mirror of
https://github.com/meta-llama/llama-stack.git
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featu: support passing "extra body" throught to providers
# What does this PR do? Allows passing through extra_body parameters to inference providers. closes #2720 ## Test Plan CI and added new test
This commit is contained in:
Eric Huang
parent
80d58ab519
commit
c4dbaa9d4c
41 changed files with 3145 additions and 200 deletions
23
docs/static/deprecated-llama-stack-spec.html
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docs/static/deprecated-llama-stack-spec.html
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@ -1527,7 +1527,7 @@
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/OpenAIChatCompletionRequest"
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"$ref": "#/components/schemas/OpenAIChatCompletionRequestWithExtraBody"
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}
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}
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},
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@ -1617,7 +1617,7 @@
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/OpenAICompletionRequest"
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"$ref": "#/components/schemas/OpenAICompletionRequestWithExtraBody"
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}
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}
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},
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@ -7522,7 +7522,7 @@
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"title": "OpenAIResponseFormatText",
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"description": "Text response format for OpenAI-compatible chat completion requests."
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},
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"OpenAIChatCompletionRequest": {
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"OpenAIChatCompletionRequestWithExtraBody": {
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"type": "object",
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"properties": {
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"model": {
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@ -7769,7 +7769,7 @@
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"model",
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"messages"
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],
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"title": "OpenAIChatCompletionRequest",
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"title": "OpenAIChatCompletionRequestWithExtraBody",
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"description": "Request parameters for OpenAI-compatible chat completion endpoint."
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},
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"OpenAIChatCompletion": {
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@ -7966,7 +7966,7 @@
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],
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"title": "OpenAICompletionWithInputMessages"
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},
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"OpenAICompletionRequest": {
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"OpenAICompletionRequestWithExtraBody": {
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"type": "object",
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"properties": {
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"model": {
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@ -8097,17 +8097,6 @@
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"type": "string",
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"description": "(Optional) The user to use."
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},
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"guided_choice": {
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"type": "array",
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"items": {
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"type": "string"
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},
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"description": "(Optional) vLLM-specific parameter for guided generation with a list of choices."
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},
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"prompt_logprobs": {
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"type": "integer",
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"description": "(Optional) vLLM-specific parameter for number of log probabilities to return for prompt tokens."
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},
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"suffix": {
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"type": "string",
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"description": "(Optional) The suffix that should be appended to the completion."
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@ -8118,7 +8107,7 @@
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"model",
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"prompt"
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],
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"title": "OpenAICompletionRequest",
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"title": "OpenAICompletionRequestWithExtraBody",
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"description": "Request parameters for OpenAI-compatible completion endpoint."
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},
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"OpenAICompletion": {
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24
docs/static/deprecated-llama-stack-spec.yaml
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docs/static/deprecated-llama-stack-spec.yaml
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@ -1098,7 +1098,7 @@ paths:
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenAIChatCompletionRequest'
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$ref: '#/components/schemas/OpenAIChatCompletionRequestWithExtraBody'
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required: true
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deprecated: true
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/v1/openai/v1/chat/completions/{completion_id}:
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@ -1167,7 +1167,7 @@ paths:
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenAICompletionRequest'
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$ref: '#/components/schemas/OpenAICompletionRequestWithExtraBody'
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required: true
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deprecated: true
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/v1/openai/v1/embeddings:
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@ -5575,7 +5575,7 @@ components:
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title: OpenAIResponseFormatText
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description: >-
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Text response format for OpenAI-compatible chat completion requests.
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OpenAIChatCompletionRequest:
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OpenAIChatCompletionRequestWithExtraBody:
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type: object
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properties:
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model:
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@ -5717,7 +5717,7 @@ components:
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required:
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- model
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- messages
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title: OpenAIChatCompletionRequest
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title: OpenAIChatCompletionRequestWithExtraBody
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description: >-
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Request parameters for OpenAI-compatible chat completion endpoint.
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OpenAIChatCompletion:
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@ -5885,7 +5885,7 @@ components:
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- model
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- input_messages
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title: OpenAICompletionWithInputMessages
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OpenAICompletionRequest:
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OpenAICompletionRequestWithExtraBody:
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type: object
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properties:
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model:
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@ -5973,18 +5973,6 @@ components:
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user:
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type: string
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description: (Optional) The user to use.
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guided_choice:
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type: array
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items:
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type: string
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description: >-
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(Optional) vLLM-specific parameter for guided generation with a list of
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choices.
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prompt_logprobs:
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type: integer
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description: >-
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(Optional) vLLM-specific parameter for number of log probabilities to
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return for prompt tokens.
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suffix:
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type: string
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description: >-
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@ -5993,7 +5981,7 @@ components:
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required:
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- model
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- prompt
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title: OpenAICompletionRequest
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title: OpenAICompletionRequestWithExtraBody
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description: >-
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Request parameters for OpenAI-compatible completion endpoint.
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OpenAICompletion:
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docs/static/llama-stack-spec.html
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@ -153,7 +153,7 @@
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/OpenAIChatCompletionRequest"
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"$ref": "#/components/schemas/OpenAIChatCompletionRequestWithExtraBody"
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}
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}
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},
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@ -243,7 +243,7 @@
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/OpenAICompletionRequest"
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"$ref": "#/components/schemas/OpenAICompletionRequestWithExtraBody"
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}
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}
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},
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"title": "OpenAIResponseFormatText",
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"description": "Text response format for OpenAI-compatible chat completion requests."
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},
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"OpenAIChatCompletionRequest": {
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"OpenAIChatCompletionRequestWithExtraBody": {
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"type": "object",
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"properties": {
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"model": {
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@ -5265,7 +5265,7 @@
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"model",
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"messages"
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],
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"title": "OpenAIChatCompletionRequest",
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"title": "OpenAIChatCompletionRequestWithExtraBody",
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"description": "Request parameters for OpenAI-compatible chat completion endpoint."
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},
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"OpenAIChatCompletion": {
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@ -5462,7 +5462,7 @@
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],
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"title": "OpenAICompletionWithInputMessages"
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},
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"OpenAICompletionRequest": {
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"OpenAICompletionRequestWithExtraBody": {
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"type": "object",
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"properties": {
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"model": {
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@ -5593,17 +5593,6 @@
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"type": "string",
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"description": "(Optional) The user to use."
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},
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"guided_choice": {
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"type": "array",
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"items": {
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"type": "string"
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},
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"description": "(Optional) vLLM-specific parameter for guided generation with a list of choices."
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},
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"prompt_logprobs": {
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"type": "integer",
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"description": "(Optional) vLLM-specific parameter for number of log probabilities to return for prompt tokens."
