RPA.OpenAI
Keyword for authorize to Azure OpenAI.
Arguments
| Argument | Type | Default value | Description |
|---|---|---|---|
| api_key | str | null | Your Azure OpenAI API key |
| api_base | str | null | Your Endpoint URL. Example: https://docs-test-001.openai.azure.com/ |
| api_type | str, None | azure | "azure" |
| api_version | str, None | 2023-05-15 | "2023-05-15" |
| param api_key: | Your Azure OpenAI API key |
|---|---|
| param api_base: | Your Endpoint URL. Example: https://docs-test-001.openai.azure.com/ |
| param api_type: | "azure" |
| param api_version: | |
| "2023-05-15" | |
Robot Framework example:
${secrets} Get Secret secret_name=AzureOpenAI
Authorize To Azure Openai
... api_key=${secrets}[api_key]
... api_base=${secrets}[api_base]
... api_type=azure
... api_version=2023-05-15
Python example:
secrets = Vault().get_secret("AzureOpenAI")
baselib = OpenAI()
baselib.authorize_to_azure_openai(
secrets["api_key"],
secrets["api_base"],
"azure",
"2023-05-15"
)
Keyword for authorize to OpenAI with your API key obtained from your account.
Arguments
| Argument | Type | Default value | Description |
|---|---|---|---|
| api_key | str | null | Your OpenAI API key |
| param api_key: | Your OpenAI API key |
|---|
Robot Framework example:
${secrets} Get Secret secret_name=OpenAI
Authorize To OpenAI api_key=${secrets}[key]
Python example:
secrets = Vault().get_secret("OpenAI")
baselib = OpenAI()
baselib.authorize_to_openai(secrets["key"])
Keyword for creating ChatGPT text completions using OpenAI or Azure OpenAI. Keyword returns the response as a string and the message history as a list.
Arguments
| Argument | Type | Default value | Description |
|---|---|---|---|
| user_content | str, None | None | Text submitted to ChatGPT to generate completions. |
| conversation | List, None | None | List containing the conversation to be continued. Leave empty for a new conversation. |
| model | str, None | gpt-3.5-turbo | For OpenAI the ID of the model to use, e.g. gpt-4 or gpt-3.5-turbo. For Azure OpenAI the Deployment name, e.g. myGPT4deployment. |
| system_content | str, None | None | The system message helps set the behavior of the assistant. |
| temperature | int, None | 1 | What sampling temperature to use between 0 to 2. Higher values means the model will take more risks. |
| top_probability | int, None | 1 | An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. |
| frequency_penalty | int, None | 0 | Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far. |
| presence_penalty | int, None | 0 | Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far. |
Note. When using Azure OpenAI you must provide the deployment_name as the model parameter instead of the model ID used with OpenAI.
| param user_content: | |
|---|---|
| Text submitted to ChatGPT to generate completions. | |
| param conversation: | |
| List containing the conversation to be continued. Leave empty for a new conversation. | |
| param model: | For OpenAI the ID of the model to use, e.g. gpt-4 or gpt-3.5-turbo. For Azure OpenAI the Deployment name, e.g. myGPT4deployment. |
| param system_content: | |
| The system message helps set the behavior of the assistant. | |
| param temperature: | |
| What sampling temperature to use between 0 to 2. Higher values means the model will take more risks. | |
| param top_probability: | |
| An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. | |
| param frequency_penalty: | |
| Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far. | |
| param presence_penalty: | |
| Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far. | |
Robot Framework example:
# Get response without conversation history.
${response} @{chatgpt_conversation}= Chat Completion Create
... user_content=What is the biggest mammal?
Log ${response}
# Continue the conversation by using the "conversation" argument.
${response} @{chatgpt_conversation}= Chat Completion Create
... conversation=${chatgpt_conversation}
... user_content=How old can it live?
Log ${response}
Keyword for creating text completions in OpenAI and Azure OpenAI. Keyword returns a text string.
