From 87571086b8354fc5e00cf508486507c07c199f48 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Erik=20Bj=C3=A4reholt?= Date: Tue, 10 Dec 2024 21:33:33 +0100 Subject: [PATCH] feat: simplify rag tool by simply calling gptme-rag via subprocess (#316) * feat: simplify rag tool by simply calling gptme-rag via subprocess if installed * build(deps): got rid of gptme-rag dependency * test: fixed tests for simplified rag tool * test: fixed docstring in test --- gptme/tools/_rag_context.py | 195 ---- gptme/tools/rag.py | 128 ++- gptme/util/context.py | 7 +- poetry.lock | 1782 +---------------------------------- pyproject.toml | 7 - tests/conftest.py | 4 +- tests/test_tools_rag.py | 106 +-- tests/test_util_cli.py | 2 +- 8 files changed, 135 insertions(+), 2096 deletions(-) delete mode 100644 gptme/tools/_rag_context.py diff --git a/gptme/tools/_rag_context.py b/gptme/tools/_rag_context.py deleted file mode 100644 index 5235bbda..00000000 --- a/gptme/tools/_rag_context.py +++ /dev/null @@ -1,195 +0,0 @@ -"""Shared RAG context functionality.""" - -import logging -from abc import ABC, abstractmethod -from dataclasses import dataclass -from pathlib import Path -from typing import Any - -from ..config import get_project_config -from ..message import Message - -logger = logging.getLogger(__name__) - -# Constant collection name to ensure consistency -DEFAULT_COLLECTION = "gptme-default" - -try: - import gptme_rag # type: ignore # fmt: skip - - _HAS_RAG = True -except ImportError: - logger.debug("gptme-rag not installed, RAG functionality will not be available") - _HAS_RAG = False - - -# Shared RAG manager instance -_rag_manager: "RAGManager | None" = None - -# Simple in-memory cache for search results -_search_cache: dict[str, tuple[list[Any], dict]] = {} - - -def get_rag_manager() -> "RAGManager": - """Get or create the shared RAG manager instance.""" - global _rag_manager - if _rag_manager is None: - _rag_manager = RAGManager() - return _rag_manager - - -def _get_search_results(query: str, n_results: int) -> tuple[list[Any], dict] | None: - """Get cached search results.""" - return _search_cache.get(f"{query}::{n_results}") - - -def _set_search_results( - query: str, n_results: int, results: tuple[list[Any], dict] -) -> None: - """Cache search results.""" - _search_cache[f"{query}::{n_results}"] = results - - -@dataclass -class Context: - """Context information to be added to messages.""" - - content: str - source: str - relevance: float - - -class ContextProvider(ABC): - """Base class for context providers.""" - - @abstractmethod - def get_context(self, query: str, max_tokens: int = 1000) -> list[Context]: - """Get relevant context for a query.""" - pass - - -class RAGManager: - """Manages RAG functionality for both context enhancement and tool use.""" - - def __init__(self, index_path: Path | None = None, collection: str | None = None): - if not _HAS_RAG: - raise ImportError("gptme-rag not installed") - - # Load config - config = get_project_config(Path.cwd()) - self.config = config.rag if config and config.rag else {} - - # Use config values if not overridden by parameters - self.index_path = index_path or Path("~/.cache/gptme/rag").expanduser() - self.collection = collection or DEFAULT_COLLECTION - - # Initialize the indexer - self.indexer = gptme_rag.Indexer( - persist_directory=self.index_path, - collection_name=self.collection, - ) - - # Context enhancement configuration - self.context_assembler = gptme_rag.ContextAssembler( - max_tokens=self.config.get("max_tokens", 2000) - ) - self.auto_context = self.config.get("auto_context", True) - self.min_relevance = self.config.get("min_relevance", 0.5) - self.max_results = self.config.get("max_results", 5) - - def search( - self, query: str, n_results: int | None = None - ) -> tuple[list[Any], dict]: - """Search the index with caching.""" - n_results = n_results or self.max_results - - # Check cache - if cached := _get_search_results(query, n_results): - logger.debug(f"Using cached search results for query: {query}") - return cached - - # Perform search - docs, results = self.indexer.search(query, n_results=n_results) - - # Cache results - _set_search_results(query, n_results, (docs, results)) - logger.debug(f"Cached search results for query: {query}") - - return docs, results - - def get_context(self, query: str, max_tokens: int = 1000) -> list[Context]: - """Get relevant context using RAG.""" - if not self.auto_context: - return [] - - try: - docs, results = self.search(query) - contexts = [] - - for i, doc in enumerate(docs): - # Calculate relevance score (1 - distance) - relevance = 1.0 - results["distances"][0][i] - - # Skip if below minimum relevance - if relevance < self.min_relevance: - continue - - contexts.append( - Context( - content=doc.content, - source=doc.metadata.get("source", "unknown"), - relevance=relevance, - ) - ) - - # Sort by relevance - contexts.sort(key=lambda x: x.relevance, reverse=True) - return contexts - - except Exception as e: - logger.warning(f"Error getting RAG context: {e}") - return [] - - def index_directory(self, path: Path, **kwargs) -> int: - """Index a directory and return number of documents indexed.""" - return self.indexer.index_directory(path, **kwargs) - - def get_document_count(self) -> int: - """Get the total number of documents in the index.""" - return self.indexer.collection.count() - - -def rag_enhance_messages(messages: list[Message]) -> list[Message]: - """Enhance messages with context from available providers.""" - if not _HAS_RAG: - return messages - - try: - rag_manager = RAGManager() - except Exception as e: - logger.warning(f"Failed to initialize RAG manager: {e}") - return messages - - enhanced_messages = [] - - for msg in messages: - if msg.role == "user": - # Get context from RAG - try: - contexts = rag_manager.get_context(msg.content) - - # Add context as a system message before the user message - if contexts: - context_msg = "Relevant context:\n\n" - for ctx in contexts: - context_msg += f"### {ctx.source}\n{ctx.content}\n\n" - - enhanced_messages.append( - Message(role="system", content=context_msg, hide=True) - ) - except Exception as e: - logger.warning(f"Error getting context: {e}") - - enhanced_messages.append(msg) - - return enhanced_messages diff --git a/gptme/tools/rag.py b/gptme/tools/rag.py index f7b776f6..d09e5ff0 100644 --- a/gptme/tools/rag.py +++ b/gptme/tools/rag.py @@ -5,9 +5,9 @@ .. rubric:: Installation -The RAG tool requires the ``gptme-rag`` package. Install it with:: +The RAG tool requires the ``gptme-rag`` CLI to be installed:: - pip install "gptme[rag]" + pipx install gptme-rag .. rubric:: Configuration @@ -19,38 +19,25 @@ .. rubric:: Features 1. Manual Search and Indexing - - Index project documentation with ``rag_index`` - Search indexed documents with ``rag_search`` - Check index status with ``rag_status`` 2. Automatic Context Enhancement - - - Automatically adds relevant context to user messages - Retrieves semantically similar documents - - Manages token budget to avoid context overflow - Preserves conversation flow with hidden context messages - -3. Performance Optimization - - - Intelligent caching system for embeddings and search results - - Memory-efficient storage - -.. rubric:: Benefits - -- Better informed responses through relevant documentation -- Reduced need for manual context inclusion -- Automatic token management -- Seamless integration with conversation flow """ import logging +import shutil +import subprocess from dataclasses import replace +from functools import lru_cache from pathlib import Path from ..config import get_project_config +from ..message import Message from ..util import get_project_dir -from ._rag_context import _HAS_RAG, get_rag_manager from .base import ToolSpec, ToolUse logger = logging.getLogger(__name__) @@ -80,45 +67,59 @@ def examples(tool_format): """ +@lru_cache +def _has_gptme_rag() -> bool: + """Check if gptme-rag is available in PATH.""" + return shutil.which("gptme-rag") is not None + + +def _run_rag_cmd(cmd: list[str]) -> subprocess.CompletedProcess: + """Run a gptme-rag command and handle errors.""" + try: + return subprocess.run(cmd, capture_output=True, text=True, check=True) + except subprocess.CalledProcessError as e: + logger.error(f"gptme-rag command failed: {e.stderr}") + raise RuntimeError(f"gptme-rag command failed: {e.stderr}") from e + + def rag_index(*paths: str, glob: str | None = None) -> str: """Index documents in specified paths.""" - manager = get_rag_manager() paths = paths or (".",) - kwargs = {"glob_pattern": glob} if glob else {} - total_docs = 0 - for path in paths: - total_docs += manager.index_directory(Path(path), **kwargs) - return f"Indexed {len(paths)} paths ({total_docs} documents)" + cmd = ["gptme-rag", "index"] + cmd.extend(paths) + if glob: + cmd.extend(["--glob", glob]) + + result = _run_rag_cmd(cmd) + return result.stdout.strip() -def rag_search(query: str) -> str: +def rag_search(query: str, return_full: bool = False) -> str: """Search indexed documents.""" - manager = get_rag_manager() - docs, _ = manager.search(query) - return "\n\n".join( - f"### {doc.metadata['source']}\n{doc.content[:200]}..." for doc in docs - ) + cmd = ["gptme-rag", "search", query] + if return_full: + # shows full context of the search results + cmd.append("--show-context") + + result = _run_rag_cmd(cmd) + return result.stdout.strip() def rag_status() -> str: """Show index status.""" - manager = get_rag_manager() - return f"Index contains {manager.get_document_count()} documents" - - -_init_run = False + cmd = ["gptme-rag", "status"] + result = _run_rag_cmd(cmd) + return result.stdout.strip() def init() -> ToolSpec: """Initialize the RAG tool.""" - global _init_run - if _init_run: - return tool - _init_run = True - - if not tool.available: - return tool + # Check if gptme-rag CLI is available + if not _has_gptme_rag(): + logger.debug("gptme-rag CLI not found in PATH") + return replace(tool, available=False) + # Check project configuration project_dir = get_project_dir() if project_dir and (config := get_project_config(project_dir)): enabled = config.rag.get("enabled", False) @@ -129,18 +130,53 @@ def init() -> ToolSpec: logger.debug("Project configuration not found, not enabling") return replace(tool, available=False) - # Initialize the shared RAG manager - get_rag_manager() return tool +def rag_enhance_messages(messages: list[Message]) -> list[Message]: + """Enhance messages with context from RAG.""" + if not _has_gptme_rag(): + return messages + + # Load config + config = get_project_config(Path.cwd()) + rag_config = config.rag if config and config.rag else {} + + if not rag_config.get("enabled", False): + return messages + + enhanced_messages = [] + for msg in messages: + if msg.role == "user": + try: + # Get context using gptme-rag CLI + cmd = ["gptme-rag", "search", msg.content, "--show-context"] + if max_tokens := rag_config.get("max_tokens"): + cmd.extend(["--max-tokens", str(max_tokens)]) + if min_relevance := rag_config.get("min_relevance"): + cmd.extend(["--min-relevance", str(min_relevance)]) + enhanced_messages.append( + Message( + role="system", + content=f"Relevant context:\n\n{_run_rag_cmd(cmd).stdout}", + hide=True, + ) + ) + except Exception as e: + logger.warning(f"Error getting context: {e}") + + enhanced_messages.append(msg) + + return enhanced_messages + + tool = ToolSpec( name="rag", desc="RAG (Retrieval-Augmented Generation) for context-aware assistance", instructions=instructions, examples=examples, functions=[rag_index, rag_search, rag_status], - available=_HAS_RAG, + available=_has_gptme_rag(), init=init, ) diff --git a/gptme/util/context.py