RobotFramework-AI
is a library that adds AI functionality to the Robot Framework
.
It can generate test data for you using the RealTestDataGenerator
but also reply to your
messages with the Chatbot
.
To setup the library:
Start by cloning this repository.
Open a terminal and locate the robotframework-ai
folder.
Use the following command to create the package.
python setup.py sdist bdist_wheel
This requires the wheel package to be installed, which can be installed with:
pip install wheel
To install the library using the package just created, use the following command.
pip install .\dist\RobotFrameworkAI-0.0.2-py3-none-any.whl
Setup the API key for the AI you want to use. This can be done by creating a new environment variable called OPENAI_KEY
with your key as the value. More information about this in the AI models header below.
The library is now properly setup, to confirm it works, run the following code in a robot file. This will generate 3 addresses and create a log.html file.
*** Settings ***
Library RobotFrameworkAI
*** Test Cases ***
Exec Test
[Documentation] Test
${response} Generate Test Data openai address
Log ${response}
Opening this testlog file in a browser and opening the suite Test
, the test Exec test
and the keyword Log
will reveal a list with the 3 addresses in the INFO
section.
Each module in the RobotFramework-AI library can support multiple different AI models. Each AI model needs an API key for the generation of test data. This key gets read directly from your environment variables. Each AI model has their own API key. To define a key, create a new variable with the name of the AI model capitalized followed by "_KEY". Then set this variable to your key. At the moment only OpenAI is supported.
Example API keys
RealTestDataGenerator
can generate test data for the Robot Framework
similar to
the library Faker
. The RealTestDataGenerator
however, generates real existing data, using AI.
To generate test data simply import the package and use the keyword: Generate Test Data
This keyword takes various arguments, some being specific for the generation of certain
types of test data.
The following arguments can be used (arguments prefixed by an * are required):
NOTE: Be careful with changing the temperature, top p, frequency- and presence penalty as it will likely deviate from the format we expect it to return.
When generating addresses additional argument are available. These arguments are as follows:
Generate 3 addresses from anywhere using OpenAI:
Generate Test Data openai address
Generate 10 addresses from Finland using the gpt-3.5-turbo from OpenAI in the default format with a token limit at 1024, temperature at 1, top p at .5 and frequency- and presence penalty at 0
Generate Test Data openai address gpt-3.5-turbo 10 None 1024 1 .5 0 0 country=finland
The Chatbot
is a simple response generating library for Robot Framework
similar to
ChatGPT
on the web. You can ask it a question or give it a task to have it automatically
reply to your emails.
The following arguments can be used (arguments prefixed by an * are required):
*ai_model: str: The AI model to be used, e.g. "openai", "gemini", "copilot", etc. Currently supporting: "openai"
*message: str: The message you want to send to the AI model, e.g. "What is the weather today?"
model: str: AI model specfic. The model of the AI model to be used. E.g. "gpt-3.5-turbo" when using the "openai" AI model. Default depends on AI model:
max_tokens: int = 256 The token limit for a conversation. Both prompt and response tokens will count towards this limit.
temperature: float = 1 This value determines the creativity of the AI model. Can be anything from 0-2.
top_p: float = 1 Similar to temperature. Determines the selection of tokens before selecting one. The higher the value the more less likely tokens get added to the selection. Can be anything from 0-2. At 1, only the top 50% of tokens will be used when selecting a token at 0 all tokens will be taken into consideration
frequency_penalty: float = 0 Penalizes more frequent token reducing the chance of it reappearing. Negative values encourage it to reuse tokens. Can be anything from -2 to 2.
presence_penalty: float = 0 Exact same as frequency_penalty except its scope is reduced to the immediate context. The immediate context can be seen as one or more paragrahps about a singular subject. Can be anything from -2 to 2.
keep_history: bool = False A flag to keep the chat history of previous messages. When settings this to True, your previous prompt and the response by the AI will be saved for the next message. This feature will keep the previous message, so if you want to send two messages and refer to your first message from the second message, you need to set this flag to True in the second message. Leaving this on for the third message aswell will keep both the first and second message.