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},
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"suffix": {
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"type": "string",
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"description": "(Optional) The suffix that should be appended to the completion."
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@ -5614,7 +5603,7 @@
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"model",
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"prompt"
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],
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"title": "OpenAICompletionRequest",
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"title": "OpenAICompletionRequestWithExtraBody",
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"description": "Request parameters for OpenAI-compatible completion endpoint."
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},
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"OpenAICompletion": {
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docs/static/llama-stack-spec.yaml
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenAIChatCompletionRequest'
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$ref: '#/components/schemas/OpenAIChatCompletionRequestWithExtraBody'
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required: true
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deprecated: false
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/v1/chat/completions/{completion_id}:
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenAICompletionRequest'
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$ref: '#/components/schemas/OpenAICompletionRequestWithExtraBody'
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required: true
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deprecated: false
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/v1/conversations:
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@ -3824,7 +3824,7 @@ components:
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title: OpenAIResponseFormatText
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description: >-
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Text response format for OpenAI-compatible chat completion requests.
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OpenAIChatCompletionRequest:
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OpenAIChatCompletionRequestWithExtraBody:
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type: object
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properties:
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model:
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required:
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- model
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- messages
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title: OpenAIChatCompletionRequest
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title: OpenAIChatCompletionRequestWithExtraBody
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description: >-
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Request parameters for OpenAI-compatible chat completion endpoint.
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OpenAIChatCompletion:
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- model
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- input_messages
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title: OpenAICompletionWithInputMessages
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OpenAICompletionRequest:
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OpenAICompletionRequestWithExtraBody:
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type: object
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properties:
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model:
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user:
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type: string
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description: (Optional) The user to use.
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guided_choice:
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type: array
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items:
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type: string
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description: >-
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(Optional) vLLM-specific parameter for guided generation with a list of
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choices.
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prompt_logprobs:
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type: integer
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description: >-
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(Optional) vLLM-specific parameter for number of log probabilities to
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return for prompt tokens.
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suffix:
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type: string
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description: >-
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required:
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- model
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- prompt
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title: OpenAICompletionRequest
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title: OpenAICompletionRequestWithExtraBody
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description: >-
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Request parameters for OpenAI-compatible completion endpoint.
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OpenAICompletion:
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/OpenAIChatCompletionRequest"
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"$ref": "#/components/schemas/OpenAIChatCompletionRequestWithExtraBody"
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}
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}
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},
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"content": {
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"application/json": {
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"schema": {
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"$ref": "#/components/schemas/OpenAICompletionRequest"
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"$ref": "#/components/schemas/OpenAICompletionRequestWithExtraBody"
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}
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}
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},
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"title": "OpenAIResponseFormatText",
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"description": "Text response format for OpenAI-compatible chat completion requests."
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},
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"OpenAIChatCompletionRequest": {
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"OpenAIChatCompletionRequestWithExtraBody": {
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"type": "object",
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"properties": {
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"model": {
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@ -7274,7 +7274,7 @@
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"model",
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"messages"
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],
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"title": "OpenAIChatCompletionRequest",
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"title": "OpenAIChatCompletionRequestWithExtraBody",
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"description": "Request parameters for OpenAI-compatible chat completion endpoint."
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},
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"OpenAIChatCompletion": {
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@ -7471,7 +7471,7 @@
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],
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"title": "OpenAICompletionWithInputMessages"
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},
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"OpenAICompletionRequest": {
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"OpenAICompletionRequestWithExtraBody": {
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"type": "object",
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"properties": {
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"model": {
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@ -7602,17 +7602,6 @@
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"type": "string",
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"description": "(Optional) The user to use."
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},
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"guided_choice": {
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"type": "array",
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"items": {
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"type": "string"
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},
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"description": "(Optional) vLLM-specific parameter for guided generation with a list of choices."
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},
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"prompt_logprobs": {
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"type": "integer",
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"description": "(Optional) vLLM-specific parameter for number of log probabilities to return for prompt tokens."
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},
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"suffix": {
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"type": "string",
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"description": "(Optional) The suffix that should be appended to the completion."
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@ -7623,7 +7612,7 @@
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"model",
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"prompt"
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],
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"title": "OpenAICompletionRequest",
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"title": "OpenAICompletionRequestWithExtraBody",
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"description": "Request parameters for OpenAI-compatible completion endpoint."
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},
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"OpenAICompletion": {
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24
docs/static/stainless-llama-stack-spec.yaml
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docs/static/stainless-llama-stack-spec.yaml
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenAIChatCompletionRequest'
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$ref: '#/components/schemas/OpenAIChatCompletionRequestWithExtraBody'
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required: true
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deprecated: false
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/v1/chat/completions/{completion_id}:
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@ -170,7 +170,7 @@ paths:
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/OpenAICompletionRequest'
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$ref: '#/components/schemas/OpenAICompletionRequestWithExtraBody'
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required: true
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deprecated: false
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/v1/conversations:
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@ -5269,7 +5269,7 @@ components:
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title: OpenAIResponseFormatText
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description: >-
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Text response format for OpenAI-compatible chat completion requests.
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OpenAIChatCompletionRequest:
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OpenAIChatCompletionRequestWithExtraBody:
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type: object
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properties:
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model:
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@ -5411,7 +5411,7 @@ components:
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required:
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- model
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- messages
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title: OpenAIChatCompletionRequest
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title: OpenAIChatCompletionRequestWithExtraBody
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description: >-
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Request parameters for OpenAI-compatible chat completion endpoint.
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OpenAIChatCompletion:
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@ -5579,7 +5579,7 @@ components:
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- model
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- input_messages
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title: OpenAICompletionWithInputMessages
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OpenAICompletionRequest:
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OpenAICompletionRequestWithExtraBody:
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type: object
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properties:
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model:
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@ -5667,18 +5667,6 @@ components:
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user:
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type: string
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description: (Optional) The user to use.
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guided_choice:
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type: array
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items:
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type: string
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description: >-
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(Optional) vLLM-specific parameter for guided generation with a list of
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choices.
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prompt_logprobs:
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type: integer
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description: >-
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(Optional) vLLM-specific parameter for number of log probabilities to
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return for prompt tokens.
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suffix:
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type: string
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description: >-
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@ -5687,7 +5675,7 @@ components:
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required:
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- model
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- prompt
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title: OpenAICompletionRequest
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title: OpenAICompletionRequestWithExtraBody
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description: >-
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||||
Request parameters for OpenAI-compatible completion endpoint.
