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https://github.com/basicmachines-co/basic-memory
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bm-claudeai
020957cd76
Signed-off-by: phernandez <paul@basicmachines.co> Co-authored-by: phernandez <paul@basicmachines.co> Co-authored-by: Claude <noreply@anthropic.com>
91 lines
3.6 KiB
Python
91 lines
3.6 KiB
Python
"""Request and response schemas for prompt-related operations."""
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from typing import Optional, List, Any, Dict
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from pydantic import BaseModel, Field
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from basic_memory.schemas.base import TimeFrame
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from basic_memory.schemas.memory import EntitySummary, ObservationSummary, RelationSummary
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class PromptContextItem(BaseModel):
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"""Container for primary and related results to render in a prompt."""
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primary_results: List[EntitySummary]
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related_results: List[EntitySummary | ObservationSummary | RelationSummary]
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class ContinueConversationRequest(BaseModel):
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"""Request for generating a continue conversation prompt.
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Used to provide context for continuing a conversation on a specific topic
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or with recent activity from a given timeframe.
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"""
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topic: Optional[str] = Field(None, description="Topic or keyword to search for")
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timeframe: Optional[TimeFrame] = Field(
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None, description="How far back to look for activity (e.g. '1d', '1 week')"
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)
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# Limit depth to max 2 for performance reasons - higher values cause significant slowdown
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search_items_limit: int = Field(
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5,
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description="Maximum number of search results to include in context (max 10)",
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ge=1,
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le=10,
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)
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depth: int = Field(
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1,
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description="How many relationship 'hops' to follow when building context (max 5)",
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ge=1,
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le=5,
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)
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# Limit related items to prevent overloading the context
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related_items_limit: int = Field(
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5, description="Maximum number of related items to include in context (max 10)", ge=1, le=10
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)
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class SearchPromptRequest(BaseModel):
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"""Request for generating a search results prompt.
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Used to format search results into a prompt with context and suggestions.
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"""
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query: str = Field(..., description="The search query text")
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timeframe: Optional[TimeFrame] = Field(
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None, description="Optional timeframe to limit results (e.g. '1d', '1 week')"
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)
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class PromptMetadata(BaseModel):
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"""Metadata about a prompt response.
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Contains statistical information about the prompt generation process
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and results, useful for debugging and UI display.
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"""
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query: Optional[str] = Field(None, description="The original query or topic")
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timeframe: Optional[str] = Field(None, description="The timeframe used for filtering")
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search_count: int = Field(0, description="Number of search results found")
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context_count: int = Field(0, description="Number of context items retrieved")
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observation_count: int = Field(0, description="Total number of observations included")
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relation_count: int = Field(0, description="Total number of relations included")
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total_items: int = Field(0, description="Total number of all items included in the prompt")
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search_limit: int = Field(0, description="Maximum search results requested")
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context_depth: int = Field(0, description="Context depth used")
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related_limit: int = Field(0, description="Maximum related items requested")
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generated_at: str = Field(..., description="ISO timestamp when this prompt was generated")
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class PromptResponse(BaseModel):
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"""Response containing the rendered prompt.
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Includes both the rendered prompt text and the context that was used
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to render it, for potential client-side use.
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"""
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prompt: str = Field(..., description="The rendered prompt text")
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context: Dict[str, Any] = Field(..., description="The context used to render the prompt")
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metadata: PromptMetadata = Field(
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..., description="Metadata about the prompt generation process"
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)
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