Supply Genie - Create Supply Chain

A comprehensive AI-powered supply chain management system that helps businesses discover, evaluate, and connect with reliable suppliers. Built with FastAPI, LangChain, and MongoDB.

🚀 Features

Intelligent Supplier Discovery: Uses AI agents to search and evaluate suppliers from multiple sources
MongoDB Integration: Stores and queries existing supplier data efficiently
Web Research: Leverages Tavily API for real-time supplier information gathering
Smart Filtering: Advanced search capabilities with location, price, certification filters
RESTful API: Clean, documented API endpoints for easy integration
CORS Support: Ready for frontend integration with cross-origin support

🛠️ Tech Stack

Backend: FastAPI with Python 3.12
AI/ML: LangChain, LangGraph, OpenAI GPT models
Database: MongoDB with text search indexing
Search: Tavily API for web research and data extraction
Logging: Loguru for structured logging
Deployment: Docker support with Cloud Run optimization

📋 Prerequisites

Python 3.12+
MongoDB database
OpenAI API key
Tavily API key (free credits available at https://tavily.com)

🔧 Installation

1. Clone the Repository

git clone <repository-url>
cd supply-genie-create-supply-chain

2. Set Up Environment

# Copy environment template
cp .env.example .env

# Edit .env with your API keys
nano .env

3. Install Dependencies

Option A: Using pip

pip install -r requirements.txt

Option B: Using uv (recommended)

uv sync

4. Configure Environment Variables

Edit .env file with your credentials:

# OpenAI API key for ChatOpenAI
OPENAI_API_KEY=sk-proj-your-openai-key-here

# Tavily API key (get free credits at https://tavily.com)
TAVILY_API_KEY=tvly-dev-your-tavily-key-here

# MongoDB connection URI
MONGO_URI=mongodb+srv://username:[email protected]/

# Override OpenAI model (optional)
MODEL_NAME=gpt-4o-mini

🚀 Running the Application

Development Mode

uvicorn src.main:app --reload --host 0.0.0.0 --port 8080

Production Mode

uvicorn src.main:app --host 0.0.0.0 --port 8080

Using Docker

# Build the image
docker build -t supply-genie .

# Run the container
docker run -p 8080:8080 --env-file .env supply-genie

The API will be available at http://localhost:8080

📖 API Documentation

Base URL

http://localhost:8080

Interactive Documentation

Swagger UI: http://localhost:8080/docs
ReDoc: http://localhost:8080/redoc

🛠️ API Endpoints

1. Health Check

GET /

Simple health check endpoint to verify the service is running.

Response

{
  "message": "Hello World"
}

Example

curl -X GET "http://localhost:8080/"

2. Get Supply Chain Recommendations

POST /api/v1/supply-chain/recommendations

The main endpoint for discovering suppliers based on your requirements. Uses AI agents to search existing databases and perform web research to find the best suppliers.

Request Body

{
  "query": "string (required, 1-2000 characters)",
  "chat_history": [
    {
      "role": "user|assistant",
      "content": "string"
    }
  ] // optional
}

Parameters

Parameter	Type	Required	Description
`query`	string	Yes	Detailed description of supplier requirements (1-2000 chars)
`chat_history`	array	No	Previous conversation context for follow-up queries

Response

{
  "suppliers": [
    {
      "company_name": "string",
      "location": "string",
      "rating": 0.0,
      "price_range": "string (in USD format: '$X-Y USD')",
      "lead_time": "string",
      "moq": "string",
      "certifications": ["string"],
      "specialties": ["string"],
      "response_time": "string (quantified: 'X-Y hours/days')",
      "contact": "string"
    }
  ]
}

Response Fields

Field	Type	Description	Example
`company_name`	string	Official company name	"ABC Manufacturing Ltd"
`location`	string	Company location/headquarters	"Shanghai, China"
`rating`	float	Company rating (0-5 scale)	4.5
`price_range`	string	Price range in USD	"$50-100 USD"
`lead_time`	string	Manufacturing/delivery lead time	"2-3 weeks"
`moq`	string	Minimum order quantity	"1000 units"
`certifications`	array	Quality/compliance certifications	["ISO 9001", "FDA"]
`specialties`	array	Company specializations	["Electronics", "Medical Devices"]
`response_time`	string	Response time for inquiries	"2-4 hours"
`contact`	string	Contact information	"[email protected]"

📝 Examples

Example 1: Basic Electronics Supplier Search

Request:

curl -X POST "http://localhost:8080/api/v1/supply-chain/recommendations" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "I need suppliers for electronic components, specifically microcontrollers and sensors. Looking for reliable manufacturers in Asia with competitive pricing, ISO certifications, and fast response times."
  }'