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OpenAICompletion:
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@ -15,7 +15,7 @@ from typing import (
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)
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from fastapi import Body
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from pydantic import BaseModel, ConfigDict, Field, field_validator
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from pydantic import BaseModel, Field, field_validator
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from typing_extensions import TypedDict
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from llama_stack.apis.common.content_types import ContentDelta, InterleavedContent
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@ -1036,8 +1036,9 @@ class ListOpenAIChatCompletionResponse(BaseModel):
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object: Literal["list"] = "list"
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# extra_body can be accessed via .model_extra
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@json_schema_type
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class OpenAICompletionRequest(BaseModel):
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class OpenAICompletionRequestWithExtraBody(BaseModel, extra="allow"):
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"""Request parameters for OpenAI-compatible completion endpoint.
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:param model: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
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@ -1058,12 +1059,8 @@ class OpenAICompletionRequest(BaseModel):
|
|||
:param top_p: (Optional) The top p to use.
|
||||
:param user: (Optional) The user to use.
|
||||
:param suffix: (Optional) The suffix that should be appended to the completion.
|
||||
:param guided_choice: (Optional) vLLM-specific parameter for guided generation with a list of choices.
|
||||
:param prompt_logprobs: (Optional) vLLM-specific parameter for number of log probabilities to return for prompt tokens.
|
||||
"""
|
||||
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
# Standard OpenAI completion parameters
|
||||
model: str
|
||||
prompt: str | list[str] | list[int] | list[list[int]]
|
||||
|
|
@ -1082,17 +1079,12 @@ class OpenAICompletionRequest(BaseModel):
|
|||
temperature: float | None = None
|
||||
top_p: float | None = None
|
||||
user: str | None = None
|
||||
|
||||
# vLLM-specific parameters (documented here but also allowed via extra fields)
|
||||
guided_choice: list[str] | None = None
|
||||
prompt_logprobs: int | None = None
|
||||
|
||||
# for fill-in-the-middle type completion
|
||||
suffix: str | None = None
|
||||
|
||||
|
||||
# extra_body can be accessed via .model_extra
|
||||
@json_schema_type
|
||||
class OpenAIChatCompletionRequest(BaseModel):
|
||||
class OpenAIChatCompletionRequestWithExtraBody(BaseModel, extra="allow"):
|
||||
"""Request parameters for OpenAI-compatible chat completion endpoint.
|
||||
|
||||
:param model: The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint.
|
||||
|
|
@ -1120,8 +1112,6 @@ class OpenAIChatCompletionRequest(BaseModel):
|
|||
:param user: (Optional) The user to use.
|
||||
"""
|
||||
|
||||
model_config = ConfigDict(extra="allow")
|
||||
|
||||
# Standard OpenAI chat completion parameters
|
||||
model: str
|
||||
messages: Annotated[list[OpenAIMessageParam], Field(..., min_length=1)]
|
||||
|
|
@ -1182,7 +1172,7 @@ class InferenceProvider(Protocol):
|
|||
@webmethod(route="/completions", method="POST", level=LLAMA_STACK_API_V1)
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: Annotated[OpenAICompletionRequest, Body(...)],
|
||||
params: Annotated[OpenAICompletionRequestWithExtraBody, Body(...)],
|
||||
) -> OpenAICompletion:
|
||||
"""Create completion.
|
||||
|
||||
|
|
@ -1195,7 +1185,7 @@ class InferenceProvider(Protocol):
|
|||
@webmethod(route="/chat/completions", method="POST", level=LLAMA_STACK_API_V1)
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: Annotated[OpenAIChatCompletionRequest, Body(...)],
|
||||
params: Annotated[OpenAIChatCompletionRequestWithExtraBody, Body(...)],
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
"""Create chat completions.
|
||||
|
||||
|
|
|
|||
|
|
@ -32,13 +32,13 @@ from llama_stack.apis.inference import (
|
|||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionChunk,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAIChatCompletionToolCall,
|
||||
OpenAIChatCompletionToolCallFunction,
|
||||
OpenAIChoice,
|
||||
OpenAIChoiceLogprobs,
|
||||
OpenAICompletion,
|
||||
OpenAICompletionRequest,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
OpenAICompletionWithInputMessages,
|
||||
OpenAIEmbeddingsResponse,
|
||||
OpenAIMessageParam,
|
||||
|
|
@ -183,7 +183,7 @@ class InferenceRouter(Inference):
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: Annotated[OpenAICompletionRequest, Body(...)],
|
||||
params: Annotated[OpenAICompletionRequestWithExtraBody, Body(...)],
|
||||
) -> OpenAICompletion:
|
||||
logger.debug(
|
||||
f"InferenceRouter.openai_completion: model={params.model}, stream={params.stream}, prompt={params.prompt}",
|
||||
|
|
@ -218,7 +218,7 @@ class InferenceRouter(Inference):
|
|||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: Annotated[OpenAIChatCompletionRequest, Body(...)],
|
||||
params: Annotated[OpenAIChatCompletionRequestWithExtraBody, Body(...)],
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
logger.debug(
|
||||
f"InferenceRouter.openai_chat_completion: model={params.model}, stream={params.stream}, messages={params.messages}",
|
||||
|
|
@ -317,7 +317,7 @@ class InferenceRouter(Inference):
|
|||
raise NotImplementedError("Get chat completion is not supported: inference store is not configured.")
