||
```yaml
|
||||
# src/my_project/config/agents.yaml
|
||||
researcher:
|
||||
role: >
|
||||
{topic} Senior Data Researcher
|
||||
goal: >
|
||||
Uncover cutting-edge developments in {topic}
|
||||
backstory: >
|
||||
You're a seasoned researcher with a knack for uncovering the latest
|
||||
developments in {topic}. Known for your ability to find the most relevant
|
||||
information and present it in a clear and concise manner.
|
||||
|
||||
reporting_analyst:
|
||||
role: >
|
||||
{topic} Reporting Analyst
|
||||
goal: >
|
||||
Create detailed reports based on {topic} data analysis and research findings
|
||||
backstory: >
|
||||
You're a meticulous analyst with a keen eye for detail. You're known for
|
||||
your ability to turn complex data into clear and concise reports, making
|
||||
it easy for others to understand and act on the information you provide.
|
||||
```
|
||||
|
||||
**tasks.yaml**
|
||||
|
||||
```yaml
|
||||
# src/my_project/config/tasks.yaml
|
||||
research_task:
|
||||
description: >
|
||||
Conduct a thorough research about {topic}
|
||||
Make sure you find any interesting and relevant information given
|
||||
the current year is 2025.
|
||||
expected_output: >
|
||||
A list with 10 bullet points of the most relevant information about {topic}
|
||||
agent: researcher
|
||||
|
||||
reporting_task:
|
||||
description: >
|
||||
Review the context you got and expand each topic into a full section for a report.
|
||||
Make sure the report is detailed and contains any and all relevant information.
|
||||
expected_output: >
|
||||
A fully fledge reports with the mains topics, each with a full section of information.
|
||||
Formatted as markdown without '```'
|
||||
agent: reporting_analyst
|
||||
output_file: report.md
|
||||
```
|
||||
|
||||
**crew.py**
|
||||
|
||||
```python
|
||||
# src/my_project/crew.py
|
||||
from crewai import Agent, Crew, Process, Task
|
||||
from crewai.project import CrewBase, agent, crew, task
|
||||
from crewai_tools import SerperDevTool
|
||||
from crewai.agents.agent_builder.base_agent import BaseAgent
|
||||
from typing import List
|
||||
|
||||
@CrewBase
|
||||
class LatestAiDevelopmentCrew():
|
||||
"""LatestAiDevelopment crew"""
|
||||
agents: List[BaseAgent]
|
||||
tasks: List[Task]
|
||||
|
||||
@agent
|
||||
def researcher(self) -> Agent:
|
||||
return Agent(
|
||||
config=self.agents_config['researcher'],
|
||||
verbose=True,
|
||||
tools=[SerperDevTool()]
|
||||
)
|
||||
|
||||
@agent
|
||||
def reporting_analyst(self) -> Agent:
|
||||
return Agent(
|
||||
config=self.agents_config['reporting_analyst'],
|
||||
verbose=True
|
||||
)
|
||||
|
||||
@task
|
||||
def research_task(self) -> Task:
|
||||
return Task(
|
||||
config=self.tasks_config['research_task'],
|
||||
)
|
||||
|
||||
@task
|
||||
def reporting_task(self) -> Task:
|
||||
return Task(
|
||||
config=self.tasks_config['reporting_task'],
|
||||
output_file='report.md'
|
||||
)
|
||||
|
||||
@crew
|
||||
def crew(self) -> Crew:
|
||||
"""Creates the LatestAiDevelopment crew"""
|
||||
return Crew(
|
||||
agents=self.agents, # Automatically created by the @agent decorator
|
||||
tasks=self.tasks, # Automatically created by the @task decorator
|
||||
process=Process.sequential,
|
||||
verbose=True,
|
||||
)
|
||||
```
|
||||
|
||||
**main.py**
|
||||
|
||||
```python
|
||||
#!/usr/bin/env python
|
||||
# src/my_project/main.py
|
||||
import sys
|
||||
from latest_ai_development.crew import LatestAiDevelopmentCrew
|
||||
|
||||
def run():
|
||||
"""
|
||||
Run the crew.
|
||||
"""
|
||||
inputs = {
|
||||
'topic': 'AI Agents'
|
||||
}
|
||||
LatestAiDevelopmentCrew().crew().kickoff(inputs=inputs)
|
||||
```
|
||||
|
||||
### 3. Running Your Crew
|
||||
|
||||
Before running your crew, make sure you have the following keys set as environment variables in your `.env` file:
|
||||
|
||||
- An [OpenAI API key](https://platform.openai.com/account/api-keys) (or other LLM API key): `OPENAI_API_KEY=sk-...`
|
||||
- A [Serper.dev](https://serper.dev/) API key: `SERPER_API_KEY=YOUR_KEY_HERE`
|
||||
|
||||
Lock the dependencies and install them by using the CLI command but first, navigate to your project directory:
|
||||
|
||||
```shell
|
||||
cd my_project
|
||||
crewai install (Optional)
|
||||
```
|
||||
|
||||
To run your crew, execute the following command in the root of your project:
|
||||
|
||||
```bash
|
||||
crewai run
|
||||
```
|
||||
|
||||
or
|
||||
|
||||
```bash
|
||||
python src/my_project/main.py
|
||||
```
|
||||
|
||||
If an error happens due to the usage of poetry, please run the following command to update your crewai package:
|
||||
|
||||
```bash
|
||||
crewai update
|
||||
```
|
||||
|
||||
You should see the output in the console and the `report.md` file should be created in the root of your project with the full final report.
|
||||
|
||||
In addition to the sequential process, you can use the hierarchical process, which automatically assigns a manager to the defined crew to properly coordinate the planning and execution of tasks through delegation and validation of results. [See more about the processes here](https://docs.crewai.com/core-concepts/Processes/).
|
||||
|
||||
## Key Features
|
||||
|
||||
CrewAI stands apart as a lean, standalone, high-performance multi-AI Agent framework delivering simplicity, flexibility, and precise control—free from the complexity and limitations found in other agent frameworks.
|
||||
|
||||
- **Standalone & Lean**: Completely independent from other frameworks like LangChain, offering faster execution and lighter resource demands.
|
||||
- **Flexible & Precise**: Easily orchestrate autonomous agents through intuitive [Crews](https://docs.crewai.com/concepts/crews) or precise [Flows](https://docs.crewai.com/concepts/flows), achieving perfect balance for your needs.
|
||||
- **Seamless Integration**: Effortlessly combine Crews (autonomy) and Flows (precision) to create complex, real-world automations.
|
||||
- **Deep Customization**: Tailor every aspect—from high-level workflows down to low-level internal prompts and agent behaviors.
|
||||
- **Reliable Performance**: Consistent results across simple tasks and complex, enterprise-level automations.
|
||||
- **Thriving Community**: Backed by robust documentation and over 100,000 certified developers, providing exceptional support and guidance.
|
||||
|
||||
Choose CrewAI to easily build powerful, adaptable, and production-ready AI automations.
|
||||
|
||||
## Examples
|
||||
|
||||
You can test different real life examples of AI crews in the [CrewAI-examples repo](https://github.com/crewAIInc/crewAI-examples?tab=readme-ov-file):
|
||||
|
||||
- [Landing Page Generator](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/landing_page_generator)
|
||||
- [Having Human input on the execution](https://docs.crewai.com/how-to/Human-Input-on-Execution)
|
||||
- [Trip Planner](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner)
|
||||
- [Stock Analysis](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis)
|
||||
|
||||
### Quick Tutorial
|
||||
|
||||
[](https://www.youtube.com/watch?v=tnejrr-0a94 "CrewAI Tutorial")
|
||||
|
||||
### Write Job Descriptions
|
||||
|
||||
[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/job-posting) or watch a video below:
|
||||
|
||||
[](https://www.youtube.com/watch?v=u98wEMz-9to "Jobs postings")
|
||||
|
||||
### Trip Planner
|
||||
|
||||
[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/trip_planner) or watch a video below:
|
||||
|
||||
[](https://www.youtube.com/watch?v=xis7rWp-hjs "Trip Planner")
|
||||
|
||||
### Stock Analysis
|
||||
|
||||
[Check out code for this example](https://github.com/crewAIInc/crewAI-examples/tree/main/crews/stock_analysis) or watch a video below:
|
||||
|
||||
[](https://www.youtube.com/watch?v=e0Uj4yWdaAg "Stock Analysis")
|
||||
|
||||
### Using Crews and Flows Together
|
||||
|
||||
CrewAI's power truly shines when combining Crews with Flows to create sophisticated automation pipelines.
|
||||
CrewAI flows support logical operators like `or_` and `and_` to combine multiple conditions. This can be used with `@start`, `@listen`, or `@router` decorators to create complex triggering conditions.
|
||||
|
||||
- `or_`: Triggers when any of the specified conditions are met.
|
||||
- `and_`Triggers when all of the specified conditions are met.
