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Code Issues Actions 4 Packages Projects Releases Wiki Activity

clean up. fix type safety. address memory config docs

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This commit is contained in:
Brandon Hancock
2025-02-05 15:06:34 -05:00
parent de6933b2d2
commit 5d9fcc38a3
6 changed files with 52 additions and 45 deletions
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39
docs/concepts/memory.mdx
View File

@@ -185,7 +185,12 @@ my_crew = Crew(
process=Process.sequential,
memory=True,
verbose=True,
embedder=OpenAIEmbeddingFunction(api_key=os.getenv("OPENAI_API_KEY"), model_name="text-embedding-3-small"),
embedder={
"provider": "openai",
"config": {
"model": 'text-embedding-3-small'
}
}
)
```
@@ -242,13 +247,16 @@ my_crew = Crew(
process=Process.sequential,
memory=True,
verbose=True,
embedder=OpenAIEmbeddingFunction(
api_key="YOUR_API_KEY",
api_base="YOUR_API_BASE_PATH",
api_type="azure",
api_version="YOUR_API_VERSION",
model_name="text-embedding-3-small"
)
embedder={
"provider": "openai",
"config": {
"api_key": "YOUR_API_KEY",
"api_base": "YOUR_API_BASE_PATH",
"api_type": "azure",
"api_version": "YOUR_API_VERSION",
"model_name": 'text-embedding-3-small'
}
}
)
```
@@ -264,12 +272,15 @@ my_crew = Crew(
process=Process.sequential,
memory=True,
verbose=True,
embedder=GoogleVertexEmbeddingFunction(
project_id="YOUR_PROJECT_ID",
region="YOUR_REGION",
api_key="YOUR_API_KEY",
model_name="textembedding-gecko"
)
embedder={
"provider": "vertexai",
"config": {
"project_id"="YOUR_PROJECT_ID",
"region"="YOUR_REGION",
"api_key"="YOUR_API_KEY",
"model_name"="textembedding-gecko"
}
}
)
```

25
src/crewai/agent.py
View File

@@ -1,6 +1,6 @@
import shutil
import subprocess
from typing import Any, Dict, List, Literal, Optional, Union
from typing import Any, Dict, List, Literal, Optional, Sequence, Union
from pydantic import Field, InstanceOf, PrivateAttr, model_validator
@@ -54,7 +54,6 @@ class Agent(BaseAgent):
llm: The language model that will run the agent.
function_calling_llm: The language model that will handle the tool calling for this agent, it overrides the crew function_calling_llm.
max_iter: Maximum number of iterations for an agent to execute a task.
memory: Whether the agent should have memory or not.
max_rpm: Maximum number of requests per minute for the agent execution to be respected.
verbose: Whether the agent execution should be in verbose mode.
allow_delegation: Whether the agent is allowed to delegate tasks to other agents.
@@ -71,9 +70,7 @@ class Agent(BaseAgent):
)
agent_ops_agent_name: str = None # type: ignore # Incompatible types in assignment (expression has type "None", variable has type "str")
agent_ops_agent_id: str = None # type: ignore # Incompatible types in assignment (expression has type "None", variable has type "str")
cache_handler: InstanceOf[CacheHandler] = Field(
default=None, description="An instance of the CacheHandler class."
)
step_callback: Optional[Any] = Field(
default=None,
description="Callback to be executed after each step of the agent execution.",
@@ -107,10 +104,6 @@ class Agent(BaseAgent):
default=True,
description="Keep messages under the context window size by summarizing content.",
)
max_iter: int = Field(
default=20,
description="Maximum number of iterations for an agent to execute a task before giving it's best answer",
)
max_retry_limit: int = Field(
default=2,
description="Maximum number of retries for an agent to execute a task when an error occurs.",
@@ -195,13 +188,15 @@ class Agent(BaseAgent):
if task.output_json:
# schema = json.dumps(task.output_json, indent=2)
schema = generate_model_description(task.output_json)
task_prompt += "\n" + self.i18n.slice(
"formatted_task_instructions"
).format(output_format=schema)
elif task.output_pydantic:
schema = generate_model_description(task.output_pydantic)
task_prompt += "\n" + self.i18n.slice("formatted_task_instructions").format(
output_format=schema
)
task_prompt += "\n" + self.i18n.slice(
"formatted_task_instructions"
).format(output_format=schema)
if context:
task_prompt = self.i18n.slice("task_with_context").format(
@@ -329,14 +324,14 @@ class Agent(BaseAgent):
tools = agent_tools.tools()
