app.py

import gradio as gr
from openai import OpenAI
import json
import os

from pydantic import BaseModel, Field
from typing import Optional, List
from openai import OpenAI
import pandas as pd


class SummaryTweet(BaseModel):
    content: str = Field(..., description="A concise version of the abstract in tweet format. No Hastags")

class AnnounceTweet(BaseModel):
    content: str = Field(..., description="A tweet announcing a new article. Text must include the author and title.  No Hastags")

class InsightTweet(BaseModel):
    content: str = Field(..., description="Simple, understandable statement distilling a complex social science concept.  No Hastags")

class ThreadTweet(BaseModel):
    content: List[str] = Field(default=[], description="A list of tweets that together form a thread about the article, summarizing its key points and implications, engaging the audience, and encouraging further discussion or reading. No hashtags.")

class GenerateTweets(BaseModel):
    summary_tweets: List[SummaryTweet] = Field(default=[], description="A list of SummaryTweet instances.")
    insight_tweets: List[InsightTweet] = Field(default=[], description="A list of InsightTweet instances.")
    announce_tweets: List[AnnounceTweet] = Field(default=[], description="A list of AnnounceTweet instances.")

def get_api_key(input_password):
    # Retrieve the password and API key from environment variables
    correct_password = os.environ.get("password")
    api_key = os.environ.get("openai_key")
    
    if input_password == correct_password:
        return api_key
    else:
        return "Incorrect password."
    


def write_tweets(input_password, abstract_input):
    
    api_key_input = get_api_key(input_password)
    if api_key_input == "Incorrect password.":
        return 'Incorrect password.'
    
    client = OpenAI(
        max_retries=3,
        api_key=api_key_input,
        timeout=90.0, 
    )
    

    messages = [
        {
            "role": "system",
            "content": ''' You write a variety of different types of social media posts about sociology articles.
If you perform well, everyone gets a raise, while there are negative consequences if the posts don't get views.
NEVER USE HASHTAGS.
''',
        },
        {
            "role": "user",
            "content": f"""Generate five different tweets of each style about this sociology article:

            
      {abstract_input}
      
      """,
        },
    ]

    completion = client.chat.completions.create(
        model = 'gpt-4o',     #   model="gpt-3.5-turbo" is 20x cheaper but isn't as insightful 
        functions=[
            {
                "name": "generate_tweets",
                "description": "Create multiple social media posts, including a tweet thread, based on an article abstract.",
                "parameters": GenerateTweets.model_json_schema(),
            },
        ],
        n=1,
        messages=messages,
    )
    r = json.loads(completion.choices[0].message.function_call.arguments)
    tweets = [{'type': tweet_type.split('_')[0], 'text': t['content']} for tweet_type in r for t in r[tweet_type]]
    df = pd.DataFrame(tweets)
    grouped = df.groupby('type')['text'].apply(list).reset_index()
    markdown = ""
    for _, row in grouped.iterrows():
        markdown += f"- **{row['type']}**\n"
        for text in row['text']:
            markdown += f"  - {text}\n"
    return markdown



with gr.Blocks() as app:
    gr.Markdown("### Social Media Post Generator")
    api_key_input = gr.Textbox(label="Password", placeholder="Enter the super secret password")
    abstract_input = gr.Textbox(label="Article Abstract", placeholder="Enter the article abstract here")
    generate_button = gr.Button("Generate Tweets")
    output_markdown = gr.Markdown()
    
    generate_button.click(fn=write_tweets, inputs=[api_key_input, abstract_input], outputs=output_markdown)

app.launch()