Submission-ByteZen

ByteZen/.gitignore

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+# .gitignore
+
+# Exclude environment (`.env`) files
+.env

ByteZen/.streamlit/config.toml

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+[theme]
+base="light"
+primaryColor="#D6EAF8"
+backgroundColor="#D6EAF8"
+secondaryBackgroundColor="#85929E"
+textColor="#000000"
+font="serif"

ByteZen/App/PATHS.py

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+NAVBAR_PATHS = {
+    'HOME':'home',
+    'ABOUT': 'about',
+    'ANALYSIS': 'analysis',
+    'CONTACT US': {
+        'FAQ': 'customer-support/faq',
+        'CHAT': 'customer-support/chat',
+        'CONTACT': 'customer-support/contact',
+        'TUTORIALS': 'customer-support/tutorials',
+        'HELP_CENTER': 'customer-support/help-center',
+        'BUG_REPORT': 'customer-support/bug-report'
+    }
+}
+
+SETTINGS = {
+    'OPTIONS':'options',
+    'CONFIGURATION':'configuration'
+}

ByteZen/App/assets/styles.css

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+.navbar{
+    font-family: 'Roboto', 'Roboto';
+    position: fixed;
+    font-weight: bold;
+    width: 100%;
+    background: #17202A;
+    z-index: 99999999999999999999;
+    left: 0rem;
+    top: 0rem;
+    height: 55px;
+}
+
+.navitem{
+    float: left;
+    font-weight: bold;
+    display: block;
+    color: #f2f2f2 !important;
+    text-align: center;
+    padding: 20px 20px;
+    text-decoration: none !important;
+    border-bottom: 2px solid transparent;
+    font-size: 14px;
+    font-family: 'Trebuchet MS', sans-serif;
+}
+
+.navitem:hover{
+    background-color: #333;
+    height: 55px !important;
+}
+
+
+.settings{
+    height:1rem;
+}
+
+.version-span{
+    color: white;
+    position: absolute;
+    right: 1rem;
+    bottom: 1.75rem;
+    opacity: 0.5;
+    z-index: 9999;
+    border: 2px solid #333;
+    border-radius: 25px;
+    padding-right: 0.5rem;
+    padding-left: 0.5rem;
+    background: #333;
+}
+
+.dropbtn {
+    background-color: transparent;
+    color: white;
+    padding: 10px;
+    font-size: 16px;
+    height: 55px;
+    opacity: 0.5;
+    filter: invert(1);
+    cursor: pointer;
+    transition: 0.3s;
+}
+
+.dropbtn:hover, .dropbtn:focus {
+    opacity:1;
+}
+
+.dropdown {
+    position: fixed;
+    display: inline-block;
+    right: 0rem;
+    top: 0rem;
+}
+
+.dropdown-content {
+    visibility: hidden;
+    position: fixed;
+    border-radius: 9px;
+    background-color: #333;
+    min-width: 160px;
+    overflow: auto;
+    right:0.3rem;
+    box-shadow: 0px 8px 16px 0px rgba(0,0,0,0.2);
+    z-index: 1;
+}
+
+.dropdown-content a {
+    color: white;
+    padding: 12px 16px;
+    text-decoration: none;
+    display: block;
+}
+
+.dropbtn:hover{
+    background-color: rgba(221, 221, 221, 0.233);
+    background: rgba(221, 221, 221, 0.233);
+}
+
+.dropdown a:hover {background-color: rgba(221, 221, 221, 0.233);}
+
+iframe{
+    height: 0rem;
+}

ByteZen/App/generate_response_opensourcemodel.py

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+import json
+import os
+import streamlit as st
+from langchain.llms import CTransformers
+
+class response_function:
+    @staticmethod
+    def generate_response(input_text, conversation_history):
+            intial_prompt = f"""
+                    You are the IT Expert, dedicated to resolving technical issues.
+                """
+            #LLM Initialization
+            #LLM Initialization
+            local_llm = "TheBloke/mistral-7b-intel-v0.1.Q4_0.gguf"
+
+            config = {
+                    'max_new_tokens': 1024,
+                    'repetition_penalty': 1.1,
+                    'temperature': 0.1,
+                    'top_k': 50,
+                    'top_p': 0.9,
+                    'stream': True,
+                    'threads': int(os.cpu_count() / 2)
+                }
+
+            llm = CTransformers(
+                model=local_llm,
+                model_type="mistral",
+                lib="avx2",  # for CPU use
+                **config
+            )
+            return response_message
+
+

ByteZen/App/ingest.py

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+import os
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import Chroma
+from langchain.embeddings import HuggingFaceBgeEmbeddings
+from langchain.document_loaders import PyPDFLoader
+
+model_name = "BAAI/bge-large-en"
+model_kwargs = {'device': 'cpu'}
+encode_kwargs = {'normalize_embeddings': False}
+embeddings = HuggingFaceBgeEmbeddings(
+    model_name=model_name,
+    model_kwargs=model_kwargs,
+    encode_kwargs=encode_kwargs
+)
+
+loader = PyPDFLoader("RAG.pdf")
+documents = loader.load()
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
+texts = text_splitter.split_documents(documents)
+
+vector_store = Chroma.from_documents(texts, embeddings, collection_metadata={"hnsw:space": "cosine"}, persist_directory="RAG/customer-support")
+
+print("Vector Store Created.......")