Parse Your First Document in 3 Minutes ⚡

This quickstart gets you from zero to parsing documents with Lexa. By the end, you’ll have made your first successful API call.

Requirements: Python 3.9+ • 3 minutes of your time

Step 1: Installation (30 seconds)

pip install cerevox

Step 2: Get API Key (30 seconds)

Get your API key

Visit cerevox.ai/lexa and sign up for your free API key

Copy the key

Save your API key - you’ll need it in the next step

Step 3: Authentication Setup (30 seconds)

export CEREVOX_API_KEY="your-api-key-here"

export CEREVOX_API_KEY="your-api-key-here"

from cerevox import Lexa

client = Lexa(api_key="your-api-key-here")

.env

CEREVOX_API_KEY=your-api-key-here

import os
from dotenv import load_dotenv
from cerevox import Lexa

load_dotenv()
client = Lexa()  # Automatically reads from environment

Step 4: First API Call (60 seconds)

Copy and run this code to parse your first document:

from cerevox import Lexa

# Initialize client (uses CEREVOX_API_KEY from environment)
client = Lexa()

# Parse a local file - replace with your file path
documents = client.parse(["path/to/your/document.pdf"])

# See what you got back
doc = documents[0]
print(f"✅ Success! Extracted {len(doc.content)} characters")
print(f"📊 Found {len(doc.tables)} tables")
print(f"📄 Content preview: {doc.content[:200]}...")

# That's it! Your document is now structured data

from cerevox import Lexa

# Initialize client (uses CEREVOX_API_KEY from environment)
client = Lexa()

# Parse a local file - replace with your file path
documents = client.parse(["path/to/your/document.pdf"])

# See what you got back
doc = documents[0]
print(f"✅ Success! Extracted {len(doc.content)} characters")
print(f"📊 Found {len(doc.tables)} tables")
print(f"📄 Content preview: {doc.content[:200]}...")

# That's it! Your document is now structured data

from cerevox import Lexa

# Parse raw text content (perfect for testing)
client = Lexa()
content = b"Invoice #12345\nTotal: $1,299.99\nVendor: Acme Corp"

documents = client.parse(content)
doc = documents[0]

print(f"✅ Parsed: {doc.content}")
# Returns: "Invoice #12345\nTotal: $1,299.99\nVendor: Acme Corp"

# Ready for your application!

from cerevox import Lexa

client = Lexa()

# Parse documents directly from URLs
documents = client.parse_urls([
    "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
])

print(f"✅ Parsed {len(documents)} documents from URL")
print(f"📄 Content: {documents[0].content[:100]}...")

Step 5: Test Your Setup (30 seconds)

Run this verification script to confirm everything works:

from cerevox import Lexa, LexaError

def verify_setup():
    try:
        client = Lexa()
        
        # Quick test with sample content
        test_content = b"Test document for Lexa API verification."
        documents = client.parse(test_content)
        
        if documents and len(documents) > 0:
            print("🎉 Perfect! Lexa is working correctly.")
            print(f"📄 Test result: {documents[0].content}")
            return True
    
    except LexaError as e:
        print(f"❌ API Error: {e.message}")
        print("💡 Check your API key and try again")
        return False
    except Exception as e:
        print(f"❌ Error: {e}")
        return False

# Run verification
if verify_setup():
    print("\n✅ You're ready to parse documents with Lexa!")

You’re Ready! 🎉 Lexa is configured and working. Start parsing your documents!

What’s Next?

Real Examples

Copy-paste ready examples with real data

Async Processing

Process multiple documents concurrently (recommended)

Vector DB Integration

Get chunks ready for your RAG applications

API Reference

Complete method signatures and parameters

Common Next Steps

Async Processing (Recommended)

import asyncio
from cerevox import AsyncLexa

async def parse_multiple():
    async with AsyncLexa() as client:
        # Process multiple files concurrently - much faster!
        documents = await client.parse([
            "report1.pdf", 
            "report2.docx",
            "data.xlsx"
        ])
        
        print(f"✅ Processed {len(documents)} documents")
        
        # Get vector DB ready chunks
        chunks = documents.get_all_text_chunks(target_size=500)
        print(f"🔗 Ready for embedding: {len(chunks)} chunks")

asyncio.run(parse_multiple())

Cloud Storage Integration

# Parse from Amazon S3
documents = client.parse_s3_folder(
    bucket_name="my-documents",
    folder_path="invoices/"
)

# Parse from SharePoint
documents = client.parse_sharepoint_folder(
    site_id="your-site-id",
    drive_id="your-drive-id", 
    folder_path="Documents"
)

print(f"✅ Processed {len(documents)} documents from cloud storage")

Vector Database Ready

# Parse and get RAG-optimized chunks
documents = client.parse(["document.pdf"])

chunks = documents.get_all_text_chunks(
    target_size=500,        # Perfect for most embeddings
    overlap_size=50,        # Prevents context loss
    include_metadata=True   # Rich metadata included
)

# Each chunk is ready for your vector database
for chunk in chunks[:3]:
    print(f"Chunk: {chunk.content[:100]}...")
    print(f"Metadata: {chunk.metadata}")

Having Issues?