|
||||
|
||||
Here's how you can orchestrate multiple Crews within a Flow:
|
||||
|
||||
```python
|
||||
from crewai.flow.flow import Flow, listen, start, router, or_
|
||||
from crewai import Crew, Agent, Task, Process
|
||||
from pydantic import BaseModel
|
||||
|
||||
# Define structured state for precise control
|
||||
class MarketState(BaseModel):
|
||||
sentiment: str = "neutral"
|
||||
confidence: float = 0.0
|
||||
recommendations: list = []
|
||||
|
||||
class AdvancedAnalysisFlow(Flow[MarketState]):
|
||||
@start()
|
||||
def fetch_market_data(self):
|
||||
# Demonstrate low-level control with structured state
|
||||
self.state.sentiment = "analyzing"
|
||||
return {"sector": "tech", "timeframe": "1W"} # These parameters match the task description template
|
||||
|
||||
@listen(fetch_market_data)
|
||||
def analyze_with_crew(self, market_data):
|
||||
# Show crew agency through specialized roles
|
||||
analyst = Agent(
|
||||
role="Senior Market Analyst",
|
||||
goal="Conduct deep market analysis with expert insight",
|
||||
backstory="You're a veteran analyst known for identifying subtle market patterns"
|
||||
)
|
||||
researcher = Agent(
|
||||
role="Data Researcher",
|
||||
goal="Gather and validate supporting market data",
|
||||
backstory="You excel at finding and correlating multiple data sources"
|
||||
)
|
||||
|
||||
analysis_task = Task(
|
||||
description="Analyze {sector} sector data for the past {timeframe}",
|
||||
expected_output="Detailed market analysis with confidence score",
|
||||
agent=analyst
|
||||
)
|
||||
research_task = Task(
|
||||
description="Find supporting data to validate the analysis",
|
||||
expected_output="Corroborating evidence and potential contradictions",
|
||||
agent=researcher
|
||||
)
|
||||
|
||||
# Demonstrate crew autonomy
|
||||
analysis_crew = Crew(
|
||||
agents=[analyst, researcher],
|
||||
tasks=[analysis_task, research_task],
|
||||
process=Process.sequential,
|
||||
verbose=True
|
||||
)
|
||||
return analysis_crew.kickoff(inputs=market_data) # Pass market_data as named inputs
|
||||
|
||||
@router(analyze_with_crew)
|
||||
def determine_next_steps(self):
|
||||
# Show flow control with conditional routing
|
||||
if self.state.confidence > 0.8:
|
||||
return "high_confidence"
|
||||
elif self.state.confidence > 0.5:
|
||||
return "medium_confidence"
|
||||
return "low_confidence"
|
||||
|
||||
@listen("high_confidence")
|
||||
def execute_strategy(self):
|
||||
# Demonstrate complex decision making
|
||||
strategy_crew = Crew(
|
||||
agents=[
|
||||
Agent(role="Strategy Expert",
|
||||
goal="Develop optimal market strategy")
|
||||
],
|
||||
tasks=[
|
||||
Task(description="Create detailed strategy based on analysis",
|
||||
expected_output="Step-by-step action plan")
|
||||
]
|
||||
)
|
||||
return strategy_crew.kickoff()
|
||||
|
||||
@listen(or_("medium_confidence", "low_confidence"))
|
||||
def request_additional_analysis(self):
|
||||
self.state.recommendations.append("Gather more data")
|
||||
return "Additional analysis required"
|
||||
```
|
||||
|
||||
This example demonstrates how to:
|
||||
|
||||
1. Use Python code for basic data operations
|
||||
2. Create and execute Crews as steps in your workflow
|
||||
3. Use Flow decorators to manage the sequence of operations
|
||||
4. Implement conditional branching based on Crew results
|
||||
|
||||
## Connecting Your Crew to a Model
|
||||
|
||||
CrewAI supports using various LLMs through a variety of connection options. By default your agents will use the OpenAI API when querying the model. However, there are several other ways to allow your agents to connect to models. For example, you can configure your agents to use a local model via the Ollama tool.
|
||||
|
||||
Please refer to the [Connect CrewAI to LLMs](https://docs.crewai.com/how-to/LLM-Connections/) page for details on configuring your agents' connections to models.
|
||||
|
||||
## How CrewAI Compares
|
||||
|
||||
**CrewAI's Advantage**: CrewAI combines autonomous agent intelligence with precise workflow control through its unique Crews and Flows architecture. The framework excels at both high-level orchestration and low-level customization, enabling complex, production-grade systems with granular control.
|
||||
|
||||
- **LangGraph**: While LangGraph provides a foundation for building agent workflows, its approach requires significant boilerplate code and complex state management patterns. The framework's tight coupling with LangChain can limit flexibility when implementing custom agent behaviors or integrating with external systems.
|
||||
|
||||
*P.S. CrewAI demonstrates significant performance advantages over LangGraph, executing 5.76x faster in certain cases like this QA task example ([see comparison](https://github.com/crewAIInc/crewAI-examples/tree/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/QA%20Agent)) while achieving higher evaluation scores with faster completion times in certain coding tasks, like in this example ([detailed analysis](https://github.com/crewAIInc/crewAI-examples/blob/main/Notebooks/CrewAI%20Flows%20%26%20Langgraph/Coding%20Assistant/coding_assistant_eval.ipynb)).*
|
||||
|
||||
- **Autogen**: While Autogen excels at creating conversational agents capable of working together, it lacks an inherent concept of process. In Autogen, orchestrating agents' interactions requires additional programming, which can become complex and cumbersome as the scale of tasks grows.
|
||||
- **ChatDev**: ChatDev introduced the idea of processes into the realm of AI agents, but its implementation is quite rigid. Customizations in ChatDev are limited and not geared towards production environments, which can hinder scalability and flexibility in real-world applications.
|
||||
|
||||
## Contribution
|
||||
|
||||
CrewAI is open-source and we welcome contributions. If you're looking to contribute, please:
|
||||
|
||||
- Fork the repository.
|
||||
- Create a new branch for your feature.
|
||||
- Add your feature or improvement.
|
||||
- Send a pull request.
|
||||
- We appreciate your input!
|
||||
|
||||
### Installing Dependencies
|
||||
|
||||
```bash
|
||||
uv lock
|
||||
uv sync
|
||||
```
|
||||
|
||||
### Virtual Env
|
||||
|
||||
```bash
|
||||
uv venv
|
||||
```
|
||||
|
||||
### Pre-commit hooks
|
||||
|
||||
```bash
|
||||
pre-commit install
|
||||
```
|
||||
|
||||
### Running Tests
|
||||
|
||||
```bash
|
||||
uv run pytest .
|
||||
```
|
||||
|
||||
### Running static type checks
|
||||
|
||||
```bash
|
||||
uvx mypy src
|
||||
```
|
||||
|
||||
### Packaging
|
||||
|
||||
```bash
|
||||
uv build
|
||||
```
|
||||
|
||||
### Installing Locally
|
||||
|
||||
```bash
|
||||
pip install dist/*.tar.gz
|
||||
```
|
||||
|
||||
## Telemetry
|
||||
|
||||
CrewAI uses anonymous telemetry to collect usage data with the main purpose of helping us improve the library by focusing our efforts on the most used features, integrations and tools.
|
||||
|
||||
It's pivotal to understand that **NO data is collected** concerning prompts, task descriptions, agents' backstories or goals, usage of tools, API calls, responses, any data processed by the agents, or secrets and environment variables, with the exception of the conditions mentioned. When the `share_crew` feature is enabled, detailed data including task descriptions, agents' backstories or goals, and other specific attributes are collected to provide deeper insights while respecting user privacy. Users can disable telemetry by setting the environment variable OTEL_SDK_DISABLED to true.
|
||||
|
||||
Data collected includes:
|
||||
|
||||
- Version of CrewAI
|
||||
- So we can understand how many users are using the latest version
|
||||
- Version of Python
|
||||
- So we can decide on what versions to better support
|
||||
- General OS (e.g. number of CPUs, macOS/Windows/Linux)
|
||||
- So we know what OS we should focus on and if we could build specific OS related features
|
||||
- Number of agents and tasks in a crew
|
||||
- So we make sure we are testing internally with similar use cases and educate people on the best practices
|
||||
- Crew Process being used
|
||||
- Understand where we should focus our efforts
|
||||
- If Agents are using memory or allowing delegation
|
||||
- Understand if we improved the features or maybe even drop them
|
||||
- If Tasks are being executed in parallel or sequentially
|
||||
- Understand if we should focus more on parallel execution
|
||||
- Language model being used
|
||||
- Improved support on most used languages
|
||||
- Roles of agents in a crew
|
||||
- Understand high level use cases so we can build better tools, integrations and examples about it
|
||||
- Tools names available
|
||||
- Understand out of the publicly available tools, which ones are being used the most so we can improve them
|
||||
|
||||
Users can opt-in to Further Telemetry, sharing the complete telemetry data by setting the `share_crew` attribute to `True` on their Crews. Enabling `share_crew` results in the collection of detailed crew and task execution data, including `goal`, `backstory`, `context`, and `output` of tasks. This enables a deeper insight into usage patterns while respecting the user's choice to share.
|
||||
|
||||
## License
|
||||
|
||||
CrewAI is released under the [MIT License](https://github.com/crewAIInc/crewAI/blob/main/LICENSE).
|
||||
|
||||
## Frequently Asked Questions (FAQ)
|
||||
|
||||
### General
|
||||
|
||||
- [What exactly is CrewAI?](#q-what-exactly-is-crewai)
|
||||
- [How do I install CrewAI?](#q-how-do-i-install-crewai)
|
||||
- [Does CrewAI depend on LangChain?](#q-does-crewai-depend-on-langchain)
|
||||
- [Is CrewAI open-source?](#q-is-crewai-open-source)
|
||||
- [Does CrewAI collect data from users?](#q-does-crewai-collect-data-from-users)
|
||||
|
||||
### Features and Capabilities
|
||||
|
||||
- [Can CrewAI handle complex use cases?](#q-can-crewai-handle-complex-use-cases)
|
||||
- [Can I use CrewAI with local AI models?](#q-can-i-use-crewai-with-local-ai-models)
|
||||
- [What makes Crews different from Flows?](#q-what-makes-crews-different-from-flows)
|
||||
- [How is CrewAI better than LangChain?](#q-how-is-crewai-better-than-langchain)
|
||||
- [Does CrewAI support fine-tuning or training custom models?](#q-does-crewai-support-fine-tuning-or-training-custom-models)
|
||||
|
||||
### Resources and Community
|
||||
|
||||
- [Where can I find real-world CrewAI examples?](#q-where-can-i-find-real-world-crewai-examples)
|
||||
- [How can I contribute to CrewAI?](#q-how-can-i-contribute-to-crewai)
|
||||
|
||||
### Enterprise Features
|
||||
|
||||
- [What additional features does CrewAI Enterprise offer?](#q-what-additional-features-does-crewai-enterprise-offer)
|
||||
- [Is CrewAI Enterprise available for cloud and on-premise deployments?](#q-is-crewai-enterprise-available-for-cloud-and-on-premise-deployments)
|
||||
- [Can I try CrewAI Enterprise for free?](#q-can-i-try-crewai-enterprise-for-free)
|
||||
|
||||
### Q: What exactly is CrewAI?
|
||||
|
||||
A: CrewAI is a standalone, lean, and fast Python framework built specifically for orchestrating autonomous AI agents. Unlike frameworks like LangChain, CrewAI does not rely on external dependencies, making it leaner, faster, and simpler.
|
||||
|
||||
### Q: How do I install CrewAI?
|
||||
|
||||
A: Install CrewAI using pip:
|
||||
|
||||
```shell
|
||||
pip install crewai
|
||||
```
|
||||
|
||||
For additional tools, use:
|
||||
|
||||
```shell
|
||||
pip install 'crewai[tools]'
|
||||
```
|
||||
|
||||
### Q: Does CrewAI depend on LangChain?
|
||||
|
||||
A: No. CrewAI is built entirely from the ground up, with no dependencies on LangChain or other agent frameworks. This ensures a lean, fast, and flexible experience.
|
||||
|
||||
### Q: Can CrewAI handle complex use cases?
|
||||
|
||||
A: Yes. CrewAI excels at both simple and highly complex real-world scenarios, offering deep customization options at both high and low levels, from internal prompts to sophisticated workflow orchestration.
|
||||
|
||||
### Q: Can I use CrewAI with local AI models?
|
||||
|
||||
A: Absolutely! CrewAI supports various language models, including local ones. Tools like Ollama and LM Studio allow seamless integration. Check the [LLM Connections documentation](https://docs.crewai.com/how-to/LLM-Connections/) for more details.
