feat(examples): add multi-node Workflow SDK example in Python and TypeScript (#440)

* feat(examples): add multi-node Workflow SDK example in Python and TypeScript Closes #369 * docs: preserve workflow name in SDK build examples --------- Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
2026-06-19 08:28:10 +02:00 · 2026-06-18 02:43:10 -07:00 · 2026-06-18 02:43:10 -07:00 · 2a92406f02
commit 2a92406f02
parent bec8a23dfb
4 changed files with 191 additions and 0 deletions
--- a/examples/python/build_workflow_with_sdk.py
+++ b/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())