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10 Commits
| Author | SHA1 | Date | |
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 Roman Isecke
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Roman Isecke
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Roman Isecke
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Roman Isecke
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Roman Isecke
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Roman Isecke
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Roman Isecke
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Roman Isecke
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Roman Isecke
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Roman Isecke
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4d0d567138 |
@@ -12,7 +12,6 @@ env:
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jobs:
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test_e2e:
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runs-on: ubuntu-latest
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timeout-minutes: 30
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strategy:
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# You can use PyPy versions in python-version.
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# For example, pypy-2.7 and pypy-3.8
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@@ -1,183 +0,0 @@
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"""
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Example: Batch Processing a Folder of PDFs with LlamaParse
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This script demonstrates how to process multiple PDFs from a folder
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using LlamaParse with controlled concurrency using asyncio and semaphores.
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|
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Usage:
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python batch_parse_folder.py --input-dir ./pdfs --max-concurrent 5
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||||
"""
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|
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import asyncio
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||||
import argparse
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||||
from pathlib import Path
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||||
from typing import List, Dict, Any
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||||
from datetime import datetime
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||||
from dotenv import load_dotenv
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import os
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||||
from llama_cloud_services import LlamaParse
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|
||||
# Load environment variables from .env file
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||||
load_dotenv()
|
||||
|
||||
|
||||
async def parse_single_file(
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||||
parser: LlamaParse,
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||||
file_path: Path,
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||||
semaphore: asyncio.Semaphore,
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||||
) -> Dict[str, Any]:
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||||
"""
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Parse a single PDF file with concurrency control.
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||||
|
||||
Args:
|
||||
parser: LlamaParse instance
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||||
file_path: Path to the PDF file
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||||
semaphore: Semaphore to control concurrent requests
|
||||
|
||||
Returns:
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||||
Dictionary with file info and parse result
|
||||
"""
|
||||
async with semaphore:
|
||||
try:
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||||
print(f"Starting parse: {file_path.name}")
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||||
|
||||
result = await parser.aparse(str(file_path))
|
||||
|
||||
print(f"✓ Completed: {file_path.name} ({len(result.pages)} pages)")
|
||||
|
||||
return {
|
||||
"file": file_path.name,
|
||||
"status": "success",
|
||||
"result": result,
|
||||
"pages": len(result.pages) if result.pages else 0,
|
||||
}
|
||||
except Exception as e:
|
||||
print(f"✗ Error parsing {file_path.name}: {str(e)}")
|
||||
return {
|
||||
"file": file_path.name,
|
||||
"status": "error",
|
||||
"error": str(e),
|
||||
}
|
||||
|
||||
|
||||
async def parse_folder(
|
||||
input_dir: Path,
|
||||
max_concurrent: int = 5,
|
||||
api_key: str = None,
|
||||
) -> List[Dict[str, any]]:
|
||||
"""
|
||||
Parse all PDFs in a folder with controlled concurrency.
|
||||
|
||||
Args:
|
||||
input_dir: Directory containing PDF files
|
||||
max_concurrent: Maximum number of concurrent parse operations
|
||||
api_key: LlamaCloud API key (loaded from .env file)
|
||||
|
||||
Returns:
|
||||
List of parse results for each file
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"""
|
||||
# Find all PDF files
|
||||
pdf_files = list(input_dir.glob("*.pdf"))
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||||
|
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if not pdf_files:
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print(f"No PDF files found in {input_dir}")
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||||
return []
|
||||
|
||||
print(f"Found {len(pdf_files)} PDF files to parse")
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||||
|
||||
# Initialize parser
|
||||
parser = LlamaParse(
|
||||
api_key=api_key,
|
||||
num_workers=1, # We control concurrency with semaphore
|
||||
show_progress=False, # We'll show our own progress
|
||||
)
|
||||
|
||||
# Create semaphore to limit concurrent requests
|
||||
semaphore = asyncio.Semaphore(max_concurrent)
|
||||
|
||||
# Create tasks for all files
|
||||
tasks = [parse_single_file(parser, pdf_file, semaphore) for pdf_file in pdf_files]
|
||||
|
||||
# Run all tasks concurrently (but limited by semaphore)
|
||||
print(
|
||||
f"Processing {len(tasks)} files with max {max_concurrent} concurrent operations..."
|
||||
)
|
||||
start_time = datetime.now()
|
||||
|
||||
results = await asyncio.gather(*tasks)
|
||||
|
||||
end_time = datetime.now()
|
||||
duration = (end_time - start_time).total_seconds()
|
||||
|
||||
# Process results
|
||||
successful = [
|
||||
r for r in results if isinstance(r, dict) and r.get("status") == "success"
|
||||
]
|
||||
failed = [r for r in results if isinstance(r, dict) and r.get("status") == "error"]
|
||||
|
||||
# Print summary
|
||||
print("PARSE SUMMARY \n")
|
||||
print(f"Total files: {len(pdf_files)}")
|
||||
print(f"Successful: {len(successful)}")
|
||||
print(f"Failed: {len(failed)}")
|
||||
print(f"Total time: {duration:.2f} seconds")
|
||||
print(f"Average time per file: {duration / len(pdf_files):.2f} seconds")
|
||||
|
||||
if failed:
|
||||
print("\nFailed files:")
|
||||
for result in failed:
|
||||
print(f" - {result['file']}: {result.get('error', 'Unknown error')}")
|
||||
|
||||
return results
|
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|
||||
|
||||
def main():
|
||||
"""Main entry point for the script."""
|
||||
parser = argparse.ArgumentParser(
|
||||
description="Batch process PDFs in a folder with LlamaParse"
|
||||
)
|
||||
parser.add_argument(
|
||||
"--input-dir",
|
||||
type=str,
|
||||
required=True,
|
||||
help="Directory containing PDF files to parse",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--max-concurrent",
|
||||
type=int,
|
||||
default=5,
|
||||
help="Maximum number of concurrent parse operations (default: 5)",
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
input_dir = Path(args.input_dir)
|
||||
|
||||
# Validate input directory
|
||||
if not input_dir.exists():
|
||||
print(f"Error: Input directory does not exist: {input_dir}")
|
||||
return
|
||||
|
||||
if not input_dir.is_dir():
|
||||
print(f"Error: Input path is not a directory: {input_dir}")
|
||||
return
|
||||
|
||||
# Get API key from environment (loaded from .env file)
|
||||
api_key = os.getenv("LLAMA_CLOUD_API_KEY")
|
||||
if not api_key:
|
||||
print("Error: LLAMA_CLOUD_API_KEY not found. Please set it in your .env file")
|
||||
return
|
||||
|
||||
# Run async function
|
||||
asyncio.run(
|
||||
parse_folder(
|
||||
input_dir=input_dir,
|
||||
max_concurrent=args.max_concurrent,
|
||||
api_key=api_key,
|
||||
)
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Binary file not shown.
@@ -1,540 +0,0 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Document Splitting with LlamaCloud\n",
|
||||
"\n",
|
||||
"This notebook demonstrates how to use the LlamaCloud **Split** API to automatically segment a concatenated PDF into logical document sections based on content categories.\n",
|
||||
"\n",
|
||||
"## Use Case\n",
|
||||
"\n",
|
||||
"When dealing with large PDFs that contain multiple distinct documents or sections (e.g., a bundle of research papers, a collection of reports), you often need to split them into individual segments. The Split API uses AI to:\n",
|
||||
"\n",
|
||||
"1. Analyze each page's content\n",
|
||||
"2. Classify pages into user-defined categories\n",
|
||||
"3. Group consecutive pages of the same category into segments\n",
|
||||
"\n",
|
||||
"## Example Document\n",
|
||||
"\n",
|
||||
"We'll use a PDF containing three concatenated documents:\n",
|
||||
"- **Alan Turing's essay** \"Intelligent Machinery, A Heretical Theory\" (an essay)\n",
|
||||
"- **ImageNet paper** (a research paper)\n",
|
||||
"- **\"Attention is All You Need\"** paper (a research paper)\n",
|
||||
"\n",
|
||||
"We'll split this into segments categorized as either `essay` or `research_paper`.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Setup\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Requirement already satisfied: llama-cloud in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (0.1.44)\n",
