This Streamlit app empowers you to research top stories and users on HackerNews using a team of AI assistants with GPT-4o.
- Research top stories and users on HackerNews
- Utilize a team of AI assistants specialized in story and user research
- Generate blog posts, reports, and social media content based on your research queries
- Clone the GitHub repository
git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
- Install the required dependencies:
pip install -r requirements.txt
- Get your OpenAI API Key
- Sign up for an OpenAI account (or the LLM provider of your choice) and obtain your API key.
- Run the Streamlit App
streamlit run research_agent.py
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Upon running the app, you will be prompted to enter your OpenAI API key. This key is used to authenticate and access the OpenAI language models.
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Once you provide a valid API key, three instances of the Assistant class are created:
- story_researcher: Specializes in researching HackerNews stories.
- user_researcher: Focuses on researching HackerNews users and reading articles from URLs.
- hn_assistant: A team assistant that coordinates the research efforts of the story and user researchers.
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Enter your research query in the provided text input field. This could be a topic, keyword, or specific question related to HackerNews stories or users.
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The hn_assistant will orchestrate the research process by delegating tasks to the story_researcher and user_researcher based on your query.
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The AI assistants will gather relevant information from HackerNews using the provided tools and generate a comprehensive response using the GPT-4 language model.
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The generated content, which could be a blog post, report, or social media post, will be displayed in the app for you to review and use.