Compare commits

...

7 Commits

Author SHA1 Message Date
Devin AI
9a6ede9ae5 Fix type-checker errors in llm.py
Co-Authored-By: Joe Moura <joao@crewai.com>
2025-03-24 11:43:00 +00:00
Devin AI
6df3007190 Improve code with type hints, error handling, and additional tests
Co-Authored-By: Joe Moura <joao@crewai.com>
2025-03-24 11:38:32 +00:00
Devin AI
3060c6f919 Fix Gemini API additionalProperties error (issue #2457)
Co-Authored-By: Joe Moura <joao@crewai.com>
2025-03-24 11:32:29 +00:00
Brandon Hancock (bhancock_ai)
ed1f009c64 Feat/improve yaml extraction (#2428)
* Support wildcard handling in `emit()`

Change `emit()` to call handlers registered for parent classes using
`isinstance()`. Ensures that base event handlers receive derived
events.

* Fix failing test

* Remove unused variable

* update interpolation to work with example response types in yaml docs

* make tests

* fix circular deps

* Fixing interpolation imports

* Improve test

---------

Co-authored-by: Vinicius Brasil <vini@hey.com>
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
2025-03-21 18:59:55 -07:00
Matisse
bb3829a9ed docs: Update model reference in LLM configuration (#2267)
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2025-03-21 15:12:26 -04:00
Fernando Galves
0a116202f0 Update the context window size for Amazon Bedrock FM- llm.py (#2304)
Update the context window size for Amazon Bedrock Foundation Models.

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
2025-03-21 14:48:25 -04:00
Stefano Baccianella
4daa88fa59 As explained in https://github.com/mangiucugna/json_repair?tab=readme-ov-file#performance-considerations we can skip a wasteful json.loads() here and save quite some time (#2397)
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
2025-03-21 14:25:19 -04:00
11 changed files with 501 additions and 131 deletions

View File

@@ -59,7 +59,7 @@ There are three ways to configure LLMs in CrewAI. Choose the method that best fi
goal: Conduct comprehensive research and analysis
backstory: A dedicated research professional with years of experience
verbose: true
llm: openai/gpt-4o-mini # your model here
llm: openai/gpt-4o-mini # your model here
# (see provider configuration examples below for more)
```
@@ -111,7 +111,7 @@ There are three ways to configure LLMs in CrewAI. Choose the method that best fi
## Provider Configuration Examples
CrewAI supports a multitude of LLM providers, each offering unique features, authentication methods, and model capabilities.
CrewAI supports a multitude of LLM providers, each offering unique features, authentication methods, and model capabilities.
In this section, you'll find detailed examples that help you select, configure, and optimize the LLM that best fits your project's needs.
<AccordionGroup>
@@ -121,7 +121,7 @@ In this section, you'll find detailed examples that help you select, configure,
```toml Code
# Required
OPENAI_API_KEY=sk-...
# Optional
OPENAI_API_BASE=<custom-base-url>
OPENAI_ORGANIZATION=<your-org-id>
@@ -226,7 +226,7 @@ In this section, you'll find detailed examples that help you select, configure,
AZURE_API_KEY=<your-api-key>
AZURE_API_BASE=<your-resource-url>
AZURE_API_VERSION=<api-version>
# Optional
AZURE_AD_TOKEN=<your-azure-ad-token>
AZURE_API_TYPE=<your-azure-api-type>
@@ -289,7 +289,7 @@ In this section, you'll find detailed examples that help you select, configure,
| Mistral 8x7B Instruct | Up to 32k tokens | An MOE LLM that follows instructions, completes requests, and generates creative text. |
</Accordion>
<Accordion title="Amazon SageMaker">
```toml Code
AWS_ACCESS_KEY_ID=<your-access-key>
@@ -474,7 +474,7 @@ In this section, you'll find detailed examples that help you select, configure,
WATSONX_URL=<your-url>
WATSONX_APIKEY=<your-apikey>
WATSONX_PROJECT_ID=<your-project-id>
# Optional
WATSONX_TOKEN=<your-token>
WATSONX_DEPLOYMENT_SPACE_ID=<your-space-id>
@@ -491,7 +491,7 @@ In this section, you'll find detailed examples that help you select, configure,
<Accordion title="Ollama (Local LLMs)">
1. Install Ollama: [ollama.ai](https://ollama.ai/)
2. Run a model: `ollama run llama2`
2. Run a model: `ollama run llama3`
3. Configure:
```python Code
@@ -600,7 +600,7 @@ In this section, you'll find detailed examples that help you select, configure,
```toml Code
OPENROUTER_API_KEY=<your-api-key>
```
Example usage in your CrewAI project:
```python Code
llm = LLM(
@@ -723,7 +723,7 @@ Learn how to get the most out of your LLM configuration:
- Small tasks (up to 4K tokens): Standard models
- Medium tasks (between 4K-32K): Enhanced models
- Large tasks (over 32K): Large context models
```python
# Configure model with appropriate settings
llm = LLM(
@@ -760,11 +760,11 @@ Learn how to get the most out of your LLM configuration:
<Warning>
Most authentication issues can be resolved by checking API key format and environment variable names.
</Warning>
```bash
# OpenAI
OPENAI_API_KEY=sk-...
# Anthropic
ANTHROPIC_API_KEY=sk-ant-...
```
@@ -773,11 +773,11 @@ Learn how to get the most out of your LLM configuration:
<Check>
Always include the provider prefix in model names
</Check>
```python
# Correct
llm = LLM(model="openai/gpt-4")
# Incorrect
llm = LLM(model="gpt-4")
```
@@ -786,5 +786,10 @@ Learn how to get the most out of your LLM configuration:
<Tip>
Use larger context models for extensive tasks
</Tip>
```python
# Large context model
llm = LLM(model="openai/gpt-4o") # 128K tokens
```
</Tab>
</Tabs>

