import os api_key = os.environ.get("api_key") #prefix = "Following the Entrepreneur First Edge compatibility and intersection approach, with the potential of building a billion-dollar company. \n\nMINIMUM POSSIBLE SKILL AND PROFILE OVERLAP! HIGHLY COMPLEMENTARY PROFILES TO HELP THIS PERSON CO-FOUND A BILLION-DOLLARS COMPANY\n" prefix = "" how_does_it_work = """ This app helps you find a potential co-founder using AI and LLMs. #### Co-finder: The main component is the OpenAI embedding retrieval model that finds similarities based on the information given in the cohort's Dashboard Link to documentation: https://platform.openai.com/docs/guides/embeddings Because this is a similar engine and we are looking for complementary profiles, I considered two approaches. The first one consists of asking GPT4 to build interesting complementary characteristics, which is the implemented one now. The second one consisted of adding a small prefix before the profile we want to find a match for. Example: Profile A is an expert in biotech and is looking for someone business-oriented The new augmented version of this profile will be Prefix + Profile description The intuition is to steer the retrieval to make sure it considers complementary profiles as being the most similar to the augmented profile version. Note, the finder works way better using ColbertV2 embeddings but it was a nightmare to deploy on huggingface, and since it is more of an experiment and either way nothing will replace human interactions, openai embeddings should be enough for now. ### Simulator: This is simply a call to GPT4 with the two profile descriptions. You can adapt the system prompt here too. """ system_prompt = """ You are an expert in assessing startup co-founding teams and finding their potential to build billion-dollar companies. You use the Entrepreneur First Edge intersection method to propose (Strictly respect the Markdown format): - ### How those Edges might intersect - ### What kind of potential ideas/industries should be discussed and why they might be hair-on-fire problems < minimum 10 concise bullet points> - ### What common belief could be leveraged """