v3.0.1

Fixed a bug when searching by document type.

Consolidated three vision model scripts into the new loader_images.py script.

src/constants.py

@@ -307,8 +307,6 @@
     ".html": "UnstructuredHTMLLoader",
 }
 
-WHISPER_MODEL_NAMES = ["tiny", "tiny.en", "base", "base.en", "small", "small.en", "medium", "medium.en", "large-v2"]
-
 CHUNKS_ONLY_TOOLTIP = "Only return relevant chunks without connecting to the LLM. Extremely useful to test the chunk size/overlap settings."
 
 SPEAK_RESPONSE_TOOLTIP = "Only click this after the LLM's entire response is received otherwise your computer might explode."

src/database_interactions.py

@@ -108,3 +108,32 @@ def get_embeddings(self, EMBEDDING_MODEL_NAME, config_data):
 if __name__ == "__main__":
     create_vector_db = CreateVectorDB()
     create_vector_db.run()
+
+# To delete entries based on the "hash" metadata attribute, you can use this as_retriever method to create a retriever that filters documents based on their metadata. Once you retrieve the documents with the specific hash, you can then extract their IDs and use the delete method to remove them from the vectorstore.
+
+# Here is how you might implement this in your CreateVectorDB class:
+
+# python
+
+# class CreateVectorDB:
+    # # ... [other methods] ...
+
+    # def delete_entries_by_hash(self, target_hash):
+        # my_cprint(f"Deleting entries with hash: {target_hash}", "red")
+
+        # # Initialize the retriever with a filter for the specific hash
+        # retriever = self.db.as_retriever(search_kwargs={'filter': {'hash': target_hash}})
+
+        # # Retrieve documents with the specific hash
+        # documents = retriever.search("")
+
+        # # Extract IDs from the documents
+        # ids_to_delete = [doc.id for doc in documents]
+
+        # # Delete entries with the extracted IDs
+        # if ids_to_delete:
+            # self.db.delete(ids=ids_to_delete)
+            # my_cprint(f"Deleted {len(ids_to_delete)} entries from the database.", "green")
+        # else:
+            # my_cprint("No entries found with the specified hash.", "yellow")
+

src/document_processor.py

@@ -21,9 +21,7 @@
 )
 
 from constants import DOCUMENT_LOADERS
-from loader_vision_llava import llava_process_images
-from loader_vision_cogvlm import cogvlm_process_images
-from loader_salesforce import salesforce_process_images
+from loader_images import loader_cogvlm, loader_llava, loader_salesforce
 from extract_metadata import extract_document_metadata
 from utilities import my_cprint
 
@@ -34,15 +32,18 @@
 for ext, loader_name in DOCUMENT_LOADERS.items():
     DOCUMENT_LOADERS[ext] = globals()[loader_name]
 
-def process_images_wrapper(config):
+def choose_image_loader(config):
     chosen_model = config["vision"]["chosen_model"]
 
     if chosen_model == 'llava' or chosen_model == 'bakllava':
-        return llava_process_images()
+        image_loader = loader_llava()
+        return image_loader.llava_process_images()
     elif chosen_model == 'cogvlm':
-        return cogvlm_process_images()
+        image_loader = loader_cogvlm()
+        return image_loader.cogvlm_process_images()
     elif chosen_model == 'salesforce':
-        return salesforce_process_images()
+        image_loader = loader_salesforce()
+        return image_loader.salesforce_process_images()
     else:
         return []
 
@@ -76,19 +77,16 @@ def load_single_document(file_path: Path) -> Document:
 
     document = loader.load()[0]
 
-    metadata = extract_document_metadata(file_path) # get metadata
+    metadata = extract_document_metadata(file_path)
     document.metadata.update(metadata)
-
-    # with open("output_load_single_document.txt", "w", encoding="utf-8") as output_file:
-    # output_file.write(document.page_content)
 
     return document
 
 def load_document_batch(filepaths):
     with ThreadPoolExecutor(len(filepaths)) as exe:
         futures = [exe.submit(load_single_document, name) for name in filepaths]
         data_list = [future.result() for future in futures]
-    return (data_list, filepaths) # "data_list" = list of all document objects created by load single document
+    return (data_list, filepaths)
 
 def load_documents(source_dir: Path) -> list[Document]:
     all_files = list(source_dir.iterdir())
@@ -118,9 +116,9 @@ def load_documents(source_dir: Path) -> list[Document]:
     with open("config.yaml", "r") as config_file:
         config = yaml.safe_load(config_file)
 