Authentication Problems

Connection Issues

File Issues

Ready to build? Check out our code examples or join the Discord community for help.

On this page

Parse Your First Document in 3 Minutes ⚡
Step 1: Installation (30 seconds)
Step 2: Get API Key (30 seconds)
Step 3: Authentication Setup (30 seconds)
Step 4: First API Call (60 seconds)
Step 5: Test Your Setup (30 seconds)
What’s Next?
Common Next Steps
Having Issues?

Parse Your First Document in 3 Minutes ⚡

This quickstart gets you from zero to parsing documents with Lexa. By the end, you’ll have made your first successful API call.

Requirements: Python 3.9+ • 3 minutes of your time

Step 1: Installation (30 seconds)

pip install cerevox

Step 2: Get API Key (30 seconds)

Get your API key

Visit cerevox.ai/lexa and sign up for your free API key

Copy the key

Save your API key - you’ll need it in the next step

Step 3: Authentication Setup (30 seconds)

export CEREVOX_API_KEY="your-api-key-here"

export CEREVOX_API_KEY="your-api-key-here"

from cerevox import Lexa

client = Lexa(api_key="your-api-key-here")

.env

CEREVOX_API_KEY=your-api-key-here

import os
from dotenv import load_dotenv
from cerevox import Lexa

load_dotenv()
client = Lexa()  # Automatically reads from environment

Step 4: First API Call (60 seconds)

Copy and run this code to parse your first document:

from cerevox import Lexa

# Initialize client (uses CEREVOX_API_KEY from environment)
client = Lexa()

# Parse a local file - replace with your file path
documents = client.parse(["path/to/your/document.pdf"])

# See what you got back
doc = documents[0]
print(f"✅ Success! Extracted {len(doc.content)} characters")
print(f"📊 Found {len(doc.tables)} tables")
print(f"📄 Content preview: {doc.content[:200]}...")

# That's it! Your document is now structured data

from cerevox import Lexa

# Initialize client (uses CEREVOX_API_KEY from environment)
client = Lexa()

# Parse a local file - replace with your file path
documents = client.parse(["path/to/your/document.pdf"])

# See what you got back
doc = documents[0]
print(f"✅ Success! Extracted {len(doc.content)} characters")
print(f"📊 Found {len(doc.tables)} tables")
print(f"📄 Content preview: {doc.content[:200]}...")

# That's it! Your document is now structured data

from cerevox import Lexa

# Parse raw text content (perfect for testing)
client = Lexa()
content = b"Invoice #12345\nTotal: $1,299.99\nVendor: Acme Corp"

documents = client.parse(content)
doc = documents[0]

print(f"✅ Parsed: {doc.content}")
# Returns: "Invoice #12345\nTotal: $1,299.99\nVendor: Acme Corp"

# Ready for your application!

from cerevox import Lexa

client = Lexa()

# Parse documents directly from URLs
documents = client.parse_urls([
    "https://www.w3.org/WAI/ER/tests/xhtml/testfiles/resources/pdf/dummy.pdf"
])

print(f"✅ Parsed {len(documents)} documents from URL")
print(f"📄 Content: {documents[0].content[:100]}...")

Step 5: Test Your Setup (30 seconds)

Run this verification script to confirm everything works:

from cerevox import Lexa, LexaError

def verify_setup():
    try:
        client = Lexa()
        
        # Quick test with sample content
        test_content = b"Test document for Lexa API verification."
        documents = client.parse(test_content)
        
        if documents and len(documents) > 0:
            print("🎉 Perfect! Lexa is working correctly.")
            print(f"📄 Test result: {documents[0].content}")
            return True
    
    except LexaError as e:
        print(f"❌ API Error: {e.message}")
        print("💡 Check your API key and try again")
        return False
    except Exception as e:
        print(f"❌ Error: {e}")
        return False

# Run verification
if verify_setup():
    print("\n✅ You're ready to parse documents with Lexa!")

You’re Ready! 🎉 Lexa is configured and working. Start parsing your documents!

What’s Next?

