forked from 0xWheatyz/SPARC
agent-company
04f4d36307
Allow users to choose the LLM model on a per-analysis basis. The model field is optional in both single and batch analysis requests, defaulting to the server-configured MODEL env var. The model used is recorded in the analysis result and database. - Add model parameter to LLMAnalyzer.analyze_patent_content and analyze_patent_portfolio - Add model field to CompanyAnalysisResult and API response - Add model field to BatchAnalysisRequest - Add GET /models endpoint listing supported models and the default - Store model in llm_messages metadata for attribution Closes leeworks-agents/SPARC#37 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
40 lines
824 B
Python
40 lines
824 B
Python
from dataclasses import dataclass, field
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from datetime import datetime
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@dataclass
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class Patent:
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patent_id: str
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pdf_link: str
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pdf_path: str | None = None
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summary: dict | None = None
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@dataclass
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class Patents:
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patents: list[Patent]
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@dataclass
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class CompanyAnalysisResult:
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"""Result of analyzing a single company's patent portfolio."""
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company_name: str
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analysis: str
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patent_count: int
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success: bool
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error: str | None = None
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model: str | None = None
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timestamp: datetime = field(default_factory=datetime.now)
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@dataclass
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class BatchAnalysisResult:
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"""Result of batch analyzing multiple companies."""
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results: list[CompanyAnalysisResult]
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total_companies: int
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successful: int
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failed: int
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timestamp: datetime = field(default_factory=datetime.now)
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