-        # Use ProcessPoolExecutor to process images
+        # ProcessPoolExecutor to process images
         with ProcessPoolExecutor(1) as executor:
-            future = executor.submit(process_images_wrapper, config)
+            future = executor.submit(choose_image_loader, config)
             processed_docs = future.result()
             additional_docs = processed_docs if processed_docs is not None else []
 
@@ -137,10 +135,6 @@ def split_documents(documents):
 
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=chunk_size, chunk_overlap=chunk_overlap)
     texts = text_splitter.split_documents(documents)
-
-    # Add 'text' attribute to metadata of each split document
-    #for document in texts:
-        #document.metadata["text"] = document.page_content
 
     my_cprint(f"Number of Chunks: {len(texts)}", "white")
 
@@ -156,9 +150,4 @@ def split_documents(documents):
         count = sum(lower_bound <= size <= upper_bound for size in chunk_sizes)
         my_cprint(f"Chunks between {lower_bound} and {upper_bound} characters: {count}", "white")
 
-    return texts
-
-'''
-# document object structure: Document(page_content="[ALL TEXT EXTRACTED]", metadata={'source': '[FULL FILE PATH WITH DOUBLE BACKSLASHES'})
-# list structure: [Document(page_content="...", metadata={'source': '...'}), Document(page_content="...", metadata={'source': '...'})]
-'''
+    return texts

src/extract_metadata.py

@@ -1,12 +1,20 @@
 import os
 import datetime
+import hashlib
 
-def extract_image_metadata(file_path, file_name):
+def compute_file_hash(file_path):
+    hash_sha256 = hashlib.sha256()
+    with open(file_path, "rb") as f:
+        for chunk in iter(lambda: f.read(4096), b""):
+            hash_sha256.update(chunk)
+    return hash_sha256.hexdigest()
 
+def extract_image_metadata(file_path, file_name):
     file_type = os.path.splitext(file_name)[1]
     file_size = os.path.getsize(file_path)
     creation_date = datetime.datetime.fromtimestamp(os.path.getctime(file_path)).isoformat()
     modification_date = datetime.datetime.fromtimestamp(os.path.getmtime(file_path)).isoformat()
+    file_hash = compute_file_hash(file_path)
 
     return {
         "file_path": file_path,
@@ -15,14 +23,16 @@ def extract_image_metadata(file_path, file_name):
         "file_size": file_size,
         "creation_date": creation_date,
         "modification_date": modification_date,
-        "image": "True"
+        "document_type": "image",
+        "hash": file_hash
     }
 
 def extract_document_metadata(file_path):
     file_type = os.path.splitext(file_path)[1]
     file_size = os.path.getsize(file_path)
     creation_date = datetime.datetime.fromtimestamp(os.path.getctime(file_path)).isoformat()
     modification_date = datetime.datetime.fromtimestamp(os.path.getmtime(file_path)).isoformat()
+    file_hash = compute_file_hash(file_path)
 
     return {
         "file_path": str(file_path),
@@ -31,5 +41,6 @@ def extract_document_metadata(file_path):
         "file_size": file_size,
         "creation_date": creation_date,
         "modification_date": modification_date,
-        "image": "False"
-    }
+        "document_type": "document",
+        "hash": file_hash
+    }

src/gui_tabs_settings_database_query.py

@@ -13,6 +13,7 @@ def __init__(self):
             self.database_creation_device = config_data['Compute_Device']['database_creation']
             self.database_query_device = config_data['Compute_Device']['database_query']
             self.search_term = config_data['database'].get('search_term', '')
+            self.document_type = config_data['database'].get('document_types', '')
 
         v_layout = QVBoxLayout()
         h_layout_device = QHBoxLayout()
@@ -64,7 +65,17 @@ def __init__(self):
         h_layout_search_term.addWidget(self.filter_button)
 
