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https://github.com/Memo-2023/mana-monorepo.git
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1495dbe476
Python/FastAPI service providing unified OpenAI-compatible API for Ollama and cloud LLM providers (OpenRouter, Groq, Together). Features: - Chat completions with streaming (SSE) - Vision/multimodal support - Embeddings generation - Multi-provider routing (provider/model format) - Prometheus metrics - Optional Redis caching
57 lines
1.6 KiB
Python
57 lines
1.6 KiB
Python
"""Request models for OpenAI-compatible API."""
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from typing import Literal
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from pydantic import BaseModel, Field
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class TextContent(BaseModel):
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"""Text content in a message."""
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type: Literal["text"] = "text"
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text: str
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class ImageUrl(BaseModel):
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"""Image URL reference."""
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url: str # Can be http(s):// or data:image/...;base64,...
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class ImageContent(BaseModel):
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"""Image content in a message."""
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type: Literal["image_url"] = "image_url"
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image_url: ImageUrl
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MessageContent = str | list[TextContent | ImageContent]
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class Message(BaseModel):
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"""A single message in the conversation."""
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role: Literal["system", "user", "assistant"]
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content: MessageContent
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class ChatCompletionRequest(BaseModel):
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"""Request body for chat completions endpoint."""
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model: str = Field(..., description="Model identifier in format 'provider/model' or just 'model'")
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messages: list[Message] = Field(..., min_length=1)
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stream: bool = False
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temperature: float | None = Field(default=None, ge=0.0, le=2.0)
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max_tokens: int | None = Field(default=None, gt=0)
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top_p: float | None = Field(default=None, ge=0.0, le=1.0)
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frequency_penalty: float | None = Field(default=None, ge=-2.0, le=2.0)
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presence_penalty: float | None = Field(default=None, ge=-2.0, le=2.0)
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stop: str | list[str] | None = None
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class EmbeddingRequest(BaseModel):
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"""Request body for embeddings endpoint."""
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model: str = Field(..., description="Model identifier")
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input: str | list[str] = Field(..., description="Text(s) to embed")
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encoding_format: Literal["float", "base64"] = "float"
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