StockBot_using_LLAMA_2.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# **GPU configration**\n"
      ],
      "metadata": {
        "id": "9Fn0to6DOLZd"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Hlt_eF5XVW36",
        "outputId": "e38ce0f4-67a4-4ee0-93fc-5532a304f666"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Tue Mar  5 13:58:48 2024       \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| NVIDIA-SMI 535.104.05             Driver Version: 535.104.05   CUDA Version: 12.2     |\n",
            "|-----------------------------------------+----------------------+----------------------+\n",
            "| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |\n",
            "| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |\n",
            "|                                         |                      |               MIG M. |\n",
            "|=========================================+======================+======================|\n",
            "|   0  Tesla V100-SXM2-16GB           Off | 00000000:00:04.0 Off |                    0 |\n",
            "| N/A   34C    P0              23W / 300W |      0MiB / 16384MiB |      0%      Default |\n",
            "|                                         |                      |                  N/A |\n",
            "+-----------------------------------------+----------------------+----------------------+\n",
            "                                                                                         \n",
            "+---------------------------------------------------------------------------------------+\n",
            "| Processes:                                                                            |\n",
            "|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |\n",
            "|        ID   ID                                                             Usage      |\n",
            "|=======================================================================================|\n",
            "|  No running processes found                                                           |\n",
            "+---------------------------------------------------------------------------------------+\n"
          ]
        }
      ],
      "source": [
        "!nvidia-smi"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **ALL THE NECESSARY INSTALLATIONS**"
      ],
      "metadata": {
        "id": "3sx7bypMOm-l"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "m7CuPAmTQ8lj"
      },
      "outputs": [],
      "source": [
        "!pip install --upgrade astrapy\n",
        "!pip install langchain_community\n",
        "!pip install -Uqqq pip --progress-bar off\n",
        "!pip install -qqq torch==2.1.0 --progress-bar off\n",
        "!pip install -qqq transformers==4.31.0 --progress-bar off\n",
        "!pip install -qqq langchain==0.0.266 --progress-bar off\n",
        "!pip install -qqq chromadb==0.4.5 --progress-bar off\n",
        "!pip install -qqq pypdf==3.15.0 --progress-bar off\n",
        "!pip install -qqq xformers==0.0.20 --progress-bar off\n",
        "!pip install -qqq sentence_transformers==2.2.2 --progress-bar off\n",
        "!pip install -qqq InstructorEmbedding==1.0.1 --progress-bar off\n",
        "!pip install -qqq pdf2image==1.16.3 --progress-bar off\n",
        "!pip install auto-gptq\n",
        "!pip install fastapi\n",
        "!pip install uvicorn\n",
        "!pip install pickle5\n",
        "!pip install scikit-learn\n",
        "!pip install requests\n",
        "!pip install pypi-json\n",
        "!pip install pyngrok\n",
        "!pip install nest-asyncio"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**ALL THE NECESSARY PACKAGES AND LIBRARIES**"
      ],
      "metadata": {
        "id": "dbh1Vbs7ISOY"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "3gNyl0Zr3w-e"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "from auto_gptq import AutoGPTQForCausalLM\n",
        "from langchain import HuggingFacePipeline, PromptTemplate\n",
        "from langchain.chains import RetrievalQA\n",
        "from langchain.document_loaders import PyPDFDirectoryLoader\n",
        "from langchain.embeddings import HuggingFaceInstructEmbeddings\n",
        "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
        "from langchain.vectorstores import Chroma\n",
        "from pdf2image import convert_from_path\n",