|
||||
|
||||
### Q: What makes Crews different from Flows?
|
||||
|
||||
A: Crews provide autonomous agent collaboration, ideal for tasks requiring flexible decision-making and dynamic interaction. Flows offer precise, event-driven control, ideal for managing detailed execution paths and secure state management. You can seamlessly combine both for maximum effectiveness.
|
||||
|
||||
### Q: How is CrewAI better than LangChain?
|
||||
|
||||
A: CrewAI provides simpler, more intuitive APIs, faster execution speeds, more reliable and consistent results, robust documentation, and an active community—addressing common criticisms and limitations associated with LangChain.
|
||||
|
||||
### Q: Is CrewAI open-source?
|
||||
|
||||
A: Yes, CrewAI is open-source and actively encourages community contributions and collaboration.
|
||||
|
||||
### Q: Does CrewAI collect data from users?
|
||||
|
||||
A: CrewAI collects anonymous telemetry data strictly for improvement purposes. Sensitive data such as prompts, tasks, or API responses are never collected unless explicitly enabled by the user.
|
||||
|
||||
### Q: Where can I find real-world CrewAI examples?
|
||||
|
||||
A: Check out practical examples in the [CrewAI-examples repository](https://github.com/crewAIInc/crewAI-examples), covering use cases like trip planners, stock analysis, and job postings.
|
||||
|
||||
### Q: How can I contribute to CrewAI?
|
||||
|
||||
A: Contributions are warmly welcomed! Fork the repository, create your branch, implement your changes, and submit a pull request. See the Contribution section of the README for detailed guidelines.
|
||||
|
||||
### Q: What additional features does CrewAI Enterprise offer?
|
||||
|
||||
A: CrewAI Enterprise provides advanced features such as a unified control plane, real-time observability, secure integrations, advanced security, actionable insights, and dedicated 24/7 enterprise support.
|
||||
|
||||
### Q: Is CrewAI Enterprise available for cloud and on-premise deployments?
|
||||
|
||||
A: Yes, CrewAI Enterprise supports both cloud-based and on-premise deployment options, allowing enterprises to meet their specific security and compliance requirements.
|
||||
|
||||
### Q: Can I try CrewAI Enterprise for free?
|
||||
|
||||
A: Yes, you can explore part of the CrewAI Enterprise Suite by accessing the [Crew Control Plane](https://app.crewai.com) for free.
|
||||
|
||||
### Q: Does CrewAI support fine-tuning or training custom models?
|
||||
|
||||
A: Yes, CrewAI can integrate with custom-trained or fine-tuned models, allowing you to enhance your agents with domain-specific knowledge and accuracy.
|
||||
|
||||
### Q: Can CrewAI agents interact with external tools and APIs?
|
||||
|
||||
A: Absolutely! CrewAI agents can easily integrate with external tools, APIs, and databases, empowering them to leverage real-world data and resources.
|
||||
|
||||
### Q: Is CrewAI suitable for production environments?
|
||||
|
||||
A: Yes, CrewAI is explicitly designed with production-grade standards, ensuring reliability, stability, and scalability for enterprise deployments.
|
||||
|
||||
### Q: How scalable is CrewAI?
|
||||
|
||||
A: CrewAI is highly scalable, supporting simple automations and large-scale enterprise workflows involving numerous agents and complex tasks simultaneously.
|
||||
|
||||
### Q: Does CrewAI offer debugging and monitoring tools?
|
||||
|
||||
A: Yes, CrewAI Enterprise includes advanced debugging, tracing, and real-time observability features, simplifying the management and troubleshooting of your automations.
|
||||
|
||||
### Q: What programming languages does CrewAI support?
|
||||
|
||||
A: CrewAI is primarily Python-based but easily integrates with services and APIs written in any programming language through its flexible API integration capabilities.
|
||||
|
||||
### Q: Does CrewAI offer educational resources for beginners?
|
||||
|
||||
A: Yes, CrewAI provides extensive beginner-friendly tutorials, courses, and documentation through learn.crewai.com, supporting developers at all skill levels.
|
||||
|
||||
### Q: Can CrewAI automate human-in-the-loop workflows?
|
||||
|
||||
A: Yes, CrewAI fully supports human-in-the-loop workflows, allowing seamless collaboration between human experts and AI agents for enhanced decision-making.
|
||||
|
||||
@@ -1,14 +1,35 @@
|
||||
[project]
|
||||
name = "crewai"
|
||||
dynamic = ["version"]
|
||||
description = "Cutting-edge framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks."
|
||||
description = ""
|
||||
readme = "README.md"
|
||||
authors = [
|
||||
{ name = "Joao Moura", email = "joao@crewai.com" }
|
||||
{ name = "Greyson Lalonde", email = "greyson.r.lalonde@gmail.com" }
|
||||
]
|
||||
keywords = [
|
||||
"crewai",
|
||||
"ai",
|
||||
"agents",
|
||||
"framework",
|
||||
"orchestration",
|
||||
"llm",
|
||||
"core",
|
||||
"typed",
|
||||
]
|
||||
classifiers = [
|
||||
"Development Status :: 3 - Alpha",
|
||||
"Intended Audience :: Developers",
|
||||
"Operating System :: OS Independent",
|
||||
"Programming Language :: Python :: 3",
|
||||
"Programming Language :: Python :: 3.12",
|
||||
"Programming Language :: Python :: 3.13",
|
||||
"Topic :: Software Development :: Libraries :: Python Modules",
|
||||
"Typing :: Typed",
|
||||
]
|
||||
requires-python = ">=3.10, <3.14"
|
||||
dependencies = [
|
||||
# Core Dependencies
|
||||
"crewai",
|
||||
"pydantic>=2.11.9",
|
||||
"openai>=1.13.3",
|
||||
"litellm==1.74.9",
|
||||
@@ -20,8 +41,6 @@ dependencies = [
|
||||
"opentelemetry-api>=1.30.0",
|
||||
"opentelemetry-sdk>=1.30.0",
|
||||
"opentelemetry-exporter-otlp-proto-http>=1.30.0",
|
||||
# Data Handling
|
||||
"chromadb~=1.1.0",
|
||||
"tokenizers>=0.20.3",
|
||||
"openpyxl>=3.1.5",
|
||||
"pyvis>=0.3.2",
|
||||
@@ -33,24 +52,19 @@ dependencies = [
|
||||
"appdirs>=1.4.4",
|
||||
"jsonref>=1.1.0",
|
||||
"json-repair==0.25.2",
|
||||
"uv>=0.4.25",
|
||||
"tomli-w>=1.1.0",
|
||||
"tomli>=2.0.2",
|
||||
"blinker>=1.9.0",
|
||||
"json5>=0.10.0",
|
||||
"portalocker==2.7.0",
|
||||
"chromadb~=1.1.0",
|
||||
"pydantic-settings>=2.10.1",
|
||||
"uv>=0.4.25",
|
||||
]
|
||||
|
||||
[project.urls]
|
||||
Homepage = "https://crewai.com"
|
||||
Documentation = "https://docs.crewai.com"
|
||||
Repository = "https://github.com/crewAIInc/crewAI"
|
||||
|
||||
|
||||
[project.optional-dependencies]
|
||||
tools = [
|
||||
"crewai-tools==1.0.0a1",
|
||||
"crewai-tools",
|
||||
]
|
||||
embeddings = [
|
||||
"tiktoken~=0.8.0"
|
||||
@@ -84,31 +98,19 @@ voyageai = [
|
||||
"voyageai>=0.3.5",
|
||||
]
|
||||
|
||||
|
||||
[project.scripts]
|
||||
crewai = "crewai.cli.cli:crewai"
|
||||
|
||||
[project.urls]
|
||||
Homepage = "https://crewai.com"
|
||||
Documentation = "https://docs.crewai.com"
|
||||
Repository = "https://github.com/crewAIInc/crewAI"
|
||||
|
||||
# PyTorch index configuration, since torch 2.5.0 is not compatible with python 3.13
|
||||
[[tool.uv.index]]
|
||||
name = "pytorch-nightly"
|
||||
url = "https://download.pytorch.org/whl/nightly/cpu"
|
||||
explicit = true
|
||||
|
||||
[[tool.uv.index]]
|
||||
name = "pytorch"
|
||||
url = "https://download.pytorch.org/whl/cpu"
|
||||
explicit = true
|
||||
|
||||
[tool.uv.sources]
|
||||
torch = [
|
||||
{ index = "pytorch-nightly", marker = "python_version >= '3.13'" },
|
||||
{ index = "pytorch", marker = "python_version < '3.13'" },
|
||||
]
|
||||
torchvision = [
|
||||
{ index = "pytorch-nightly", marker = "python_version >= '3.13'" },
|
||||
{ index = "pytorch", marker = "python_version < '3.13'" },
|
||||
]
|
||||
[tool.pytest.ini_options]
|
||||
testpaths = ["tests"]
|
||||
asyncio_mode = "strict"
|
||||
asyncio_default_fixture_loop_scope = "function"
|
||||
|
||||
|
||||
[build-system]
|
||||
@@ -117,3 +119,6 @@ build-backend = "hatchling.build"
|
||||
|
||||
[tool.hatch.version]
|
||||
path = "src/crewai/__init__.py"
|
||||
|
||||
[tool.hatch.build.targets.wheel]
|
||||
packages = ["src/crewai"]
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import threading
|
||||
from typing import Any
|
||||
import urllib.request
|
||||
import warnings
|
||||
from typing import Any
|
||||
|
||||
from crewai.agent import Agent
|
||||
from crewai.crew import Crew
|
||||
@@ -40,7 +40,7 @@ def _suppress_pydantic_deprecation_warnings() -> None:
|
||||
|
||||
_suppress_pydantic_deprecation_warnings()
|
||||
|
||||
__version__ = "1.0.0a1"
|
||||
__version__ = "1.0.0a0"
|
||||
_telemetry_submitted = False
|
||||
|
||||
|
||||
|
||||
@@ -1,189 +0,0 @@
|
||||
import time
|
||||
import webbrowser
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
import requests
|
||||
from pydantic import BaseModel, Field
|
||||
from rich.console import Console
|
||||
|
||||
from crewai.cli.config import Settings
|
||||
from crewai.cli.shared.token_manager import TokenManager
|
||||
|
||||
from .utils import validate_jwt_token
|
||||
|
||||
console = Console()
|
||||
|
||||
|
||||
class Oauth2Settings(BaseModel):
|
||||
provider: str = Field(
|
||||
description="OAuth2 provider used for authentication (e.g., workos, okta, auth0)."
|
||||
)
|
||||
client_id: str = Field(
|
||||
description="OAuth2 client ID issued by the provider, used during authentication requests."
