entry-on-kitchen 0.3.2

Official Python Module for using entry blocks on kitchen

Entry on Kitchen Python Library

Official Python module for executing recipes on the Entry on Kitchen API. Supports both synchronous execution and real-time HTTP streaming.

Installation

pip install entry-on-kitchen

Quick Start

from entry_on_kitchen import KitchenClient

# Initialize the client with your auth code
client = KitchenClient(
    auth_code="your-auth-code-here",
    entry_point="beta"  # Optional: use "" for production
)

# Synchronous execution
result = client.sync(
    recipe_id="your-recipe-id",
    entry_id="your-entry-id",
    body={"message": "Hello, Kitchen!"}
)

print(result)

KitchenClient Class

The KitchenClient class provides a simple interface for executing recipes.

Constructor

KitchenClient(auth_code, entry_point="")

Parameters:

• auth_code (str, required): Your X-Entry-Auth-Code for authentication
• entry_point (str, optional): Entry point environment (e.g., "beta" for beta). Defaults to "" (production)

Raises:

• ValueError: If auth_code is not provided or empty

Methods

sync(recipe_id, entry_id, body, use_kitchen_billing=False, llm_override=None, api_key_override=None)

Execute a recipe synchronously and wait for the complete result.

Parameters:

• recipe_id (str): The ID of the pipeline/recipe
• entry_id (str): The ID of the entry block
• body (dict or str): Request body data
• use_kitchen_billing (bool, optional): Enable Kitchen billing
• llm_override (str, optional): Override the LLM model (e.g., "gpt-4", "claude-3")
• api_key_override (dict, optional): Override API keys for external services

Returns: Dictionary containing:

• runId: The execution run ID
• status: Execution status ("finished", "error", etc.)
• result: The execution result (if successful)
• error: Error message (if failed)
• exitBlock: Exit block information

Example:

result = client.sync(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body={
        "message": "Hello!",
        "provider": "google_genai",
        "model": "gemini-2.5-flash"
    }
)

if result["status"] == "finished":
    print("Success:", result["result"])
else:
    print("Error:", result["error"])

stream(recipe_id, entry_id, body, use_kitchen_billing=False, llm_override=None, api_key_override=None)

Execute a recipe with real-time streaming. Yields events as they arrive.

Parameters:

• recipe_id (str): The ID of the pipeline/recipe
• entry_id (str): The ID of the entry block
• body (dict or str): Request body data
• use_kitchen_billing (bool, optional): Enable Kitchen billing
• llm_override (str, optional): Override the LLM model (e.g., "gpt-4", "claude-3")
• api_key_override (dict, optional): Override API keys for external services

Yields: Dictionary objects representing stream events with keys:

• runId: The execution run ID
• type: Event type (see types below)
• time: Timestamp of the event
• data: Event-specific data
• socket: Socket ID (for "result" and "delta" events)
• statusCode: HTTP status code

Event Types:

• "progress": Execution progress updates
• "result": Output data from blocks
• "delta": Incremental content updates (for streaming LLM responses)
• "info": Informational messages
• "end": Final result (marks completion)

Example:

for event in client.stream(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body={"message": "Hello!"}
):
    event_type = event["type"]

    if event_type == "progress":
        data = event["data"]
        print(f"Progress: {data['blockPosition']}/{data['blocksToExitBlock']}")

    elif event_type == "result":
        socket = event["socket"]
        data = event["data"]
        print(f"Result from {socket}: {data}")

    elif event_type == "delta":
        socket = event["socket"]
        delta = event["data"]
        print(f"Delta update for {socket}: {delta}")

    elif event_type == "end":
        print("Complete!")
        print(f"Final result: {event['data']}")

stream_raw(recipe_id, entry_id, body)

Execute a recipe with streaming, yielding raw JSON strings. Useful for custom parsing.

