first streamlit app.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "authorship_tag": "ABX9TyMn+tHiWG9crzP8ftSAbb3k",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/shubhambagalsrb/my-streamlit-app/blob/main/first%20streamlit%20app.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install streamlit dotenv langchain_google_genai langchain_community unstructured faiss-cpu pyngrok"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EvaZz1AzmkLa",
        "outputId": "1aae14e6-4571-456a-eda2-4db0414cb77c"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Downloading pyngrok-7.2.3-py3-none-any.whl (23 kB)\n",
            "Installing collected packages: pyngrok\n",
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          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "cuzE0fCmuQep"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E5plyBIPmhXF",
        "outputId": "8a1f6475-9be9-40c4-e9a8-a1bc2fe5a2bb"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Writing app.py\n"
          ]
        }
      ],
      "source": [
        "%%writefile app.py\n",
        "\n",
        "import streamlit as st\n",
        "\n",
        "# Initialize session state for chat history\n",
        "if \"messages\" not in st.session_state:\n",
        "    st.session_state.messages = []\n",
        "\n",
        "# App title\n",
        "st.title(\"Chat with URLs\")\n",
        "\n",
        "# Input fields for two URLs\n",
        "url1 = st.text_input(\"Enter first URL:\")\n",
        "url2 = st.text_input(\"Enter second URL:\")\n",
        "\n",
        "# Display entered URLs\n",
        "if url1 and url2:\n",
        "    st.write(f\"✅ URL 1: {url1}\")\n",
        "    st.write(f\"✅ URL 2: {url2}\")\n",
        "\n",
        "# Chat area\n",
        "st.subheader(\"Chat Interface\")\n",
        "\n",
        "# Display previous messages\n",
        "for message in st.session_state.messages:\n",
        "    with st.chat_message(message[\"role\"]):\n",
        "        st.write(message[\"content\"])\n",
        "\n",
        "# User input\n",
        "user_input = st.chat_input(\"Type your message here...\")\n",
        "\n",
        "# If user sends a message\n",
        "if user_input:\n",
        "    # Store user message\n",
        "    st.session_state.messages.append({\"role\": \"user\", \"content\": user_input})\n",
        "\n",
        "    # Placeholder response (Modify this to process URLs or integrate an LLM)\n",
        "    response = f\"🤖 You said: {user_input}\"\n",
        "\n",
        "    # Store bot response\n",
        "    st.session_state.messages.append({\"role\": \"bot\", \"content\": response})\n",
        "\n",
        "    # Display bot response\n",
        "    with st.chat_message(\"bot\"):\n",
        "        st.write(response)\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%writefile app.py\n",
        "\n",
        "from langchain_google_genai import GoogleGenerativeAIEmbeddings,ChatGoogleGenerativeAI\n",
        "import os\n",
        "import streamlit as st\n",
        "import pickle\n",
        "import time\n",
        "from langchain import OpenAI\n",
        "from langchain.chains import RetrievalQAWithSourcesChain,conversational_retrieval\n",
        "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
        "from langchain.document_loaders import UnstructuredURLLoader\n",
        "from langchain.embeddings import OpenAIEmbeddings\n",
        "from langchain.vectorstores import FAISS\n",
        "\n",
        "from dotenv import load_dotenv\n",
        "\n",
        "google_api_key = \"AIzaSyDZedPp_BPZXjmS9laPVdYSz2tflOEQGps\"\n",
        "embeddings = GoogleGenerativeAIEmbeddings(model=\"gemini-1.5-pro\",google_api_key=google_api_key)\n",
        "\n",
        "llm = ChatGoogleGenerativeAI(\n",
        " model=\"gemini-1.5-pro\",\n",
        "    temperature=1,\n",
        "    max_retries=2,\n",
        " api_key= google_api_key)\n",
        "\n",
        "load_dotenv()\n",
        "# Initialize session state for chat history\n",
        "if \"messages\" not in st.session_state:\n",
        "    st.session_state.messages = []\n",
        "\n",
        "file_path = \"faiss_store_openai.pkl\"\n",
        "\n",
        "st.title(\"RockyBot: News Research Tool 📈\")\n",
        "st.sidebar.title(\"News Article URLs\")\n",
        "\n",
        "# Input fields for two URLs\n",
        "url1 = st.sidebar.text_input(\"Enter first URL:\")\n",
        "url2 = st.sidebar.text_input(\"Enter second URL:\")\n",
        "\n",
        "# Display entered URLs\n",
        "if url1 and url2:\n",
        "    st.write(f\"✅ URL 1: {url1}\")\n",
        "    st.write(f\"✅ URL 2: {url2}\")\n",