|
||||
)
|
||||
domain: str = Field(
|
||||
description="OAuth2 provider's domain (e.g., your-org.auth0.com) used for issuing tokens."
|
||||
)
|
||||
audience: Optional[str] = Field(
|
||||
description="OAuth2 audience value, typically used to identify the target API or resource.",
|
||||
default=None,
|
||||
)
|
||||
|
||||
@classmethod
|
||||
def from_settings(cls):
|
||||
settings = Settings()
|
||||
|
||||
return cls(
|
||||
provider=settings.oauth2_provider,
|
||||
domain=settings.oauth2_domain,
|
||||
client_id=settings.oauth2_client_id,
|
||||
audience=settings.oauth2_audience,
|
||||
)
|
||||
|
||||
|
||||
class ProviderFactory:
|
||||
@classmethod
|
||||
def from_settings(cls, settings: Optional[Oauth2Settings] = None):
|
||||
settings = settings or Oauth2Settings.from_settings()
|
||||
|
||||
import importlib
|
||||
|
||||
module = importlib.import_module(
|
||||
f"crewai.cli.authentication.providers.{settings.provider.lower()}"
|
||||
)
|
||||
provider = getattr(module, f"{settings.provider.capitalize()}Provider")
|
||||
|
||||
return provider(settings)
|
||||
|
||||
|
||||
class AuthenticationCommand:
|
||||
def __init__(self):
|
||||
self.token_manager = TokenManager()
|
||||
self.oauth2_provider = ProviderFactory.from_settings()
|
||||
|
||||
def login(self) -> None:
|
||||
"""Sign up to CrewAI+"""
|
||||
console.print("Signing in to CrewAI Enterprise...\n", style="bold blue")
|
||||
|
||||
device_code_data = self._get_device_code()
|
||||
self._display_auth_instructions(device_code_data)
|
||||
|
||||
return self._poll_for_token(device_code_data)
|
||||
|
||||
def _get_device_code(self) -> Dict[str, Any]:
|
||||
"""Get the device code to authenticate the user."""
|
||||
|
||||
device_code_payload = {
|
||||
"client_id": self.oauth2_provider.get_client_id(),
|
||||
"scope": "openid",
|
||||
"audience": self.oauth2_provider.get_audience(),
|
||||
}
|
||||
response = requests.post(
|
||||
url=self.oauth2_provider.get_authorize_url(),
|
||||
data=device_code_payload,
|
||||
timeout=20,
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
def _display_auth_instructions(self, device_code_data: Dict[str, str]) -> None:
|
||||
"""Display the authentication instructions to the user."""
|
||||
console.print("1. Navigate to: ", device_code_data["verification_uri_complete"])
|
||||
console.print("2. Enter the following code: ", device_code_data["user_code"])
|
||||
webbrowser.open(device_code_data["verification_uri_complete"])
|
||||
|
||||
def _poll_for_token(self, device_code_data: Dict[str, Any]) -> None:
|
||||
"""Polls the server for the token until it is received, or max attempts are reached."""
|
||||
|
||||
token_payload = {
|
||||
"grant_type": "urn:ietf:params:oauth:grant-type:device_code",
|
||||
"device_code": device_code_data["device_code"],
|
||||
"client_id": self.oauth2_provider.get_client_id(),
|
||||
}
|
||||
|
||||
console.print("\nWaiting for authentication... ", style="bold blue", end="")
|
||||
|
||||
attempts = 0
|
||||
while True and attempts < 10:
|
||||
response = requests.post(
|
||||
self.oauth2_provider.get_token_url(), data=token_payload, timeout=30
|
||||
)
|
||||
token_data = response.json()
|
||||
|
||||
if response.status_code == 200:
|
||||
self._validate_and_save_token(token_data)
|
||||
|
||||
console.print(
|
||||
"Success!",
|
||||
style="bold green",
|
||||
)
|
||||
|
||||
self._login_to_tool_repository()
|
||||
|
||||
console.print(
|
||||
"\n[bold green]Welcome to CrewAI Enterprise![/bold green]\n"
|
||||
)
|
||||
return
|
||||
|
||||
if token_data["error"] not in ("authorization_pending", "slow_down"):
|
||||
raise requests.HTTPError(token_data["error_description"])
|
||||
|
||||
time.sleep(device_code_data["interval"])
|
||||
attempts += 1
|
||||
|
||||
console.print(
|
||||
"Timeout: Failed to get the token. Please try again.", style="bold red"
|
||||
)
|
||||
|
||||
def _validate_and_save_token(self, token_data: Dict[str, Any]) -> None:
|
||||
"""Validates the JWT token and saves the token to the token manager."""
|
||||
|
||||
jwt_token = token_data["access_token"]
|
||||
issuer = self.oauth2_provider.get_issuer()
|
||||
jwt_token_data = {
|
||||
"jwt_token": jwt_token,
|
||||
"jwks_url": self.oauth2_provider.get_jwks_url(),
|
||||
"issuer": issuer,
|
||||
"audience": self.oauth2_provider.get_audience(),
|
||||
}
|
||||
|
||||
decoded_token = validate_jwt_token(**jwt_token_data)
|
||||
|
||||
expires_at = decoded_token.get("exp", 0)
|
||||
self.token_manager.save_tokens(jwt_token, expires_at)
|
||||
|
||||
def _login_to_tool_repository(self) -> None:
|
||||
"""Login to the tool repository."""
|
||||
|
||||
from crewai.cli.tools.main import ToolCommand
|
||||
|
||||
try:
|
||||
console.print(
|
||||
"Now logging you in to the Tool Repository... ",
|
||||
style="bold blue",
|
||||
end="",
|
||||
)
|
||||
|
||||
ToolCommand().login()
|
||||
|
||||
console.print(
|
||||
"Success!\n",
|
||||
style="bold green",
|
||||
)
|
||||
|
||||
settings = Settings()
|
||||
console.print(
|
||||
f"You are authenticated to the tool repository as [bold cyan]'{settings.org_name}'[/bold cyan] ({settings.org_uuid})",
|
||||
style="green",
|
||||
)
|
||||
except Exception:
|
||||
console.print(
|
||||
"\n[bold yellow]Warning:[/bold yellow] Authentication with the Tool Repository failed.",
|
||||
style="yellow",
|
||||
)
|
||||
console.print(
|
||||
"Other features will work normally, but you may experience limitations "
|
||||
"with downloading and publishing tools."
|
||||
"\nRun [bold]crewai login[/bold] to try logging in again.\n",
|
||||
style="yellow",
|
||||
)
|
||||
@@ -1,277 +0,0 @@
|
||||
from typing import Any, Dict, List, Optional
|
||||
|
||||
from rich.console import Console
|
||||
|
||||
from crewai.cli import git
|
||||
from crewai.cli.command import BaseCommand, PlusAPIMixin
|
||||
from crewai.cli.utils import fetch_and_json_env_file, get_project_name
|
||||
|
||||
console = Console()
|
||||
|
||||
|
||||
class DeployCommand(BaseCommand, PlusAPIMixin):
|
||||
"""
|
||||
A class to handle deployment-related operations for CrewAI projects.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
"""
|
||||
Initialize the DeployCommand with project name and API client.
|
||||
"""
|
||||
|
||||
BaseCommand.__init__(self)
|
||||
PlusAPIMixin.__init__(self, telemetry=self._telemetry)
|
||||
self.project_name = get_project_name(require=True)
|
||||
|
||||
def _standard_no_param_error_message(self) -> None:
|
||||
"""
|
||||
Display a standard error message when no UUID or project name is available.
|
||||
"""
|
||||
console.print(
|
||||
"No UUID provided, project pyproject.toml not found or with error.",
|
||||
style="bold red",
|
||||
)
|
||||
|
||||
def _display_deployment_info(self, json_response: Dict[str, Any]) -> None:
|
||||
"""
|
||||
Display deployment information.
|
||||
|
||||
Args:
|
||||
json_response (Dict[str, Any]): The deployment information to display.
|
||||
"""
|
||||
console.print("Deploying the crew...\n", style="bold blue")
|
||||
for key, value in json_response.items():
|
||||
console.print(f"{key.title()}: [green]{value}[/green]")
|
||||
console.print("\nTo check the status of the deployment, run:")
|
||||
console.print("crewai deploy status")
|
||||
console.print(" or")
|
||||
console.print(f'crewai deploy status --uuid "{json_response["uuid"]}"')
|
||||
|
||||
def _display_logs(self, log_messages: List[Dict[str, Any]]) -> None:
|
||||
"""
|
||||
Display log messages.
|
||||
|
||||
Args:
|
||||
log_messages (List[Dict[str, Any]]): The log messages to display.
|
||||
"""
|
||||
for log_message in log_messages:
|
||||
console.print(
|
||||
f"{log_message['timestamp']} - {log_message['level']}: {log_message['message']}"
|
||||
)
|
||||
|
||||
def deploy(self, uuid: Optional[str] = None) -> None:
|
||||
"""
|
||||
Deploy a crew using either UUID or project name.
|
||||
|
||||
Args:
|
||||
uuid (Optional[str]): The UUID of the crew to deploy.
|
||||
"""
|
||||
self._start_deployment_span = self._telemetry.start_deployment_span(uuid)
|
||||
console.print("Starting deployment...", style="bold blue")
|
||||
if uuid:
|
||||
response = self.plus_api_client.deploy_by_uuid(uuid)
|
||||
elif self.project_name:
|
||||
response = self.plus_api_client.deploy_by_name(self.project_name)
|
||||
else:
|
||||
self._standard_no_param_error_message()
|
||||
return
|
||||
|
||||
self._validate_response(response)
|
||||
self._display_deployment_info(response.json())
|
||||
|
||||
def create_crew(self, confirm: bool = False) -> None:
|
||||
"""
|
||||
Create a new crew deployment.
|
||||
"""
|
||||
self._create_crew_deployment_span = (
|
||||
self._telemetry.create_crew_deployment_span()
|
||||
)
|
||||
console.print("Creating deployment...", style="bold blue")
|
||||
env_vars = fetch_and_json_env_file()
|
||||
|
||||
try:
|
||||
remote_repo_url = git.Repository().origin_url()
|
||||
except ValueError:
|
||||
remote_repo_url = None
|
||||
|
||||
if remote_repo_url is None:
|
||||
console.print("No remote repository URL found.", style="bold red")
|
||||
console.print(
|
||||
"Please ensure your project has a valid remote repository.",
|
||||
style="yellow",
|
||||
)
|
||||
return
|
||||
|
||||
self._confirm_input(env_vars, remote_repo_url, confirm)
|
||||
payload = self._create_payload(env_vars, remote_repo_url)
|
||||
response = self.plus_api_client.create_crew(payload)
|
||||
|
||||
self._validate_response(response)
|
||||
self._display_creation_success(response.json())
|
||||
|
||||
def _confirm_input(
|
||||
self, env_vars: Dict[str, str], remote_repo_url: str, confirm: bool
|
||||
) -> None:
|
||||
"""
|
||||
Confirm input parameters with the user.
