Closed lijinta1984 closed 2 days ago
Had the exact same issue. Upgraded pip to latest (0.28.8 as of right this second) Cured issue.
Got same issue!
Try upgrading crewai - pip install crewai --upgrade
Hey thanks for the quick reply.
I am already in the latest version
crewai==0.28.8
crewai-tools==0.1.7
from the docs I am testing this main.py
from crewai import Crew, Process, Task
from tasks import Tasks
from agents import Agents
from dotenv import load_dotenv
load_dotenv()
from crewai import Agent
from crewai_tools import SerperDevTool
search_tool = SerperDevTool()
# Creating a senior researcher agent with memory and verbose mode
researcher = Agent(
role='Senior Researcher',
goal='Uncover groundbreaking technologies in {topic}',
verbose=True,
memory=True,
backstory=(
"Driven by curiosity, you're at the forefront of"
"innovation, eager to explore and share knowledge that could change"
"the world."
),
tools=[search_tool],
allow_delegation=True
)
# Creating a writer agent with custom tools and delegation capability
writer = Agent(
role='Writer',
goal='Narrate compelling tech stories about {topic}',
verbose=True,
memory=True,
backstory=(
"With a flair for simplifying complex topics, you craft"
"engaging narratives that captivate and educate, bringing new"
"discoveries to light in an accessible manner."
),
tools=[search_tool],
allow_delegation=False
)
research_task = Task(
description=(
"Identify the next big trend in {topic}."
"Focus on identifying pros and cons and the overall narrative."
"Your final report should clearly articulate the key points,"
"its market opportunities, and potential risks."
),
expected_output='A comprehensive 3 paragraphs long report on the latest AI trends.',
tools=[search_tool],
agent=researcher,
)
# Writing task with language model configuration
write_task = Task(
description=(
"Compose an insightful article on {topic}."
"Focus on the latest trends and how it's impacting the industry."
"This article should be easy to understand, engaging, and positive."
),
expected_output='A 4 paragraph article on {topic} advancements formatted as markdown.',
tools=[search_tool],
agent=writer,
async_execution=False,
output_file='new-blog-post.md' # Example of output customization
)
crew = Crew(
agents=[researcher, writer],
tasks=[research_task, write_task],
process=Process.sequential, # Optional: Sequential task execution is default
memory=True,
cache=True,
max_rpm=100,
share_crew=True
)
result = crew.kickoff(inputs={'topic': 'AI in healthcare'})
print(result)
and I am trying to use lama3 in local here is the env for that
OPENAI_API_BASE=http://localhost:11434/v1
OPENAI_MODEL_NAME=crewai-llama3
OPENAI_API_KEY=NA
I have build the crewai-llama3
locally
and when I try to run I am getting following error
Traceback (most recent call last):
File "/Users/kartik/Code/experiments/ai/learning_pyenv/main.py", line 79, in <module>
result = crew.kickoff(inputs={'topic': 'AI in healthcare'})
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/crew.py", line 252, in kickoff
result = self._run_sequential_process()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/crew.py", line 293, in _run_sequential_process
output = task.execute(context=task_output)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/task.py", line 173, in execute
result = self._execute(
^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/task.py", line 182, in _execute
result = agent.execute_task(
^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/agent.py", line 207, in execute_task
memory = contextual_memory.build_context_for_task(task, context)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/memory/contextual/contextual_memory.py", line 22, in build_context_for_task
context.append(self._fetch_stm_context(query))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/memory/contextual/contextual_memory.py", line 31, in _fetch_stm_context
stm_results = self.stm.search(query)
^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/memory/short_term/short_term_memory.py", line 23, in search
return self.storage.search(query=query, score_threshold=score_threshold)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/memory/storage/rag_storage.py", line 90, in search
else self.app.search(query, limit)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/embedchain/embedchain.py", line 635, in search
return [{"context": c[0], "metadata": c[1]} for c in self.db.query(**params)]
^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/embedchain/vectordb/chroma.py", line 220, in query
result = self.collection.query(
^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/chromadb/api/models/Collection.py", line 327, in query
valid_query_embeddings = self._embed(input=valid_query_texts)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/chromadb/api/models/Collection.py", line 633, in _embed
return self._embedding_function(input=input)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/chromadb/api/types.py", line 193, in __call__
result = call(self, input)
^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/chromadb/utils/embedding_functions.py", line 188, in __call__
embeddings = self._client.create(
^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/openai/resources/embeddings.py", line 114, in create
return self._post(
^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/openai/_base_client.py", line 1232, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/openai/_base_client.py", line 921, in request
return self._request(
^^^^^^^^^^^^^^
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/openai/_base_client.py", line 1012, in _request
raise self._make_status_error_from_response(err.response) from None
openai.NotFoundError: 404 page not found
Exception in thread Thread-1:
Traceback (most recent call last):
File "/opt/homebrew/opt/python@3.12/lib/python3.12/threading.py", line 1073, in _bootstrap_inner
self.run()
File "/opt/homebrew/opt/python@3.12/lib/python3.12/threading.py", line 1431, in run
self.function(*self.args, **self.kwargs)
File "/Users/kartik/.local/share/virtualenvs/learning_pyenv-snJKqLZa/lib/python3.12/site-packages/crewai/utilities/rpm_controller.py", line 59, in _reset_request_count
self._timer.start()
File "/opt/homebrew/opt/python@3.12/lib/python3.12/threading.py", line 992, in start
_start_new_thread(self._bootstrap, ())
RuntimeError: can't create new thread at interpreter shutdown
My project use pip env I can share my project for testing if required let me know.
