AI-Ollama-Client
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ollama/ollama-curated.yaml view on Meta::CPAN
schema:
$ref: '#/components/schemas/DeleteModelRequest'
responses:
'200':
description: Successful operation.
/pull:
post:
operationId: pullModel
tags:
- Models
summary: Download a model from the ollama library.
description: Cancelled pulls are resumed from where they left off, and multiple calls will share the same download progress.
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/PullModelRequest'
responses:
'200':
description: Successful operation.
content:
application/x-ndjson:
schema:
$ref: '#/components/schemas/PullModelResponse'
/push:
post:
operationId: pushModel
tags:
- Models
summary: Upload a model to a model library.
description: Requires registering for ollama.ai and adding a public key first.
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/PushModelRequest'
responses:
'200':
description: Successful operation.
content:
application/json:
schema:
$ref: '#/components/schemas/PushModelResponse'
"/blobs/{digest}":
head:
operationId: checkBlob
tags:
- Models
summary: Check to see if a blob exists on the Ollama server which is useful when creating models.
parameters:
- in: path
name: digest
schema:
type: string
required: true
description: the SHA256 digest of the blob
example: sha256:c8edda1f17edd2f1b60253b773d837bda7b9d249a61245931a4d7c9a8d350250
responses:
'200':
description: Blob exists on the server
'404':
description: Blob was not found
post:
operationId: createBlob
tags:
- Models
summary: Create a blob from a file. Returns the server file path.
parameters:
- in: path
name: digest
schema:
type: string
required: true
description: the SHA256 digest of the blob
example: sha256:c8edda1f17edd2f1b60253b773d837bda7b9d249a61245931a4d7c9a8d350250
requestBody:
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
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