|
||||
|
||||
async def _nonstream_openai_chat_completion(
|
||||
self, provider: Inference, params: OpenAIChatCompletionRequest
|
||||
self, provider: Inference, params: OpenAIChatCompletionRequestWithExtraBody
|
||||
) -> OpenAIChatCompletion:
|
||||
response = await provider.openai_chat_completion(params)
|
||||
for choice in response.choices:
|
||||
|
|
|
|||
|
|
@ -49,7 +49,7 @@ from llama_stack.apis.inference import (
|
|||
Inference,
|
||||
Message,
|
||||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAIDeveloperMessageParam,
|
||||
OpenAIMessageParam,
|
||||
OpenAISystemMessageParam,
|
||||
|
|
@ -583,7 +583,7 @@ class ChatAgent(ShieldRunnerMixin):
|
|||
max_tokens = getattr(sampling_params, "max_tokens", None)
|
||||
|
||||
# Use OpenAI chat completion
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=self.agent_config.model,
|
||||
messages=openai_messages,
|
||||
tools=openai_tools if openai_tools else None,
|
||||
|
|
|
|||
|
|
@ -49,7 +49,7 @@ from llama_stack.apis.inference import (
|
|||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionChunk,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAIChatCompletionToolCall,
|
||||
OpenAIChoice,
|
||||
OpenAIMessageParam,
|
||||
|
|
@ -169,7 +169,7 @@ class StreamingResponseOrchestrator:
|
|||
# (some providers don't support non-empty response_format when tools are present)
|
||||
response_format = None if self.ctx.response_format.type == "text" else self.ctx.response_format
|
||||
logger.debug(f"calling openai_chat_completion with tools: {self.ctx.chat_tools}")
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=self.ctx.model,
|
||||
messages=messages,
|
||||
tools=self.ctx.chat_tools,
|
||||
|
|
|
|||
|
|
@ -22,8 +22,8 @@ from llama_stack.apis.files import Files, OpenAIFilePurpose
|
|||
from llama_stack.apis.inference import (
|
||||
Inference,
|
||||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAICompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
OpenAIDeveloperMessageParam,
|
||||
OpenAIMessageParam,
|
||||
OpenAISystemMessageParam,
|
||||
|
|
@ -608,7 +608,7 @@ class ReferenceBatchesImpl(Batches):
|
|||
# TODO(SECURITY): review body for security issues
|
||||
if request.url == "/v1/chat/completions":
|
||||
request.body["messages"] = [convert_to_openai_message_param(msg) for msg in request.body["messages"]]
|
||||
chat_params = OpenAIChatCompletionRequest(**request.body)
|
||||
chat_params = OpenAIChatCompletionRequestWithExtraBody(**request.body)
|
||||
chat_response = await self.inference_api.openai_chat_completion(chat_params)
|
||||
|
||||
# this is for mypy, we don't allow streaming so we'll get the right type
|
||||
|
|
@ -623,7 +623,7 @@ class ReferenceBatchesImpl(Batches):
|
|||
},
|
||||
}
|
||||
elif request.url == "/v1/completions":
|
||||
completion_params = OpenAICompletionRequest(**request.body)
|
||||
completion_params = OpenAICompletionRequestWithExtraBody(**request.body)
|
||||
completion_response = await self.inference_api.openai_completion(completion_params)
|
||||
|
||||
# this is for mypy, we don't allow streaming so we'll get the right type
|
||||
|
|
|
|||
|
|
@ -14,8 +14,8 @@ from llama_stack.apis.datasetio import DatasetIO
|
|||
from llama_stack.apis.datasets import Datasets
|
||||
from llama_stack.apis.inference import (
|
||||
Inference,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAICompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
OpenAISystemMessageParam,
|
||||
OpenAIUserMessageParam,
|
||||
UserMessage,
|
||||
|
|
@ -175,7 +175,7 @@ class MetaReferenceEvalImpl(
|
|||
sampling_params["stop"] = candidate.sampling_params.stop
|
||||
|
||||
input_content = json.loads(x[ColumnName.completion_input.value])
|
||||
params = OpenAICompletionRequest(
|
||||
params = OpenAICompletionRequestWithExtraBody(
|
||||
model=candidate.model,
|
||||
prompt=input_content,
|
||||
**sampling_params,
|
||||
|
|
@ -195,7 +195,7 @@ class MetaReferenceEvalImpl(
|
|||
messages += [OpenAISystemMessageParam(**x) for x in chat_completion_input_json if x["role"] == "system"]
|
||||
|
||||
messages += input_messages
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=candidate.model,
|
||||
messages=messages,
|
||||
**sampling_params,
|
||||
|
|
|
|||
|
|
@ -9,8 +9,8 @@ from collections.abc import AsyncIterator
|
|||
|
||||
from llama_stack.apis.inference import (
|
||||
InferenceProvider,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAICompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
)
|
||||
from llama_stack.apis.inference.inference import (
|
||||
OpenAIChatCompletion,
|
||||
|
|
@ -67,7 +67,7 @@ class MetaReferenceInferenceImpl(
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: OpenAICompletionRequest,
|
||||
params: OpenAICompletionRequestWithExtraBody,
|
||||
) -> OpenAICompletion:
|
||||
raise NotImplementedError("OpenAI completion not supported by meta reference provider")
|
||||
|
||||
|
|
@ -153,6 +153,6 @@ class MetaReferenceInferenceImpl(
|
|||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: OpenAIChatCompletionRequest,
|
||||
params: OpenAIChatCompletionRequestWithExtraBody,
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
raise NotImplementedError("OpenAI chat completion not supported by meta-reference inference provider")
|
||||
|
|
|
|||
|
|
@ -8,8 +8,8 @@ from collections.abc import AsyncIterator
|
|||
|
||||
from llama_stack.apis.inference import (
|
||||
InferenceProvider,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAICompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
)
|
||||
from llama_stack.apis.inference.inference import (
|
||||
OpenAIChatCompletion,
|
||||
|
|
@ -72,12 +72,12 @@ class SentenceTransformersInferenceImpl(
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: OpenAICompletionRequest,
|
||||
params: OpenAICompletionRequestWithExtraBody,
|
||||
) -> OpenAICompletion:
|
||||
raise NotImplementedError("OpenAI completion not supported by sentence transformers provider")
|
||||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: OpenAIChatCompletionRequest,
|
||||
params: OpenAIChatCompletionRequestWithExtraBody,
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
raise NotImplementedError("OpenAI chat completion not supported by sentence transformers provider")
|
||||
|
|
|
|||
|
|
@ -13,7 +13,7 @@ from llama_stack.apis.common.content_types import ImageContentItem, TextContentI
|
|||
from llama_stack.apis.inference import (
|
||||
Inference,
|
||||
Message,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAIUserMessageParam,
|
||||
UserMessage,
|
||||
)
|
||||
|
|
@ -296,7 +296,7 @@ class LlamaGuardShield:
|
|||
else:
|
||||
shield_input_message = self.build_text_shield_input(messages)
|
||||
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=self.model,
|
||||
messages=[shield_input_message],
|
||||
stream=False,
|
||||
|
|
@ -384,7 +384,7 @@ class LlamaGuardShield:
|
|||
# TODO: Add Image based support for OpenAI Moderations
|
||||
shield_input_message = self.build_text_shield_input(messages)
|
||||
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=self.model,
|
||||
messages=[shield_input_message],
|
||||
stream=False,
|
||||
|
|
|
|||
|
|
@ -6,7 +6,7 @@
|
|||
import re
|
||||
from typing import Any
|
||||
|
||||
from llama_stack.apis.inference import Inference, OpenAIChatCompletionRequest
|
||||
from llama_stack.apis.inference import Inference, OpenAIChatCompletionRequestWithExtraBody
|
||||
from llama_stack.apis.scoring import ScoringResultRow
|
||||
from llama_stack.apis.scoring_functions import ScoringFnParams
|
||||
from llama_stack.providers.utils.scoring.base_scoring_fn import RegisteredBaseScoringFn
|
||||
|
|
@ -55,7 +55,7 @@ class LlmAsJudgeScoringFn(RegisteredBaseScoringFn):
|
|||
generated_answer=generated_answer,
|
||||
)
|
||||
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=fn_def.params.judge_model,
|
||||
