Invoke inference API manually

.gitignores

@@ -0,0 +1 @@
+secrets*

app.py

@@ -1,11 +1,63 @@
+import os
+import json
+
+import requests
 import gradio as gr
+from gradio import inputs, outputs
+
+ENDPOINT = (
+    "https://api-inference.huggingface.co/models/ceshine/t5-paraphrase-quora-paws"
+)
+
 
-interface = gr.Interface.load(
-    "huggingface/ceshine/t5-paraphrase-quora-paws",
-    description="Paraphrasing model trained on PAWS and Quora datasets",
+def paraphrase(source_text):
+    res = requests.post(
+        ENDPOINT,
+        headers={"Authorization": f"Bearer {os.environ['TOKEN']}"},
+        data=json.dumps(
+            {
+                "inputs": source_text,
+                "parameters": {
+                    # "do_sample": True,
+                    "num_beams": 10,
+                    "top_k": 5,
+                    "repetition_penalty": 2.0,
+                    "temperature": 1.5,
+                    "num_return_sequences": 10,
+                    "max_length": 200,
+                },
+            }
+        ),
+    )
+    if not (res.status_code == 200):
+        raise ValueError(
+            "Could not complete request to HuggingFace API, Error {}".format(
+                res.status_code
+            )
+        )
+    results = res.json()
+    print(results)
+    outputs = [
+        x["generated_text"]
+        for x in results
+        if x["generated_text"].lower() != source_text.lower().strip()
+    ][:3]
+    text = ""
+    for i, output in enumerate(outputs):
+        text += f"{i+1}:  {output}\n\n"
+    return text
+
+
+interface = gr.Interface(
+    fn=paraphrase,
+    inputs=inputs.Textbox(label="Input"),
+    outputs=outputs.Textbox(label="Generated text:"),
+    title="T5 Sentence Paraphraser",
+    description="A paraphrasing model trained on PAWS and Quora datasets",
     examples=[
         ["I bought a ticket from London to New York."],
-        ["Weh Seun spends 14 hours a week doing housework."]
-    ]
+        ["Weh Seun spends 14 hours a week doing housework."],
+    ],
 )
-interface.launch()
+
+interface.launch(enable_queue=True)