return tools
def get_multimodal_tools(self) -> List[Tool]:
def get_multimodal_tools(self) -> Sequence[BaseTool]:
from crewai.tools.agent_tools.add_image_tool import AddImageTool
return [AddImageTool()]
def get_code_execution_tools(self):
try:
from crewai_tools import CodeInterpreterTool
from crewai_tools import CodeInterpreterTool # type: ignore
# Set the unsafe_mode based on the code_execution_mode attribute
unsafe_mode = self.code_execution_mode == "unsafe"

12
src/crewai/agents/agent_builder/base_agent.py
View File

@@ -24,6 +24,7 @@ from crewai.tools import BaseTool
from crewai.tools.base_tool import Tool
from crewai.utilities import I18N, Logger, RPMController
from crewai.utilities.config import process_config
from crewai.utilities.converter import Converter
T = TypeVar("T", bound="BaseAgent")
@@ -42,7 +43,7 @@ class BaseAgent(ABC, BaseModel):
max_rpm (Optional[int]): Maximum number of requests per minute for the agent execution.
allow_delegation (bool): Allow delegation of tasks to agents.
tools (Optional[List[Any]]): Tools at the agent's disposal.
max_iter (Optional[int]): Maximum iterations for an agent to execute a task.
max_iter (int): Maximum iterations for an agent to execute a task.
agent_executor (InstanceOf): An instance of the CrewAgentExecutor class.
llm (Any): Language model that will run the agent.
crew (Any): Crew to which the agent belongs.
@@ -114,7 +115,7 @@ class BaseAgent(ABC, BaseModel):
tools: Optional[List[Any]] = Field(
default_factory=list, description="Tools at agents' disposal"
)
max_iter: Optional[int] = Field(
max_iter: int = Field(
default=25, description="Maximum iterations for an agent to execute a task"
)
agent_executor: InstanceOf = Field(
@@ -125,11 +126,12 @@ class BaseAgent(ABC, BaseModel):
)
crew: Any = Field(default=None, description="Crew to which the agent belongs.")
i18n: I18N = Field(default=I18N(), description="Internationalization settings.")
cache_handler: InstanceOf[CacheHandler] = Field(
cache_handler: Optional[InstanceOf[CacheHandler]] = Field(
default=None, description="An instance of the CacheHandler class."
)
tools_handler: InstanceOf[ToolsHandler] = Field(
default=None, description="An instance of the ToolsHandler class."
default_factory=ToolsHandler,
description="An instance of the ToolsHandler class.",
)
max_tokens: Optional[int] = Field(
default=None, description="Maximum number of tokens for the agent's execution."
@@ -254,7 +256,7 @@ class BaseAgent(ABC, BaseModel):
@abstractmethod
def get_output_converter(
self, llm: Any, text: str, model: type[BaseModel] | None, instructions: str
):
) -> Converter:
"""Get the converter class for the agent to create json/pydantic outputs."""
pass

2
src/crewai/memory/entity/entity_memory.py
View File

@@ -11,7 +11,7 @@ class EntityMemory(Memory):
"""
def __init__(self, crew=None, embedder_config=None, storage=None, path=None):
if hasattr(crew, "memory_config") and crew.memory_config is not None:
if crew and hasattr(crew, "memory_config") and crew.memory_config is not None:
self.memory_provider = crew.memory_config.get("provider")
else:
self.memory_provider = None

8
src/crewai/memory/memory.py
View File

@@ -1,14 +1,16 @@
from typing import Any, Dict, List, Optional
from typing import Any, Dict, List, Optional, Union
from pydantic import BaseModel
from crewai.memory.storage.rag_storage import RAGStorage
class Memory:
class Memory(BaseModel):
"""
Base class for memory, now supporting agent tags and generic metadata.
"""
def __init__(self, storage: RAGStorage):
def __init__(self, storage: Union[RAGStorage, Any]):
self.storage = storage
def save(

11
src/crewai/tools/agent_tools/add_image_tool.py
View File

@@ -7,11 +7,11 @@ from crewai.utilities import I18N
i18n = I18N()
class AddImageToolSchema(BaseModel):
image_url: str = Field(..., description="The URL or path of the image to add")
action: Optional[str] = Field(
default=None,
description="Optional context or question about the image"
default=None, description="Optional context or question about the image"
)
@@ -36,10 +36,7 @@ class AddImageTool(BaseTool):
"image_url": {
"url": image_url,
},
}
},
]
return {
"role": "user",
"content": content
}
return {"role": "user", "content": content}