remove unused create_analysis_toolset and AnalysisResult
This commit is contained in:
Yiorgis Gozadinos
parent
1049586469
commit
499a843a43
6 changed files with 1 additions and 165 deletions
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@ -27,6 +27,7 @@
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- **`context_radius` config**: Replaced by automatic section-bounded expansion. Context expansion no longer requires configuration.
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- **DoclingDocument LRU cache**: No longer needed — the document_items table replaces in-memory caching for context expansion
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- **`cachetools` dependency**: No longer used
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- **`create_analysis_toolset()`**: Removed unused `tools/analysis.py` module.
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## [0.39.0] - 2026-04-09
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@ -59,22 +59,6 @@ docs = create_document_toolset(config)
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- `get_document(query)` — Retrieve a document by title or URI.
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- `summarize_document(query)` — Generate an LLM summary of a document's content.
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### Analysis Toolset
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`create_analysis_toolset()` provides computational analysis via the RLM agent.
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```python
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from haiku.rag.tools import create_analysis_toolset
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analysis = create_analysis_toolset(config)
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```
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| Parameter | Default | Description |
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|-----------|---------|-------------|
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| `config` | required | `AppConfig` |
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| `base_filter` | `None` | SQL WHERE clause applied to searches |
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| `tool_name` | `"analyze"` | Name of the tool exposed to the agent |
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## Filter Helpers
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`haiku.rag.tools.filters` provides utilities for building SQL filters:
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@ -1,4 +1,3 @@
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from haiku.rag.tools.analysis import AnalysisResult, create_analysis_toolset
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from haiku.rag.tools.context import RAGDeps
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from haiku.rag.tools.document import create_document_toolset
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from haiku.rag.tools.filters import (
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@ -10,14 +9,12 @@ from haiku.rag.tools.qa import PRIOR_ANSWER_RELEVANCE_THRESHOLD, QAHistoryEntry
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from haiku.rag.tools.search import create_search_toolset
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__all__ = [
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"AnalysisResult",
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"PRIOR_ANSWER_RELEVANCE_THRESHOLD",
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"QAHistoryEntry",
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"RAGDeps",
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"build_document_filter",
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"build_multi_document_filter",
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"combine_filters",
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"create_analysis_toolset",
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"create_document_toolset",
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"create_search_toolset",
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]
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@ -1,87 +0,0 @@
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from pydantic import BaseModel, Field
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from pydantic_ai import FunctionToolset, RunContext
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from haiku.rag.agents.rlm.agent import create_rlm_agent
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from haiku.rag.agents.rlm.dependencies import RLMContext, RLMDeps
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from haiku.rag.agents.rlm.sandbox import Sandbox
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from haiku.rag.config.models import AppConfig
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from haiku.rag.tools.context import RAGDeps
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from haiku.rag.tools.filters import (
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build_document_filter,
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combine_filters,
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)
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class AnalysisResult(BaseModel):
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"""Result from the analysis toolset (RLM execution)."""
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answer: str = Field(description="The answer produced by analysis")
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code_executed: bool = Field(
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default=True,
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description="Whether code was executed to produce this answer",
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)
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def create_analysis_toolset(
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config: AppConfig,
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base_filter: str | None = None,
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tool_name: str = "analyze",
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) -> FunctionToolset[RAGDeps]:
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"""Create a toolset with code analysis capabilities via RLM agent.
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Args:
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config: Application configuration.
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base_filter: Optional base SQL WHERE clause applied to searches.
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tool_name: Name for the analyze tool. Defaults to "analyze".
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Returns:
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FunctionToolset with an analyze tool.
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"""
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async def analyze( # pragma: no cover
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ctx: RunContext[RAGDeps],
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task: str,
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document_name: str | None = None,
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) -> AnalysisResult:
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"""Execute a computational task via code execution.
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Uses the RLM (Recursive Language Model) agent to write and execute
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Python code to answer the task.
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Args:
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task: A specific, actionable instruction describing what to compute.
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document_name: Optional document name/title to focus on.
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Returns:
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AnalysisResult with answer and execution metadata.
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"""
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client = ctx.deps.client
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doc_filter = build_document_filter(document_name) if document_name else None
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effective_filter = combine_filters(base_filter, doc_filter)
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rlm_context = RLMContext(filter=effective_filter)
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sandbox = Sandbox(
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client=client,
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config=config,
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context=rlm_context,
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)
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deps = RLMDeps(
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sandbox=sandbox,
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context=rlm_context,
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)
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rlm_agent = create_rlm_agent(config)
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result = await rlm_agent.run(task, deps=deps)
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program = result.output.program
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return AnalysisResult(
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answer=result.output.answer,
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code_executed=bool(program),
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)
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toolset: FunctionToolset[RAGDeps] = FunctionToolset()
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toolset.add_function(analyze, name=tool_name)
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return toolset
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@ -1,42 +0,0 @@
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import pytest
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from haiku.rag.tools.analysis import create_analysis_toolset
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class TestAnalysisToolset:
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"""Tests for create_analysis_toolset."""
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def test_create_analysis_toolset_returns_function_toolset(self, analysis_config):
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"""create_analysis_toolset returns a FunctionToolset."""
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from pydantic_ai import FunctionToolset
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toolset = create_analysis_toolset(analysis_config)
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assert isinstance(toolset, FunctionToolset)
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def test_analysis_toolset_has_analyze_tool(self, analysis_config):
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"""The toolset includes an 'analyze' tool."""
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toolset = create_analysis_toolset(analysis_config)
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assert "analyze" in toolset.tools
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def test_analysis_toolset_custom_tool_name(self, analysis_config):
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"""Toolset supports custom tool name."""
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toolset = create_analysis_toolset(analysis_config, tool_name="run_code")
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assert "run_code" in toolset.tools
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assert "analyze" not in toolset.tools
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@pytest.fixture
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async def analysis_client(temp_db_path):
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"""Create a HaikuRAG client for analysis tests."""
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from haiku.rag.client import HaikuRAG
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async with HaikuRAG(temp_db_path, create=True) as rag:
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yield rag
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@pytest.fixture
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def analysis_config():
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"""Default AppConfig for analysis tests."""
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from haiku.rag.config import Config
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return Config
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@ -1,17 +0,0 @@
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from haiku.rag.tools.analysis import AnalysisResult
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def test_analysis_result_defaults():
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"""Test AnalysisResult has sensible defaults."""
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result = AnalysisResult(answer="The result is 42")
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assert result.code_executed is True
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def test_analysis_result_with_values():
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"""Test AnalysisResult with explicit values."""
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result = AnalysisResult(
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answer="The result is 42",
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code_executed=True,
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)
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assert result.answer == "The result is 42"
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assert result.code_executed is True
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