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Ashwin Bharambe 2025-01-29 09:09:51 -08:00
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247
docs/resources/llama-stack-spec.html
View file

@ -2337,15 +2337,6 @@
"rows"
]
},
"BuiltinTool": {
"type": "string",
"enum": [
"brave_search",
"wolfram_alpha",
"photogen",
"code_interpreter"
]
},
"CompletionMessage": {
"type": "object",
"properties": {
@ -2360,7 +2351,12 @@
"description": "The content of the model's response"
},
"stop_reason": {
"$ref": "#/components/schemas/StopReason",
"type": "string",
"enum": [
"end_of_turn",
"end_of_message",
"out_of_tokens"
],
"description": "Reason why the model stopped generating. Options are: - `StopReason.end_of_turn`: The model finished generating the entire response. - `StopReason.end_of_message`: The model finished generating but generated a partial response -- usually, a tool call. The user may call the tool and continue the conversation with the tool's response. - `StopReason.out_of_tokens`: The model ran out of token budget."
},
"tool_calls": {
@ -2587,25 +2583,7 @@
"type": "object",
"properties": {
"strategy": {
"oneOf": [
{
"$ref": "#/components/schemas/GreedySamplingStrategy"
},
{
"$ref": "#/components/schemas/TopPSamplingStrategy"
},
{
"$ref": "#/components/schemas/TopKSamplingStrategy"
}
],
"discriminator": {
"propertyName": "type",
"mapping": {
"greedy": "#/components/schemas/GreedySamplingStrategy",
"top_p": "#/components/schemas/TopPSamplingStrategy",
"top_k": "#/components/schemas/TopKSamplingStrategy"
}
}
"$ref": "#/components/schemas/SamplingStrategy"
},
"max_tokens": {
"type": "integer",
@ -2621,13 +2599,26 @@
"strategy"
]
},
"StopReason": {
"type": "string",
"enum": [
"end_of_turn",
"end_of_message",
"out_of_tokens"
]
"SamplingStrategy": {
"oneOf": [
{
"$ref": "#/components/schemas/GreedySamplingStrategy"
},
{
"$ref": "#/components/schemas/TopPSamplingStrategy"
},
{
"$ref": "#/components/schemas/TopKSamplingStrategy"
}
],
"discriminator": {
"propertyName": "type",
"mapping": {
"greedy": "#/components/schemas/GreedySamplingStrategy",
"top_p": "#/components/schemas/TopPSamplingStrategy",
"top_k": "#/components/schemas/TopKSamplingStrategy"
}
}
},
"SystemMessage": {
"type": "object",
@ -2677,7 +2668,13 @@
"tool_name": {
"oneOf": [
{
"$ref": "#/components/schemas/BuiltinTool"
"type": "string",
"enum": [
"brave_search",
"wolfram_alpha",
"photogen",
"code_interpreter"
]
},
{
"type": "string"
@ -2758,21 +2755,19 @@
"arguments"
]
},
"ToolChoice": {
"type": "string",
"enum": [
"auto",
"required"
],
"title": "Whether tool use is required or automatic. This is a hint to the model which may not be followed. It depends on the Instruction Following capabilities of the model."
},
"ToolDefinition": {
"type": "object",
"properties": {
"tool_name": {
"oneOf": [
{
"$ref": "#/components/schemas/BuiltinTool"
"type": "string",
"enum": [
"brave_search",
"wolfram_alpha",
"photogen",
"code_interpreter"
]
},
{
"type": "string"
@ -2835,16 +2830,6 @@
"param_type"
]
},
"ToolPromptFormat": {
"type": "string",
"enum": [
"json",
"function_tag",
"python_list"
],
"title": "This Enum refers to the prompt format for calling custom / zero shot tools",
"description": "`json` --\n Refers to the json format for calling tools.\n The json format takes the form like\n {\n \"type\": \"function\",\n \"function\" : {\n \"name\": \"function_name\",\n \"description\": \"function_description\",\n \"parameters\": {...}\n }\n }\n\n`function_tag` --\n This is an example of how you could define\n your own user defined format for making tool calls.\n The function_tag format looks like this,\n <function=function_name>(parameters)</function>\n\nThe detailed prompts for each of these formats are added to llama cli"
},
"ToolResponseMessage": {
"type": "object",
"properties": {
@ -2861,7 +2846,13 @@
"tool_name": {
"oneOf": [
{
"$ref": "#/components/schemas/BuiltinTool"
"type": "string",
"enum": [
"brave_search",
"wolfram_alpha",
"photogen",
"code_interpreter"
]
},
{
"type": "string"
@ -2984,10 +2975,22 @@
}
},
"tool_choice": {
"$ref": "#/components/schemas/ToolChoice"
"type": "string",
"enum": [
"auto",
"required"
],
"title": "Whether tool use is required or automatic. This is a hint to the model which may not be followed. It depends on the Instruction Following capabilities of the model."
