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[GH-ISSUE #24] no operation provided:) #10
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Originally created by @sfz009900 on GitHub (Mar 28, 2025).
Original GitHub issue: https://github.com/vxcontrol/pentagi/issues/24
Originally assigned to: @asdek on GitHub.
My.env configuration is as follows:
Then my docker-compose.yml configuration is as follows:
But return visit https://localhost:8443/api/v1/graphql:
{"errors":[{"message":"no operation provided","extensions":{"code":"GRAPHQL_VALIDATION_FAILED"}}],"data":null}@sfz009900 commented on GitHub (Mar 28, 2025):
This is the result of "docker exec -it pentagi/ opt/pentagi/bin/ ctester-verbose ":
But an error is still reported:
@asdek commented on GitHub (Mar 28, 2025):
Hello @sfz009900
Thank you for bringing this to our attention.
It appears there's a bug in the latest update where the LLM Provider isn't automatically populated when you first open the interface. To resolve this issue for now, please manually select the appropriate provider from the dropdown list.
I'm working on a fix to address this problem and will provide an update soon within this issue.
@sfz009900 commented on GitHub (Mar 28, 2025):
@asdek Same thing happened to me now 😅https://github.com/vxcontrol/pentagi/issues/19#issuecomment-2759999134
@asdek commented on GitHub (Mar 28, 2025):
@sfz009900 I'll do my best 😉
@sfz009900 commented on GitHub (Mar 28, 2025):
Wow @asdek, you're a lifesaver! It'd be awesome if we could customize things though, like with an ollama embedding query or something. 😉
@sfz009900 commented on GitHub (Mar 28, 2025):
Hey @asdek sorry! Forgot I have a third-party API that's compatible with OpenAI. I can set it up for just OpenAI, and then the embedded model should be good to go :)
@sfz009900 commented on GitHub (Mar 28, 2025):
Hey @asdek, something seems off here... 🤔
@sfz009900 commented on GitHub (Mar 28, 2025):
It keeps trying to download "https://http.kali.org/kali/pool/main/b/bind9/dnsutils_9.18.16-1_all.deb" but that thing doesn't exist! It's stuck in a loop, lol.
@asdek commented on GitHub (Mar 28, 2025):
@sfz009900
First of all, thank you so much for your kind words! I'm glad the solution was helpful to you. 😊
Regarding Customizing Embeddings with Ollama:
Support for Ollama was implemented in the early versions of the product. However, as the number of functions grew and with the increasing need for strict adherence to JSON structures when invoking functions, we had to discontinue that support. Unfortunately, I couldn't find models that were sophisticated enough to handle complex tasks like attack simulations. These LLMs also tended to deviate from the required function structure, making it challenging to guide them back on track. The context length likely plays a significant role in this issue.
Using an OpenAI-Compatible Backend:
If you have an OpenAI-compatible backend, the Custom provider is designed to work seamlessly with such interfaces. You can finely tune the model's parameters through your own configuration file to make it respond more accurately to your requests. All parameters specified in the OpenAI API specification are supported.
You can find more details here: Custom Provider Configuration.
Issue with Installing
dnsutils:Regarding the issue you're experiencing with the installation of the
dnsutilspackage, it seems there's a problem with the apt repository:Apt Update Error: The error during
apt updateindicates that the package lists aren't being updated due to a GPG key error. This means apt isn't aware of the latest packages, which is why it tries to download a package version that no longer exists on the server.Cached Package Lists: It's possible that when the Docker image was built, the package lists were cached and haven't been updated since. Therefore,
aptis attempting to fetch an outdated version ofdnsutilsFor Now:
You can explicitly specify in your initial task prompt which Docker image the agent should use, and it will follow those instructions. If you find a more suitable image from another repository, please let me know! 😉
About the Embedding Server Support:
I'll do my best to deliver this update tomorrow. However, today's update includes many useful fixes, including resolving the issue you mentioned earlier with the empty provider value in the UI and more.
Additional Information on Model Behavior:
PentAGI includes a separate agent called "reflector" that monitors the format of responses and attempts to guide the model when it makes mistakes. However, with smaller models, this doesn't always help, and tasks sometimes still end with errors. For example, I couldn't get Mistral-3.1-24B to work properly, and there were issues with Qwen-32B as well.
Configuring the initial prompt to ensure models strictly follow instructions often requires significant effort. Here's an example of one of the prompts for testing web applications, where we have to provide detailed instructions on how to perform and decompose tasks: Web Pentest Base Prompt.
@asdek commented on GitHub (Mar 29, 2025):
Hello @sfz009900
I replied here in #21
I hope that it's will be helpful for your case.