diff --git a/examples/extract-table/run.py b/examples/extract-table/run.py new file mode 100644 index 0000000..740db9f --- /dev/null +++ b/examples/extract-table/run.py @@ -0,0 +1,41 @@ +from openai import OpenAI + +client = OpenAI() + + +response = client.chat.completions.create( + model="gpt-4-vision-preview", + max_tokens=1000, + messages=[ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "Describe this data accurately as a table in markdown format.", + }, + { + "type": "image_url", + "image_url": { + # "url": "https://a.storyblok.com/f/47007/2400x1260/f816b031cb/uk-ireland-in-three-charts_chart_a.png/m/2880x0", + # "url": "https://a.storyblok.com/f/47007/2400x2000/bf383abc3c/231031_uk-ireland-in-three-charts_table_v01_b.png/m/2880x0", + # "url": "https://a.storyblok.com/f/47007/4800x2766/1688e25601/230629_attoptinratesmidyear_blog_chart02_v01.png/m/2880x0" + "url": "https://a.storyblok.com/f/47007/2400x1260/934d294894/uk-ireland-in-three-charts_chart_b.png/m/2880x0" + }, + }, + { + "type": "text", + "text": """ + First take a moment to reason about the best set of headers for the tables. + Write a good h1 for the image above. Then follow up with a short description of the what the data is about. + Then for each table you identified, write a h2 tag that is a descriptive title of the table. + Then follow up with a short description of the what the data is about. + Lastly, produce the markdown table for each table you identified. + """, + }, + ], + } + ], +) + +print(response.choices[0].message.content)