View File

@@ -25,6 +25,7 @@ from crewai.tools.base_tool import BaseTool, Tool
from crewai.utilities import I18N, Logger, RPMController
from crewai.utilities.config import process_config
from crewai.utilities.converter import Converter
from crewai.utilities.string_utils import interpolate_only
T = TypeVar("T", bound="BaseAgent")
@@ -333,9 +334,15 @@ class BaseAgent(ABC, BaseModel):
self._original_backstory = self.backstory
if inputs:
self.role = self._original_role.format(**inputs)
self.goal = self._original_goal.format(**inputs)
self.backstory = self._original_backstory.format(**inputs)
self.role = interpolate_only(
input_string=self._original_role, inputs=inputs
)
self.goal = interpolate_only(
input_string=self._original_goal, inputs=inputs
)
self.backstory = interpolate_only(
input_string=self._original_backstory, inputs=inputs
)
def set_cache_handler(self, cache_handler: CacheHandler) -> None:
"""Set the cache handler for the agent.

View File

@@ -114,6 +114,60 @@ LLM_CONTEXT_WINDOW_SIZES = {
"Llama-3.2-11B-Vision-Instruct": 16384,
"Meta-Llama-3.2-3B-Instruct": 4096,
"Meta-Llama-3.2-1B-Instruct": 16384,
# bedrock
"us.amazon.nova-pro-v1:0": 300000,
"us.amazon.nova-micro-v1:0": 128000,
"us.amazon.nova-lite-v1:0": 300000,
"us.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000,
"us.anthropic.claude-3-5-haiku-20241022-v1:0": 200000,
"us.anthropic.claude-3-5-sonnet-20241022-v2:0": 200000,
"us.anthropic.claude-3-7-sonnet-20250219-v1:0": 200000,
"us.anthropic.claude-3-sonnet-20240229-v1:0": 200000,
"us.anthropic.claude-3-opus-20240229-v1:0": 200000,
"us.anthropic.claude-3-haiku-20240307-v1:0": 200000,
"us.meta.llama3-2-11b-instruct-v1:0": 128000,
"us.meta.llama3-2-3b-instruct-v1:0": 131000,
"us.meta.llama3-2-90b-instruct-v1:0": 128000,
"us.meta.llama3-2-1b-instruct-v1:0": 131000,
"us.meta.llama3-1-8b-instruct-v1:0": 128000,
"us.meta.llama3-1-70b-instruct-v1:0": 128000,
"us.meta.llama3-3-70b-instruct-v1:0": 128000,
"us.meta.llama3-1-405b-instruct-v1:0": 128000,
"eu.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000,
"eu.anthropic.claude-3-sonnet-20240229-v1:0": 200000,
"eu.anthropic.claude-3-haiku-20240307-v1:0": 200000,
"eu.meta.llama3-2-3b-instruct-v1:0": 131000,
"eu.meta.llama3-2-1b-instruct-v1:0": 131000,
"apac.anthropic.claude-3-5-sonnet-20240620-v1:0": 200000,
"apac.anthropic.claude-3-5-sonnet-20241022-v2:0": 200000,
"apac.anthropic.claude-3-sonnet-20240229-v1:0": 200000,
"apac.anthropic.claude-3-haiku-20240307-v1:0": 200000,
"amazon.nova-pro-v1:0": 300000,
"amazon.nova-micro-v1:0": 128000,
"amazon.nova-lite-v1:0": 300000,
"anthropic.claude-3-5-sonnet-20240620-v1:0": 200000,
"anthropic.claude-3-5-haiku-20241022-v1:0": 200000,
"anthropic.claude-3-5-sonnet-20241022-v2:0": 200000,
"anthropic.claude-3-7-sonnet-20250219-v1:0": 200000,
"anthropic.claude-3-sonnet-20240229-v1:0": 200000,
"anthropic.claude-3-opus-20240229-v1:0": 200000,
"anthropic.claude-3-haiku-20240307-v1:0": 200000,
"anthropic.claude-v2:1": 200000,
"anthropic.claude-v2": 100000,
"anthropic.claude-instant-v1": 100000,
"meta.llama3-1-405b-instruct-v1:0": 128000,
"meta.llama3-1-70b-instruct-v1:0": 128000,
"meta.llama3-1-8b-instruct-v1:0": 128000,
"meta.llama3-70b-instruct-v1:0": 8000,
"meta.llama3-8b-instruct-v1:0": 8000,
"amazon.titan-text-lite-v1": 4000,
"amazon.titan-text-express-v1": 8000,
"cohere.command-text-v14": 4000,
"ai21.j2-mid-v1": 8191,
"ai21.j2-ultra-v1": 8191,
"ai21.jamba-instruct-v1:0": 256000,
"mistral.mistral-7b-instruct-v0:2": 32000,
"mistral.mixtral-8x7b-instruct-v0:1": 32000,
# mistral
"mistral-tiny": 32768,
"mistral-small-latest": 32768,
@@ -251,8 +305,6 @@ class LLM:
Args:
messages: Input messages for the LLM
tools: Optional list of tool schemas
callbacks: Optional list of callback functions
available_functions: Optional dict of available functions
Returns:
Dict[str, Any]: Parameters for the completion call
@@ -262,7 +314,10 @@ class LLM:
messages = [{"role": "user", "content": messages}]
formatted_messages = self._format_messages_for_provider(messages)
# --- 2) Prepare the parameters for the completion call
# --- 2) If using Gemini, ensure additionalProperties is not in tool schemas
self._clean_gemini_tool_parameters(tools)
# --- 3) Prepare the parameters for the completion call
params = {
"model": self.model,
"messages": formatted_messages,
@@ -291,6 +346,22 @@ class LLM:
# Remove None values from params
return {k: v for k, v in params.items() if v is not None}
def _clean_gemini_tool_parameters(
self, tools: Optional[List[dict]]
) -> None:
"""Remove additionalProperties from tool parameters for Gemini compatibility.
Args:
tools: List of tool dictionaries that may contain function schemas
"""
if not tools or "gemini" not in self.model.lower():
return
for tool in tools:
if isinstance(tool, dict) and "function" in tool:
params = tool["function"].get("parameters", {})
params.pop("additionalProperties", None)
def _handle_streaming_response(
self,

