Advanced usage

from memvai import Memv

client = Memv()

# Get raw response with headers
response = client.spaces.with_raw_response().list()

# Access headers
print(response.headers.get('X-Request-ID'))
print(response.headers.get('X-RateLimit-Remaining'))

# Parse the response
spaces = response.parse()
print(spaces.spaces)

import asyncio
from memvai import AsyncMemv

async def main():
    client = AsyncMemv()

    # Execute multiple requests in parallel
    spaces_task = client.spaces.list()
    stats_task = client.spaces.get_stats()

    spaces, stats = await asyncio.gather(spaces_task, stats_task)

    print(f"Spaces: {len(spaces.spaces)}")
    print(f"Total memories: {stats.total_memories}")

asyncio.run(main())

async def upload_files_parallel(space_id: str, file_paths: list[str]):
    """Upload multiple files concurrently."""
    client = AsyncMemv()

    async def upload_file(file_path: str):
        with open(file_path, 'rb') as f:
            return await client.upload.batch.create(
                space_id=space_id,
                files=[f]
            )

    # Upload all files concurrently
    tasks = [upload_file(path) for path in file_paths]
    results = await asyncio.gather(*tasks)

    return [r.batch_id for r in results]

# Usage
files = ["doc1.pdf", "doc2.pdf", "doc3.pdf"]
batch_ids = asyncio.run(upload_files_parallel("space_abc123", files))

import logging
from memvai import Memv

# Configure logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

client = Memv()

# Logging is automatic with MEMV_LOG environment variable