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# Import_Functionality.py
# Functionality to import content into the DB
#
# Imports
from datetime import datetime
from time import sleep
import logging
import re
import shutil
import tempfile
import os
from pathlib import Path
import sqlite3
import traceback
from typing import Optional, List, Dict, Tuple
import uuid
import zipfile
#
# External Imports
import gradio as gr
from chardet import detect
#
# Local Imports
from App_Function_Libraries.DB.DB_Manager import insert_prompt_to_db, import_obsidian_note_to_db, \
add_media_to_database, list_prompts
from App_Function_Libraries.Prompt_Handling import import_prompt_from_file, import_prompts_from_zip#
from App_Function_Libraries.Summarization.Summarization_General_Lib import perform_summarization
#
###################################################################################################################
#
# Functions:
logger = logging.getLogger()
def import_data(file, title, author, keywords, custom_prompt, summary, auto_summarize, api_name, api_key):
logging.debug(f"Starting import_data with file: {file} / Title: {title} / Author: {author} / Keywords: {keywords}")
if file is None:
return "No file uploaded. Please upload a file."
try:
logging.debug(f"File object type: {type(file)}")
logging.debug(f"File object attributes: {dir(file)}")
if hasattr(file, 'name'):
file_name = file.name
else:
file_name = 'unknown_file'
# Create a temporary file
with tempfile.NamedTemporaryFile(mode='w+', delete=False, suffix='.txt', encoding='utf-8') as temp_file:
if isinstance(file, str):
# If file is a string, it's likely file content
temp_file.write(file)
elif hasattr(file, 'read'):
# If file has a 'read' method, it's likely a file-like object
content = file.read()
if isinstance(content, bytes):
content = content.decode('utf-8')
temp_file.write(content)
else:
# If it's neither a string nor a file-like object, try converting it to a string
temp_file.write(str(file))
temp_file.seek(0)
file_content = temp_file.read()
logging.debug(f"File name: {file_name}")
logging.debug(f"File content (first 100 chars): {file_content[:100]}")
# Create info_dict
info_dict = {
'title': title or 'Untitled',
'uploader': author or 'Unknown',
}
# FIXME - Add chunking support... I added chapter chunking specifically for this...
# Create segments (assuming one segment for the entire content)
segments = [{'Text': file_content}]
# Process keywords
keyword_list = [kw.strip() for kw in keywords.split(',') if kw.strip()] if keywords else []
# Handle summarization
if auto_summarize and api_name and api_key:
summary = perform_summarization(api_name, file_content, custom_prompt, api_key)
elif not summary:
summary = "No summary provided"
# Add to database
result = add_media_to_database(
url=file_name, # Using filename as URL
info_dict=info_dict,
segments=segments,
summary=summary,
keywords=keyword_list,
custom_prompt_input=custom_prompt,
whisper_model="Imported", # Indicating this was an imported file
media_type="document",
overwrite=False # Set this to True if you want to overwrite existing entries
)
# Clean up the temporary file
os.unlink(temp_file.name)
return f"File '{file_name}' import attempt complete. Database result: {result}"
except Exception as e:
logging.exception(f"Error importing file: {str(e)}")
return f"Error importing file: {str(e)}"
def process_obsidian_zip(zip_file):
with tempfile.TemporaryDirectory() as temp_dir:
try:
with zipfile.ZipFile(zip_file, 'r') as zip_ref:
zip_ref.extractall(temp_dir)
imported_files, total_files, errors = import_obsidian_vault(temp_dir)
return imported_files, total_files, errors
except zipfile.BadZipFile:
error_msg = "The uploaded file is not a valid zip file."
