spykio-client 1.2.0

A client library for interacting with the Spykio API.

Spykio Client

A Python client library for interacting with the Spykio API.

Installation

pip install spykio-client

API Keys

To use this client, you'll need an API key from Spykio. Visit the Spykio website to sign up and obtain your API key.

Usage

Initializing the Client

from spykio import SpykioClient

client = SpykioClient(api_key="your-api-key")

Searching in an Index

Use the query.search method to search for information in a specific index:

def search_example():
    try:
        result = client.query.search(
            index="your-index-name",
            user_query="What hotel did I stay at in Warsaw?",
            accurate_match=False,  # Optional, defaults to False
            get_relevant_info=False  # Optional, defaults to False
        )
        
        print("Search results:", result)
    except Exception as error:
        print("Error searching:", error)

Search for Complete Documents (Default Behavior)

By default (accurate_match=False, get_relevant_info=False), the API returns complete documents:

# Using default parameters (accurate_match=False, get_relevant_info=False)
result = client.query.search(
    index="your-index-name",
    user_query="What hotel did I stay at in Warsaw?"
)

# Sample response:
# {
#   "documents": [
#     {
#       "id": "abc123-example-id",
#       "summary": "This document is a booking confirmation for a hotel in Warsaw, Poland.",
#       "content": "# Hotel Booking Confirmation\n\n**Hotel Name: Warsaw Central Hotel**\n\n* Address: Example Street 123, Warsaw, Poland\n...",
#       "created_at": "2023-04-09T17:40:43.122Z"
#     }
#   ],
#   "metrics": {
#     "totalTime": 433,
#     "resultCount": 1,
#     "usedExtraction": False
#   }
# }

Search with Relevant Sections

When accurate_match and get_relevant_info are set to True, the API returns focused relevant sections of content:

result = client.query.search(
    index="your-index-name",
    user_query="What hotel did I stay at in Warsaw?",
    accurate_match=True,
    get_relevant_info=True
)

# Sample response:
# {
#   "documents": [],
#   "relevantSections": [
#     {
#       "text": "Hotel Name: Warsaw Central Hotel\n\n* Address: Example Street 123, Warsaw, Poland",
#       "relevanceScore": 0.95,
#       "explanation": "This section provides the location of the hotel in Warsaw, Poland.",
#       "documentId": "abc123-example-id"
#     },
#     {
#       "text": "| CHECK-IN | CHECK-OUT | ROOMS | NIGHTS |\n| -------- | --------- | ----- | ------ |\n| June 15 | June 16 | 1 | 1 |",
#       "relevanceScore": 0.85,
#       "explanation": "This section confirms the dates of the hotel stay.",
#       "documentId": "abc123-example-id"
#     }
#   ],
#   "metrics": {
#     "totalTime": 2513,
#     "resultCount": 1,
#     "extractionCount": 1,
#     "sectionsCount": 2,
#     "usedExtraction": True
#   }
# }

Listing Documents

You can retrieve a paginated list of all documents in an index using the documents.list method:

def list_documents_example():
    try:
        result = client.documents.list(
            index="your-index-name",
            region="EU",      # Optional, defaults to "EU"
            limit=20,         # Optional, defaults to 100
            offset=0          # Optional, defaults to 0
        )
        
        print("Documents:", result.get("documents"))
        print("Pagination info:", result.get("pagination"))
        
        # Sample response:
        # {
        #   "success": True,
        #   "documents": [
        #     {
        #       "id": "abc123-example-id",
        #       "summary": "Document summary text",
        #       "content": "Full document content...",
        #       "created_at": "2023-04-09T17:40:43.122Z"
        #     },
        #     # More documents...
        #   ],
        #   "pagination": {
        #     "total": 42,
        #     "limit": 20,
        #     "offset": 0,
        #     "hasMore": True
        #   }
        # }
    except Exception as error:
        print("Error listing documents:", error)

Extracting Information from a Specific Document

You can extract specific information from a document using the documents.extract method:

def extract_information_example():
    try:
        result = client.documents.extract(
            index="your-index-name",
            document_id="abc123-example-id",
            user_query="What is the hotel address?",
            region="EU"       # Optional, defaults to "EU"
        )
        
        print("Document summary:", result.get("documentSummary"))
        print("Relevant sections:", result.get("relevantSections"))
        