},
"tool_prompt_format": {
"$ref": "#/components/schemas/ToolPromptFormat"
"type": "string",
"enum": [
"json",
"function_tag",
"python_list"
],
"title": "This Enum refers to the prompt format for calling custom / zero shot tools",
"description": "The detailed prompts for each of these formats are added to llama cli"
},
"response_format": {
"$ref": "#/components/schemas/ResponseFormat"
@ -3122,7 +3125,12 @@
"description": "The generated completion text"
},
"stop_reason": {
"$ref": "#/components/schemas/StopReason",
"type": "string",
"enum": [
"end_of_turn",
"end_of_message",
"out_of_tokens"
],
"description": "Reason why generation stopped"
},
"logprobs": {
@ -3178,11 +3186,20 @@
"description": "(Optional) List of tool definitions available to the model"
},
"tool_choice": {
"$ref": "#/components/schemas/ToolChoice",
"type": "string",
"enum": [
"auto",
"required"
],
"description": "(Optional) Whether tool use is required or automatic. Defaults to ToolChoice.auto."
},
"tool_prompt_format": {
"$ref": "#/components/schemas/ToolPromptFormat",
"type": "string",
"enum": [
"json",
"function_tag",
"python_list"
],
"description": "(Optional) Instructs the model how to format tool calls. By default, Llama Stack will attempt to use a format that is best adapted to the model. - `ToolPromptFormat.json`: The tool calls are formatted as a JSON object. - `ToolPromptFormat.function_tag`: The tool calls are enclosed in a <function=function_name> tag. - `ToolPromptFormat.python_list`: The tool calls are output as Python syntax -- a list of function calls."
},
"response_format": {
@ -3216,7 +3233,12 @@
"type": "object",
"properties": {
"event_type": {
"$ref": "#/components/schemas/ChatCompletionResponseEventType",
"type": "string",
"enum": [
"start",
"complete",
"progress"
],
"description": "Type of the event"
},
"delta": {
@ -3231,7 +3253,12 @@
"description": "Optional log probabilities for generated tokens"
},
"stop_reason": {
"$ref": "#/components/schemas/StopReason",
"type": "string",
"enum": [
"end_of_turn",
"end_of_message",
"out_of_tokens"
],
"description": "Optional reason why generation stopped, if complete"
}
},
@ -3242,15 +3269,6 @@
],
"title": "An event during chat completion generation."
},
"ChatCompletionResponseEventType": {
"type": "string",
"enum": [
"start",
"complete",
"progress"
],
"title": "Types of events that can occur during chat completion."
},
"ChatCompletionResponseStreamChunk": {
"type": "object",
"properties": {
@ -3342,7 +3360,13 @@
]
},
"parse_status": {
"$ref": "#/components/schemas/ToolCallParseStatus"
"type": "string",
"enum": [
"started",
"in_progress",
"failed",
"succeeded"
]
}
},
"additionalProperties": false,
@ -3352,15 +3376,6 @@
"parse_status"
]
},
"ToolCallParseStatus": {
"type": "string",
"enum": [
"started",
"in_progress",
"failed",
"succeeded"
]
},
"CompletionRequest": {
"type": "object",
"properties": {
@ -3411,7 +3426,12 @@
"description": "New content generated since last chunk. This can be one or more tokens."