messages=[
|
||||
{
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@
|
|||
from jinja2 import Template
|
||||
|
||||
from llama_stack.apis.common.content_types import InterleavedContent
|
||||
from llama_stack.apis.inference import OpenAIChatCompletionRequest, OpenAIUserMessageParam
|
||||
from llama_stack.apis.inference import OpenAIChatCompletionRequestWithExtraBody, OpenAIUserMessageParam
|
||||
from llama_stack.apis.tools.rag_tool import (
|
||||
DefaultRAGQueryGeneratorConfig,
|
||||
LLMRAGQueryGeneratorConfig,
|
||||
|
|
@ -65,7 +65,7 @@ async def llm_rag_query_generator(
|
|||
|
||||
model = config.model
|
||||
message = OpenAIUserMessageParam(content=rendered_content)
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=model,
|
||||
messages=[message],
|
||||
stream=False,
|
||||
|
|
|
|||
|
|
@ -12,8 +12,8 @@ from botocore.client import BaseClient
|
|||
from llama_stack.apis.inference import (
|
||||
ChatCompletionRequest,
|
||||
Inference,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAICompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
OpenAIEmbeddingsResponse,
|
||||
)
|
||||
from llama_stack.apis.inference.inference import (
|
||||
|
|
@ -134,12 +134,12 @@ class BedrockInferenceAdapter(
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: OpenAICompletionRequest,
|
||||
params: OpenAICompletionRequestWithExtraBody,
|
||||
) -> OpenAICompletion:
|
||||
raise NotImplementedError("OpenAI completion not supported by the Bedrock provider")
|
||||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: OpenAIChatCompletionRequest,
|
||||
params: OpenAIChatCompletionRequestWithExtraBody,
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
raise NotImplementedError("OpenAI chat completion not supported by the Bedrock provider")
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@ from collections.abc import Iterable
|
|||
|
||||
from databricks.sdk import WorkspaceClient
|
||||
|
||||
from llama_stack.apis.inference import OpenAICompletion, OpenAICompletionRequest
|
||||
from llama_stack.apis.inference import OpenAICompletion, OpenAICompletionRequestWithExtraBody
|
||||
from llama_stack.log import get_logger
|
||||
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
|
||||
|
||||
|
|
@ -39,6 +39,6 @@ class DatabricksInferenceAdapter(OpenAIMixin):
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: OpenAICompletionRequest,
|
||||
params: OpenAICompletionRequestWithExtraBody,
|
||||
) -> OpenAICompletion:
|
||||
raise NotImplementedError()
|
||||
|
|
|
|||
|
|
@ -3,7 +3,12 @@
|
|||
#
|
||||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
from llama_stack.apis.inference.inference import OpenAICompletion, OpenAICompletionRequest, OpenAIEmbeddingsResponse
|
||||
|
||||
from llama_stack.apis.inference.inference import (
|
||||
OpenAICompletion,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
OpenAIEmbeddingsResponse,
|
||||
)
|
||||
from llama_stack.log import get_logger
|
||||
from llama_stack.providers.remote.inference.llama_openai_compat.config import LlamaCompatConfig
|
||||
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
|
||||
|
|
@ -29,7 +34,7 @@ class LlamaCompatInferenceAdapter(OpenAIMixin):
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: OpenAICompletionRequest,
|
||||
params: OpenAICompletionRequestWithExtraBody,
|
||||
) -> OpenAICompletion:
|
||||
raise NotImplementedError()
|
||||
|
||||
|
|
|
|||
|
|
@ -13,9 +13,9 @@ from llama_stack.apis.inference import (
|
|||
Inference,
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionChunk,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAICompletion,
|
||||
OpenAICompletionRequest,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
OpenAIEmbeddingsResponse,
|
||||
)
|
||||
from llama_stack.apis.models import Model
|
||||
|
|
@ -79,7 +79,7 @@ class PassthroughInferenceAdapter(Inference):
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: OpenAICompletionRequest,
|
||||
params: OpenAICompletionRequestWithExtraBody,
|
||||
) -> OpenAICompletion:
|
||||
client = self._get_client()
|
||||
model_obj = await self.model_store.get_model(params.model)
|
||||
|
|
@ -93,7 +93,7 @@ class PassthroughInferenceAdapter(Inference):
|
|||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: OpenAIChatCompletionRequest,
|
||||
params: OpenAIChatCompletionRequestWithExtraBody,
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
client = self._get_client()
|
||||
model_obj = await self.model_store.get_model(params.model)
|
||||
|
|
|
|||
|
|
@ -9,7 +9,7 @@ from collections.abc import AsyncIterator
|
|||
from llama_stack.apis.inference import (
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionChunk,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
)
|
||||
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
|
||||
|
||||
|
|
@ -31,7 +31,7 @@ class RunpodInferenceAdapter(OpenAIMixin):
|
|||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: OpenAIChatCompletionRequest,
|
||||
params: OpenAIChatCompletionRequestWithExtraBody,
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
"""Override to add RunPod-specific stream_options requirement."""
|
||||
params = params.model_copy()
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ from pydantic import ConfigDict
|
|||
|
||||
from llama_stack.apis.inference import (
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
ToolChoice,
|
||||
)
|
||||
from llama_stack.log import get_logger
|
||||
|
|
@ -93,7 +93,7 @@ class VLLMInferenceAdapter(OpenAIMixin):
|
|||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: OpenAIChatCompletionRequest,
|
||||
params: OpenAIChatCompletionRequestWithExtraBody,
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
params = params.model_copy()
|
||||
|
||||
|
|
|
|||
|
|
@ -16,9 +16,9 @@ from llama_stack.apis.inference import (
|
|||
JsonSchemaResponseFormat,
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionChunk,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAICompletion,
|
||||
OpenAICompletionRequest,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
OpenAIEmbeddingData,
|
||||
OpenAIEmbeddingsResponse,
|
||||
OpenAIEmbeddingUsage,
|
||||
|
|
@ -226,7 +226,7 @@ class LiteLLMOpenAIMixin(
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: OpenAICompletionRequest,
|
||||
params: OpenAICompletionRequestWithExtraBody,
|
||||
) -> OpenAICompletion:
|
||||
model_obj = await self.model_store.get_model(params.model)
|
||||
|
||||
|
|
@ -248,8 +248,6 @@ class LiteLLMOpenAIMixin(
|
|||
temperature=params.temperature,
|
||||
top_p=params.top_p,
|
||||
user=params.user,
|
||||
guided_choice=params.guided_choice,
|
||||
prompt_logprobs=params.prompt_logprobs,
|
||||
suffix=params.suffix,
|
||||
api_key=self.get_api_key(),
|
||||
api_base=self.api_base,
|
||||
|
|
@ -258,7 +256,7 @@ class LiteLLMOpenAIMixin(
|
|||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: OpenAIChatCompletionRequest,
|
||||
params: OpenAIChatCompletionRequestWithExtraBody,
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
# Add usage tracking for streaming when telemetry is active
|
||||
from llama_stack.providers.utils.telemetry.tracing import get_current_span
|
||||
|
|
|
|||
|
|
@ -17,9 +17,9 @@ from llama_stack.apis.inference import (
|
|||
Model,
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionChunk,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAICompletion,
|
||||
OpenAICompletionRequest,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
OpenAIEmbeddingData,
|
||||
OpenAIEmbeddingsResponse,
|
||||
OpenAIEmbeddingUsage,
|
||||
|
|
@ -223,21 +223,11 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
|
|||
|
||||
async def openai_completion(
|
||||
self,
|
||||
params: OpenAICompletionRequest,
|
||||
params: OpenAICompletionRequestWithExtraBody,
|
||||
) -> OpenAICompletion:
|
||||
"""
|
||||
Direct OpenAI completion API call.
