Import source: axon/models

Import the existing local project snapshot. This commit organizes existing files; it does not represent newly developed functionality.

axon/models.py

@@ -0,0 +1,185 @@
+from typing import Literal
+from pydantic import BaseModel, Field
+
+
+class SearchRequest(BaseModel):
+    query: str
+    max_results: int = Field(default=10, ge=1, le=20)
+    search_depth: Literal["basic", "advanced"] = "basic"
+    include_answer: bool = False
+    include_raw_content: bool = False
+    domains_whitelist: list[str] = []
+    domains_blacklist: list[str] = []
+    topic: Literal["general", "news"] = "general"
+    time_range: Literal["day", "week", "month", "year"] | None = None
+    include_private: bool = True
+
+
+class SearchResult(BaseModel):
+    title: str
+    url: str
+    content: str
+    score: float = 0.5
+    published_date: str | None = None
+    favicon: str | None = None
+    source_quality: float | None = None
+
+
+class SearchResponse(BaseModel):
+    query: str
+    answer: str | None = None
+    results: list[SearchResult]
+    response_time: float
+    credits_used: int = 1
+
+
+class ExtractRequest(BaseModel):
+    urls: list[str]
+    include_images: bool = False
+
+
+class ExtractResult(BaseModel):
+    url: str
+    title: str | None = None
+    content: str = ""
+    success: bool
+    error: str | None = None
+
+
+class ExtractResponse(BaseModel):
+    results: list[ExtractResult]
+
+
+class CrawlRequest(BaseModel):
+    url: str
+    max_depth: int = Field(default=1, ge=0, le=3)
+    max_pages: int = Field(default=20, ge=1, le=50)
+    include_raw_content: bool = False
+    instructions: str | None = None
+
+
+class CrawlResult(BaseModel):
+    url: str
+    title: str | None = None
+    content: str = ""
+    links: list[str] = []
+    depth: int = 0
+    success: bool
+    error: str | None = None
+
+
+class CrawlResponse(BaseModel):
+    start_url: str
+    results: list[CrawlResult]
+    response_time: float
+
+
+class MapRequest(BaseModel):
+    url: str
+    max_depth: int = Field(default=1, ge=0, le=3)
+    max_pages: int = Field(default=50, ge=1, le=200)
+    instructions: str | None = None
+
+
+class MapResponse(BaseModel):
+    start_url: str
+    urls: list[str]
+    response_time: float
+
+
+class ResearchRequest(BaseModel):
+    query: str
+    depth: Literal["basic", "deep"] = "basic"
+    output_format: Literal["markdown", "json"] = "markdown"
+    search_depth: Literal["basic", "advanced"] = "advanced"
+    max_results_per_query: int = Field(default=5, ge=1, le=10)
+
+
+class ResearchResponse(BaseModel):
+    query: str
+    report: str
+    sources: list[SearchResult]
+    sub_queries: list[str]
+    response_time: float
+
+
+class MetricsResponse(BaseModel):
+    requests_total: int
+    requests_by_path: dict[str, int]
+    errors_total: int
+    average_latency_ms: float
+
+
+class CitationValidationRequest(BaseModel):
+    report: str
+    sources: list[SearchResult]
+
+
+class CitationValidationResponse(BaseModel):
+    citation_count: int
+    missing_citations: list[int]
+    valid: bool
+
+
+class IngestDocument(BaseModel):
+    id: str | None = None
+    title: str
+    content: str
+    url: str | None = None
+    metadata: dict[str, str] = {}
+
+
+class IngestRequest(BaseModel):
+    documents: list[IngestDocument]
+
+
+class IngestResponse(BaseModel):
+    indexed: int
+
+
+class IndexSearchRequest(BaseModel):
+    query: str
+    max_results: int = Field(default=10, ge=1, le=50)
+
+
+class IndexDocument(BaseModel):
+    id: str
+    title: str
+    content: str
+    url: str | None = None
+    score: float
+
+
+class IndexSearchResponse(BaseModel):
+    query: str
+    results: list[IndexDocument]
+
+
+class JobCreateResponse(BaseModel):
+    job_id: str
+    status: Literal["queued", "running", "succeeded", "failed"]
+
+
+class JobResponse(BaseModel):
+    job_id: str
+    kind: str
+    status: Literal["queued", "running", "succeeded", "failed"]
+    result: dict | None = None
+    error: str | None = None
+
+
+class TavilySearchRequest(BaseModel):
+    query: str
+    search_depth: Literal["basic", "advanced"] = "basic"
+    max_results: int = Field(default=10, ge=1, le=20)
+    include_answer: bool | str = False
+    include_raw_content: bool = False
+    include_domains: list[str] = []
+    exclude_domains: list[str] = []
+    topic: Literal["general", "news"] = "general"
+    time_range: Literal["day", "week", "month", "year"] | None = None
+
+
+class TavilyExtractRequest(BaseModel):
+    urls: str | list[str]
+    include_images: bool = False