        "from transformers import AutoTokenizer, TextStreamer, pipeline\n",
        "from langchain.memory import (\n",
        "    ChatMessageHistory,\n",
        "    ConversationBufferMemory,\n",
        "    ConversationBufferWindowMemory,\n",
        "    ConversationSummaryBufferMemory,\n",
        "    VectorStoreRetrieverMemory,\n",
        ")\n",
        "from langchain.chains.question_answering import load_qa_chain\n",
        "from langchain_community.vectorstores import AstraDB\n",
        "DEVICE = \"cuda:0\" if torch.cuda.is_available() else \"cpu\"\n",
        "\n",
        "from fastapi import FastAPI\n",
        "import pickle\n",
        "import json\n",
        "import uvicorn\n",
        "from pyngrok import ngrok\n",
        "from fastapi.middleware.cors import CORSMiddleware\n",
        "import nest_asyncio"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import userdata\n",
        "astra_db_api_endpoint=userdata.get('astra_db_api_endpoint')\n",
        "astra_db_application_token=userdata.get('astra_db_application_token')\n"
      ],
      "metadata": {
        "id": "LKXFPGk10keW"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **INITIALIZING FASTAPI APP**"
      ],
      "metadata": {
        "id": "PIFB1romO4bI"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "nNmhk4dc3sBM"
      },
      "outputs": [],
      "source": [
        "app = FastAPI()"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**SETTING UP CORS**"
      ],
      "metadata": {
        "id": "6fK3bCwZO-cn"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rMaxvzkg3tvg"
      },
      "outputs": [],
      "source": [
        "origins = [\"*\"]\n",
        "\n",
        "app.add_middleware(\n",
        "    CORSMiddleware,\n",
        "    allow_origins=origins,\n",
        "    allow_credentials=True,\n",
        "    allow_methods=[\"*\"],\n",
        "    allow_headers=[\"*\"],\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**AUTOGPT FOR PREVIOUS CUDA VERSION**"
      ],
      "metadata": {
        "id": "VfHFrMIQPEZ3"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "TW-eiLEWS9RO"
      },
      "outputs": [],
      "source": [
        "!wget -q https://github.com/PanQiWei/AutoGPTQ/releases/download/v0.4.1/auto_gptq-0.4.1+cu122-cp310-cp310-linux_x86_64.whl"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LRt2uqPvWvMN"
      },
      "outputs": [],
      "source": [
        "!pip install -qqq auto_gptq-0.4.1+cu122-cp310-cp310-linux_x86_64.whl --progress-bar off"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "vP9OXL66Vq8J"
      },
      "outputs": [],
      "source": [
        "\n",
        "!sudo apt-get install poppler-utils"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **BUFFER MEMORY INITIALISATION**"
      ],
      "metadata": {
        "id": "2xpPksbFPL8X"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "HSCyOAW9B8fZ"
      },
      "outputs": [],
      "source": [
        "memory = ConversationBufferMemory(memory_key=\"chat_history\", input_key=\"question\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **LOADING PDF INTO LOCAL DIRECTORY UNDER \"PDFS\"**"
      ],
      "metadata": {
        "id": "3xJx8UVmPUHY"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "JQbqi8D-W4Nm"
      },
      "outputs": [],
      "source": [
        "!mkdir pdfs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lIur_NMBX3SI"
      },
      "outputs": [],
      "source": [
        "!gdown --id 1v-Rn1FVU1pLTAQEgm0N9oB6cExMoebZr -O pdfs/tesla-earnings-report.pdf\n",
        "!gdown --id 1Xc890jrQvCExAkryVWAttsv1DBLdVefN -O pdfs/nvidia-earnings-report.pdf\n",
        "!gdown --id 1Epz-SQ3idPpoz75GlTzzomag8gplzLv8 -O pdfs/meta-earnings-report.pdf\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "loader = PyPDFDirectoryLoader(\"pdfs\")\n",
        "docs = loader.load()\n",
        "len(docs)\n",
        "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1024, chunk_overlap=64)\n",
        "texts = text_splitter.split_documents(docs)\n",
        "len(texts)"
      ],
      "metadata": {
        "id": "RIZmenTOPt3A"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "XRHZdK0CMsBD"
      },
      "outputs": [],
      "source": [
        "from langchain_community.document_loaders import WebBaseLoader\n",
        "from langchain.text_splitter import RecursiveCharacterTextSplitter\n",