|
||||
"""
|
||||
# Handle parameters that are not supported by OpenAI API, but may be by the provider
|
||||
# prompt_logprobs is supported by vLLM
|
||||
# guided_choice is supported by vLLM
|
||||
# TODO: test coverage
|
||||
extra_body: dict[str, Any] = {}
|
||||
if params.prompt_logprobs is not None and params.prompt_logprobs >= 0:
|
||||
extra_body["prompt_logprobs"] = params.prompt_logprobs
|
||||
if params.guided_choice:
|
||||
extra_body["guided_choice"] = params.guided_choice
|
||||
|
||||
# TODO: fix openai_completion to return type compatible with OpenAI's API response
|
||||
completion_kwargs = await prepare_openai_completion_params(
|
||||
model=await self._get_provider_model_id(params.model),
|
||||
|
|
@ -259,13 +249,15 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
|
|||
user=params.user,
|
||||
suffix=params.suffix,
|
||||
)
|
||||
resp = await self.client.completions.create(**completion_kwargs, extra_body=extra_body)
|
||||
if extra_body := params.model_extra:
|
||||
completion_kwargs["extra_body"] = extra_body
|
||||
resp = await self.client.completions.create(**completion_kwargs)
|
||||
|
||||
return await self._maybe_overwrite_id(resp, params.stream) # type: ignore[no-any-return]
|
||||
|
||||
async def openai_chat_completion(
|
||||
self,
|
||||
params: OpenAIChatCompletionRequest,
|
||||
params: OpenAIChatCompletionRequestWithExtraBody,
|
||||
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
|
||||
"""
|
||||
Direct OpenAI chat completion API call.
|
||||
|
|
@ -316,6 +308,8 @@ class OpenAIMixin(NeedsRequestProviderData, ABC, BaseModel):
|
|||
user=params.user,
|
||||
)
|
||||
|
||||
if extra_body := params.model_extra:
|
||||
request_params["extra_body"] = extra_body
|
||||
resp = await self.client.chat.completions.create(**request_params)
|
||||
|
||||
return await self._maybe_overwrite_id(resp, params.stream) # type: ignore[no-any-return]
|
||||
|
|
|
|||
|
|
@ -0,0 +1,44 @@
|
|||
{
|
||||
"test_id": "tests/integration/batches/test_batches.py::TestBatchesIntegration::test_batch_e2e_completions[txt=ollama/llama3.2:3b-instruct-fp16]",
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "http://0.0.0.0:11434/v1/v1/completions",
|
||||
"headers": {},
|
||||
"body": {
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"prompt": "Say completions",
|
||||
"max_tokens": 20
|
||||
},
|
||||
"endpoint": "/v1/completions",
|
||||
"model": "llama3.2:3b-instruct-fp16"
|
||||
},
|
||||
"response": {
|
||||
"body": {
|
||||
"__type__": "openai.types.completion.Completion",
|
||||
"__data__": {
|
||||
"id": "rec-92d49675c903",
|
||||
"choices": [
|
||||
{
|
||||
"finish_reason": "length",
|
||||
"index": 0,
|
||||
"logprobs": null,
|
||||
"text": "What would you like me to say completion about? Would you like me to complete a thought, finish"
|
||||
}
|
||||
],
|
||||
"created": 0,
|
||||
"model": "llama3.2:3b-instruct-fp16",
|
||||
"object": "text_completion",
|
||||
"system_fingerprint": "fp_ollama",
|
||||
"usage": {
|
||||
"completion_tokens": 20,
|
||||
"prompt_tokens": 28,
|
||||
"total_tokens": 48,
|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
}
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -0,0 +1,881 @@
|
|||
{
|
||||
"test_id": null,
|
||||
"request": {
|
||||
"method": "POST",
|
||||
"url": "https://api.openai.com/v1/v1/models",
|
||||
"headers": {},
|
||||
"body": {},
|
||||
"endpoint": "/v1/models",
|
||||
"model": ""
|
||||
},
|
||||
"response": {
|
||||
"body": [
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4-0613",
|
||||
"created": 1686588896,
|
||||
"object": "model",
|
||||
"owned_by": "openai"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4",
|
||||
"created": 1687882411,
|
||||
"object": "model",
|
||||
"owned_by": "openai"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-3.5-turbo",
|
||||
"created": 1677610602,
|
||||
"object": "model",
|
||||
"owned_by": "openai"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "sora-2-pro",
|
||||
"created": 1759708663,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-audio-mini-2025-10-06",
|
||||
"created": 1759512137,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-realtime-mini",
|
||||
"created": 1759517133,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-realtime-mini-2025-10-06",
|
||||
"created": 1759517175,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "sora-2",
|
||||
"created": 1759708615,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "davinci-002",
|
||||
"created": 1692634301,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "babbage-002",
|
||||
"created": 1692634615,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-3.5-turbo-instruct",
|
||||
"created": 1692901427,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-3.5-turbo-instruct-0914",
|
||||
"created": 1694122472,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "dall-e-3",
|
||||
"created": 1698785189,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "dall-e-2",
|
||||
"created": 1698798177,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4-1106-preview",
|
||||
"created": 1698957206,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-3.5-turbo-1106",
|
||||
"created": 1698959748,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "tts-1-hd",