         self.file_type_combo = QComboBox()
-        self.file_type_combo.addItems(["All Files", "Images Only", "Non-Images Only"])
+        file_type_items = ["All Files", "Images Only", "Documents Only"]
+        self.file_type_combo.addItems(file_type_items)
+
+        if self.document_type == 'image':
+            default_index = file_type_items.index("Images Only")
+        elif self.document_type == 'document':
+            default_index = file_type_items.index("Documents Only")
+        else:
+            default_index = file_type_items.index("All Files")
+        self.file_type_combo.setCurrentIndex(default_index)
+
         h_layout_search_term.addWidget(self.file_type_combo)
 
         v_layout.addLayout(h_layout_search_term)
@@ -106,16 +117,16 @@ def update_config(self):
 
         file_type_map = {
             "All Files": '',
-            "Images Only": True,
-            "Non-Images Only": False
+            "Images Only": 'image',
+            "Documents Only": 'document'
         }
 
         file_type_selection = self.file_type_combo.currentText()
-        images_only_value = file_type_map[file_type_selection]
+        document_type_value = file_type_map[file_type_selection]
 
-        if images_only_value != config_data['database'].get('images_only', ''):
+        if document_type_value != config_data['database'].get('document_types', ''):
             settings_changed = True
-            config_data['database']['images_only'] = images_only_value
+            config_data['database']['document_types'] = document_type_value
 
         if settings_changed:
             with open('config.yaml', 'w') as f:

src/gui_tabs_settings_whisper.py

@@ -57,7 +57,7 @@ def create_layout(self):
         model_label = QLabel("Model")
         layout.addWidget(model_label, 0, 0)
         self.model_combo = QComboBox()
-        self.model_combo.addItems(["tiny", "tiny.en", "base", "base.en", "small", "small.en", "medium", "medium.en", "large-v2"])
+        self.model_combo.addItems(["whisper-tiny.en", "whisper-base.en", "whisper-small.en", "whisper-medium.en", "whisper-large-v2"])
         layout.addWidget(self.model_combo, 0, 1)
 
         # Quantization
@@ -116,12 +116,3 @@ def update_config(self):
                 yaml.dump(config_data, f)
 
         return settings_changed
-
-if __name__ == "__main__":
-    from PySide6.QtWidgets import QApplication
-    import sys
-
-    app = QApplication(sys.argv)
-    transcriber_settings_tab = TranscriberSettingsTab()
-    transcriber_settings_tab.show()
-    sys.exit(app.exec())

src/gui_tabs_tools_transcribe.py

@@ -5,7 +5,6 @@
 from PySide6.QtCore import Qt
 import yaml
 from pathlib import Path
-from constants import WHISPER_MODEL_NAMES
 from transcribe_module import TranscribeFile
 import threading
 
@@ -38,7 +37,7 @@ def create_layout(self):
         hbox1 = QHBoxLayout()
         hbox1.addWidget(QLabel("Model"))
         self.model_combo = QComboBox()
-        self.model_combo.addItems([model for model in WHISPER_MODEL_NAMES if model not in ["tiny", "tiny.en", "base", "base.en"]])
+        self.model_combo.addItems(["whisper-small.en", "whisper-medium.en", "whisper-large-v2"])
         self.model_combo.setCurrentText(self.default_model)
         self.model_combo.currentTextChanged.connect(self.update_model_in_config)
         hbox1.addWidget(self.model_combo)
@@ -73,7 +72,7 @@ def create_layout(self):
 
         main_layout.addLayout(hbox2)
 
-        # Third row of widgets (Select Audio File and Transcribe buttons)
+        # Third row of widgets
         hbox3 = QHBoxLayout()
         self.select_file_button = QPushButton("Select Audio File")
         self.select_file_button.clicked.connect(self.select_audio_file)
@@ -85,7 +84,6 @@ def create_layout(self):
 
         main_layout.addLayout(hbox3)
 
-        # Label for displaying the selected file path
         self.file_path_label = QLabel("No file currently selected")
         main_layout.addWidget(self.file_path_label)