View File

@@ -2,6 +2,7 @@ import datetime
import inspect
import json
import logging
import re
import threading
import uuid
from concurrent.futures import Future
@@ -49,6 +50,7 @@ from crewai.utilities.events import (
from crewai.utilities.events.crewai_event_bus import crewai_event_bus
from crewai.utilities.i18n import I18N
from crewai.utilities.printer import Printer
from crewai.utilities.string_utils import interpolate_only
class Task(BaseModel):
@@ -507,7 +509,9 @@ class Task(BaseModel):
return
try:
self.description = self._original_description.format(**inputs)
self.description = interpolate_only(
input_string=self._original_description, inputs=inputs
)
except KeyError as e:
raise ValueError(
f"Missing required template variable '{e.args[0]}' in description"
@@ -516,7 +520,7 @@ class Task(BaseModel):
raise ValueError(f"Error interpolating description: {str(e)}") from e
try:
self.expected_output = self.interpolate_only(
self.expected_output = interpolate_only(
input_string=self._original_expected_output, inputs=inputs
)
except (KeyError, ValueError) as e:
@@ -524,7 +528,7 @@ class Task(BaseModel):
if self.output_file is not None:
try:
self.output_file = self.interpolate_only(
self.output_file = interpolate_only(
input_string=self._original_output_file, inputs=inputs
)
except (KeyError, ValueError) as e:
@@ -555,72 +559,6 @@ class Task(BaseModel):
f"\n\n{conversation_instruction}\n\n{conversation_history}"
)
def interpolate_only(
self,
input_string: Optional[str],
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]],
) -> str:
"""Interpolate placeholders (e.g., {key}) in a string while leaving JSON untouched.
Args:
input_string: The string containing template variables to interpolate.
Can be None or empty, in which case an empty string is returned.
inputs: Dictionary mapping template variables to their values.
Supported value types are strings, integers, floats, and dicts/lists
containing only these types and other nested dicts/lists.
Returns:
The interpolated string with all template variables replaced with their values.
Empty string if input_string is None or empty.
Raises:
ValueError: If a value contains unsupported types
"""
# Validation function for recursive type checking
def validate_type(value: Any) -> None:
if value is None:
return
if isinstance(value, (str, int, float, bool)):
return
if isinstance(value, (dict, list)):
for item in value.values() if isinstance(value, dict) else value:
validate_type(item)
return
raise ValueError(
f"Unsupported type {type(value).__name__} in inputs. "
"Only str, int, float, bool, dict, and list are allowed."
)
# Validate all input values
for key, value in inputs.items():
try:
validate_type(value)
except ValueError as e:
raise ValueError(f"Invalid value for key '{key}': {str(e)}") from e
if input_string is None or not input_string:
return ""
if "{" not in input_string and "}" not in input_string:
return input_string
if not inputs:
raise ValueError(
"Inputs dictionary cannot be empty when interpolating variables"
)
try:
escaped_string = input_string.replace("{", "{{").replace("}", "}}")
for key in inputs.keys():
escaped_string = escaped_string.replace(f"{{{{{key}}}}}", f"{{{key}}}")
return escaped_string.format(**inputs)
except KeyError as e:
raise KeyError(
f"Template variable '{e.args[0]}' not found in inputs dictionary"
) from e
except ValueError as e:
raise ValueError(f"Error during string interpolation: {str(e)}") from e
def increment_tools_errors(self) -> None:
"""Increment the tools errors counter."""
self.tools_errors += 1

View File

@@ -2,7 +2,7 @@ from __future__ import annotations
import inspect
import textwrap
from typing import Any, Callable, Optional, Union, get_type_hints
from typing import Any, Callable, Dict, List, Optional, Type, Union, get_type_hints
from pydantic import BaseModel, Field, create_model
@@ -239,6 +239,37 @@ class CrewStructuredTool:
def args(self) -> dict:
"""Get the tool's input arguments schema."""
return self.args_schema.model_json_schema()["properties"]
def to_openai_function(self) -> Dict[str, Any]:
"""Convert the tool to an OpenAI function format.
Returns:
Dict[str, Any]: A dictionary in the OpenAI function format.
Example:
```python
tool = CrewStructuredTool(...)
function_dict = tool.to_openai_function()
# Use with OpenAI or compatible APIs
```
Raises:
ValueError: If the schema conversion fails
"""
try:
schema = self.args_schema.model_json_schema()
schema.pop("additionalProperties", None)
return {
"type": "function",
"function": {
"name": self.name,
"description": self.description,
"parameters": schema
}
}
except Exception as e:
raise ValueError(f"Failed to convert tool to OpenAI function format: {str(e)}")
def __repr__(self) -> str:
return (

View File

@@ -455,7 +455,7 @@ class ToolUsage:
# Attempt 4: Repair JSON
try:
repaired_input = repair_json(tool_input)
repaired_input = repair_json(tool_input, skip_json_loads=True)
self._printer.print(
content=f"Repaired JSON: {repaired_input}", color="blue"
)

View File

@@ -1,10 +1,12 @@
from typing import List
import re
from typing import TYPE_CHECKING, List
from crewai.task import Task
from crewai.tasks.task_output import TaskOutput
if TYPE_CHECKING:
from crewai.task import Task
from crewai.tasks.task_output import TaskOutput
def aggregate_raw_outputs_from_task_outputs(task_outputs: List[TaskOutput]) -> str:
def aggregate_raw_outputs_from_task_outputs(task_outputs: List["TaskOutput"]) -> str:
"""Generate string context from the task outputs."""
dividers = "\n\n----------\n\n"
@@ -13,7 +15,7 @@ def aggregate_raw_outputs_from_task_outputs(task_outputs: List[TaskOutput]) -> s
return context
def aggregate_raw_outputs_from_tasks(tasks: List[Task]) -> str:
def aggregate_raw_outputs_from_tasks(tasks: List["Task"]) -> str:
"""Generate string context from the tasks."""
task_outputs = [task.output for task in tasks if task.output is not None]

