feat(batch_upload): 添加批量上传和处理文件功能,支持文件记录管理,优化API交互和错误处理逻辑(并发访问Milvus)
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scripts/batch_upload.py
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316
scripts/batch_upload.py
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@ -0,0 +1,316 @@
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import asyncio
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import hashlib
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import json
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import pathlib
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import httpx
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import typer
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from rich.console import Console
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from rich.progress import Progress, SpinnerColumn, BarColumn, TextColumn, TimeElapsedColumn
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app = typer.Typer()
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console = Console()
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async def login(client: httpx.AsyncClient, base_url: str, username: str, password: str) -> str | None:
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"""Logs in to the API and returns the access token."""
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try:
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response = await client.post(
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f"{base_url}/auth/token",
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data={"username": username, "password": password},
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)
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response.raise_for_status()
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return response.json().get("access_token")
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except httpx.HTTPStatusError as e:
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console.print(f"[bold red]Login failed: {e.response.status_code} - {e.response.text}[/bold red]")
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return None
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except httpx.RequestError as e:
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console.print(f"[bold red]Login request failed: {e}[/bold red]")
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return None
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async def upload_file(
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client: httpx.AsyncClient,
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base_url: str,
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db_id: str,
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file_path: pathlib.Path,
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) -> str | None:
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"""Uploads a single file and returns its server-side path."""
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try:
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with open(file_path, "rb") as f:
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files = {"file": (file_path.name, f, "application/octet-stream")}
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response = await client.post(
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f"{base_url}/knowledge/files/upload",
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params={"db_id": db_id},
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files=files,
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timeout=300, # 5 minutes timeout for large files
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)
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response.raise_for_status()
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return response.json().get("file_path")
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except httpx.HTTPStatusError as e:
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console.print(f"[bold red]Failed to upload {file_path.name}: {e.response.status_code} - {e.response.text}[/bold red]")
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return None
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except httpx.RequestError as e:
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console.print(f"[bold red]Failed to upload {file_path.name}: {e}[/bold red]")
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return None
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async def process_document(
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client: httpx.AsyncClient,
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base_url: str,
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db_id: str,
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server_file_path: str,
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) -> bool:
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"""Triggers the processing of an uploaded file in the knowledge base."""
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try:
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response = await client.post(
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f"{base_url}/knowledge/databases/{db_id}/documents",
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json={"items": [server_file_path], "params": {"content_type": "file"}},
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timeout=600, # 10 minutes timeout for processing
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)
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response.raise_for_status()
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result = response.json()
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# Check if the overall request was successful
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if result.get("status") != "success":
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console.print(f"[bold yellow]Processing warning for {server_file_path}: {result.get('message')}[/bold yellow]")
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return False
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# Check the specific file's processing status in the items array
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items = result.get("items", [])
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if not items:
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console.print(f"[bold red]No processing result for {server_file_path}[/bold red]")
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return False
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# Since we only sent one file, check the first item
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item = items[0]
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# Check for both 'success' and 'done' status (different APIs might use different status values)
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if item.get("status") in ["success", "done"]:
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return True
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else:
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# Get more detailed error information
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error_msg = item.get("message", "")
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error_detail = item.get("detail", "")
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error_reason = item.get("reason", "")
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# Combine all available error information
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error_info = []
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if error_msg:
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error_info.append(error_msg)
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if error_detail:
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error_info.append(error_detail)
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if error_reason:
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error_info.append(error_reason)
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if not error_info:
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error_info = ["Unknown error"]
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full_error = " | ".join(error_info)
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console.print(f"[bold red]Failed to process {server_file_path}: {full_error}[/bold red]")
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# Also log the full item for debugging
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console.print(f"[dim]Debug - Full item response: {item}[/dim]")
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return False
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except httpx.HTTPStatusError as e:
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console.print(f"[bold red]Failed to process {server_file_path}: {e.response.status_code} - {e.response.text}[/bold red]")
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return False
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except httpx.RequestError as e:
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console.print(f"[bold red]Failed to process {server_file_path}: {e}[/bold red]")
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return False
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async def worker(
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semaphore: asyncio.Semaphore,
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client: httpx.AsyncClient,
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base_url: str,
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db_id: str,
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file_path: pathlib.Path,
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file_hash: str,
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progress: Progress,
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upload_task_id: int,
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process_task_id: int,
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):
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"""A worker task that uploads and then processes a single file."""
