import os import gradio as gr from haystack.nodes import TransformersImageToText from haystack.nodes import PromptNode, PromptTemplate from haystack import Pipeline description = """ # Captionate ✨ 📸 ## Create Instagram captions for your insta pics! Built by [Bilge Yucel](https://twitter.com/bilgeycl) using [Haystack](https://github.com/deepset-ai/haystack)💙 """ image_to_text = TransformersImageToText( model_name_or_path="nlpconnect/vit-gpt2-image-captioning", progress_bar=True ) prompt_template = PromptTemplate(prompt=""" You will receive a describing text of a photo. Try to come up with a nice Instagram caption. Requirements for the caption: * Must rhyme with the describing text * Should be at least 10 words * Needs to include one emoji and suitable hastags Describing text:{documents}; Caption: """) hf_api_key = os.environ["HF_API_KEY"] prompt_node = PromptNode(model_name_or_path="tiiuae/falcon-7b-instruct", api_key=hf_api_key, default_prompt_template=prompt_template, model_kwargs={"trust_remote_code":True}) captioning_pipeline = Pipeline() captioning_pipeline.add_node(component=image_to_text, name="image_to_text", inputs=["File"]) captioning_pipeline.add_node(component=prompt_node, name="prompt_node", inputs=["image_to_text"]) def generate_caption(image_file_paths): caption = captioning_pipeline.run(file_paths=[image_file_paths]) print(caption) return caption["results"][0] with gr.Blocks(theme="soft") as demo: gr.Markdown(value=description) image = gr.Image(type="filepath") submit_btn = gr.Button("✨ Captionate ✨") caption = gr.Textbox(label="Caption") submit_btn.click(fn=generate_caption, inputs=[image], outputs=[caption]) if __name__ == "__main__": demo.launch()