|
||||
"Requirement already satisfied: python-dotenv in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (1.2.1)\n",
|
||||
"Requirement already satisfied: requests in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (2.32.5)\n",
|
||||
"Requirement already satisfied: certifi>=2024.7.4 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from llama-cloud) (2025.11.12)\n",
|
||||
"Requirement already satisfied: httpx>=0.20.0 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from llama-cloud) (0.28.1)\n",
|
||||
"Requirement already satisfied: pydantic>=1.10 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from llama-cloud) (2.12.5)\n",
|
||||
"Requirement already satisfied: charset_normalizer<4,>=2 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from requests) (3.4.4)\n",
|
||||
"Requirement already satisfied: idna<4,>=2.5 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from requests) (3.11)\n",
|
||||
"Requirement already satisfied: urllib3<3,>=1.21.1 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from requests) (2.5.0)\n",
|
||||
"Requirement already satisfied: anyio in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from httpx>=0.20.0->llama-cloud) (4.11.0)\n",
|
||||
"Requirement already satisfied: httpcore==1.* in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from httpx>=0.20.0->llama-cloud) (1.0.9)\n",
|
||||
"Requirement already satisfied: h11>=0.16 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from httpcore==1.*->httpx>=0.20.0->llama-cloud) (0.16.0)\n",
|
||||
"Requirement already satisfied: annotated-types>=0.6.0 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from pydantic>=1.10->llama-cloud) (0.7.0)\n",
|
||||
"Requirement already satisfied: pydantic-core==2.41.5 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from pydantic>=1.10->llama-cloud) (2.41.5)\n",
|
||||
"Requirement already satisfied: typing-extensions>=4.14.1 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from pydantic>=1.10->llama-cloud) (4.15.0)\n",
|
||||
"Requirement already satisfied: typing-inspection>=0.4.2 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from pydantic>=1.10->llama-cloud) (0.4.2)\n",
|
||||
"Requirement already satisfied: sniffio>=1.1 in /Users/javier/llama_cloud_services/.venv/lib/python3.11/site-packages (from anyio->httpx>=0.20.0->llama-cloud) (1.3.1)\n",
|
||||
"\n",
|
||||
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m25.0.1\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m25.3\u001b[0m\n",
|
||||
"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
|
||||
"Note: you may need to restart the kernel to use updated packages.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Install required packages\n",
|
||||
"%pip install llama-cloud python-dotenv requests"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"✅ API configured with base URL: https://api.cloud.llamaindex.ai\n",
|
||||
"✅ Project ID: using default project\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import os\n",
|
||||
"import time\n",
|
||||
"import requests\n",
|
||||
"from dotenv import load_dotenv\n",
|
||||
"\n",
|
||||
"# Load environment variables\n",
|
||||
"load_dotenv()\n",
|
||||
"\n",
|
||||
"# Configuration\n",
|
||||
"LLAMA_CLOUD_API_KEY = os.environ.get(\"LLAMA_CLOUD_API_KEY\", \"llx-...\")\n",
|
||||
"BASE_URL = os.environ.get(\"LLAMA_CLOUD_BASE_URL\", \"https://api.cloud.llamaindex.ai\")\n",
|
||||
"PROJECT_ID = os.environ.get(\"LLAMA_CLOUD_PROJECT_ID\", None)\n",
|
||||
"\n",
|
||||
"# Headers for API requests\n",
|
||||
"headers = {\n",
|
||||
" \"Authorization\": f\"Bearer {LLAMA_CLOUD_API_KEY}\",\n",
|
||||
" \"Content-Type\": \"application/json\",\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"print(f\"✅ API configured with base URL: {BASE_URL}\")\n",
|
||||
"print(f\"✅ Project ID: {PROJECT_ID or 'using default project'}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Step 1: Upload the PDF File\n",
|
||||
"\n",
|
||||
"First, we'll upload our concatenated PDF to LlamaCloud using the Files API. This can be done using the `llama-cloud` SDK.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"📤 Uploading ./data/turing+imagenet+attention.pdf...\n",
|
||||
"✅ File uploaded successfully!\n",
|
||||
" File name: turing+imagenet+attention.pdf\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"from llama_cloud.client import LlamaCloud\n",
|
||||
"\n",
|
||||
"# Initialize the client\n",
|
||||
"client = LlamaCloud(token=LLAMA_CLOUD_API_KEY, base_url=BASE_URL)\n",
|
||||
"\n",
|
||||
"# Path to the PDF file\n",
|
||||
"pdf_path = \"./data/turing+imagenet+attention.pdf\"\n",
|
||||
"\n",
|
||||
"# Upload the file\n",
|
||||
"print(f\"📤 Uploading {pdf_path}...\")\n",
|
||||
"\n",
|
||||
"with open(pdf_path, \"rb\") as f:\n",
|
||||
" uploaded_file = client.files.upload_file(upload_file=f, project_id=PROJECT_ID)\n",
|
||||
"\n",
|
||||
"file_id = uploaded_file.id\n",
|
||||
"print(f\"✅ File uploaded successfully!\")\n",
|
||||
"print(f\" File name: {uploaded_file.name}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Step 2: Create a Split Job\n",
|
||||
"\n",
|
||||
"Now we'll create a split job using the Split API. Since the Split API is in beta and not yet available in the SDK, we'll use raw HTTP requests.\n",
|
||||
"\n",
|
||||
"We define two categories:\n",
|
||||
"- **essay**: For philosophical or reflective writing\n",
|
||||
"- **research_paper**: For formal academic documents with methodology and citations\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"🔄 Creating split job...\n",
|
||||
"✅ Split job created!\n",
|
||||
" Job ID: spl-zsssb632a742aikliu96pqkb56t5\n",
|
||||
" Status: pending\n",
|
||||
" Categories: ['essay', 'research_paper']\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Define the split job request\n",
|
||||
"split_request = {\n",
|
||||
" \"document_input\": {\n",
|
||||
" \"type\": \"file_id\", # only file_id is supported for now\n",
|
||||
" \"value\": file_id,\n",
|
||||
" },\n",
|
||||
" \"categories\": [\n",
|
||||
" {\n",
|
||||
" \"name\": \"essay\",\n",
|
||||
" \"description\": \"A philosophical or reflective piece of writing that presents personal viewpoints, arguments, or thoughts on a topic without strict formal structure\",\n",
|
||||
" },\n",
|
||||
" {\n",
|
||||
" \"name\": \"research_paper\",\n",
|
||||
" \"description\": \"A formal academic document presenting original research, methodology, experiments, results, and conclusions with citations and references\",\n",
|
||||
" },\n",
|
||||
" ],\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"# Create the split job\n",
|
||||
"print(\"🔄 Creating split job...\")\n",
|
||||
"response = requests.post(\n",
|
||||
" f\"{BASE_URL}/api/v1/beta/split/jobs\",\n",
|
||||
" params={\"project_id\": PROJECT_ID},\n",
|
||||
" headers=headers,\n",
|
||||
" json=split_request,\n",
|
||||
")\n",
|
||||
"response.raise_for_status()\n",
|
||||
"\n",
|
||||
"split_job = response.json()\n",
|
||||
"job_id = split_job[\"id\"]\n",
|
||||
"\n",
|
||||
"print(f\"✅ Split job created!\")\n",
|
||||
"print(f\" Job ID: {job_id}\")\n",
|
||||
"print(f\" Status: {split_job['status']}\")\n",
|
||||
"print(f\" Categories: {[c['name'] for c in split_job['categories']]}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Step 3: Poll for Job Completion\n",
|
||||
"\n",
|
||||
"The split job runs asynchronously. We'll poll the job status until it completes.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"⏳ Waiting for split job to complete...\n",
|
||||
" Status: processing (elapsed: 0s)\n",
|
||||
" Status: processing (elapsed: 5s)\n",
|
||||
" Status: processing (elapsed: 11s)\n",
|
||||
" Status: completed (elapsed: 16s)\n",
|
||||
"\n",
|
||||
"✅ Split job completed successfully!\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"def poll_split_job(job_id: str, max_wait_seconds: int = 180, poll_interval: int = 5):\n",
|
||||
" \"\"\"\n",
|
||||
" Poll a split job until it reaches a terminal state.\n",
|
||||
"\n",
|
||||
" Args:\n",
|
||||
" job_id: The split job ID\n",
|
||||
" max_wait_seconds: Maximum time to wait for completion\n",
|
||||
" poll_interval: Seconds between poll attempts\n",
|
||||
"\n",
|
||||
" Returns:\n",
|
||||
" The completed job response\n",
|
||||
" \"\"\"\n",
|
||||
" start_time = time.time()\n",
|
||||
"\n",
|
||||
" while (time.time() - start_time) < max_wait_seconds:\n",
|
||||
" response = requests.get(\n",
|
||||
" f\"{BASE_URL}/api/v1/beta/split/jobs/{job_id}\",\n",
|
||||
" params={\"project_id\": PROJECT_ID},\n",
|
||||
" headers=headers,\n",
|
||||
" )\n",
|
||||
" response.raise_for_status()\n",
|
||||
" job = response.json()\n",
|
||||
"\n",
|
||||
" status = job[\"status\"]\n",
|
||||
" elapsed = int(time.time() - start_time)\n",
|
||||
" print(f\" Status: {status} (elapsed: {elapsed}s)\")\n",
|
||||
"\n",
|
||||
" if status in [\"completed\", \"failed\"]:\n",
|
||||
" return job\n",
|
||||
"\n",
|
||||
" time.sleep(poll_interval)\n",
|
||||
"\n",
|
||||
" raise TimeoutError(f\"Job did not complete within {max_wait_seconds} seconds\")\n",
|
||||
"\n",
|
||||
"\n",
|
||||
"print(\"⏳ Waiting for split job to complete...\")\n",
|
||||
"completed_job = poll_split_job(job_id)\n",
|
||||
"\n",
|
||||
"if completed_job[\"status\"] == \"completed\":\n",
|
||||
" print(\"\\n✅ Split job completed successfully!\")\n",
|
||||
"else:\n",
|
||||
" print(\n",
|
||||
" f\"\\n❌ Split job failed: {completed_job.get('error_message', 'Unknown error')}\"\n",
|
||||
" )"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Step 4: Analyze the Results\n",
|
||||
"\n",
|
||||
"Let's examine the split results to see how the document was segmented.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"📊 Split Results Summary\n",
|
||||
"==================================================\n",
|
||||
"Total segments found: 3\n",
|
||||
"\n",
|
||||
"Segments by category:\n",
|
||||
" • essay: 1 segment(s)\n",
|
||||
