fix: fixed bugs in rag

gptme/config.py

@@ -1,6 +1,7 @@
 import logging
 import os
 from dataclasses import dataclass, field
+from functools import lru_cache
 from pathlib import Path
 
 import tomlkit
@@ -73,12 +74,12 @@ class ProjectConfig:
 def get_config() -> Config:
     global _config
     if _config is None:
-        _config = load_config()
+        _config = _load_config()
     return _config
 
 
-def load_config() -> Config:
-    config = _load_config()
+def _load_config() -> Config:
+    config = _load_config_doc()
     assert "prompt" in config, "prompt key missing in config"
     assert "env" in config, "env key missing in config"
     prompt = config.pop("prompt")
@@ -88,7 +89,7 @@ def load_config() -> Config:
     return Config(prompt=prompt, env=env)
 
 
-def _load_config() -> tomlkit.TOMLDocument:
+def _load_config_doc() -> tomlkit.TOMLDocument:
     # Check if the config file exists
     if not os.path.exists(config_path):
         # If not, create it and write some default settings
@@ -106,7 +107,7 @@ def _load_config() -> tomlkit.TOMLDocument:
 
 
 def set_config_value(key: str, value: str) -> None:  # pragma: no cover
-    doc: TOMLDocument | Container = _load_config()
+    doc: TOMLDocument | Container = _load_config_doc()
 
     # Set the value
     keypath = key.split(".")
@@ -121,9 +122,10 @@ def set_config_value(key: str, value: str) -> None:  # pragma: no cover
 
     # Reload config
     global _config
-    _config = load_config()
+    _config = _load_config()
 
 
+@lru_cache
 def get_project_config(workspace: Path) -> ProjectConfig | None:
     project_config_paths = [
         p

gptme/context.py

@@ -35,6 +35,8 @@ def get_context(self, query: str, max_tokens: int = 1000) -> list[Context]:
 class RAGContextProvider(ContextProvider):
     """Context provider using RAG."""
 
+    # TODO: refactor this to share code with rag tool
+
     def __init__(self):
         try:
             self._has_rag = True
@@ -45,7 +47,7 @@ def __init__(self):
             # Storage configuration
             self.indexer = gptme_rag.Indexer(
                 persist_directory=config.rag.get("index_path", "~/.cache/gptme/rag"),
-                collection_name=config.rag.get("collection", "gptme_docs"),
+                collection_name=config.rag.get("collection", "default"),
             )
 
             # Context enhancement configuration

gptme/init.py

@@ -3,7 +3,7 @@
 
 from dotenv import load_dotenv
 
-from .config import config_path, load_config, set_config_value
+from .config import config_path, get_config, set_config_value
 from .llm import init_llm
 from .models import (
     PROVIDERS,
@@ -30,7 +30,7 @@ def init(model: str | None, interactive: bool, tool_allowlist: list[str] | None)
     logger.debug("Started")
     load_dotenv()
 
-    config = load_config()
+    config = get_config()
 
     # get from config
     if not model: