7ea297231a
* initial commit * Add database migration for compaction_settings field This migration adds the compaction_settings column to the agents table to support customized summarization configuration for each agent. 🐾 Generated with [Letta Code](https://letta.com) Co-Authored-By: Letta <noreply@letta.com> * fix * rename * update apis * fix tests * update web test --------- Co-authored-by: Letta <noreply@letta.com> Co-authored-by: Kian Jones <kian@letta.com>
47 lines
2.0 KiB
Python
47 lines
2.0 KiB
Python
from typing import Literal
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from pydantic import BaseModel, Field
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from letta.schemas.llm_config import LLMConfig
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from letta.schemas.model import ModelSettings
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class CompactionSettings(BaseModel):
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# summarizer_model: LLMConfig = Field(default=..., description="The model to use for summarization.")
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model_settings: ModelSettings = Field(default=..., description="The model settings to use for summarization.")
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prompt: str = Field(default=..., description="The prompt to use for summarization.")
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prompt_acknowledgement: str = Field(
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default=..., description="Whether to include an acknowledgement post-prompt (helps prevent non-summary outputs)."
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)
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clip_chars: int | None = Field(
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default=2000, description="The maximum length of the summary in characters. If none, no clipping is performed."
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)
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mode: Literal["all", "sliding_window"] = Field(default="sliding_window", description="The type of summarization technique use.")
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sliding_window_percentage: float = Field(
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default=0.3, description="The percentage of the context window to keep post-summarization (only used in sliding window mode)."
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)
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def get_default_compaction_settings(model_settings: ModelSettings) -> CompactionSettings:
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"""Build a default CompactionSettings from global settings for backward compatibility.
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Args:
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llm_config: The LLMConfig to use for the summarizer model (typically the agent's llm_config).
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Returns:
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A CompactionSettings with default values from global settings.
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"""
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from letta.constants import MESSAGE_SUMMARY_REQUEST_ACK
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from letta.prompts import gpt_summarize
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from letta.settings import summarizer_settings
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return CompactionSettings(
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mode="sliding_window",
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model_settings=model_settings,
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prompt=gpt_summarize.SYSTEM,
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prompt_acknowledgement=MESSAGE_SUMMARY_REQUEST_ACK,
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clip_chars=2000,
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sliding_window_percentage=summarizer_settings.partial_evict_summarizer_percentage,
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)
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