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My_Self_Bot

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BOB0920 commited on Jan 1

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__pycache__/rag.cpython-311.pyc +0 -0
__pycache__/templates/index.html +231 -0
ingest.py +54 -0
main.py +28 -0
rag.py +66 -0
vectorstore/db_faiss/index.faiss +0 -0
vectorstore/db_faiss/index.pkl +3 -0

__pycache__/rag.cpython-311.pyc ADDED Viewed

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__pycache__/templates/index.html ADDED Viewed

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>RGB Bot</title>
+    <style>
+        :root {
+            --bg-color: #0d0d0d;
+            --text-color: #e0e0e0;
+            --accent-color: #00ff00; /* Green typical of terminal/RGB */
+            --input-bg: #1a1a1a;
+            --bot-msg-bg: #2a2a2a;
+            --user-msg-bg: #004400;
+        }
+        body {
+            font-family: 'Courier New', Courier, monospace;
+            background-color: var(--bg-color);
+            color: var(--text-color);
+            margin: 0;
+            display: flex;
+            flex-direction: column;
+            height: 100vh;
+            overflow: hidden;
+        }
+        /* RGB Border Effect */
+        body::before {
+            content: "";
+            position: absolute;
+            top: 0; left: 0; right: 0; height: 3px;
+            background: linear-gradient(90deg, red, green, blue);
+            z-index: 1000;
+        }
+        header {
+            padding: 20px;
+            text-align: center;
+            border-bottom: 1px solid #333;
+            background: rgba(0,0,0,0.8);
+        }
+        h1 {
+            margin: 0;
+            font-size: 1.5rem;
+            text-transform: uppercase;
+            letter-spacing: 2px;
+            background: linear-gradient(90deg, #ff0000, #00ff00, #0000ff);
+            -webkit-background-clip: text;
+            -webkit-text-fill-color: transparent;
+            text-shadow: 0 0 10px rgba(255, 255, 255, 0.1);
+        }
+        #chat-container {
+            flex: 1;
+            padding: 20px;
+            overflow-y: auto;
+            display: flex;
+            flex-direction: column;
+            gap: 15px;
+            scroll-behavior: smooth;
+        }
+        .message {
+            max-width: 80%;
+            padding: 12px 16px;
+            border-radius: 8px;
+            line-height: 1.5;
+            position: relative;
+            word-wrap: break-word;
+        }
+        .bot-message {
+            align-self: flex-start;
+            background-color: var(--bot-msg-bg);
+            border-left: 3px solid #00f;
+            box-shadow: 0 0 10px rgba(0, 0, 255, 0.2);
+        }
+        .user-message {
+            align-self: flex-end;
+            background-color: var(--user-msg-bg);
+            border-right: 3px solid #0f0;
+            box-shadow: 0 0 10px rgba(0, 255, 0, 0.2);
+        }
+        .input-area {
+            padding: 20px;
+            background-color: #111;
+            border-top: 1px solid #333;
+            display: flex;
+            gap: 10px;
+        }
+        input[type="text"] {
+            flex: 1;
+            padding: 15px;
+            background-color: var(--input-bg);
+            border: 1px solid #333;
+            color: white;
+            border-radius: 4px;
+            font-family: inherit;
+            outline: none;
+            transition: border-color 0.3s;
+        }
+        input[type="text"]:focus {
+            border-color: var(--accent-color);
+            box-shadow: 0 0 8px rgba(0, 255, 0, 0.1);
+        }
+        button {
+            padding: 10px 25px;
+            background: linear-gradient(45deg, #0000aa, #00aa00);
+            border: none;
+            color: white;
+            font-weight: bold;
+            font-family: inherit;
+            cursor: pointer;
+            border-radius: 4px;
+            text-transform: uppercase;
+            letter-spacing: 1px;
+            transition: transform 0.1s;
+        }
+        button:active {
+            transform: scale(0.98);
+        }
+        /* Scrollbar */
+        ::-webkit-scrollbar {
+            width: 8px;
+        }
+        ::-webkit-scrollbar-track {
+            background: #111;
+        }
+        ::-webkit-scrollbar-thumb {
+            background: #333;
+            border-radius: 4px;
+        }
+        ::-webkit-scrollbar-thumb:hover {
+            background: #555;
+        }
+        .typing-indicator::after {
+            content: '...';
+            animation: blink 1s infinite;
+        }
+        @keyframes blink {
+            0% { opacity: 0; }
+            50% { opacity: 1; }
+            100% { opacity: 0; }
+        }
+    </style>
+</head>
+<body>
+    <header>
+        <h1>Peronal Assistant</h1>
+    </header>
+    <div id="chat-container">
+        <div class="message bot-message">
+            Hello! I'm Sagar's personal assistant. Feel free to ask me anything about Sagar.
+        </div>
+    </div>
+    <div class="input-area">
+        <input type="text" id="user-input" placeholder="Type your question..." autocomplete="off">
+        <button onclick="sendMessage()">Send</button>
+    </div>
+    <script>
+        const inputField = document.getElementById("user-input");
+        const chatContainer = document.getElementById("chat-container");
+        inputField.addEventListener("keypress", function(event) {
+            if (event.key === "Enter") {
+                sendMessage();
+            }
+        });
+        async function sendMessage() {
+            const text = inputField.value.trim();
+            if (!text) return;
+            // Add User Message
+            addMessage(text, "user-message");
+            inputField.value = "";
+            // Add Loading Indicator
+            const loadingId = "loading-" + Date.now();
+            addMessage("Thinking", "bot-message typing-indicator", loadingId);
+            try {
+                const response = await fetch("/chat", {
+                    method: "POST",
+                    headers: { "Content-Type": "application/json" },
+                    body: JSON.stringify({ message: text })
+                });
+                const data = await response.json();
+                // Remove loading
+                const loadingElement = document.getElementById(loadingId);
+                if (loadingElement) loadingElement.remove();
+                // Add Bot Response
+                addMessage(data.answer, "bot-message");
+            } catch (error) {
+                console.error("Error:", error);
+                const loadingElement = document.getElementById(loadingId);
+                if (loadingElement) loadingElement.remove();
+                addMessage("Error connecting to server.", "bot-message");
+            }
+        }
+        function addMessage(text, className, id = null) {
+            const div = document.createElement("div");
+            div.className = "message " + className;
+            div.innerText = text;
+            if (id) div.id = id;
+            chatContainer.appendChild(div);
+            // Scroll to bottom
+            chatContainer.scrollTop = chatContainer.scrollHeight;
+        }
+    </script>
+</body>
+</html>

