refereshed after short vacation.. hope to see you frequently

The quality is 10/10 thanks mate

Hey Brandon, welcome back after your vacay!

thanks! Your crewai tutorial are top-of-the-shelf stuff. do you have any crewai proejct with streamlit connected to show output on the ui? thanks

Man, I do not know how to create and write code but you have made a video and I think I can do this! Bless you my friend!

Thanks! Is Claude 3 opus still not supported though? How come?

Great stuff. Maybe a silly question, but when it was fetching to read data from remote website (the analysis part), does it read it remotely OR does it capture screenshots & download text to feed into its prompt and then clear this cached data or such local cached data needs to be cleaned eventually? Hope it simply reads remotely without too much data saved locally as I plan to use this approach to analyze many websites without flooding my local storage.

Friendly commment: You look better with glasses, more professional. Great content.

Great content as always! Do you know if it's sustainable to use a single groqcloud API key to host LLM access for a multi-user app? Or would a service like AWS Sagemaker be better for simultaneous users? Cheers!

Appreciate your support (with those contents), the only drawback, was the need to subscribe to get access to a project that isn't yours. 😞

What would you say are the minimum hardware requirements to make it run smoothly?

Brandon excellent tutorial 👍

Thank you :)

Excellent video! Would be interesting to see these frameworks, but within LightningAI Studios. Also, I saw CrewAI will be having a more golden standard approach to their code structuring in the near future.

Thank you for this and for the code.. How does Llama 3 compare to Dolphin-Mistral 2.8 running locally as the more junior agents do you know? Dolphin-Mistral with its extra conversatuon/coding training and bigger 32k context window appeals! Ive had agents go round in circles creating nonsense with other frameworks as they dont remember what they are supposed to do! A big context window defo could bring some benefits! I try and avoid using GPT3.5 or 4 for coding preferring for this reason. Id then like to use Claude 3 Opus with his 200k context window and extra capability for the heavy liftin and oversight!

This is awesome! 😎

your awesome, thank you!

Hi Brandon, the groq rate limit is a big issue for my use case, can i use this same method to use another similar hosted llama 3 70b with crewai like openrouter api or can any api be used instead of groq with your method?

Nice! 😃

Please for the love of god somebody explain to me why we are using Ollama to download local models and then using Groq anyway to run the model in the cloud. Why can't we just skip the ollama part? I beg you i see all the videos using Ollama with Groq and i don't understand the aspect! thank you. Does ollama do something special to make it work better for crewai then a direct Groq connect?

perfect run with Groq. I get great speeds on my PC with Local LLAMA3, but nothing I can do stops it throwing errors. I find that before with other projects thgat a lot of local LLMs have odd issues that change each run from failing to run functions as they change the name to just saying they cant pass tool info. Must be something in the local limitations either with Ollama or CrewAi.

I get a error, then I noticed that we need search api, I added that but still get the error pydantic_core._pydantic_core.ValidationError: 1 validation error for Task expected_output Field required [type=missing, input_value={'description': "Analyze ...e business landscapes.)}, input_type=dict]

Is there an easy way to build No Code AI Assistants or Agents with Groq? I know zero code

That is using a very old version of CrewAI - if you run it with the current version of CrewAI it fails because of lack of expected_output parameter in the Tasks

Just curious why VSCode doesn't display file types on Mac. I'm going bonkers trying to figure out what to save the Modelfile as.

With both the Groq 8b and 70b with crew max_rpm set at both 1 or 2 I do get it halting for a while with: [INFO]: Max RPM reached, waiting for next minute to start.

What graphic card do you use on your computer when running local with Ollama?

Hello sir Nice content

might want to revoke those keys you revealed if you haven't

gyus do u know any way to run crewai and\or llama on gpu? only CPU is soooooooooooooooooooooooo sloooooooooooooow

Very good video demonstration. I noticed that you chose to use serper search in the video. I would like to know the difference between serper and duckduckgo search and how to choose between them. If you know, please introduce it to me. Thank you.

Hello Brandon thanks for the awesome video, I was trying to do the same setup with crew AI, but I am getting an error while running, I added the error message below Traceback (most recent call last): File "D:\crew_ai\crew.py", line 114, in result = crew.kickoff() ^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\crewai\crew.py", line 252, in kickoff result = self._run_sequential_process() ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\crewai\crew.py", line 293, in _run_sequential_process output = task.execute(context=task_output) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\crewai\task.py", line 173, in execute result = self._execute( ^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\crewai\task.py", line 182, in _execute result = agent.execute_task( ^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\crewai\agent.py", line 207, in execute_task memory = contextual_memory.build_context_for_task(task, context) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\crewai\memory\contextual\contextual_memory.py", line 22, in build_context_for_task context.append(self._fetch_stm_context(query)) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\crewai\memory\contextual\contextual_memory.py", line 31, in _fetch_stm_context stm_results = self.stm.search(query) ^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\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 "D:\crew_ai\.my_crew_env\Lib\site-packages\crewai\memory\storage ag_storage.py", line 90, in search else self.app.search(query, limit) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\embedchain\embedchain.py", line 635, in search return [{"context": c[0], "metadata": c[1]} for c in self.db.query(**params)] ^^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\embedchain\vectordb\chroma.py", line 220, in query result = self.collection.query( ^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\chromadb\api\models\Collection.py", line 327, in query valid_query_embeddings = self._embed(input=valid_query_texts) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\chromadb\api\models\Collection.py", line 633, in _embed return self._embedding_function(input=input) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\chromadb\api\types.py", line 193, in __call__ result = call(self, input) ^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\chromadb\utils\embedding_functions.py", line 188, in __call__ embeddings = self._client.create( ^^^^^^^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\site-packages\openai esources\embeddings.py", line 113, in create return self._post( ^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\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 "D:\crew_ai\.my_crew_env\Lib\site-packages\openai\_base_client.py", line 921, in request return self._request( ^^^^^^^^^^^^^^ File "D:\crew_ai\.my_crew_env\Lib\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