},
"stop_reason": {
"$ref": "#/components/schemas/StopReason",
"type": "string",
"enum": [
"end_of_turn",
"end_of_message",
"out_of_tokens"
],
"description": "Optional reason why generation stopped, if complete"
},
"logprobs": {
@ -3459,11 +3479,23 @@
}
},
"tool_choice": {
"$ref": "#/components/schemas/ToolChoice",
"type": "string",
"enum": [
"auto",
"required"
],
"title": "Whether tool use is required or automatic. This is a hint to the model which may not be followed. It depends on the Instruction Following capabilities of the model.",
"default": "auto"
},
"tool_prompt_format": {
"$ref": "#/components/schemas/ToolPromptFormat"
"type": "string",
"enum": [
"json",
"function_tag",
"python_list"
],
"title": "This Enum refers to the prompt format for calling custom / zero shot tools",
"description": "The detailed prompts for each of these formats are added to llama cli"
},
"max_infer_iters": {
"type": "integer",
@ -4170,7 +4202,13 @@
"tool_name": {
"oneOf": [
{
"$ref": "#/components/schemas/BuiltinTool"
"type": "string",
"enum": [
"brave_search",
"wolfram_alpha",
"photogen",
"code_interpreter"
]
},
{
"type": "string"
@ -7917,10 +7955,6 @@
"name": "BooleanType",
"description": ""
},
{
"name": "BuiltinTool",
"description": ""
},
{
"name": "CancelTrainingJobRequest",
"description": ""
@ -7941,10 +7975,6 @@
"name": "ChatCompletionResponseEvent",
"description": "An event during chat completion generation."
},
{
"name": "ChatCompletionResponseEventType",
"description": "Types of events that can occur during chat completion."
},
{
"name": "ChatCompletionResponseStreamChunk",
"description": "A chunk of a streamed chat completion response."
@ -8376,6 +8406,10 @@
"name": "SamplingParams",
"description": ""
},
{
"name": "SamplingStrategy",
"description": ""
},
{
"name": "SaveSpansToDatasetRequest",
"description": ""
@ -8449,10 +8483,6 @@
"name": "SpanWithStatus",
"description": ""
},
{
"name": "StopReason",
"description": ""
},
{
"name": "StringType",
"description": ""
@ -8511,14 +8541,6 @@
"name": "ToolCallDelta",
"description": ""
},
{
"name": "ToolCallParseStatus",
"description": ""
},
{
"name": "ToolChoice",
"description": "Whether tool use is required or automatic. This is a hint to the model which may not be followed. It depends on the Instruction Following capabilities of the model."
},
{
"name": "ToolDef",
"description": ""
@ -8554,10 +8576,6 @@
"name": "ToolParameter",
"description": ""
},
{
"name": "ToolPromptFormat",
"description": "This Enum refers to the prompt format for calling custom / zero shot tools\n\n`json` --\n Refers to the json format for calling tools.\n The json format takes the form like\n {\n \"type\": \"function\",\n \"function\" : {\n \"name\": \"function_name\",\n \"description\": \"function_description\",\n \"parameters\": {...}\n }\n }\n\n`function_tag` --\n This is an example of how you could define\n your own user defined format for making tool calls.\n The function_tag format looks like this,\n <function=function_name>(parameters)</function>\n\nThe detailed prompts for each of these formats are added to llama cli"
},
{
"name": "ToolResponse",
"description": ""
@ -8680,13 +8698,11 @@
"BatchCompletionResponse",
"BenchmarkEvalTaskConfig",
"BooleanType",
"BuiltinTool",
"CancelTrainingJobRequest",
"ChatCompletionInputType",
"ChatCompletionRequest",
"ChatCompletionResponse",
"ChatCompletionResponseEvent",
"ChatCompletionResponseEventType",
"ChatCompletionResponseStreamChunk",
"Checkpoint",
"CompletionInputType",
@ -8788,6 +8804,7 @@
"RunShieldResponse",
"SafetyViolation",
"SamplingParams",
"SamplingStrategy",
"SaveSpansToDatasetRequest",
"ScoreBatchRequest",
"ScoreBatchResponse",
@ -8804,7 +8821,6 @@
"SpanStartPayload",
"SpanStatus",
"SpanWithStatus",
"StopReason",
"StringType",
"StructuredLogEvent",
"StructuredLogPayload",
@ -8818,8 +8834,6 @@
"Tool",
"ToolCall",
"ToolCallDelta",
"ToolCallParseStatus",
"ToolChoice",
"ToolDef",
"ToolDefinition",
"ToolExecutionStep",
@ -8828,7 +8842,6 @@
"ToolInvocationResult",
"ToolParamDefinition",
"ToolParameter",
"ToolPromptFormat",