        "loader = WebBaseLoader(\"https://www.stockgro.club/faq/\")\n",
        "data = loader.load()\n",
        "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1024, chunk_overlap=64)\n",
        "website_texts = text_splitter.split_documents(data)\n",
        "print(website_texts)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 986
        },
        "id": "TlqQZ1WnYHXK",
        "outputId": "e47a9189-5dae-4823-96d0-4b50b29f3c0a"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<PIL.PpmImagePlugin.PpmImageFile image mode=RGB size=749x969>"
            ]
          },
          "execution_count": 10,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "meta_images = convert_from_path(\"pdfs/meta-earnings-report.pdf\", dpi=88)\n",
        "meta_images[0]\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **DOWNLOADING EMBEDDINGS MODEL**"
      ],
      "metadata": {
        "id": "pdl4u4uHP1gU"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fHySR1bUf4BC"
      },
      "outputs": [],
      "source": [
        "embeddings = HuggingFaceInstructEmbeddings( model_name=\"hkunlp/instructor-large\", model_kwargs={\"device\": DEVICE} )"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **UPLOADING PDFS IN KNOWLEDGE BASE (AstraDB Vector Database)**"
      ],
      "metadata": {
        "id": "rXldTavl3XXU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def get_pdf_text_from_folder(folder_path):\n",
        "    loader = PyPDFDirectoryLoader(folder_path)\n",
        "    docs = loader.load()\n",
        "    return docs\n",
        "\n",
        "\n",
        "def get_text_chunks(text):\n",
        "    text_splitter = RecursiveCharacterTextSplitter(chunk_size=1024, chunk_overlap=64)\n",
        "    texts = text_splitter.split_documents(text)\n",
        "    return texts\n",
        "\n",
        "def get_vector_store(text_chunks):\n",
        "\n",
        "    #embeddings = HuggingFaceInstructEmbeddings( model_name=\"sentence-transformers/all-MiniLM-L6-v2\")\n",
        "    embeddings = HuggingFaceInstructEmbeddings( model_name=\"hkunlp/instructor-large\")\n",
        "    vstore = AstraDB(\n",
        "        embedding=embeddings,\n",
        "        collection_name=\"pdfdata\",\n",
        "        token=astra_db_application_token,\n",
        "        api_endpoint=astra_db_api_endpoint\n",
        "    )\n",
        "    vstore.add_documents(text_chunks)\n",
        "    # vector_store = FAISS.from_texts(text_chunks, embedding=embeddings)\n",
        "    # vector_store.save_local(\"faiss_index\")\n",
        "\n",
        "\n",
        "loader = WebBaseLoader(\"https://www.stockgro.club/faq/\")\n",
        "data = loader.load()\n",
        "text_splitter = RecursiveCharacterTextSplitter(chunk_size=1024, chunk_overlap=64)\n",
        "website_texts = text_splitter.split_documents(data)\n",
        "get_vector_store(website_texts)\n",
        "pdf_folder_path = \"pdfs\"\n",
        "raw_text = get_pdf_text_from_folder(pdf_folder_path)\n",
        "text_chunks = get_text_chunks(raw_text)\n",
        "get_vector_store(text_chunks)"
      ],
      "metadata": {
        "id": "LiBlzC6M2-1P"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **INITIALIZING ASTRA DB DATASTAX VECTOR DB**"
      ],
      "metadata": {
        "id": "V0tQvr2tP8zt"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dxb6ZzmzN1wx"
      },
      "outputs": [],
      "source": [
        "\n",
        "vstore = AstraDB(\n",
        "    embedding=embeddings,\n",
        "    collection_name=\"pdfdata\",\n",
        "    token=astra_db_application_token,\n",
        "    api_endpoint=astra_db_api_endpoint\n",
        ")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BAsoiEff8HBo"
      },
      "outputs": [],
      "source": [
        "vstore.add_documents(texts)\n",
        "vstore.add_documents(website_texts)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xkxjKdhbOsCT"
      },
      "outputs": [],
      "source": [
        " relevant_docs = vstore.similarity_search(\"what is Stockgro?\", astra_db_application_token=\"AstraCS:caMHvgsIrkHpjTCAoyhRnsRK:945bdbb46d23f616e73a5a3675bcbfa6353152446500bec0e2ab1185119736f3\",search_kwargs={\"k\": 2})"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "l-y2IN9sBjyb"
      },
      "outputs": [],
      "source": [
        "print(relevant_docs)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "H3mJCXhLgNYu"