NOTE: This works by incorporating the previous messages into the prompt, this will charge you again for both the prompt and response. So leaving this on, could quickly drain all your tokens.
response_format: dict = None Can be used to make the response compile to JSON. Set this to { "type": "json_object" } to make the response compile to JSON or None if it shouldn't necessarily.
Generate a response to a question using OpenAI
Generate Response openai What is the wheather today?
Declare a rule in the first message and refer to it in the second message
Generate Response openai If I say water you say fire
Generate Response openai Water keep_history=True
Generate the meaning of life in a json format using the gpt-3.5-turbo from OpenAI in the default format with a token limit at 1024, temperature at 2, top p at .5 and frequency- and presence penalty at 0 without using the previous messages in the response.
Generate Response openai What is the meaning of life? In json. gpt-3.5-turbo 1024 2 .5 0 0 False {"type": "json_object"}
The Assistant
is a module that allows talking to AI and adding files to the conversation.
It functions similar to the Chatbot module, but with some changes.
With the Assistant
module AI Assistants can be created, these will exists for aslong as they
are not deleted, meaning that they are still available several weeks later or indefinitely.
In the mean time new AI Assistants can be created and talked to.
Files can be uploaded to the AI for inspection or to add knowledge. Similarly files can also be send along side a message to the AI Assistant. The difference being that files send alongsides message only remain aslong as the thread (conversation). When a new thread is created, the AI Assistant wont remember previous message send to it, including files. It will only remember files uploaded to the AI assistant itself.
The Assistant
can also be given instructions and parameters to influence its behaviour. These
can be given at creation or later be changed.
The Assistant
has 9 different keywords that can be used to interact with the AI assistant.
The way the Assistant
module works is that there can be multiple AI assistants. But there can
only be 1 active assistant. All keywords where it isn't explicitely mentioned which assistant
will be affected (all keywords that don't require an Id as argument), will be performed on the
active assistant.
This keyword creates a new assistant and sets it as the active assistant.
Returns the Id of the newly created assistant.
The following arguments can be used (arguments prefixed by an * are required):
Create a new assistant Test Assistant:
Set AI Model openai
Set Name Test Assistant
Create Assistant
Create a new assistant with all changing all default arguments:
Set AI Model openai
Set Name Full Featured Assistant
Set Instructions This assistant is capable of handling various technical queries.
Set Model gpt-3.5-turbo
Set Temperature 1.5
Set Top P 0.8
Set Response Format { "type": "json_object" }
Create Assistant
This keyword updates parameters of the active assistant.
This keyword takes the same arguments as the Create Assistant keyword
Returns a success message explaining which parameters have been updated.
The following arguments can be used (arguments prefixed by an * are required):
Update the active assistant's name:
Set AI Model openai
Set Name Mark
Update Assistant
Update the all the parameters of the active assistant:
Set AI Model openai
Set Name Helpy
Set Instructions You write documentation for code.
Set Model gpt-3.5-turbo
Set Temperature 1.8
Set Top P 0.6
Set Response Format { "type": "json_object" }
Update Assistant
Sends a prompt to the active assistant and returns its response
By supplying file_paths as an argument in the method call, files can be send with it as well. Make sure to unset file_paths to not send it with each prompt.
The following arguments can be used (arguments prefixed by an * are required):
Send a prompt to ask for the weather:
Set AI Model openai
Set Message What is the weather today?
Send Message
Send a prompt to ask for improvements for code:
Set AI Model openai
Set Message How can I improve my code?
Send Message file_paths=["src/main.py", "src/resources"]
Deletes the active assistant
After deleting the active assistant, there will be no active assistant. Either create a new assistant or set a new assistant as active.
The following arguments can be used (arguments prefixed by an * are required):
Delete the active assistant:
Set AI Model openai
Delete Assistant
Deletes the assistant with the specified Id
If that assistant is also the active assistant, there will be no active assistant. Either create a new assistant or set a new assistant as active.