"ToolResponse",
"ToolResponseMessage",
"TopKSamplingStrategy",

248
docs/resources/llama-stack-spec.yaml
View file

@ -1383,13 +1383,6 @@ components:
required:
- dataset_id
- rows
BuiltinTool:
type: string
enum:
- brave_search
- wolfram_alpha
- photogen
- code_interpreter
CompletionMessage:
type: object
properties:
@ -1403,7 +1396,11 @@ components:
$ref: '#/components/schemas/InterleavedContent'
description: The content of the model's response
stop_reason:
$ref: '#/components/schemas/StopReason'
type: string
enum:
- end_of_turn
- end_of_message
- out_of_tokens
description: >-
Reason why the model stopped generating. Options are: - `StopReason.end_of_turn`:
The model finished generating the entire response. - `StopReason.end_of_message`:
@ -1552,16 +1549,7 @@ components:
type: object
properties:
strategy:
oneOf:
- $ref: '#/components/schemas/GreedySamplingStrategy'
- $ref: '#/components/schemas/TopPSamplingStrategy'
- $ref: '#/components/schemas/TopKSamplingStrategy'
discriminator:
propertyName: type
mapping:
greedy: '#/components/schemas/GreedySamplingStrategy'
top_p: '#/components/schemas/TopPSamplingStrategy'
top_k: '#/components/schemas/TopKSamplingStrategy'
$ref: '#/components/schemas/SamplingStrategy'
max_tokens:
type: integer
default: 0
@ -1571,12 +1559,17 @@ components:
additionalProperties: false
required:
- strategy
StopReason:
type: string
enum:
- end_of_turn
- end_of_message
- out_of_tokens
SamplingStrategy:
oneOf:
- $ref: '#/components/schemas/GreedySamplingStrategy'
- $ref: '#/components/schemas/TopPSamplingStrategy'
- $ref: '#/components/schemas/TopKSamplingStrategy'
discriminator:
propertyName: type
mapping:
greedy: '#/components/schemas/GreedySamplingStrategy'
top_p: '#/components/schemas/TopPSamplingStrategy'
top_k: '#/components/schemas/TopKSamplingStrategy'
SystemMessage:
type: object
properties:
@ -1618,7 +1611,12 @@ components:
type: string
tool_name:
oneOf:
- $ref: '#/components/schemas/BuiltinTool'
- type: string
enum:
- brave_search
- wolfram_alpha
- photogen
- code_interpreter
- type: string
arguments:
type: object
@ -1650,21 +1648,17 @@ components:
- call_id
- tool_name
- arguments
ToolChoice:
type: string
enum:
- auto
- required
title: >-
Whether tool use is required or automatic. This is a hint to the model which
may not be followed. It depends on the Instruction Following capabilities
of the model.
ToolDefinition:
type: object
properties:
tool_name:
oneOf:
- $ref: '#/components/schemas/BuiltinTool'
- type: string
enum:
- brave_search
- wolfram_alpha
- photogen
- code_interpreter
- type: string
description:
type: string
@ -1696,34 +1690,6 @@ components:
additionalProperties: false
required:
- param_type
ToolPromptFormat:
type: string
enum:
- json
- function_tag
- python_list
title: >-
This Enum refers to the prompt format for calling custom / zero shot tools
description: >-
`json` --
Refers to the json format for calling tools.
The json format takes the form like
{
"type": "function",
"function" : {
"name": "function_name",
"description": "function_description",
"parameters": {...}
}
}
`function_tag` --
This is an example of how you could define
your own user defined format for making tool calls.
The function_tag format looks like this,
<function=function_name>(parameters)</function>
The detailed prompts for each of these formats are added to llama cli
ToolResponseMessage:
type: object
properties:
@ -1739,7 +1705,12 @@ components:
Unique identifier for the tool call this response is for
tool_name:
oneOf:
- $ref: '#/components/schemas/BuiltinTool'
- type: string
enum:
- brave_search
- wolfram_alpha
- photogen
- code_interpreter
- type: string
description: Name of the tool that was called
content:
@ -1831,9 +1802,24 @@ components:
items:
$ref: '#/components/schemas/ToolDefinition'
tool_choice:
$ref: '#/components/schemas/ToolChoice'
type: string
enum:
- auto
- required
title: >-
Whether tool use is required or automatic. This is a hint to the model
which may not be followed. It depends on the Instruction Following capabilities
of the model.