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async with semaphore:
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# 1. Upload file
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server_file_path = await upload_file(client, base_url, db_id, file_path)
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progress.update(upload_task_id, advance=1, postfix=f"Uploaded {file_path.name}")
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if not server_file_path:
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progress.update(process_task_id, advance=1) # Mark as processed to not hang the progress bar
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return file_path, file_hash, "upload_failed"
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# 2. Process file
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success = await process_document(client, base_url, db_id, server_file_path)
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progress.update(process_task_id, advance=1, postfix=f"Processed {file_path.name}")
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return file_path, file_hash, "success" if success else "processing_failed"
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def get_file_hash(file_path: pathlib.Path) -> str:
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"""Calculate SHA256 hash of a file."""
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hash_sha256 = hashlib.sha256()
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with open(file_path, "rb") as f:
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for chunk in iter(lambda: f.read(4096), b""):
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hash_sha256.update(chunk)
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return hash_sha256.hexdigest()
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def load_processed_files(record_file: pathlib.Path) -> set[str]:
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"""Load the set of processed file hashes from the record file."""
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if not record_file.exists():
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return set()
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try:
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with open(record_file) as f:
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data = json.load(f)
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return set(data.get('processed_files', []))
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except (OSError, json.JSONDecodeError) as e:
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console.print(f"[bold yellow]Warning: Could not load processed files record: {e}[/bold yellow]")
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return set()
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def save_processed_files(record_file: pathlib.Path, processed_files: set[str]):
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"""Save the set of processed file hashes to the record file."""
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# Ensure the directory exists
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record_file.parent.mkdir(parents=True, exist_ok=True)
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try:
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with open(record_file, 'w') as f:
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json.dump({'processed_files': list(processed_files)}, f, indent=2)
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except OSError as e:
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console.print(f"[bold red]Error: Could not save processed files record: {e}[/bold red]")
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@app.command()
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def main(
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db_id: str = typer.Option(..., help="The ID of the knowledge base."),
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directory: pathlib.Path = typer.Option(..., help="The directory containing files to upload.", exists=True, file_okay=False),
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pattern: str = typer.Option("*.md", help="The glob pattern for files to upload (e.g., '*.pdf', '**/*.txt')."),
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base_url: str = typer.Option("http://127.0.0.1:5050", help="The base URL of the API server."),
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username: str = typer.Option(..., help="Admin username for login."),
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password: str = typer.Option(..., help="Admin password for login."),
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concurrency: int = typer.Option(4, help="The number of concurrent upload/process tasks."),
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recursive: bool = typer.Option(False, "--recursive", "-r", help="Search for files recursively in subdirectories."),
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record_file: pathlib.Path = typer.Option("scripts/tmp/batch_processed_files.txt", help="File to store processed files record."),
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):
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"""
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Batch upload and process files into a Yuxi-Know knowledge base.
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"""
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console.print(f"[bold green]Starting batch upload for knowledge base: {db_id}[/bold green]")
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# Load previously processed files
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processed_files = load_processed_files(record_file)
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console.print(f"Loaded {len(processed_files)} previously processed files from record.")
