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feat/funct
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devin/1742
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4daa88fa59 |
@@ -59,7 +59,7 @@ There are three ways to configure LLMs in CrewAI. Choose the method that best fi
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goal: Conduct comprehensive research and analysis
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backstory: A dedicated research professional with years of experience
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verbose: true
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llm: openai/gpt-4o-mini # your model here
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llm: openai/gpt-4o-mini # your model here
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# (see provider configuration examples below for more)
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```
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@@ -111,7 +111,7 @@ There are three ways to configure LLMs in CrewAI. Choose the method that best fi
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## Provider Configuration Examples
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CrewAI supports a multitude of LLM providers, each offering unique features, authentication methods, and model capabilities.
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CrewAI supports a multitude of LLM providers, each offering unique features, authentication methods, and model capabilities.
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In this section, you'll find detailed examples that help you select, configure, and optimize the LLM that best fits your project's needs.
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|
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<AccordionGroup>
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@@ -121,7 +121,7 @@ In this section, you'll find detailed examples that help you select, configure,
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```toml Code
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# Required
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||||
OPENAI_API_KEY=sk-...
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||||
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||||
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# Optional
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OPENAI_API_BASE=<custom-base-url>
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OPENAI_ORGANIZATION=<your-org-id>
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@@ -226,7 +226,7 @@ In this section, you'll find detailed examples that help you select, configure,
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AZURE_API_KEY=<your-api-key>
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AZURE_API_BASE=<your-resource-url>
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AZURE_API_VERSION=<api-version>
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|
||||
|
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# Optional
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AZURE_AD_TOKEN=<your-azure-ad-token>
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AZURE_API_TYPE=<your-azure-api-type>
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@@ -289,7 +289,7 @@ In this section, you'll find detailed examples that help you select, configure,
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| Mistral 8x7B Instruct | Up to 32k tokens | An MOE LLM that follows instructions, completes requests, and generates creative text. |
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|
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</Accordion>
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||||
|
||||
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<Accordion title="Amazon SageMaker">
|
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```toml Code
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AWS_ACCESS_KEY_ID=<your-access-key>
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||||
@@ -474,7 +474,7 @@ In this section, you'll find detailed examples that help you select, configure,
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WATSONX_URL=<your-url>
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WATSONX_APIKEY=<your-apikey>
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WATSONX_PROJECT_ID=<your-project-id>
|
||||
|
||||
|
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# Optional
|
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WATSONX_TOKEN=<your-token>
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WATSONX_DEPLOYMENT_SPACE_ID=<your-space-id>
|
||||
@@ -491,7 +491,7 @@ In this section, you'll find detailed examples that help you select, configure,
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|
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<Accordion title="Ollama (Local LLMs)">
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1. Install Ollama: [ollama.ai](https://ollama.ai/)
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2. Run a model: `ollama run llama2`
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2. Run a model: `ollama run llama3`
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3. Configure:
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```python Code
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@@ -600,7 +600,7 @@ In this section, you'll find detailed examples that help you select, configure,
|
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```toml Code
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OPENROUTER_API_KEY=<your-api-key>
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```
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|
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|
||||
Example usage in your CrewAI project:
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```python Code
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llm = LLM(
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@@ -723,7 +723,7 @@ Learn how to get the most out of your LLM configuration:
|
||||
- Small tasks (up to 4K tokens): Standard models
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- Medium tasks (between 4K-32K): Enhanced models
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- Large tasks (over 32K): Large context models
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|
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|
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```python
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# Configure model with appropriate settings
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llm = LLM(
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@@ -760,11 +760,11 @@ Learn how to get the most out of your LLM configuration:
|
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<Warning>
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Most authentication issues can be resolved by checking API key format and environment variable names.
|
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</Warning>
|
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|
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|
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```bash
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# OpenAI
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OPENAI_API_KEY=sk-...
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|
||||
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# Anthropic
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ANTHROPIC_API_KEY=sk-ant-...
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```
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@@ -773,11 +773,11 @@ Learn how to get the most out of your LLM configuration:
|
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<Check>
|
||||
Always include the provider prefix in model names
|
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</Check>
|
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|
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|
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```python
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# Correct
|
||||
llm = LLM(model="openai/gpt-4")
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|
||||
|
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# Incorrect
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llm = LLM(model="gpt-4")
|
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```
|
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@@ -786,5 +786,10 @@ Learn how to get the most out of your LLM configuration:
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<Tip>
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Use larger context models for extensive tasks
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</Tip>
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|
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```python
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# Large context model
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||||
llm = LLM(model="openai/gpt-4o") # 128K tokens
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```
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</Tab>
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</Tabs>
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@@ -25,6 +25,7 @@ from crewai.tools.base_tool import BaseTool, Tool
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from crewai.utilities import I18N, Logger, RPMController
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from crewai.utilities.config import process_config
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from crewai.utilities.converter import Converter
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from crewai.utilities.string_utils import interpolate_only
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T = TypeVar("T", bound="BaseAgent")
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@@ -333,9 +334,15 @@ class BaseAgent(ABC, BaseModel):
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self._original_backstory = self.backstory
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|
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if inputs:
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self.role = self._original_role.format(**inputs)
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self.goal = self._original_goal.format(**inputs)
|
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self.backstory = self._original_backstory.format(**inputs)
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self.role = interpolate_only(
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input_string=self._original_role, inputs=inputs
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||||
)
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self.goal = interpolate_only(
|
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input_string=self._original_goal, inputs=inputs
|
||||
)
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self.backstory = interpolate_only(
|
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input_string=self._original_backstory, inputs=inputs
|
||||
)
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||||
def set_cache_handler(self, cache_handler: CacheHandler) -> None:
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"""Set the cache handler for the agent.
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|
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@@ -114,6 +114,60 @@ LLM_CONTEXT_WINDOW_SIZES = {
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"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,
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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 (
|
||||
|
||||
@@ -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"
|
||||
)
|
||||
|
||||
@@ -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]
|
||||
|
||||
|
||||
82
src/crewai/utilities/string_utils.py
Normal file
82
src/crewai/utilities/string_utils.py
Normal 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
|
||||
@@ -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
|
||||
|
||||
@@ -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
|
||||
|
||||
187
tests/utilities/test_string_utils.py
Normal file
187
tests/utilities/test_string_utils.py
Normal 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()
|
||||
Reference in New Issue
Block a user