Merge branch 'main' of https://github.com/dograh-hq/dograh

examples/README.md

@@ -27,6 +27,10 @@ python python/fetch_workflow_and_call.py
 # Create a new workflow from a definition.
 python python/create_workflow.py
 
+# Build a 3-node agent with the Workflow SDK and save it as a draft.
+# Edit WORKFLOW_ID at the top of the file first.
+python python/build_workflow_with_sdk.py
+
 # Load an existing workflow, edit the startCall prompt, and save as a draft.
 # Edit WORKFLOW_ID at the top of the file first.
 python python/load_and_edit_workflow.py
@@ -45,5 +49,6 @@ export DOGRAH_API_TOKEN=sk-...
 
 npm run call    # fetch_workflow_and_call.ts
 npm run create  # create_workflow.ts
+npm run build   # build_workflow_with_sdk.ts  (edit WORKFLOW_ID in the file first)
 npm run edit    # load_and_edit_workflow.ts  (edit WORKFLOW_ID in the file first)
 ```

examples/python/build_workflow_with_sdk.py

@@ -0,0 +1,101 @@
+"""Build a multi-node voice agent using the Workflow SDK and save it as a draft.
+
+Requirements:
+    pip install -r requirements.txt
+
+Environment variables (loaded from `.env` in this directory):
+    DOGRAH_API_ENDPOINT  - Dograh API base URL (e.g. http://localhost:8000)
+    DOGRAH_API_TOKEN     - API token sent as X-API-Key
+
+Run:
+    python build_workflow_with_sdk.py
+"""
+
+from __future__ import annotations
+
+import os
+import sys
+from pathlib import Path
+
+from dotenv import load_dotenv
+
+from dograh_sdk import DograhClient, Workflow
+
+load_dotenv(Path(__file__).parent / ".env")
+
+# Replace with the numeric ID of an existing agent in your Dograh account.
+# Create one via the UI or with create_workflow.py if you don't have one yet.
+WORKFLOW_ID = 0
+
+
+def main() -> int:
+    api_endpoint = os.environ.get("DOGRAH_API_ENDPOINT", "http://localhost:8000")
+    api_token = os.environ.get("DOGRAH_API_TOKEN")
+
+    if not api_token:
+        print("DOGRAH_API_TOKEN is required", file=sys.stderr)
+        return 1
+
+    if WORKFLOW_ID == 0:
+        print("Set WORKFLOW_ID at the top of this file to an existing workflow ID", file=sys.stderr)
+        return 1
+
+    with DograhClient(base_url=api_endpoint, api_key=api_token) as client:
+        existing = client.get_workflow(WORKFLOW_ID)
+        # Preserve the live workflow name; save_workflow sends name with the draft update.
+        wf = Workflow(client=client, name=existing.name)
+
+        greeting = wf.add(
+            type="startCall",
+            name="greeting",
+            prompt=(
+                "# Goal\n"
+                "You are a helpful agent having a conversation over voice with a human. "
+                "This is a voice conversation, so transcripts can be error prone.\n\n"
+                "## Flow\n"
+                "Greet the caller warmly and ask whether they would like to continue."
+            ),
+        )
+        qualify = wf.add(
+            type="agentNode",
+            name="qualify",
+            prompt=(
+                "# Goal\n"
+                "Qualify the lead by asking about their needs, budget, and timeline.\n\n"
+                "## Rules\n"
+                "- Keep responses short — 2-3 sentences max\n"
+                "- Confirm all three answers before moving on"
+            ),
+        )
+        done = wf.add(
+            type="endCall",
+            name="done",
+            prompt="Thank the caller for their time and let them know the team will follow up shortly.",
+        )
+
+        wf.edge(
+            greeting,
+            qualify,
+            label="interested",
+            condition="Caller confirms they want to continue.",
+        )
+        wf.edge(
+            qualify,
+            done,
+            label="qualified",
+            condition="All qualification questions have been answered.",
+        )
+
