chat-cohere-chat-request-v2

Description

Creates a response for the given conversation.

Usage

oci generative-ai-inference chat-result chat-cohere-chat-request-v2 [OPTIONS]

Required Parameters

--chat-request-messages [complex type]

A list of chat messages in chronological order, representing a conversation between the user and the model. This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

--compartment-id, -c [text]

The OCID of compartment in which to call the Generative AI service to chat.

--serving-mode [complex type]

This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

Optional Parameters

--chat-request-citation-options [complex type]

This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

--chat-request-documents [complex type]

A list of relevant documents that the model can refer to for generating grounded responses to the user’s requests. Some example keys that you can add to the dictionary are “text”, “author”, and “date”. Keep the total word count of the strings in the dictionary to 300 words or less. This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

--chat-request-frequency-penalty [text]

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.

--chat-request-is-log-probs-enabled [boolean]

The log probabilities of the generated tokens will be included in the response.

--chat-request-is-raw-prompting [boolean]

When enabled, the user’s message will be sent to the model without any preprocessing.

--chat-request-is-search-queries-only [boolean]

When set to true, the response contains only a list of generated search queries without the search results and the model will not respond to the user’s message.

--chat-request-is-stream [boolean]

Whether to stream the partial progress of the model’s response. When set to true, as tokens become available, they are sent as data-only server-sent events.

--chat-request-is-strict-tools-enabled [boolean]

When set to true, tool calls in the Assistant message will be forced to follow the tool definition strictly. Note:The first few requests with a new set of tools will take longer to process.

--chat-request-max-tokens [integer]

The maximum number of output tokens that the model will generate for the response. The token count of your prompt plus maxTokens must not exceed the model’s context length. For on-demand inferencing, the response length is capped at 4,000 tokens for each run.

--chat-request-presence-penalty [text]

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.

--chat-request-priority [integer]

The priority of the request (lower means earlier handling; default 0 highest priority). Higher priority requests are handled first, and dropped last when the system is under load.

--chat-request-response-format [complex type]

This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

--chat-request-safety-mode [text]

Safety mode: Adds a safety instruction for the model to use when generating responses. Contextual: (Default) Puts fewer constraints on the output. It maintains core protections by aiming to reject harmful or illegal suggestions, but it allows profanity and some toxic content, sexually explicit and violent content, and content that contains medical, financial, or legal information. Contextual mode is suited for entertainment, creative, or academic use. Strict: Aims to avoid sensitive topics, such as violent or sexual acts and profanity. This mode aims to provide a safer experience by prohibiting responses or recommendations that it finds inappropriate. Strict mode is suited for corporate use, such as for corporate communications and customer service. Off: No safety mode is applied. Note: This parameter is only compatible with models cohere.command-r-08-2024, cohere.command-r-plus-08-2024 and Cohere models released after these models. See release dates.

Accepted values are:

CONTEXTUAL, OFF, STRICT
--chat-request-seed [integer]

If specified, the backend will make a best effort to sample tokens deterministically, so that repeated requests with the same seed and parameters yield the same result. However, determinism cannot be fully guaranteed.

--chat-request-stop-sequences [complex type]

Stop the model generation when it reaches a stop sequence defined in this parameter. This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

--chat-request-stream-options [complex type]

This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

--chat-request-temperature [text]

A number that sets the randomness of the generated output. A lower temperature means less random generations. Use lower numbers for tasks 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.

--chat-request-thinking [complex type]

This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

--chat-request-tools [complex type]

A list of available tools (functions) that the model may suggest invoking before producing a text response.

This option is a JSON list with items of type CohereToolV2. For documentation on CohereToolV2 please see our API reference: https://docs.cloud.oracle.com/api/#/en/generativeaiinference/20231130/datatypes/CohereToolV2. This is a complex type whose value must be valid JSON. The value can be provided as a string on the command line or passed in as a file using the file://path/to/file syntax.

The --generate-param-json-input option can be used to generate an example of the JSON which must be provided. We recommend storing this example in a file, modifying it as needed and then passing it back in via the file:// syntax.

--chat-request-tools-choice [text]

Used to control whether or not the model will be forced to use a tool when answering. When REQUIRED is specified, the model will be forced to use at least one of the user-defined tools, and the tools parameter must be passed in the request. When NONE is specified, the model will be forced not to use one of the specified tools, and give a direct response. If tool_choice isn’t specified, then the model is free to choose whether to use the specified tools or not. Note:This parameter is only compatible with models Command-r7b and newer.

Accepted values are:

NONE, REQUIRED
--chat-request-top-k [integer]

A sampling method in which the model chooses the next token randomly from the top k most likely tokens. A higher value for k generates more random output, which makes the output text sound more natural. The default value for k 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 only the probabilities of the top 10 add up to the value of p, then only the top 10 tokens are chosen.

--chat-request-top-p [text]

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.

--from-json [text]

Provide input to this command as a JSON document from a file using the file://path-to/file syntax.

The --generate-full-command-json-input option can be used to generate a sample json file to be used with this command option. The key names are pre-populated and match the command option names (converted to camelCase format, e.g. compartment-id –> compartmentId), while the values of the keys need to be populated by the user before using the sample file as an input to this command. For any command option that accepts multiple values, the value of the key can be a JSON array.

Options can still be provided on the command line. If an option exists in both the JSON document and the command line then the command line specified value will be used.

For examples on usage of this option, please see our “using CLI with advanced JSON options” link: https://docs.cloud.oracle.com/iaas/Content/API/SDKDocs/cliusing.htm#AdvancedJSONOptions

Example using required parameter

Copy and paste the following example into a JSON file, replacing the example parameters with your own.

    oci generative-ai-inference chat-result chat-cohere-chat-request-v2 --generate-param-json-input chat-request-messages > chat-request-messages.json
    oci generative-ai-inference chat-result chat-cohere-chat-request-v2 --generate-param-json-input serving-mode > serving-mode.json

Copy the following CLI commands into a file named example.sh. Run the command by typing “bash example.sh” and replacing the example parameters with your own.

Please note this sample will only work in the POSIX-compliant bash-like shell. You need to set up the OCI configuration and appropriate security policies before trying the examples.

    export compartment_id=<substitute-value-of-compartment_id> # https://docs.cloud.oracle.com/en-us/iaas/tools/oci-cli/latest/oci_cli_docs/cmdref/generative-ai-inference/chat-result/chat-cohere-chat-request-v2.html#cmdoption-compartment-id

    oci generative-ai-inference chat-result chat-cohere-chat-request-v2 --chat-request-messages file://chat-request-messages.json --compartment-id $compartment_id --serving-mode file://serving-mode.json