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# Discover files
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glob_method = directory.rglob if recursive else directory.glob
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all_files = list(glob_method(pattern))
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if not all_files:
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console.print(f"[bold yellow]No files found in '{directory}' matching '{pattern}'. Aborting.[/bold yellow]")
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raise typer.Exit()
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# Filter out already processed files
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files_to_upload = []
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skipped_files = []
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for file_path in all_files:
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file_hash = get_file_hash(file_path)
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if file_hash in processed_files:
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skipped_files.append(file_path)
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else:
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files_to_upload.append((file_path, file_hash))
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if not files_to_upload:
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console.print(f"[bold green]All {len(all_files)} files have already been processed. Nothing to do.[/bold green]")
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raise typer.Exit()
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console.print(f"Found {len(all_files)} total files:")
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console.print(f" - [green]New files to process:[/green] {len(files_to_upload)}")
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console.print(f" - [blue]Already processed (skipped):[/blue] {len(skipped_files)}")
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async def run():
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async with httpx.AsyncClient() as client:
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# Login
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token = await login(client, base_url, username, password)
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if not token:
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raise typer.Exit(code=1)
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client.headers = {"Authorization": f"Bearer {token}"}
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# Setup concurrency and tasks
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semaphore = asyncio.Semaphore(concurrency)
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tasks = []
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with Progress(
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SpinnerColumn(),
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TextColumn("[progress.description]{task.description}"),
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BarColumn(),
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TextColumn("[progress.percentage]{task.percentage:>3.0f}%"),
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TimeElapsedColumn(),
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TextColumn("{task.fields[postfix]}"),
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console=console,
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transient=True,
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) as progress:
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upload_task_id = progress.add_task("[bold blue]Uploading...", total=len(files_to_upload), postfix="")
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process_task_id = progress.add_task("[bold cyan]Processing...", total=len(files_to_upload), postfix="")
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for file_path, file_hash in files_to_upload:
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task = asyncio.create_task(
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worker(semaphore, client, base_url, db_id, file_path, file_hash, progress, upload_task_id, process_task_id)
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)
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tasks.append(task)
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results = await asyncio.gather(*tasks)
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# Summarize results and update processed files record
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successful_files = []
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upload_failures = []
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processing_failures = []
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newly_processed_hashes = set()
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for file_path, file_hash, status in results:
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if status == 'success':
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successful_files.append(file_path)
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newly_processed_hashes.add(file_hash)
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elif status == 'upload_failed':
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upload_failures.append(file_path)
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elif status == 'processing_failed':
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processing_failures.append(file_path)
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# Don't add to processed files if processing failed
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# Save newly processed files to record