|
||||
|
||||
Args:
|
||||
env_vars (Dict[str, str]): Environment variables.
|
||||
remote_repo_url (str): Remote repository URL.
|
||||
confirm (bool): Whether to confirm input.
|
||||
"""
|
||||
if not confirm:
|
||||
input(f"Press Enter to continue with the following Env vars: {env_vars}")
|
||||
input(
|
||||
f"Press Enter to continue with the following remote repository: {remote_repo_url}\n"
|
||||
)
|
||||
|
||||
def _create_payload(
|
||||
self,
|
||||
env_vars: Dict[str, str],
|
||||
remote_repo_url: str,
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Create the payload for crew creation.
|
||||
|
||||
Args:
|
||||
remote_repo_url (str): Remote repository URL.
|
||||
env_vars (Dict[str, str]): Environment variables.
|
||||
|
||||
Returns:
|
||||
Dict[str, Any]: The payload for crew creation.
|
||||
"""
|
||||
return {
|
||||
"deploy": {
|
||||
"name": self.project_name,
|
||||
"repo_clone_url": remote_repo_url,
|
||||
"env": env_vars,
|
||||
}
|
||||
}
|
||||
|
||||
def _display_creation_success(self, json_response: Dict[str, Any]) -> None:
|
||||
"""
|
||||
Display success message after crew creation.
|
||||
|
||||
Args:
|
||||
json_response (Dict[str, Any]): The response containing crew information.
|
||||
"""
|
||||
console.print("Deployment created successfully!\n", style="bold green")
|
||||
console.print(
|
||||
f"Name: {self.project_name} ({json_response['uuid']})", style="bold green"
|
||||
)
|
||||
console.print(f"Status: {json_response['status']}", style="bold green")
|
||||
console.print("\nTo (re)deploy the crew, run:")
|
||||
console.print("crewai deploy push")
|
||||
console.print(" or")
|
||||
console.print(f"crewai deploy push --uuid {json_response['uuid']}")
|
||||
|
||||
def list_crews(self) -> None:
|
||||
"""
|
||||
List all available crews.
|
||||
"""
|
||||
console.print("Listing all Crews\n", style="bold blue")
|
||||
|
||||
response = self.plus_api_client.list_crews()
|
||||
json_response = response.json()
|
||||
if response.status_code == 200:
|
||||
self._display_crews(json_response)
|
||||
else:
|
||||
self._display_no_crews_message()
|
||||
|
||||
def _display_crews(self, crews_data: List[Dict[str, Any]]) -> None:
|
||||
"""
|
||||
Display the list of crews.
|
||||
|
||||
Args:
|
||||
crews_data (List[Dict[str, Any]]): List of crew data to display.
|
||||
"""
|
||||
for crew_data in crews_data:
|
||||
console.print(
|
||||
f"- {crew_data['name']} ({crew_data['uuid']}) [blue]{crew_data['status']}[/blue]"
|
||||
)
|
||||
|
||||
def _display_no_crews_message(self) -> None:
|
||||
"""
|
||||
Display a message when no crews are available.
|
||||
"""
|
||||
console.print("You don't have any Crews yet. Let's create one!", style="yellow")
|
||||
console.print(" crewai create crew <crew_name>", style="green")
|
||||
|
||||
def get_crew_status(self, uuid: Optional[str] = None) -> None:
|
||||
"""
|
||||
Get the status of a crew.
|
||||
|
||||
Args:
|
||||
uuid (Optional[str]): The UUID of the crew to check.
|
||||
"""
|
||||
console.print("Fetching deployment status...", style="bold blue")
|
||||
if uuid:
|
||||
response = self.plus_api_client.crew_status_by_uuid(uuid)
|
||||
elif self.project_name:
|
||||
response = self.plus_api_client.crew_status_by_name(self.project_name)
|
||||
else:
|
||||
self._standard_no_param_error_message()
|
||||
return
|
||||
|
||||
self._validate_response(response)
|
||||
self._display_crew_status(response.json())
|
||||
|
||||
def _display_crew_status(self, status_data: Dict[str, str]) -> None:
|
||||
"""
|
||||
Display the status of a crew.
|
||||
|
||||
Args:
|
||||
status_data (Dict[str, str]): The status data to display.
|
||||
"""
|
||||
console.print(f"Name:\t {status_data['name']}")
|
||||
console.print(f"Status:\t {status_data['status']}")
|
||||
|
||||
def get_crew_logs(self, uuid: Optional[str], log_type: str = "deployment") -> None:
|
||||
"""
|
||||
Get logs for a crew.
|
||||
|
||||
Args:
|
||||
uuid (Optional[str]): The UUID of the crew to get logs for.
|
||||
log_type (str): The type of logs to retrieve (default: "deployment").
|
||||
"""
|
||||
self._get_crew_logs_span = self._telemetry.get_crew_logs_span(uuid, log_type)
|
||||
console.print(f"Fetching {log_type} logs...", style="bold blue")
|
||||
|
||||
if uuid:
|
||||
response = self.plus_api_client.crew_by_uuid(uuid, log_type)
|
||||
elif self.project_name:
|
||||
response = self.plus_api_client.crew_by_name(self.project_name, log_type)
|
||||
else:
|
||||
self._standard_no_param_error_message()
|
||||
return
|
||||
|
||||
self._validate_response(response)
|
||||
self._display_logs(response.json())
|
||||
|
||||
def remove_crew(self, uuid: Optional[str]) -> None:
|
||||
"""
|
||||
Remove a crew deployment.
|
||||
|
||||
Args:
|
||||
uuid (Optional[str]): The UUID of the crew to remove.
|
||||
"""
|
||||
self._remove_crew_span = self._telemetry.remove_crew_span(uuid)
|
||||
console.print("Removing deployment...", style="bold blue")
|
||||
|
||||
if uuid:
|
||||
response = self.plus_api_client.delete_crew_by_uuid(uuid)
|
||||
elif self.project_name:
|
||||
response = self.plus_api_client.delete_crew_by_name(self.project_name)
|
||||
else:
|
||||
self._standard_no_param_error_message()
|
||||
return
|
||||
|
||||
if response.status_code == 204:
|
||||
console.print(
|
||||
f"Crew '{self.project_name}' removed successfully.", style="green"
|
||||
)
|
||||
else:
|
||||
console.print(
|
||||
f"Failed to remove crew '{self.project_name}'", style="bold red"
|
||||
)
|
||||
@@ -1,100 +0,0 @@
|
||||
from typing import Any, Dict
|
||||
|
||||
import requests
|
||||
from requests.exceptions import JSONDecodeError, RequestException
|
||||
from rich.console import Console
|
||||
|
||||
from crewai.cli.command import BaseCommand
|
||||
from crewai.cli.settings.main import SettingsCommand
|
||||
from crewai.cli.version import get_crewai_version
|
||||
|
||||
console = Console()
|
||||
|
||||
|
||||
class EnterpriseConfigureCommand(BaseCommand):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.settings_command = SettingsCommand()
|
||||
|
||||
def configure(self, enterprise_url: str) -> None:
|
||||
try:
|
||||
enterprise_url = enterprise_url.rstrip("/")
|
||||
|
||||
oauth_config = self._fetch_oauth_config(enterprise_url)
|
||||
|
||||
self._update_oauth_settings(enterprise_url, oauth_config)
|
||||
|
||||
console.print(
|
||||
f"✅ Successfully configured CrewAI Enterprise with OAuth2 settings from {enterprise_url}",
|
||||
style="bold green",
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
console.print(
|
||||
f"❌ Failed to configure Enterprise settings: {e!s}", style="bold red"
|
||||
)
|
||||
raise SystemExit(1)
|
||||
|
||||
def _fetch_oauth_config(self, enterprise_url: str) -> Dict[str, Any]:
|
||||
oauth_endpoint = f"{enterprise_url}/auth/parameters"
|
||||
|
||||
try:
|
||||
console.print(f"🔄 Fetching OAuth2 configuration from {oauth_endpoint}...")
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"User-Agent": f"CrewAI-CLI/{get_crewai_version()}",
|
||||
"X-Crewai-Version": get_crewai_version(),
|
||||
}
|
||||
response = requests.get(oauth_endpoint, timeout=30, headers=headers)
|
||||
response.raise_for_status()
|
||||
|
||||
try:
|
||||
oauth_config = response.json()
|
||||
except JSONDecodeError:
|
||||
raise ValueError(f"Invalid JSON response from {oauth_endpoint}")
|
||||
|
||||
required_fields = [
|
||||
"audience",
|
||||
"domain",
|
||||
"device_authorization_client_id",
|
||||
"provider",
|
||||
]
|
||||
missing_fields = [
|
||||
field for field in required_fields if field not in oauth_config
|
||||
]
|
||||
|
||||
if missing_fields:
|
||||
raise ValueError(
|
||||
f"Missing required fields in OAuth2 configuration: {', '.join(missing_fields)}"
|
||||
)
|
||||
|
||||
console.print(
|
||||
"✅ Successfully retrieved OAuth2 configuration", style="green"
|
||||
)
|
||||
return oauth_config
|
||||
|
||||
except RequestException as e:
|
||||
raise ValueError(f"Failed to connect to enterprise URL: {e!s}")
|
||||
except Exception as e:
|
||||
raise ValueError(f"Error fetching OAuth2 configuration: {e!s}")
|
||||
|
||||
def _update_oauth_settings(
|
||||
self, enterprise_url: str, oauth_config: Dict[str, Any]
|
||||
) -> None:
|
||||
try:
|
||||
config_mapping = {
|
||||
"enterprise_base_url": enterprise_url,
|
||||
"oauth2_provider": oauth_config["provider"],
|
||||
"oauth2_audience": oauth_config["audience"],
|
||||
"oauth2_client_id": oauth_config["device_authorization_client_id"],
|
||||
"oauth2_domain": oauth_config["domain"],
|
||||
}
|
||||
|
||||
console.print("🔄 Updating local OAuth2 configuration...")
