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import openai |
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from openai import OpenAI |
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import os |
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openai.api_key = os.getenv("OPENAI_KEY") |
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client = OpenAI(api_key=openai.api_key) |
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def model_api(input, prompt_type): |
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return prompt_type(input) |
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def sentiment(text): |
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print(text) |
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prompt = f"""You are trained to analyze and detect the sentiment of the given text. |
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If you are unsure of an answer, you can say "not sure" and recommend the user review manually. |
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Analyze the following text and determine if the sentiment is: POSITIVE, NEGATIVE or NEUTRAL. |
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Reply in single word. |
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Examples |
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Input: dress was beautiful. Output: POSITIVE |
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Input: pizza had weird smell. Output: NEGATIVE |
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Input: {text}. Output:""" |
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response = client.chat.completions.create( |
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model="gpt-3.5-turbo", |
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messages=[ |
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{"role": "system", "content": "You are a helpful assistant."}, |
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{"role": "user", "content": prompt} |
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], |
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temperature=0 |
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) |
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print(response) |
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sentiment = response.choices[0].message.content.strip() |
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return sentiment |
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def image_gen(text): |
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print(text) |
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response = client.images.generate( |
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model="dall-e-3", |
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prompt= text, |
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size="1024x1024", |
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quality="standard", |
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n=1, |
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) |
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image_url = response.data[0].url |
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return image_url |