View File

@@ -0,0 +1,82 @@
import re
from typing import Any, Dict, List, Optional, Union
def interpolate_only(
input_string: Optional[str],
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]],
) -> str:
"""Interpolate placeholders (e.g., {key}) in a string while leaving JSON untouched.
Only interpolates placeholders that follow the pattern {variable_name} where
variable_name starts with a letter/underscore and contains only letters, numbers, and underscores.
Args:
input_string: The string containing template variables to interpolate.
Can be None or empty, in which case an empty string is returned.
inputs: Dictionary mapping template variables to their values.
Supported value types are strings, integers, floats, and dicts/lists
containing only these types and other nested dicts/lists.
Returns:
The interpolated string with all template variables replaced with their values.
Empty string if input_string is None or empty.
Raises:
ValueError: If a value contains unsupported types or a template variable is missing
"""
# Validation function for recursive type checking
def validate_type(value: Any) -> None:
if value is None:
return
if isinstance(value, (str, int, float, bool)):
return
if isinstance(value, (dict, list)):
for item in value.values() if isinstance(value, dict) else value:
validate_type(item)
return
raise ValueError(
f"Unsupported type {type(value).__name__} in inputs. "
"Only str, int, float, bool, dict, and list are allowed."
)
# Validate all input values
for key, value in inputs.items():
try:
validate_type(value)
except ValueError as e:
raise ValueError(f"Invalid value for key '{key}': {str(e)}") from e
if input_string is None or not input_string:
return ""
if "{" not in input_string and "}" not in input_string:
return input_string
if not inputs:
raise ValueError(
"Inputs dictionary cannot be empty when interpolating variables"
)
# The regex pattern to find valid variable placeholders
# Matches {variable_name} where variable_name starts with a letter/underscore
# and contains only letters, numbers, and underscores
pattern = r"\{([A-Za-z_][A-Za-z0-9_]*)\}"
# Find all matching variables in the input string
variables = re.findall(pattern, input_string)
result = input_string
# Check if all variables exist in inputs
missing_vars = [var for var in variables if var not in inputs]
if missing_vars:
raise KeyError(
f"Template variable '{missing_vars[0]}' not found in inputs dictionary"
)
# Replace each variable with its value
for var in variables:
if var in inputs:
placeholder = "{" + var + "}"
value = str(inputs[var])
result = result.replace(placeholder, value)
return result

