first test with webapp
This commit is contained in:
ALIHAN DIKEL
45
.gitignore
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45
.gitignore
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# .gitignore
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# Python
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*.pyc
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*.pyo
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*.pyd
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__pycache__
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*.so
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*.egg
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*.egg-info
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dist
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build
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*.tar.gz
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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# PyCharm
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.idea/
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# macOS
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.DS_Store
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# Pip
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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.pytest_cache/
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# Jupyter Notebook
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.ipynb_checkpoints
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3
.idea/.gitignore
generated
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3
.idea/.gitignore
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# Default ignored files
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/shelf/
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/workspace.xml
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23
main.py
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main.py
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from fastapi import FastAPI, Request, Form
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from fastapi.responses import HTMLResponse
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from fastapi.templating import Jinja2Templates
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from pydantic import HttpUrl
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import uvicorn
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import services
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app = FastAPI()
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templates = Jinja2Templates(directory="templates")
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@app.get("/", response_class=HTMLResponse)
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def function(root: Request):
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return templates.TemplateResponse("index.html", {"request": root})
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@app.post("/", response_class=HTMLResponse)
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def function(summarize: Request, url: str = Form(...)):
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summary = services.generate_summary(url)
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return templates.TemplateResponse("index.html", {"request": summarize, "summary": summary})
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=8000)
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0
requirements.txt
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0
requirements.txt
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43
services.py
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43
services.py
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import io
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import os
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import time
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import pickle
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from jinja2 import Template
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import yt_dlp
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from whisper import load_model
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from loguru import logger
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from dotenv import load_dotenv
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import tiktoken
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from llms import LLMService
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import pipeline
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import utils
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logger.debug("loading env vars")
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load_dotenv(dotenv_path='./env')
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logger.debug("initializing llm query engines")
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query_engines = {}
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for model in ["gpt35turbo", "gpt4"]:
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llm_service = LLMService(provider="azure", model=model)
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query_engine = llm_service.initialize_client_query_engine()
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query_engines[model] = query_engine
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llm_servce = None
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logger.debug("loading stt model")
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model = load_model("large-v3", device="cpu")
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logger.debug("distributing stt model on multi-gpu setup")
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model.encoder.to("cuda:0")
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model.decoder.to("cuda:1")
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model.decoder.register_forward_pre_hook(lambda _, inputs: tuple([inputs[0].to("cuda:1"), inputs[1].to("cuda:1")] + list(inputs[2:])))
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model.decoder.register_forward_hook(lambda _, inputs, outputs: outputs.to("cuda:0"))
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def generate_summary(url):
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path_audiofile, name_audiofile = pipeline.download_audio(url=url)
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transcript = pipeline.transcribe(model=model, audio=path_audiofile)
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subtranscripts = pipeline.divide_transcript(transcript, max_tokens=2048)
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partial_summaries = pipeline.generate_partial_summaries(subtranscripts)
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merged_summary = pipeline.generate_merged_summary(partial_summaries)
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return merged_summary
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templates/index.html
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templates/index.html
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<link
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rel="stylesheet"
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href="https://cdnjs.cloudflare.com/ajax/libs/bootstrap/5.1.3/css/bootstrap.min.css"
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crossorigin="anonymous"
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>
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<title>URL Summarizer</title>
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<style>
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body, html {
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height: 100%;
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margin: 0;
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}
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.container {
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max-width: 600px;
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}
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.centered-container {
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height: 100vh;
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}
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</style>
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</head>
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<body>
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<div class="d-flex align-items-center justify-content-center centered-container">
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<div class="container text-center">
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<h1 class="mb-4">URL Summarizer</h1>
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<form method="post" class="form-inline justify-content-center">
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<div class="form-group mx-sm-3 mb-4">
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<label for="urlInput" class="sr-only">URL</label>
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<input type="url" class="form-control" id="urlInput" name="url" placeholder="Enter URL" required>
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</div>
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<button type="submit" class="btn btn-primary mb-2">Summarize</button>
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</form>
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{% if summary %}
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<div class="alert alert-info mt-4" role="alert">
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{{ summary }}
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</div>
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{% endif %}
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</div>
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</div>
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</body>
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</html>
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