This could be something

[Lucyan11]

I put together the gpt4 pdf langchain model and then converted your project into pdf form. And I have had an interestin sucess. My next goal is to have the autogpt talk directly to it that way it can ask any questions about its code and how to improve it it in a 2 way conversation.

Took a few adjustments, but then bingo

AI
Hi, what would you like to learn about this legal case?

Me
Tell me about the pdf

AI
Hmm, I'm not sure.

Source 1

Source 2
Me
what language is the program writen in?

AI
Hmm, I'm not sure.

Source 1

Source 2
Me
read the first 10 lines

AI
Hmm, I'm not sure.

Source 1

Source 2
Me
what are the first words?

AI
The first words of the pdf are: "Funding.yml".

Source 1

Source 2
Me
that is incorect. are you able to read this file?

AI
Hmm, I'm not sure.

Source 1

Source 2
This is the structure of the project https://github.com/Torantulino/Auto-GPT

Auto-GPT .github ┣ ISSUE_TEMPLATE ┃ ┣ 1.bug.yml ┃ ┗ 2.feature.yml ┣ workflows ┃ ┗ auto_format.yml ┣ FUNDING.yml ┗ PULL_REQUEST_TEMPLATE.md auto_gpt_workspace outputs ┣ logs ┃ ┣ message-log-1.txt ┃ ┣ message-log-2.txt ┃ ┣ message-log-3.txt ┃ ┗ message-log-4.txt ┣ guest_post_email.txt ┣ how_to_save_money_on_energy_bills.txt ┣ post1_output.txt ┗ post2_output.txt pdfGPT ┣ .git ┃ ┣ fsmonitor--daemon ┃ ┃ ┗ cookies ┃ ┣ hooks ┃ ┃ ┣ applypatch-msg.sample ┃ ┃ ┣ commit-msg.sample ┃ ┃ ┣ fsmonitor-watchman.sample ┃ ┃ ┣ post-update.sample ┃ ┃ ┣ pre-applypatch.sample ┃ ┃ ┣ pre-commit.sample ┃ ┃ ┣ pre-merge-commit.sample ┃ ┃ ┣ pre-push.sample ┃ ┃ ┣ pre-rebase.sample ┃ ┃ ┣ pre-receive.sample ┃ ┃ ┣ prepare-commit-msg.sample ┃ ┃ ┣ push-to-checkout.sample ┃ ┃ ┗ update.sample ┃ ┣ info ┃ ┃ ┗ exclude ┃ ┣ logs ┃ ┃ ┣ refs ┃ ┃ ┃ ┣ heads

Source: D:\gpt4-pdf-chatbot-langchain\docs\autobot\autobot.pdf

Me
how many pages is it?

AI
Hmm, I'm not sure.

Source 1

Source 2
Me
how would i improve the api call functions?

AI
Based on the provided context, I have a few suggestions for improving the API call functions:

In the evaluate_code and improve_code functions, consider using more descriptive variable names for better readability and maintainability. For example, you could rename function_string to analyze_code_function and result_string to suggestions_list.

In the write_tests function, the focus parameter is of type List[str], but in the args list, you are using json.dumps(focus). It would be better to keep the data types consistent. Either change the type of focus to Optional[str] or remove the json.dumps() call when passing the focus parameter.

Add error handling and validation for the input parameters in each function. This will help ensure that the functions are more robust and can handle unexpected inputs gracefully.

Consider adding docstrings to each function to provide more information about their purpose, input parameters, and expected output. This will make it easier for others to understand and use your code.

You may want to refactor the call_ai_function function to accept a dictionary of arguments instead of a list. This would make it easier to understand which arguments are being passed and their corresponding values.

[Lucyan11]

It worked!!