View File

@@ -15,6 +15,7 @@ from crewai import Agent, Crew, Process, Task
from crewai.tasks.conditional_task import ConditionalTask
from crewai.tasks.task_output import TaskOutput
from crewai.utilities.converter import Converter
from crewai.utilities.string_utils import interpolate_only
def test_task_tool_reflect_agent_tools():
@@ -822,7 +823,7 @@ def test_interpolate_only():
# Test JSON structure preservation
json_string = '{"info": "Look at {placeholder}", "nested": {"val": "{nestedVal}"}}'
result = task.interpolate_only(
result = interpolate_only(
input_string=json_string,
inputs={"placeholder": "the data", "nestedVal": "something else"},
)
@@ -833,20 +834,18 @@ def test_interpolate_only():
# Test normal string interpolation
normal_string = "Hello {name}, welcome to {place}!"
result = task.interpolate_only(
result = interpolate_only(
input_string=normal_string, inputs={"name": "John", "place": "CrewAI"}
)
assert result == "Hello John, welcome to CrewAI!"
# Test empty string
result = task.interpolate_only(input_string="", inputs={"unused": "value"})
result = interpolate_only(input_string="", inputs={"unused": "value"})
assert result == ""
# Test string with no placeholders
no_placeholders = "Hello, this is a test"
result = task.interpolate_only(
input_string=no_placeholders, inputs={"unused": "value"}
)
result = interpolate_only(input_string=no_placeholders, inputs={"unused": "value"})
assert result == no_placeholders
@@ -858,7 +857,7 @@ def test_interpolate_only_with_dict_inside_expected_output():
)
json_string = '{"questions": {"main_question": "What is the user\'s name?", "secondary_question": "What is the user\'s age?"}}'
result = task.interpolate_only(
result = interpolate_only(
input_string=json_string,
inputs={
"questions": {
@@ -872,18 +871,16 @@ def test_interpolate_only_with_dict_inside_expected_output():
assert result == json_string
normal_string = "Hello {name}, welcome to {place}!"
result = task.interpolate_only(
result = interpolate_only(
input_string=normal_string, inputs={"name": "John", "place": "CrewAI"}
)
assert result == "Hello John, welcome to CrewAI!"
result = task.interpolate_only(input_string="", inputs={"unused": "value"})
result = interpolate_only(input_string="", inputs={"unused": "value"})
assert result == ""
no_placeholders = "Hello, this is a test"
result = task.interpolate_only(
input_string=no_placeholders, inputs={"unused": "value"}
)
result = interpolate_only(input_string=no_placeholders, inputs={"unused": "value"})
assert result == no_placeholders
@@ -1085,12 +1082,12 @@ def test_interpolate_with_list_of_strings():
# Test simple list of strings
input_str = "Available items: {items}"
inputs = {"items": ["apple", "banana", "cherry"]}
result = task.interpolate_only(input_str, inputs)
result = interpolate_only(input_str, inputs)
assert result == f"Available items: {inputs['items']}"
# Test empty list
empty_list_input = {"items": []}
result = task.interpolate_only(input_str, empty_list_input)
result = interpolate_only(input_str, empty_list_input)
assert result == "Available items: []"
@@ -1106,7 +1103,7 @@ def test_interpolate_with_list_of_dicts():
{"name": "Bob", "age": 25, "skills": ["Java", "Cloud"]},
]
}
result = task.interpolate_only("{people}", input_data)
result = interpolate_only("{people}", input_data)
parsed_result = eval(result)
assert isinstance(parsed_result, list)
@@ -1138,7 +1135,7 @@ def test_interpolate_with_nested_structures():
],
}
}
result = task.interpolate_only("{company}", input_data)
result = interpolate_only("{company}", input_data)
parsed = eval(result)
assert parsed["name"] == "TechCorp"
@@ -1161,7 +1158,7 @@ def test_interpolate_with_special_characters():
"empty": "",
}
}
result = task.interpolate_only("{special_data}", input_data)
result = interpolate_only("{special_data}", input_data)
parsed = eval(result)
assert parsed["quotes"] == """This has "double" and 'single' quotes"""