+        result = client.save_workflow(workflow_id=WORKFLOW_ID, workflow=wf)
+        node_count = len(result.workflow_definition.get("nodes", []))
+        print(
+            f"Saved workflow {result.id}: {result.name!r} "
+            f"(version={result.version_number}, status={result.version_status}, "
+            f"nodes={node_count})"
+        )
+
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

examples/typescript/build_workflow_with_sdk.ts

@@ -0,0 +1,84 @@
+// Build a multi-node voice agent using the Workflow SDK and save it as a draft.
+//
+// Requirements:
+//   npm install @dograh/sdk
+//
+// Environment variables:
+//   DOGRAH_API_ENDPOINT  - Dograh API base URL (e.g. http://localhost:8000)
+//   DOGRAH_API_TOKEN     - API token sent as X-API-Key
+//
+// Run:
+//   npx tsx build_workflow_with_sdk.ts
+
+import { DograhClient, Workflow } from "@dograh/sdk";
+
+// Replace with the numeric ID of an existing agent in your Dograh account.
+// Create one via the UI or with create_workflow.ts if you don't have one yet.
+const WORKFLOW_ID = 0;
+
+async function main(): Promise<void> {
+    const apiEndpoint = process.env.DOGRAH_API_ENDPOINT ?? "http://localhost:8000";
+    const apiToken = process.env.DOGRAH_API_TOKEN;
+
+    if (!apiToken) throw new Error("DOGRAH_API_TOKEN is required");
+    if (WORKFLOW_ID === 0) throw new Error("Set WORKFLOW_ID at the top of this file to an existing workflow ID");
+
+    const client = new DograhClient({
+        baseUrl: apiEndpoint,
+        apiKey: apiToken,
+    });
+
+    const existing = await client.getWorkflow(WORKFLOW_ID);
+    // Preserve the live workflow name; saveWorkflow sends name with the draft update.
+    const wf = new Workflow({ client, name: existing.name });
+
+    const greeting = await wf.add({
+        type: "startCall",
+        name: "greeting",
+        prompt: [
+            "# Goal",
+            "You are a helpful agent having a conversation over voice with a human. This is a voice conversation, so transcripts can be error prone.",
+            "",
+            "## Flow",
+            "Greet the caller warmly and ask whether they would like to continue.",
+        ].join("\n"),
+    });
+    const qualify = await wf.add({
+        type: "agentNode",
+        name: "qualify",
+        prompt: [
+            "# Goal",
+            "Qualify the lead by asking about their needs, budget, and timeline.",
+            "",
+            "## Rules",
+            "- Keep responses short — 2-3 sentences max",
+            "- Confirm all three answers before moving on",
+        ].join("\n"),
+    });
+    const done = await wf.add({
+        type: "endCall",
+        name: "done",
+        prompt: "Thank the caller for their time and let them know the team will follow up shortly.",
+    });
+
+    wf.edge(greeting, qualify, {
+        label: "interested",
+        condition: "Caller confirms they want to continue.",
+    });
+    wf.edge(qualify, done, {
+        label: "qualified",
+        condition: "All qualification questions have been answered.",
+    });
+
+    const result = await client.saveWorkflow(WORKFLOW_ID, wf);
+    const nodeCount = ((result.workflow_definition?.nodes as unknown[]) ?? []).length;
+    console.log(
+        `Saved workflow ${result.id}: ${JSON.stringify(result.name)} ` +
+        `(version=${result.version_number}, status=${result.version_status}, nodes=${nodeCount})`,
+    );
+}
+
+main().catch((err) => {
+    console.error(err);
+    process.exit(1);
+});

examples/typescript/package.json

@@ -6,6 +6,7 @@
   "scripts": {
     "call": "tsx --env-file=.env fetch_workflow_and_call.ts",
     "create": "tsx --env-file=.env create_workflow.ts",
+    "build": "tsx --env-file=.env build_workflow_with_sdk.ts",
     "edit": "tsx --env-file=.env load_and_edit_workflow.ts"
   },
   "dependencies": {