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Base Functions

This document summarizes the functions in the app.py file that handle various API routes for an AI agent. There are functions for translation, returning the agent's details, running commands on the system, fetching internet content, and more. The functions use an LLMIndex object for translation and the server is configured to integrate with Langchain. The server starts a Flask application to provide an API to interact with the agent's capabilities.

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28 views1 page

Base Functions

This document summarizes the functions in the app.py file that handle various API routes for an AI agent. There are functions for translation, returning the agent's details, running commands on the system, fetching internet content, and more. The functions use an LLMIndex object for translation and the server is configured to integrate with Langchain. The server starts a Flask application to provide an API to interact with the agent's capabilities.

Uploaded by

denny7437
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Download as PDF, TXT or read online on Scribd
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base-functions.

md 2024-02-27

Here's a summary of the functions in app.py:


. translate(): This function handles the /translate route, which accepts a POST request with a
JSON payload containing the text to translate, the source language, and the target language. It uses
the LLMIndex object to translate the text and returns the translation in the response as JSON.
. index(): This function handles the root route (/) and returns a string containing the AI agent's
name, version, and description.
. run_langchain_api(): This function handles the /runLangchain route, which accepts a POST
request with a JSON payload containing the text to process using Langchain. It sends a request to
the Langchain API with the provided text and returns the response as JSON.
. create_file_route(): This function handles the /createFile route, which accepts a POST
request with a JSON payload containing the file name and content. It creates a file with the provided
name and content and returns a success message as JSON.
. execute_command_route(): This function handles the /executeCommand route, which accepts a
POST request with a JSON payload containing the command name and arguments. It executes the
command with the provided arguments and returns the result as JSON.
. get_environment_details_route(): This function handles the /getEnvironmentDetails
route, which accepts a GET request. It returns environment details as JSON.
. run_val_script_api(): This function handles the /runValScript route, which accepts a POST
request with a JSON payload containing the script name. It runs the Val script with the provided name
and returns the result as JSON.
. fetch_internet_api(): This function handles the /fetchInternet route, which accepts a GET
request with a URL query parameter. It fetches the content of the URL and returns it as JSON.
These functions are part of a Flask application that provides an API for interacting with the AI agent and its
capabilities. The server is configured with Langchain, and the LLMIndex object is used for translation. The
server is started at the end of the script when the __name__ is __main__.
Note from the developer: There are other
functionalities like a Vectorstore for easy RAG,
Autonomous Agent and Copilot / AI Assistant
I highly recommend commenting out the
/executeCommand function because it is very real
and can destroy your computer

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