Create app.py

app.py

@@ -0,0 +1,71 @@
+import gradio as gr
+import requests
+import os
+
+# Configuration
+LANGFLOW_API_URL = os.environ.get("LANGFLOW_API_URL", "https://rossiter78-langflowpoc.hf.space/api/v1/run/d53e1b2f-3572-40c8-84ab-725106ee858f")
+#LANGFLOW_API_URL = "https://rossiter78-langflowpoc.hf.space/api/v1/run/d53e1b2f-3572-40c8-84ab-725106ee858f"
+LANGFLOW_API_KEY = os.environ.get("LANGFLOW_API_KEY", "")  # If needed
+HF_API_KEY = os.environ.get("HF_API_KEY", "") 
+
+def call_langflow(message, history):
+    """
+    Call Langflow API and return the response
+    """
+    headers = {
+        "Content-Type": "application/json",
+    }
+    
+    # Add API key if needed
+    if LANGFLOW_API_KEY:
+       headers["Authorization"] = f"Bearer {LANGFLOW_API_KEY}"
+    if HF_API_KEY: 
+        headers["x-api-key"] = f"{HF_API_KEY}"
+       
+    
+    # Adjust this payload based on your Langflow API structure
+    payload = {
+        "input_value": message,
+        "output_type": "chat",
+        "input_type": "chat",
+        "tweaks": {}
+    }
+    
+    try:
+        response = requests.post(
+            LANGFLOW_API_URL,
+            json=payload,
+            headers=headers,
+            timeout=30
+        )
+        response.raise_for_status()
+        
+        # Parse response - adjust based on your API response structure
+        data = response.json()
+        
+        # Common Langflow response structures:
+        # Option 1: data["outputs"][0]["outputs"][0]["results"]["message"]["text"]
+        # Option 2: data["result"]["message"]
+        # Adjust the following line based on your actual response:
+        
+        bot_message = data["outputs"][0]["outputs"][0]["results"]["message"]["text"]
+        return bot_message
+        
+    except requests.exceptions.RequestException as e:
+        return f"Error connecting to Langflow: {str(e)}"
+    except (KeyError, IndexError) as e:
+        return f"Error parsing response: {str(e)}\nResponse: {data}"
+
+# Create Gradio Chat Interface
+demo = gr.ChatInterface(
+    fn=call_langflow,
+    title="My Langflow Chatbot",
+    description="Chat with my AI assistant powered by Langflow",
+    examples=["Hello!", "What can you help me with?"],
+    theme=gr.themes.Soft(),
+    retry_btn=None,
+    undo_btn=None,
+)
+
+if __name__ == "__main__":
+    demo.launch()