@@ -1188,7 +1185,7 @@ def test_interpolate_mixed_types():
},
}
}
result = task.interpolate_only("{data}", input_data)
result = interpolate_only("{data}", input_data)
parsed = eval(result)
assert parsed["name"] == "Test Dataset"
@@ -1216,7 +1213,7 @@ def test_interpolate_complex_combination():
},
]
}
result = task.interpolate_only("{report}", input_data)
result = interpolate_only("{report}", input_data)
parsed = eval(result)
assert len(parsed) == 2
@@ -1233,7 +1230,7 @@ def test_interpolate_invalid_type_validation():
# Test with invalid top-level type
with pytest.raises(ValueError) as excinfo:
task.interpolate_only("{data}", {"data": set()}) # type: ignore we are purposely testing this failure
interpolate_only("{data}", {"data": set()}) # type: ignore we are purposely testing this failure
assert "Unsupported type set" in str(excinfo.value)
@@ -1246,7 +1243,7 @@ def test_interpolate_invalid_type_validation():
}
}
with pytest.raises(ValueError) as excinfo:
task.interpolate_only("{data}", {"data": invalid_nested})
interpolate_only("{data}", {"data": invalid_nested})
assert "Unsupported type set" in str(excinfo.value)
@@ -1265,24 +1262,22 @@ def test_interpolate_custom_object_validation():
# Test with custom object at top level
with pytest.raises(ValueError) as excinfo:
task.interpolate_only("{obj}", {"obj": CustomObject(5)}) # type: ignore we are purposely testing this failure
interpolate_only("{obj}", {"obj": CustomObject(5)}) # type: ignore we are purposely testing this failure
assert "Unsupported type CustomObject" in str(excinfo.value)
# Test with nested custom object in dictionary
with pytest.raises(ValueError) as excinfo:
task.interpolate_only(
"{data}", {"data": {"valid": 1, "invalid": CustomObject(5)}}
)
interpolate_only("{data}", {"data": {"valid": 1, "invalid": CustomObject(5)}})
assert "Unsupported type CustomObject" in str(excinfo.value)
# Test with nested custom object in list
with pytest.raises(ValueError) as excinfo:
task.interpolate_only("{data}", {"data": [1, "valid", CustomObject(5)]})
interpolate_only("{data}", {"data": [1, "valid", CustomObject(5)]})
assert "Unsupported type CustomObject" in str(excinfo.value)
# Test with deeply nested custom object
with pytest.raises(ValueError) as excinfo:
task.interpolate_only(
interpolate_only(
"{data}", {"data": {"level1": {"level2": [{"level3": CustomObject(5)}]}}}
)
assert "Unsupported type CustomObject" in str(excinfo.value)
@@ -1306,7 +1301,7 @@ def test_interpolate_valid_complex_types():
}
# Should not raise any errors
result = task.interpolate_only("{data}", {"data": valid_data})
result = interpolate_only("{data}", {"data": valid_data})
parsed = eval(result)
assert parsed["name"] == "Valid Dataset"
assert parsed["stats"]["nested"]["deeper"]["b"] == 2.5
@@ -1319,16 +1314,16 @@ def test_interpolate_edge_cases():
)
# Test empty dict and list
assert task.interpolate_only("{}", {"data": {}}) == "{}"
assert task.interpolate_only("[]", {"data": []}) == "[]"
assert interpolate_only("{}", {"data": {}}) == "{}"
assert interpolate_only("[]", {"data": []}) == "[]"
# Test numeric types
assert task.interpolate_only("{num}", {"num": 42}) == "42"
assert task.interpolate_only("{num}", {"num": 3.14}) == "3.14"
assert interpolate_only("{num}", {"num": 42}) == "42"
assert interpolate_only("{num}", {"num": 3.14}) == "3.14"
# Test boolean values (valid JSON types)
assert task.interpolate_only("{flag}", {"flag": True}) == "True"
assert task.interpolate_only("{flag}", {"flag": False}) == "False"
assert interpolate_only("{flag}", {"flag": True}) == "True"
assert interpolate_only("{flag}", {"flag": False}) == "False"
def test_interpolate_valid_types():
@@ -1346,7 +1341,7 @@ def test_interpolate_valid_types():
"nested": {"flag": True, "empty": None},
}
result = task.interpolate_only("{data}", {"data": valid_data})
result = interpolate_only("{data}", {"data": valid_data})
parsed = eval(result)
assert parsed["active"] is True

