| palm.txt.optimize.code {PaLMr} | R Documentation |
Optimize code based on a query using the Google PaLM 2 text model.
Description
This function sends a query with a code snippet to the Google PaLM 2 text model and generates an optimized version of the code. You can specify the programming language and the aspect you want to optimize (e.g., "runtime" or "memory"). The optimized code is provided along with the original code for comparison.
Usage
palm.txt.optimize.code(
model.parameter,
prompt,
goal,
language = "R",
temperature = 0.7,
maxOutputTokens = 1024,
topP = 0.95,
topK = 40,
htUnspecified = "meda",
htDerogatory = "meda",
htToxicity = "meda",
htViolence = "meda",
htSexual = "meda",
htMedical = "meda",
htDangerous = "meda"
)
Arguments
model.parameter |
A character vector containing the API key, model version, and proxy status. Model version and type
are specified by Google. See function |
prompt |
A character string representing the code snippet for explanation. The length of the code snippet should be between 1 and 8196 characters, inclusive. |
goal |
A character string specifying the aspect you want to optimize. |
language |
A character string specifying the programming language used in the code (default: "R"). |
temperature |
A numeric value (default: 0.7). Controls the randomness of the generated optimization. A higher value (e.g., 0.9) results in more creative optimizations, while a lower value (e.g., 0.3) produces more straightforward optimizations. |
maxOutputTokens |
An integer value between 1 and 1024, inclusive (default: 1024). Specifies the maximum number of tokens to include in the generated optimization. |
topP |
A numeric value (default: 0.95). Defines the maximum cumulative probability of tokens considered when sampling. It controls the diversity of the optimization generated. |
topK |
An integer value (default: 40). Sets the maximum number of tokens to consider when sampling. |
htUnspecified |
Safety setting threshold for unspecified harm. The default threshold is "meda". Valid options are as follows.
|
htDerogatory |
Safety setting threshold for derogatory harm. The default threshold is "meda". Valid options are as follows.
|
htToxicity |
Safety setting threshold for toxicity harm. The default threshold is "meda". Valid options are as follows.
|
htViolence |
Safety setting threshold for violence harm. The default threshold is "meda". Valid options are as follows.
|
htSexual |
Safety setting threshold for sexual harm. The default threshold is "meda". Valid options are as follows.
|
htMedical |
Safety setting threshold for medical harm. The default threshold is "meda". Valid options are as follows.
|
htDangerous |
Safety setting threshold for dangerous harm. The default threshold is "meda". Valid options are as follows.
|
Details
This function interacts with the Google PaLM model by sending a code query for code optimization. It allows you to customize the generated code optimizations by specifying the programming language, optimization aspect, and additional parameters like temperature, token limits, and safety settings.
If the function is successful, it returns an optimized version of the provided code as a character string. If an error occurs during the API request, it will stop execution and provide an error message.
The 'model.parameter' argument should be a character vector with the API key, model version, and model type provided by Google. You can obtain this information by following the instructions provided by Google for using the PaLM API.
The safety settings control the content's safety level based on different harm categories. Harm thresholds are specified as per Google's guidelines and can be customized to control the content generated.
Value
A character string containing the optimized version of the provided code snippet based on the query and parameters.
See Also
Safety Setting - Google AI for Developers
HarmCategory - Google AI for Developers
Examples
## Not run:
# Connect to the model, replace API_KEY with your api key
palm.model = palm.connect("v1beta2",
"API_KEY",
FALSE)
prompt = "foo <- function(n) {
if (n <= 0) {
return(0)
} else if (n == 1) {
return(1)
} else {
return(foo(n - 1) + foo(n - 2))
}
}"
code.optimization = palm.txt.optimize.code(palm.model,
"Improve the runtime.",
prompt)
cat(code.optimization)
## End(Not run)