|
||||
"created": 1699046015,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "tts-1-1106",
|
||||
"created": 1699053241,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "tts-1-hd-1106",
|
||||
"created": 1699053533,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "text-embedding-3-small",
|
||||
"created": 1705948997,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "text-embedding-3-large",
|
||||
"created": 1705953180,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4-0125-preview",
|
||||
"created": 1706037612,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4-turbo-preview",
|
||||
"created": 1706037777,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-3.5-turbo-0125",
|
||||
"created": 1706048358,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4-turbo",
|
||||
"created": 1712361441,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4-turbo-2024-04-09",
|
||||
"created": 1712601677,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4o",
|
||||
"created": 1715367049,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4o-2024-05-13",
|
||||
"created": 1715368132,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4o-mini-2024-07-18",
|
||||
"created": 1721172717,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4o-mini",
|
||||
"created": 1721172741,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "gpt-4o-2024-08-06",
|
||||
"created": 1722814719,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
}
|
||||
},
|
||||
{
|
||||
"__type__": "openai.types.model.Model",
|
||||
"__data__": {
|
||||
"id": "chatgpt-4o-latest",
|
||||
"created": 1723515131,
|
||||
"object": "model",
|
||||
"owned_by": "system"
|
||||
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|
||||
"completion_tokens_details": null,
|
||||
"prompt_tokens_details": null
|
||||
}
|
||||
}
|
||||
},
|
||||
"is_streaming": false
|
||||
},
|
||||
"id_normalization_mapping": {}
|
||||
}
|
||||
|
|
@ -223,7 +223,7 @@ def test_openai_completion_guided_choice(llama_stack_client, client_with_models,
|
|||
model=text_model_id,
|
||||
prompt=prompt,
|
||||
stream=False,
|
||||
guided_choice=["joy", "sadness"],
|
||||
extra_body={"guided_choice": ["joy", "sadness"]},
|
||||
)
|
||||
assert len(response.choices) > 0
|
||||
choice = response.choices[0]
|
||||
|
|
|
|||
|
|
@ -33,7 +33,7 @@ from llama_stack.apis.agents.openai_responses import (
|
|||
from llama_stack.apis.inference import (
|
||||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletionContentPartTextParam,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAIDeveloperMessageParam,
|
||||
OpenAIJSONSchema,
|
||||
OpenAIResponseFormatJSONObject,
|
||||
|
|
@ -162,7 +162,7 @@ async def test_create_openai_response_with_string_input(openai_responses_impl, m
|
|||
chunks = [chunk async for chunk in result]
|
||||
|
||||
mock_inference_api.openai_chat_completion.assert_called_once_with(
|
||||
OpenAIChatCompletionRequest(
|
||||
OpenAIChatCompletionRequestWithExtraBody(
|
||||
model=model,
|
||||
messages=[OpenAIUserMessageParam(role="user", content="What is the capital of Ireland?", name=None)],
|
||||
response_format=None,
|
||||
|
|
|
|||
|
|
@ -13,11 +13,16 @@ import pytest
|
|||
from llama_stack.apis.inference import (
|
||||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletion,
|
||||
OpenAIChatCompletionRequest,
|
||||
OpenAIChatCompletionRequestWithExtraBody,
|
||||
OpenAIChoice,
|
||||
OpenAICompletion,
|
||||
OpenAICompletionChoice,
|
||||
OpenAICompletionRequestWithExtraBody,
|
||||
ToolChoice,
|
||||
)
|
||||
from llama_stack.apis.models import Model
|
||||
from llama_stack.core.routers.inference import InferenceRouter
|
||||
from llama_stack.core.routing_tables.models import ModelsRoutingTable
|
||||
from llama_stack.providers.datatypes import HealthStatus
|
||||
from llama_stack.providers.remote.inference.vllm.config import VLLMInferenceAdapterConfig
|
||||
from llama_stack.providers.remote.inference.vllm.vllm import VLLMInferenceAdapter
|
||||
|
|
@ -57,7 +62,7 @@ async def test_old_vllm_tool_choice(vllm_inference_adapter):
|
|||
mock_client_property.return_value = mock_client
|
||||
|
||||
# No tools but auto tool choice
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model="mock-model",
|
||||
messages=[{"role": "user", "content": "test"}],
|
||||
stream=False,
|
||||
|
|
@ -173,7 +178,7 @@ async def test_openai_chat_completion_is_async(vllm_inference_adapter):
|
|||
)
|
||||
|
||||
async def do_inference():
|
||||
params = OpenAIChatCompletionRequest(
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model="mock-model",
|
||||
messages=[{"role": "user", "content": "one fish two fish"}],
|
||||
stream=False,
|
||||
|
|
@ -191,3 +196,148 @@ async def test_openai_chat_completion_is_async(vllm_inference_adapter):
|
|||
|
||||
assert mock_create_client.call_count == 4 # no cheating
|
||||
assert total_time < (sleep_time * 2), f"Total time taken: {total_time}s exceeded expected max"
|
||||
|
||||
|
||||
async def test_vllm_completion_extra_body():
|
||||
"""
|
||||
Test that vLLM-specific guided_choice and prompt_logprobs parameters are correctly forwarded
|
||||
via extra_body to the underlying OpenAI client through the InferenceRouter.
