Feature/import path in first steps wizard

learn2rag/evaluation/tools.py

@@ -10,7 +10,6 @@
 import pandas as pd
 
 import learn2rag.pipeline.ingestion
-from learn2rag.pipeline.config import opt_config
 
 
 def key_document(key: str) -> Callable[[Any], Any]:
@@ -117,9 +116,10 @@ def basic_pipeline(dataset_name: str, question: str) -> dict[str, Any]:
         'imported_documents_file_path': None,
         'llm': None,
     }
-    documents = learn2rag.pipeline.search.search(question, user_config, opt_config)
-    answer = learn2rag.pipeline.generate.generate(question, documents.points, opt_config)
-    return {
-        'documents': documents,
-        'answer': answer,
-    }
+    raise NotImplementedError()
+    # documents = learn2rag.pipeline.search.search(question, user_config, opt_config)
+    # answer = learn2rag.pipeline.generate.generate(question, documents.points, opt_config)
+    # return {
+    #     'documents': documents,
+    #     'answer': answer,
+    # }

learn2rag/pipeline/qdrant.py

@@ -1,12 +1,12 @@
 import os
+
 from typing import Any, Optional
+
 import logging
 from qdrant_client import QdrantClient
 from qdrant_client.models import Distance, VectorParams, SparseVectorParams, SparseIndexParams, MultiVectorComparator, MultiVectorConfig
 from qdrant_client.http.exceptions import UnexpectedResponse
 
-from .config import user_config
-
 # FIXME: when running a Windows package,
 # this import causes segmentation fault if done after creating QdrantClient.
 # Importing it here prevents this situation...

learn2rag/ui/__init__.py

@@ -32,6 +32,7 @@
     normalize_path,
     open_web_browser,
     save_data_path,
+    get_default_rag_dir,
 )
 
 from datetime import datetime
@@ -191,6 +192,7 @@ def inject_info() -> dict[str, Any]:
             'debug_logging': config.get('logging', {}).get('debug', False),
             'current_timestamp': math.floor(time.time()),
             'llm': learn2rag.pipeline.llm,
+            'default_rag_dir': get_default_rag_dir(),
         }
 
     @app.context_processor