" • research_paper: 2 segment(s)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Get the segments from the result\n",
|
||||
"segments = completed_job.get(\"result\", {}).get(\"segments\", [])\n",
|
||||
"\n",
|
||||
"print(f\"📊 Split Results Summary\")\n",
|
||||
"print(f\"=\" * 50)\n",
|
||||
"print(f\"Total segments found: {len(segments)}\")\n",
|
||||
"print()\n",
|
||||
"\n",
|
||||
"# Count by category\n",
|
||||
"category_counts = {}\n",
|
||||
"for segment in segments:\n",
|
||||
" cat = segment[\"category\"]\n",
|
||||
" category_counts[cat] = category_counts.get(cat, 0) + 1\n",
|
||||
"\n",
|
||||
"print(\"Segments by category:\")\n",
|
||||
"for cat, count in category_counts.items():\n",
|
||||
" print(f\" • {cat}: {count} segment(s)\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"📄 Segment Details\n",
|
||||
"==================================================\n",
|
||||
"\n",
|
||||
"Segment 1:\n",
|
||||
" Category: essay\n",
|
||||
" Pages 1-4 (4 pages)\n",
|
||||
" Confidence: high\n",
|
||||
"\n",
|
||||
"Segment 2:\n",
|
||||
" Category: research_paper\n",
|
||||
" Pages 5-13 (9 pages)\n",
|
||||
" Confidence: high\n",
|
||||
"\n",
|
||||
"Segment 3:\n",
|
||||
" Category: research_paper\n",
|
||||
" Pages 14-24 (11 pages)\n",
|
||||
" Confidence: high\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Display detailed segment information\n",
|
||||
"print(f\"\\n📄 Segment Details\")\n",
|
||||
"print(f\"=\" * 50)\n",
|
||||
"\n",
|
||||
"for i, segment in enumerate(segments, 1):\n",
|
||||
" category = segment[\"category\"]\n",
|
||||
" pages = segment[\"pages\"]\n",
|
||||
" confidence = segment[\"confidence_category\"]\n",
|
||||
"\n",
|
||||
" # Format page range\n",
|
||||
" if len(pages) == 1:\n",
|
||||
" page_range = f\"Page {pages[0]}\"\n",
|
||||
" else:\n",
|
||||
" page_range = f\"Pages {min(pages)}-{max(pages)}\"\n",
|
||||
"\n",
|
||||
" print(f\"\\nSegment {i}:\")\n",
|
||||
" print(f\" Category: {category}\")\n",
|
||||
" print(f\" {page_range} ({len(pages)} page{'s' if len(pages) > 1 else ''})\")\n",
|
||||
" print(f\" Confidence: {confidence}\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Expected Results\n",
|
||||
"\n",
|
||||
"Based on our test document, we expect:\n",
|
||||
"- **1 essay segment**: Alan Turing's \"Intelligent Machinery, A Heretical Theory\"\n",
|
||||
"- **2 research paper segments**: ImageNet paper and \"Attention is All You Need\" paper\n",
|
||||
"\n",
|
||||
"The pages should be grouped consecutively, with no overlap between segments.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"\n",
|
||||
"✅ Validation\n",
|
||||
"==================================================\n",
|
||||
"Total pages assigned: 24\n",
|
||||
"Unique pages: 24\n",
|
||||
"✅ No page overlap detected - each page belongs to exactly one segment\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Verify no page overlap\n",
|
||||
"all_pages = []\n",
|
||||
"for segment in segments:\n",
|
||||
" all_pages.extend(segment[\"pages\"])\n",
|
||||
"\n",
|
||||
"unique_pages = set(all_pages)\n",
|
||||
"\n",
|
||||
"print(f\"\\n✅ Validation\")\n",
|
||||
"print(f\"=\" * 50)\n",
|
||||
"print(f\"Total pages assigned: {len(all_pages)}\")\n",
|
||||
"print(f\"Unique pages: {len(unique_pages)}\")\n",
|
||||
"\n",
|
||||
"if len(all_pages) == len(unique_pages):\n",
|
||||
" print(f\"✅ No page overlap detected - each page belongs to exactly one segment\")\n",
|
||||
"else:\n",
|
||||
" print(\n",
|
||||
" f\"⚠️ Page overlap detected - {len(all_pages) - len(unique_pages)} duplicate assignments\"\n",
|
||||
" )"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Using `allow_uncategorized` Strategy\n",
|
||||
"\n",
|
||||
"You can also use the `allow_uncategorized` splitting strategy. This is useful when you want to capture pages that don't match any defined category.\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"📝 With allow_uncategorized=True and only 'essay' category defined,\n",
|
||||
" pages that don't match 'essay' will be grouped as 'uncategorized'.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Example with allow_uncategorized strategy\n",
|
||||
"split_request_uncategorized = {\n",
|
||||
" \"document_input\": {\"type\": \"file_id\", \"value\": file_id},\n",
|
||||
" \"categories\": [\n",
|
||||
" {\n",
|
||||
" \"name\": \"essay\",\n",
|
||||
" \"description\": \"A philosophical or reflective piece of writing that presents personal viewpoints, arguments, or thoughts on a topic\",\n",
|
||||
" }\n",
|
||||
" # Note: We only define 'essay' category\n",
|
||||
" # Research papers will be classified as 'uncategorized'\n",
|
||||
" ],\n",
|
||||
" \"splitting_strategy\": {\"allow_uncategorized\": True},\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"print(\"📝 With allow_uncategorized=True and only 'essay' category defined,\")\n",
|
||||
"print(\" pages that don't match 'essay' will be grouped as 'uncategorized'.\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Conclusion\n",
|
||||
"\n",
|
||||
"The LlamaCloud Split API provides a powerful way to automatically segment concatenated documents based on content categories. This is useful for:\n",
|
||||
"\n",
|
||||
"- **Document processing pipelines**: Automatically separate bundled documents before further processing\n",
|
||||
"- **Content organization**: Categorize and organize mixed document collections\n",
|
||||
"- **Information extraction**: Identify different document types within a single file\n",
|
||||
"\n",
|
||||
"### Key Features\n",
|
||||
"\n",
|
||||
"- **AI-powered classification**: Uses LLMs to understand page content and assign categories\n",
|
||||
"- **Flexible categories**: Define any categories relevant to your use case\n",
|
||||
"- **Confidence scoring**: Each segment includes a confidence level\n",
|
||||
"- **Page-level granularity**: Results include exact page numbers for each segment\n",
|
||||
"\n",
|
||||
"### API Reference\n",
|
||||
"\n",
|
||||
"- **Create Split Job**: `POST /api/v1/beta/split/jobs`\n",
|
||||
"- **Get Split Job**: `GET /api/v1/beta/split/jobs/{job_id}`\n",
|
||||
"- **List Split Jobs**: `GET /api/v1/beta/split/jobs`\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": ".venv",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 2
|
||||
}
|
||||
+1
-1
@@ -398,6 +398,6 @@ Another option (orthogonal to the above) is to break the document into smaller s
|
||||
## Additional Resources
|
||||
|
||||
- [Extract Documentation](https://docs.cloud.llamaindex.ai/llamaextract/getting_started) - Details on Extract features, API and examples.
|
||||
- [Example Notebook](examples/extract/resume_screening.ipynb) - Detailed walkthrough of resume parsing
|
||||
- [Example Notebook](docs/examples-py/extract/resume_screening.ipynb) - Detailed walkthrough of resume parsing
|
||||
- [Example Application with TypeScript](./examples-ts/extract/) - End-to-end examples using LlamaExtract TypeScript client.
|
||||
- [Discord Community](https://discord.com/invite/eN6D2HQ4aX) - Get help and share feedback
|
||||
|
||||
@@ -97,7 +97,7 @@ for page in result.pages:
|
||||
print(page.structuredData)
|
||||
```
|
||||
|
||||
See more details about the result object in the [example notebook](./examples/parse/demo_json_tour.ipynb).
|
||||
See more details about the result object in the [example notebook](./docs/examples-py/parse/demo_json_tour.ipynb).
|
||||
|
||||
### Using with file object / bytes
|
||||
|
||||
@@ -153,10 +153,10 @@ Full documentation for `SimpleDirectoryReader` can be found on the [LlamaIndex D
|
||||
|
||||
Several end-to-end indexing examples can be found in the examples folder
|
||||
|
||||
- [Getting Started](examples/parse/demo_basic.ipynb)
|
||||
- [Advanced RAG Example](examples/parse/demo_advanced.ipynb)
|
||||
- [Raw API Usage](examples/parse/demo_api.ipynb)
|
||||
- [Result Object Tour](examples/parse/demo_json_tour.ipynb)
|
||||
- [Getting Started](docs/examples-py/parse/demo_basic.ipynb)
|
||||
- [Advanced RAG Example](docs/examples-py/parse/demo_advanced.ipynb)
|
||||
- [Raw API Usage](docs/examples-py/parse/demo_api.ipynb)
|
||||
- [Result Object Tour](docs/examples-py/parse/demo_json_tour.ipynb)
|
||||
|
||||
## Documentation
|
||||
|
||||
|
||||
Generated
+3260
-48
File diff suppressed because it is too large
Load Diff
@@ -1,41 +1,5 @@
|
||||
# llama-cloud-services-py
|
||||
|
||||
## 0.6.88
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 71db318: Add tier and version
|
||||
|
||||
## 0.6.87
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 06c3c55: Update spreadsheet parsing config
|
||||
|
||||
## 0.6.86
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 1b7198d: Update extract to have confidence scores available in all modes
|
||||
|
||||
## 0.6.85
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- ae30990: Add line-level bbox support
|
||||
|
||||
## 0.6.84
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 0a110de: Release to re-align versions
|
||||
|
||||
## 0.6.83
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- ca78113: Do not use presigned URLs by default in files client
|
||||
|
||||
## 0.6.82
|
||||
|
||||
### Patch Changes
|
||||
|
||||
+1
-1
@@ -15,4 +15,4 @@ test: ## Run unit tests via pytest
|
||||
|
||||
.PHONY: e2e
|
||||
e2e: ## Run all tests. Run with high parallelism using xdist since tests are bottlenecked bound by the slow backend parsing
|
||||
uv run pytest -v -n 32 --timeout=300 --session-timeout=1740 tests/
|
||||
uv run pytest -v -n 32 tests/
|
||||
|
||||
@@ -2,7 +2,7 @@ import asyncio
|
||||
import io
|
||||
import os
|
||||
import time
|
||||
from typing import Any, Dict, TYPE_CHECKING
|
||||
from typing import TYPE_CHECKING
|
||||
|
||||
import httpx
|
||||
from llama_cloud.client import AsyncLlamaCloud
|
||||
@@ -68,8 +68,6 @@ class LlamaSheets:
|
||||
max_timeout: int = 300,
|
||||
poll_interval: int = 5,
|
||||
max_retries: int = 3,
|
||||
project_id: str | None = None,
|
||||
organization_id: str | None = None,
|
||||
async_httpx_client: httpx.AsyncClient | None = None,
|
||||
) -> None:
|
||||
"""Initialize the LlamaSheets client.