|
||||
"""
|
||||
# Set up the vLLM adapter
|
||||
config = VLLMInferenceAdapterConfig(url="http://mocked.localhost:12345")
|
||||
vllm_adapter = VLLMInferenceAdapter(config=config)
|
||||
vllm_adapter.__provider_id__ = "vllm"
|
||||
await vllm_adapter.initialize()
|
||||
|
||||
# Create a mock model store
|
||||
mock_model_store = AsyncMock()
|
||||
mock_model = Model(identifier="mock-model", provider_resource_id="mock-model", provider_id="vllm")
|
||||
mock_model_store.get_model.return_value = mock_model
|
||||
mock_model_store.has_model.return_value = True
|
||||
|
||||
# Create a mock dist_registry
|
||||
mock_dist_registry = MagicMock()
|
||||
mock_dist_registry.get = AsyncMock(return_value=mock_model)
|
||||
mock_dist_registry.set = AsyncMock()
|
||||
|
||||
# Set up the routing table
|
||||
routing_table = ModelsRoutingTable(
|
||||
impls_by_provider_id={"vllm": vllm_adapter},
|
||||
dist_registry=mock_dist_registry,
|
||||
policy=[],
|
||||
)
|
||||
# Inject the model store into the adapter
|
||||
vllm_adapter.model_store = routing_table
|
||||
|
||||
# Create the InferenceRouter
|
||||
router = InferenceRouter(routing_table=routing_table)
|
||||
|
||||
# Patch the OpenAI client
|
||||
with patch.object(VLLMInferenceAdapter, "client", new_callable=PropertyMock) as mock_client_property:
|
||||
mock_client = MagicMock()
|
||||
mock_client.completions.create = AsyncMock(
|
||||
return_value=OpenAICompletion(
|
||||
id="cmpl-abc123",
|
||||
created=1,
|
||||
model="mock-model",
|
||||
choices=[
|
||||
OpenAICompletionChoice(
|
||||
text="joy",
|
||||
finish_reason="stop",
|
||||
index=0,
|
||||
)
|
||||
],
|
||||
)
|
||||
)
|
||||
mock_client_property.return_value = mock_client
|
||||
|
||||
# Test with guided_choice and prompt_logprobs as extra fields
|
||||
params = OpenAICompletionRequestWithExtraBody(
|
||||
model="mock-model",
|
||||
prompt="I am feeling happy",
|
||||
stream=False,
|
||||
guided_choice=["joy", "sadness"],
|
||||
prompt_logprobs=5,
|
||||
)
|
||||
await router.openai_completion(params)
|
||||
|
||||
# Verify that the client was called with extra_body containing both parameters
|
||||
mock_client.completions.create.assert_called_once()
|
||||
call_kwargs = mock_client.completions.create.call_args.kwargs
|
||||
assert "extra_body" in call_kwargs
|
||||
assert "guided_choice" in call_kwargs["extra_body"]
|
||||
assert call_kwargs["extra_body"]["guided_choice"] == ["joy", "sadness"]
|
||||
assert "prompt_logprobs" in call_kwargs["extra_body"]
|
||||
assert call_kwargs["extra_body"]["prompt_logprobs"] == 5
|
||||
|
||||
|
||||
async def test_vllm_chat_completion_extra_body():
|
||||
"""
|
||||
Test that vLLM-specific parameters (e.g., chat_template_kwargs) are correctly forwarded
|
||||
via extra_body to the underlying OpenAI client through the InferenceRouter for chat completion.
|
||||
"""
|
||||
# Set up the vLLM adapter
|
||||
config = VLLMInferenceAdapterConfig(url="http://mocked.localhost:12345")
|
||||
vllm_adapter = VLLMInferenceAdapter(config=config)
|
||||
vllm_adapter.__provider_id__ = "vllm"
|
||||
await vllm_adapter.initialize()
|
||||
|
||||
# Create a mock model store
|
||||
mock_model_store = AsyncMock()
|
||||
mock_model = Model(identifier="mock-model", provider_resource_id="mock-model", provider_id="vllm")
|
||||
mock_model_store.get_model.return_value = mock_model
|
||||
mock_model_store.has_model.return_value = True
|
||||
|
||||
# Create a mock dist_registry
|
||||
mock_dist_registry = MagicMock()
|
||||
mock_dist_registry.get = AsyncMock(return_value=mock_model)
|
||||
mock_dist_registry.set = AsyncMock()
|
||||
|
||||
# Set up the routing table
|
||||
routing_table = ModelsRoutingTable(
|
||||
impls_by_provider_id={"vllm": vllm_adapter},
|
||||
dist_registry=mock_dist_registry,
|
||||
policy=[],
|
||||
)
|
||||
# Inject the model store into the adapter
|
||||
vllm_adapter.model_store = routing_table
|
||||
|
||||
# Create the InferenceRouter
|
||||
router = InferenceRouter(routing_table=routing_table)
|
||||
|
||||
# Patch the OpenAI client
|
||||
with patch.object(VLLMInferenceAdapter, "client", new_callable=PropertyMock) as mock_client_property:
|
||||
mock_client = MagicMock()
|
||||
mock_client.chat.completions.create = AsyncMock(
|
||||
return_value=OpenAIChatCompletion(
|
||||
id="chatcmpl-abc123",
|
||||
created=1,
|
||||
model="mock-model",
|
||||
choices=[
|
||||
OpenAIChoice(
|
||||
message=OpenAIAssistantMessageParam(
|
||||
content="test response",
|
||||
),
|
||||
finish_reason="stop",
|
||||
index=0,
|
||||
)
|
||||
],
|
||||
)
|
||||
)
|
||||
mock_client_property.return_value = mock_client
|
||||
|
||||
# Test with chat_template_kwargs as extra field
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(
|
||||
model="mock-model",
|
||||
messages=[{"role": "user", "content": "test"}],
|
||||
stream=False,
|
||||
chat_template_kwargs={"thinking": True},
|
||||
)
|
||||
await router.openai_chat_completion(params)
|
||||
|
||||
# Verify that the client was called with extra_body containing chat_template_kwargs
|
||||
mock_client.chat.completions.create.assert_called_once()
|
||||
call_kwargs = mock_client.chat.completions.create.call_args.kwargs
|
||||
assert "extra_body" in call_kwargs
|
||||
assert "chat_template_kwargs" in call_kwargs["extra_body"]
|
||||
assert call_kwargs["extra_body"]["chat_template_kwargs"] == {"thinking": True}
|
||||
|
|
|
|||
|
|
@ -12,7 +12,7 @@ from unittest.mock import AsyncMock, MagicMock, Mock, PropertyMock, patch
|
|||
import pytest
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from llama_stack.apis.inference import Model, OpenAIChatCompletionRequest, OpenAIUserMessageParam
|
||||
from llama_stack.apis.inference import Model, OpenAIChatCompletionRequestWithExtraBody, OpenAIUserMessageParam
|
||||
from llama_stack.apis.models import ModelType
|
||||
from llama_stack.core.request_headers import request_provider_data_context
|
||||
from llama_stack.providers.utils.inference.model_registry import RemoteInferenceProviderConfig
|
||||
|
|
@ -271,7 +271,7 @@ class TestOpenAIMixinImagePreprocessing:
|
|||
with patch("llama_stack.providers.utils.inference.openai_mixin.localize_image_content") as mock_localize:
|
||||
mock_localize.return_value = (b"fake_image_data", "jpeg")
|
||||
|
||||
params = OpenAIChatCompletionRequest(model="test-model", messages=[message])
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(model="test-model", messages=[message])
|
||||
await mixin.openai_chat_completion(params)
|
||||
|
||||
mock_localize.assert_called_once_with("http://example.com/image.jpg")
|
||||
|
|
@ -304,7 +304,7 @@ class TestOpenAIMixinImagePreprocessing:
|
|||
|
||||
with patch.object(type(mixin), "client", new_callable=PropertyMock, return_value=mock_client):
|
||||
with patch("llama_stack.providers.utils.inference.openai_mixin.localize_image_content") as mock_localize:
|
||||
params = OpenAIChatCompletionRequest(model="test-model", messages=[message])
|
||||
params = OpenAIChatCompletionRequestWithExtraBody(model="test-model", messages=[message])
|
||||
await mixin.openai_chat_completion(params)
|
||||
|
||||
mock_localize.assert_not_called()
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue