open-webui/backend/open_webui/retrieval/loaders/mistral.py
2025-05-23 10:00:19 -07:00

576 lines
22 KiB
Python

import requests
import aiohttp
import asyncio
import logging
import os
import sys
import time
from typing import List, Dict, Any
from contextlib import asynccontextmanager
from langchain_core.documents import Document
from open_webui.env import SRC_LOG_LEVELS, GLOBAL_LOG_LEVEL
logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL)
log = logging.getLogger(__name__)
log.setLevel(SRC_LOG_LEVELS["RAG"])
class MistralLoader:
"""
Enhanced Mistral OCR loader with both sync and async support.
Loads documents by processing them through the Mistral OCR API.
"""
BASE_API_URL = "https://api.mistral.ai/v1"
def __init__(
self,
api_key: str,
file_path: str,
timeout: int = 300, # 5 minutes default
max_retries: int = 3,
enable_debug_logging: bool = False
):
"""
Initializes the loader with enhanced features.
Args:
api_key: Your Mistral API key.
file_path: The local path to the PDF file to process.
timeout: Request timeout in seconds.
max_retries: Maximum number of retry attempts.
enable_debug_logging: Enable detailed debug logs.
"""
if not api_key:
raise ValueError("API key cannot be empty.")
if not os.path.exists(file_path):
raise FileNotFoundError(f"File not found at {file_path}")
self.api_key = api_key
self.file_path = file_path
self.timeout = timeout
self.max_retries = max_retries
self.debug = enable_debug_logging
# Pre-compute file info for performance
self.file_name = os.path.basename(file_path)
self.file_size = os.path.getsize(file_path)
self.headers = {
"Authorization": f"Bearer {self.api_key}",
"User-Agent": "OpenWebUI-MistralLoader/2.0"
}
def _debug_log(self, message: str, *args) -> None:
"""Conditional debug logging for performance."""
if self.debug:
log.debug(message, *args)
def _handle_response(self, response: requests.Response) -> Dict[str, Any]:
"""Checks response status and returns JSON content."""
try:
response.raise_for_status() # Raises HTTPError for bad responses (4xx or 5xx)
# Handle potential empty responses for certain successful requests (e.g., DELETE)
if response.status_code == 204 or not response.content:
return {} # Return empty dict if no content
return response.json()
except requests.exceptions.HTTPError as http_err:
log.error(f"HTTP error occurred: {http_err} - Response: {response.text}")
raise
except requests.exceptions.RequestException as req_err:
log.error(f"Request exception occurred: {req_err}")
raise
except ValueError as json_err: # Includes JSONDecodeError
log.error(f"JSON decode error: {json_err} - Response: {response.text}")
raise # Re-raise after logging
async def _handle_response_async(self, response: aiohttp.ClientResponse) -> Dict[str, Any]:
"""Async version of response handling with better error info."""
try:
response.raise_for_status()
# Check content type
content_type = response.headers.get('content-type', '')
if 'application/json' not in content_type:
if response.status == 204:
return {}
text = await response.text()
raise ValueError(f"Unexpected content type: {content_type}, body: {text[:200]}...")
return await response.json()
except aiohttp.ClientResponseError as e:
error_text = await response.text() if response else "No response"
log.error(f"HTTP {e.status}: {e.message} - Response: {error_text[:500]}")
raise
except aiohttp.ClientError as e:
log.error(f"Client error: {e}")
raise
except Exception as e:
log.error(f"Unexpected error processing response: {e}")
raise
def _retry_request_sync(self, request_func, *args, **kwargs):
"""Synchronous retry logic with exponential backoff."""
for attempt in range(self.max_retries):
try:
return request_func(*args, **kwargs)
except (requests.exceptions.RequestException, Exception) as e:
if attempt == self.max_retries - 1:
raise
wait_time = (2 ** attempt) + 0.5
log.warning(f"Request failed (attempt {attempt + 1}/{self.max_retries}): {e}. Retrying in {wait_time}s...")
time.sleep(wait_time)
async def _retry_request_async(self, request_func, *args, **kwargs):
"""Async retry logic with exponential backoff."""