        "\n",
        "process_url_clicked = st.sidebar.button(\"Process URLs\")\n",
        "\n",
        "main_placeholder = st.empty()\n",
        "urls = [url1, url2]\n",
        "process_url_clicked = True\n",
        "if process_url_clicked:\n",
        "    # load data\n",
        "    loader = UnstructuredURLLoader(urls=urls)\n",
        "    # main_placeholder.text(\"Data Loading...Started...✅✅✅\")\n",
        "    data = loader.load()\n",
        "    time.sleep(2)\n",
        "\n",
        "from langchain.chains import ConversationChain\n",
        "\n",
        "\n",
        "# Chat area\n",
        "# st.subheader(\"Chat Interface\")\n",
        "\n",
        "# Display previous messages\n",
        "for message in st.session_state.messages:\n",
        "    with st.chat_message(message[\"role\"]):\n",
        "        st.write(message[\"content\"])\n",
        "count = 0\n",
        "while True :\n",
        "  # User input\n",
        "  user_input = st.chat_input(\"Type your message here...\",key=\"chat_input\")\n",
        "\n",
        "  # If user sends a message\n",
        "  if user_input:\n",
        "      # Store user message\n",
        "      st.session_state.messages.append({\"role\": \"user\", \"content\": user_input})\n",
        "      convo = ConversationChain(llm=llm)\n",
        "      result = convo.predict(input=f\"here is some information {data}. which one is better\")\n",
        "      # Placeholder response (Modify this to process URLs or integrate an LLM)\n",
        "      response = f\"🤖 Answer : {result}\"\n",
        "\n",
        "      # Store bot response\n",
        "      st.session_state.messages.append({\"role\": \"bot\", \"content\": result})\n",
        "\n",
        "      # Display bot response\n",
        "      with st.chat_message(\"bot\"):\n",
        "          st.write(response)\n",
        "      result = convo.run(user_input)\n",
        "      time.sleep(2)\n",
        "\n",
        "  count +=1\n",
        "  if count >=3:\n",
        "    break\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_N3OgbtivKWw",
        "outputId": "a89f3090-e163-4072-b3fa-6b11ed40a424"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting app.py\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%writefile app.py\n",
        "\n",
        "import os\n",
        "import streamlit as st\n",
        "import time\n",
        "from langchain_google_genai import GoogleGenerativeAIEmbeddings, ChatGoogleGenerativeAI\n",
        "from langchain.chains import ConversationChain\n",
        "from langchain.document_loaders import UnstructuredURLLoader\n",
        "from dotenv import load_dotenv\n",
        "\n",
        "# Load API Key (Avoid hardcoding)\n",
        "google_api_key = \"AIzaSyDZedPp_BPZXjmS9laPVdYSz2tflOEQGps\"\n",
        "\n",
        "embeddings = GoogleGenerativeAIEmbeddings(model=\"gemini-1.5-pro\", google_api_key=google_api_key)\n",
        "llm = ChatGoogleGenerativeAI(model=\"gemini-1.5-pro\", temperature=0.3, max_retries=2, api_key=google_api_key)\n",
        "convo = ConversationChain(llm=llm)  # Define once\n",
        "\n",
        "load_dotenv()\n",
        "\n",
        "# Initialize session state for chat history\n",
        "if \"messages\" not in st.session_state:\n",
        "    st.session_state.messages = []\n",
        "\n",
        "st.title(\"RockyBot: News Research Tool 📈\")\n",
        "st.sidebar.title(\"News Article URLs\")\n",
        "\n",
        "# Input fields for URLs\n",
        "url1 = st.sidebar.text_input(\"Enter first URL:\")\n",
        "url2 = st.sidebar.text_input(\"Enter second URL:\")\n",
        "\n",
        "# Display entered URLs\n",
        "if url1 and url2:\n",
        "    st.write(f\"✅ URL 1: {url1}\")\n",
        "    st.write(f\"✅ URL 2: {url2}\")\n",
        "\n",
        "# Process URLs\n",
        "process_url_clicked = st.sidebar.button(\"Process URLs\")\n",
        "\n",
        "if process_url_clicked and url1 and url2:\n",
        "    urls = [url1, url2]\n",
        "    loader = UnstructuredURLLoader(urls=urls)\n",
        "    st.write(\"🔄 Loading Data...\")\n",
        "    st.session_state.data = loader.load()\n",
        "    time.sleep(2)\n",
        "    st.write(\"✅ Data Loaded Successfully!\")\n",
        "\n",
        "# Chat Interface\n",
        "st.subheader(\"Chat Interface\")\n",
        "\n",
        "# Display previous chat messages\n",
        "for message in st.session_state.messages:\n",
        "    with st.chat_message(message[\"role\"]):\n",
        "        st.write(message[\"content\"])\n",
        "\n",
        "# User input\n",