logger.error(error_msg)
return 0, 0, [error_msg]
except Exception as e:
error_msg = f"Error processing zip file: {str(e)}\n{traceback.format_exc()}"
logger.error(error_msg)
return 0, 0, [error_msg]
finally:
shutil.rmtree(temp_dir, ignore_errors=True)
def scan_obsidian_vault(vault_path):
markdown_files = []
for root, dirs, files in os.walk(vault_path):
for file in files:
if file.endswith('.md'):
markdown_files.append(os.path.join(root, file))
return markdown_files
def parse_obsidian_note(file_path):
with open(file_path, 'r', encoding='utf-8') as file:
content = file.read()
frontmatter = {}
frontmatter_match = re.match(r'^---\s*\n(.*?)\n---\s*\n', content, re.DOTALL)
if frontmatter_match:
frontmatter_text = frontmatter_match.group(1)
import yaml
frontmatter = yaml.safe_load(frontmatter_text)
content = content[frontmatter_match.end():]
tags = re.findall(r'#(\w+)', content)
links = re.findall(r'\[\[(.*?)\]\]', content)
return {
'title': os.path.basename(file_path).replace('.md', ''),
'content': content,
'frontmatter': frontmatter,
'tags': tags,
'links': links,
'file_path': file_path # Add this line
}
def create_import_single_prompt_tab():
with gr.TabItem("Import a Prompt", visible=True):
gr.Markdown("# Import a prompt into the database")
with gr.Row():
with gr.Column():
import_file = gr.File(label="Upload file for import", file_types=["txt", "md"])
title_input = gr.Textbox(label="Title", placeholder="Enter the title of the content")
author_input = gr.Textbox(label="Author", placeholder="Enter the author's name")
system_input = gr.Textbox(label="System", placeholder="Enter the system message for the prompt", lines=3)
user_input = gr.Textbox(label="User", placeholder="Enter the user message for the prompt", lines=3)
keywords_input = gr.Textbox(label="Keywords", placeholder="Enter keywords separated by commas")
import_button = gr.Button("Import Prompt")
with gr.Column():
import_output = gr.Textbox(label="Import Status")
save_button = gr.Button("Save to Database")
save_output = gr.Textbox(label="Save Status")
def handle_import(file):
result = import_prompt_from_file(file)
if isinstance(result, tuple) and len(result) == 5:
title, author, system, user, keywords = result
return gr.update(value="File successfully imported. You can now edit the content before saving."), \
gr.update(value=title), gr.update(value=author), gr.update(value=system), \
gr.update(value=user), gr.update(value=", ".join(keywords))
else:
return gr.update(value=result), gr.update(), gr.update(), gr.update(), gr.update(), gr.update()
import_button.click(
fn=handle_import,
inputs=[import_file],
outputs=[import_output, title_input, author_input, system_input, user_input, keywords_input]
)
def save_prompt_to_db(title, author, system, user, keywords):
keyword_list = [k.strip() for k in keywords.split(',') if k.strip()]
return insert_prompt_to_db(title, author, system, user, keyword_list)
save_button.click(
fn=save_prompt_to_db,
inputs=[title_input, author_input, system_input, user_input, keywords_input],
outputs=save_output
)
def create_import_item_tab():
with gr.TabItem("Import Markdown/Text Files", visible=True):
gr.Markdown("# Import a markdown file or text file into the database")
gr.Markdown("...and have it tagged + summarized")
with gr.Row():
with gr.Column():
import_file = gr.File(label="Upload file for import", file_types=["txt", "md"])
title_input = gr.Textbox(label="Title", placeholder="Enter the title of the content")
author_input = gr.Textbox(label="Author", placeholder="Enter the author's name")
keywords_input = gr.Textbox(label="Keywords", placeholder="Enter keywords, comma-separated")
custom_prompt_input = gr.Textbox(label="Custom Prompt",
placeholder="Enter a custom prompt for summarization (optional)")
summary_input = gr.Textbox(label="Summary",
placeholder="Enter a summary or leave blank for auto-summarization", lines=3)
auto_summarize_checkbox = gr.Checkbox(label="Auto-summarize", value=False)
api_name_input = gr.Dropdown(
choices=[None, "Local-LLM", "OpenAI", "Anthropic", "Cohere", "Groq", "DeepSeek", "Mistral", "OpenRouter",
"Llama.cpp", "Kobold", "Ooba", "Tabbyapi", "VLLM","ollama", "HuggingFace", "Custom-OpenAI-API"],
label="API for Auto-summarization"
)
api_key_input = gr.Textbox(label="API Key", type="password")
with gr.Column():
import_button = gr.Button("Import Data")
import_output = gr.Textbox(label="Import Status")
import_button.click(
fn=import_data,
inputs=[import_file, title_input, author_input, keywords_input, custom_prompt_input,
summary_input, auto_summarize_checkbox, api_name_input, api_key_input],
outputs=import_output
)
def create_import_multiple_prompts_tab():
with gr.TabItem("Import Multiple Prompts", visible=True):
gr.Markdown("# Import multiple prompts into the database")
gr.Markdown("Upload a zip file containing multiple prompt files (txt or md)")
# Initialize state variables for pagination
current_page_state = gr.State(value=1)
total_pages_state = gr.State(value=1)
with gr.Row():
with gr.Column():
zip_file = gr.File(label="Upload zip file for import", file_types=["zip"])
