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| import os | |
| import gradio as gr | |
| import google.generativeai as palm | |
| palm.configure(api_key=os.environ["YOUR_API_KEY"]) | |
| defaults = { | |
| 'model': 'models/chat-bison-001', | |
| 'temperature': 0.25, | |
| 'candidate_count': 1, | |
| 'top_k': 40, | |
| 'top_p': 0.95, | |
| } | |
| def get_recommendation(prompt, recommendation_type): | |
| context = "" | |
| if recommendation_type == "Letter of Recommendation": | |
| context = f"Write a formal Letter of Recommendation with a header and signature for a job addressed to hiring manager for a candidate who is male/he named Ziga who is a recruiting professional without mention of time worked together and follow this instructions: {prompt}" | |
| else: | |
| context = f"Write a Recommendation for LinkedIn for a candidate who is male/he named Ziga who is a recruiting professional without mention of time worked together and follow this instructions: {prompt}" | |
| messages = [context] | |
| response = palm.chat( | |
| **defaults, | |
| context=context, | |
| examples=[], | |
| messages=messages | |
| ) | |
| return response.last | |
| inputs = [ | |
| gr.inputs.Radio(choices=["Letter of Recommendation", "LinkedIn Recommendation"], label="Recommendation Type"), | |
| gr.inputs.Textbox(lines=7, label="Description") | |
| ] | |
| outputs = gr.outputs.Textbox(label="Reply") | |
| gr.Interface(fn=get_recommendation, inputs=inputs, outputs=outputs, title="Recommendation Generator", description="Describe what you enjoyed and observed while working with Ziga. Choose the type of recommendation you want.", theme="compact").launch() | |