bstraehle commited on
Commit
284b63f
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1 Parent(s): c5fa73d

Update app.py

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Files changed (1) hide show
  1. app.py +5 -3
app.py CHANGED
@@ -47,8 +47,10 @@ def invoke(openai_api_key, youtube_url, process_video, prompt):
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  #print(result)
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  return result["result"]
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- description = """<strong>Overview:</strong> The app demonstrates how to use a <strong>Large Language Model</strong> (LLM) with <strong>Retrieval Augmented Generation</strong>
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- (RAG) on external data (YouTube videos in this case, but it could be PDFs, URLs, databases, etc.)\n\n
 
 
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  <strong>Instructions:</strong> Enter an OpenAI API key, YouTube URL, and prompt to perform semantic search, sentiment analysis, summarization,
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  translation, etc. To ask multiple questions related to the same video, set "Process Video" to "True" on the first submission and then to "False".
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  The example is a 3:12 min. video about GPT-4 and takes less than 30 sec. to process. Experiment with different prompts, for example "what is gpt-4,
@@ -60,7 +62,7 @@ description = """<strong>Overview:</strong> The app demonstrates how to use a <s
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  gr.close_all()
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  demo = gr.Interface(fn=invoke,
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- inputs = [gr.Textbox(label = "OpenAI API Key", value = "sk-", lines = 1), gr.Textbox(label = "YouTube URL", value = "https://www.youtube.com/watch?v=--khbXchTeE", lines = 1), gr.Radio([True, False], label="Process Video", value = True), gr.Textbox(label = "Prompt", value = "what is gpt-4", lines = 1)],
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  outputs = [gr.Textbox(label = "Completion", lines = 1)],
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  title = "Generative AI - LLM & RAG",
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  description = description)
 
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  #print(result)
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  return result["result"]
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+ description = """<strong>Overview:</strong> The app demonstrates how to use a <strong>Large Language Model</strong> (LLM) with <strong>Retrieval Augmented Generation
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+ </strong> (RAG) on external data (YouTube videos in this case, but it could be PDFs, URLs, databases, or other
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+ <a href='https://github.com/bstraehle/ai-ml-dl/blob/667f92d0a4cf2a35e2861faefe97d1f094cd79e2/langchain/langchain-document-loaders.png'>
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+ structured/unstructured private/public data sources</a>).\n\n
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  <strong>Instructions:</strong> Enter an OpenAI API key, YouTube URL, and prompt to perform semantic search, sentiment analysis, summarization,
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  translation, etc. To ask multiple questions related to the same video, set "Process Video" to "True" on the first submission and then to "False".
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  The example is a 3:12 min. video about GPT-4 and takes less than 30 sec. to process. Experiment with different prompts, for example "what is gpt-4,
 
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  gr.close_all()
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  demo = gr.Interface(fn=invoke,
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+ inputs = [gr.Textbox(label = "OpenAI API Key", value = "sk-", lines = 1), gr.Textbox(label = "YouTube URL", value = "https://www.youtube.com/watch?v=--khbXchTeE", lines = 1), gr.Radio([True, False], label="Process Video", value = False), gr.Textbox(label = "Prompt", value = "what is gpt-4", lines = 1)],
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  outputs = [gr.Textbox(label = "Completion", lines = 1)],
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  title = "Generative AI - LLM & RAG",
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  description = description)