|
||||
@@ -80,8 +78,6 @@ class LlamaSheets:
|
||||
max_timeout: Maximum time to wait for job completion in seconds
|
||||
poll_interval: Interval between status checks in seconds
|
||||
max_retries: Maximum number of retries for failed requests
|
||||
project_id: Project ID for file operations. If not provided, will use LLAMA_CLOUD_PROJECT_ID env var
|
||||
organization_id: Organization ID for file operations. If not provided, will use LLAMA_CLOUD_ORGANIZATION_ID env var
|
||||
async_httpx_client: Optional custom async httpx client
|
||||
"""
|
||||
self.api_key = api_key or os.environ.get("LLAMA_CLOUD_API_KEY")
|
||||
@@ -97,32 +93,15 @@ class LlamaSheets:
|
||||
self.poll_interval = poll_interval
|
||||
self.max_retries = max_retries
|
||||
|
||||
self.project_id = project_id or os.environ.get("LLAMA_CLOUD_PROJECT_ID")
|
||||
self.organization_id = organization_id or os.environ.get(
|
||||
"LLAMA_CLOUD_ORGANIZATION_ID"
|
||||
)
|
||||
|
||||
self._async_client: httpx.AsyncClient | None = async_httpx_client
|
||||
self._files_client = FileClient(
|
||||
AsyncLlamaCloud(
|
||||
token=self.api_key,
|
||||
base_url=self.base_url,
|
||||
httpx_client=async_httpx_client,
|
||||
),
|
||||
project_id=self.project_id,
|
||||
organization_id=self.organization_id,
|
||||
)
|
||||
)
|
||||
|
||||
def _get_default_params(self) -> dict[str, str]:
|
||||
"""Get default query parameters for API requests"""
|
||||
params = {}
|
||||
if self.project_id is not None:
|
||||
params["project_id"] = self.project_id
|
||||
if self.organization_id is not None:
|
||||
params["organization_id"] = self.organization_id
|
||||
|
||||
return params
|
||||
|
||||
def _get_async_client(self) -> httpx.AsyncClient:
|
||||
"""Get or create the async httpx client"""
|
||||
if self._async_client is None:
|
||||
@@ -327,8 +306,6 @@ class LlamaSheets:
|
||||
"config": config.model_dump(mode="json", exclude_none=True),
|
||||
}
|
||||
|
||||
params = self._get_default_params()
|
||||
|
||||
try:
|
||||
async for attempt in AsyncRetrying(
|
||||
stop=stop_after_attempt(self.max_retries),
|
||||
@@ -341,7 +318,6 @@ class LlamaSheets:
|
||||
response = await client.post(
|
||||
f"{self.base_url}/api/v1/beta/sheets/jobs",
|
||||
headers=self._get_headers(),
|
||||
params=params,
|
||||
json=payload,
|
||||
)
|
||||
response.raise_for_status()
|
||||
@@ -371,17 +347,12 @@ class LlamaSheets:
|
||||
):
|
||||
with attempt:
|
||||
client = self._get_async_client()
|
||||
params: Dict[str, Any] = {
|
||||
"include_results": include_results_metadata,
|
||||
**self._get_default_params(),
|
||||
}
|
||||
response = await client.get(
|
||||
f"{self.base_url}/api/v1/beta/sheets/jobs/{job_id}",
|
||||
headers=self._get_headers(),
|
||||
params=params,
|
||||
params={"include_results": include_results_metadata},
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
return SpreadsheetJobResult.model_validate(response.json())
|
||||
except Exception as e:
|
||||
raise SpreadsheetAPIError(f"Failed to get job status: {e}") from e
|
||||
@@ -444,8 +415,6 @@ class LlamaSheets:
|
||||
# Get presigned URL
|
||||
presigned_response = None
|
||||
result_type_str = str(result_type)
|
||||
params = self._get_default_params()
|
||||
|
||||
try:
|
||||
async for attempt in AsyncRetrying(
|
||||
stop=stop_after_attempt(self.max_retries),
|
||||
@@ -458,7 +427,6 @@ class LlamaSheets:
|
||||
response = await client.get(
|
||||
f"{self.base_url}/api/v1/beta/sheets/jobs/{job_id}/regions/{region_id}/result/{result_type_str}",
|
||||
headers=self._get_headers(),
|
||||
params=params,
|
||||
)
|
||||
response.raise_for_status()
|
||||
presigned_response = PresignedUrlResponse.model_validate(
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
from datetime import datetime
|
||||
from enum import Enum
|
||||
from typing import Literal
|
||||
|
||||
from pydantic import BaseModel, ConfigDict, Field, field_validator
|
||||
|
||||
@@ -64,7 +63,7 @@ class SpreadsheetParseResult(BaseModel):
|
||||
class SpreadsheetParsingConfig(BaseModel):
|
||||
"""Configuration for spreadsheet parsing and region extraction"""
|
||||
|
||||
model_config = ConfigDict(extra="ignore")
|
||||
model_config = ConfigDict(extra="forbid")
|
||||
|
||||
sheet_names: list[str] | None = Field(
|
||||
default=None,
|
||||
@@ -87,16 +86,6 @@ class SpreadsheetParsingConfig(BaseModel):
|
||||
description="Enables experimental processing. Accuracy may be impacted.",
|
||||
)
|
||||
|
||||
flatten_hierarchical_tables: bool = Field(
|
||||
default=False,
|
||||
description="Return a flattened dataframe when a detected table is recognized as hierarchical.",
|
||||
)
|
||||
|
||||
table_merge_sensitivity: Literal["strong", "weak"] = Field(
|
||||
default="strong",
|
||||
description="Influences how likely similar-looking regions are merged into a single table. Useful for spreadsheets that either have sparse tables (strong merging) or many distinct tables close together (weak merging).",
|
||||
)
|
||||
|
||||
|
||||
class SpreadsheetJob(BaseModel):
|
||||
"""A spreadsheet parsing job"""
|
||||
|
||||
@@ -240,6 +240,11 @@ def _extraction_config_warning(config: ExtractConfig) -> None:
|
||||
raise ValueError(
|
||||
"`cite_sources` is only supported with MULTIMODAL or PREMIUM extraction modes."
|
||||
)
|
||||
if config.confidence_scores:
|
||||
if config.extraction_mode in (ExtractMode.FAST, ExtractMode.BALANCED):
|
||||
raise ValueError(
|
||||
"`confidence_scores` is only supported with MULTIMODAL or PREMIUM extraction modes."
|
||||
)
|
||||
|
||||
|
||||
class ExtractionAgent:
|
||||
|
||||
@@ -11,7 +11,7 @@ from llama_cloud_services.utils import SourceText, FileInput
|
||||
class FileClient:
|
||||
"""
|
||||
Higher-level client for interacting with the LlamaCloud Files API.
|
||||
Optionally uses presigned URLs for uploads.
|
||||
Uses presigned URLs for uploads by default.
|
||||
|
||||
Args:
|
||||
client: The LlamaCloud client to use.
|
||||
@@ -25,7 +25,7 @@ class FileClient:
|
||||
client: AsyncLlamaCloud,
|
||||
project_id: Optional[str] = None,
|
||||
organization_id: Optional[str] = None,
|
||||
use_presigned_url: bool = False,
|
||||
use_presigned_url: bool = True,
|
||||
):
|
||||
self.client = client
|
||||
self.project_id = project_id
|
||||
@@ -91,10 +91,6 @@ class FileClient:
|
||||
organization_id=self.organization_id,
|
||||
)
|
||||
else:
|
||||
# Set buffer.name if not already set, so the upload uses external_file_id
|
||||
# for file type detection
|
||||
if not getattr(buffer, "name", None):
|
||||
setattr(buffer, "name", external_file_id)
|
||||
return await self.client.files.upload_file(
|
||||
upload_file=buffer,
|
||||
external_file_id=external_file_id,
|
||||
|
||||
@@ -654,9 +654,6 @@ class LlamaCloudIndex(BaseManagedIndex):
|
||||
],
|
||||
)
|
||||
|
||||
# Trigger a sync
|
||||
client.pipelines.sync_pipeline(pipeline_id=index.pipeline.id)
|
||||
|
||||
doc_ids = [doc.id for doc in upserted_documents]
|
||||
index.wait_for_completion(
|
||||
doc_ids=doc_ids, verbose=verbose, raise_on_error=raise_on_error
|
||||
@@ -741,10 +738,6 @@ class LlamaCloudIndex(BaseManagedIndex):
|
||||
)
|
||||
],
|
||||
)
|
||||
|
||||
# Trigger a sync
|
||||
self._client.pipelines.sync_pipeline(pipeline_id=self.pipeline.id)
|
||||
|
||||
upserted_document = upserted_documents[0]
|
||||
self.wait_for_completion(
|
||||
doc_ids=[upserted_document.id], verbose=verbose, raise_on_error=True
|
||||
@@ -767,9 +760,6 @@ class LlamaCloudIndex(BaseManagedIndex):
|
||||
)
|
||||
],
|
||||
)
|
||||
# Trigger a sync
|
||||
await self._aclient.pipelines.sync_pipeline(pipeline_id=self.pipeline.id)
|
||||
|
||||
upserted_document = upserted_documents[0]
|
||||
await self.await_for_completion(
|
||||
doc_ids=[upserted_document.id], verbose=verbose, raise_on_error=True
|
||||
@@ -792,9 +782,6 @@ class LlamaCloudIndex(BaseManagedIndex):
|
||||
)
|
||||
],
|
||||
)
|
||||
# Trigger a sync
|
||||
self._client.pipelines.sync_pipeline(pipeline_id=self.pipeline.id)
|
||||
|
||||
upserted_document = upserted_documents[0]
|
||||
self.wait_for_completion(
|
||||
doc_ids=[upserted_document.id], verbose=verbose, raise_on_error=True
|
||||
@@ -817,9 +804,6 @@ class LlamaCloudIndex(BaseManagedIndex):
|
||||
)
|
||||
],
|
||||
)
|
||||
# Trigger a sync
|
||||
await self._aclient.pipelines.sync_pipeline(pipeline_id=self.pipeline.id)
|
||||
|
||||
upserted_document = upserted_documents[0]
|
||||
await self.await_for_completion(
|
||||
doc_ids=[upserted_document.id], verbose=verbose, raise_on_error=True
|
||||
@@ -843,9 +827,6 @@ class LlamaCloudIndex(BaseManagedIndex):
|
||||
for doc in documents
|
||||
],
|
||||
)
|
||||
# Trigger a sync
|
||||
self._client.pipelines.sync_pipeline(pipeline_id=self.pipeline.id)
|
||||
|
||||
doc_ids = [doc.id for doc in upserted_documents]
|
||||
self.wait_for_completion(doc_ids=doc_ids, verbose=True, raise_on_error=True)
|
||||
return [True] * len(doc_ids)
|
||||
@@ -868,9 +849,6 @@ class LlamaCloudIndex(BaseManagedIndex):
|
||||
for doc in documents
|
||||
],
|
||||
)
|
||||
# Trigger a sync
|
||||
await self._aclient.pipelines.sync_pipeline(pipeline_id=self.pipeline.id)
|
||||
|
||||
doc_ids = [doc.id for doc in upserted_documents]
|
||||
await self.await_for_completion(
|
||||
doc_ids=doc_ids, verbose=True, raise_on_error=True
|
||||
|
||||
@@ -564,17 +564,6 @@ class LlamaParse(BasePydanticReader):
|
||||
default=None,
|
||||
description="Whether to extract the printed page numbers from pages in the document.",
|
||||
)
|
||||
line_level_bounding_box: Optional[bool] = Field(
|
||||
default=False,
|
||||
description="If set to true, the parser will include line-level bounding boxes in the result.",
|
||||
)
|
||||
tier: Optional[str] = Field(
|
||||
default=None, description="The tier to use for the parsing job."
|
||||
)
|
||||
version: Optional[str] = Field(
|
||||
default=None,
|
||||
description="The version of the parser to use at the specified tier.",
|
||||
)
|
||||
|
||||
# Deprecated
|
||||
bounding_box: Optional[str] = Field(
|
||||
@@ -1129,15 +1118,6 @@ class LlamaParse(BasePydanticReader):
|
||||
if self.extract_printed_page_number is not None:
|
||||
data["extract_printed_page_number"] = self.extract_printed_page_number
|
||||
|
||||
if self.line_level_bounding_box is not None:
|
||||
data["line_level_bounding_box"] = self.line_level_bounding_box
|
||||
|
||||
if self.tier is not None:
|
||||
data["tier"] = self.tier
|
||||
|
||||
if self.version is not None:
|
||||
data["version"] = self.version
|
||||
|
||||
# Deprecated
|
||||
if self.bounding_box is not None:
|
||||
data["bounding_box"] = self.bounding_box
|
||||
|
||||
@@ -115,26 +115,6 @@ class BBox(SafeBaseModel):
|
||||
)
|
||||
|
||||
|
||||
class LineLevelBboxItem(SafeBaseModel):
|
||||
"""A line-level bounding box item."""