|
||||
|
||||
for key, value in config_mapping.items():
|
||||
self.settings_command.set(key, value)
|
||||
console.print(f" ✓ Set {key}: {value}", style="dim")
|
||||
|
||||
except Exception as e:
|
||||
raise ValueError(f"Failed to update OAuth2 settings: {e!s}")
|
||||
@@ -1,76 +0,0 @@
|
||||
from rich.console import Console
|
||||
from rich.table import Table
|
||||
|
||||
from requests import HTTPError
|
||||
from crewai.cli.command import BaseCommand, PlusAPIMixin
|
||||
from crewai.cli.config import Settings
|
||||
|
||||
console = Console()
|
||||
|
||||
class OrganizationCommand(BaseCommand, PlusAPIMixin):
|
||||
def __init__(self):
|
||||
BaseCommand.__init__(self)
|
||||
PlusAPIMixin.__init__(self, telemetry=self._telemetry)
|
||||
|
||||
def list(self):
|
||||
try:
|
||||
response = self.plus_api_client.get_organizations()
|
||||
response.raise_for_status()
|
||||
orgs = response.json()
|
||||
|
||||
if not orgs:
|
||||
console.print("You don't belong to any organizations yet.", style="yellow")
|
||||
return
|
||||
|
||||
table = Table(title="Your Organizations")
|
||||
table.add_column("Name", style="cyan")
|
||||
table.add_column("ID", style="green")
|
||||
for org in orgs:
|
||||
table.add_row(org["name"], org["uuid"])
|
||||
|
||||
console.print(table)
|
||||
except HTTPError as e:
|
||||
if e.response.status_code == 401:
|
||||
console.print("You are not logged in to any organization. Use 'crewai login' to login.", style="bold red")
|
||||
return
|
||||
console.print(f"Failed to retrieve organization list: {str(e)}", style="bold red")
|
||||
raise SystemExit(1)
|
||||
except Exception as e:
|
||||
console.print(f"Failed to retrieve organization list: {str(e)}", style="bold red")
|
||||
raise SystemExit(1)
|
||||
|
||||
def switch(self, org_id):
|
||||
try:
|
||||
response = self.plus_api_client.get_organizations()
|
||||
response.raise_for_status()
|
||||
orgs = response.json()
|
||||
|
||||
org = next((o for o in orgs if o["uuid"] == org_id), None)
|
||||
if not org:
|
||||
console.print(f"Organization with id '{org_id}' not found.", style="bold red")
|
||||
return
|
||||
|
||||
settings = Settings()
|
||||
settings.org_name = org["name"]
|
||||
settings.org_uuid = org["uuid"]
|
||||
settings.dump()
|
||||
|
||||
console.print(f"Successfully switched to {org['name']} ({org['uuid']})", style="bold green")
|
||||
except HTTPError as e:
|
||||
if e.response.status_code == 401:
|
||||
console.print("You are not logged in to any organization. Use 'crewai login' to login.", style="bold red")
|
||||
return
|
||||
console.print(f"Failed to retrieve organization list: {str(e)}", style="bold red")
|
||||
raise SystemExit(1)
|
||||
except Exception as e:
|
||||
console.print(f"Failed to switch organization: {str(e)}", style="bold red")
|
||||
raise SystemExit(1)
|
||||
|
||||
def current(self):
|
||||
settings = Settings()
|
||||
if settings.org_uuid:
|
||||
console.print(f"Currently logged in to organization {settings.org_name} ({settings.org_uuid})", style="bold green")
|
||||
else:
|
||||
console.print("You're not currently logged in to any organization.", style="yellow")
|
||||
console.print("Use 'crewai org list' to see available organizations.", style="yellow")
|
||||
console.print("Use 'crewai org switch <id>' to switch to an organization.", style="yellow")
|
||||
@@ -28,9 +28,7 @@ def reset_memories_command(
|
||||
"""
|
||||
|
||||
try:
|
||||
if not any(
|
||||
[long, short, entity, kickoff_outputs, knowledge, agent_knowledge, all]
|
||||
):
|
||||
if not any([long, short, entity, kickoff_outputs, knowledge, agent_knowledge, all]):
|
||||
click.echo(
|
||||
"No memory type specified. Please specify at least one type to reset."
|
||||
)
|
||||
|
||||
@@ -1,70 +0,0 @@
|
||||
from typing import Any
|
||||
|
||||
from rich.console import Console
|
||||
from rich.table import Table
|
||||
|
||||
from crewai.cli.command import BaseCommand
|
||||
from crewai.cli.config import HIDDEN_SETTINGS_KEYS, READONLY_SETTINGS_KEYS, Settings
|
||||
|
||||
console = Console()
|
||||
|
||||
|
||||
class SettingsCommand(BaseCommand):
|
||||
"""A class to handle CLI configuration commands."""
|
||||
|
||||
def __init__(self, settings_kwargs: dict[str, Any] | None = None):
|
||||
super().__init__()
|
||||
settings_kwargs = settings_kwargs or {}
|
||||
self.settings = Settings(**settings_kwargs)
|
||||
|
||||
def list(self) -> None:
|
||||
"""List all CLI configuration parameters."""
|
||||
table = Table(title="CrewAI CLI Configuration")
|
||||
table.add_column("Setting", style="cyan", no_wrap=True)
|
||||
table.add_column("Value", style="green")
|
||||
table.add_column("Description", style="yellow")
|
||||
|
||||
# Add all settings to the table
|
||||
for field_name, field_info in Settings.model_fields.items():
|
||||
if field_name in HIDDEN_SETTINGS_KEYS:
|
||||
# Do not display hidden settings
|
||||
continue
|
||||
|
||||
current_value = getattr(self.settings, field_name)
|
||||
description = field_info.description or "No description available"
|
||||
display_value = (
|
||||
str(current_value) if current_value is not None else "Not set"
|
||||
)
|
||||
|
||||
table.add_row(field_name, display_value, description)
|
||||
|
||||
console.print(table)
|
||||
|
||||
def set(self, key: str, value: str) -> None:
|
||||
"""Set a CLI configuration parameter."""
|
||||
|
||||
readonly_settings = READONLY_SETTINGS_KEYS + HIDDEN_SETTINGS_KEYS
|
||||
|
||||
if not hasattr(self.settings, key) or key in readonly_settings:
|
||||
console.print(
|
||||
f"Error: Unknown or readonly configuration key '{key}'",
|
||||
style="bold red",
|
||||
)
|
||||
console.print("Available keys:", style="yellow")
|
||||
for field_name in Settings.model_fields.keys():
|
||||
if field_name not in readonly_settings:
|
||||
console.print(f" - {field_name}", style="yellow")
|
||||
raise SystemExit(1)
|
||||
|
||||
setattr(self.settings, key, value)
|
||||
self.settings.dump()
|
||||
|
||||
console.print(f"Successfully set '{key}' to '{value}'", style="bold green")
|
||||
|
||||
def reset_all_settings(self) -> None:
|
||||
"""Reset all CLI configuration parameters to default values."""
|
||||
self.settings.reset()
|
||||
console.print(
|
||||
"Successfully reset all configuration parameters to default values. It is recommended to run [bold yellow]'crewai login'[/bold yellow] to re-authenticate.",
|
||||
style="bold green",
|
||||
)
|
||||
@@ -1,68 +0,0 @@
|
||||
#!/usr/bin/env python
|
||||
import sys
|
||||
import warnings
|
||||
|
||||
from datetime import datetime
|
||||
|
||||
from {{folder_name}}.crew import {{crew_name}}
|
||||
|
||||
warnings.filterwarnings("ignore", category=SyntaxWarning, module="pysbd")
|
||||
|
||||
# This main file is intended to be a way for you to run your
|
||||
# crew locally, so refrain from adding unnecessary logic into this file.
|
||||
# Replace with inputs you want to test with, it will automatically
|
||||
# interpolate any tasks and agents information
|
||||
|
||||
def run():
|
||||
"""
|
||||
Run the crew.
|
||||
"""
|
||||
inputs = {
|
||||
'topic': 'AI LLMs',
|
||||
'current_year': str(datetime.now().year)
|
||||
}
|
||||
|
||||
try:
|
||||
{{crew_name}}().crew().kickoff(inputs=inputs)
|
||||
except Exception as e:
|
||||
raise Exception(f"An error occurred while running the crew: {e}")
|
||||
|
||||
|
||||
def train():
|
||||
"""
|
||||
Train the crew for a given number of iterations.
|
||||
"""
|
||||
inputs = {
|
||||
"topic": "AI LLMs",
|
||||
'current_year': str(datetime.now().year)
|
||||
}
|
||||
try:
|
||||
{{crew_name}}().crew().train(n_iterations=int(sys.argv[1]), filename=sys.argv[2], inputs=inputs)
|
||||
|
||||
except Exception as e:
|
||||
raise Exception(f"An error occurred while training the crew: {e}")
|
||||
|
||||
def replay():
|
||||
"""
|
||||
Replay the crew execution from a specific task.
|
||||
"""
|
||||
try:
|
||||
{{crew_name}}().crew().replay(task_id=sys.argv[1])
|
||||
|
||||
except Exception as e:
|
||||
raise Exception(f"An error occurred while replaying the crew: {e}")
|
||||
|
||||
def test():
|
||||
"""
|
||||
Test the crew execution and returns the results.
|
||||
"""
|
||||
inputs = {
|
||||
"topic": "AI LLMs",
|
||||
"current_year": str(datetime.now().year)
|
||||
}
|
||||
|
||||
try:
|
||||
{{crew_name}}().crew().test(n_iterations=int(sys.argv[1]), eval_llm=sys.argv[2], inputs=inputs)
|
||||
|
||||
except Exception as e:
|
||||
raise Exception(f"An error occurred while testing the crew: {e}")
|
||||
@@ -1,5 +1,3 @@
|
||||
from typing import List
|
||||
|
||||
from crewai import Agent, Crew, Process, Task
|
||||
from crewai.agents.agent_builder.base_agent import BaseAgent
|
||||
from crewai.project import CrewBase, agent, crew, task
|
||||
@@ -13,8 +11,8 @@ from crewai.project import CrewBase, agent, crew, task
|
||||
class PoemCrew:
|
||||
"""Poem Crew"""
|
||||
|
||||
agents: List[BaseAgent]
|
||||
tasks: List[Task]
|
||||
agents: list[BaseAgent]
|
||||
tasks: list[Task]
|
||||
|
||||
# Learn more about YAML configuration files here:
|
||||
# Agents: https://docs.crewai.com/concepts/agents#yaml-configuration-recommended
|
||||
|
||||
@@ -1,53 +0,0 @@
|
||||
#!/usr/bin/env python
|
||||
from random import randint
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from crewai.flow import Flow, listen, start
|
||||
|
||||
from {{folder_name}}.crews.poem_crew.poem_crew import PoemCrew
|
||||
|
||||
|
||||
class PoemState(BaseModel):
|
||||
sentence_count: int = 1
|
||||
poem: str = ""
|
||||
|
||||
|
||||
class PoemFlow(Flow[PoemState]):
|
||||
|
||||
@start()
|
||||
def generate_sentence_count(self):
|
||||
print("Generating sentence count")
|
||||
self.state.sentence_count = randint(1, 5)
|
||||
|
||||
@listen(generate_sentence_count)
|
||||
def generate_poem(self):
|
||||
print("Generating poem")
|
||||
result = (
|
||||
PoemCrew()
|
||||
.crew()
|
||||
.kickoff(inputs={"sentence_count": self.state.sentence_count})
|
||||
)
|
||||
|
||||
print("Poem generated", result.raw)
|
||||
self.state.poem = result.raw
|
||||
|
||||
@listen(generate_poem)
|
||||
def save_poem(self):
|
||||
print("Saving poem")
|
||||
with open("poem.txt", "w") as f:
|
||||
f.write(self.state.poem)
|
||||
|
||||
|
||||
def kickoff():
|
||||
poem_flow = PoemFlow()
|
||||
poem_flow.kickoff()
|
||||
|
||||
|
||||
def plot():
|
||||
poem_flow = PoemFlow()
|
||||
poem_flow.plot()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
kickoff()
|
||||
@@ -1,5 +1,3 @@
|
||||
from typing import Type
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from crewai.tools import BaseTool
|
||||
@@ -14,7 +12,7 @@ class MyCustomToolInput(BaseModel):
|
||||
class MyCustomTool(BaseTool):
|
||||
name: str = "Name of my tool"
|
||||
description: str = "Clear description for what this tool is useful for, your agent will need this information to use it."
