1st commit!

app.py

@@ -0,0 +1,44 @@
+import openai
+import os
+import gradio as gr
+import json
+from dotenv import load_dotenv, find_dotenv
+_ = load_dotenv(find_dotenv())
+
+
+openai.api_key  = os.getenv('OPENAI_API_KEY')
+
+def get_completion(prompt, model="gpt-3.5-turbo"):
+    messages = [{"role": "user", "content": prompt}]
+    response = openai.ChatCompletion.create(
+        model=model,
+        messages=messages,
+        temperature=0, # this is the degree of randomness of the model's output
+    )
+    return response.choices[0].message["content"]
+
+def greet(company, solution, target_customer, problem, features):
+
+    pitch = f"""
+    My company, {company} is developing {solution} to help {target_customer} {problem} with {features}
+    """
+
+	prompt = f"""
+Determine the product or solution, the problem being solved, features, target customer that are being discussed in the \
+following text, which is delimited by triple backticks. Then, pretend that you are the target customer. \
+State if you would use this product and elaborate on why. Also state if you would pay for it and elaborate on why.\
+
+Format your response as a JSON object with \
+'solution', 'problem', 'features', 'target_customer', 'fg_will_use', 'reason_to_use', 'fg_will_pay', 'reason_to_pay' as the keys.\
+
+Text sample: '''{pitch}'''
+	"""
+	response = get_completion(prompt)
+	return json.dumps(response)
+
+#iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+#iface.launch()
+
+#iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Text to find entities", lines=2)], outputs=[gr.HighlightedText(label="Text with entities")], title="NER with dslim/bert-base-NER", description="Find entities using the `dslim/bert-base-NER` model under the hood!", allow_flagging="never", examples=["My name is Andrew and I live in California", "My name is Poli and work at HuggingFace"])
+iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Company"), gr.Textbox(label="Solution"), gr.Textbox(label="Target Customer"), gr.Textbox(label="Problem"),  gr.Textbox(label="Killer Feture")], outputs="json")
+iface.launch()