Try!!!
Browse files
app.py
CHANGED
@@ -90,8 +90,8 @@ def get_completion(prompt):
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return score_model(model_uri, databricks_token, prompt)
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#def get_completion(prompt):
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def greet(company, solution, target_customer, problem, features):
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customer_persona =
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pitch = f"""My company, {company} is developing {solution} to help {target_customer} {problem} with {features}"""
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input = pitch
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@@ -124,5 +124,5 @@ Give a score for the product. Format your response as a JSON object with \
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gen_text = response["predictions"][0]["generated_text"]
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return json.dumps(extract_json(gen_text, 3))
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iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Company"), gr.Textbox(label="Solution"), gr.Textbox(label="Customer"), gr.Textbox(label="Problem"), gr.Textbox(label="Feature")], outputs="json")
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iface.launch()
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return score_model(model_uri, databricks_token, prompt)
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#def get_completion(prompt):
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def greet(company, solution, target_customer, problem, features, target_audience_persona="the target customer"):
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customer_persona = target_audience_persona
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pitch = f"""My company, {company} is developing {solution} to help {target_customer} {problem} with {features}"""
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input = pitch
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gen_text = response["predictions"][0]["generated_text"]
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return json.dumps(extract_json(gen_text, 3))
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iface = gr.Interface(fn=greet, inputs=[gr.Textbox(label="Company"), gr.Textbox(label="Solution"), gr.Textbox(label="Customer"), gr.Textbox(label="Problem"), gr.Textbox(label="Feature"), gr.Textbox(label="Target Audience persona", lines=3)], outputs="json")
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iface.launch()
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