        # Sample response:
        # {
        #   "documentId": "abc123-example-id",
        #   "documentSummary": "This document is a booking confirmation for a hotel in Warsaw, Poland.",
        #   "relevantSections": [
        #     {
        #       "text": "Hotel Name: Warsaw Central Hotel\n\n* Address: Example Street 123, Warsaw, Poland",
        #       "relevanceScore": 0.95,
        #       "explanation": "This section contains the hotel address information.",
        #       "documentId": "abc123-example-id"
        #     }
        #   ],
        #   "metrics": {
        #     "totalTime": 1256,
        #     "extractionTime": 950,
        #     "sectionsCount": 1
        #   }
        # }
    except Exception as error:
        print("Error extracting information:", error)

Uploading Files

You can upload files to an index using the files.upload method:

Upload using base64 string

def upload_file_example():
    try:
        result = client.files.upload(
            index="your-index-name",
            mime_type="application/pdf",  # MIME type of the file
            base64_string="base64EncodedString"  # Base64 encoded file content
        )
        
        print("Upload result:", result)
        # Sample response:
        # {
        #   "success": True,
        #   "id": "abc123-example-id",
        #   "fileName": "uploaded-document.pdf"
        # }
    except Exception as error:
        print("Error uploading file:", error)

Upload using text content

def upload_content_example():
    try:
        result = client.files.upload(
            index="your-index-name",
            content="This is the text content to be uploaded."
        )
        
        print("Upload result:", result)
        # Sample response:
        # {
        #   "success": True,
        #   "id": "def456-example-id",
        #   "fileName": "text-content.txt"
        # }
    except Exception as error:
        print("Error uploading content:", error)

Removing Documents

You can remove documents from an index using the files.remove method:

def remove_document_example():
    try:
        result = client.files.remove(
            index="your-index-name",
            document_id="abc123-example-id",  # The ID of the document to remove
            region="EU"  # Optional, defaults to "EU"
        )
        
        print("Removal result:", result)
        # Sample response:
        # {
        #   "success": True,
        #   "message": "Document successfully removed"
        # }
    except Exception as error:
        print("Error removing document:", error)

API Reference

SpykioClient(api_key, base_url="https://api.spyk.io")

Creates a new Spykio client instance.

Parameters:

• api_key (required): Your Spykio API key
• base_url (optional): API base URL. Defaults to "https://api.spyk.io"

client.query.search(index, user_query, accurate_match=False, get_relevant_info=False)

Searches for information in a specific index.

Parameters:

• index (required): The name of the index to search in
• user_query (required): The search query
• accurate_match (optional): When True, performs more precise matching. Defaults to False
• get_relevant_info (optional): When True, returns specific relevant sections rather than full documents. Defaults to False

Returns: Dict containing search results with either:

• Full documents with only id, content, summary, and created_at properties (when accurate_match and get_relevant_info are False)
• Relevant sections with explanations (when both parameters are True)
• Metrics information (with tokenUsage removed)

client.documents.list(index, region="EU", limit=100, offset=0)

Retrieves a paginated list of all documents in an index.

Parameters:

• index (required): The name of the index to list documents from
• region (optional): The region where the index is located. Defaults to "EU"
• limit (optional): Maximum number of documents to return. Defaults to 100
• offset (optional): Number of documents to skip for pagination. Defaults to 0

Returns: Dict containing:

• success: Boolean indicating whether the operation was successful
• documents: List of document dicts with id, content, summary, and created_at properties
• pagination: Dict with pagination details (total, limit, offset, hasMore)

client.documents.extract(index, document_id, user_query, region="EU")

Extracts specific information from a document based on a query.

Parameters:

• index (required): The name of the index containing the document
• document_id (required): The ID of the document to extract information from
• user_query (required): The query to extract specific information from the document
• region (optional): The region where the index is located. Defaults to "EU"

Returns: Dict containing:

• documentId: The ID of the document
• documentSummary: A summary of the document
• relevantSections: List of extracted sections relevant to the query, each with text, relevanceScore, explanation, and documentId
• metrics: Dict with performance metrics (with tokenUsage removed)

client.files.upload(index, mime_type=None, base64_string=None, content=None)

Uploads a file or content to a specific index.

Parameters:

• index (required): The name of the index to upload to
• For file uploads: mime_type and base64_string required
• For text uploads: content required

Returns: Dict containing upload result with categorization and metrics information removed

client.files.remove(index, document_id, region="EU")

Removes a document from an index.

Parameters:

• index (required): The name of the index containing the document
• document_id (required): The ID of the document to remove
• region (optional): The region where the index is located. Defaults to "EU"

Returns: Dict containing removal result with metrics information removed