Real Examples

Copy-paste ready examples with real data

Async Processing

Process multiple documents concurrently (recommended)

Vector DB Integration

Get chunks ready for your RAG applications

API Reference

Complete method signatures and parameters

Common Next Steps

Async Processing (Recommended)

import asyncio
from cerevox import AsyncLexa

async def parse_multiple():
    async with AsyncLexa() as client:
        # Process multiple files concurrently - much faster!
        documents = await client.parse([
            "report1.pdf", 
            "report2.docx",
            "data.xlsx"
        ])
        
        print(f"✅ Processed {len(documents)} documents")
        
        # Get vector DB ready chunks
        chunks = documents.get_all_text_chunks(target_size=500)
        print(f"🔗 Ready for embedding: {len(chunks)} chunks")

asyncio.run(parse_multiple())

Cloud Storage Integration

# Parse from Amazon S3
documents = client.parse_s3_folder(
    bucket_name="my-documents",
    folder_path="invoices/"
)

# Parse from SharePoint
documents = client.parse_sharepoint_folder(
    site_id="your-site-id",
    drive_id="your-drive-id", 
    folder_path="Documents"
)

print(f"✅ Processed {len(documents)} documents from cloud storage")

Vector Database Ready

# Parse and get RAG-optimized chunks
documents = client.parse(["document.pdf"])

chunks = documents.get_all_text_chunks(
    target_size=500,        # Perfect for most embeddings
    overlap_size=50,        # Prevents context loss
    include_metadata=True   # Rich metadata included
)

# Each chunk is ready for your vector database
for chunk in chunks[:3]:
    print(f"Chunk: {chunk.content[:100]}...")
    print(f"Metadata: {chunk.metadata}")

Having Issues?

Authentication Problems

Connection Issues

File Issues

Ready to build? Check out our code examples or join the Discord community for help.

On this page

Parse Your First Document in 3 Minutes ⚡
Step 1: Installation (30 seconds)
Step 2: Get API Key (30 seconds)
Step 3: Authentication Setup (30 seconds)
Step 4: First API Call (60 seconds)
Step 5: Test Your Setup (30 seconds)
What’s Next?
Common Next Steps
Having Issues?

Quickstart

Parse Your First Document in 3 Minutes ⚡

Step 1: Installation (30 seconds)

Step 2: Get API Key (30 seconds)

Step 3: Authentication Setup (30 seconds)

Step 4: First API Call (60 seconds)

Step 5: Test Your Setup (30 seconds)

What’s Next?

Real Examples

Async Processing

Vector DB Integration

API Reference

Common Next Steps

Having Issues?

Getting Started

API Reference

Examples

Guides

Use Cases

Company

Legal

Quickstart

Parse Your First Document in 3 Minutes ⚡

Step 1: Installation (30 seconds)

Step 2: Get API Key (30 seconds)

Step 3: Authentication Setup (30 seconds)

Step 4: First API Call (60 seconds)

Step 5: Test Your Setup (30 seconds)

What’s Next?

Real Examples

Async Processing

Vector DB Integration

API Reference

Common Next Steps

Having Issues?

​Parse Your First Document in 3 Minutes ⚡

​Step 1: Installation (30 seconds)

​Step 2: Get API Key (30 seconds)

​Step 3: Authentication Setup (30 seconds)

​Step 4: First API Call (60 seconds)

​Step 5: Test Your Setup (30 seconds)

​What’s Next?

Real Examples

Async Processing

Vector DB Integration

API Reference

​Common Next Steps

​Having Issues?

Getting Started

API Reference

Examples

Guides

Use Cases

Company

Legal

​Parse Your First Document in 3 Minutes ⚡

​Step 1: Installation (30 seconds)

​Step 2: Get API Key (30 seconds)

​Step 3: Authentication Setup (30 seconds)

​Step 4: First API Call (60 seconds)

​Step 5: Test Your Setup (30 seconds)

​What’s Next?

Real Examples

Async Processing

Vector DB Integration

API Reference

​Common Next Steps

​Having Issues?

Parse Your First Document in 3 Minutes ⚡

Step 1: Installation (30 seconds)

Step 2: Get API Key (30 seconds)

Step 3: Authentication Setup (30 seconds)

Step 4: First API Call (60 seconds)

Step 5: Test Your Setup (30 seconds)

What’s Next?

Common Next Steps

Having Issues?

Parse Your First Document in 3 Minutes ⚡

Step 1: Installation (30 seconds)

Step 2: Get API Key (30 seconds)

Step 3: Authentication Setup (30 seconds)

Step 4: First API Call (60 seconds)

Step 5: Test Your Setup (30 seconds)

What’s Next?

Common Next Steps

Having Issues?