Response:

{
  "suppliers": [
    {
      "company_name": "TechFlow Electronics",
      "location": "Shenzhen, China",
      "rating": 4.7,
      "price_range": "$5-25 USD",
      "lead_time": "2-3 weeks",
      "moq": "1000 units",
      "certifications": ["ISO 9001", "RoHS", "CE"],
      "specialties": ["Microcontrollers", "Sensors", "IoT Components"],
      "response_time": "2-4 hours",
      "contact": "[email protected]"
    },
    {
      "company_name": "AsiaChip Manufacturing",
      "location": "Taipei, Taiwan",
      "rating": 4.5,
      "price_range": "$8-30 USD",
      "lead_time": "1-2 weeks",
      "moq": "500 units",
      "certifications": ["ISO 9001", "ISO 14001", "OHSAS 18001"],
      "specialties": ["Semiconductors", "Custom ICs", "Sensors"],
      "response_time": "1-2 days",
      "contact": "[email protected]"
    }
  ]
}

Example 2: Textile Supplier Search with Chat History

Request:

curl -X POST "http://localhost:8080/api/v1/supply-chain/recommendations" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Actually, I need organic cotton suppliers specifically for t-shirt manufacturing",
    "chat_history": [
      {
        "role": "user",
        "content": "I need textile suppliers for clothing manufacturing"
      },
      {
        "role": "assistant",
        "content": "I can help you find textile suppliers. What specific type of textiles and clothing items are you looking to manufacture?"
      }
    ]
  }'

Response:

{
  "suppliers": [
    {
      "company_name": "Green Cotton Co.",
      "location": "Gujarat, India",
      "rating": 4.8,
      "price_range": "$3-8 USD",
      "lead_time": "3-4 weeks",
      "moq": "5000 yards",
      "certifications": ["GOTS", "OCS", "OEKO-TEX"],
      "specialties": [
        "Organic Cotton",
        "Sustainable Textiles",
        "T-shirt Fabric"
      ],
      "response_time": "4-6 hours",
      "contact": "[email protected]"
    },
    {
      "company_name": "EcoTextile Solutions",
      "location": "Istanbul, Turkey",
      "rating": 4.6,
      "price_range": "$4-10 USD",
      "lead_time": "2-3 weeks",
      "moq": "3000 yards",
      "certifications": ["GOTS", "Cradle to Cradle", "BCI"],
      "specialties": [
        "Organic Fabrics",
        "Eco-friendly Dyeing",
        "Apparel Textiles"
      ],
      "response_time": "3-5 hours",
      "contact": "[email protected]"
    }
  ]
}

Example 3: Packaging Materials Search

Request:

curl -X POST "http://localhost:8080/api/v1/supply-chain/recommendations" \
  -H "Content-Type: application/json" \
  -d '{
    "query": "Looking for sustainable packaging suppliers for food products. Need biodegradable containers, boxes, and wrapping materials. Prefer suppliers in North America with FDA approval and competitive bulk pricing."
  }'

Response:

{
  "suppliers": [
    {
      "company_name": "EcoPackage America",
      "location": "Portland, Oregon, USA",
      "rating": 4.9,
      "price_range": "$15-45 USD",
      "lead_time": "1-2 weeks",
      "moq": "2000 units",
      "certifications": ["FDA", "USDA Organic", "BPI Certified"],
      "specialties": [
        "Biodegradable Containers",
        "Food-Safe Packaging",
        "Compostable Materials"
      ],
      "response_time": "1-2 hours",
      "contact": "[email protected]"
    },
    {
      "company_name": "Green Box Solutions",
      "location": "Toronto, Ontario, Canada",
      "rating": 4.4,
      "price_range": "$12-40 USD",
      "lead_time": "2-3 weeks",
      "moq": "1500 units",
      "certifications": ["Health Canada", "FSC", "SFI"],
      "specialties": [
        "Corrugated Boxes",
        "Sustainable Packaging",
        "Custom Food Containers"
      ],
      "response_time": "2-3 hours",
      "contact": "[email protected]"
    }
  ]
}

🔍 How It Works

The system uses an intelligent agent-based approach:

Requirements Analysis: AI analyzes your query to understand specific needs
Database Search: Queries existing supplier database using MongoDB text search
Web Research: Uses Tavily API to find new suppliers from web sources
Data Extraction: Extracts detailed supplier information from company websites
Evaluation: AI evaluates and ranks suppliers based on your criteria
Response: Returns top suppliers with complete, verified information