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if newly_processed_hashes:
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all_processed_files = processed_files | newly_processed_hashes
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save_processed_files(record_file, all_processed_files)
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console.print(f"[bold green]Updated processed files record with {len(newly_processed_hashes)} new entries.[/bold green]")
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console.print("[bold green]Batch operation complete.[/bold green]")
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console.print(f" - [green]Successful:[/green] {len(successful_files)}")
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console.print(f" - [red]Upload Failed:[/red] {len(upload_failures)}")
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if upload_failures:
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for f in upload_failures:
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console.print(f" - {f}")
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console.print(f" - [yellow]Processing Failed:[/yellow] {len(processing_failures)}")
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if processing_failures:
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for f in processing_failures:
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console.print(f" - {f}")
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asyncio.run(run())
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"""
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uv run scripts/batch_upload.py \
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--db-id kb_845a9eedb211b349ddb3127ae9be2bfa \
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--directory data.local/XXXX/ \
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--pattern "*.html" \
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--base-url http://172.19.13.5:5050/api \
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--username zwj \
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--password zwj12138 \
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--concurrency 4 \
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--recursive \
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--record-file scripts/tmp/batch_processed_files.txt
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"""
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if __name__ == "__main__":
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app()
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@ -72,7 +72,7 @@ async def update_database_info(
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"""更新知识库信息"""
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logger.debug(f"Update database {db_id} info: {name}, {description}")
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try:
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database = knowledge_base.update_database(db_id, name, description)
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database = await knowledge_base.update_database(db_id, name, description)
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return {"message": "更新成功", "database": database}
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except Exception as e:
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logger.error(f"更新数据库失败 {e}, {traceback.format_exc()}")
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@ -83,7 +83,7 @@ async def delete_database(db_id: str, current_user: User = Depends(get_admin_use
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"""删除知识库"""
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logger.debug(f"Delete database {db_id}")
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try:
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knowledge_base.delete_database(db_id)
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await knowledge_base.delete_database(db_id)
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# 需要重新加载所有智能体,因为工具刷新了
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from src.agents import agent_manager
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import os
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import json
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import time
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import asyncio
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from typing import Any
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from datetime import datetime
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@ -32,6 +33,9 @@ class KnowledgeBaseManager:
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# 全局数据库元信息 {db_id: metadata_with_kb_type}
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self.global_databases_meta: dict[str, dict] = {}
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# 元数据锁
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self._metadata_lock = asyncio.Lock()
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# 加载全局元数据
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self._load_global_metadata()
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@ -55,16 +59,13 @@ class KnowledgeBaseManager:
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def _save_global_metadata(self):
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"""保存全局元数据"""
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meta_file = os.path.join(self.work_dir, "global_metadata.json")
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try:
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data = {
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"databases": self.global_databases_meta,
