This should work now

I am now actually calling BLOOM.

app.py

@@ -1,7 +1,45 @@
 import gradio as gr
+import requests
+import os
 
-def greet(name):
-    return "Hello " + name + "!!"
+API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom"
+HF_TOKEN = os.environ["HF_TOKEN"]
+headers = {"Authorization": f"Bearer {HF_TOKEN}"}
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+def get_results(prompt):
+    json_ = {"inputs": p,
+            "parameters":
+            {
+            "top_p": 0.9,
+            "typical_p":0.2
+          "temperature": 1.1,
+          "max_new_tokens": 250,
+          "return_full_text": True
+          }, "options": 
+              {
+              "use_cache": True,
+              "wait_for_model":True
+              },}
+    try:
+        response = requests.post(API_URL, headers=headers, json=json_)
+        output = response.json()
+        output_tmp = output[0]['generated_text']
+    except:
+        output_tmp = "Not able to work"
+    return output_tmp     
+
+
+def learn_goals(topic, text):
+    prompt = "Topic: " + topic + '\n'
+    prompt = prompt + text + '\n'
+    prompt = prompt + """Some examples of learning goals from above are:
+    1. The student will be able to"""
+    
+    return get_results(prompt)
+     
+
+topic = gr.Textbox(lines = 1, placeholder="Topic")
+text = gr.Textbox(lines = 5, placeholder="Text")
+
+iface = gr.Interface(fn=learn_goals, inputs=[topic, text], outputs="text")
 iface.launch()