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| import chromadb | |
| from openai import OpenAI | |
| from dotenv import load_dotenv | |
| load_dotenv() | |
| # setting the environment | |
| DATA_PATH = r"data" | |
| CHROMA_PATH = r"chroma_db" | |
| chroma_client = chromadb.PersistentClient(path=CHROMA_PATH) | |
| collection = chroma_client.get_or_create_collection(name="growing_vegetables") | |
| user_query = input("What do you want to know about growing vegetables?\n\n") | |
| results = collection.query( | |
| query_texts=[user_query], | |
| n_results=1 | |
| ) | |
| #print(results['documents']) | |
| #print(results['metadatas']) | |
| client = OpenAI() | |
| system_prompt = """ | |
| You are a helpful assistant. You answer questions about growing vegetables in Florida. | |
| But you only answer based on knowledge I'm providing you. You don't use your internal | |
| knowledge and you don't make thins up. | |
| If you don't know the answer, just say: I don't know | |
| -------------------- | |
| The data: | |
| """+str(results['documents'])+""" | |
| """ | |
| #print(system_prompt) | |
| response = client.chat.completions.create( | |
| model="gpt-4o", | |
| messages = [ | |
| {"role":"system","content":system_prompt}, | |
| {"role":"user","content":user_query} | |
| ] | |
| ) | |
| print("\n\n---------------------\n\n") | |
| print(response.choices[0].message.content) |