View File

@@ -25,7 +25,7 @@ def schema_class():
return TestSchema
class InternalCrewStructuredTool:
class TestInternalCrewStructuredTool:
def test_initialization(self, basic_function, schema_class):
"""Test basic initialization of CrewStructuredTool"""
tool = CrewStructuredTool(
@@ -144,3 +144,55 @@ class InternalCrewStructuredTool:
{"required_param": "test", "optional_param": "custom", "nullable_param": 42}
)
assert result == "test custom 42"
def test_to_openai_function_no_additional_properties(self):
"""Test that the to_openai_function method doesn't include additionalProperties."""
class TestSchema(BaseModel):
test_field: str = Field(..., description="A test field")
def test_func(test_field: str) -> str:
"""Test function that returns the input."""
return f"Test function received: {test_field}"
tool = CrewStructuredTool(
name="test_tool",
description="A test tool",
args_schema=TestSchema,
func=test_func
)
function_dict = tool.to_openai_function()
assert "additionalProperties" not in function_dict["function"]["parameters"]
# Verify other properties are correct
assert function_dict["type"] == "function"
assert function_dict["function"]["name"] == "test_tool"
assert function_dict["function"]["description"] == "A test tool"
assert "properties" in function_dict["function"]["parameters"]
assert "test_field" in function_dict["function"]["parameters"]["properties"]
def test_to_openai_function_edge_cases(self):
"""Test edge cases for to_openai_function conversion."""
class EmptySchema(BaseModel):
pass
def empty_func() -> None:
pass
tool = CrewStructuredTool(
name="empty_tool",
description="A tool with empty schema",
args_schema=EmptySchema,
func=empty_func
)
function_dict = tool.to_openai_function()
assert function_dict["type"] == "function"
assert function_dict["function"]["name"] == "empty_tool"
# Check that parameters contains the expected fields
params = function_dict["function"]["parameters"]
assert params["title"] == "EmptySchema"
assert params["type"] == "object"
assert "properties" in params # Empty schema still has a properties field

