@Generated(value="OracleSDKGenerator",
comments="API Version: 20231130")
public final class GenericChatRequest
extends BaseChatRequest
Details for the chat request.
Note: Objects should always be created or deserialized using the GenericChatRequest.Builder. This model
distinguishes fields that are null because they are unset from fields that are explicitly
set to null. This is done in the setter methods of the GenericChatRequest.Builder, which maintain a
set of all explicitly set fields called GenericChatRequest.Builder.__explicitlySet__. The hashCode() and equals(Object) methods are implemented to take the explicitly set
fields into account. The constructor, on the other hand, does not take the explicitly set fields
into account (since the constructor cannot distinguish explicit null from unset null).
| Modifier and Type | Class and Description |
|---|---|
static class |
GenericChatRequest.Builder |
BaseChatRequest.ApiFormatEXPLICITLY_SET_FILTER_NAME, EXPLICITLY_SET_PROPERTY_NAME| Constructor and Description |
|---|
GenericChatRequest(List<Message> messages,
Boolean isStream,
Integer numGenerations,
Boolean isEcho,
Integer topK,
Double topP,
Double temperature,
Double frequencyPenalty,
Double presencePenalty,
List<String> stop,
Integer logProbs,
Integer maxTokens,
Object logitBias)
Deprecated.
|
| Modifier and Type | Method and Description |
|---|---|
static GenericChatRequest.Builder |
builder()
Create a new builder.
|
boolean |
equals(Object o) |
Double |
getFrequencyPenalty()
To reduce repetitiveness of generated tokens, this number penalizes new tokens based on their
frequency in the generated text so far.
|
Boolean |
getIsEcho()
Whether to include the user prompt in the response.
|
Boolean |
getIsStream()
Whether to stream back partial progress.
|
Object |
getLogitBias()
Modifies the likelihood of specified tokens that appear in the completion.
|
Integer |
getLogProbs()
Includes the logarithmic probabilities for the most likely output tokens and the chosen
tokens.
|
Integer |
getMaxTokens()
The maximum number of tokens that can be generated per output sequence.
|
List<Message> |
getMessages()
The series of messages in a chat request.
|
Integer |
getNumGenerations()
The number of of generated texts that will be returned.
|
Double |
getPresencePenalty()
To reduce repetitiveness of generated tokens, this number penalizes new tokens based on
whether they’ve appeared in the generated text so far.
|
List<String> |
getStop()
List of strings that stop the generation if they are generated for the response text.
|
Double |
getTemperature()
A number that sets the randomness of the generated output.
|
Integer |
getTopK()
An integer that sets up the model to use only the top k most likely tokens in the generated
output.
|
Double |
getTopP()
If set to a probability 0.0 < p < 1.0, it ensures that only the most likely tokens, with
total probability mass of p, are considered for generation at each step.
|
int |
hashCode() |
GenericChatRequest.Builder |
toBuilder() |
String |
toString() |
String |
toString(boolean includeByteArrayContents)
Return a string representation of the object.
|
markPropertyAsExplicitlySet, wasPropertyExplicitlySet@Deprecated public GenericChatRequest(List<Message> messages, Boolean isStream, Integer numGenerations, Boolean isEcho, Integer topK, Double topP, Double temperature, Double frequencyPenalty, Double presencePenalty, List<String> stop, Integer logProbs, Integer maxTokens, Object logitBias)
public static GenericChatRequest.Builder builder()
Create a new builder.
public GenericChatRequest.Builder toBuilder()
public List<Message> getMessages()
The series of messages in a chat request. Includes the previous messages in a conversation.
Each message includes a role (USER or the CHATBOT) and content.
public Boolean getIsStream()
Whether to stream back partial progress. If set to true, as tokens become available, they are sent as data-only server-sent events.
public Integer getNumGenerations()
The number of of generated texts that will be returned.
public Boolean getIsEcho()
Whether to include the user prompt in the response. Applies only to non-stream results.
public Integer getTopK()
An integer that sets up the model to use only the top k most likely tokens in the generated output. A higher k introduces more randomness into the output making the output text sound more natural. Default value is -1 which means to consider all tokens. Setting to 0 disables this method and considers all tokens.
If also using top p, then the model considers only the top tokens whose probabilities add up to p percent and ignores the rest of the k tokens. For example, if k is 20, but the probabilities of the top 10 add up to .75, then only the top 10 tokens are chosen.
public Double getTopP()
If set to a probability 0.0 < p < 1.0, it ensures that only the most likely tokens, with total probability mass of p, are considered for generation at each step.
To eliminate tokens with low likelihood, assign p a minimum percentage for the next token's likelihood. For example, when p is set to 0.75, the model eliminates the bottom 25 percent for the next token. Set to 1 to consider all tokens and set to 0 to disable. If both k and p are enabled, p acts after k.
public Double getTemperature()
A number that sets the randomness of the generated output. A lower temperature means a less random generations.
Use lower numbers for tasks with a correct answer such as question answering or summarizing. High temperatures can generate hallucinations or factually incorrect information. Start with temperatures lower than 1.0 and increase the temperature for more creative outputs, as you regenerate the prompts to refine the outputs.
public Double getFrequencyPenalty()
To reduce repetitiveness of generated tokens, this number penalizes new tokens based on their frequency in the generated text so far. Values > 0 encourage the model to use new tokens and values < 0 encourage the model to repeat tokens. Set to 0 to disable.
public Double getPresencePenalty()
To reduce repetitiveness of generated tokens, this number penalizes new tokens based on whether they’ve appeared in the generated text so far. Values > 0 encourage the model to use new tokens and values < 0 encourage the model to repeat tokens.
Similar to frequency penalty, a penalty is applied to previously present tokens, except that this penalty is applied equally to all tokens that have already appeared, regardless of how many times they've appeared. Set to 0 to disable.
public List<String> getStop()
List of strings that stop the generation if they are generated for the response text. The returned output will not contain the stop strings.
public Integer getLogProbs()
Includes the logarithmic probabilities for the most likely output tokens and the chosen tokens.
For example, if the log probability is 5, the API returns a list of the 5 most likely tokens. The API returns the log probability of the sampled token, so there might be up to logprobs+1 elements in the response.
public Integer getMaxTokens()
The maximum number of tokens that can be generated per output sequence. The token count of
your prompt plus maxTokens must not exceed the model’s context length. Not setting a
value for maxTokens results in the possible use of model’s full context length.
public Object getLogitBias()
Modifies the likelihood of specified tokens that appear in the completion.
Example: '{"6395": 2, "8134": 1, "21943": 0.5, "5923": -100}'
public String toString()
toString in class BaseChatRequestpublic String toString(boolean includeByteArrayContents)
Return a string representation of the object.
toString in class BaseChatRequestincludeByteArrayContents - true to include the full contents of byte arrayspublic boolean equals(Object o)
equals in class BaseChatRequestpublic int hashCode()
hashCode in class BaseChatRequestCopyright © 2016–2024. All rights reserved.