haiku.rag/haiku_rag_slim/haiku/rag/tools/search.py

78 lines
2.5 KiB
Python

from collections.abc import Callable
from pydantic_ai import FunctionToolset, RunContext
from haiku.rag.config.models import AppConfig
from haiku.rag.store.models import SearchResult
from haiku.rag.tools.context import RAGDeps
from haiku.rag.tools.filters import combine_filters
def create_search_toolset(
config: AppConfig,
expand_context: bool = True,
base_filter: str | None = None,
tool_name: str = "search",
on_results: Callable[[list[SearchResult]], None] | None = None,
) -> FunctionToolset[RAGDeps]:
"""Create a toolset with search capabilities.
Args:
config: Application configuration.
expand_context: Whether to expand search results with surrounding context.
Defaults to True.
base_filter: Optional base SQL WHERE clause applied to all searches.
Combined with any filter passed to the search tool.
tool_name: Name for the search tool. Defaults to "search".
on_results: Optional callback invoked with search results after each search.
Useful for accumulating results externally (e.g., for citation resolution).
Returns:
FunctionToolset with a search tool.
"""
async def search(
ctx: RunContext[RAGDeps],
query: str,
limit: int | None = None,
filter: str | None = None,
) -> str:
"""Search the knowledge base for relevant documents.
Args:
query: The search query (what to search for).
limit: Number of results to return (default: from config).
filter: Optional SQL WHERE clause to filter documents.
Returns:
Formatted search results with content and metadata.
"""
client = ctx.deps.client
effective_filter = combine_filters(base_filter, filter)
effective_limit = limit or config.search.limit
results = await client.search(
query, limit=effective_limit, filter=effective_filter
)
if expand_context:
results = await client.expand_context(results)
results_list = list(results)
if on_results:
on_results(results_list)
if not results_list:
return "No results found."
total = len(results_list)
formatted = [
r.format_for_agent(rank=i + 1, total=total)
for i, r in enumerate(results_list)
]
return "\n\n".join(formatted)
toolset: FunctionToolset[RAGDeps] = FunctionToolset()
toolset.add_function(search, name=tool_name)
return toolset