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Python SDK for the Memic Context Engineering API

Project description

Memic Python SDK

Official Python SDK for the Memic Context Engineering API.

Upload documents, process them into searchable chunks, and perform semantic search with metadata filters.

Installation

pip install memic

Quick Start

from memic import Memic, MetadataFilters, PageRange

# Initialize client (uses MEMIC_API_KEY env var if not provided)
client = Memic(api_key="mk_...")

# List projects
projects = client.list_projects()
for p in projects:
    print(f"{p.name}: {p.id}")

# Upload a file (waits for processing by default)
file = client.upload_file(
    project_id="your-project-id",
    file_path="/path/to/document.pdf",
    reference_id="lesson_123"  # Optional: for linking with external systems
)
print(f"Uploaded: {file.id}, status: {file.status}")

# Search with filters
results = client.search(
    query="key findings about climate change",
    project_id="your-project-id",
    top_k=10,
    min_score=0.7,
    filters=MetadataFilters(
        reference_id="TG_G1_Math",
        page_range=PageRange(gte=1, lte=50)
    )
)

for result in results:
    print(f"[{result.score:.2f}] {result.file_name} (p.{result.page_number})")
    print(f"  {result.content[:200]}...")

Features

  • File Upload: 3-step presigned URL flow for efficient uploads
  • Wait for Ready: Automatic polling until file processing completes
  • Semantic Search: Vector similarity search with rich metadata
  • Metadata Filters: Filter by reference_id, page numbers, categories
  • Simple API: Single client class, no complex patterns

Configuration

API Key

Set your API key via environment variable or constructor:

export MEMIC_API_KEY=mk_your_api_key_here
# Or pass directly
client = Memic(api_key="mk_...")

Custom Base URL

For development or self-hosted deployments:

client = Memic(
    api_key="mk_...",
    base_url="https://your-api.example.com"
)

API Reference

Memic Client

client = Memic(
    api_key: str = None,        # Uses MEMIC_API_KEY env var if not provided
    base_url: str = None,       # Default: https://api.memic.ai
    timeout: int = 30           # Request timeout in seconds
)

Methods

list_projects() -> List[Project]

List all projects in your organization.

upload_file(project_id, file_path, ...) -> File

Upload a file to a project.

Parameter Type Default Description
project_id str required Target project ID
file_path str/Path required Path to file
wait_for_ready bool True Wait for processing to complete
reference_id str None External reference ID
metadata dict None Custom metadata
poll_interval float 2.0 Seconds between status checks
poll_timeout float 300 Max wait time in seconds

get_file_status(project_id, file_id) -> File

Get current processing status of a file.

search(query, ...) -> SearchResults

Search for content across documents.

Parameter Type Default Description
query str required Search query
project_id str None Limit to project
file_ids List[str] None Limit to specific files
top_k int 10 Number of results
min_score float 0.7 Minimum similarity score
filters MetadataFilters None Metadata filters

Types

FileStatus

Enum with processing states:

  • UPLOADING, UPLOADED, UPLOAD_FAILED
  • CONVERSION_STARTED, CONVERSION_COMPLETE, CONVERSION_FAILED
  • PARSING_STARTED, PARSING_COMPLETE, PARSING_FAILED
  • CHUNKING_STARTED, CHUNKING_COMPLETE, CHUNKING_FAILED
  • EMBEDDING_STARTED, EMBEDDING_COMPLETE, EMBEDDING_FAILED
  • READY

Properties:

  • .is_failed - True if status indicates failure
  • .is_processing - True if still processing

MetadataFilters

MetadataFilters(
    reference_id: str = None,       # Filter by reference ID
    reference_ids: List[str] = None, # Multiple reference IDs (OR)
    page_number: int = None,        # Exact page match
    page_numbers: List[int] = None, # Multiple pages (OR)
    page_range: PageRange = None,   # Page range
    category: str = None,           # Category filter
    document_type: str = None       # Document type filter
)

Exceptions

from memic import MemicError, AuthenticationError, NotFoundError, APIError

try:
    results = client.search(query="test")
except AuthenticationError:
    print("Invalid API key")
except NotFoundError:
    print("Resource not found")
except APIError as e:
    print(f"API error: {e.status_code} - {e.message}")
except MemicError as e:
    print(f"Error: {e.message}")

Development

# Install dev dependencies
pip install -e ".[dev]"

# Run tests
pytest tests/

# Type check
mypy src/memic/

# Lint
ruff check src/

License

MIT License - see LICENSE for details.

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