|
||||
|
||||
md: Optional[str] = Field(
|
||||
default=None, description="The markdown-formatted content of the line."
|
||||
)
|
||||
text: Optional[str] = Field(
|
||||
default=None, description="The text content of the line."
|
||||
)
|
||||
bBox: Optional[BBox] = Field(
|
||||
default=None, description="The bounding box of the line."
|
||||
)
|
||||
startIndex: Optional[int] = Field(
|
||||
default=None, description="The start index of the line in the page text."
|
||||
)
|
||||
endIndex: Optional[int] = Field(
|
||||
default=None, description="The end index of the line in the page text."
|
||||
)
|
||||
|
||||
|
||||
class PageItem(SafeBaseModel):
|
||||
"""An item in a page."""
|
||||
|
||||
@@ -158,9 +138,6 @@ class PageItem(SafeBaseModel):
|
||||
default=None,
|
||||
description="The HTML-formatted content of the item. Only applicable for table items when output_tables_as_HTML=True.",
|
||||
)
|
||||
lines: Optional[List[LineLevelBboxItem]] = Field(
|
||||
default=None, description="The line-level bounding box items of the item."
|
||||
)
|
||||
|
||||
|
||||
class ImageItem(SafeBaseModel):
|
||||
|
||||
@@ -1,48 +1,5 @@
|
||||
# llama_parse
|
||||
|
||||
## 0.6.88
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [71db318]
|
||||
- llama-cloud-services-py@0.6.88
|
||||
|
||||
## 0.6.87
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [06c3c55]
|
||||
- llama-cloud-services-py@0.6.87
|
||||
|
||||
## 0.6.86
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 1b7198d: Update extract to have confidence scores available in all modes
|
||||
- Updated dependencies [1b7198d]
|
||||
- llama-cloud-services-py@0.6.86
|
||||
|
||||
## 0.6.85
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [ae30990]
|
||||
- llama-cloud-services-py@0.6.85
|
||||
|
||||
## 0.6.84
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [0a110de]
|
||||
- llama-cloud-services-py@0.6.84
|
||||
|
||||
## 0.6.83
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- Updated dependencies [ca78113]
|
||||
- llama-cloud-services-py@0.6.83
|
||||
|
||||
## 0.6.82
|
||||
|
||||
### Patch Changes
|
||||
|
||||
@@ -146,9 +146,9 @@ Full documentation for `SimpleDirectoryReader` can be found on the [LlamaIndex D
|
||||
|
||||
Several end-to-end indexing examples can be found in the examples folder
|
||||
|
||||
- [Getting Started](../../examples/parse/demo_basic.ipynb)
|
||||
- [Advanced RAG Example](../../examples/parse/demo_advanced.ipynb)
|
||||
- [Raw API Usage](../../examples/parse/demo_api.ipynb)
|
||||
- [Getting Started](/docs/examples-py/parse/demo_basic.ipynb)
|
||||
- [Advanced RAG Example](/docs/examples-py/parse/demo_advanced.ipynb)
|
||||
- [Raw API Usage](/docs/examples-py/parse/demo_api.ipynb)
|
||||
|
||||
## Documentation
|
||||
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "llama_parse",
|
||||
"version": "0.6.88",
|
||||
"version": "0.6.82",
|
||||
"description": "",
|
||||
"main": "index.js",
|
||||
"private": false,
|
||||
|
||||
@@ -11,13 +11,13 @@ dev = [
|
||||
|
||||
[project]
|
||||
name = "llama-parse"
|
||||
version = "0.6.88"
|
||||
version = "0.6.83"
|
||||
description = "Parse files into RAG-Optimized formats."
|
||||
authors = [{name = "Logan Markewich", email = "logan@llamaindex.ai"}]
|
||||
requires-python = ">=3.9,<4.0"
|
||||
readme = "README.md"
|
||||
license = "MIT"
|
||||
dependencies = ["llama-cloud-services>=0.6.88"]
|
||||
dependencies = ["llama-cloud-services>=0.6.82"]
|
||||
|
||||
[project.scripts]
|
||||
llama-parse = "llama_parse.cli.main:parse"
|
||||
|
||||
+1
-1
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "llama-cloud-services-py",
|
||||
"version": "0.6.88",
|
||||
"version": "0.6.82",
|
||||
"private": false,
|
||||
"license": "MIT",
|
||||
"scripts": {},
|
||||
|
||||
+2
-3
@@ -7,7 +7,6 @@ dev = [
|
||||
"pytest>=8.0.0,<9",
|
||||
"pytest-xdist>=3.6.1,<4",
|
||||
"pytest-asyncio",
|
||||
"pytest-timeout>=2.3.1",
|
||||
"ipykernel>=6.29.0,<7",
|
||||
"pre-commit==3.2.0",
|
||||
"autoevals>=0.0.114,<0.0.115",
|
||||
@@ -23,7 +22,7 @@ dev = [
|
||||
|
||||
[project]
|
||||
name = "llama-cloud-services"
|
||||
version = "0.6.88"
|
||||
version = "0.6.83"
|
||||
description = "Tailored SDK clients for LlamaCloud services."
|
||||
authors = [{name = "Logan Markewich", email = "logan@runllama.ai"}]
|
||||
requires-python = ">=3.9,<4.0"
|
||||
@@ -31,7 +30,7 @@ readme = "README.md"
|
||||
license = "MIT"
|
||||
dependencies = [
|
||||
"llama-index-core>=0.12.0",
|
||||
"llama-cloud==0.1.45",
|
||||
"llama-cloud==0.1.44",
|
||||
"pydantic>=2.8,!=2.10",
|
||||
"click>=8.1.7,<9",
|
||||
"python-dotenv>=1.0.1,<2",
|
||||
|
||||
@@ -2,58 +2,24 @@ import os
|
||||
import tempfile
|
||||
import pytest
|
||||
import pandas as pd
|
||||
from pydantic import ValidationError
|
||||
|
||||
from llama_cloud_services.beta.sheets import LlamaSheets
|
||||
from llama_cloud_services.beta.sheets.types import SpreadsheetParsingConfig
|
||||
|
||||
|
||||
class TestSpreadsheetParsingConfig:
|
||||
"""Unit tests for SpreadsheetParsingConfig."""
|
||||
|
||||
def test_default_values(self):
|
||||
"""Test that default values are set correctly."""
|
||||
config = SpreadsheetParsingConfig()
|
||||
assert config.flatten_hierarchical_tables is False
|
||||
assert config.table_merge_sensitivity == "strong"
|
||||
|
||||
def test_custom_values(self):
|
||||
"""Test setting custom values for new fields."""
|
||||
config = SpreadsheetParsingConfig(
|
||||
flatten_hierarchical_tables=True,
|
||||
table_merge_sensitivity="weak",
|
||||
)
|
||||
assert config.flatten_hierarchical_tables is True
|
||||
assert config.table_merge_sensitivity == "weak"
|
||||
|
||||
def test_table_merge_sensitivity_validation(self):
|
||||
"""Test that invalid table_merge_sensitivity values are rejected."""
|
||||
with pytest.raises(ValidationError):
|
||||
SpreadsheetParsingConfig(table_merge_sensitivity="invalid")
|
||||
|
||||
def test_unknown_fields_ignored(self):
|
||||
"""Test that unknown fields are silently ignored."""
|
||||
config = SpreadsheetParsingConfig(
|
||||
unknown_field="test",
|
||||
another_unknown=123,
|
||||
)
|
||||
assert not hasattr(config, "unknown_field")
|
||||
assert not hasattr(config, "another_unknown")
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sheets_client():
|
||||
"""Create a LlamaSheets client for testing."""