Example:

for raw_json in client.stream_raw(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body={"message": "Hello!"}
):
    print(raw_json)

Complete Examples

Synchronous Execution

from entry_on_kitchen import KitchenClient

client = KitchenClient(auth_code="your-auth-code", entry_point="beta")

result = client.sync(
    recipe_id="my-recipe",
    entry_id="my-entry",
    body={"input": "value"}
)

print(f"Run ID: {result['runId']}")
print(f"Status: {result['status']}")
print(f"Result: {result.get('result')}")

Streaming with Progress Tracking

from entry_on_kitchen import KitchenClient

client = KitchenClient(auth_code="your-auth-code")

result_buffer = {}

for event in client.stream(
    recipe_id="my-recipe",
    entry_id="my-entry",
    body={"input": "value"}
):
    if event["type"] == "progress":
        # Show progress
        block = event["data"]["blockPosition"]
        total = event["data"]["blocksToExitBlock"]
        print(f"\rProgress: {block}/{total} blocks", end="", flush=True)

    elif event["type"] == "result":
        # Store results
        socket = event["socket"]
        result_buffer[socket] = event["data"]
        print(f"\nReceived result from {socket}")

    elif event["type"] == "end":
        print("\nExecution complete!")
        print(f"Final result: {event['data']}")

print("\nAll results:", result_buffer)

Streaming LLM Responses

from entry_on_kitchen import KitchenClient

client = KitchenClient(auth_code="your-auth-code")

full_response = ""

for event in client.stream(
    recipe_id="llm-recipe",
    entry_id="llm-entry",
    body={"prompt": "Tell me a story"}
):
    if event["type"] == "delta":
        # Delta updates contain incremental text
        for op in event["data"]:
            if op[0] == "i":  # Insert operation
                position, length, text = op[1], op[2], op[3]
                full_response += text
                print(text, end="", flush=True)

    elif event["type"] == "end":
        print("\n\nComplete!")

Environment Configuration

Production

client = KitchenClient(auth_code="your-auth-code", entry_point="")
# Uses: https://entry.on.kitchen

Beta

client = KitchenClient(auth_code="your-auth-code", entry_point="beta")
# Uses: https://beta.entry.on.kitchen

Custom Entry Point

client = KitchenClient(auth_code="your-auth-code", entry_point="custom")
# Uses: https://custom.entry.on.kitchen

Optional Features

Kitchen Billing

Enable Kitchen billing for your recipe execution:

result = client.sync(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body={"message": "Hello!"},
    use_kitchen_billing=True
)

LLM Model Override

Override the LLM model used in your recipe:

result = client.sync(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body={"message": "Write a poem"},
    llm_override="gpt-4"
)

# Or with streaming
for event in client.stream(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body={"message": "Write a poem"},
    llm_override="claude-3"
):
    # Handle events
    pass

Combining Options

You can use both options together:

result = client.sync(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body={"message": "Hello!"},
    use_kitchen_billing=True,
    llm_override="gpt-4"
)

Requirements

• Python 3.7 or higher
• requests library

Error Handling

from entry_on_kitchen import KitchenClient
import requests

client = KitchenClient(auth_code="your-auth-code")

try:
    result = client.sync(
        recipe_id="recipe-123",
        entry_id="entry-456",
        body={"input": "value"}
    )
except requests.HTTPError as e:
    print(f"HTTP Error: {e}")
except ValueError as e:
    print(f"Value Error: {e}")
except Exception as e:
    print(f"Unexpected error: {e}")

Migration from v0.x

Version 0.3.0 is a breaking change from v0.x. Here's how to migrate:

Old API (v0.x)

from entry_on_kitchen.Kitchen import EntryBlock

entry = EntryBlock(
    pipelineId="recipe-123",
    entryBlockId="entry-456",
    entryAuthCode="your-auth-code",
    entryPoint="beta"
)

# Synchronous
result = entry.runSync(input_data)

# Asynchronous with polling
result = await entry.runAsync(input_data)

New API (v0.3.0)

from entry_on_kitchen import KitchenClient

client = KitchenClient(
    auth_code="your-auth-code",
    entry_point="beta"
)

# Synchronous
result = client.sync(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body=input_data
)

# Streaming (replaces async/polling)
for event in client.stream(
    recipe_id="recipe-123",
    entry_id="entry-456",
    body=input_data
):
    handle_event(event)

License

Copyright © Endevre Technologies

Support

For issues and questions, contact: [e-mail]