for attempt in range(self.max_retries):
try:
return await request_func(*args, **kwargs)
except (aiohttp.ClientError, asyncio.TimeoutError) as e:
if attempt == self.max_retries - 1:
raise
wait_time = (2 ** attempt) + 0.5
log.warning(f"Request failed (attempt {attempt + 1}/{self.max_retries}): {e}. Retrying in {wait_time}s...")
await asyncio.sleep(wait_time)
def _upload_file(self) -> str:
"""Uploads the file to Mistral for OCR processing (sync version)."""
log.info("Uploading file to Mistral API")
url = f"{self.BASE_API_URL}/files"
file_name = os.path.basename(self.file_path)
def upload_request():
with open(self.file_path, "rb") as f:
files = {"file": (file_name, f, "application/pdf")}
data = {"purpose": "ocr"}
response = requests.post(
url,
headers=self.headers,
files=files,
data=data,
timeout=self.timeout
)
return self._handle_response(response)
try:
response_data = self._retry_request_sync(upload_request)
file_id = response_data.get("id")
if not file_id:
raise ValueError("File ID not found in upload response.")
log.info(f"File uploaded successfully. File ID: {file_id}")
return file_id
except Exception as e:
log.error(f"Failed to upload file: {e}")
raise
async def _upload_file_async(self, session: aiohttp.ClientSession) -> str:
"""Async file upload with streaming for better memory efficiency."""
url = f"{self.BASE_API_URL}/files"
async def upload_request():
# Create multipart writer for streaming upload
writer = aiohttp.MultipartWriter('form-data')
# Add purpose field
purpose_part = writer.append('ocr')
purpose_part.set_content_disposition('form-data', name='purpose')
# Add file part with streaming
file_part = writer.append_payload(aiohttp.streams.FilePayload(
self.file_path,
filename=self.file_name,
content_type='application/pdf'
))
file_part.set_content_disposition('form-data', name='file', filename=self.file_name)
self._debug_log(f"Uploading file: {self.file_name} ({self.file_size:,} bytes)")
async with session.post(
url,
data=writer,
headers=self.headers,
timeout=aiohttp.ClientTimeout(total=self.timeout)
) as response:
return await self._handle_response_async(response)
response_data = await self._retry_request_async(upload_request)
file_id = response_data.get("id")
if not file_id:
raise ValueError("File ID not found in upload response.")
log.info(f"File uploaded successfully. File ID: {file_id}")
return file_id
def _get_signed_url(self, file_id: str) -> str:
"""Retrieves a temporary signed URL for the uploaded file (sync version)."""
log.info(f"Getting signed URL for file ID: {file_id}")
url = f"{self.BASE_API_URL}/files/{file_id}/url"
params = {"expiry": 1}
signed_url_headers = {**self.headers, "Accept": "application/json"}
def url_request():
response = requests.get(
url,
headers=signed_url_headers,
params=params,
timeout=self.timeout
)
return self._handle_response(response)
try:
response_data = self._retry_request_sync(url_request)
signed_url = response_data.get("url")
if not signed_url:
raise ValueError("Signed URL not found in response.")
log.info("Signed URL received.")
return signed_url
except Exception as e:
log.error(f"Failed to get signed URL: {e}")
raise
async def _get_signed_url_async(self, session: aiohttp.ClientSession, file_id: str) -> str:
"""Async signed URL retrieval."""
url = f"{self.BASE_API_URL}/files/{file_id}/url"
params = {"expiry": 1}
headers = {
**self.headers,
"Accept": "application/json"
}
async def url_request():
self._debug_log(f"Getting signed URL for file ID: {file_id}")
async with session.get(
url,
headers=headers,
params=params,
timeout=aiohttp.ClientTimeout(total=self.timeout)
) as response:
return await self._handle_response_async(response)
response_data = await self._retry_request_async(url_request)
signed_url = response_data.get("url")
if not signed_url:
raise ValueError("Signed URL not found in response.")
self._debug_log("Signed URL received successfully")
return signed_url
def _process_ocr(self, signed_url: str) -> Dict[str, Any]:
"""Sends the signed URL to the OCR endpoint for processing (sync version)."""
