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Vadalog API

The Vadalog API provides direct access to the Vadalog reasoning engine for evaluating logic programs and managing execution.

Evaluate Program​

Execute a Vadalog program with specified parameters.

import prometheux_chain as px

program = """
@input("products").
@output("expensive_products").
expensive_products(Product, Price) :- products(Product, Price), Price > ?threshold.
"""

parameters = {"threshold": 100}
execution_options = {
    "step_by_step": False,
    "materialize_intermediate": True,
    "debug_mode": False,
    "max_iterations": 1000
}

result = px.evaluate_vadalog(
    program=program, 
    parameters=parameters, 
    execution_options=execution_options
)
print(f"Execution completed in {result['execution_time']}s")
print(f"Results: {result['results']}")

Function Signature

def evaluate_vadalog(
    program, 
    parameters=None, 
    execution_options=None, 
    timeout=300
)

Parameters

ParameterTypeRequiredDescription
programstrYesVadalog program code
parametersdictNoProgram parameters
execution_optionsdictNoExecution configuration
timeoutintNoExecution timeout in seconds. Defaults to 300

Execution Options

OptionTypeDescription
step_by_stepboolEnable step-by-step execution
materialize_intermediateboolMaterialize intermediate results
debug_modeboolEnable debug output
max_iterationsintMaximum number of iterations

Returns

The evaluation results data.

Response​

{
  "data": {
    "execution_id": "exec_12345",
    "results": {
      "expensive_products": [
        ["Laptop", 1200],
        ["Smartphone", 800],
        ["Tablet", 600]
      ]
    },
    "execution_time": 0.45,
    "iterations": 3,
    "memory_usage": "12MB",
    "statistics": {
      "facts_derived": 150,
      "rules_fired": 25
    }
  },
  "message": "Program evaluated successfully",
  "status": "success"
}

Stop Evaluation​

Force stop a running Vadalog evaluation.

import prometheux_chain as px

# Stop a running Vadalog evaluation
result = px.stop_vadalog_evaluation()
print(result['message'])

Validate Program​

Validate a Vadalog program syntax without executing it.

import prometheux_chain as px

program = """
@input("products").
@output("expensive_products").
expensive_products(Product, Price) :- products(Product, Price), Price > 100.
"""

result = px.validate_vadalog(program=program, strict_mode=True)
if result['status'] == 'success':
    print("Program is valid!")
    print(f"Analysis: {result['analysis']}")
else:
    print(f"Validation errors: {result['errors']}")

Function Signature

def validate_vadalog(program, strict_mode=False)

Parameters

ParameterTypeRequiredDescription
programstrYesVadalog program code to validate
strict_modeboolNoEnable strict validation. Defaults to False

Get Execution Status​

Check the status of a running or completed evaluation.

import prometheux_chain as px

status = px.get_vadalog_status(execution_id="exec_12345")
print(f"Execution status: {status['status']}")
print(f"Progress: {status['progress']}%")
if status['status'] == 'completed':
    print(f"Results available: {len(status['results'])} facts")

Function Signature

def get_vadalog_status(execution_id)

Parameters

ParameterTypeRequiredDescription
execution_idstrYesThe execution ID to check

List Built-in Functions​

Get a list of available built-in functions for Vadalog programs.

import prometheux_chain as px

functions = px.list_vadalog_functions(category="math")
print("Available math functions:")
for func in functions['functions']:
    print(f"  - {func['name']}: {func['description']}")
    print(f"    Syntax: {func['syntax']}")
    print(f"    Example: {func['example']}")

Function Signature

def list_vadalog_functions(category="all")

Parameters

ParameterTypeRequiredDescription
categorystrNoFunction category: "all", "math", "string", "date", "aggregation". Defaults to "all"

Explain Program​

Get an explanation of how a Vadalog program works.

import prometheux_chain as px

program = """
@input("products").
@output("expensive_products").
expensive_products(Product, Price) :- products(Product, Price), Price > 100.
"""

explanation = px.explain_vadalog(
    program=program, 
    explanation_type="detailed"
)
print("Program Explanation:")
print(explanation['explanation'])
if explanation.get('examples'):
    print("\nExamples:")
    for example in explanation['examples']:
        print(f"  - {example}")

Function Signature

def explain_vadalog(
    program, 
    explanation_type="overview", 
    include_examples=True
)

Parameters

ParameterTypeRequiredDescription
programstrYesVadalog program to explain
explanation_typestrNoType: "overview", "detailed", "step_by_step". Defaults to "overview"
include_examplesboolNoInclude usage examples. Defaults to True

Complete Workflow Example​

import prometheux_chain as px
import os

# Set up authentication and configuration
os.environ['PMTX_TOKEN'] = 'my_pmtx_token'
px.config.set('JARVISPY_URL', "https://api.prometheux.ai/jarvispy/my-org/my-user")

# Define a Vadalog program
program = """
@input("products").
@output("expensive_products").
expensive_products(Product, Price) :- products(Product, Price), Price > ?threshold.
"""

# Validate the program first
validation = px.validate_vadalog(program=program, strict_mode=True)
if validation['status'] != 'success':
    print(f"Validation failed: {validation['errors']}")
    exit(1)

# Get an explanation of the program
explanation = px.explain_vadalog(program=program, explanation_type="overview")
print(f"Program explanation: {explanation['explanation']}")

# Execute the program
result = px.evaluate_vadalog(
    program=program,
    parameters={"threshold": 100},
    execution_options={
        "materialize_intermediate": True
    }
)

print(f"Execution completed in {result['execution_time']}s")
print(f"Results: {result['results']}")