Thanks @theCyberTech
Any update on this?
hey @kartik1225 I think i hit the same issue and removed the "imputs=" so that my kickoff works like this:
crew.kickoff({"topic": topic})
same issue i also get.even after changing to crew.kickoff({"topic": topic}) it gives same error
Same issue, checked input to be of type Dict[Str : Any] and it still gave the error.
Same problem. No answer yet.
It seems some people got it fixed by using a more up to date version, for the folks that are still experiencing this could you share what version you are using?
I've tried like this: crew.kickoff(inputs={"topic": topic}) and works for me.
Or you can try also: crew.kickoff({"topic": topic}), without inputs parameter. Also works!
I uninstalled Crew, updated to the latest version and applied this suggestion by thallys and it worked:
crew.kickoff(inputs={"topic": topic}) .
It was driving me crazy :D
i am on crewai==-0.1.7. tried a bunch of things. still complains about unexpected keyword argument 'inputs'
. this is very frustrating.
This issue is stale because it has been open for 30 days with no activity. Remove stale label or comment or this will be closed in 5 days.
Consegui resolver o problema da seguinte maneira:
from crewai import Crew, Process, Task
from tasks import Tasks
from agents import Agents
from dotenv import load_dotenv
load_dotenv()
from crewai import Agent
from crewai_tools import SerperDevTool
search_tool = SerperDevTool()
# Creating a senior researcher agent with memory and verbose mode
researcher = Agent(
role='Senior Researcher',
goal='Uncover groundbreaking technologies in {topic}',
verbose=True,
memory=True,
backstory=(
"Driven by curiosity, you're at the forefront of"
"innovation, eager to explore and share knowledge that could change"
"the world."
),
tools=[search_tool],
allow_delegation=True
)
# Input
topics = "AI in healthcare"
# Creating a writer agent with custom tools and delegation capability
writer = Agent(
role='Writer',
goal='Narrate compelling tech stories about {topic}',
verbose=True,
memory=True,
backstory=(
"With a flair for simplifying complex topics, you craft"
"engaging narratives that captivate and educate, bringing new"
"discoveries to light in an accessible manner."
),
tools=[search_tool],
allow_delegation=False
)
research_task = Task(
description=(
f"""
Identify the next big trend in {topic}.
Focus on identifying pros and cons and the overall narrative.
Your final report should clearly articulate the key points,
its market opportunities, and potential risks.
"""
),
expected_output='A comprehensive 3 paragraphs long report on the latest AI trends.',
tools=[search_tool],
agent=researcher,
)
# Writing task with language model configuration
write_task = Task(
description=(
f """ Compose an insightful article on {topic}.
Focus on the latest trends and how it's impacting the industry.
This article should be easy to understand, engaging, and positive.
"""),
expected_output=f'A 4 paragraph article on {topic} advancements formatted as markdown.',
tools=[search_tool],
agent=writer,
async_execution=False,
output_file='new-blog-post.md' # Example of output customization
)
crew = Crew(
agents=[researcher, writer],
tasks=[research_task, write_task],
process=Process.sequential, # Optional: Sequential task execution is default
memory=True,
cache=True,
max_rpm=100,
share_crew=True
)
result = crew.kickoff()
print(result)
Got this error while running the script:
Traceback (most recent call last): File "/home/lijin/crew.py", line 75, in
result = crew.kickoff(inputs={'topic': 'AMD Ryzen 7 Mini PCs'})
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: Crew.kickoff() got an unexpected keyword argument 'inputs'
This is the full code:
Traceback (most recent call last): import os from crewai import Task from crewai import Crew, Process from crewai import Agent from crewai_tools import SerperDevTool
os.environ["SERPER_API_KEY"] = "xxxxx" # serper.dev API key os.environ["OPENAI_API_KEY"] = "xxxxxxx"
search_tool = SerperDevTool()
Creating a senior researcher agent with memory and verbose mode
researcher = Agent( role='Senior Researcher', goal='Uncover groundbreaking technologies in {topic}', verbose=True, memory=True, backstory=( "Driven by curiosity, you're at the forefront of" "innovation, eager to explore and share knowledge that could change" "the world." ), tools=[search_tool], allow_delegation=True )
Creating a writer agent with custom tools and delegation capability
writer = Agent( role='Writer', goal='Narrate compelling tech stories about {topic}', verbose=True, memory=True, backstory=( "With a flair for simplifying complex topics, you craft" "engaging narratives that captivate and educate, bringing new" "discoveries to light in an accessible manner." ), tools=[search_tool], allow_delegation=False )
Research task
research_task = Task( description=( "Identify the next big trend in {topic}." "Focus on identifying pros and cons and the overall narrative." "Your final report should clearly articulate the key points" "its market opportunities, and potential risks." ), expected_output='A comprehensive 3 paragraphs long report on the latest innovations.', tools=[search_tool], agent=researcher, )
Writing task with language model configuration
write_task = Task( description=( "Compose an insightful article on {topic}." "Focus on the latest trends and how it's impacting the industry." "This article should be easy to understand, engaging, and positive." ), expected_output='A 4 paragraph article on {topic} advancements formatted as markdown.', tools=[search_tool], agent=writer, async_execution=False, output_file='new-blog-post.md' # Example of output customization )
Forming the tech-focused crew with enhanced configurations
crew = Crew( agents=[researcher, writer], tasks=[research_task, write_task], process=Process.sequential # Optional: Sequential task execution is default )
Starting the task execution process with enhanced feedback
result = crew.kickoff(inputs={'topic': 'AMD Ryzen 7 Mini PCs'}) print(result)