View File

@@ -0,0 +1,187 @@
from typing import Any, Dict, List, Union
import pytest
from crewai.utilities.string_utils import interpolate_only
class TestInterpolateOnly:
"""Tests for the interpolate_only function in string_utils.py."""
def test_basic_variable_interpolation(self):
"""Test basic variable interpolation works correctly."""
template = "Hello, {name}! Welcome to {company}."
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"name": "Alice",
"company": "CrewAI",
}
result = interpolate_only(template, inputs)
assert result == "Hello, Alice! Welcome to CrewAI."
def test_multiple_occurrences_of_same_variable(self):
"""Test that multiple occurrences of the same variable are replaced."""
template = "{name} is using {name}'s account."
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"name": "Bob"
}
result = interpolate_only(template, inputs)
assert result == "Bob is using Bob's account."
def test_json_structure_preservation(self):
"""Test that JSON structures are preserved and not interpolated incorrectly."""
template = """
Instructions for {agent}:
Please return the following object:
{"name": "person's name", "age": 25, "skills": ["coding", "testing"]}
"""
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"agent": "DevAgent"
}
result = interpolate_only(template, inputs)
assert "Instructions for DevAgent:" in result
assert (
'{"name": "person\'s name", "age": 25, "skills": ["coding", "testing"]}'
in result
)
def test_complex_nested_json(self):
"""Test with complex JSON structures containing curly braces."""
template = """
{agent} needs to process:
{
"config": {
"nested": {
"value": 42
},
"arrays": [1, 2, {"inner": "value"}]
}
}
"""
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"agent": "DataProcessor"
}
result = interpolate_only(template, inputs)
assert "DataProcessor needs to process:" in result
assert '"nested": {' in result
assert '"value": 42' in result
assert '[1, 2, {"inner": "value"}]' in result
def test_missing_variable(self):
"""Test that an error is raised when a required variable is missing."""
template = "Hello, {name}!"
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"not_name": "Alice"
}
with pytest.raises(KeyError) as excinfo:
interpolate_only(template, inputs)
assert "template variable" in str(excinfo.value).lower()
assert "name" in str(excinfo.value)
def test_invalid_input_types(self):
"""Test that an error is raised with invalid input types."""
template = "Hello, {name}!"
# Using Any for this test since we're intentionally testing an invalid type
inputs: Dict[str, Any] = {"name": object()} # Object is not a valid input type
with pytest.raises(ValueError) as excinfo:
interpolate_only(template, inputs)
assert "unsupported type" in str(excinfo.value).lower()
def test_empty_input_string(self):
"""Test handling of empty or None input string."""
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"name": "Alice"
}
assert interpolate_only("", inputs) == ""
assert interpolate_only(None, inputs) == ""
def test_no_variables_in_template(self):
"""Test a template with no variables to replace."""
template = "This is a static string with no variables."
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"name": "Alice"
}
result = interpolate_only(template, inputs)
assert result == template
def test_variable_name_starting_with_underscore(self):
"""Test variables starting with underscore are replaced correctly."""
template = "Variable: {_special_var}"
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"_special_var": "Special Value"
}
result = interpolate_only(template, inputs)
assert result == "Variable: Special Value"
def test_preserves_non_matching_braces(self):
"""Test that non-matching braces patterns are preserved."""
template = (
"This {123} and {!var} should not be replaced but {valid_var} should."
)
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"valid_var": "works"
}
result = interpolate_only(template, inputs)
assert (
result == "This {123} and {!var} should not be replaced but works should."
)
def test_complex_mixed_scenario(self):
"""Test a complex scenario with both valid variables and JSON structures."""
template = """
{agent_name} is working on task {task_id}.
Instructions:
1. Process the data
2. Return results as:
{
"taskId": "{task_id}",
"results": {
"processed_by": "agent_name",
"status": "complete",
"values": [1, 2, 3]
}
}
"""
inputs: Dict[str, Union[str, int, float, Dict[str, Any], List[Any]]] = {
"agent_name": "AnalyticsAgent",
"task_id": "T-12345",
}
result = interpolate_only(template, inputs)
assert "AnalyticsAgent is working on task T-12345" in result
assert '"taskId": "T-12345"' in result
assert '"processed_by": "agent_name"' in result # This shouldn't be replaced
assert '"values": [1, 2, 3]' in result
def test_empty_inputs_dictionary(self):
"""Test that an error is raised with empty inputs dictionary."""
template = "Hello, {name}!"
inputs: Dict[str, Any] = {}
with pytest.raises(ValueError) as excinfo:
interpolate_only(template, inputs)
assert "inputs dictionary cannot be empty" in str(excinfo.value).lower()