        "user_input = st.chat_input(\"Type your message here...\", key=\"chat_input\")\n",
        "count = 0\n",
        "with st.chat_message(\"user\"):\n",
        "        st.write(f\"User: {user_input}\")\n",
        "if user_input:\n",
        "    # Store user message\n",
        "    st.session_state.messages.append({\"role\": \"user\", \"content\": user_input})\n",
        "    with st.chat_message(\"user\"):\n",
        "        st.write(user_input)\n",
        "\n",
        "\n",
        "    # Get response\n",
        "    if url1 and url2 and count==0:\n",
        "        result = convo.predict(input=f\"Here is some information {st.session_state.data}. Which one is better?\")\n",
        "    else:\n",
        "        result = convo.run(input=user_input)\n",
        "    count +=1\n",
        "    time.sleep(2)\n",
        "    # Display bot response\n",
        "    with st.chat_message(\"bot\"):\n",
        "        st.write(f\"🤖 Answer: {result}\")\n",
        "    # Store and display bot response\n",
        "    st.session_state.messages.append({\"role\": \"bot\", \"content\": result})\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "htlnvUzM6glK",
        "outputId": "1bd14f02-6c21-4d00-8278-6ca3464a4c03"
      },
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting app.py\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ngrok authtoken 2tdTCjUFlMeLiMYhgqAO4gsqcZ6_2BUu9D1yK79BoFJsGgEPm"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a8GeDBwrqpeb",
        "outputId": "f326fa02-f987-497f-ab89-b467c23c8112"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Authtoken saved to configuration file: /root/.config/ngrok/ngrok.yml\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!ngrok config 2tdTCjUFlMeLiMYhgqAO4gsqcZ6_2BUu9D1yK79BoFJsGgEPm\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gjLTw27Frt6E",
        "outputId": "d5e814db-4e01-4a40-f21f-2f913eb4b045"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "NAME:\n",
            "  config - update or migrate ngrok's configuration file\n",
            "\n",
            "USAGE:\n",
            "  ngrok config [flags]\n",
            "\n",
            "DESCRIPTION: \n",
            "  The config command gives a quick way to create or update ngrok's configuration\n",
            "  file. Use 'add-authtoken' or 'add-api-key' to set the corresponding properties.\n",
            "\n",
            "  Use 'check' to test a configuration file for validity. If you have an old\n",
            "  configuration file, you can also use 'upgrade' to automatically migrate to the\n",
            "  latest version.\n",
            "\n",
            "COMMANDS:\n",
            "  add-api-key                    save api key to configuration file\n",
            "  add-authtoken                  save authtoken to configuration file\n",
            "  add-connect-url                adds the connect URL (connect_url) to configuration file for custom agent ingress\n",
            "  add-server-addr                alias of add-connect-url\n",
            "  check                          check configuration file\n",
            "  edit                           edit configuration file\n",
            "  upgrade                        auto-upgrade configuration file\n",
            "\n",
            "OPTIONS:\n",
            "      --config strings   path to config files; they are merged if multiple\n",
            "  -h, --help             help for config\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# !ngrok http 8000 --basic-auth 'ngrok:issecure'"
      ],
      "metadata": {
        "id": "jgVIxnFZrV3S"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from pyngrok import ngrok\n",
        "import os\n",
        "\n",
        "# Kill any running ngrok processes\n",
        "os.system(\"pkill -f ngrok\")\n",
        "\n",
        "# # Start Streamlit app\n",
        "# !streamlit run app.py &\n",
        "# Start Streamlit in the background\n",
        "os.system(\"streamlit run app.py &\")\n",
        "\n",
        "# Expose the Streamlit app to the internet\n",
        "url = ngrok.connect(addr=8501,bind_tls=True)\n",
        "print(\"hello\")\n",
        "print(f\"🚀 Open your Streamlit app here: {url}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Eatcixx-nUnK",
        "outputId": "2e774fa9-1a88-40c2-a152-f04009c9edb0"
      },
      "execution_count": 85,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "hello\n",
            "🚀 Open your Streamlit app here: NgrokTunnel: \"https://6a94-34-80-42-110.ngrok-free.app\" -> \"http://localhost:8501\"\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "SV8pv5qjnZ1k"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}