Agent NoCode

Technology

Built with Python & LangGraph

A2A Protocol v0.3.0 Compliant Server

Built with Python and powered by LangGraph, this NoCode RAG agent enables seamless agent-to-agent communication using the standardized A2A protocol. Implemented with FastAPI and the official A2A SDK, it provides intelligent RAG capabilities, stateful multi-agent workflow orchestration, and comprehensive no-code tool integration for enterprise applications.

Uses LangGraph with a graph-based architecture for defining complex agent interactions and stateful workflows. Workflows are composed of nodes (representing processing steps) and edges (representing state transitions and message flow), enabling sophisticated multi-step reasoning, conditional logic, and human-in-the-loop patterns.

Python LangGraph A2A Protocol LangGraph Docs

API Endpoints & Documentation

Explore the A2A protocol endpoints, agent cards, and LangGraph RAG APIs.

API Documentation Health Status A2A Agent Card

Agent Orchestrator Dashboard

Live monitoring of all subsystems and services. Updates every 30 seconds.

Loading system status...

Quick Start: Chat with Agent

Use this curl command to send a message to the orchestrator agent via the A2A protocol. The agent will return a task ID that you can use to check the status and results.

Terminal Command

curl -X POST [Loading...]/invoke \
-H "Content-Type: application/json" \
-d '{"input": {"message": "Explain quantum computing in simple terms"}}'

Response:

{
  "task_id": "abc-123...",
  "task_url": "[Loading...]/tasks/abc-123...",
  "status": {"state": "running"}
}

Next Step: Click or curl the task_url to check status and get results.

Agent Configuration

Configure the NoCode RAG Langraph agent with LLM, RAG database, and authentication settings.

Required Environment Variables

Configure these parameters to enable full agent functionality:

Parameter	Required	Default	Description
Agent Configuration
`AGENT_ID`	Required	`""`	Unique identifier for this agent instance
`AGENT_NAME`	Optional	`NoCode RAG Langraph Agent`	Display name for the agent
`AGENT_DESCRIPTION`	Optional	`A LangGraph-based AI assistant`	Description of agent capabilities
LLM Configuration
`LLM_ENDPOINT`	Required	`""`	Azure OpenAI endpoint URL (e.g., https://your-resource.openai.azure.com/)
`LLM_KEY`	Required	`""`	Azure OpenAI API key for authentication
`LLM_DEPLOYMENT_NAME`	Optional	`gpt-4o`	Azure OpenAI deployment name
`LLM_VERSION`	Optional	`2024-02-01`	Azure OpenAI API version
`LLM_MODEL`	Optional	`gpt-4`	Azure OpenAI model name
Embedding Service Configuration
`EMBEDDING_BASE_URL`	Optional	`""`	Base URL for embedding service
`EMBEDDING_API_KEY`	Optional	`""`	API key for embedding service authentication
`EMBEDDING_PROVIDER`	Optional	`azure`	Embedding provider (azure, openai, etc.)
Database Configuration
`DB_HOST` or `PG_HOST`	Optional	`localhost`	PostgreSQL database host
`DB_PORT` or `PG_PORT`	Optional	`5432`	PostgreSQL database port
`DB_NAME`	Optional	`orchestrator`	PostgreSQL database name
`DB_USERNAME` or `PG_USER`	Optional	`postgres`	PostgreSQL database username
`DB_PASSWORD` or `PG_PASSWORD`	Optional	`""`	PostgreSQL database password
Server Configuration
`PORT`	Optional	`8080`	Server port (5015 for local development)
`HOST`	Optional	`0.0.0.0`	Server host address
`ENVIRONMENT`	Optional	`development`	Application environment (development, production)
`DEBUG`	Optional	`false`	Enable debug mode

Example Configuration

.env file

# Agent Configuration
AGENT_ID=my-agent-001
AGENT_NAME="NoCode RAG Langraph Agent"
AGENT_DESCRIPTION="A LangGraph-based RAG AI assistant"

# LLM Configuration
LLM_ENDPOINT=https://your-openai.openai.azure.com/
LLM_KEY=your-api-key-here
LLM_DEPLOYMENT_NAME=gpt-4o

Sync Parameters to Fabric Developer Workflow Application

Automatically sync your local environment variables to Fabric Developer Workflow Application using the make params command. This eliminates manual configuration in the Application Dashboard.

Prerequisites

Install Fabric Developer Journey CLI from Null Platform:
```
npm install -g @nullplatform/cli
```
Get your API Key:
Go to your App Dashboard from Fabric Workspace → Click user profile icon → Click "Copy personal access token"
Export the API Key:
```
export NP_TOKEN=<your-token>
```
Get your App NRN (Null Resource Name):
1. Go to your Application Dashboard
2. Click the NRN button to copy your application's NRN
3. You'll use this NRN when running the make params command
```
# Format: organization=ID:account=ID:namespace=ID:application=ID
# Example: organization=1234567890:account=9876543210:namespace=1122334455:application=5544332211
```

Run the Command

Once prerequisites are met, run this command in your terminal: