AssetGraph - Backend

Prerequisites

• Python 3.9+
• An API key from Financial Modeling Prep

Setup

1. Clone the repository

2. Set up environment variables:

   • Copy the example environment file:

     cp .env.example .env

   • Edit the .env file and add your FMP API key:

     FMP_API_KEY=YOUR_ACTUAL_FMP_API_KEY
     

3. Install Python dependencies:

   pip install -r requirements.txt

Running the Server

From the project root directory (AssetGraph), run the FastAPI server using uvicorn:

uvicorn backend.main:app --reload --host 0.0.0.0 --port 8000

The --reload flag automatically restarts the server when code changes are detected. The API will be available at http://localhost:8000.

Testing the Endpoint

You can test the /api/execute-graph endpoint by sending a POST request with a GraphSpec JSON payload.

Example using curl:

curl -X POST http://localhost:8000/api/execute-graph \
-H "Content-Type: application/json" \
-d '{
  "nodes": [
    { "id": "load_profile", "type": "LoadTickerData", "params": { "ticker": "AAPL" } },
    { "id": "load_income", "type": "LoadIncomeStatement", "params": { "period": "annual", "limit": 3 } },
    { "id": "load_balance", "type": "LoadBalanceSheet", "params": { "period": "annual", "limit": 3 } },
    { "id": "load_cashflow", "type": "LoadCashFlow", "params": { "period": "annual", "limit": 3 } },
    { "id": "preprocess", "type": "PreprocessFinancials", "params": {} },
    { "id": "summarize", "type": "SummarizeIncomeStatement", "params": {} },
    { "id": "report", "type": "GenerateMarkdownReport", "params": {} }
  ],
  "edges": [
    { "from_": "load_profile", "to": "load_income" },
    { "from_": "load_income", "to": "load_balance" },
    { "from_": "load_balance", "to": "load_cashflow" },
   { "from_": "load_cashflow", "to": "preprocess" },
    { "from_": "preprocess", "to": "summarize" },
    { "from_": "summarize", "to": "report" }
  ]
}'