chat.edit {GenAI}

Chat Edit with New Text as the Input

Description

This function establishes a connection to a generative AI model through a generative AI object. It generates a chat response based on the new prompt and stores it in the chat history along with the generative AI object.

Usage

chat.edit(
  genai.object,
  prompt,
  message.to.edit,
  verbose = FALSE,
  config = list()
)

Arguments

genai.object

A generative AI object containing necessary and correct information.

prompt

A character string representing the query for chat generation.

message.to.edit

An integer representing the index of the message to be edited.

verbose

Optional. Default to FALSE. A boolean value determining whether or not to print out the details of the chat request.

config

Optional. Default to list(). A list of configuration parameters for chat generation.

Details

Providing accurate and valid information for each argument is crucial for successful chat generation by the generative AI model. If any parameter is incorrect, the function responds with an error message based on the API feedback. To view all supported generative AI models, use the function available.models.

In addition, this function modifies the chat history along with the generative AI object directly, meaning the chat history is mutable. You can print out the chat history using the function chat.history.print or simply use verbose = TRUE in this function. To reset the chat history along with the chat history along with the generative AI object, use the function chat.history.reset.

For Google Generative AI models, available configurations are as follows. For more detail, please refer to https://ai.google.dev/api/rest/v1/HarmCategory, https://ai.google.dev/api/rest/v1/SafetySetting, and https://ai.google.dev/api/rest/v1/GenerationConfig.

• harm.category.dangerous.content

  Optional. An integer, from 1 to 5 inclusive, representing the threshold for dangerous content, with a higher value representing a lower probability of being blocked.

• harm.category.harassment

  Optional. An integer, from 1 to 5 inclusive, representing the threshold for harasment content, with a higher value representing a lower probability of being blocked.

• harm.category.hate.speech

  Optional. An integer, from 1 to 5 inclusive, representing the threshold for hate speech and content, with a higher value representing a lower probability of being blocked.

• harm.category.sexually.explicit

  Optional. An integer, from 1 to 5 inclusive, representing the threshold for sexually explicit content, with a higher value representing a lower probability of being blocked.

• stop.sequences

  Optional. A list of character sequences (up to 5) that will stop output generation. If specified, the API will stop at the first appearance of a stop sequence. The stop sequence will not be included as part of the response.

• max.output.tokens

  Optional. An integer, value varies by model, representing maximum number of tokens to include in a candidate.

• temperature

  Optional. A number, from 0.0 to 1.0 inclusive, controlling the randomness of the output.

• top.p

  Optional. A number, value varies by model, representing maximum cumulative probability of tokens to consider when sampling.

• top.k

  Optional. A number, value varies by model, representing maximum number of tokens to consider when sampling.

For Moonshot AI models, available configurations are as follows. For more detail, please refer to https://platform.moonshot.cn/api.html#chat-completion.

• max.tokens

  Optional. An integer. The maximum number of tokens that will be generated when the chat completes. If the chat is not finished by the maximum number of tokens generated, the finish reason will be "length", otherwise it will be "stop".

• temperature

  Optional. A number. What sampling temperature to use, between 0 and 1. Higher values (e.g. 0.7) will make the output more random, while lower values (e.g. 0.2) will make it more focused and deterministic.

• top.p

  Optional. A number. Another sampling temperature.

For OpenAI models, available configurations are as follows. For more detail, please refer to https://platform.openai.com/docs/api-reference/chat/create.

• frequency.penalty

  Optional. A number from -2.0 to 2.0 inclusive. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.

• logit.bias

  Optional. A map. Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100. Mathematically, the bias is added to the logits generated by the model prior to sampling. The exact effect will vary per model, but values between -1 and 1 should decrease or increase likelihood of selection; values like -100 or 100 should result in a ban or exclusive selection of the relevant token.

• logprobs

  Optional. A boolean value. Whether to return log probabilities of the output tokens or not. If true, returns the log probabilities of each output token returned in the content of message

• top.logprobs

  Optional. An integer between 0 and 5 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to TRUE if this parameter is used.

• max.tokens

  Optional. An integer. The maximum number of tokens that can be generated in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.

• presence.penalty

  Optional. A Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.

• response.format

  Optional. An object specifying the format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106.

• seed

  Optional. An integer. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result.

• stop

  Optional. A character string or list contains up to 4 sequences where the API will stop generating further tokens.

• temperature

  Optional. A number. What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.

• top.p

  Optional. A number. An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top.p probability mass. So 0.1 means only the tokens comprising the top 10

• tools

  Optional. A list of tools the model may call. Currently, only functions are supported as a tool. Use this to provide a list of functions the model may generate JSON inputs for.

• tool.choice

  Optional. A character string or object. Controls which (if any) function is called by the model. none means the model will not call a function and instead generates a message. auto means the model can pick between generating a message or calling a function.

• user

  Optional. A character string. A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse.

Value

If successful, the most recent chat response will be returned. If the API response indicates an error, the function halts execution and provides an error message.

See Also

GenAI - R Package "GenAI" Documentation

Live Demo in Colab

Examples

## Not run: 
# Assuming there is a GenAI object named 'genai.model' supporting this
# function, please refer to the "Live Demo in Colab" above for real
# examples. The following examples are just some basic guidelines.

# Method 1 (recommended): use the pipe operator "%>%"
genai.model %>%
  chat.edit(prompt = "What is XGBoost?",
            message.to.edit = 5,
            verbose = TRUE,
            config = parameters) %>%
  cat()

# Method 2: use the reference operator "$"
cat(genai.model$chat.edit(prompt = "What is CatBoost?",
                          message.to.edit = 3))

# Method 3: use the function chat.edit() directly
cat(chat.edit(genai.object = genai.model,
              prompt = "What is LightGBM?",
              message.to.edit = 1))

## End(Not run)