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app.py

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+# app.py
+from daggr import GradioNode, InferenceNode, FnNode, Graph
+import gradio as gr
+from typing import Dict, Any
+import requests
+import os
+
+# Environment variables for API keys
+API_KEYS = {
+    "OPENAI": os.getenv("OPENAI_API_KEY"),
+    "HUGGINGFACE": os.getenv("HF_API_KEY")
+}
+
+# ========== Input Processing Node ==========
+def preprocess_inputs(user_input: str, metadata: Dict[str, Any]) -> Dict[str, Any]:
+    """Clean and validate inputs with metadata enrichment"""
+    return {
+        "cleaned_input": user_input.strip(),
+        "timestamp": metadata.get("timestamp"),
+        "source": metadata.get("source", "web")
+    }
+
+input_processor = FnNode(
+    fn=preprocess_inputs,
+    inputs={
+        "user_input": gr.Textbox(label="User Input"),
+        "metadata": gr.JSON(label="Metadata")
+    },
+    outputs={
+        "processed_data": gr.JSON(label="Processed Input")
+    }
+)
+
+# ========== LLM Processing Node ==========
+llm_processor = InferenceNode(
+    model="meta-llama/Llama-3-70B-Instruct",
+    inputs={
+        "prompt": gr.Textbox(label="LLM Prompt"),
+        "temperature": gr.Slider(0, 1, value=0.7)
+    },
+    outputs={
+        "response": gr.Textbox(label="LLM Response")
+    },
+    api_key=API_KEYS["HUGGINGFACE"]
+)
+
+# ========== Image Generation Node ==========
+image_generator = GradioNode(
+    space_or_url="stabilityai/stable-diffusion-xl-base-1.0",
+    api_name="/generate",
+    inputs={
+        "prompt": gr.Textbox(label="Image Prompt"),
+        "negative_prompt": gr.Textbox(label="Negative Prompt"),
+        "steps": gr.Slider(10, 50, value=30)
+    },
+    outputs={
+        "image": gr.Image(label="Generated Image")
+    }
+)
+
+# ========== API Integration Node ==========
+def call_external_api(data: Dict[str, Any]) -> Dict[str, Any]:
+    """Generic API caller with error handling"""
+    try:
+        response = requests.post(
+            "https://api.example.com/v1/process",
+            json=data,
+            headers={"Authorization": f"Bearer {API_KEYS.get('OPENAI')}"},
+            timeout=30
+        )
+        response.raise_for_status()
+        return response.json()
+    except Exception as e:
+        return {"error": str(e)}
+
+api_integrator = FnNode(
+    fn=call_external_api,
+    inputs={
+        "api_data": gr.JSON(label="API Payload")
+    },
+    outputs={
+        "api_response": gr.JSON(label="API Results")
+    }
+)
+
+# ========== Output Formatter Node ==========
+def format_output(llm_response: str, image: Any, api_data: Dict) -> Dict[str, Any]:
+    """Create unified output format"""
+    return {
+        "text_response": llm_response,
+        "visual_response": image,
+        "api_data": api_data,
+        "status": "success"
+    }
+
+output_formatter = FnNode(
+    fn=format_output,
+    inputs={
+        "llm_response": gr.Textbox(),
+        "image": gr.Image(),
+        "api_data": gr.JSON()
+    },
+    outputs={
+        "final_output": gr.JSON(label="Final Output")
+    }
+)
+
+# ========== Create and Connect Workflow ==========
+workflow = Graph(
+    name="Global Integration Platform",
+    nodes=[
+        input_processor,
+        llm_processor,
+        image_generator,
+        api_integrator,
+        output_formatter
+    ],
+    connections=[
+        (input_processor.outputs["processed_data"], llm_processor.inputs["prompt"]),
+        (input_processor.outputs["processed_data"], image_generator.inputs["prompt"]),
+        (input_processor.outputs["processed_data"], api_integrator.inputs["api_data"]),
+        (llm_processor.outputs["response"], output_formatter.inputs["llm_response"]),
+        (image_generator.outputs["image"], output_formatter.inputs["image"]),
+        (api_integrator.outputs["api_response"], output_formatter.inputs["api_data"])
+    ]
+)
+
+# ========== Launch Application ==========
+if __name__ == "__main__":
+    workflow.launch(
+        server_name="0.0.0.0",
+        server_port=7860,
+        share=True,
+        auth=("admin", os.getenv("APP_PASSWORD")),
+        favicon_path="https://example.com/favicon.ico"
+    )

requirements.txt

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+daggr>=0.5.4
+gradio>=6.0.2
+requests