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11 Commits

Author SHA1 Message Date
Brandon Hancock (bhancock_ai)
2e900c6443 Merge branch 'main' into bugfix/utc-in-python-3_10 2025-02-26 13:21:50 -05:00
Lorenze Jay
1e8ee247ca feat: Enhance agent knowledge setup with optional crew embedder (#2232)
- Modify `Agent` class to add `set_knowledge` method
- Allow setting embedder from crew-level configuration
- Remove `_set_knowledge` method from initialization
- Update `Crew` class to set agent knowledge during agent setup
- Add default implementation in `BaseAgent` for compatibility
2025-02-26 12:10:43 -05:00
Brandon Hancock
5a8d9019fa Add support for python 3.10 2025-02-25 16:05:22 -05:00
Fernando Galves
34d2993456 Update the constants.py file adding the list of foundation models available in Amazon Bedrock (#2170)
* Update constants.py

This PR updates the list of foundation models available in Amazon Bedrock to reflect the latest offerings.

* Update constants.py with inference profiles

Add the cross-region inference profiles to increase throughput and improve resiliency by routing your requests across multiple AWS Regions during peak utilization bursts.

* Update constants.py

Fix the model order

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2025-02-25 15:39:23 -05:00
devin-ai-integration[bot]
e3c5c174ee feat: add context window size for o3-mini model (#2192)
* feat: add context window size for o3-mini model

Fixes #2191

Co-Authored-By: Joe Moura <joao@crewai.com>

* feat: add context window validation and tests

- Add validation for context window size bounds (1024-2097152)
- Add test for context window validation
- Fix test import error

Co-Authored-By: Joe Moura <joao@crewai.com>

* style: fix import sorting in llm_test.py

Co-Authored-By: Joe Moura <joao@crewai.com>

---------

Co-authored-by: Devin AI <158243242+devin-ai-integration[bot]@users.noreply.github.com>
Co-authored-by: Joe Moura <joao@crewai.com>
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2025-02-25 15:32:14 -05:00
Brandon Hancock (bhancock_ai)
b4e2db0306 incorporating fix from @misrasaurabh1 with additional type fix (#2213)
Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
2025-02-25 15:29:21 -05:00
Shivtej Narake
9cc759ba32 [MINOR]support ChatOllama from langchain_ollama (#2158)
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2025-02-25 15:19:36 -05:00
Vidit Ostwal
ac9f8b9d5a Fixed the issue 2123 around memory command with CLI (#2155)
* Fixed the issue 2123 around memory command with CLI

* Fixed typo, added the recommendations

* Fixed Typo

* Fixed lint issue

* Fixed the print statement to include path as well

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2025-02-25 12:29:33 -05:00
Victor Degliame
3d4a1e4b18 fix: typo in 'delegate_work' and 'ask_question' promps (#2144)
Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2025-02-25 12:16:04 -05:00
nikolaidk
123f302744 Update kickoff-async.mdx (#2138)
Missing mandatory field expected_output on task in example

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>
2025-02-25 12:12:27 -05:00
Brandon Hancock (bhancock_ai)
5bae78639e Revert "feat: add prompt observability code (#2027)" (#2211)
* Revert "feat: add prompt observability code (#2027)"

This reverts commit 90f1bee602.

* Fix issues with flows post merge

* Decoupling telemetry and ensure tests  (#2212)

* feat: Enhance event listener and telemetry tracking

- Update event listener to improve telemetry span handling
- Add execution_span field to Task for better tracing
- Modify event handling in EventListener to use new span tracking
- Remove debug print statements
- Improve test coverage for crew and flow events
- Update cassettes to reflect new event tracking behavior

* Remove telemetry references from Crew class

- Remove Telemetry import and initialization from Crew class
- Delete _telemetry attribute from class configuration
- Clean up unused telemetry-related code

* test: Improve crew verbose output test with event log filtering

- Filter out event listener logs in verbose output test
- Ensure no output when verbose is set to False
- Enhance test coverage for crew logging behavior

* dropped comment

* refactor: Improve telemetry span tracking in EventListener

- Remove `execution_span` from Task class
- Add `execution_spans` dictionary to EventListener to track spans
- Update task event handlers to use new span tracking mechanism
- Simplify span management across task lifecycle events

