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"""
My Workflow App
A workflow application created with MOUSE Workflow builder.
Generated by MOUSE Workflow
"""
import os
import json
import gradio as gr
import requests
# Workflow configuration
WORKFLOW_DATA = {
"nodes": [
{
"id": "input_1",
"type": "ChatInput",
"position": {
"x": 100,
"y": 200
},
"data": {
"label": "User Question",
"template": {
"input_value": {
"value": "What is the capital of Korea?"
}
}
}
},
{
"id": "llm_1",
"type": "llmNode",
"position": {
"x": 400,
"y": 200
},
"data": {
"label": "AI Processing",
"template": {
"provider": {
"value": "OpenAI"
},
"model": {
"value": "gpt-4.1-mini"
},
"temperature": {
"value": 0.7
},
"system_prompt": {
"value": "You are a helpful assistant."
}
}
}
},
{
"id": "output_1",
"type": "ChatOutput",
"position": {
"x": 700,
"y": 200
},
"data": {
"label": "Answer"
}
}
],
"edges": [
{
"id": "e1",
"source": "input_1",
"target": "llm_1"
},
{
"id": "e2",
"source": "llm_1",
"target": "output_1"
}
]
}
def execute_workflow(*input_values):
"""Execute the workflow with given inputs"""
# API keys from environment
vidraft_token = os.getenv("FRIENDLI_TOKEN")
openai_key = os.getenv("OPENAI_API_KEY")
nodes = WORKFLOW_DATA.get("nodes", [])
edges = WORKFLOW_DATA.get("edges", [])
results = {}
# Get input nodes
input_nodes = [n for n in nodes if n.get("type") in ["ChatInput", "textInput", "Input", "numberInput"]]
# Map inputs to node IDs
for i, node in enumerate(input_nodes):
if i < len(input_values):
results[node["id"]] = input_values[i]
# Process nodes
for node in nodes:
node_id = node.get("id")
node_type = node.get("type", "")
node_data = node.get("data", {})
template = node_data.get("template", {})
if node_type == "textNode":
# Combine connected inputs
base_text = template.get("text", {}).get("value", "")
connected_inputs = []
for edge in edges:
if edge.get("target") == node_id:
source_id = edge.get("source")
if source_id in results:
connected_inputs.append(f"{source_id}: {results[source_id]}")
if connected_inputs:
results[node_id] = f"{base_text}\n\nInputs:\n" + "\n".join(connected_inputs)
else:
results[node_id] = base_text
elif node_type in ["llmNode", "OpenAIModel", "ChatModel"]:
# Get provider and model
provider = template.get("provider", {}).get("value", "OpenAI")
temperature = template.get("temperature", {}).get("value", 0.7)
system_prompt = template.get("system_prompt", {}).get("value", "")
# Get input text
input_text = ""
for edge in edges:
if edge.get("target") == node_id:
source_id = edge.get("source")
if source_id in results:
input_text = results[source_id]
break
# Call API
if provider == "OpenAI" and openai_key:
try:
from openai import OpenAI
client = OpenAI(api_key=openai_key)
messages = []
if system_prompt:
messages.append({"role": "system", "content": system_prompt})
messages.append({"role": "user", "content": input_text})
response = client.chat.completions.create(
model="gpt-4.1-mini",
messages=messages,
temperature=temperature,
max_tokens=1000
)
results[node_id] = response.choices[0].message.content
except Exception as e:
results[node_id] = f"[OpenAI Error: {str(e)}]"
elif provider == "VIDraft" and vidraft_token:
try:
headers = {
"Authorization": f"Bearer {vidraft_token}",
"Content-Type": "application/json"
}
messages = []
if system_prompt:
messages.append({"role": "system", "content": system_prompt})
messages.append({"role": "user", "content": input_text})
payload = {
"model": "dep89a2fld32mcm",
"messages": messages,
"max_tokens": 16384,
"temperature": temperature,
"top_p": 0.8,
"stream": False
}
response = requests.post(
"https://api.friendli.ai/dedicated/v1/chat/completions",
headers=headers,
json=payload,
timeout=30
)
if response.status_code == 200:
results[node_id] = response.json()["choices"][0]["message"]["content"]
else:
results[node_id] = f"[VIDraft Error: {response.status_code}]"
except Exception as e:
results[node_id] = f"[VIDraft Error: {str(e)}]"
else:
results[node_id] = f"[Simulated Response: {input_text[:50]}...]"
elif node_type in ["ChatOutput", "textOutput", "Output"]:
# Get connected result
for edge in edges:
if edge.get("target") == node_id:
source_id = edge.get("source")
if source_id in results:
results[node_id] = results[source_id]
break
# Return outputs
output_nodes = [n for n in nodes if n.get("type") in ["ChatOutput", "textOutput", "Output"]]
return [results.get(n["id"], "") for n in output_nodes]
# Build UI
with gr.Blocks(title="My Workflow App", theme=gr.themes.Soft()) as demo:
gr.Markdown("# My Workflow App")
gr.Markdown("A workflow application created with MOUSE Workflow builder.")
# Extract nodes
nodes = WORKFLOW_DATA.get("nodes", [])
input_nodes = [n for n in nodes if n.get("type") in ["ChatInput", "textInput", "Input", "numberInput"]]
output_nodes = [n for n in nodes if n.get("type") in ["ChatOutput", "textOutput", "Output"]]
# Create inputs
inputs = []
if input_nodes:
gr.Markdown("### 📥 Inputs")
for node in input_nodes:
label = node.get("data", {}).get("label", node.get("id"))
template = node.get("data", {}).get("template", {})
default_value = template.get("input_value", {}).get("value", "")
if node.get("type") == "numberInput":
inp = gr.Number(label=label, value=float(default_value) if default_value else 0)
else:
inp = gr.Textbox(label=label, value=default_value, lines=2)
inputs.append(inp)
# Execute button
btn = gr.Button("🚀 Execute Workflow", variant="primary")
# Create outputs
outputs = []
if output_nodes:
gr.Markdown("### 📤 Outputs")
for node in output_nodes:
label = node.get("data", {}).get("label", node.get("id"))
out = gr.Textbox(label=label, interactive=False, lines=3)
outputs.append(out)
# Connect
btn.click(fn=execute_workflow, inputs=inputs, outputs=outputs)
gr.Markdown("---")
gr.Markdown("*Powered by MOUSE Workflow*")
if __name__ == "__main__":
demo.launch()
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