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combine datatypes.py and endpoints.py into api.py
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30 changed files with 436 additions and 546 deletions
199
llama_toolchain/inference/api/api.py
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199
llama_toolchain/inference/api/api.py
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from enum import Enum
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from typing import List, Literal, Optional, Protocol, Union
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from llama_models.schema_utils import json_schema_type, webmethod
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from pydantic import BaseModel, Field
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from typing_extensions import Annotated
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from llama_models.llama3.api.datatypes import * # noqa: F403
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class LogProbConfig(BaseModel):
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top_k: Optional[int] = 0
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@json_schema_type
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class QuantizationType(Enum):
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bf16 = "bf16"
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fp8 = "fp8"
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@json_schema_type
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class Fp8QuantizationConfig(BaseModel):
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type: Literal[QuantizationType.fp8.value] = QuantizationType.fp8.value
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@json_schema_type
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class Bf16QuantizationConfig(BaseModel):
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type: Literal[QuantizationType.bf16.value] = QuantizationType.bf16.value
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QuantizationConfig = Annotated[
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Union[Bf16QuantizationConfig, Fp8QuantizationConfig],
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Field(discriminator="type"),
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]
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@json_schema_type
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class ChatCompletionResponseEventType(Enum):
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start = "start"
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complete = "complete"
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progress = "progress"
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@json_schema_type
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class ToolCallParseStatus(Enum):
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started = "started"
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in_progress = "in_progress"
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failure = "failure"
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success = "success"
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@json_schema_type
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class ToolCallDelta(BaseModel):
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content: Union[str, ToolCall]
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parse_status: ToolCallParseStatus
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@json_schema_type
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class ChatCompletionResponseEvent(BaseModel):
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"""Chat completion response event."""
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event_type: ChatCompletionResponseEventType
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delta: Union[str, ToolCallDelta]
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logprobs: Optional[List[TokenLogProbs]] = None
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stop_reason: Optional[StopReason] = None
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@json_schema_type
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class CompletionRequest(BaseModel):
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model: str
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content: InterleavedTextMedia
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sampling_params: Optional[SamplingParams] = SamplingParams()
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stream: Optional[bool] = False
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logprobs: Optional[LogProbConfig] = None
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@json_schema_type
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class CompletionResponse(BaseModel):
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completion_message: CompletionMessage
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logprobs: Optional[List[TokenLogProbs]] = None
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@json_schema_type
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class CompletionResponseStreamChunk(BaseModel):
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"""streamed completion response."""
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delta: str
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stop_reason: Optional[StopReason] = None
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logprobs: Optional[List[TokenLogProbs]] = None
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@json_schema_type
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class BatchCompletionRequest(BaseModel):
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model: str
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content_batch: List[InterleavedTextMedia]
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sampling_params: Optional[SamplingParams] = SamplingParams()
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logprobs: Optional[LogProbConfig] = None
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@json_schema_type
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class BatchCompletionResponse(BaseModel):
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completion_message_batch: List[CompletionMessage]
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@json_schema_type
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class ChatCompletionRequest(BaseModel):
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model: str
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messages: List[Message]
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sampling_params: Optional[SamplingParams] = SamplingParams()
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# zero-shot tool definitions as input to the model
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tools: Optional[List[ToolDefinition]] = Field(default_factory=list)
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tool_choice: Optional[ToolChoice] = Field(default=ToolChoice.auto)
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tool_prompt_format: Optional[ToolPromptFormat] = Field(
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default=ToolPromptFormat.json
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)
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stream: Optional[bool] = False
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logprobs: Optional[LogProbConfig] = None
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@json_schema_type
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class ChatCompletionResponseStreamChunk(BaseModel):
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"""SSE-stream of these events."""
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event: ChatCompletionResponseEvent
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@json_schema_type
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class ChatCompletionResponse(BaseModel):
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completion_message: CompletionMessage
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logprobs: Optional[List[TokenLogProbs]] = None
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@json_schema_type
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class BatchChatCompletionRequest(BaseModel):
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model: str
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messages_batch: List[List[Message]]
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sampling_params: Optional[SamplingParams] = SamplingParams()
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# zero-shot tool definitions as input to the model
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tools: Optional[List[ToolDefinition]] = Field(default_factory=list)
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tool_choice: Optional[ToolChoice] = Field(default=ToolChoice.auto)
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tool_prompt_format: Optional[ToolPromptFormat] = Field(
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default=ToolPromptFormat.json
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)
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logprobs: Optional[LogProbConfig] = None
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@json_schema_type
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class BatchChatCompletionResponse(BaseModel):
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completion_message_batch: List[CompletionMessage]
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@json_schema_type
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class EmbeddingsResponse(BaseModel):
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embeddings: List[List[float]]
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class Inference(Protocol):
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@webmethod(route="/inference/completion")
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async def completion(
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self,
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request: CompletionRequest,
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) -> Union[CompletionResponse, CompletionResponseStreamChunk]: ...
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@webmethod(route="/inference/chat_completion")
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async def chat_completion(
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self,
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request: ChatCompletionRequest,
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) -> Union[ChatCompletionResponse, ChatCompletionResponseStreamChunk]: ...
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@webmethod(route="/inference/embeddings")
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async def embeddings(
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self,
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model: str,
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contents: List[InterleavedTextMedia],
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) -> EmbeddingsResponse: ...
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@webmethod(route="/inference/batch_completion")
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async def batch_completion(
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self,
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request: BatchCompletionRequest,
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) -> BatchCompletionResponse: ...
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@webmethod(route="/inference/batch_chat_completion")
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async def batch_chat_completion(
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self,
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request: BatchChatCompletionRequest,
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) -> BatchChatCompletionResponse: ...
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