|
||||
args_schema: Type[BaseModel] = MyCustomToolInput
|
||||
args_schema: type[BaseModel] = MyCustomToolInput
|
||||
|
||||
def _run(self, argument: str) -> str:
|
||||
# Implementation goes here
|
||||
|
||||
@@ -1,235 +0,0 @@
|
||||
import base64
|
||||
import os
|
||||
import subprocess
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
import click
|
||||
from rich.console import Console
|
||||
|
||||
from crewai.cli import git
|
||||
from crewai.cli.command import BaseCommand, PlusAPIMixin
|
||||
from crewai.cli.config import Settings
|
||||
from crewai.cli.utils import (
|
||||
build_env_with_tool_repository_credentials,
|
||||
extract_available_exports,
|
||||
get_project_description,
|
||||
get_project_name,
|
||||
get_project_version,
|
||||
tree_copy,
|
||||
tree_find_and_replace,
|
||||
)
|
||||
|
||||
console = Console()
|
||||
|
||||
|
||||
class ToolCommand(BaseCommand, PlusAPIMixin):
|
||||
"""
|
||||
A class to handle tool repository related operations for CrewAI projects.
|
||||
"""
|
||||
|
||||
def __init__(self):
|
||||
BaseCommand.__init__(self)
|
||||
PlusAPIMixin.__init__(self, telemetry=self._telemetry)
|
||||
|
||||
def create(self, handle: str):
|
||||
self._ensure_not_in_project()
|
||||
|
||||
folder_name = handle.replace(" ", "_").replace("-", "_").lower()
|
||||
class_name = handle.replace("_", " ").replace("-", " ").title().replace(" ", "")
|
||||
|
||||
project_root = Path(folder_name)
|
||||
if project_root.exists():
|
||||
click.secho(f"Folder {folder_name} already exists.", fg="red")
|
||||
raise SystemExit
|
||||
os.makedirs(project_root)
|
||||
|
||||
click.secho(f"Creating custom tool {folder_name}...", fg="green", bold=True)
|
||||
|
||||
template_dir = Path(__file__).parent.parent / "templates" / "tool"
|
||||
tree_copy(template_dir, project_root)
|
||||
tree_find_and_replace(project_root, "{{folder_name}}", folder_name)
|
||||
tree_find_and_replace(project_root, "{{class_name}}", class_name)
|
||||
|
||||
old_directory = os.getcwd()
|
||||
os.chdir(project_root)
|
||||
try:
|
||||
self.login()
|
||||
subprocess.run(["git", "init"], check=True) # noqa: S607
|
||||
console.print(
|
||||
f"[green]Created custom tool [bold]{folder_name}[/bold]. Run [bold]cd {project_root}[/bold] to start working.[/green]"
|
||||
)
|
||||
finally:
|
||||
os.chdir(old_directory)
|
||||
|
||||
def publish(self, is_public: bool, force: bool = False):
|
||||
if not git.Repository().is_synced() and not force:
|
||||
console.print(
|
||||
"[bold red]Failed to publish tool.[/bold red]\n"
|
||||
"Local changes need to be resolved before publishing. Please do the following:\n"
|
||||
"* [bold]Commit[/bold] your changes.\n"
|
||||
"* [bold]Push[/bold] to sync with the remote.\n"
|
||||
"* [bold]Pull[/bold] the latest changes from the remote.\n"
|
||||
"\nOnce your repository is up-to-date, retry publishing the tool."
|
||||
)
|
||||
raise SystemExit()
|
||||
|
||||
project_name = get_project_name(require=True)
|
||||
assert isinstance(project_name, str) # noqa: S101
|
||||
|
||||
project_version = get_project_version(require=True)
|
||||
assert isinstance(project_version, str) # noqa: S101
|
||||
|
||||
project_description = get_project_description(require=False)
|
||||
encoded_tarball = None
|
||||
|
||||
console.print("[bold blue]Discovering tools from your project...[/bold blue]")
|
||||
available_exports = extract_available_exports()
|
||||
|
||||
if available_exports:
|
||||
console.print(
|
||||
f"[green]Found these tools to publish: {', '.join([e['name'] for e in available_exports])}[/green]"
|
||||
)
|
||||
self._print_current_organization()
|
||||
|
||||
with tempfile.TemporaryDirectory() as temp_build_dir:
|
||||
subprocess.run( # noqa: S603
|
||||
["uv", "build", "--sdist", "--out-dir", temp_build_dir], # noqa: S607
|
||||
check=True,
|
||||
capture_output=False,
|
||||
)
|
||||
|
||||
tarball_filename = next(
|
||||
(f for f in os.listdir(temp_build_dir) if f.endswith(".tar.gz")), None
|
||||
)
|
||||
if not tarball_filename:
|
||||
console.print(
|
||||
"Project build failed. Please ensure that the command `uv build --sdist` completes successfully.",
|
||||
style="bold red",
|
||||
)
|
||||
raise SystemExit
|
||||
|
||||
tarball_path = os.path.join(temp_build_dir, tarball_filename)
|
||||
with open(tarball_path, "rb") as file:
|
||||
tarball_contents = file.read()
|
||||
|
||||
encoded_tarball = base64.b64encode(tarball_contents).decode("utf-8")
|
||||
|
||||
console.print("[bold blue]Publishing tool to repository...[/bold blue]")
|
||||
publish_response = self.plus_api_client.publish_tool(
|
||||
handle=project_name,
|
||||
is_public=is_public,
|
||||
version=project_version,
|
||||
description=project_description,
|
||||
encoded_file=f"data:application/x-gzip;base64,{encoded_tarball}",
|
||||
available_exports=available_exports,
|
||||
)
|
||||
|
||||
self._validate_response(publish_response)
|
||||
|
||||
published_handle = publish_response.json()["handle"]
|
||||
console.print(
|
||||
f"Successfully published `{published_handle}` ({project_version}).\n\n"
|
||||
+ "⚠️ Security checks are running in the background. Your tool will be available once these are complete.\n"
|
||||
+ f"You can monitor the status or access your tool here:\nhttps://app.crewai.com/crewai_plus/tools/{published_handle}",
|
||||
style="bold green",
|
||||
)
|
||||
|
||||
def install(self, handle: str):
|
||||
self._print_current_organization()
|
||||
get_response = self.plus_api_client.get_tool(handle)
|
||||
|
||||
if get_response.status_code == 404:
|
||||
console.print(
|
||||
"No tool found with this name. Please ensure the tool was published and you have access to it.",
|
||||
style="bold red",
|
||||
)
|
||||
raise SystemExit
|
||||
if get_response.status_code != 200:
|
||||
console.print(
|
||||
"Failed to get tool details. Please try again later.", style="bold red"
|
||||
)
|
||||
raise SystemExit
|
||||
|
||||
self._add_package(get_response.json())
|
||||
|
||||
console.print(f"Successfully installed {handle}", style="bold green")
|
||||
|
||||
def login(self) -> None:
|
||||
login_response = self.plus_api_client.login_to_tool_repository()
|
||||
|
||||
if login_response.status_code != 200:
|
||||
console.print(
|
||||
"Authentication failed. Verify access to the tool repository, or try `crewai login`. ",
|
||||
style="bold red",
|
||||
)
|
||||
raise SystemExit
|
||||
|
||||
login_response_json = login_response.json()
|
||||
|
||||
settings = Settings()
|
||||
settings.tool_repository_username = login_response_json["credential"][
|
||||
"username"
|
||||
]
|
||||
settings.tool_repository_password = login_response_json["credential"][
|
||||
"password"
|
||||
]
|
||||
settings.org_uuid = login_response_json["current_organization"]["uuid"]
|
||||
settings.org_name = login_response_json["current_organization"]["name"]
|
||||
settings.dump()
|
||||
|
||||
def _add_package(self, tool_details: dict[str, Any]):
|
||||
is_from_pypi = tool_details.get("source", None) == "pypi"
|
||||
tool_handle = tool_details["handle"]
|
||||
repository_handle = tool_details["repository"]["handle"]
|
||||
repository_url = tool_details["repository"]["url"]
|
||||
index = f"{repository_handle}={repository_url}"
|
||||
|
||||
add_package_command = [
|
||||
"uv",
|
||||
"add",
|
||||
]
|
||||
|
||||
if is_from_pypi:
|
||||
add_package_command.append(tool_handle)
|
||||
else:
|
||||
add_package_command.extend(["--index", index, tool_handle])
|
||||
|
||||
add_package_result = subprocess.run( # noqa: S603
|
||||
add_package_command,
|
||||
capture_output=False,
|
||||
env=build_env_with_tool_repository_credentials(repository_handle),
|
||||
text=True,
|
||||
check=True,
|
||||
)
|
||||
|
||||
if add_package_result.stderr:
|
||||
click.echo(add_package_result.stderr, err=True)
|
||||
raise SystemExit
|
||||
|
||||
def _ensure_not_in_project(self):
|
||||
if os.path.isfile("./pyproject.toml"):
|
||||
console.print(
|
||||
"[bold red]Oops! It looks like you're inside a project.[/bold red]"
|
||||
)
|
||||
console.print(
|
||||
"You can't create a new tool while inside an existing project."
|
||||
)
|
||||
console.print(
|
||||
"[bold yellow]Tip:[/bold yellow] Navigate to a different directory and try again."
