Config

The config module provides an interface for reading and writing configuration values. It includes functions to load, retrieve, and update configuration values for the Prometheux platform.

---

Configuration Functions

Get Configuration Value

Retrieves a value from the configuration using the specified key.

Python SDK

import prometheux_chain as px

token = px.config.get("PMTX_TOKEN")
print(token)

Function Signature

def get(key, default=None)

Parameters

Parameter	Type	Required	Description
key	str	Yes	The key for the configuration value to retrieve
default	any	No	A default value to return if the key is not found

Returns

The value associated with the specified key, or None if the key does not exist.

REST API

HTTP Request

GET /api/v1/users/load-config?scope=user

Parameters

Parameter	Type	Required	Description
scope	string	No	Configuration scope (default: "user")

cURL Example

curl -X GET "https://api.prometheux.ai/jarvispy/my-org/my-user/api/v1/users/load-config?scope=user" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN"

---

Set Configuration Value

Sets a configuration value for the specified key.

Python SDK

import prometheux_chain as px

px.config.set("PMTX_TOKEN", "new_token")

Function Signature

def set(key, value)

Parameters

Parameter	Type	Required	Description
key	str	Yes	The key for the configuration value to set
value	any	Yes	The value to associate with the key

REST API

HTTP Request

POST /api/v1/users/save-config

Parameters

Parameter	Type	Required	Description
config_data	object	Yes	Configuration data to save
scope	string	No	Configuration scope (default: "user")

cURL Example

curl -X POST "https://api.prometheux.ai/jarvispy/my-org/my-user/api/v1/users/save-config" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -d '{
    "config_data": {
      "theme": "dark",
      "language": "en",
      "notifications": true
    },
    "scope": "user"
  }'

---

Update Multiple Configuration Values

Update multiple configuration values at once from a dictionary.

Python SDK

import prometheux_chain as px

px.config.update_config({
    "PMTX_TOKEN": "updated_token",
    "LLM_API_KEY": "new_api_key"
})

Function Signature

def update_config(updates)

Parameters

Parameter	Type	Required	Description
updates	dict	Yes	A dictionary containing keys and values to update

REST API

Use the save-config endpoint with all values in the config_data object:

curl -X POST "https://api.prometheux.ai/jarvispy/my-org/my-user/api/v1/users/save-config" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN" \
  -d '{
    "config_data": {
      "PMTX_TOKEN": "updated_token",
      "LLM_API_KEY": "new_api_key"
    },
    "scope": "user"
  }'

---

Authentication Token

The PMTX_TOKEN can be configured in two ways:

Using Environment Variables

import os

os.environ['PMTX_TOKEN'] = 'pmtx_token'

Using the SDK Configuration

import prometheux_chain as px

px.config.set("PMTX_TOKEN", "pmtx_token")

---

Configuring LLMs

The Prometheux Chain exploits LLMs to generate more human-readable explanations, translations of Vadalog rules, graph rag and LLM output validation tasks. By default, no LLM is configured.

Setting up the LLM

To enable and configure an LLM, such as OpenAI's GPT, follow these steps:

1. Set the LLM Provider:

import prometheux_chain as px

px.config.set("LLM_PROVIDER", "OpenAI")

2. Provide the API Key:

px.config.set("LLM_API_KEY", "your_api_key")

---

Default Configurations

The SDK uses the following default configurations:

Key	Default Value	Description
PMTX_TOKEN	None	Prometheux authentication token
LLM_API_KEY	None	LLM API key
LLM_PROVIDER	OpenAI	LLM provider name
LLM_VERSION	gpt-4o	LLM model version
LLM_TEMPERATURE	0.50	LLM temperature setting
LLM_MAX_TOKENS	2000	Maximum tokens for LLM responses
EMBEDDING_MODEL_VERSION	text-embedding-3-large	Embedding model version
EMBEDDING_DIMENSIONS	2048	Embedding dimensions

---

User Management

Get User Role

Retrieve the current user's role.

Python SDK

import prometheux_chain as px

role = px.get_user_role()
print(f"User role: {role}")

REST API

HTTP Request

GET /api/v1/users/get-role

cURL Example

curl -X GET "https://api.prometheux.ai/jarvispy/my-org/my-user/api/v1/users/get-role" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN"

Response

{
  "data": {
    "role": "user"
  },
  "message": "Role retrieved successfully",
  "status": "success"
}

---

Get Usage Status

Get current API usage statistics and limits.

Python SDK

import prometheux_chain as px

usage = px.get_usage_status()
print(f"LLM usage: {usage['llm_usage']}")
print(f"Embedding usage: {usage['embedding_usage']}")

REST API

HTTP Request

GET /api/v1/users/usage-status

cURL Example

curl -X GET "https://api.prometheux.ai/jarvispy/my-org/my-user/api/v1/users/usage-status" \
  -H "Authorization: Bearer YOUR_JWT_TOKEN"

Response

{
  "data": {
    "llm_usage": {
      "current": 150,
      "limit": 1000,
      "remaining": 850
    },
    "embedding_usage": {
      "current": 50,
      "limit": 500,
      "remaining": 450
    }
  },
  "message": "Usage status retrieved successfully",
  "status": "success"
}

---

Complete Configuration Example

import prometheux_chain as px
import os

# Set up authentication via environment variable
os.environ['PMTX_TOKEN'] = 'my_pmtx_token'

# Or set via SDK
px.config.set("PMTX_TOKEN", "my_pmtx_token")

# Configure the backend URL
px.config.set('JARVISPY_URL', "https://api.prometheux.ai/jarvispy/my-org/my-user")

# Configure LLM settings
px.config.update_config({
    "LLM_PROVIDER": "OpenAI",
    "LLM_API_KEY": "your_openai_api_key",
    "LLM_VERSION": "gpt-4o",
    "LLM_TEMPERATURE": 0.7,
    "LLM_MAX_TOKENS": 4000
})

# Verify configuration
print(f"API URL: {px.config.get('JARVISPY_URL')}")
print(f"LLM Provider: {px.config.get('LLM_PROVIDER')}")