tool_prompt_format:
$ref: '#/components/schemas/ToolPromptFormat'
type: string
enum:
- json
- function_tag
- python_list
title: >-
This Enum refers to the prompt format for calling custom / zero shot tools
description: >-
The detailed prompts for each of these formats are added to llama cli
response_format:
$ref: '#/components/schemas/ResponseFormat'
logprobs:
@ -1931,7 +1917,11 @@ components:
type: string
description: The generated completion text
stop_reason:
$ref: '#/components/schemas/StopReason'
type: string
enum:
- end_of_turn
- end_of_message
- out_of_tokens
description: Reason why generation stopped
logprobs:
type: array
@ -1976,11 +1966,18 @@ components:
description: >-
(Optional) List of tool definitions available to the model
tool_choice:
$ref: '#/components/schemas/ToolChoice'
type: string
enum:
- auto
- required
description: >-
(Optional) Whether tool use is required or automatic. Defaults to ToolChoice.auto.
tool_prompt_format:
$ref: '#/components/schemas/ToolPromptFormat'
type: string
enum:
- json
- function_tag
- python_list
description: >-
(Optional) Instructs the model how to format tool calls. By default, Llama
Stack will attempt to use a format that is best adapted to the model.
@ -2021,7 +2018,11 @@ components:
type: object
properties:
event_type:
$ref: '#/components/schemas/ChatCompletionResponseEventType'
type: string
enum:
- start
- complete
- progress
description: Type of the event
delta:
$ref: '#/components/schemas/ContentDelta'
@ -2035,7 +2036,11 @@ components:
description: >-
Optional log probabilities for generated tokens
stop_reason:
$ref: '#/components/schemas/StopReason'
type: string
enum:
- end_of_turn
- end_of_message
- out_of_tokens
description: >-
Optional reason why generation stopped, if complete
additionalProperties: false
@ -2044,14 +2049,6 @@ components:
- delta
title: >-
An event during chat completion generation.
ChatCompletionResponseEventType:
type: string
enum:
- start
- complete
- progress
title: >-
Types of events that can occur during chat completion.
ChatCompletionResponseStreamChunk:
type: object
properties:
@ -2113,19 +2110,17 @@ components:
- type: string
- $ref: '#/components/schemas/ToolCall'
parse_status:
$ref: '#/components/schemas/ToolCallParseStatus'
type: string
enum:
- started
- in_progress
- failed
- succeeded
additionalProperties: false
required:
- type
- tool_call
- parse_status
ToolCallParseStatus:
type: string
enum:
- started
- in_progress
- failed
- succeeded
CompletionRequest:
type: object
properties:
@ -2174,7 +2169,11 @@ components:
description: >-
New content generated since last chunk. This can be one or more tokens.
stop_reason:
$ref: '#/components/schemas/StopReason'
type: string
enum:
- end_of_turn
- end_of_message
- out_of_tokens
description: >-
Optional reason why generation stopped, if complete
logprobs:
@ -2210,10 +2209,25 @@ components:
items:
$ref: '#/components/schemas/ToolDef'
tool_choice:
$ref: '#/components/schemas/ToolChoice'
type: string
enum:
- auto
- required
title: >-
Whether tool use is required or automatic. This is a hint to the model
which may not be followed. It depends on the Instruction Following capabilities
of the model.
default: auto
tool_prompt_format:
$ref: '#/components/schemas/ToolPromptFormat'
type: string
enum:
- json
- function_tag
- python_list
title: >-
This Enum refers to the prompt format for calling custom / zero shot tools
description: >-
The detailed prompts for each of these formats are added to llama cli
max_infer_iters:
type: integer
default: 10
@ -2656,7 +2670,12 @@ components:
type: string
tool_name:
oneOf:
- $ref: '#/components/schemas/BuiltinTool'
- type: string
enum:
- brave_search
- wolfram_alpha
- photogen
- code_interpreter
- type: string
content:
$ref: '#/components/schemas/InterleavedContent'
@ -4942,8 +4961,6 @@ tags:
description: ''
- name: BooleanType
description: ''
- name: BuiltinTool
description: ''
- name: CancelTrainingJobRequest
description: ''
- name: ChatCompletionInputType
@ -4955,9 +4972,6 @@ tags:
- name: ChatCompletionResponseEvent
description: >-
An event during chat completion generation.
- name: ChatCompletionResponseEventType
description: >-
Types of events that can occur during chat completion.
- name: ChatCompletionResponseStreamChunk
description: >-
A chunk of a streamed chat completion response.
