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app.py

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+"""
+나의 첫번째 챗봇 AI
+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": "name_input",
+      "type": "textInput",
+      "position": {
+        "x": 100,
+        "y": 100
+      },
+      "data": {
+        "label": "Your Name",
+        "template": {
+          "input_value": {
+            "value": "John"
+          }
+        }
+      }
+    },
+    {
+      "id": "topic_input",
+      "type": "textInput",
+      "position": {
+        "x": 100,
+        "y": 250
+      },
+      "data": {
+        "label": "Topic",
+        "template": {
+          "input_value": {
+            "value": "Python programming"
+          }
+        }
+      }
+    },
+    {
+      "id": "level_input",
+      "type": "textInput",
+      "position": {
+        "x": 100,
+        "y": 400
+      },
+      "data": {
+        "label": "Skill Level",
+        "template": {
+          "input_value": {
+            "value": "beginner"
+          }
+        }
+      }
+    },
+    {
+      "id": "combiner",
+      "type": "textNode",
+      "position": {
+        "x": 350,
+        "y": 250
+      },
+      "data": {
+        "label": "Combine Inputs",
+        "template": {
+          "text": {
+            "value": "Create a personalized learning plan"
+          }
+        }
+      }
+    },
+    {
+      "id": "llm_1",
+      "type": "llmNode",
+      "position": {
+        "x": 600,
+        "y": 250
+      },
+      "data": {
+        "label": "Generate Learning Plan",
+        "template": {
+          "provider": {
+            "value": "VIDraft"
+          },
+          "model": {
+            "value": "Gemma-3-r1984-27B"
+          },
+          "temperature": {
+            "value": 0.7
+          },
+          "system_prompt": {
+            "value": "You are an expert educational consultant. Create personalized learning plans based on the user's name, topic of interest, and skill level."
+          }
+        }
+      }
+    },
+    {
+      "id": "output_1",
+      "type": "ChatOutput",
+      "position": {
+        "x": 900,
+        "y": 250
+      },
+      "data": {
+        "label": "Your Learning Plan"
+      }
+    }
+  ],
+  "edges": [
+    {
+      "id": "e1",
+      "source": "name_input",
+      "target": "combiner"
+    },
+    {
+      "id": "e2",
+      "source": "topic_input",
+      "target": "combiner"
+    },
+    {
+      "id": "e3",
+      "source": "level_input",
+      "target": "combiner"
+    },
+    {
+      "id": "e4",
+      "source": "combiner",
+      "target": "llm_1"
+    },
+    {
+      "id": "e5",
+      "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 - VIDraft as default
+            provider = template.get("provider", {}).get("value", "VIDraft")
+            if provider not in ["VIDraft", "OpenAI"]:
+                provider = "VIDraft"  # Default to VIDraft
+            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:
+                # Show which API key is missing
+                if provider == "OpenAI":
+                    results[node_id] = "[OpenAI API key not found. Please set OPENAI_API_KEY in Space secrets]"
+                elif provider == "VIDraft":
+                    results[node_id] = "[VIDraft API key not found. Please set FRIENDLI_TOKEN in Space secrets]"
+                else:
+                    results[node_id] = f"[No API key found for {provider}. Using 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="나의 첫번째 챗봇 AI", theme=gr.themes.Soft()) as demo:
+    gr.Markdown("# 나의 첫번째 챗봇 AI")
+    gr.Markdown("A workflow application created with MOUSE Workflow builder.")
+    
+    # API Status Check
+    vidraft_token = os.getenv("FRIENDLI_TOKEN")
+    openai_key = os.getenv("OPENAI_API_KEY")
+    
+    with gr.Accordion("🔑 API Status", open=False):
+        if vidraft_token:
+            gr.Markdown("✅ **VIDraft API**: Connected (Gemma-3-r1984-27B)")
+        else:
+            gr.Markdown("❌ **VIDraft API**: Not configured")
+            
+        if openai_key:
+            gr.Markdown("✅ **OpenAI API**: Connected (gpt-4.1-mini)")
+        else:
+            gr.Markdown("⚠️ **OpenAI API**: Not configured (optional)")
+        
+        if not vidraft_token:
+            gr.Markdown("""
+            **⚠️ Important**: Please add FRIENDLI_TOKEN to Space secrets for the app to work properly.
+            
+            Go to: Space settings → Repository secrets → Add secret
+            """)
+        elif not openai_key:
+            gr.Markdown("""
+            **💡 Tip**: The app will work with VIDraft alone. Add OPENAI_API_KEY if you need OpenAI features.
+            """)
+        else:
+            gr.Markdown("**✨ All APIs configured! Your app is fully functional.**")
+    
+    # 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()