Arguments
| Argument | Type | Default value | Description |
|---|---|---|---|
| prompt | str | null | Text submitted to OpenAI for creating natural language. |
| model | str, None | text-davinci-003 | For OpenAI the ID of the model to use, e.g. text-davinci-003. For Azure OpenAI the Deployment name, e.g. myDavinci3deployment. |
| temperature | int, None | 0.7 | What sampling temperature to use. Higher values means the model will take more risks.. |
| max_tokens | int, None | 256 | The maximum number of tokens to generate in the completion.. |
| top_probability | int, None | 1 | Controls diversity via nucleus sampling. 0.5 means half of all likelihood-weighted options are considered. |
| frequency_penalty | int, None | 0 | Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far. |
| presence_penalty | int, None | 0 | Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far. |
| result_format | str, None | string | Result format (string / json). Return just a string or the default JSON response. |
Note. When using Azure OpenAI you must provide the deployment_name as the model parameter instead of the model ID used with OpenAI.
| param prompt: | Text submitted to OpenAI for creating natural language. |
|---|---|
| param model: | For OpenAI the ID of the model to use, e.g. text-davinci-003. For Azure OpenAI the Deployment name, e.g. myDavinci3deployment. |
| param temperature: | |
| What sampling temperature to use. Higher values means the model will take more risks.. | |
| param max_tokens: | |
| The maximum number of tokens to generate in the completion.. | |
| param top_probability: | |
| Controls diversity via nucleus sampling. 0.5 means half of all likelihood-weighted options are considered. | |
| param frequency_penalty: | |
| Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far. | |
| param presence_penalty: | |
| Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far. | |
| param result_format: | |
| Result format (string / json). Return just a string or the default JSON response. | |
Robot Framework example:
${response} Completion Create
... Write a tagline for an icecream shop.
... temperature=0.6
Log ${response}
Python example:
result = baselib.completion_create(
'Create a tagline for icecream shop',
temperature=0.6,
)
print(result)
Keyword for creating one or more images using OpenAI. Keyword returns a list of urls for the images created.
Arguments
| Argument | Type | Default value | Description |
|---|---|---|---|
| prompt | str | null | A text description of the desired image(s). The maximum length is 1000 characters. |
| size | str, None | 512x512 | Size of the files to be created. 256x256, 512x512, 1024x1024 |
| num_images | int, None | 1 | The number of images to generate. Must be between 1 and 10. |
| result_format | str, None | list | Result format (list / json). |
Note. Keyword not supported in the Azure OpenAI service.
| param prompt: | A text description of the desired image(s). The maximum length is 1000 characters. |
|---|---|
| param size: | Size of the files to be created. 256x256, 512x512, 1024x1024 |
| param num_images: | |
| The number of images to generate. Must be between 1 and 10. | |
| param result_format: | |
| Result format (list / json). | |
Robot Framework example:
${images} Image Create
... Cartoon style picture of a cute monkey skateboarding.
... size=256x256
... num_images=2
FOR ${url} IN @{images}
Log ${url}
END
Python example:
images = baselib.image_create(
'Cartoon style picture of a cute monkey skateboarding',
size='256x256',
num_images=2,
)
for url in images:
print(url)
Keyword for creating one or more variations of a image. Keyword returns a list of urls for the images created. Source file must be a valid PNG file, less than 4MB, and square.
Arguments
| Argument | Type | Default value | Description |
|---|---|---|---|
| src_image | str | null | The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and square. |
| size | str, None | 512x512 | The size of the generated images. Must be one of 256x256, 512x512, or 1024x1024. |
| num_images | int, None | 1 | The number of images to generate. Must be between 1 and 10 |
| result_format | str, None | list | Result format (list / json). |
Note. Keyword not supported in the Azure OpenAI service.
| param src_image: | |
|---|---|
| The image to use as the basis for the variation(s). Must be a valid PNG file, less than 4MB, and square. | |
| param size: | The size of the generated images. Must be one of 256x256, 512x512, or 1024x1024. |
| param num_images: | |
| The number of images to generate. Must be between 1 and 10 | |
| param result_format: | |
| Result format (list / json). | |
Robot Framework example:
${variations} Image Create Variation
... source_image.png
... size=256x256
... num_images=2
FOR ${url} IN @{variations}
Log ${url}
END
Python example:
variations = baselib.image_create_variation(
'source_image.png',
size='256x256',
num_images=2,
)
for url in variations:
print(url)