log.info("Processing OCR via Mistral API")
url = f"{self.BASE_API_URL}/ocr"
ocr_headers = {
**self.headers,
"Content-Type": "application/json",
"Accept": "application/json",
}
payload = {
"model": "mistral-ocr-latest",
"document": {
"type": "document_url",
"document_url": signed_url,
},
"include_image_base64": False,
}
def ocr_request():
response = requests.post(
url,
headers=ocr_headers,
json=payload,
timeout=self.timeout
)
return self._handle_response(response)
try:
ocr_response = self._retry_request_sync(ocr_request)
log.info("OCR processing done.")
self._debug_log("OCR response: %s", ocr_response)
return ocr_response
except Exception as e:
log.error(f"Failed during OCR processing: {e}")
raise
async def _process_ocr_async(self, session: aiohttp.ClientSession, signed_url: str) -> Dict[str, Any]:
"""Async OCR processing with timing metrics."""
url = f"{self.BASE_API_URL}/ocr"
headers = {
**self.headers,
"Content-Type": "application/json",
"Accept": "application/json",
}
payload = {
"model": "mistral-ocr-latest",
"document": {
"type": "document_url",
"document_url": signed_url,
},
"include_image_base64": False,
}
async def ocr_request():
log.info("Starting OCR processing via Mistral API")
start_time = time.time()
async with session.post(
url,
json=payload,
headers=headers,
timeout=aiohttp.ClientTimeout(total=self.timeout)
) as response:
ocr_response = await self._handle_response_async(response)
processing_time = time.time() - start_time
log.info(f"OCR processing completed in {processing_time:.2f}s")
return ocr_response
return await self._retry_request_async(ocr_request)
def _delete_file(self, file_id: str) -> None:
"""Deletes the file from Mistral storage (sync version)."""
log.info(f"Deleting uploaded file ID: {file_id}")
url = f"{self.BASE_API_URL}/files/{file_id}"
try:
response = requests.delete(url, headers=self.headers, timeout=30)
delete_response = self._handle_response(response)
log.info(f"File deleted successfully: {delete_response}")
except Exception as e:
# Log error but don't necessarily halt execution if deletion fails
log.error(f"Failed to delete file ID {file_id}: {e}")
async def _delete_file_async(self, session: aiohttp.ClientSession, file_id: str) -> None:
"""Async file deletion with error tolerance."""
try:
async def delete_request():
self._debug_log(f"Deleting file ID: {file_id}")
async with session.delete(
url=f"{self.BASE_API_URL}/files/{file_id}",
headers=self.headers,
timeout=aiohttp.ClientTimeout(total=30) # Shorter timeout for cleanup
) as response:
return await self._handle_response_async(response)
await self._retry_request_async(delete_request)
self._debug_log(f"File {file_id} deleted successfully")
except Exception as e:
# Don't fail the entire process if cleanup fails
log.warning(f"Failed to delete file ID {file_id}: {e}")
@asynccontextmanager
async def _get_session(self):
"""Context manager for HTTP session with optimized settings."""
connector = aiohttp.TCPConnector(
limit=10, # Total connection limit
limit_per_host=5, # Per-host connection limit
ttl_dns_cache=300, # DNS cache TTL
use_dns_cache=True,
keepalive_timeout=30,
enable_cleanup_closed=True
)
async with aiohttp.ClientSession(
connector=connector,
timeout=aiohttp.ClientTimeout(total=self.timeout),
headers={"User-Agent": "OpenWebUI-MistralLoader/2.0"}
) as session:
yield session
def _process_results(self, ocr_response: Dict[str, Any]) -> List[Document]:
"""Process OCR results into Document objects with enhanced metadata."""
pages_data = ocr_response.get("pages")
if not pages_data:
log.warning("No pages found in OCR response.")
return [Document(page_content="No text content found", metadata={"error": "no_pages"})]
documents = []
total_pages = len(pages_data)
skipped_pages = 0
for page_data in pages_data:
page_content = page_data.get("markdown")
page_index = page_data.get("index") # API uses 0-based index
if page_content is not None and page_index is not None:
# Clean up content efficiently
cleaned_content = page_content.strip() if isinstance(page_content, str) else str(page_content)
if cleaned_content: # Only add non-empty pages
documents.append(
Document(
page_content=cleaned_content,
metadata={
"page": page_index, # 0-based index from API
"page_label": page_index + 1, # 1-based label for convenience
"total_pages": total_pages,
"file_name": self.file_name,
"file_size": self.file_size,
"processing_engine": "mistral-ocr"
},
)
)
else:
skipped_pages += 1
self._debug_log(f"Skipping empty page {page_index}")
else:
skipped_pages += 1
self._debug_log(f"Skipping page due to missing 'markdown' or 'index'. Data: {page_data}")
if skipped_pages > 0:
log.info(f"Processed {len(documents)} pages, skipped {skipped_pages} empty/invalid pages")
if not documents:
# Case where pages existed but none had valid markdown/index
log.warning("OCR response contained pages, but none had valid content/index.")
