@Generated(value="OracleSDKGenerator", comments="API Version: 20231130") public final class CohereChatRequest extends BaseChatRequest
Details for the chat request for Cohere models.
Note: Objects should always be created or deserialized using the CohereChatRequest.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 CohereChatRequest.Builder
, which maintain a
set of all explicitly set fields called CohereChatRequest.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 |
CohereChatRequest.Builder |
BaseChatRequest.ApiFormat
EXPLICITLY_SET_FILTER_NAME, EXPLICITLY_SET_PROPERTY_NAME
Constructor and Description |
---|
CohereChatRequest(String message,
List<CohereMessage> chatHistory,
List<Object> documents,
Boolean isSearchQueriesOnly,
String preambleOverride,
Boolean isStream,
Integer maxTokens,
Double temperature,
Integer topK,
Double topP,
Double frequencyPenalty,
Double presencePenalty)
Deprecated.
|
Modifier and Type | Method and Description |
---|---|
static CohereChatRequest.Builder |
builder()
Create a new builder.
|
boolean |
equals(Object o) |
List<CohereMessage> |
getChatHistory()
A list of previous messages between the user and the model, meant to give the model
conversational context for responding to the user’s message.
|
List<Object> |
getDocuments()
list of relevant documents that the model can cite to generate a more accurate reply.
|
Double |
getFrequencyPenalty()
To reduce repetitiveness of generated tokens, this number penalizes new tokens based on their
frequency in the generated text so far.
|
Boolean |
getIsSearchQueriesOnly()
When true, the response will only contain a list of generated search queries, but no search
will take place, and no reply from the model to the user’s message will be generated.
|
Boolean |
getIsStream()
Whether to stream back partial progress.
|
Integer |
getMaxTokens()
The maximum number of tokens to predict for each response.
|
String |
getMessage()
Text input for the model to respond to.
|
String |
getPreambleOverride()
When specified, the default Cohere preamble will be replaced with the provided one.
|
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.
|
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() |
CohereChatRequest.Builder |
toBuilder() |
String |
toString() |
String |
toString(boolean includeByteArrayContents)
Return a string representation of the object.
|
markPropertyAsExplicitlySet, wasPropertyExplicitlySet
@Deprecated public CohereChatRequest(String message, List<CohereMessage> chatHistory, List<Object> documents, Boolean isSearchQueriesOnly, String preambleOverride, Boolean isStream, Integer maxTokens, Double temperature, Integer topK, Double topP, Double frequencyPenalty, Double presencePenalty)
public static CohereChatRequest.Builder builder()
Create a new builder.
public CohereChatRequest.Builder toBuilder()
public String getMessage()
Text input for the model to respond to.
public List<CohereMessage> getChatHistory()
A list of previous messages between the user and the model, meant to give the model conversational context for responding to the user’s message.
public List<Object> getDocuments()
list of relevant documents that the model can cite to generate a more accurate reply. Some suggested keys are “text”, “author”, and “date”. For better generation quality, it is recommended to keep the total word count of the strings in the dictionary to under 300 words.
public Boolean getIsSearchQueriesOnly()
When true, the response will only contain a list of generated search queries, but no search will take place, and no reply from the model to the user’s message will be generated.
public String getPreambleOverride()
When specified, the default Cohere preamble will be replaced with the provided one. Preambles are a part of the prompt used to adjust the model’s overall behavior and conversation style. Default preambles vary for different models.
public Boolean getIsStream()
Whether to stream back partial progress. If set, tokens are sent as data-only server-sent events as they become available.
public Integer getMaxTokens()
The maximum number of tokens to predict for each response. Includes input plus output tokens.
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 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 0 which disables this method and considers all tokens. To set a number for the likely tokens, choose an integer between 1 and 500.
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 1.0 to consider all tokens and set to 0 to disable. If both k and p are enabled, p acts after k.
public Double getFrequencyPenalty()
To reduce repetitiveness of generated tokens, this number penalizes new tokens based on their frequency in the generated text so far. Greater numbers encourage the model to use new tokens, while lower numbers encourage the model to repeat the 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. Greater numbers encourage the model to use new tokens, while lower numbers encourage the model to repeat the 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 String toString()
toString
in class BaseChatRequest
public String toString(boolean includeByteArrayContents)
Return a string representation of the object.
toString
in class BaseChatRequest
includeByteArrayContents
- true to include the full contents of byte arrayspublic boolean equals(Object o)
equals
in class BaseChatRequest
public int hashCode()
hashCode
in class BaseChatRequest
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