Spaces:
Sleeping
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8338481
1
Parent(s):
0d4441c
Add application file
Browse files- __pycache__/app.cpython-311.pyc +0 -0
- app.py +2 -10
- templates/index.html +120 -0
__pycache__/app.cpython-311.pyc
ADDED
Binary file (4.36 kB). View file
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app.py
CHANGED
@@ -11,15 +11,12 @@ from qdrant_client import QdrantClient
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from langchain.vectorstores import Qdrant
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import os
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import json
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app = FastAPI()
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templates = Jinja2Templates(directory="templates")
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app.mount("/static", StaticFiles(directory="static"), name="static")
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# local_llm = r"meditron-7b.Q2_K.gguf"
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# local_llm = 'neural-chat-7b-v3-1.Q2_K.gguf'
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local_llm = 'Models/zephyr-7b-beta.Q2_K.gguf'
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config = {
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'max_new_tokens': 1024,
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'context_length': 2048,
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'threads': int(os.cpu_count() / 2)
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}
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llm =
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model=local_llm,
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model_type="mistral",
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lib="avx2",
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**config
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)
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print("LLM Initialized....")
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from langchain.vectorstores import Qdrant
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import os
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import json
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from ctransformers import AutoModelForCausalLM
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app = FastAPI()
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templates = Jinja2Templates(directory="templates")
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app.mount("/static", StaticFiles(directory="static"), name="static")
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config = {
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'max_new_tokens': 1024,
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'context_length': 2048,
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'threads': int(os.cpu_count() / 2)
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}
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llm = AutoModelForCausalLM.from_pretrained("TheBloke/zephyr-7B-beta-GGUF", model_file="zephyr-7b-beta.Q8_0.gguf", model_type="mistral", gpu_layers=50, **config)
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print("LLM Initialized....")
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templates/index.html
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@@ -0,0 +1,120 @@
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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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<title>Patent RAG QA App</title>
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<link href="https://fonts.googleapis.com/css2?family=Poppins:wght@400;600&display=swap" rel="stylesheet">
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<link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet">
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<style>
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body {
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background-color: black;
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font-family: 'Poppins', sans-serif;
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color: white;
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}
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.chat-container {
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max-width: 800px;
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margin: 50px auto;
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margin-top: 10%;
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padding: 20px;
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background-color: #333;
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border-radius: 10px;
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}
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.chat-heading {
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text-align: center;
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font-size: 2.5em;
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font-weight: 600;
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margin-bottom: 30px;
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color: #ffd700; /* Golden color for the heading */
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}
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.chat-input {
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margin-top: 20px; /* Added margin */
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margin-bottom: 20px;
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height: 100px; /* Increased height */
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}
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.chat-button {
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background-color: green;
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color: white;
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padding: 10px 20px;
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font-size: 1.2em;
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}
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.chat-response {
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background-color: #444;
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padding: 15px;
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border-radius: 5px;
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min-height: 100px; /* Minimum height for the response box */
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margin-top: 20px;
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}
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.accordion {
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margin-top: 20px;
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background-color: #444;
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border-radius: 5px;
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}
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.accordion-button {
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color: white;
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background-color: #555;
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}
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.accordion-body {
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color: white; /* Improved visibility of text */
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}
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pre {
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white-space:pre-wrap;
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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="container chat-container">
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<h1 class="chat-heading">Patent RAG QA App</h1>
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<div class="accordion" id="appDescriptionAccordion">
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<div class="accordion-item">
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<h2 class="accordion-header" id="descriptionHeading">
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<button class="accordion-button collapsed" type="button" data-bs-toggle="collapse" data-bs-target="#collapseDescription" aria-expanded="true" aria-controls="collapseDescription">
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About This App
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</button>
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</h2>
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<div id="collapseDescription" class="accordion-collapse collapse" aria-labelledby="descriptionHeading" data-bs-parent="#appDescriptionAccordion">
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<div class="accordion-body text-dark">
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This is a RAG implementation using Open Source stack.
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</div>
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</div>
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</div>
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</div>
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<div class="row">
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<div class="col">
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<textarea id="userInput" class="form-control chat-input" placeholder="Type your query here..."></textarea>
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<button id="submitBtn" class="btn chat-button">Submit</button>
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<div id="response" class="chat-response"></div>
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</div>
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</div>
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</div>
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<script src="https://cdn.jsdelivr.net/npm/[email protected]/dist/js/bootstrap.bundle.min.js"></script>
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<script>
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document.getElementById('submitBtn').addEventListener('click', async function() {
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var userInput = document.getElementById('userInput').value;
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document.getElementById('response').innerHTML = '<p>Processing...</p>';
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const formData = new FormData();
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formData.append('query', userInput);
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try {
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const response = await fetch('/get_response', {
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method: 'POST',
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body: formData
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});
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if (!response.ok) {
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throw new Error('Network response was not ok');
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}
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const data = await response.json();
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document.getElementById('response').innerHTML = `<p>${data.answer}</p><br><pre><b>Context: </b> ${data.source_document}</pre><br><pre><b>Source Document: </b> ${data.doc}</pre>`;
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} catch (error) {
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console.error('Error:', error);
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document.getElementById('response').innerHTML = '<p>Error processing your request</p>';
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}
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});
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</script>
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</body>
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</html>
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