* lint

* Fix failing test

---------

Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
2025-02-24 16:30:16 -05:00
13 changed files with 205 additions and 70 deletions

View File

@@ -506,7 +506,7 @@ my_crew = Crew(
)
```
### Resetting Memory
### Resetting Memory via cli
```shell
crewai reset-memories [OPTIONS]
@@ -520,8 +520,46 @@ crewai reset-memories [OPTIONS]
| `-s`, `--short` | Reset SHORT TERM memory. | Flag (boolean) | False |
| `-e`, `--entities` | Reset ENTITIES memory. | Flag (boolean) | False |
| `-k`, `--kickoff-outputs` | Reset LATEST KICKOFF TASK OUTPUTS. | Flag (boolean) | False |
| `-kn`, `--knowledge` | Reset KNOWLEDEGE storage | Flag (boolean) | False |
| `-a`, `--all` | Reset ALL memories. | Flag (boolean) | False |
Note: To use the cli command you need to have your crew in a file called crew.py in the same directory.
### Resetting Memory via crew object
```python
my_crew = Crew(
agents=[...],
tasks=[...],
process=Process.sequential,
memory=True,
verbose=True,
embedder={
"provider": "custom",
"config": {
"embedder": CustomEmbedder()
}
}
)
my_crew.reset_memories(command_type = 'all') # Resets all the memory
```
#### Resetting Memory Options
| Command Type | Description |
| :----------------- | :------------------------------- |
| `long` | Reset LONG TERM memory. |
| `short` | Reset SHORT TERM memory. |
| `entities` | Reset ENTITIES memory. |
| `kickoff_outputs` | Reset LATEST KICKOFF TASK OUTPUTS. |
| `knowledge` | Reset KNOWLEDGE memory. |
| `all` | Reset ALL memories. |
## Benefits of Using CrewAI's Memory System

View File

@@ -54,7 +54,8 @@ coding_agent = Agent(
# Create a task that requires code execution
data_analysis_task = Task(
description="Analyze the given dataset and calculate the average age of participants. Ages: {ages}",
agent=coding_agent
agent=coding_agent,
expected_output="The average age of the participants."
)
# Create a crew and add the task
@@ -116,4 +117,4 @@ async def async_multiple_crews():
# Run the async function
asyncio.run(async_multiple_crews())
```
```

View File

@@ -114,7 +114,6 @@ class Agent(BaseAgent):
@model_validator(mode="after")
def post_init_setup(self):
self._set_knowledge()
self.agent_ops_agent_name = self.role
self.llm = create_llm(self.llm)
@@ -134,8 +133,11 @@ class Agent(BaseAgent):
self.cache_handler = CacheHandler()
self.set_cache_handler(self.cache_handler)
def _set_knowledge(self):
def set_knowledge(self, crew_embedder: Optional[Dict[str, Any]] = None):
try:
if self.embedder is None and crew_embedder:
self.embedder = crew_embedder
if self.knowledge_sources:
full_pattern = re.compile(r"[^a-zA-Z0-9\-_\r\n]|(\.\.)")
knowledge_agent_name = f"{re.sub(full_pattern, '_', self.role)}"

View File

@@ -351,3 +351,6 @@ class BaseAgent(ABC, BaseModel):
if not self._rpm_controller:
self._rpm_controller = rpm_controller
self.create_agent_executor()
def set_knowledge(self, crew_embedder: Optional[Dict[str, Any]] = None):
pass