import_button = gr.Button("Import Prompts")
prompts_dropdown = gr.Dropdown(label="Select Prompt to Edit", choices=[])
prev_page_button = gr.Button("Previous Page", visible=False)
page_display = gr.Markdown("Page 1 of X", visible=False)
next_page_button = gr.Button("Next Page", visible=False)
title_input = gr.Textbox(label="Title", placeholder="Enter the title of the content")
author_input = gr.Textbox(label="Author", placeholder="Enter the author's name")
system_input = gr.Textbox(label="System", placeholder="Enter the system message for the prompt",
lines=3)
user_input = gr.Textbox(label="User", placeholder="Enter the user message for the prompt", lines=3)
keywords_input = gr.Textbox(label="Keywords", placeholder="Enter keywords separated by commas")
with gr.Column():
import_output = gr.Textbox(label="Import Status")
save_button = gr.Button("Save to Database")
save_output = gr.Textbox(label="Save Status")
prompts_display = gr.Textbox(label="Identified Prompts")
# State to store imported prompts
zip_import_state = gr.State([])
# Function to handle zip import
def handle_zip_import(zip_file):
result = import_prompts_from_zip(zip_file)
if isinstance(result, list):
prompt_titles = [prompt['title'] for prompt in result]
return gr.update(
value="Zip file successfully imported. Select a prompt to edit from the dropdown."), prompt_titles, gr.update(
value="\n".join(prompt_titles)), result
else:
return gr.update(value=result), [], gr.update(value=""), []
import_button.click(
fn=handle_zip_import,
inputs=[zip_file],
outputs=[import_output, prompts_dropdown, prompts_display, zip_import_state]
)
# Function to handle prompt selection from imported prompts
def handle_prompt_selection(selected_title, prompts):
selected_prompt = next((prompt for prompt in prompts if prompt['title'] == selected_title), None)
if selected_prompt:
return (
selected_prompt['title'],
selected_prompt.get('author', ''),
selected_prompt['system'],
selected_prompt.get('user', ''),
", ".join(selected_prompt.get('keywords', []))
)
else:
return "", "", "", "", ""
zip_import_state = gr.State([])
import_button.click(
fn=handle_zip_import,
inputs=[zip_file],
outputs=[import_output, prompts_dropdown, prompts_display, zip_import_state]
)
prompts_dropdown.change(
fn=handle_prompt_selection,
inputs=[prompts_dropdown, zip_import_state],
outputs=[title_input, author_input, system_input, user_input, keywords_input]
)
# Function to save prompt to the database
def save_prompt_to_db(title, author, system, user, keywords):
keyword_list = [k.strip() for k in keywords.split(',') if k.strip()]
result = insert_prompt_to_db(title, author, system, user, keyword_list)
return result
save_button.click(
fn=save_prompt_to_db,
inputs=[title_input, author_input, system_input, user_input, keywords_input],
outputs=[save_output]
)
# Adding pagination controls to navigate prompts in the database
def on_prev_page_click(current_page, total_pages):
new_page = max(current_page - 1, 1)
prompts, total_pages, current_page = list_prompts(page=new_page, per_page=10)
page_display_text = f"Page {current_page} of {total_pages}"
return (
gr.update(choices=prompts),
gr.update(value=page_display_text),
current_page
)
def on_next_page_click(current_page, total_pages):
new_page = min(current_page + 1, total_pages)
prompts, total_pages, current_page = list_prompts(page=new_page, per_page=10)
page_display_text = f"Page {current_page} of {total_pages}"
return (
gr.update(choices=prompts),
gr.update(value=page_display_text),
current_page
)
prev_page_button.click(
fn=on_prev_page_click,
inputs=[current_page_state, total_pages_state],
outputs=[prompts_dropdown, page_display, current_page_state]
)
next_page_button.click(
fn=on_next_page_click,
inputs=[current_page_state, total_pages_state],
outputs=[prompts_dropdown, page_display, current_page_state]
)
# Function to update prompts dropdown after saving to the database
def update_prompt_dropdown():
prompts, total_pages, current_page = list_prompts(page=1, per_page=10)
page_display_text = f"Page {current_page} of {total_pages}"
return (
gr.update(choices=prompts),
gr.update(visible=True),
gr.update(value=page_display_text, visible=True),
current_page,
total_pages
)
# Update the dropdown after saving
save_button.click(
fn=update_prompt_dropdown,
inputs=[],
outputs=[prompts_dropdown, prev_page_button, page_display, current_page_state, total_pages_state]
)
def create_import_obsidian_vault_tab():
with gr.TabItem("Import Obsidian Vault", visible=True):
gr.Markdown("## Import Obsidian Vault")
with gr.Row():
with gr.Column():
vault_path_input = gr.Textbox(label="Obsidian Vault Path (Local)")
vault_zip_input = gr.File(label="Upload Obsidian Vault (Zip)")
with gr.Column():
import_vault_button = gr.Button("Import Obsidian Vault")
import_status = gr.Textbox(label="Import Status", interactive=False)
def import_vault(vault_path, vault_zip):
if vault_zip:
imported, total, errors = process_obsidian_zip(vault_zip.name)
elif vault_path:
imported, total, errors = import_obsidian_vault(vault_path)
else:
return "Please provide either a local vault path or upload a zip file."
