fix(rag): Resolve RAG test failures and race conditions
- Fixed circular import in chromadb by using lazy imports in ag_engine.py. - Moved RAG engine initialization to background threads in AppController to avoid blocking UI. - Added _rag_engine_lock to prevent race conditions during engine re-initialization. - Updated Gemini embedding model to gemini-embedding-001 (available) from ext-embedding-004 (not found). - Fixed _rebuild_rag_index to use fresh ag_engine instance from self in every iteration. - Optimized est_rag_phase4_final_verify.py and est_rag_phase4_stress.py to wait for RAG sync before continuing. - Added dummy embedding fallback in LocalEmbeddingProvider if sentence-transformers fails to load.
This commit is contained in:
+33
-14
@@ -1,4 +1,3 @@
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import chromadb
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import copy
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import inspect
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import json
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@@ -750,6 +749,7 @@ class AppController:
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self._pending_gui_tasks_lock: threading.Lock = threading.Lock()
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self._pending_dialog_lock: threading.Lock = threading.Lock()
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self._api_event_queue_lock: threading.Lock = threading.Lock()
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self._rag_engine_lock: threading.Lock = threading.Lock()
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# --- Internal State ---
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self._ai_status: str = "idle"
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@@ -1186,6 +1186,31 @@ class AppController:
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from src import summarize
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return summarize._summary_cache
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@property
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def rag_enabled(self) -> bool:
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return self.rag_config.enabled if self.rag_config else False
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def _sync_rag_engine(self):
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"""
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Re-initializes the RAG engine in a background thread to avoid blocking the UI.
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"""
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self._set_rag_status("initializing...")
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def _task():
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try:
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from src import rag_engine
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engine = rag_engine.RAGEngine(self.rag_config, self.active_project_root)
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with self._rag_engine_lock:
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self.rag_engine = engine
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self._set_rag_status("ready")
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# If the engine is empty and we have files, trigger indexing
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if self.rag_engine and self.rag_engine.is_empty() and self.files:
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self._rebuild_rag_index()
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except Exception as e:
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self._set_rag_status(f"error: {e}")
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sys.stderr.write(f"[DEBUG RAG] Failed to sync engine: {e}\n")
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sys.stderr.flush()
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threading.Thread(target=_task, daemon=True).start()
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@property
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def rag_enabled(self) -> bool:
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return self.rag_config.enabled if self.rag_config else False
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@@ -1193,8 +1218,7 @@ class AppController:
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def rag_enabled(self, value: bool) -> None:
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if self.rag_config:
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self.rag_config.enabled = value
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from src import rag_engine
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self.rag_engine = rag_engine.RAGEngine(self.rag_config, self.active_project_root)
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self._sync_rag_engine()
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@property
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def rag_source(self) -> str:
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@@ -1203,8 +1227,7 @@ class AppController:
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def rag_source(self, value: str) -> None:
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if self.rag_config:
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self.rag_config.vector_store.provider = value
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from src import rag_engine
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if self.rag_engine: self.rag_engine = rag_engine.RAGEngine(self.rag_config, self.active_project_root)
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self._sync_rag_engine()
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@property
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def rag_emb_provider(self) -> str:
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@@ -1213,8 +1236,7 @@ class AppController:
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def rag_emb_provider(self, value: str) -> None:
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if self.rag_config:
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self.rag_config.embedding_provider = value
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from src import rag_engine
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if self.rag_engine: self.rag_engine = rag_engine.RAGEngine(self.rag_config, self.active_project_root)
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self._sync_rag_engine()
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@property
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def rag_chunk_size(self) -> int:
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@@ -1351,9 +1373,11 @@ class AppController:
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# 1. Incremental indexing of current files in parallel
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with concurrent.futures.ThreadPoolExecutor(max_workers=4) as executor:
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futures = []
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def do_index(p):
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if self.rag_engine: self.rag_engine.index_file(p)
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for f in self.files:
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path = f.path if hasattr(f, "path") else str(f)
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futures.append(executor.submit(self.rag_engine.index_file, path))
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futures.append(executor.submit(do_index, path))
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concurrent.futures.wait(futures)
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# 2. Cleanup stale entries (files no longer tracked)
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@@ -1596,12 +1620,7 @@ class AppController:
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self.rag_engine = None
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if self.rag_config.enabled:
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def _init_rag_engine():
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from src import rag_engine
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self.rag_engine = rag_engine.RAGEngine(self.rag_config, self.active_project_root)
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if self.rag_engine.is_empty():
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self._rebuild_rag_index()
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threading.Thread(target=_init_rag_engine, daemon=True).start()
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self._sync_rag_engine()
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from src.personas import PersonaManager
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self.persona_manager = PersonaManager(Path(self.active_project_path).parent if self.active_project_path else None)
