Added main app

app.py

@@ -0,0 +1,53 @@
+import gradio as gr
+import requests
+import json
+
+def txt2img1(text):
+    url = "https://stablediffusionapi.com/api/v3/text2img"
+
+    payload = json.dumps({
+      "key": "qXpCKAkXLdKWb2sqcMlMzB0Q3gqHEggJIXxspJzHIVHUy6H9S060RN0BNGqj",
+      "prompt": text,
+      "negative_prompt": None,
+      "width": "512",
+      "height": "512",
+      "samples": "1",
+      "num_inference_steps": "20",
+      "seed": None,
+      "guidance_scale": 7.5,
+      "safety_checker": "yes",
+      "multi_lingual": "no",
+      "panorama": "no",
+      "self_attention": "no",
+      "upscale": "no",
+      "embeddings_model": "embeddings_model_id",
+      "webhook": None,
+      "track_id": None
+    })
+
+    headers = {
+      'Content-Type': 'application/json'
+    }
+
+    response = requests.request("POST", url, headers=headers, data=payload)
+    response_dict = response.json()
+    
+    return response_dict['output'][0]
+
+def txt2txt(text):
+    API_TOKEN = "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"
+    API_URL = "https://api-inference.huggingface.co/models/gpt2"
+    headers = {"Authorization": f"Bearer {API_TOKEN}"}
+
+    def query(payload):
+        response = requests.post(API_URL, headers=headers, json=payload)
+        return response.json()
+
+    output = query({"inputs": text})
+    return output[0]['generated_text']
+
+iface = gr.Interface(fn=txt2img1, inputs="text", outputs="image", title="Text to Image")
+iface.launch()
+
+iface2 = gr.Interface(fn=txt2txt, inputs="text", outputs="text", title="Text to Text")
+iface2.launch()