status = f"Imported {imported} out of {total} files.\n"
if errors:
status += f"Encountered {len(errors)} errors:\n" + "\n".join(errors)
return status
import_vault_button.click(
fn=import_vault,
inputs=[vault_path_input, vault_zip_input],
outputs=[import_status],
)
def import_obsidian_vault(vault_path, progress=gr.Progress()):
try:
markdown_files = scan_obsidian_vault(vault_path)
total_files = len(markdown_files)
imported_files = 0
errors = []
for i, file_path in enumerate(markdown_files):
try:
note_data = parse_obsidian_note(file_path)
success, error_msg = import_obsidian_note_to_db(note_data)
if success:
imported_files += 1
else:
errors.append(error_msg)
except Exception as e:
error_msg = f"Error processing {file_path}: {str(e)}"
logger.error(error_msg)
errors.append(error_msg)
progress((i + 1) / total_files, f"Imported {imported_files} of {total_files} files")
sleep(0.1) # Small delay to prevent UI freezing
return imported_files, total_files, errors
except Exception as e:
error_msg = f"Error scanning vault: {str(e)}\n{traceback.format_exc()}"
logger.error(error_msg)
return 0, 0, [error_msg]
class RAGQABatchImporter:
def __init__(self, db_path: str):
self.db_path = Path(db_path)
self.setup_logging()
self.file_processor = FileProcessor()
self.zip_validator = ZipValidator()
def setup_logging(self):
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(levelname)s - %(message)s',
handlers=[
logging.FileHandler('rag_qa_import.log'),
logging.StreamHandler()
]
)
def process_markdown_content(self, content: str) -> List[Dict[str, str]]:
"""Process markdown content into a conversation format."""
messages = []
sections = content.split('\n\n')
for section in sections:
if section.strip():
messages.append({
'role': 'user',
'content': section.strip()
})
return messages
def process_keywords(self, db: sqlite3.Connection, conversation_id: str, keywords: str):
"""Process and link keywords to a conversation."""
if not keywords:
return
keyword_list = [k.strip() for k in keywords.split(',')]
for keyword in keyword_list:
# Insert keyword if it doesn't exist
db.execute("""
INSERT OR IGNORE INTO rag_qa_keywords (keyword)
VALUES (?)
""", (keyword,))
# Get keyword ID
keyword_id = db.execute("""
SELECT id FROM rag_qa_keywords WHERE keyword = ?
""", (keyword,)).fetchone()[0]
# Link keyword to conversation
db.execute("""
INSERT INTO rag_qa_conversation_keywords
(conversation_id, keyword_id)
VALUES (?, ?)
""", (conversation_id, keyword_id))
def import_single_file(
self,
db: sqlite3.Connection,
content: str,
filename: str,
keywords: str,
custom_prompt: Optional[str] = None,
rating: Optional[int] = None
) -> str:
"""Import a single file's content into the database"""
conversation_id = str(uuid.uuid4())
current_time = datetime.now().isoformat()
# Process filename into title
title = FileProcessor.process_filename_to_title(filename)
if title.lower().endswith(('.md', '.txt')):
title = title[:-3] if title.lower().endswith('.md') else title[:-4]
# Insert conversation metadata
db.execute("""
INSERT INTO conversation_metadata
(conversation_id, created_at, last_updated, title, rating)
VALUES (?, ?, ?, ?, ?)
