AI-Ollama-Client
view release on metacpan or search on metacpan
ollama/ollama-curated.yaml view on Meta::CPAN
content:
application/octet-stream:
schema:
type: string
format: binary
responses:
'201':
description: Blob was successfully created
components:
schemas:
GenerateCompletionRequest:
type: object
description: Request class for the generate endpoint.
properties:
model:
type: string
description: &model_name |
The model name.
Model names follow a `model:tag` format. Some examples are `orca-mini:3b-q4_1` and `llama2:70b`. The tag is optional and, if not provided, will default to `latest`. The tag is used to identify a specific version.
example: llama2:7b
prompt:
type: string
description: The prompt to generate a response.
example: Why is the sky blue?
images:
type: array
description: (optional) a list of Base64-encoded images to include in the message (for multimodal models such as llava)
items:
type: string
contentEncoding: base64
description: Base64-encoded image (for multimodal models such as llava)
example: iVBORw0KGgoAAAANSUhEUgAAAAkAAAANCAIAAAD0YtNRAAAABnRSTlMA/AD+APzoM1ogAAAAWklEQVR4AWP48+8PLkR7uUdzcMvtU8EhdykHKAciEXL3pvw5FQIURaBDJkARoDhY3zEXiCgCHbNBmAlUiyaBkENoxZSDWnOtBmoAQu7TnT+3WuDOA7KBIkAGAGwiNeqjusp/AAAAAElFTkSuQmCC
system:
type: string
description: The system prompt to (overrides what is defined in the Modelfile).
template:
type: string
description: The full prompt or prompt template (overrides what is defined in the Modelfile).
context:
type: array
description: The context parameter returned from a previous request to [generateCompletion], this can be used to keep a short conversational memory.
items:
type: integer
options:
$ref: '#/components/schemas/RequestOptions'
format:
$ref: '#/components/schemas/ResponseFormat'
raw:
type: boolean
description: |
If `true` no formatting will be applied to the prompt and no context will be returned.
You may choose to use the `raw` parameter if you are specifying a full templated prompt in your request to the API, and are managing history yourself.
stream:
type: boolean
description: &stream |
If `false` the response will be returned as a single response object, otherwise the response will be streamed as a series of objects.
default: false
keep_alive:
type: integer
description: &keep_alive |
How long (in minutes) to keep the model loaded in memory.
- If set to a positive duration (e.g. 20), the model will stay loaded for the provided duration.
- If set to a negative duration (e.g. -1), the model will stay loaded indefinitely.
- If set to 0, the model will be unloaded immediately once finished.
- If not set, the model will stay loaded for 5 minutes by default
required:
- model
- prompt
RequestOptions:
type: object
description: Additional model parameters listed in the documentation for the Modelfile such as `temperature`.
properties:
num_keep:
type: integer
description: |
Number of tokens to keep from the prompt.
seed:
type: integer
description: |
Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0)
num_predict:
type: integer
description: |
Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context)
top_k:
type: integer
description: |
Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)
top_p:
type: number
format: float
description: |
Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)
tfs_z:
type: number
format: float
description: |
Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1)
typical_p:
type: number
format: float
description: |
Typical p is used to reduce the impact of less probable tokens from the output.
repeat_last_n:
type: integer
description: |
Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)
temperature:
type: number
format: float
description: |
The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)
repeat_penalty:
type: number
format: float
description: |
Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)
presence_penalty:
type: number
ollama/ollama-curated.yaml view on Meta::CPAN
response:
type: string
description: The response for a given prompt with a provided model.
example: The sky appears blue because of a phenomenon called Rayleigh scattering.
done:
type: boolean
description: Whether the response has completed.
example: true
context:
type: array
description: |
An encoding of the conversation used in this response, this can be sent in the next request to keep a conversational memory.
items:
type: integer
example: [ 1, 2, 3 ]
total_duration:
type: integer
description: Time spent generating the response.
example: 5589157167
load_duration:
type: integer
description: Time spent in nanoseconds loading the model.
example: 3013701500
prompt_eval_count:
type: integer
description: Number of tokens in the prompt.
example: 46
prompt_eval_duration:
type: integer
description: Time spent in nanoseconds evaluating the prompt.
example: 1160282000
eval_count:
type: integer
description: Number of tokens the response.
example: 113
eval_duration:
type: integer
description: Time in nanoseconds spent generating the response.
example: 1325948000
GenerateChatCompletionRequest:
type: object
description: Request class for the chat endpoint.
properties:
model:
type: string
description: *model_name
example: llama2:7b
messages:
type: array
description: The messages of the chat, this can be used to keep a chat memory
items:
$ref: '#/components/schemas/Message'
format:
$ref: '#/components/schemas/ResponseFormat'
options:
$ref: '#/components/schemas/RequestOptions'
stream:
type: boolean
description: *stream
default: false
keep_alive:
type: integer
description: *keep_alive
required:
- model
- messages
GenerateChatCompletionResponse:
type: object
description: The response class for the chat endpoint.
properties:
message:
$ref: '#/components/schemas/Message'
model:
type: string
description: *model_name
example: llama2:7b
created_at:
type: string
format: date-time
description: Date on which a model was created.
example: 2023-08-04T19:22:45.499127Z
done:
type: boolean
description: Whether the response has completed.
example: true
total_duration:
type: integer
description: Time spent generating the response.
example: 5589157167
load_duration:
type: integer
description: Time spent in nanoseconds loading the model.
example: 3013701500
prompt_eval_count:
type: integer
description: Number of tokens in the prompt.
example: 46
prompt_eval_duration:
type: integer
description: Time spent in nanoseconds evaluating the prompt.
example: 1160282000
eval_count:
type: integer
description: Number of tokens the response.
example: 113
eval_duration:
type: integer
description: Time in nanoseconds spent generating the response.
example: 1325948000
Message:
type: object
description: A message in the chat endpoint
properties:
role:
type: string
description: The role of the message
enum: [ "system", "user", "assistant" ]
content:
type: string
description: The content of the message
example: Why is the sky blue?
images:
type: array
( run in 1.386 second using v1.01-cache-2.11-cpan-5c0b1e786e0 )