|
||||
api_key = os.getenv("LLAMA_CLOUD_API_KEY")
|
||||
base_url = os.getenv("LLAMA_CLOUD_BASE_URL", "https://api.cloud.llamaindex.ai")
|
||||
project_id = os.getenv("LLAMA_CLOUD_PROJECT_ID")
|
||||
api_key = os.getenv(
|
||||
"LLAMA_CLOUD_API_KEY", "llx-3AEorIw5v0lnJPzEOI9xSl0N8yFx3fguw0Zn8QJHzGWmwg5r"
|
||||
)
|
||||
base_url = os.getenv("LLAMA_CLOUD_BASE_URL", "https://api.staging.llamaindex.ai")
|
||||
|
||||
client = LlamaSheets(
|
||||
api_key=api_key,
|
||||
base_url=base_url,
|
||||
max_timeout=300,
|
||||
poll_interval=2,
|
||||
project_id=project_id,
|
||||
)
|
||||
return client
|
||||
|
||||
@@ -85,7 +51,10 @@ def sample_excel_file():
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
os.environ.get("LLAMA_CLOUD_API_KEY", "") == "",
|
||||
os.environ.get(
|
||||
"LLAMA_CLOUD_API_KEY", "llx-3AEorIw5v0lnJPzEOI9xSl0N8yFx3fguw0Zn8QJHzGWmwg5r"
|
||||
)
|
||||
== "",
|
||||
reason="LLAMA_CLOUD_API_KEY not set",
|
||||
)
|
||||
@pytest.mark.asyncio
|
||||
@@ -165,7 +134,10 @@ async def test_spreadsheet_extraction_e2e(
|
||||
|
||||
|
||||
@pytest.mark.skipif(
|
||||
os.environ.get("LLAMA_CLOUD_API_KEY", "") == "",
|
||||
os.environ.get(
|
||||
"LLAMA_CLOUD_API_KEY", "llx-3AEorIw5v0lnJPzEOI9xSl0N8yFx3fguw0Zn8QJHzGWmwg5r"
|
||||
)
|
||||
== "",
|
||||
reason="LLAMA_CLOUD_API_KEY not set",
|
||||
)
|
||||
@pytest.mark.asyncio
|
||||
|
||||
@@ -78,7 +78,7 @@ async def test_upload_bytes(
|
||||
uploaded_file = await file_client.upload_bytes(file_bytes, external_file_id)
|
||||
|
||||
assert isinstance(uploaded_file, File)
|
||||
expected_name = external_file_id
|
||||
expected_name = external_file_id if use_presigned_url else "upload"
|
||||
assert uploaded_file.name == expected_name
|
||||
assert uploaded_file.external_file_id == external_file_id
|
||||
|
||||
@@ -100,7 +100,7 @@ async def test_upload_buffer(
|
||||
uploaded_file = await file_client.upload_buffer(buffer, external_file_id, file_size)
|
||||
|
||||
assert isinstance(uploaded_file, File)
|
||||
expected_name = external_file_id
|
||||
expected_name = external_file_id if use_presigned_url else "upload"
|
||||
assert uploaded_file.name == expected_name
|
||||
assert uploaded_file.external_file_id == external_file_id
|
||||
|
||||
|
||||
Generated
+12
-264
@@ -1,10 +1,9 @@
|
||||
version = 1
|
||||
revision = 2
|
||||
revision = 3
|
||||
requires-python = ">=3.9, <4.0"
|
||||
resolution-markers = [
|
||||
"python_full_version >= '3.14'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.14'",
|
||||
"python_full_version == '3.11.*'",
|
||||
"python_full_version >= '3.11' and python_full_version < '3.14'",
|
||||
"python_full_version == '3.10.*'",
|
||||
"python_full_version < '3.10'",
|
||||
]
|
||||
@@ -221,8 +220,7 @@ name = "argon2-cffi-bindings"
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version = "25.1.0"
|
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source = { registry = "https://pypi.org/simple" }
|
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resolution-markers = [
|
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"python_full_version >= '3.12' and python_full_version < '3.14'",
|
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"python_full_version == '3.11.*'",
|
||||
"python_full_version >= '3.11' and python_full_version < '3.14'",
|
||||
"python_full_version == '3.10.*'",
|
||||
"python_full_version < '3.10'",
|
||||
]
|
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@@ -591,8 +589,7 @@ version = "8.2.1"
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source = { registry = "https://pypi.org/simple" }
|
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resolution-markers = [
|
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"python_full_version >= '3.14'",
|
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"python_full_version >= '3.12' and python_full_version < '3.14'",
|
||||
"python_full_version == '3.11.*'",
|
||||
"python_full_version >= '3.11' and python_full_version < '3.14'",
|
||||
"python_full_version == '3.10.*'",
|
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]
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dependencies = [
|
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@@ -723,15 +720,6 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/33/6b/e0547afaf41bf2c42e52430072fa5658766e3d65bd4b03a563d1b6336f57/distlib-0.4.0-py2.py3-none-any.whl", hash = "sha256:9659f7d87e46584a30b5780e43ac7a2143098441670ff0a49d5f9034c54a6c16", size = 469047, upload-time = "2025-07-17T16:51:58.613Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "et-xmlfile"
|
||||
version = "2.0.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
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sdist = { url = "https://files.pythonhosted.org/packages/d3/38/af70d7ab1ae9d4da450eeec1fa3918940a5fafb9055e934af8d6eb0c2313/et_xmlfile-2.0.0.tar.gz", hash = "sha256:dab3f4764309081ce75662649be815c4c9081e88f0837825f90fd28317d4da54", size = 17234, upload-time = "2024-10-25T17:25:40.039Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/c1/8b/5fe2cc11fee489817272089c4203e679c63b570a5aaeb18d852ae3cbba6a/et_xmlfile-2.0.0-py3-none-any.whl", hash = "sha256:7a91720bc756843502c3b7504c77b8fe44217c85c537d85037f0f536151b2caa", size = 18059, upload-time = "2024-10-25T17:25:39.051Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "eval-type-backport"
|
||||
version = "0.2.2"
|
||||
@@ -1132,8 +1120,7 @@ version = "8.37.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
resolution-markers = [
|
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"python_full_version >= '3.14'",
|
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"python_full_version >= '3.12' and python_full_version < '3.14'",
|
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"python_full_version == '3.11.*'",
|
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"python_full_version >= '3.11' and python_full_version < '3.14'",
|
||||
"python_full_version == '3.10.*'",
|
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]
|
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dependencies = [
|
||||
@@ -1595,21 +1582,21 @@ wheels = [
|
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|
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[[package]]
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name = "llama-cloud"
|
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version = "0.1.45"
|
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version = "0.1.44"
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source = { registry = "https://pypi.org/simple" }
|
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dependencies = [
|
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{ name = "certifi" },
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{ name = "httpx" },
|
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{ name = "pydantic" },
|
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]
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|
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sdist = { url = "https://files.pythonhosted.org/packages/54/eb/16e31fb0fc4df91b08fa19cc3f28ac6e3c7d4df0bcbb71dd2bf596e9586f/llama_cloud-0.1.44.tar.gz", hash = "sha256:276a2b4f94463da037431ca3063331b3b6be398bbfb003113ee76b7c2a873b53", size = 120502, upload-time = "2025-11-04T00:51:58.578Z" }
|
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wheels = [
|
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{ url = "https://files.pythonhosted.org/packages/62/1d/466b0df69b81ce9410ad6ec7229a1e6601ff69640f02f246e06cfcc7428c/llama_cloud-0.1.45-py3-none-any.whl", hash = "sha256:500299a6d3f25f97bcf6755d6338523023564fa8f376955c2cf299bbc9561cc2", size = 397184, upload-time = "2025-12-03T02:22:48.335Z" },
|
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{ url = "https://files.pythonhosted.org/packages/69/0a/fabe54c21d5927d626550cb9560a20e51e42468355f5f0fb300f84806e28/llama_cloud-0.1.44-py3-none-any.whl", hash = "sha256:dfdcc4932353711fc8639f14261cbb54a88139b7790ebdd3ed4fde29bbbc0b88", size = 332779, upload-time = "2025-11-04T00:51:57.371Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "llama-cloud-services"
|
||||
version = "0.6.85"
|
||||
version = "0.6.79"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "click", version = "8.1.8", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
|
||||
@@ -1633,15 +1620,10 @@ dev = [
|
||||
{ name = "ipython", version = "8.37.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
|
||||
{ name = "jupyter" },
|
||||
{ name = "mypy" },
|
||||
{ name = "openpyxl" },
|
||||
{ name = "pandas" },
|
||||
{ name = "pre-commit" },
|
||||
{ name = "pyarrow", version = "21.0.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
|
||||
{ name = "pyarrow", version = "22.0.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
|
||||
{ name = "pydantic-settings" },
|
||||
{ name = "pytest" },
|
||||
{ name = "pytest-asyncio" },
|
||||
{ name = "pytest-timeout" },
|
||||
{ name = "pytest-xdist" },
|
||||
]
|
||||
|
||||
@@ -1649,7 +1631,7 @@ dev = [
|
||||
requires-dist = [
|
||||
{ name = "click", specifier = ">=8.1.7,<9" },
|
||||
{ name = "eval-type-backport", marker = "python_full_version < '3.10'", specifier = ">=0.2.0,<0.3" },
|
||||
{ name = "llama-cloud", specifier = "==0.1.45" },
|
||||
{ name = "llama-cloud", specifier = "==0.1.44" },
|
||||
{ name = "llama-index-core", specifier = ">=0.12.0" },
|
||||
{ name = "packaging", specifier = ">=23.0" },
|
||||
{ name = "platformdirs", specifier = ">=4.3.7,<5" },
|
||||
@@ -1666,14 +1648,10 @@ dev = [
|
||||
{ name = "ipython", specifier = ">=8.12.3,<9" },
|
||||
{ name = "jupyter", specifier = ">=1.1.1,<2" },
|
||||
{ name = "mypy", specifier = ">=1.14.1,<2" },
|
||||
{ name = "openpyxl" },
|
||||
{ name = "pandas" },
|
||||
{ name = "pre-commit", specifier = "==3.2.0" },
|
||||
{ name = "pyarrow" },
|
||||
{ name = "pydantic-settings", specifier = ">=2.10.1" },
|
||||
{ name = "pytest", specifier = ">=8.0.0,<9" },
|
||||
{ name = "pytest-asyncio" },
|
||||
{ name = "pytest-timeout", specifier = ">=2.3.1" },
|
||||
{ name = "pytest-xdist", specifier = ">=3.6.1,<4" },
|
||||
]
|
||||
|
||||
@@ -2120,8 +2098,7 @@ version = "3.5"
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source = { registry = "https://pypi.org/simple" }
|
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resolution-markers = [
|
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"python_full_version >= '3.14'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.14'",
|
||||
"python_full_version == '3.11.*'",
|
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"python_full_version >= '3.11' and python_full_version < '3.14'",
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|
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wheels = [
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@@ -2307,8 +2284,7 @@ version = "2.3.2"
|
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source = { registry = "https://pypi.org/simple" }
|
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resolution-markers = [
|
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"python_full_version >= '3.14'",
|
||||
"python_full_version >= '3.12' and python_full_version < '3.14'",
|
||||
"python_full_version == '3.11.*'",
|
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"python_full_version >= '3.11' and python_full_version < '3.14'",
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|
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@@ -2387,18 +2363,6 @@ wheels = [
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|
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|
||||
[[package]]
|
||||
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|
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|
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|
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wheels = [
|
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|
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|
||||
[[package]]
|
||||
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|
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|
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|
||||
[[package]]
|
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|
||||
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|
||||
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|
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|
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{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.10.*'" },
|
||||
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|
||||
{ name = "python-dateutil" },
|
||||
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|
||||
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|
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|
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|
||||
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|
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||||
{ url = "https://files.pythonhosted.org/packages/c7/9d/bf86eddabf8c6c9cb1ea9a869d6873b46f105a5d292d3a6f7071f5b07935/pytest_asyncio-1.1.0-py3-none-any.whl", hash = "sha256:5fe2d69607b0bd75c656d1211f969cadba035030156745ee09e7d71740e58ecf", size = 15157, upload-time = "2025-07-16T04:29:24.929Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pytest-timeout"
|
||||
version = "2.4.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "pytest" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/ac/82/4c9ecabab13363e72d880f2fb504c5f750433b2b6f16e99f4ec21ada284c/pytest_timeout-2.4.0.tar.gz", hash = "sha256:7e68e90b01f9eff71332b25001f85c75495fc4e3a836701876183c4bcfd0540a", size = 17973, upload-time = "2025-05-05T19:44:34.99Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/fa/b6/3127540ecdf1464a00e5a01ee60a1b09175f6913f0644ac748494d9c4b21/pytest_timeout-2.4.0-py3-none-any.whl", hash = "sha256:c42667e5cdadb151aeb5b26d114aff6bdf5a907f176a007a30b940d3d865b5c2", size = 14382, upload-time = "2025-05-05T19:44:33.502Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pytest-xdist"
|
||||
version = "3.8.0"
|
||||
@@ -3203,15 +2969,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/08/20/0f2523b9e50a8052bc6a8b732dfc8568abbdc42010aef03a2d750bdab3b2/python_json_logger-3.3.0-py3-none-any.whl", hash = "sha256:dd980fae8cffb24c13caf6e158d3d61c0d6d22342f932cb6e9deedab3d35eec7", size = 15163, upload-time = "2025-03-07T07:08:25.627Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pytz"
|
||||
version = "2025.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/f8/bf/abbd3cdfb8fbc7fb3d4d38d320f2441b1e7cbe29be4f23797b4a2b5d8aac/pytz-2025.2.tar.gz", hash = "sha256:360b9e3dbb49a209c21ad61809c7fb453643e048b38924c765813546746e81c3", size = 320884, upload-time = "2025-03-25T02:25:00.538Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/81/c4/34e93fe5f5429d7570ec1fa436f1986fb1f00c3e0f43a589fe2bbcd22c3f/pytz-2025.2-py2.py3-none-any.whl", hash = "sha256:5ddf76296dd8c44c26eb8f4b6f35488f3ccbf6fbbd7adee0b7262d43f0ec2f00", size = 509225, upload-time = "2025-03-25T02:24:58.468Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "pywin32"
|
||||
version = "311"
|
||||
@@ -4103,15 +3860,6 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/17/69/cd203477f944c353c31bade965f880aa1061fd6bf05ded0726ca845b6ff7/typing_inspection-0.4.1-py3-none-any.whl", hash = "sha256:389055682238f53b04f7badcb49b989835495a96700ced5dab2d8feae4b26f51", size = 14552, upload-time = "2025-05-21T18:55:22.152Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "tzdata"
|
||||
version = "2025.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/95/32/1a225d6164441be760d75c2c42e2780dc0873fe382da3e98a2e1e48361e5/tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9", size = 196380, upload-time = "2025-03-23T13:54:43.652Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/5c/23/c7abc0ca0a1526a0774eca151daeb8de62ec457e77262b66b359c3c7679e/tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8", size = 347839, upload-time = "2025-03-23T13:54:41.845Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "uri-template"
|
||||
version = "1.3.0"
|
||||
|
||||
@@ -1,32 +1,5 @@
|
||||
# llama-cloud-services
|
||||
|
||||
## 0.5.1
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- d5b18a0: Fix publishing
|
||||
|
||||
## 0.5.0
|
||||
|
||||
### Minor Changes
|
||||
|
||||
- 576c3d9: feat: support zod v4 & v3
|
||||
|
||||
Adds support for zod v4 while maintaining backward compatibility with v3.
