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Update llama_types and names to match openai api
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‎llama_cpp/llama_types.py

+80-19
Original file line numberDiff line numberDiff line change
@@ -1,3 +1,9 @@
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"""Types and request signatrues for OpenAI compatibility
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Based on the OpenAI OpenAPI specification:
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https://github.com/openai/openai-openapi/blob/master/openapi.yaml
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"""
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from typing import Any, List, Optional, Dict, Union
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from typing_extensions import TypedDict, NotRequired, Literal
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@@ -7,16 +13,19 @@ class EmbeddingUsage(TypedDict):
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total_tokens: int
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class EmbeddingData(TypedDict):
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class Embedding(TypedDict):
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index: int
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object: str
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embedding: List[float]
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class Embedding(TypedDict):
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EmbeddingData = Embedding
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class CreateEmbeddingResponse(TypedDict):
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object: Literal["list"]
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model: str
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data: List[EmbeddingData]
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data: List[Embedding]
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usage: EmbeddingUsage
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@@ -31,7 +40,7 @@ class CompletionChoice(TypedDict):
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text: str
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index: int
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logprobs: Optional[CompletionLogprobs]
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finish_reason: Optional[str]
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finish_reason: Optional[Literal["stop", "length"]]
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class CompletionUsage(TypedDict):
@@ -40,15 +49,18 @@ class CompletionUsage(TypedDict):
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total_tokens: int
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class CompletionChunk(TypedDict):
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class CreateCompletionStreamResponse(TypedDict):
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id: str
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object: Literal["text_completion"]
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created: int
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model: str
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choices: List[CompletionChoice]
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class Completion(TypedDict):
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CompletionChunk = CreateCompletionStreamResponse
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class CreateCompletionResponse(TypedDict):
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id: str
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object: Literal["text_completion"]
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created: int
@@ -57,29 +69,43 @@ class Completion(TypedDict):
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usage: CompletionUsage
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class ChatCompletionMessage(TypedDict):
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role: Literal["assistant", "user", "system"]
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content: str
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Completion = CreateCompletionResponse
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class ChatCompletionFunctionCall(TypedDict):
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name: str
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arguments: str
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class ChatCompletionResponseMessage(TypedDict):
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role: Literal["assistant", "user", "system", "function"]
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content: Optional[str]
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user: NotRequired[str]
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function_call: NotRequired[ChatCompletionFunctionCall]
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ChatCompletionMessage = ChatCompletionResponseMessage
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class ChatCompletionFunction(TypedDict):
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class ChatCompletionResponseFunction(TypedDict):
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name: str
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description: NotRequired[str]
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parameters: Dict[str, Any] # TODO: make this more specific
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class ChatCompletionFunctionCall(TypedDict):
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name: str
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ChatCompletionFunction = ChatCompletionResponseFunction
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class ChatCompletionChoice(TypedDict):
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class ChatCompletionResponseChoice(TypedDict):
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index: int
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message: ChatCompletionMessage
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finish_reason: Optional[str]
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class ChatCompletion(TypedDict):
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ChatCompletionChoice = ChatCompletionResponseChoice
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class CreateChatCompletionResponse(TypedDict):
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id: str
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object: Literal["chat.completion"]
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created: int
@@ -88,24 +114,59 @@ class ChatCompletion(TypedDict):
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usage: CompletionUsage
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class ChatCompletionChunkDeltaEmpty(TypedDict):
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ChatCompletion = CreateChatCompletionResponse
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class ChatCompletionStreamResponseDeltaEmpty(TypedDict):
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pass
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class ChatCompletionChunkDelta(TypedDict):
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ChatCompletionChunkDeltaEmpty = ChatCompletionStreamResponseDeltaEmpty
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class ChatCompletionStreamResponseDelta(TypedDict):
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role: NotRequired[Literal["assistant"]]
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content: NotRequired[str]
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function_call: NotRequired[ChatCompletionFunctionCall]
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ChatCompletionChunkDelta = ChatCompletionStreamResponseDelta
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class ChatCompletionChunkChoice(TypedDict):
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class ChatCompletionStreamResponseChoice(TypedDict):
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index: int
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delta: Union[ChatCompletionChunkDelta, ChatCompletionChunkDeltaEmpty]
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finish_reason: Optional[str]
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finish_reason: Optional[Literal["stop", "length", "function_call"]]
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ChatCompletionChunkChoice = ChatCompletionStreamResponseChoice
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class ChatCompletionChunk(TypedDict):
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class ChatCompletionStreamResponse(TypedDict):
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id: str
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model: str
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object: Literal["chat.completion.chunk"]
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created: int
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choices: List[ChatCompletionChunkChoice]
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ChatCompletionChunk = ChatCompletionStreamResponse
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JsonType = Union[None, int, str, bool, List["JsonType"], Dict[str, "JsonType"]]
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class ChatCompletionFunctions(TypedDict):
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name: str
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description: NotRequired[str]
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parameters: Dict[str, JsonType] # TODO: make this more specific
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class ChatCompletionFunctionCallOption(TypedDict):
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name: str
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class ChatCompletionRequestMessage(TypedDict):
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role: Literal["assistant", "user", "system", "function"]
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content: Optional[str]
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name: NotRequired[str]
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funcion_call: NotRequired[ChatCompletionFunctionCall]

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