View File

@@ -216,10 +216,43 @@ MODELS = {
"watsonx/ibm/granite-3-8b-instruct",
],
"bedrock": [
"bedrock/us.amazon.nova-pro-v1:0",
"bedrock/us.amazon.nova-micro-v1:0",
"bedrock/us.amazon.nova-lite-v1:0",
"bedrock/us.anthropic.claude-3-5-sonnet-20240620-v1:0",
"bedrock/us.anthropic.claude-3-5-haiku-20241022-v1:0",
"bedrock/us.anthropic.claude-3-5-sonnet-20241022-v2:0",
"bedrock/us.anthropic.claude-3-7-sonnet-20250219-v1:0",
"bedrock/us.anthropic.claude-3-sonnet-20240229-v1:0",
"bedrock/us.anthropic.claude-3-opus-20240229-v1:0",
"bedrock/us.anthropic.claude-3-haiku-20240307-v1:0",
"bedrock/us.meta.llama3-2-11b-instruct-v1:0",
"bedrock/us.meta.llama3-2-3b-instruct-v1:0",
"bedrock/us.meta.llama3-2-90b-instruct-v1:0",
"bedrock/us.meta.llama3-2-1b-instruct-v1:0",
"bedrock/us.meta.llama3-1-8b-instruct-v1:0",
"bedrock/us.meta.llama3-1-70b-instruct-v1:0",
"bedrock/us.meta.llama3-3-70b-instruct-v1:0",
"bedrock/us.meta.llama3-1-405b-instruct-v1:0",
"bedrock/eu.anthropic.claude-3-5-sonnet-20240620-v1:0",
"bedrock/eu.anthropic.claude-3-sonnet-20240229-v1:0",
"bedrock/eu.anthropic.claude-3-haiku-20240307-v1:0",
"bedrock/eu.meta.llama3-2-3b-instruct-v1:0",
"bedrock/eu.meta.llama3-2-1b-instruct-v1:0",
"bedrock/apac.anthropic.claude-3-5-sonnet-20240620-v1:0",
"bedrock/apac.anthropic.claude-3-5-sonnet-20241022-v2:0",
"bedrock/apac.anthropic.claude-3-sonnet-20240229-v1:0",
"bedrock/apac.anthropic.claude-3-haiku-20240307-v1:0",
"bedrock/amazon.nova-pro-v1:0",
"bedrock/amazon.nova-micro-v1:0",
"bedrock/amazon.nova-lite-v1:0",
"bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0",
"bedrock/anthropic.claude-3-5-haiku-20241022-v1:0",
"bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0",
"bedrock/anthropic.claude-3-7-sonnet-20250219-v1:0",
"bedrock/anthropic.claude-3-sonnet-20240229-v1:0",
"bedrock/anthropic.claude-3-haiku-20240307-v1:0",
"bedrock/anthropic.claude-3-opus-20240229-v1:0",
"bedrock/anthropic.claude-3-haiku-20240307-v1:0",
"bedrock/anthropic.claude-v2:1",
"bedrock/anthropic.claude-v2",
"bedrock/anthropic.claude-instant-v1",
@@ -234,8 +267,6 @@ MODELS = {
"bedrock/ai21.j2-mid-v1",
"bedrock/ai21.j2-ultra-v1",
"bedrock/ai21.jamba-instruct-v1:0",
"bedrock/meta.llama2-13b-chat-v1",
"bedrock/meta.llama2-70b-chat-v1",
"bedrock/mistral.mistral-7b-instruct-v0:2",
"bedrock/mistral.mixtral-8x7b-instruct-v0:1",
],

View File

@@ -257,11 +257,11 @@ def get_crew(crew_path: str = "crew.py", require: bool = False) -> Crew | None:
import os
for root, _, files in os.walk("."):
if "crew.py" in files:
crew_path = os.path.join(root, "crew.py")
if crew_path in files:
crew_os_path = os.path.join(root, crew_path)
try:
spec = importlib.util.spec_from_file_location(
"crew_module", crew_path
"crew_module", crew_os_path
)
if not spec or not spec.loader:
continue
@@ -273,9 +273,11 @@ def get_crew(crew_path: str = "crew.py", require: bool = False) -> Crew | None:
for attr_name in dir(module):
attr = getattr(module, attr_name)
try:
if callable(attr) and hasattr(attr, "crew"):
crew_instance = attr().crew()
return crew_instance
if isinstance(attr, Crew) and hasattr(attr, "kickoff"):
print(
f"Found valid crew object in attribute '{attr_name}' at {crew_os_path}."
)
return attr
except Exception as e:
print(f"Error processing attribute {attr_name}: {e}")

View File

@@ -600,6 +600,7 @@ class Crew(BaseModel):
agent.i18n = i18n
# type: ignore[attr-defined] # Argument 1 to "_interpolate_inputs" of "Crew" has incompatible type "dict[str, Any] | None"; expected "dict[str, Any]"
agent.crew = self # type: ignore[attr-defined]
agent.set_knowledge(crew_embedder=self.embedder)
# TODO: Create an AgentFunctionCalling protocol for future refactoring
if not agent.function_calling_llm: # type: ignore # "BaseAgent" has no attribute "function_calling_llm"
agent.function_calling_llm = self.function_calling_llm # type: ignore # "BaseAgent" has no attribute "function_calling_llm"

View File

@@ -4,7 +4,7 @@ SQLite-based implementation of flow state persistence.
import json
import sqlite3
from datetime import datetime
from datetime import datetime, timezone
from pathlib import Path
from typing import Any, Dict, Optional, Union
@@ -34,6 +34,7 @@ class SQLiteFlowPersistence(FlowPersistence):
ValueError: If db_path is invalid
"""
from crewai.utilities.paths import db_storage_path
# Get path from argument or default location
path = db_path or str(Path(db_storage_path()) / "flow_states.db")
@@ -46,7 +47,8 @@ class SQLiteFlowPersistence(FlowPersistence):
def init_db(self) -> None:
"""Create the necessary tables if they don't exist."""
with sqlite3.connect(self.db_path) as conn:
conn.execute("""
conn.execute(
"""
CREATE TABLE IF NOT EXISTS flow_states (
id INTEGER PRIMARY KEY AUTOINCREMENT,
flow_uuid TEXT NOT NULL,
@@ -54,12 +56,15 @@ class SQLiteFlowPersistence(FlowPersistence):
timestamp DATETIME NOT NULL,
state_json TEXT NOT NULL
)
""")
"""
)
# Add index for faster UUID lookups
conn.execute("""
conn.execute(
"""
CREATE INDEX IF NOT EXISTS idx_flow_states_uuid
ON flow_states(flow_uuid)
""")
"""
)
def save_state(
self,
@@ -85,19 +90,22 @@ class SQLiteFlowPersistence(FlowPersistence):
)
with sqlite3.connect(self.db_path) as conn:
conn.execute("""
conn.execute(
"""
INSERT INTO flow_states (
flow_uuid,
method_name,
timestamp,
state_json
) VALUES (?, ?, ?, ?)
""", (
flow_uuid,
method_name,
datetime.utcnow().isoformat(),
json.dumps(state_dict),
))
""",
(
flow_uuid,
method_name,
datetime.now(timezone.utc).isoformat(),
json.dumps(state_dict),
),
)
def load_state(self, flow_uuid: str) -> Optional[Dict[str, Any]]:
"""Load the most recent state for a given flow UUID.
@@ -109,13 +117,16 @@ class SQLiteFlowPersistence(FlowPersistence):
The most recent state as a dictionary, or None if no state exists
"""
with sqlite3.connect(self.db_path) as conn:
cursor = conn.execute("""
cursor = conn.execute(
"""
SELECT state_json
FROM flow_states
WHERE flow_uuid = ?
ORDER BY id DESC
LIMIT 1
""", (flow_uuid,))
""",
(flow_uuid,),
)
row = cursor.fetchone()
if row:

View File

@@ -16,7 +16,8 @@ Example
import ast
import inspect
import textwrap
from typing import Any, Dict, List, Optional, Set, Union
from collections import defaultdict, deque
from typing import Any, Deque, Dict, List, Optional, Set, Union
def get_possible_return_constants(function: Any) -> Optional[List[str]]:
@@ -118,7 +119,7 @@ def calculate_node_levels(flow: Any) -> Dict[str, int]:
- Processes router paths separately
"""
levels: Dict[str, int] = {}
queue: List[str] = []
queue: Deque[str] = deque()
visited: Set[str] = set()
pending_and_listeners: Dict[str, Set[str]] = {}
@@ -128,28 +129,35 @@ def calculate_node_levels(flow: Any) -> Dict[str, int]:
levels[method_name] = 0
queue.append(method_name)
# Precompute listener dependencies
or_listeners = defaultdict(list)
and_listeners = defaultdict(set)
for listener_name, (condition_type, trigger_methods) in flow._listeners.items():
if condition_type == "OR":
for method in trigger_methods:
or_listeners[method].append(listener_name)
elif condition_type == "AND":
and_listeners[listener_name] = set(trigger_methods)
# Breadth-first traversal to assign levels
while queue:
current = queue.pop(0)
current = queue.popleft()
current_level = levels[current]
visited.add(current)
for listener_name, (condition_type, trigger_methods) in flow._listeners.items():
if condition_type == "OR":
if current in trigger_methods:
if (
listener_name not in levels
or levels[listener_name] > current_level + 1
):
levels[listener_name] = current_level + 1
if listener_name not in visited:
queue.append(listener_name)
elif condition_type == "AND":
for listener_name in or_listeners[current]:
if listener_name not in levels or levels[listener_name] > current_level + 1:
levels[listener_name] = current_level + 1
if listener_name not in visited:
queue.append(listener_name)
for listener_name, required_methods in and_listeners.items():
if current in required_methods:
if listener_name not in pending_and_listeners:
pending_and_listeners[listener_name] = set()
if current in trigger_methods:
pending_and_listeners[listener_name].add(current)
if set(trigger_methods) == pending_and_listeners[listener_name]:
pending_and_listeners[listener_name].add(current)
if required_methods == pending_and_listeners[listener_name]:
if (
listener_name not in levels
or levels[listener_name] > current_level + 1
@@ -159,22 +167,7 @@ def calculate_node_levels(flow: Any) -> Dict[str, int]:
queue.append(listener_name)
# Handle router connections
if current in flow._routers:
router_method_name = current
paths = flow._router_paths.get(router_method_name, [])
for path in paths:
for listener_name, (
condition_type,
trigger_methods,
) in flow._listeners.items():
if path in trigger_methods:
if (
listener_name not in levels
or levels[listener_name] > current_level + 1
):
levels[listener_name] = current_level + 1
if listener_name not in visited:
queue.append(listener_name)
process_router_paths(flow, current, current_level, levels, queue)
return levels
@@ -227,10 +220,7 @@ def build_ancestor_dict(flow: Any) -> Dict[str, Set[str]]:
def dfs_ancestors(
node: str,
ancestors: Dict[str, Set[str]],
visited: Set[str],
flow: Any
node: str, ancestors: Dict[str, Set[str]], visited: Set[str], flow: Any
) -> None:
"""
Perform depth-first search to build ancestor relationships.
@@ -274,7 +264,9 @@ def dfs_ancestors(
dfs_ancestors(listener_name, ancestors, visited, flow)
def is_ancestor(node: str, ancestor_candidate: str, ancestors: Dict[str, Set[str]]) -> bool:
def is_ancestor(
node: str, ancestor_candidate: str, ancestors: Dict[str, Set[str]]
) -> bool:
"""
Check if one node is an ancestor of another.
@@ -339,7 +331,9 @@ def build_parent_children_dict(flow: Any) -> Dict[str, List[str]]:
return parent_children
def get_child_index(parent: str, child: str, parent_children: Dict[str, List[str]]) -> int:
def get_child_index(
parent: str, child: str, parent_children: Dict[str, List[str]]
) -> int:
"""
Get the index of a child node in its parent's sorted children list.
@@ -360,3 +354,23 @@ def get_child_index(parent: str, child: str, parent_children: Dict[str, List[str
children = parent_children.get(parent, [])
children.sort()
return children.index(child)
def process_router_paths(flow, current, current_level, levels, queue):
"""
Handle the router connections for the current node.
"""
if current in flow._routers:
paths = flow._router_paths.get(current, [])
for path in paths:
for listener_name, (
condition_type,
trigger_methods,
) in flow._listeners.items():
if path in trigger_methods:
if (
listener_name not in levels
or levels[listener_name] > current_level + 1
):
levels[listener_name] = current_level + 1
queue.append(listener_name)

View File

@@ -64,6 +64,7 @@ LLM_CONTEXT_WINDOW_SIZES = {
"gpt-4-turbo": 128000,
"o1-preview": 128000,
"o1-mini": 128000,
"o3-mini": 200000, # Based on official o3-mini specifications
# gemini
"gemini-2.0-flash": 1048576,
"gemini-1.5-pro": 2097152,
@@ -485,10 +486,23 @@ class LLM:
"""
Returns the context window size, using 75% of the maximum to avoid
cutting off messages mid-thread.
Raises:
ValueError: If a model's context window size is outside valid bounds (1024-2097152)
"""
if self.context_window_size != 0:
return self.context_window_size
MIN_CONTEXT = 1024
MAX_CONTEXT = 2097152 # Current max from gemini-1.5-pro
# Validate all context window sizes
for key, value in LLM_CONTEXT_WINDOW_SIZES.items():
if value < MIN_CONTEXT or value > MAX_CONTEXT:
raise ValueError(
f"Context window for {key} must be between {MIN_CONTEXT} and {MAX_CONTEXT}"
)
self.context_window_size = int(
DEFAULT_CONTEXT_WINDOW_SIZE * CONTEXT_WINDOW_USAGE_RATIO
)

View File

@@ -39,8 +39,8 @@
"validation_error": "### Previous attempt failed validation: {guardrail_result_error}\n\n\n### Previous result:\n{task_output}\n\n\nTry again, making sure to address the validation error."
},
"tools": {
"delegate_work": "Delegate a specific task to one of the following coworkers: {coworkers}\nThe input to this tool should be the coworker, the task you want them to do, and ALL necessary context to execute the task, they know nothing about the task, so share absolute everything you know, don't reference things but instead explain them.",
"ask_question": "Ask a specific question to one of the following coworkers: {coworkers}\nThe input to this tool should be the coworker, the question you have for them, and ALL necessary context to ask the question properly, they know nothing about the question, so share absolute everything you know, don't reference things but instead explain them.",
"delegate_work": "Delegate a specific task to one of the following coworkers: {coworkers}\nThe input to this tool should be the coworker, the task you want them to do, and ALL necessary context to execute the task, they know nothing about the task, so share absolutely everything you know, don't reference things but instead explain them.",
"ask_question": "Ask a specific question to one of the following coworkers: {coworkers}\nThe input to this tool should be the coworker, the question you have for them, and ALL necessary context to ask the question properly, they know nothing about the question, so share absolutely everything you know, don't reference things but instead explain them.",
"add_image": {
"name": "Add image to content",
"description": "See image to understand its content, you can optionally ask a question about the image",

View File

@@ -44,6 +44,7 @@ def create_llm(
# Extract attributes with explicit types
model = (
getattr(llm_value, "model_name", None)
or getattr(llm_value, "model", None)
or getattr(llm_value, "deployment_name", None)
or str(llm_value)
)

View File

@@ -6,7 +6,7 @@ import pytest
from pydantic import BaseModel
from crewai.agents.agent_builder.utilities.base_token_process import TokenProcess
from crewai.llm import LLM
from crewai.llm import CONTEXT_WINDOW_USAGE_RATIO, LLM
from crewai.utilities.events import crewai_event_bus
from crewai.utilities.events.tool_usage_events import ToolExecutionErrorEvent
from crewai.utilities.token_counter_callback import TokenCalcHandler
@@ -285,6 +285,23 @@ def test_o3_mini_reasoning_effort_medium():
assert isinstance(result, str)
assert "Paris" in result
def test_context_window_validation():
"""Test that context window validation works correctly."""
# Test valid window size
llm = LLM(model="o3-mini")
assert llm.get_context_window_size() == int(200000 * CONTEXT_WINDOW_USAGE_RATIO)
# Test invalid window size
with pytest.raises(ValueError) as excinfo:
with patch.dict(
"crewai.llm.LLM_CONTEXT_WINDOW_SIZES",
{"test-model": 500}, # Below minimum
clear=True,
):
llm = LLM(model="test-model")
llm.get_context_window_size()
assert "must be between 1024 and 2097152" in str(excinfo.value)
@pytest.mark.vcr(filter_headers=["authorization"])
@pytest.fixture