|
||||
- Updated zod peer dependency to accept both v3 and v4: `^3.25.76 || ^4.0.0`
|
||||
- Migrated all import statements to use `zod/v4` import path for compatibility
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- c8321d2: Improve parse results polling
|
||||
- 576c3d9: Support zod v3 an v4
|
||||
|
||||
## 0.4.3
|
||||
|
||||
### Patch Changes
|
||||
|
||||
- 71db318: Add tier and version
|
||||
|
||||
## 0.4.2
|
||||
|
||||
### Patch Changes
|
||||
|
||||
+14804
-9434
File diff suppressed because it is too large
Load Diff
@@ -1,12 +1,12 @@
|
||||
{
|
||||
"name": "llama-cloud-services",
|
||||
"version": "0.5.1",
|
||||
"version": "0.4.2",
|
||||
"type": "module",
|
||||
"license": "MIT",
|
||||
"scripts": {
|
||||
"get-openapi": "node ./scripts/get-openapi.js",
|
||||
"generate": "./node_modules/.bin/openapi-ts",
|
||||
"build": "bunchee",
|
||||
"build": "pnpm run generate && bunchee",
|
||||
"dev": "bunchee --watch",
|
||||
"lint": "eslint src/ --ignore-pattern client/*.ts --no-warn-ignored",
|
||||
"format": "prettier --write ./src/ tests/",
|
||||
@@ -116,9 +116,9 @@
|
||||
"@eslint/js": "^9.32.0",
|
||||
"@hey-api/client-fetch": "^0.10.1",
|
||||
"@hey-api/openapi-ts": "^0.67.5",
|
||||
"@llamaindex/core": "^0.6.22",
|
||||
"@llamaindex/core": "^0.6.19",
|
||||
"@llamaindex/env": "^0.1.30",
|
||||
"@llamaindex/workflow-core": "^1.3.3",
|
||||
"@llamaindex/workflow-core": "^0.4.1",
|
||||
"@types/node": "^20.19.9",
|
||||
"@typescript-eslint/eslint-plugin": "^8.38.0",
|
||||
"@typescript-eslint/parser": "^8.38.0",
|
||||
@@ -131,19 +131,18 @@
|
||||
"turbo": "^2.5.5",
|
||||
"typescript": "^5.8.3",
|
||||
"typescript-eslint": "^8.38.0",
|
||||
"vitest": "^2.0.0",
|
||||
"zod": "^4.1.13"
|
||||
"vitest": "^2.0.0"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@llamaindex/core": "^0.6.19",
|
||||
"@llamaindex/env": "^0.1.30",
|
||||
"@llamaindex/workflow-core": "^1.3.3",
|
||||
"zod": "^3.25.0 || ^4.0.0"
|
||||
"@llamaindex/workflow-core": "^0.4.1"
|
||||
},
|
||||
"dependencies": {
|
||||
"ajv": "^8.17.1",
|
||||
"file-type": "^21.0.0",
|
||||
"p-retry": "^6.2.1"
|
||||
"p-retry": "^6.2.1",
|
||||
"zod": "^3.25.76"
|
||||
},
|
||||
"packageManager": "pnpm@10.8.1"
|
||||
}
|
||||
|
||||
@@ -1,7 +1,7 @@
|
||||
import {
|
||||
addFilesToPipelineApiApiV1PipelinesPipelineIdFilesPut,
|
||||
getPipelineFileStatusApiV1PipelinesPipelineIdFilesFileIdStatusGet,
|
||||
listPipelineFiles2ApiV1PipelinesPipelineIdFiles2Get,
|
||||
listPipelineFilesApiV1PipelinesPipelineIdFilesGet,
|
||||
listProjectsApiV1ProjectsGet,
|
||||
readFileContentApiV1FilesIdContentGet,
|
||||
searchPipelinesApiV1PipelinesGet,
|
||||
@@ -97,20 +97,21 @@ export class LLamaCloudFileService {
|
||||
*/
|
||||
public static async getFileUrl(pipelineId: string, filename: string) {
|
||||
initService();
|
||||
const response = await listPipelineFiles2ApiV1PipelinesPipelineIdFiles2Get({
|
||||
path: {
|
||||
pipeline_id: pipelineId,
|
||||
},
|
||||
throwOnError: true,
|
||||
});
|
||||
const file = response.data.files.find((file) => file.name === filename);
|
||||
const { data: allPipelineFiles } =
|
||||
await listPipelineFilesApiV1PipelinesPipelineIdFilesGet({
|
||||
path: {
|
||||
pipeline_id: pipelineId,
|
||||
},
|
||||
throwOnError: true,
|
||||
});
|
||||
const file = allPipelineFiles.find((file) => file.name === filename);
|
||||
if (!file?.file_id) return null;
|
||||
const { data: fileContent } = await readFileContentApiV1FilesIdContentGet({
|
||||
path: {
|
||||
id: file.file_id,
|
||||
},
|
||||
query: {
|
||||
project_id: file.project_id || null,
|
||||
project_id: file.project_id,
|
||||
},
|
||||
throwOnError: true,
|
||||
});
|
||||
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -1,6 +1,6 @@
|
||||
import { workflowEvent } from "@llamaindex/workflow-core";
|
||||
import { zodEvent } from "@llamaindex/workflow-core/util/zod";
|
||||
import { z } from "zod/v4";
|
||||
import { z } from "zod";
|
||||
import { parseFormSchema } from "./schema";
|
||||
|
||||
export const uploadEvent = zodEvent(
|
||||
|
||||
@@ -2,7 +2,7 @@ import type { JSONValue } from "@llamaindex/core/global";
|
||||
import type { ToolMetadata } from "@llamaindex/core/llms";
|
||||
import type { BaseQueryEngine } from "@llamaindex/core/query-engine";
|
||||
import { tool } from "@llamaindex/core/tools";
|
||||
import { z } from "zod/v4";
|
||||
import { z } from "zod";
|
||||
|
||||
const DEFAULT_NAME = "llama_cloud_index_tool";
|
||||
const DEFAULT_DESCRIPTION =
|
||||
@@ -21,7 +21,9 @@ export function createQueryEngineTool(
|
||||
name: metadata?.name ?? DEFAULT_NAME,
|
||||
description: metadata?.description ?? DEFAULT_DESCRIPTION,
|
||||
parameters: z.object({
|
||||
query: z.string().describe("The query to search for"),
|
||||
query: z.string({
|
||||
description: "The query to search for",
|
||||
}),
|
||||
}),
|
||||
execute: async ({ query }) => {
|
||||
const response = await queryEngine.query({ query });
|
||||
|
||||
@@ -1,10 +1,9 @@
|
||||
/* eslint-disable @typescript-eslint/no-explicit-any */
|
||||
import { type Client, createClient, createConfig } from "@hey-api/client-fetch";
|
||||
import { type FailedAttemptError } from "p-retry";
|
||||
import { Document, FileReader } from "@llamaindex/core/schema";
|
||||
import { fs, getEnv, path } from "@llamaindex/env";
|
||||
import {
|
||||
type BodyUploadFileApiV1ParsingUploadPost,
|
||||
type BodyUploadFileApiParsingUploadPost,
|
||||
type FailPageMode,
|
||||
type ParserLanguages,
|
||||
type ParsingMode,
|
||||
@@ -33,33 +32,6 @@ type WriteStream = {
|
||||
// eslint-disable-next-line no-var
|
||||
var process: any;
|
||||
|
||||
function handleFailedAttempt(
|
||||
error: FailedAttemptError,
|
||||
jobId: string,
|
||||
verbose: boolean,
|
||||
) {
|
||||
// Retry only on 5XX or socket errors.
|
||||
const status = (error.cause as any)?.response?.status;
|
||||
if (
|
||||
!(
|
||||
(status && status >= 500 && status < 600) ||
|
||||
((error.cause as any)?.code &&
|
||||
((error.cause as any).code === "ECONNRESET" ||
|
||||
(error.cause as any).code === "ETIMEDOUT" ||
|
||||
(error.cause as any).code === "ECONNREFUSED")) ||
|
||||
(status && status === 404)
|
||||
)
|
||||
) {
|
||||
throw error;
|
||||
}
|
||||
|
||||
if (verbose) {
|
||||
console.warn(
|
||||
`Attempting to get job ${jobId} result (attempt ${error.attemptNumber}) failed. Retrying...`,
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Represents a reader for parsing files using the LlamaParse API.