The following arguments can be used (arguments prefixed by an * are required):
Delete an assistant by Id:
Set AI Model openai
Set Id asst_0Ta3aCdE675foHxkLTnujjgl
Delete Assistant By Id
Attaches files to the active assistant
These files can be used by the assistant in any thread as opposed to sending files with a prompt.
The following arguments can be used (arguments prefixed by an * are required):
Attach the main.py file and all files in the src/resources directory:
Set AI Model openai
Set File Paths ["src/main.py", "src/resources"]
Attach Files
Returns the Id of the active assistant
The following arguments can be used (arguments prefixed by an * are required):
Get the Id of the active assistant using setters:
Set AI Model openai
Get Active Assistant Id
Create a new thread
Creating a new thread effectively restarts the conversation.
The following arguments can be used (arguments prefixed by an * are required):
Create a new thread using setters:
Set AI Model openai
Create New Thread
Sets the assistant with the specified Id as active
This will also create a new thread
The following arguments can be used (arguments prefixed by an * are required):
Set a specific assistant as the active assistant and start a new thread using setters:
Set AI Model openai
Set Id asst_0Ta3aCdE675foHxkLTnujjgl
Set Active Assistant
Each module in the RobotFramework-AI library can support multiple different AI models. Each AI model needs an API key for the generation of test data. This key gets read directly from your environment variables. Each AI model has their own API key. To define a key, create a new variable with the name of the AI model capitalized followed by "_KEY". Then set this variable to your key.
Example API keys OPENAI_KEY=278bxw4m89monwxmu89wm98ufx8hwxfhqwifmxou09qwxp09jmx GEMINI_KEY=cavhjbcZCJKnvmzxcnzkcjkczckzcskjnjn7h38nwd923hdnind
Instead of providing all arguments through this keyword, it is also possible to set each argument beforehand. This way, when making repeated calls, arguments do not have to be supplied each time. After setting these arguments they will remain untill set again. When arguments are set and the keyword also has arguments supplied, then the supplied arguments will take priority.
NOTE: Setting arguments will impact other modules aswell. This means that when setting the temperature to 2, that both the RealTestDataGenerator and the Chatbot will use this temperature from then on. This is only the case when both modules share arguments, the arguments that are shared are as followed:
ai_model, model, max_tokens, temperature, top_p,
frequency_penalty, presence_penalty, response_format
Each argument has its own setter, the name of the keyword is 'Set' plus the name of the argument e.g. Set AI Model for AI Model. In the case of kwargs, use the setter to set individual kwargs, set to None to unset it. The setter takes 2 arguments, the name of the kwarg to set and its value. To set a kwarg use:
Set Kwarg country Czechia
NOTE: file_paths can not be set using setters. Allowing file_paths to be set could cause users to accidentally add the same files multiple times to the same assistant and will also cause users to send those with every prompt. This would make the library slower but more importantly lose the user a lot of money.
Generate 3 addresses from anywhere using OpenAI:
Set AI Model openai
Set Type address
Generate Test Data
Generate 10 addresses from Finland using the gpt-3.5-turbo from OpenAI in the default format with a token limit at 1024, temperature at 1, top p at .5 and frequency- and presence penalty at 0
Set AI Model openai
Set Type address
Set Model gpt-3.5-turbo
Set Amount 10
Set Format None
Set Max Tokens 1024
Set Temperature 1
Set Top P .5
Set Frequency Penalty 0
Set Presence Penalty 0
Set Kwarg country finland
Generate Test Data
The RobotFramework-AI library includes configurable logging capabilities to assist with debugging and monitoring. This logging setup ensures that log messages are handled appropriately, including support for Unicode characters.
To enable logging, use the Setup Logging keyword provided by the RobotFramework-AI library. This keyword allows you to configure console and file logging, and to enable or disable logging as needed.
The Setup Logging keyword takes the following arguments:
To log to both the console and a file:
Setup Logging
To log for tests without console logging:
Setup Logging True True False