return [
Document(
page_content="No valid text content found in document",
metadata={"error": "no_valid_pages", "total_pages": total_pages}
)
]
return documents
def load(self) -> List[Document]:
"""
Executes the full OCR workflow: upload, get URL, process OCR, delete file.
Synchronous version for backward compatibility.
Returns:
A list of Document objects, one for each page processed.
"""
file_id = None
start_time = time.time()
try:
# 1. Upload file
file_id = self._upload_file()
# 2. Get Signed URL
signed_url = self._get_signed_url(file_id)
# 3. Process OCR
ocr_response = self._process_ocr(signed_url)
# 4. Process results
documents = self._process_results(ocr_response)
total_time = time.time() - start_time
log.info(f"Sync OCR workflow completed in {total_time:.2f}s, produced {len(documents)} documents")
return documents
except Exception as e:
total_time = time.time() - start_time
log.error(f"An error occurred during the loading process after {total_time:.2f}s: {e}")
# Return an error document on failure
return [Document(
page_content=f"Error during processing: {e}",
metadata={"error": "processing_failed", "file_name": self.file_name}
)]
finally:
# 5. Delete file (attempt even if prior steps failed after upload)
if file_id:
try:
self._delete_file(file_id)
except Exception as del_e:
# Log deletion error, but don't overwrite original error if one occurred
log.error(f"Cleanup error: Could not delete file ID {file_id}. Reason: {del_e}")
async def load_async(self) -> List[Document]:
"""
Asynchronous OCR workflow execution with optimized performance.
Returns:
A list of Document objects, one for each page processed.
"""
file_id = None
start_time = time.time()
try:
async with self._get_session() as session:
# 1. Upload file with streaming
file_id = await self._upload_file_async(session)
# 2. Get signed URL
signed_url = await self._get_signed_url_async(session, file_id)
# 3. Process OCR
ocr_response = await self._process_ocr_async(session, signed_url)
# 4. Process results
documents = self._process_results(ocr_response)
total_time = time.time() - start_time
log.info(f"Async OCR workflow completed in {total_time:.2f}s, produced {len(documents)} documents")
return documents
except Exception as e:
total_time = time.time() - start_time
log.error(f"Async OCR workflow failed after {total_time:.2f}s: {e}")
return [Document(
page_content=f"Error during OCR processing: {e}",
metadata={"error": "processing_failed", "file_name": self.file_name}
)]
finally:
# 5. Cleanup - always attempt file deletion
if file_id:
try:
async with self._get_session() as session:
await self._delete_file_async(session, file_id)
except Exception as cleanup_error:
log.error(f"Cleanup failed for file ID {file_id}: {cleanup_error}")
@staticmethod
async def load_multiple_async(loaders: List['MistralLoader']) -> List[List[Document]]:
"""
Process multiple files concurrently for maximum performance.
Args:
loaders: List of MistralLoader instances
Returns:
List of document lists, one for each loader
"""
if not loaders:
return []
log.info(f"Starting concurrent processing of {len(loaders)} files")
start_time = time.time()
# Process all files concurrently
tasks = [loader.load_async() for loader in loaders]
results = await asyncio.gather(*tasks, return_exceptions=True)
# Handle any exceptions in results
processed_results = []
for i, result in enumerate(results):
if isinstance(result, Exception):
log.error(f"File {i} failed: {result}")
processed_results.append([Document(
page_content=f"Error processing file: {result}",
metadata={"error": "batch_processing_failed", "file_index": i}
)])
else:
processed_results.append(result)
total_time = time.time() - start_time
total_docs = sum(len(docs) for docs in processed_results)
log.info(f"Batch processing completed in {total_time:.2f}s, produced {total_docs} total documents")
return processed_results