""", (conversation_id, current_time, current_time, title, rating))
# Process content and insert messages
messages = self.process_markdown_content(content)
for msg in messages:
db.execute("""
INSERT INTO rag_qa_chats
(conversation_id, timestamp, role, content)
VALUES (?, ?, ?, ?)
""", (conversation_id, current_time, msg['role'], msg['content']))
# Process keywords
self.process_keywords(db, conversation_id, keywords)
return conversation_id
def extract_zip(self, zip_path: str) -> List[Tuple[str, str]]:
"""Extract and validate files from zip"""
is_valid, error_msg, valid_files = self.zip_validator.validate_zip_file(zip_path)
if not is_valid:
raise ValueError(error_msg)
files = []
with zipfile.ZipFile(zip_path, 'r') as zip_ref:
for filename in valid_files:
with zip_ref.open(filename) as f:
content = f.read()
# Try to decode with detected encoding
try:
detected_encoding = detect(content)['encoding'] or 'utf-8'
content = content.decode(detected_encoding)
except UnicodeDecodeError:
content = content.decode('utf-8', errors='replace')
filename = os.path.basename(filename)
files.append((filename, content))
return files
def import_files(
self,
files: List[str],
keywords: str = "",
custom_prompt: Optional[str] = None,
rating: Optional[int] = None,
progress=gr.Progress()
) -> Tuple[bool, str]:
"""Import multiple files or zip files into the RAG QA database."""
try:
imported_files = []
with sqlite3.connect(self.db_path) as db:
# Process each file
for file_path in progress.tqdm(files, desc="Processing files"):
filename = os.path.basename(file_path)
# Handle zip files
if filename.lower().endswith('.zip'):
zip_files = self.extract_zip(file_path)
for zip_filename, content in progress.tqdm(zip_files, desc=f"Processing files from {filename}"):
conv_id = self.import_single_file(
db=db,
content=content,
filename=zip_filename,
keywords=keywords,
custom_prompt=custom_prompt,
rating=rating
)
imported_files.append(zip_filename)
# Handle individual markdown/text files
elif filename.lower().endswith(('.md', '.txt')):
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
conv_id = self.import_single_file(
db=db,
content=content,
filename=filename,
keywords=keywords,
custom_prompt=custom_prompt,
rating=rating
)
imported_files.append(filename)
db.commit()
return True, f"Successfully imported {len(imported_files)} files:\n" + "\n".join(imported_files)
except Exception as e:
logging.error(f"Import failed: {str(e)}")
return False, f"Import failed: {str(e)}"
class FileProcessor:
"""Handles file reading and name processing"""
VALID_EXTENSIONS = {'.md', '.txt', '.zip'}
ENCODINGS_TO_TRY = [
'utf-8',
'utf-16',
'windows-1252',
'iso-8859-1',
'ascii'
]
@staticmethod
def detect_encoding(file_path: str) -> str:
"""Detect the file encoding using chardet"""
with open(file_path, 'rb') as file:
raw_data = file.read()
result = detect(raw_data)
return result['encoding'] or 'utf-8'
@staticmethod
def read_file_content(file_path: str) -> str:
"""Read file content with automatic encoding detection"""
detected_encoding = FileProcessor.detect_encoding(file_path)
# Try detected encoding first
try:
with open(file_path, 'r', encoding=detected_encoding) as f:
return f.read()
except UnicodeDecodeError:
# If detected encoding fails, try others
for encoding in FileProcessor.ENCODINGS_TO_TRY:
try:
with open(file_path, 'r', encoding=encoding) as f:
return f.read()
except UnicodeDecodeError:
continue
# If all encodings fail, use utf-8 with error handling
with open(file_path, 'r', encoding='utf-8', errors='replace') as f:
return f.read()
@staticmethod
def process_filename_to_title(filename: str) -> str:
"""Convert filename to a readable title"""
# Remove extension
name = os.path.splitext(filename)[0]
# Look for date patterns
date_pattern = r'(\d{4}[-_]?\d{2}[-_]?\d{2})'
date_match = re.search(date_pattern, name)
date_str = ""
if date_match:
try:
date = datetime.strptime(date_match.group(1).replace('_', '-'), '%Y-%m-%d')
