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| import openai | |
| import os | |
| # Set up your OpenAI API key | |
| openai.api_key = os.getenv("22ec84421ec24230a3638d1b51e3a7dc") | |
| def generate_use_cases(company_info): | |
| use_cases = [] | |
| references = ["McKinsey AI Report", "Deloitte Industry Insights"] | |
| # Generate suggestions based on company focus areas | |
| if "customer experience" in company_info["focus_areas"]: | |
| suggestion = get_openai_response("Suggest a GenAI-driven chatbot for enhanced customer support.") | |
| use_cases.append(suggestion) | |
| if "operations" in company_info["focus_areas"]: | |
| suggestion = get_openai_response("Propose using predictive maintenance models to streamline operations.") | |
| use_cases.append(suggestion) | |
| if "supply chain" in company_info["focus_areas"]: | |
| suggestion = get_openai_response("Describe how real-time analytics could improve supply chain transparency.") | |
| use_cases.append(suggestion) | |
| return {"use_cases": use_cases, "references": references} | |
| def get_openai_response(prompt, model="gpt-4"): | |
| try: | |
| response = openai.ChatCompletion.create( | |
| model=model, | |
| messages=[{"role": "user", "content": prompt}] | |
| ) | |
| return response['choices'][0]['message']['content'] | |
| except Exception as e: | |
| print(f"Error generating response from OpenAI: {e}") | |
| return "Could not generate use case." | |