b/gptme/util/context.py index 8f65c099..6c757cb5 100644 --- a/gptme/util/context.py +++ b/gptme/util/context.py @@ -282,14 +282,13 @@ def enrich_messages_with_context( - git status - contents of files modified after their message timestamp """ - from ..tools._rag_context import _HAS_RAG, rag_enhance_messages # fmt: skip + from ..tools.rag import rag_enhance_messages # fmt: skip # Make a copy of messages to avoid modifying the original msgs = copy(msgs) - # First enhance messages with context - if _HAS_RAG: - msgs = rag_enhance_messages(msgs) + # First enhance messages with context, if gptme-rag is available + msgs = rag_enhance_messages(msgs) msgs = [ append_file_content(msg, workspace, check_modified=use_fresh_context) diff --git a/poetry.lock b/poetry.lock index ad97eb44..29a56b05 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. 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[extras] -all = ["flask", "flask-cors", "gptme-rag", "matplotlib", "numpy", "pandas", "pillow", "playwright", "python-xlib", "youtube_transcript_api"] +all = ["flask", "flask-cors", "matplotlib", "numpy", "pandas", "pillow", "playwright", "python-xlib", "youtube_transcript_api"] browser = ["playwright"] computer = ["pillow", "python-xlib"] datascience = ["matplotlib", "numpy", "pandas", "pillow"] -rag = ["gptme-rag"] server = ["flask", "flask-cors"] youtube = ["youtube_transcript_api"] [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "557bec90cc2a425d4ab0f80bc085b3e2996d81bc0c01192d2206d8d789b58e1e" +content-hash = "6e975adbd86cd22447a9cec642860f3ebd3c6092f2dc3989960a700b9168edff" diff --git a/pyproject.toml b/pyproject.toml index 1a02f962..868b38f9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -68,10 +68,6 @@ playwright = {version = "1.47.*", optional=true} # version constrained due to a youtube_transcript_api = {version = "^0.6.1", optional=true} python-xlib = {version = "^0.33", optional=true} # for X11 interaction -# RAG -gptme-rag = {version = "^0.3.1", optional=true} -#gptme-rag = {path = "../gptme-rag", optional=true, develop=true} - # evals multiprocessing-logging = "^0.3.4" @@ -120,7 +116,6 @@ server = ["flask", "flask-cors"] browser = ["playwright"] datascience = ["matplotlib", "pandas", "numpy", "pillow"] computer = ["python-xlib", "pillow"] # pillow already in datascience but listed for clarity -rag = ["gptme-rag"] # RAG functionality youtube = ["youtube_transcript_api"] all = [ # server @@ -131,8 +126,6 @@ all = [ "matplotlib", "pandas", "numpy", "pillow", # computer "python-xlib", - # rag - "gptme-rag", # youtube transcript tool "youtube_transcript_api", ] diff --git a/tests/conftest.py b/tests/conftest.py index 5a233c8c..25a56c3a 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -5,7 +5,7 @@ import pytest import tempfile -from gptme.tools.rag import _HAS_RAG +from gptme.tools.rag import _has_gptme_rag def pytest_sessionstart(session): @@ -14,7 +14,7 @@ def pytest_sessionstart(session): def download_model(): - if not _HAS_RAG: + if not _has_gptme_rag(): return # downloads the model if it doesn't exist diff --git a/tests/test_tools_rag.py b/tests/test_tools_rag.py index dbae41fe..fe1f6616 100644 --- a/tests/test_tools_rag.py +++ b/tests/test_tools_rag.py @@ -2,92 +2,54 @@ from unittest.mock import patch -import gptme.tools._rag_context -import gptme.tools.rag import pytest from gptme.message import Message -from gptme.tools._rag_context import rag_enhance_messages -from gptme.tools.rag import _HAS_RAG -from gptme.tools.rag import init as init_rag -from gptme.tools.rag import rag_index, rag_search +from gptme.tools.rag import _has_gptme_rag, rag_enhance_messages -@pytest.fixture(autouse=True) -def reset_rag(): - """Reset the RAG manager and init state before and after each test.""" - - gptme.tools._rag_context._rag_manager = None - gptme.tools.rag._init_run = False - yield - gptme.tools._rag_context._rag_manager = None - gptme.tools.rag._init_run = False - +@pytest.mark.skipif(not _has_gptme_rag(), reason="RAG is not available") +def test_enhance_messages_with_rag(): + """Test that enhancement works when RAG is available.""" + messages = [ + Message("user", "Tell me about Python"), + Message("assistant", "Python is a programming language"), + ] -@pytest.fixture(scope="function") -def temp_docs(tmp_path): - """Create temporary test documents.""" - doc1 = tmp_path / "doc1.md" - doc1.write_text("# Test Document\nThis is a test document about Python functions.") + enhanced = rag_enhance_messages(messages) - doc2 = tmp_path / "doc2.md" - doc2.write_text("# Another Document\nThis document discusses testing practices.") + # Enhanced messages should have extra RAG context msg + assert len(enhanced) >= len(messages) - return tmp_path +def test_enhance_messages_no_rag(): + """Test that enhancement works even without RAG available.""" + with patch("gptme.tools.rag._has_gptme_rag", return_value=False): + messages = [ + Message("user", "Tell me about Python"), + Message("assistant", "Python is a programming language"), + ] -def test_rag_tool_init_without_gptme_rag(): - """Test RAG tool initialization when gptme-rag is not available.""" - with ( - patch("gptme.tools.rag._HAS_RAG", False), - patch("gptme.tools.rag.get_project_config") as mock_config, - ): - # Mock config to disable RAG - mock_config.return_value.rag = {"enabled": False} + enhanced = rag_enhance_messages(messages) - tool = init_rag() - assert tool.name == "rag" - assert tool.available is False + # Should be unchanged when RAG is not available + assert len(enhanced) == len(messages) + assert enhanced == messages -@pytest.mark.skipif(not _HAS_RAG, reason="gptme-rag not installed") -def test_rag_tool_functionality(temp_docs): - """Test basic RAG tool functionality.""" +def test_enhance_messages_disabled(): + """Test message enhancement when RAG is disabled in config.""" with ( + patch("subprocess.run", return_value=type("Proc", (), {"returncode": 0})), patch("gptme.tools.rag.get_project_config") as mock_config, - patch("gptme.tools.rag.get_project_dir") as mock_project_dir, ): - # Mock project dir to return a path - mock_project_dir.return_value = temp_docs - - # Mock config to enable RAG - class MockConfig: - def __init__(self): - self.rag = {"enabled": True} - - mock_config.return_value = MockConfig() - - # Initialize RAG - tool = init_rag() - assert tool.available is True - - # Test indexing - index_result = rag_index(str(temp_docs)) - assert "Indexed" in index_result - - # Test searching - search_result = rag_search("test document") - assert "test document" in search_result.lower() - - -def test_enhance_messages_no_rag(): - """Test that enhancement works even without RAG available.""" - messages = [ - Message("user", "Tell me about Python"), - Message("assistant", "Python is a programming language"), - ] + mock_config.return_value.rag = {"enabled": False} + messages = [ + Message("user", "Tell me about Python"), + Message("assistant", "Python is a programming language"), + ] - enhanced = rag_enhance_messages(messages) + enhanced = rag_enhance_messages(messages) - # Should be unchanged when RAG is not available - assert len(enhanced) == len(messages) - assert enhanced == messages + # Should be unchanged when RAG is disabled + assert len(enhanced) == len(messages) + assert enhanced == messages diff --git a/tests/test_util_cli.py b/tests/test_util_cli.py index 16b7f4b7..897e6642 100644 --- a/tests/test_util_cli.py +++ b/tests/test_util_cli.py @@ -102,7 +102,7 @@ def test_context_generate(tmp_path, mocker): test_file.write_text("Hello, world!") # Mock RAG dependencies - mocker.patch("gptme.tools._rag_context._HAS_RAG", True) + mocker.patch("gptme.tools.rag._has_gptme_rag", return_value=True) mocker.patch("gptme.tools.rag.init") # Mock the init function # Mock the rag_index function