Refactor ArangoDB class and script for fetching electric car documents

example_fetch_docs.py

@@ -1,7 +1,7 @@
 # Example of fetching documents and go though them one by one using Ollama:
 
 from arango_class import ArangoDB
-import ollama
+from ollama_class import Ollama
 
 
 # Get the documents where "electric car" is mentioned
@@ -13,6 +13,8 @@ documents = list(cursor)
 
 
 # Go though the documents one by one
+ollama = Ollama()
+
 for doc in documents:
     text = doc['translation']
     prompt =f"""Below is a transcript of a speech given in the European Parliament. I'm interested in all arguments related to electric cars. 
@@ -20,4 +22,4 @@ for doc in documents:
         Please give me a list of all arguments related to electric cars in the text above. One argument per line.
 Answer ONLY with the arguments. Kepp to the information in the text.""" #TODO Make a better prompt!
     
-    arguments = ollama.generate(prompt=prompt, model='llama3:8b-instruct-q5_K_M', options={'temperature': 0})
+    arguments = ollama.generate(prompt)