🗄️ Database Schema

Suppliers Collection

{
  "_id": ObjectId,
  "company_name": String,
  "location": String,
  "rating": Number,
  "price_range": String,
  "lead_time": String,
  "moq": String,
  "certifications": [String],
  "specialties": [String],
  "response_time": String,
  "contact": String,
  "created_at": Date,
  "updated_at": Date
}

🔒 Error Handling

Common Error Responses

{
  "detail": "Error message description"
}

HTTP Status Codes

200: Success
400: Bad Request (invalid input)
422: Validation Error
500: Internal Server Error

Example Error Response

{
  "detail": [
    {
      "loc": ["body", "query"],
      "msg": "field required",
      "type": "value_error.missing"
    }
  ]
}

🧪 Testing

# Run tests
pytest

# Run with coverage
pytest --cov=src

# Run specific test
pytest tests/test_main.py::test_health_check

🐳 Docker Deployment

Build and Run

# Build
docker build -t supply-genie .

# Run
docker run -p 8080:8080 --env-file .env supply-genie

Docker Compose (Optional)

version: "3.8"
services:
  supply-genie:
    build: .
    ports:
      - "8080:8080"
    environment:
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - TAVILY_API_KEY=${TAVILY_API_KEY}
      - MONGO_URI=${MONGO_URI}
      - MODEL_NAME=${MODEL_NAME}

🌐 Cloud Deployment

Google Cloud Run

# Build and push to Google Container Registry
gcloud builds submit --tag gcr.io/PROJECT_ID/supply-genie

# Deploy to Cloud Run
gcloud run deploy supply-genie \
  --image gcr.io/PROJECT_ID/supply-genie \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated \
  --port 8080

📊 Monitoring and Logging

The application uses structured logging with Loguru. Logs include:

Request/response tracking
Agent execution steps
Database operations
Error handling

Log Levels

INFO: General operation info
DEBUG: Detailed debugging info
WARNING: Non-critical issues
ERROR: Error conditions

🔧 Configuration

Environment Variables

Variable	Required	Default	Description
`OPENAI_API_KEY`	Yes	-	OpenAI API key for LLM
`TAVILY_API_KEY`	Yes	-	Tavily API key for web search
`MONGO_URI`	Yes	-	MongoDB connection string
`MODEL_NAME`	No	`gpt-4o-mini`	OpenAI model to use

Advanced Configuration

Edit src/config.py for advanced settings:

# Agent configuration
AGENT_MAX_SUPPLIERS = 10
AGENT_RECURSION_LIMIT = 50
DEFAULT_REMAINING_STEPS = 10

# Query limits
MAX_QUERY_LENGTH = 2000
MAX_EXTRACT_URLS = 10

# LLM settings
LLM_TEMPERATURE = 0.0

🤝 Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

🆘 Support

For support, please:

Check the API documentation
Review the logs for error details
Ensure all environment variables are set correctly
Verify MongoDB connection and API keys

📈 Roadmap

Add supplier comparison features
Implement caching for improved performance
Add supplier verification workflows
Create supplier rating system
Add export functionality (CSV, PDF)
Implement real-time notifications
Add multi-language support

Built with ❤️ using FastAPI, LangChain, and MongoDB

Name		Name	Last commit message	Last commit date
Latest commit History 19 Commits
.claude		.claude
archive		archive
notebooks		notebooks
src		src
.env.example		.env.example
.gitignore		.gitignore
.python-version		.python-version
Dockerfile		Dockerfile
README.md		README.md
pyproject.toml		pyproject.toml
requirements.txt		requirements.txt
uv.lock		uv.lock

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Supply Genie - Create Supply Chain

🚀 Features

🛠️ Tech Stack

📋 Prerequisites

🔧 Installation

1. Clone the Repository

2. Set Up Environment

3. Install Dependencies

4. Configure Environment Variables

🚀 Running the Application

Development Mode

Production Mode

Using Docker

📖 API Documentation

Base URL

Interactive Documentation

🛠️ API Endpoints

1. Health Check

Response

Example

2. Get Supply Chain Recommendations

Request Body

Parameters

Response

Response Fields

📝 Examples

Example 1: Basic Electronics Supplier Search

Example 2: Textile Supplier Search with Chat History

Example 3: Packaging Materials Search

🔍 How It Works

🗄️ Database Schema

Suppliers Collection

🔒 Error Handling

Common Error Responses

HTTP Status Codes

Example Error Response

🧪 Testing

🐳 Docker Deployment

Build and Run

Docker Compose (Optional)

🌐 Cloud Deployment

Google Cloud Run

📊 Monitoring and Logging

Log Levels

🔧 Configuration

Environment Variables

Advanced Configuration

🤝 Contributing

📄 License

🆘 Support

📈 Roadmap

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