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"updated_at": datetime.now().isoformat(),
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"version": "2.0" # 标识新版本
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}
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with open(meta_file, 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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except Exception as e:
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logger.error(f"Failed to save global metadata: {e}")
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data = {
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"databases": self.global_databases_meta,
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"updated_at": datetime.now().isoformat(),
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"version": "2.0"
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}
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with open(meta_file, 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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def _initialize_existing_kbs(self):
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"""初始化已存在的知识库实例"""
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@ -139,7 +140,7 @@ class KnowledgeBaseManager:
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return {"databases": all_databases}
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def create_database(self, database_name: str, description: str, kb_type: str, embed_info: dict | None = None, **kwargs) -> dict:
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async def create_database(self, database_name: str, description: str, kb_type: str, embed_info: dict | None = None, **kwargs) -> dict:
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"""
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创建数据库
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@ -153,48 +154,44 @@ class KnowledgeBaseManager:
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Returns:
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数据库信息字典
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"""
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# 验证知识库类型
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if not KnowledgeBaseFactory.is_type_supported(kb_type):
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available_types = list(KnowledgeBaseFactory.get_available_types().keys())
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raise ValueError(f"Unsupported knowledge base type: {kb_type}. Available types: {available_types}")
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# 获取或创建对应类型的知识库实例
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kb_instance = self._get_or_create_kb_instance(kb_type)
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# 在知识库实例中创建数据库
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db_info = kb_instance.create_database(database_name, description,
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embed_info, **kwargs)
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db_id = db_info["db_id"]
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# 在全局元数据中记录
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self.global_databases_meta[db_id] = {
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"name": database_name,
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"description": description,
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"kb_type": kb_type,
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"created_at": datetime.now().isoformat(),
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"additional_params": kwargs.copy() # 将所有额外参数存储在additional_params中
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}
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self._save_global_metadata()
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async with self._metadata_lock:
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self.global_databases_meta[db_id] = {
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"name": database_name,
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"description": description,
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"kb_type": kb_type,
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"created_at": datetime.now().isoformat(),
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"additional_params": kwargs.copy()
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}
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self._save_global_metadata()
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logger.info(f"Created {kb_type} database: {database_name} ({db_id}) with {kwargs}")
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return db_info
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def delete_database(self, db_id: str) -> dict:
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async def delete_database(self, db_id: str) -> dict:
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"""删除数据库"""
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try:
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kb_instance = self._get_kb_for_database(db_id)
|
||||
result = kb_instance.delete_database(db_id)
|
||||
|
||||
# 从全局元数据中删除
|
||||
if db_id in self.global_databases_meta:
|
||||
del self.global_databases_meta[db_id]
|
||||
self._save_global_metadata()
|
||||
async with self._metadata_lock:
|
||||
if db_id in self.global_databases_meta:
|
||||
del self.global_databases_meta[db_id]
|
||||
self._save_global_metadata()
|
||||
|
||||
return result
|
||||
except KBNotFoundError as e:
|
||||
logger.warning(f"Database {db_id} not found during deletion: {e}")
|
||||
return {"message": "删除成功"} # 兼容性:即使不存在也返回成功
|
||||
return {"message": "删除成功"}
|
||||
|
||||
async def add_content(self, db_id: str, items: list[str], params: dict | None = None) -> list[dict]:
|
||||
"""添加内容(文件/URL)"""
|
||||
@ -253,16 +250,16 @@ class KnowledgeBaseManager:
|
||||
os.makedirs(general_uploads, exist_ok=True)
|
||||
return general_uploads
|
||||
|
||||
def update_database(self, db_id: str, name: str, description: str) -> dict:
|
||||
async def update_database(self, db_id: str, name: str, description: str) -> dict:
|
||||
"""更新数据库"""
|
||||
kb_instance = self._get_kb_for_database(db_id)
|
||||
result = kb_instance.update_database(db_id, name, description)
|
||||
|
||||
# 同时更新全局元数据
|
||||
if db_id in self.global_databases_meta:
|
||||
self.global_databases_meta[db_id]["name"] = name
|
||||
self.global_databases_meta[db_id]["description"] = description
|
||||
self._save_global_metadata()
|
||||
async with self._metadata_lock:
|
||||
if db_id in self.global_databases_meta:
|
||||
self.global_databases_meta[db_id]["name"] = name
|
||||
self.global_databases_meta[db_id]["description"] = description
|
||||
self._save_global_metadata()
|
||||
|
||||
return result
|
||||
|
||||
|
||||
@ -2,6 +2,7 @@ import os
|
||||
import time
|
||||
import traceback
|
||||
import json
|
||||
import asyncio
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
from datetime import datetime
|
||||
@ -54,6 +55,9 @@ class MilvusKB(KnowledgeBase):
|
||||
self.chunk_size = kwargs.get('chunk_size', 1000)
|
||||
self.chunk_overlap = kwargs.get('chunk_overlap', 200)
|
||||
|
||||
# 元数据锁
|
||||
self._metadata_lock = asyncio.Lock()
|
||||
|
||||
# 初始化连接
|
||||
self._init_connection()
|
||||
|
||||
@ -240,64 +244,59 @@ class MilvusKB(KnowledgeBase):
|
||||
processed_items_info = []
|
||||
|
||||
for item in items:
|
||||
# 准备文件元数据
|
||||
metadata = prepare_item_metadata(item, content_type, db_id)
|
||||
file_id = metadata["file_id"]
|
||||
filename = metadata["filename"]
|
||||
|
||||
# 添加文件记录
|
||||
file_record = metadata.copy()
|
||||
del file_record["file_id"] # 从记录中移除file_id,因为它是key
|
||||
self.files_meta[file_id] = file_record
|
||||
self._save_metadata()
|
||||
del file_record["file_id"]
|
||||
async with self._metadata_lock:
|
||||
self.files_meta[file_id] = file_record
|
||||
self._save_metadata()
|
||||
|
||||
# 添加 file_id 到返回数据
|
||||
file_record = file_record.copy()
|
||||
file_record["file_id"] = file_id
|
||||
|
||||
try:
|
||||
# 根据内容类型处理内容
|
||||
if content_type == "file":
|
||||
markdown_content = await self._process_file_to_markdown(item, params=params)
|
||||
else: # URL
|
||||
else:
|
||||
markdown_content = await self._process_url_to_markdown(item, params=params)
|
||||
|
||||
# 分割文本成块
|
||||
chunks = self._split_text_into_chunks(markdown_content, file_id, filename, params)
|
||||
logger.info(f"Split {filename} into {len(chunks)} chunks")
|
||||
|
||||
# 准备 Milvus 插入的数据
|
||||
if chunks:
|
||||
# 生成嵌入向量
|
||||
texts = [chunk["content"] for chunk in chunks]
|
||||
embeddings = await embedding_function(texts)
|
||||
|
||||
# 准备插入数据
|
||||
entities = [
|
||||
[chunk["id"] for chunk in chunks], # id
|
||||
[chunk["content"] for chunk in chunks], # content
|
||||
[chunk["source"] for chunk in chunks], # source
|
||||
[chunk["chunk_id"] for chunk in chunks], # chunk_id
|
||||
[chunk["file_id"] for chunk in chunks], # file_id
|
||||
[chunk["chunk_index"] for chunk in chunks], # chunk_index
|
||||
embeddings # embedding
|
||||
[chunk["id"] for chunk in chunks],
|
||||
[chunk["content"] for chunk in chunks],
|
||||
[chunk["source"] for chunk in chunks],
|
||||
[chunk["chunk_id"] for chunk in chunks],
|
||||
[chunk["file_id"] for chunk in chunks],
|
||||
[chunk["chunk_index"] for chunk in chunks],
|
||||
embeddings
|
||||
]
|
||||
|
||||
# 插入到 Milvus
|
||||
collection.insert(entities)
|
||||
collection.flush()
|
||||
def _insert_and_flush():
|
||||
collection.insert(entities)
|
||||
collection.flush()
|
||||
|
||||
await asyncio.to_thread(_insert_and_flush)
|
||||
|
||||
logger.info(f"Inserted {content_type} {item} into Milvus. Done.")
|
||||
|
||||
# 更新状态为完成
|
||||
self.files_meta[file_id]["status"] = "done"
|
||||
self._save_metadata()
|
||||
async with self._metadata_lock:
|
||||
self.files_meta[file_id]["status"] = "done"
|
||||
self._save_metadata()
|
||||
file_record['status'] = "done"
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"处理{content_type} {item} 失败: {e}, {traceback.format_exc()}")
|
||||
self.files_meta[file_id]["status"] = "failed"
|
||||
self._save_metadata()
|
||||
async with self._metadata_lock:
|
||||
self.files_meta[file_id]["status"] = "failed"
|
||||
self._save_metadata()
|
||||
file_record['status'] = "failed"
|
||||
|
||||
processed_items_info.append(file_record)
|
||||
@ -367,21 +366,25 @@ class MilvusKB(KnowledgeBase):
|
||||
async def delete_file(self, db_id: str, file_id: str) -> None:
|
||||
"""删除文件"""
|
||||
collection = await self._get_milvus_collection(db_id)
|
||||
if collection:
|
||||
|
||||
def _delete_from_milvus():
|
||||
"""同步执行 Milvus 删除操作的辅助函数"""
|
||||
try:
|
||||
# 删除所有相关chunks
|
||||
expr = f'file_id == "{file_id}"'
|
||||
collection.delete(expr)
|
||||
collection.flush()
|
||||
logger.info(f"Deleted chunks for file {file_id} from Milvus")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error deleting file {file_id} from Milvus: {e}")
|
||||
|
||||
# 删除文件记录
|
||||
if file_id in self.files_meta:
|
||||
del self.files_meta[file_id]
|
||||
self._save_metadata()
|
||||
if collection:
|
||||
await asyncio.to_thread(_delete_from_milvus)
|
||||
|
||||
# 使用锁确保元数据操作的原子性
|
||||
async with self._metadata_lock:
|
||||
if file_id in self.files_meta:
|
||||
del self.files_meta[file_id]
|
||||
self._save_metadata()
|
||||
|
||||
async def get_file_info(self, db_id: str, file_id: str) -> dict:
|
||||
"""获取文件信息和chunks"""
|
||||
|
||||
Loading…
Reference in New Issue
Block a user