|
||||
* See https://github.com/run-llama/llama_parse
|
||||
@@ -214,18 +186,6 @@ export class LlamaParseReader extends FileReader {
|
||||
page_footer_suffix?: string | undefined;
|
||||
merge_tables_across_pages_in_markdown?: boolean | undefined;
|
||||
extract_printed_page_number?: boolean | undefined;
|
||||
tier?: string | undefined;
|
||||
version?: string | undefined;
|
||||
layout_aware?: boolean | undefined;
|
||||
line_level_bounding_box?: boolean | undefined;
|
||||
specialized_image_parsing?: boolean | undefined;
|
||||
aggressive_table_extraction?: boolean | undefined;
|
||||
preserve_very_small_text?: boolean | undefined;
|
||||
spreadsheet_force_formula_computation?: boolean | undefined;
|
||||
inline_images_in_markdown?: boolean | undefined;
|
||||
keep_page_separator_when_merging_tables?: boolean | undefined;
|
||||
remove_hidden_text?: boolean | undefined;
|
||||
presentation_out_of_bounds_content?: boolean | undefined;
|
||||
|
||||
constructor(
|
||||
params: Partial<Omit<LlamaParseReader, "language" | "apiKey">> & {
|
||||
@@ -423,27 +383,11 @@ export class LlamaParseReader extends FileReader {
|
||||
merge_tables_across_pages_in_markdown:
|
||||
this.merge_tables_across_pages_in_markdown,
|
||||
extract_printed_page_number: this.extract_printed_page_number,
|
||||
tier: this.tier,
|
||||
version: this.version,
|
||||
layout_aware: this.layout_aware,
|
||||
line_level_bounding_box: this.line_level_bounding_box,
|
||||
specialized_image_parsing: this.specialized_image_parsing,
|
||||
aggressive_table_extraction: this.aggressive_table_extraction,
|
||||
preserve_very_small_text: this.preserve_very_small_text,
|
||||
spreadsheet_force_formula_computation:
|
||||
this.spreadsheet_force_formula_computation,
|
||||
inline_images_in_markdown: this.inline_images_in_markdown,
|
||||
webhook_configurations: undefined,
|
||||
keep_page_separator_when_merging_tables:
|
||||
this.keep_page_separator_when_merging_tables,
|
||||
remove_hidden_text: this.remove_hidden_text,
|
||||
presentation_out_of_bounds_content:
|
||||
this.presentation_out_of_bounds_content,
|
||||
} satisfies {
|
||||
[Key in keyof BodyUploadFileApiV1ParsingUploadPost]-?:
|
||||
| BodyUploadFileApiV1ParsingUploadPost[Key]
|
||||
[Key in keyof BodyUploadFileApiParsingUploadPost]-?:
|
||||
| BodyUploadFileApiParsingUploadPost[Key]
|
||||
| undefined;
|
||||
} as unknown as BodyUploadFileApiV1ParsingUploadPost;
|
||||
} as unknown as BodyUploadFileApiParsingUploadPost;
|
||||
|
||||
const response = await uploadFileApiV1ParsingUploadPost({
|
||||
client: this.#client,
|
||||
@@ -495,8 +439,26 @@ export class LlamaParseReader extends FileReader {
|
||||
}),
|
||||
{
|
||||
retries: this.maxErrorCount,
|
||||
onFailedAttempt: (error) =>
|
||||
handleFailedAttempt(error, jobId, this.verbose),
|
||||
onFailedAttempt: (error) => {
|
||||
// Retry only on 5XX or socket errors.
|
||||
const status = (error.cause as any)?.response?.status;
|
||||
if (
|
||||
!(
|
||||
(status && status >= 500 && status < 600) ||
|
||||
((error.cause as any)?.code &&
|
||||
((error.cause as any).code === "ECONNRESET" ||
|
||||
(error.cause as any).code === "ETIMEDOUT" ||
|
||||
(error.cause as any).code === "ECONNREFUSED"))
|
||||
)
|
||||
) {
|
||||
throw error;
|
||||
}
|
||||
if (this.verbose) {
|
||||
console.warn(
|
||||
`Attempting to get job ${jobId} result (attempt ${error.attemptNumber}) failed. Retrying...`,
|
||||
);
|
||||
}
|
||||
},
|
||||
},
|
||||
);
|
||||
} catch (e: any) {
|
||||
@@ -509,69 +471,49 @@ export class LlamaParseReader extends FileReader {
|
||||
const status = (data as Record<string, unknown>)["status"];
|
||||
|
||||
if (status === "SUCCESS") {
|
||||
let resultData;
|
||||
switch (resultType) {
|
||||
case "json": {
|
||||
const resultData = await pRetry(
|
||||
() =>
|
||||
getJobJsonResultApiV1ParsingJobJobIdResultJsonGet({
|
||||
client: this.#client,
|
||||
throwOnError: true,
|
||||
path: { job_id: jobId },
|
||||
query: {
|
||||
organization_id: this.organization_id ?? null,
|
||||
},
|
||||
signal: AbortSignal.timeout(this.maxTimeout * 1000),
|
||||
}),
|
||||
{
|
||||
retries: this.maxErrorCount,
|
||||
onFailedAttempt: (error) =>
|
||||
handleFailedAttempt(error, jobId, this.verbose),
|
||||
},
|
||||
);
|
||||
return resultData.data;
|
||||
resultData =
|
||||
await getJobJsonResultApiV1ParsingJobJobIdResultJsonGet({
|
||||
client: this.#client,
|
||||
throwOnError: true,
|
||||
path: { job_id: jobId },
|
||||
query: {
|
||||
organization_id: this.organization_id ?? null,
|
||||
},
|
||||
signal: AbortSignal.timeout(this.maxTimeout * 1000),
|
||||
});
|
||||
break;
|
||||
}
|
||||
case "markdown": {
|
||||
const resultData = await pRetry(
|
||||
() =>
|
||||
getJobResultApiV1ParsingJobJobIdResultMarkdownGet({
|
||||
client: this.#client,
|
||||
throwOnError: true,
|
||||
path: { job_id: jobId },
|
||||
query: {
|
||||
organization_id: this.organization_id ?? null,
|
||||
},
|
||||
signal: AbortSignal.timeout(this.maxTimeout * 1000),
|
||||
}),
|
||||
{
|
||||
retries: this.maxErrorCount,
|
||||
onFailedAttempt: (error) =>
|
||||
handleFailedAttempt(error, jobId, this.verbose),
|
||||
},
|
||||
);
|
||||
return resultData.data;
|
||||
resultData =
|
||||
await getJobResultApiV1ParsingJobJobIdResultMarkdownGet({
|
||||
client: this.#client,
|
||||
throwOnError: true,
|
||||
path: { job_id: jobId },
|
||||
query: {
|
||||
organization_id: this.organization_id ?? null,
|
||||
},
|
||||
signal: AbortSignal.timeout(this.maxTimeout * 1000),
|
||||
});
|
||||
break;
|
||||
}
|
||||
case "text": {
|
||||
const resultData = await pRetry(
|
||||
() =>
|
||||
getJobTextResultApiV1ParsingJobJobIdResultTextGet({
|
||||
client: this.#client,
|
||||
throwOnError: true,
|
||||
path: { job_id: jobId },
|
||||
query: {
|
||||
organization_id: this.organization_id ?? null,
|
||||
},
|
||||
signal: AbortSignal.timeout(this.maxTimeout * 1000),
|
||||
}),
|
||||
{
|
||||
retries: this.maxErrorCount,
|
||||
onFailedAttempt: (error) =>
|
||||
handleFailedAttempt(error, jobId, this.verbose),
|
||||
},
|
||||
);
|
||||
|
||||
return resultData.data;
|
||||
resultData =
|
||||
await getJobTextResultApiV1ParsingJobJobIdResultTextGet({
|
||||
client: this.#client,
|
||||
throwOnError: true,
|
||||
path: { job_id: jobId },
|
||||
query: {
|
||||
organization_id: this.organization_id ?? null,
|
||||
},
|
||||
signal: AbortSignal.timeout(this.maxTimeout * 1000),
|
||||
});
|
||||
break;
|
||||
}
|
||||
}
|
||||
return resultData.data;
|
||||
} else if (status === "PENDING") {
|
||||
if (this.verbose && tries % 10 === 0) {
|
||||
this.stdout?.write(".");
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
import { FailPageMode, ParserLanguages, ParsingMode } from "./client";
|
||||
|
||||
import { z } from "zod/v4";
|
||||
import { z } from "zod";
|
||||
|
||||
type Language = ParserLanguages;
|
||||
const VALUES: [Language, ...Language[]] = [
|
||||
@@ -52,10 +52,9 @@ export const parseFormSchema = z.object({
|
||||
html_remove_navigation_elements: z.boolean().optional(),
|
||||
http_proxy: z
|
||||
.string()
|
||||
.url({
|
||||
error:
|
||||
'Set a valid URL for the HTTP proxy, e.g., "http://proxy.example.com:8080"',
|
||||
})
|
||||
.url(
|
||||
'Set a valid URL for the HTTP proxy, e.g., "http://proxy.example.com:8080"',
|
||||
)
|
||||
.refine(
|
||||
(url) => {
|
||||
try {
|
||||
@@ -68,7 +67,7 @@ export const parseFormSchema = z.object({
|
||||
}
|
||||
},
|
||||
{
|
||||
error: "Invalid HTTP proxy URL",
|
||||
message: "Invalid HTTP proxy URL",
|
||||
},
|
||||
)
|
||||
.optional(),
|
||||
@@ -101,7 +100,7 @@ export const parseFormSchema = z.object({
|
||||
vendor_multimodal_model_name: z.string().optional(),
|
||||
model: z.string().optional(),
|
||||
webhook_url: z.string().url().optional(),
|
||||
parse_mode: z.enum(ParsingMode).nullable().optional(),
|
||||
parse_mode: z.nativeEnum(ParsingMode).nullable().optional(),
|
||||
system_prompt: z.string().optional(),
|
||||
system_prompt_append: z.string().optional(),
|
||||
user_prompt: z.string().optional(),
|
||||
@@ -130,7 +129,7 @@ export const parseFormSchema = z.object({
|
||||
compact_markdown_table: z.boolean().optional(),
|
||||
markdown_table_multiline_header_separator: z.string().optional(),
|
||||
page_error_tolerance: z.number().min(0).max(1).optional(),
|
||||
replace_failed_page_mode: z.enum(FailPageMode).nullable().optional(),
|
||||
replace_failed_page_mode: z.nativeEnum(FailPageMode).nullable().optional(),
|
||||
replace_failed_page_with_error_message_prefix: z.string().optional(),
|
||||
replace_failed_page_with_error_message_suffix: z.string().optional(),
|
||||
});
|
||||
|
||||
Reference in New Issue
Block a user