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* Implement tool call history keeping * Refactor to match single message implementation * Simplify data representation * Cleanup chat page rendering * Include system message to not break cache * Formatting * Update tests and update .gitignore
62 lines
2.0 KiB
Python
62 lines
2.0 KiB
Python
"""Chat API request models."""
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from typing import Any, Optional
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from pydantic import BaseModel, Field
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class ChatMessage(BaseModel):
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"""A single message in a chat conversation."""
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role: str = Field(
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description="Message role: 'user', 'assistant', 'system', or 'tool'"
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)
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content: Optional[Any] = Field(
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default=None,
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description=(
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"Message content. Usually a string, but may be a multimodal content "
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"list (e.g. text + image_url) or null for assistant turns that only "
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"request tool calls."
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),
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)
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tool_call_id: Optional[str] = Field(
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default=None, description="For tool messages, the ID of the tool call"
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)
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name: Optional[str] = Field(
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default=None, description="For tool messages, the tool name"
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)
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tool_calls: Optional[list[dict[str, Any]]] = Field(
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default=None,
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description=(
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"For assistant messages replayed from prior turns, the OpenAI-format "
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"tool calls the model previously requested. Replaying these verbatim "
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"keeps the conversation prefix byte-for-byte identical so the model "
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"server's prompt cache hits on follow-up turns."
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),
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)
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class ChatCompletionRequest(BaseModel):
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"""Request for chat completion with tool calling."""
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messages: list[ChatMessage] = Field(
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description="List of messages in the conversation"
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)
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max_tool_iterations: int = Field(
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default=5,
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ge=1,
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le=10,
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description="Maximum number of tool call iterations (default: 5)",
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)
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stream: bool = Field(
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default=False,
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description="If true, stream the final assistant response in the body as newline-delimited JSON.",
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)
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enable_thinking: Optional[bool] = Field(
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default=None,
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description=(
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"Per-request thinking toggle. None means use the provider default. "
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"Ignored by providers that do not expose a per-request thinking switch."
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),
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)
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