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| ########################### | |
| # UI for Meeting RAG Q&A. # | |
| ########################### | |
| ##################### Imports ##################### | |
| import gradio as gr | |
| from utilities.setup import get_files | |
| from connections.pinecone import PineconeConnector | |
| from connections.model import InferencePipeline | |
| from services.embed_service.embed import EmbeddingService | |
| from services.qa_service.qna import QAService | |
| #from server import QAService | |
| import spaces | |
| #################### Functions #################### | |
| def process_transcripts(files, context): | |
| print(files) | |
| with EmbeddingService(conf, | |
| pinecone=pinecones) as e: | |
| f = e.run(files) | |
| # some way to wait or a progress bar? | |
| return "Completed Loading Data" | |
| def retrieve_answer(question, goals): | |
| #with QAService(conf) as q: | |
| # q.infer(question) | |
| with QAService(conf, | |
| pinecone=pinecones, | |
| model_pipeline=pipeline, | |
| question=question, | |
| goals=goals) as q: | |
| q.run() | |
| return question + goals | |
| ##################### Process ##################### | |
| def main(conf): | |
| with gr.Blocks() as demo: | |
| # Main page | |
| with gr.TabItem(conf["layout"]["page_names"][0]): | |
| gr.Markdown(get_files.load_markdown_file(conf["layout"]["about"])) | |
| # User config page | |
| with gr.TabItem(conf["layout"]["page_names"][1]): | |
| gr.Markdown("# Upload Transcript and Necessary Context") | |
| gr.Markdown("Please wait as the transcript is being processed.") | |
| load_file = gr.UploadButton(label="Upload Transcript (.vtt)", | |
| file_types=[".vtt"], | |
| file_count='multiple') | |
| goals = gr.Textbox(label="Project Goals", | |
| value=conf["defaults"]["goals"]) # not incorporated yet. Will be with Q&A. | |
| repository = gr.Textbox(label="Progress", value="Waiting for load...", visible=True) | |
| load_file.upload(process_transcripts, [load_file, goals], repository) | |
| # Meeting Question & Answer Page | |
| with gr.TabItem(conf["layout"]["page_names"][2]): | |
| question = gr.Textbox(label="Ask a Question", | |
| value=conf["defaults"]["question"]) | |
| ask_button = gr.Button("Ask!") | |
| model_output = gr.components.Textbox(label="Answer") | |
| ask_button.click(fn=retrieve_answer, | |
| inputs=[question, goals], | |
| outputs=model_output) | |
| demo.launch() | |
| ##################### Execute ##################### | |
| if __name__ == "__main__": | |
| # Get config | |
| conf = get_files.json_cfg() | |
| # Get keys | |
| keys = get_files.get_keys() | |
| # initialize pinecone connector | |
| pc_connector = PineconeConnector( | |
| api_key=keys["pinecone"], | |
| index_name=conf["embeddings"]["index_name"], | |
| embedding=conf["embeddings"]["embedding"], | |
| ) | |
| pinecones = pc_connector.run() | |
| # initialize model connector | |
| pipeline = InferencePipeline() | |
| pipeline = InferencePipeline(conf, | |
| api_key=keys["huggingface"] | |
| ) | |
| # run main | |
| main(conf) | |