|
||||
)
|
||||
raise SystemExit
|
||||
|
||||
def _print_current_organization(self) -> None:
|
||||
settings = Settings()
|
||||
if settings.org_uuid:
|
||||
console.print(
|
||||
f"Current organization: {settings.org_name} ({settings.org_uuid})",
|
||||
style="bold blue",
|
||||
)
|
||||
else:
|
||||
console.print(
|
||||
"No organization currently set. We recommend setting one before using: `crewai org switch <org_id>` command.",
|
||||
style="yellow",
|
||||
)
|
||||
@@ -1,9 +1,8 @@
|
||||
import contextvars
|
||||
import os
|
||||
from contextlib import contextmanager
|
||||
from typing import Optional
|
||||
|
||||
_platform_integration_token: contextvars.ContextVar[Optional[str]] = (
|
||||
_platform_integration_token: contextvars.ContextVar[str | None] = (
|
||||
contextvars.ContextVar("platform_integration_token", default=None)
|
||||
)
|
||||
|
||||
@@ -12,7 +11,7 @@ def set_platform_integration_token(integration_token: str) -> None:
|
||||
_platform_integration_token.set(integration_token)
|
||||
|
||||
|
||||
def get_platform_integration_token() -> Optional[str]:
|
||||
def get_platform_integration_token() -> str | None:
|
||||
token = _platform_integration_token.get()
|
||||
if token is None:
|
||||
token = os.getenv("CREWAI_PLATFORM_INTEGRATION_TOKEN")
|
||||
|
||||
@@ -26,7 +26,11 @@ class LLMGuardrailStartedEvent(BaseEvent):
|
||||
if isinstance(self.guardrail, (LLMGuardrail, HallucinationGuardrail)):
|
||||
self.guardrail = self.guardrail.description.strip()
|
||||
elif isinstance(self.guardrail, Callable):
|
||||
self.guardrail = getsource(self.guardrail).strip()
|
||||
try:
|
||||
self.guardrail = getsource(self.guardrail).strip()
|
||||
except (OSError, TypeError):
|
||||
# Can't get source for lambdas or built-in functions
|
||||
self.guardrail = f"<{self.guardrail.__name__ if hasattr(self.guardrail, '__name__') else 'callable'}>"
|
||||
|
||||
|
||||
class LLMGuardrailCompletedEvent(BaseEvent):
|
||||
|
||||
@@ -1,3 +1,4 @@
|
||||
|
||||
def get_legend_items(colors):
|
||||
return [
|
||||
{"label": "Start Method", "color": colors["start"]},
|
||||
@@ -31,23 +32,23 @@ def generate_legend_items_html(legend_items):
|
||||
style = "dashed" if item["dashed"] else "solid"
|
||||
legend_items_html += f"""
|
||||
<div class="legend-item">
|
||||
<div class="legend-color-box" style="background-color: {item["color"]}; border: 2px {style} {item["border"]}; border-radius: 5px;"></div>
|
||||
<div>{item["label"]}</div>
|
||||
<div class="legend-color-box" style="background-color: {item['color']}; border: 2px {style} {item['border']}; border-radius: 5px;"></div>
|
||||
<div>{item['label']}</div>
|
||||
</div>
|
||||
"""
|
||||
elif item.get("dashed") is not None:
|
||||
style = "dashed" if item["dashed"] else "solid"
|
||||
legend_items_html += f"""
|
||||
<div class="legend-item">
|
||||
<div class="legend-{style}" style="border-bottom: 2px {style} {item["color"]}; border-radius: 5px;"></div>
|
||||
<div>{item["label"]}</div>
|
||||
<div class="legend-{style}" style="border-bottom: 2px {style} {item['color']}; border-radius: 5px;"></div>
|
||||
<div>{item['label']}</div>
|
||||
</div>
|
||||
"""
|
||||
else:
|
||||
legend_items_html += f"""
|
||||
<div class="legend-item">
|
||||
<div class="legend-color-box" style="background-color: {item["color"]}; border-radius: 5px;"></div>
|
||||
<div>{item["label"]}</div>
|
||||
<div class="legend-color-box" style="background-color: {item['color']}; border-radius: 5px;"></div>
|
||||
<div>{item['label']}</div>
|
||||
</div>
|
||||
"""
|
||||
return legend_items_html
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
from collections.abc import Callable
|
||||
from functools import wraps
|
||||
from typing import Callable
|
||||
|
||||
from crewai import Crew
|
||||
from crewai.project.utils import memoize
|
||||
|
||||
@@ -72,11 +72,11 @@ def CrewBase(cls: T) -> T: # noqa: N802
|
||||
|
||||
# Add close mcp server method to after kickoff
|
||||
bound_method = self._create_close_mcp_server_method()
|
||||
self._after_kickoff["_close_mcp_server"] = bound_method
|
||||
self._after_kickoff['_close_mcp_server'] = bound_method
|
||||
|
||||
def _create_close_mcp_server_method(self):
|
||||
def _close_mcp_server(self, instance, outputs):
|
||||
adapter = getattr(self, "_mcp_server_adapter", None)
|
||||
adapter = getattr(self, '_mcp_server_adapter', None)
|
||||
if adapter is not None:
|
||||
try:
|
||||
adapter.stop()
|
||||
@@ -87,7 +87,6 @@ def CrewBase(cls: T) -> T: # noqa: N802
|
||||
_close_mcp_server.is_after_kickoff = True
|
||||
|
||||
import types
|
||||
|
||||
return types.MethodType(_close_mcp_server, self)
|
||||
|
||||
def get_mcp_tools(self, *tool_names: list[str]) -> list[BaseTool]:
|
||||
@@ -96,14 +95,16 @@ def CrewBase(cls: T) -> T: # noqa: N802
|
||||
|
||||
from crewai_tools import MCPServerAdapter # type: ignore[import-untyped]
|
||||
|
||||
adapter = getattr(self, "_mcp_server_adapter", None)
|
||||
adapter = getattr(self, '_mcp_server_adapter', None)
|
||||
if not adapter:
|
||||
self._mcp_server_adapter = MCPServerAdapter(
|
||||
self.mcp_server_params, connect_timeout=self.mcp_connect_timeout
|
||||
self.mcp_server_params,
|
||||
connect_timeout=self.mcp_connect_timeout
|
||||
)
|
||||
|
||||
return self._mcp_server_adapter.tools.filter_by_names(tool_names or None)
|
||||
|
||||
|
||||
def load_configurations(self):
|
||||
"""Load agent and task configurations from YAML files."""
|
||||
if isinstance(self.original_agents_config_path, str):
|
||||
@@ -208,13 +209,9 @@ def CrewBase(cls: T) -> T: # noqa: N802
|
||||
|
||||
if function_calling_llm := agent_info.get("function_calling_llm"):
|
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try:
|
||||
self.agents_config[agent_name]["function_calling_llm"] = llms[
|
||||
function_calling_llm
|
||||
]()
|
||||
self.agents_config[agent_name]["function_calling_llm"] = llms[function_calling_llm]()
|
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except KeyError:
|
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self.agents_config[agent_name]["function_calling_llm"] = (
|
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function_calling_llm
|
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|
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self.agents_config[agent_name]["function_calling_llm"] = function_calling_llm
|
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|
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if step_callback := agent_info.get("step_callback"):
|
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self.agents_config[agent_name]["step_callback"] = callbacks[
|
||||
|
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@@ -1,11 +1,12 @@
|
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from typing import Any
|
||||
|
||||
import pytest
|
||||
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|
||||
|
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|
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|
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|
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|
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|
||||
|
||||
|
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# Concrete implementation for testing
|
||||
|
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@@ -1,4 +1,5 @@
|
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import pytest
|
||||
|
||||
from crewai.agents import parser
|
||||
from crewai.agents.parser import (
|
||||
AgentAction,
|
||||
|
||||
@@ -4,6 +4,8 @@ from typing import cast
|
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from unittest.mock import Mock, patch
|
||||
|
||||
import pytest
|
||||
from pydantic import BaseModel, Field
|
||||
|
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from crewai import LLM, Agent
|
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from crewai.events.event_bus import crewai_event_bus
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|
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@@ -12,7 +14,6 @@ from crewai.flow import Flow, start
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|
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from crewai.llms.base_llm import BaseLLM
|
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|
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|
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|
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|
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|
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|
||||
|
||||
result = agent.kickoff(messages="Top 10 best players in the world?")
|
||||
|
||||
assert len(guardrail_events["started"]) == 2
|
||||
assert len(guardrail_events["completed"]) == 2
|
||||
assert not guardrail_events["completed"][0].success
|
||||
assert guardrail_events["completed"][1].success
|
||||
# Guardrail may be called 2 or 3 times depending on LLM response
|
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assert len(guardrail_events["started"]) >= 2
|
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assert len(guardrail_events["completed"]) >= 2
|
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# At least one should fail and the last one should succeed
|
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assert any(not event.success for event in guardrail_events["completed"][:-1])
|
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assert guardrail_events["completed"][-1].success
|
||||
assert (
|
||||
"Here are the top 10 best soccer players in the world, focusing exclusively on Brazilian players"
|
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in result.raw
|
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@@ -435,6 +438,7 @@ def test_guardrail_reached_attempt_limit():
|
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|
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|
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@pytest.mark.vcr(filter_headers=["authorization"])
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@pytest.mark.requires_local_services
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def test_agent_output_when_guardrail_returns_base_model():
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class Player(BaseModel):
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name: str
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cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
- REDACTED
|
||||
openai-processing-ms:
|
||||
- '14224'
|
||||
openai-version:
|
||||
@@ -728,7 +728,7 @@ interactions:
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
- REDACTED
|
||||
openai-processing-ms:
|
||||
- '814'
|
||||
openai-version:
|
||||
@@ -982,7 +982,7 @@ interactions:
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
- REDACTED
|
||||
openai-processing-ms:
|
||||
- '30105'
|
||||
openai-version:
|
||||
|
||||
@@ -237,7 +237,7 @@ interactions:
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
- REDACTED
|
||||
openai-processing-ms:
|
||||
- '7947'
|
||||
openai-version:
|
||||
@@ -386,7 +386,7 @@ interactions:
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
- REDACTED
|
||||
openai-processing-ms:
|
||||
- '1302'
|
||||
openai-version:
|
||||
@@ -600,7 +600,7 @@ interactions:
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
- REDACTED
|
||||
openai-processing-ms:
|
||||
- '15866'
|
||||
openai-version:
|
||||
@@ -763,7 +763,7 @@ interactions:
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
- REDACTED
|
||||
openai-processing-ms:
|
||||
- '1348'
|
||||
openai-version:
|
||||
@@ -1022,7 +1022,7 @@ interactions:
|
||||
cf-cache-status:
|
||||
- DYNAMIC
|
||||
openai-organization:
|
||||
- crewai-iuxna1
|
||||
- REDACTED
|
||||
openai-processing-ms:
|
||||
- '24425'
|
||||
openai-version:
|
||||
|
||||
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Reference in New Issue
Block a user