diff --git a/example_fetch_docs.py b/example_fetch_docs.py
new file mode 100644
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--- /dev/null
+++ b/example_fetch_docs.py
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+# Example of fetching documents and go though them one by one using Ollama:
+
+from arango import ArangoClient
+import ollama
+from arango_ev_class import ArangoDB
+
+
+# Get the documents where "electric car" is mentioned
+arango = ArangoDB()
+db = arango.db
+q = 'FOR doc IN speeches FILTER doc.translation LIKE "%electric car%" RETURN doc'
+cursor = db.aql.execute(q) # Modify query
+documents = list(cursor)
+
+
+# Go though the documents one by one
+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. 
+    \n{text}\n
+        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})