date_str = date.strftime("%b %d, %Y")
name = name.replace(date_match.group(1), '').strip('-_')
except ValueError:
pass
# Replace separators with spaces
name = re.sub(r'[-_]+', ' ', name)
# Remove redundant spaces
name = re.sub(r'\s+', ' ', name).strip()
# Capitalize words, excluding certain words
exclude_words = {'a', 'an', 'the', 'in', 'on', 'at', 'to', 'for', 'of', 'with'}
words = name.split()
capitalized = []
for i, word in enumerate(words):
if i == 0 or word not in exclude_words:
capitalized.append(word.capitalize())
else:
capitalized.append(word.lower())
name = ' '.join(capitalized)
# Add date if found
if date_str:
name = f"{name} - {date_str}"
return name
class ZipValidator:
"""Validates zip file contents and structure"""
MAX_ZIP_SIZE = 100 * 1024 * 1024 # 100MB
MAX_FILES = 100
VALID_EXTENSIONS = {'.md', '.txt'}
@staticmethod
def validate_zip_file(zip_path: str) -> Tuple[bool, str, List[str]]:
"""
Validate zip file and its contents
Returns: (is_valid, error_message, valid_files)
"""
try:
# Check zip file size
if os.path.getsize(zip_path) > ZipValidator.MAX_ZIP_SIZE:
return False, "Zip file too large (max 100MB)", []
valid_files = []
with zipfile.ZipFile(zip_path, 'r') as zip_ref:
# Check number of files
if len(zip_ref.filelist) > ZipValidator.MAX_FILES:
return False, f"Too many files in zip (max {ZipValidator.MAX_FILES})", []
# Check for directory traversal attempts
for file_info in zip_ref.filelist:
if '..' in file_info.filename or file_info.filename.startswith('/'):
return False, "Invalid file paths detected", []
# Validate each file
total_size = 0
for file_info in zip_ref.filelist:
# Skip directories
if file_info.filename.endswith('/'):
continue
# Check file size
if file_info.file_size > ZipValidator.MAX_ZIP_SIZE:
return False, f"File {file_info.filename} too large", []
total_size += file_info.file_size
if total_size > ZipValidator.MAX_ZIP_SIZE:
return False, "Total uncompressed size too large", []
# Check file extension
ext = os.path.splitext(file_info.filename)[1].lower()
if ext in ZipValidator.VALID_EXTENSIONS:
valid_files.append(file_info.filename)
if not valid_files:
return False, "No valid markdown or text files found in zip", []
return True, "", valid_files
except zipfile.BadZipFile:
return False, "Invalid or corrupted zip file", []
except Exception as e:
return False, f"Error processing zip file: {str(e)}", []
def create_conversation_import_tab() -> gr.Tab:
"""Create the import tab for the Gradio interface"""
with gr.Tab("Import RAG Chats") as tab:
gr.Markdown("# Import RAG Chats into the Database")
gr.Markdown("""
Import your RAG Chat markdown/text files individually or as a zip archive
Supported file types:
- Markdown (.md)
- Text (.txt)
- Zip archives containing .md or .txt files
Maximum zip file size: 100MB
Maximum files per zip: 100
""")
with gr.Row():
with gr.Column():
import_files = gr.File(
label="Upload Files",
file_types=["txt", "md", "zip"],
file_count="multiple"
)
keywords_input = gr.Textbox(
label="Keywords",
placeholder="Enter keywords to apply to all imported files (comma-separated)"
)
custom_prompt_input = gr.Textbox(
label="Custom Prompt",
placeholder="Enter a custom prompt for processing (optional)"
)
rating_input = gr.Slider(
minimum=1,
maximum=3,
step=1,
label="Rating (1-3)",
value=None
)
with gr.Column():
import_button = gr.Button("Import Files")
import_output = gr.Textbox(
label="Import Status",
lines=10
)
def handle_import(files, keywords, custom_prompt, rating):
importer = RAGQABatchImporter("rag_qa.db") # Update with your DB path
success, message = importer.import_files(
files=[f.name for f in files],
keywords=keywords,
custom_prompt=custom_prompt,
rating=rating
)
return message
import_button.click(
fn=handle_import,
inputs=[
import_files,
keywords_input,
custom_prompt_input,
rating_input
],
outputs=import_output
)
return tab
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