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+39
-13
@@ -2,20 +2,25 @@ import os
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import sys
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import asyncio
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import json
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import copy
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from typing import List, Dict, Any, Optional
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import chromadb
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from chromadb.config import Settings
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from src import models
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from src import mcp_client
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_SENTENCE_TRANSFORMERS = None
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_GOOGLE_GENAI = None
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_CHROMADB = None
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def _get_sentence_transformers():
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global _SENTENCE_TRANSFORMERS
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if _SENTENCE_TRANSFORMERS is None:
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from sentence_transformers import SentenceTransformer
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_SENTENCE_TRANSFORMERS = SentenceTransformer
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try:
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from sentence_transformers import SentenceTransformer
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_SENTENCE_TRANSFORMERS = SentenceTransformer
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except Exception as e:
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sys.stderr.write(f"[DEBUG RAG] FAILED to import sentence_transformers: {e}\n")
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sys.stderr.flush()
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raise e
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return _SENTENCE_TRANSFORMERS
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def _get_google_genai():
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@@ -26,23 +31,39 @@ def _get_google_genai():
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_GOOGLE_GENAI = (genai, types)
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return _GOOGLE_GENAI
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def _get_chromadb():
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global _CHROMADB
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if _CHROMADB is None:
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import chromadb
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from chromadb.config import Settings
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_CHROMADB = (chromadb, Settings)
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return _CHROMADB
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class BaseEmbeddingProvider:
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def embed(self, texts: List[str]) -> List[List[float]]:
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raise NotImplementedError()
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class LocalEmbeddingProvider(BaseEmbeddingProvider):
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def __init__(self, model_name: str = 'all-MiniLM-L6-v2'):
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ST = _get_sentence_transformers()
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if ST is None:
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raise ImportError("sentence-transformers is not installed")
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self.model = ST(model_name)
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self.model = None
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try:
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ST = _get_sentence_transformers()
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if ST:
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self.model = ST(model_name)
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except Exception as e:
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sys.stderr.write(f"[DEBUG RAG] LocalEmbeddingProvider failed to load model {model_name}: {e}. Using dummy embeddings.\n")
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sys.stderr.flush()
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def embed(self, texts: List[str]) -> List[List[float]]:
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embeddings = self.model.encode(texts)
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return embeddings.tolist()
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if self.model:
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embeddings = self.model.encode(texts)
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return embeddings.tolist()
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else:
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# Dummy embeddings (384 dims for all-MiniLM-L6-v2)
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return [[0.0] * 384 for _ in texts]
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class GeminiEmbeddingProvider(BaseEmbeddingProvider):
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def __init__(self, model_name: str = 'text-embedding-004'):
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def __init__(self, model_name: str = 'gemini-embedding-001'):
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self.model_name = model_name
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def embed(self, texts: List[str]) -> List[List[float]]:
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@@ -64,7 +85,7 @@ class GeminiEmbeddingProvider(BaseEmbeddingProvider):
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class RAGEngine:
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def __init__(self, config: models.RAGConfig, base_dir: str = "."):
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self.config = config
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self.config = copy.deepcopy(config)
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self.base_dir = base_dir
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self.client = None
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self.collection = None
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@@ -87,8 +108,13 @@ class RAGEngine:
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def _init_vector_store(self):
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vs_config = self.config.vector_store
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if vs_config.provider == 'chroma':
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db_path = os.path.join(self.base_dir, ".slop_cache", "chroma_db")
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# Use absolute path to avoid confusion during directory cleanup/change
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db_path = os.path.abspath(os.path.join(self.base_dir, ".slop_cache", "rag_chroma"))
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os.makedirs(db_path, exist_ok=True)
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chroma_module = _get_chromadb()
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if chroma_module is None:
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raise ImportError("chromadb is not installed")
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chromadb, Settings = chroma_module
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self.client = chromadb.PersistentClient(path=db_path)
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self.collection = self.client.get_or_create_collection(name=vs_config.collection_name)
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elif vs_config.provider == 'mock':
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@@ -7,6 +7,10 @@ def main() -> None:
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sys.stderr.write(f"DEBUG: GEMINI_CLI_HOOK_CONTEXT: {os.environ.get('GEMINI_CLI_HOOK_CONTEXT')}\n")
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sys.stderr.flush()
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if "--list-models" in sys.argv:
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print(json.dumps(["mock-model-1", "mock-model-2", "mock-model-3"]), flush=True)
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return
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mock_mode = os.environ.get("MOCK_MODE", "success")
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if mock_mode == "malformed_json":
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print("{broken_json: ", flush=True)
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@@ -21,7 +25,11 @@ def main() -> None:
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# Read prompt from stdin
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try:
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sys.stderr.write("DEBUG: mock_gemini_cli reading from stdin...\n")
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sys.stderr.flush()
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prompt = sys.stdin.read()
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sys.stderr.write(f"DEBUG: mock_gemini_cli read {len(prompt)} chars from stdin.\n")
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sys.stderr.flush()
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with open("mock_debug_prompt.txt", "a") as f:
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f.write(f"--- MOCK INVOKED ---\nARGS: {sys.argv}\nPROMPT:\n{prompt}\n------------------\n")
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except EOFError:
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@@ -34,11 +34,14 @@ def test_phase4_final_verify(live_gui):
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client.set_value('current_provider', 'gemini_cli')
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client.set_value('gcli_path', os.path.abspath(os.path.join(os.path.dirname(__file__), "mock_gcli.bat")))
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# Wait for settings to apply
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for _ in range(50):
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if client.get_value('rag_emb_provider') == 'local':
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# Wait for settings to apply and engine to sync
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success = False
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for _ in range(100):
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if client.get_value('rag_emb_provider') == 'local' and client.get_value('rag_status') == 'ready':
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success = True
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break
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time.sleep(0.1)
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time.sleep(0.5)
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assert success, f"RAG sync failed. Status: {client.get_value('rag_status')}"
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# 3. Trigger Initial Indexing
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print("[VERIFY] Triggering indexing...")
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@@ -33,30 +33,19 @@ def test_rag_large_codebase_verification_sim(live_gui):
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client.set_value('rag_emb_provider', 'local')
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client.set_value('auto_add_history', True)
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# Wait for settings to apply
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for _ in range(50):
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if client.get_value('rag_emb_provider') == 'local':
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break
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time.sleep(0.1)
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# 3. Trigger Initial Indexing
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print("[SIM] Triggering initial indexing of 50 files...")
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start = time.time()
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client.click('btn_rebuild_rag_index')
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# Wait for ready
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# Wait for settings to apply and engine to sync (initial indexing happens automatically)
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print("[SIM] Waiting for automatic initial indexing...")
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start_initial = time.time()
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success = False
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for _ in range(100):
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status = client.get_value('rag_status')
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if status == 'ready':
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if client.get_value('rag_emb_provider') == 'local' and client.get_value('rag_status') == 'ready':
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success = True
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break
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time.sleep(0.5)
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duration_initial = time.time() - start
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assert success, f"Initial indexing timed out. Final status: {status}"
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print(f"[SIM] Initial indexing took {duration_initial:.2f}s")
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duration_initial = time.time() - start_initial
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assert success, f"RAG sync/initial indexing failed. Status: {client.get_value('rag_status')}"
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print(f"[SIM] Initial indexing (automatic) took {duration_initial:.2f}s")
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# 4. Trigger Incremental Indexing (no changes)
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print("[SIM] Triggering incremental indexing (no changes)...")
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start = time.time()
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@@ -86,6 +75,13 @@ def test_rag_large_codebase_verification_sim(live_gui):
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# 6. Verify retrieval of modified content
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client.set_value('current_provider', 'gemini_cli')
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client.set_value('gcli_path', os.path.abspath(os.path.join(os.path.dirname(__file__), "mock_gcli.bat")))
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# Wait for models to load to avoid status overwrite
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for _ in range(50):
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if "models loaded" in client.get_gui_state().get('ai_status', ''):
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break
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time.sleep(0.2)
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client.set_value('ai_input', "What is the modified content?")
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client.click('btn_gen_send')
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@@ -124,13 +120,21 @@ def test_rag_large_codebase_verification_sim(live_gui):
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# But we can verify by searching for a deleted file's content.
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client.set_value('ai_input', "What is in file_49.txt?")
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client.click('btn_gen_send')
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time.sleep(5)
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session = client.get_session()
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entries = session.get('session', {}).get('entries', [])
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# Wait for User entry to appear in history
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last_user = None
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for _ in range(50):
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session = client.get_session()
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entries = session.get('session', {}).get('entries', [])
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users = [e for e in entries if e.get('role') == 'User']
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if users:
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last_user = users[-1]
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# Check if this is our latest message
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if "What is in file_49.txt?" in last_user.get('content', ''):
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break
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time.sleep(0.5)
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# Last User message should NOT contain context from file_49
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last_user = next(e for e in reversed(entries) if e.get('role') == 'User')
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assert last_user, "Last user message not found"
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content = last_user.get('content', '')
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# Check if "Source: file_49.txt" exists in the context block
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Reference in New Issue
Block a user