Add How-To guide: Scaffold a QType Project

docs/How To/Command Line Usage/scaffold_a_qtype_project.md

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+# Scaffold a QType Project
+
+Get a new QType project up and running in minutes by creating the required directory structure, configuring credentials, and authoring a minimal starter YAML.
+
+---
+
+### Step 1: Install QType
+
+```bash
+pip install qtype
+```
+
+---
+
+### Step 2: Create the Project Directory
+
+```bash
+mkdir my-qtype-app && cd my-qtype-app
+```
+
+A typical project layout looks like this:
+
+```
+my-qtype-app/
+├── .env                        # API credentials (never commit this)
+└── app.qtype.yaml              # Your application spec
+```
+
+---
+
+### Step 3: Set Up Credentials
+
+Create a `.env` file in the project root with your AWS credentials:
+
+```bash
+# .env
+AWS_ACCESS_KEY_ID=your_access_key
+AWS_SECRET_ACCESS_KEY=your_secret_key
+AWS_REGION=us-east-1
+```
+
+QType automatically loads `.env` at startup. Add `.env` to your `.gitignore` to avoid accidentally committing secrets.
+
+---
+
+### Step 4: Create the Starter YAML
+
+Create `app.qtype.yaml` with this minimal template:
+
+```yaml
+id: my_app
+description: My first QType application
+
+models:
+  - type: Model
+    id: claude
+    provider: aws-bedrock
+    model_id: anthropic.claude-sonnet-4-20250514-v1:0
+
+flows:
+  - type: Flow
+    id: chat
+    variables:
+      - id: question
+        type: text
+      - id: prompt
+        type: text
+      - id: answer
+        type: text
+    inputs:
+      - question
+    outputs:
+      - answer
+    steps:
+      - id: build_prompt
+        type: PromptTemplate
+        template: "Answer the following question:\n{question}\n"
+        inputs:
+          - question
+        outputs:
+          - prompt
+
+      - id: generate
+        type: LLMInference
+        model: claude
+        inputs:
+          - prompt
+        outputs:
+          - answer
+```
+
+---
+
+### Step 5: Validate the Spec
+
+```bash
+qtype validate app.qtype.yaml
+```
+
+Fix any reported errors before proceeding.
+
+---
+
+### Step 6: Run or Serve the Application
+
+Run a single flow from the command line:
+
+```bash
+qtype run -i '{"question": "What is QType?"}' app.qtype.yaml
+```
+
+Or serve the application as an HTTP API:
+
+```bash
+qtype serve app.qtype.yaml
+```
+
+---
+
+### Explanation
+
+- **`id`**: Unique identifier for the application; used in logging and the serve endpoint
+- **`models`**: List of language model definitions; each model is referenced by its `id` in steps
+- **`provider: aws-bedrock`**: Routes inference calls through AWS Bedrock using ambient AWS credentials
+- **`PromptTemplate`**: Step that renders a string template using named inputs, producing a formatted prompt
+- **`LLMInference`**: Step that sends a prompt to a language model and captures the response
+- **`qtype validate`**: Parses and type-checks the YAML spec without executing any flows
+- **`qtype serve`**: Starts an HTTP server exposing each flow as a REST endpoint
+
+## See Also
+
+- [Validate a QType Spec](../Observability%20%26%20Debugging/validate_qtype_yaml.md)
+- [Serve Flows as APIs](../Qtype%20Server/serve_flows_as_apis.md)
+- [Tutorial: First QType Application](../../Tutorials/01-first-qtype-application.md)