ingest.py ADDED Viewed

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+import os
+from langchain_community.document_loaders import PyPDFLoader, TextLoader
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langchain_community.vectorstores import FAISS
+from langchain_huggingface import HuggingFaceEmbeddings
+from dotenv import load_dotenv
+# Load environment variables
+load_dotenv()
+DATA_PATH = "data"
+DB_FAISS_PATH = "vectorstore/db_faiss"
+def create_vector_db():
+    documents = []
+    # Check if data directory exists
+    if not os.path.exists(DATA_PATH):
+        print(f"Directory {DATA_PATH} not found.")
+        return
+    # Load documents
+    for filename in os.listdir(DATA_PATH):
+        file_path = os.path.join(DATA_PATH, filename)
+        if filename.endswith(".pdf"):
+            loader = PyPDFLoader(file_path)
+            documents.extend(loader.load())
+            print(f"Loaded {filename}")
+        elif filename.endswith(".txt"):
+            loader = TextLoader(file_path, encoding='utf-8')
+            documents.extend(loader.load())
+            print(f"Loaded {filename}")
+    if not documents:
+        print("No documents found to ingest.")
+        return
+    # Split text
+    text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=50)
+    texts = text_splitter.split_documents(documents)
+    print(f"Split documents into {len(texts)} chunks.")
+    # Create embeddings
+    print("Generating embeddings... This might take a moment.")
+    embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2',
+                                       model_kwargs={'device': 'cpu'})
+    # Create vector store
+    db = FAISS.from_documents(texts, embeddings)
+    db.save_local(DB_FAISS_PATH)
+    print(f"Vector store saved to {DB_FAISS_PATH}")
+if __name__ == "__main__":
+    create_vector_db()

main.py ADDED Viewed

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+from rag import get_answer
+import sys
+def main():
+    print("🔵 RGB Bot: Hello! I'm here to answer questions about Sagar. (Type 'exit' to quit)")
+    while True:
+        try:
+            query = input("\nYou: ")
+            if query.lower() in ["exit", "quit", "q"]:
+                print("🔵 RGB Bot: Goodbye!")
+                break
+            if not query.strip():
+                continue
+            print("🔵 RGB Bot: Thinking...")
+            response = get_answer(query)
+            print(f"🔵 RGB Bot: {response}")
+        except KeyboardInterrupt:
+            print("\n🔵 RGB Bot: Goodbye!")
+            sys.exit()
+        except Exception as e:
+            print(f"Error: {e}")
+if __name__ == "__main__":
+    main()

rag.py ADDED Viewed

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+import os
+from langchain_openai import ChatOpenAI
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import RunnablePassthrough
+from langchain_community.vectorstores import FAISS
+from langchain_huggingface import HuggingFaceEmbeddings
+from dotenv import load_dotenv
+load_dotenv()
+DB_FAISS_PATH = "vectorstore/db_faiss"
+def format_docs(docs):
+    return "\n\n".join(doc.page_content for doc in docs)
+def get_answer(query):
+    # Load Embeddings
+    embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2',
+                                       model_kwargs={'device': 'cpu'})
+    # Load Vector DB
+    try:
+        db = FAISS.load_local(DB_FAISS_PATH, embeddings, allow_dangerous_deserialization=True)
+    except Exception as e:
+        return f"Error loading FAISS index: {e} \n (Did you run ingest.py?)"
+    # Setup LLM (OpenRouter)
+    llm = ChatOpenAI(
+        base_url="https://openrouter.ai/api/v1",
+        api_key=os.getenv("OPENROUTER_API_KEY"),
+        model="openai/gpt-3.5-turbo",
+    )
+    # Define Prompt
+    template = """You are the RGB Bot, a personal assistant for Sagar.
+    Answer questions based strictly on the following context:
+    {context}
+    Guidelines:
+    1. Answer only from the provided context.
+    2. Be professional, friendly, and slightly playful (RGB style).
+    3. If the answer is not in the context, say 'As an AI chatbot. I don't have information about that yet, you may contact with orignal Sagar Rathi at sagar_rathi@zohomail.in.'
+    4. Do not make up facts.
+    Question: {question}
+    """
+    prompt = ChatPromptTemplate.from_template(template)
+    # Create LCEL Chain
+    retriever = db.as_retriever()
+    rag_chain = (
+        {"context": retriever | format_docs, "question": RunnablePassthrough()}
+        | prompt
+        | llm
+        | StrOutputParser()
+    )
+    try:
+        response = rag_chain.invoke(query)
+        return response
+    except Exception as e:
+        return f"Error gathering response: {e}"
+# Kept for backward compatibility if main.py expects get_rag_chain (it doesn't, it calls get_answer)

vectorstore/db_faiss/index.faiss ADDED Viewed

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vectorstore/db_faiss/index.pkl ADDED Viewed

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ac097e42d4290b6266f343f0f098c639b10aec869762c68ee080529bee217072
+size 14840