@ -5175,6 +5189,8 @@ tags:
description: ''
- name: SamplingParams
description: ''
- name: SamplingStrategy
description: ''
- name: SaveSpansToDatasetRequest
description: ''
- name: ScoreBatchRequest
@ -5212,8 +5228,6 @@ tags:
description: ''
- name: SpanWithStatus
description: ''
- name: StopReason
description: ''
- name: StringType
description: ''
- name: StructuredLogEvent
@ -5245,13 +5259,6 @@ tags:
description: ''
- name: ToolCallDelta
description: ''
- name: ToolCallParseStatus
description: ''
- name: ToolChoice
description: >-
Whether tool use is required or automatic. This is a hint to the model which
may not be followed. It depends on the Instruction Following capabilities of
the model.
- name: ToolDef
description: ''
- name: ToolDefinition
@ -5269,30 +5276,6 @@ tags:
description: ''
- name: ToolParameter
description: ''
- name: ToolPromptFormat
description: >-
This Enum refers to the prompt format for calling custom / zero shot tools
`json` --
Refers to the json format for calling tools.
The json format takes the form like
{
"type": "function",
"function" : {
"name": "function_name",
"description": "function_description",
"parameters": {...}
}
}
`function_tag` --
This is an example of how you could define
your own user defined format for making tool calls.
The function_tag format looks like this,
<function=function_name>(parameters)</function>
The detailed prompts for each of these formats are added to llama cli
- name: ToolResponse
description: ''
- name: ToolResponseMessage
@ -5379,13 +5362,11 @@ x-tagGroups:
- BatchCompletionResponse
- BenchmarkEvalTaskConfig
- BooleanType
- BuiltinTool
- CancelTrainingJobRequest
- ChatCompletionInputType
- ChatCompletionRequest
- ChatCompletionResponse
- ChatCompletionResponseEvent
- ChatCompletionResponseEventType
- ChatCompletionResponseStreamChunk
- Checkpoint
- CompletionInputType
@ -5487,6 +5468,7 @@ x-tagGroups:
- RunShieldResponse
- SafetyViolation
- SamplingParams
- SamplingStrategy
- SaveSpansToDatasetRequest
- ScoreBatchRequest
- ScoreBatchResponse
@ -5503,7 +5485,6 @@ x-tagGroups:
- SpanStartPayload
- SpanStatus
- SpanWithStatus
- StopReason
- StringType
- StructuredLogEvent
- StructuredLogPayload
@ -5517,8 +5498,6 @@ x-tagGroups:
- Tool
- ToolCall
- ToolCallDelta
- ToolCallParseStatus
- ToolChoice
- ToolDef
- ToolDefinition
- ToolExecutionStep
@ -5527,7 +5506,6 @@ x-tagGroups:
- ToolInvocationResult
- ToolParamDefinition
- ToolParameter
- ToolPromptFormat
- ToolResponse
- ToolResponseMessage
- TopKSamplingStrategy

1
llama_stack/apis/common/content_types.py
View file

@ -77,7 +77,6 @@ class ImageDelta(BaseModel):
image: bytes
@json_schema_type
class ToolCallParseStatus(Enum):
started = "started"
in_progress = "in_progress"

4
llama_stack/apis/inference/inference.py
View file

@ -43,7 +43,6 @@ class LogProbConfig(BaseModel):
top_k: Optional[int] = 0
@json_schema_type
class QuantizationType(Enum):
"""Type of model quantization to run inference with.
@ -177,7 +176,6 @@ class ToolResponse(BaseModel):
return v
@json_schema_type
class ToolChoice(Enum):
"""Whether tool use is required or automatic. This is a hint to the model which may not be followed. It depends on the Instruction Following capabilities of the model.
@ -199,7 +197,6 @@ class TokenLogProbs(BaseModel):
logprobs_by_token: Dict[str, float]
@json_schema_type
class ChatCompletionResponseEventType(Enum):
"""Types of events that can occur during chat completion.
@ -229,7 +226,6 @@ class ChatCompletionResponseEvent(BaseModel):
stop_reason: Optional[StopReason] = None
@json_schema_type
class ResponseFormatType(Enum):
"""Types of formats for structured (guided) decoding.

2
llama_stack/apis/resource.py
View file

@ -6,11 +6,9 @@
from enum import Enum
from llama_models.schema_utils import json_schema_type
from pydantic import BaseModel, Field
@json_schema_type
class ResourceType(Enum):
model = "model"
shield = "shield"