      },
      "outputs": [],
      "source": [
        "db = Chroma.from_documents(texts, embeddings, persist_directory=\"db\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **DOWNLOADING LARGE LANGAUGE MODEL**"
      ],
      "metadata": {
        "id": "mJMxXTW5QNoD"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zlZ4GFapglVP"
      },
      "outputs": [],
      "source": [
        "\n",
        "model_name_or_path = \"TheBloke/Llama-2-7B-chat-GPTQ\"\n",
        "model_basename = \"model\"\n",
        "tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)\n",
        "model = AutoGPTQForCausalLM.from_quantized(\n",
        "    model_name_or_path,\n",
        "    revision=\"gptq-4bit-128g-actorder_True\",\n",
        "    model_basename=model_basename,\n",
        "    use_safetensors=True,\n",
        "    trust_remote_code=True,\n",
        "    inject_fused_attention=False,\n",
        "    device=DEVICE,\n",
        "    quantize_config=None,\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**FINE_TUNED MODEL NOT RECOMMENDED FOR RAG**"
      ],
      "metadata": {
        "id": "JDlkxpZMQf4n"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "UnG8EwBhKOgx"
      },
      "outputs": [],
      "source": [
        "!pip install -q bitsandbytes datasets accelerate loralib einops\n",
        "!pip install -q git+https://github.com/huggingface/peft.git\n",
        "\n",
        "import torch\n",
        "from peft import PeftModel, PeftConfig\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
        "\n",
        "peft_model_id = \"Ansh154/llama-2-Stockgro\"\n",
        "config = PeftConfig.from_pretrained(peft_model_id)\n",
        "model = AutoModelForCausalLM.from_pretrained(\n",
        "    config.base_model_name_or_path,\n",
        "    return_dict=True,\n",
        "    load_in_8bit=True,\n",
        "    device_map=\"auto\",\n",
        "    trust_remote_code=True,\n",
        ")\n",
        "tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)\n",
        "tokenizer.pad_token = tokenizer.eos_token\n",
        "\n",
        "# Load the Lora model\n",
        "model = PeftModel.from_pretrained(model, peft_model_id)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**DEFAULT META LLAMA 2 PROPMT FROM HUGGINFACE MODEL CARD**"
      ],
      "metadata": {
        "id": "JRPINi6jQnfJ"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "qhdbfAD9hUrj"
      },
      "outputs": [],
      "source": [
        "DEFAULT_SYSTEM_PROMPT = \"\"\"\n",
        "You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe. Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.\n",
        "\n",
        "If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.\n",
        "\"\"\".strip()\n",
        "\n",
        "\n",
        "def generate_prompt(prompt: str, system_prompt: str = DEFAULT_SYSTEM_PROMPT) -> str:\n",
        "    return f\"\"\"\n",
        "[INST] <>\n",
        "{system_prompt}\n",
        "<>\n",
        "\n",
        "{prompt} [/INST]\n",
        "\"\"\".strip()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**FOR STREAMING TEXT FROM LLM**"
      ],
      "metadata": {
        "id": "5h6qsY2QQwj_"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "rIW6ClHwhw-i"
      },
      "outputs": [],
      "source": [
        "streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**SETTING UP TEXT PIPELINE**"
      ],
      "metadata": {
        "id": "cY_WbqJTQ9Lo"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aVVjHNFqhySz"
      },
      "outputs": [],
      "source": [
        "text_pipeline = pipeline(\n",
        "    \"text-generation\",\n",
        "    model=model,\n",
        "    tokenizer=tokenizer,\n",
        "    max_new_tokens=1024,\n",
        "    temperature=0,\n",
        "    top_p=0.95,\n",
        "    repetition_penalty=1.15,\n",
        "    streamer=streamer,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "XSTnQmVUh5J_"
      },
      "outputs": [],
      "source": [
        "llm = HuggingFacePipeline(pipeline=text_pipeline, model_kwargs={\"temperature\": 0})\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**SYSTEM PROPMT**"
      ],
      "metadata": {
        "id": "I6jvkTCqRC6j"
      }
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "3LfRja0QiAwO"
      },
      "outputs": [],
      "source": [
        "SYSTEM_PROMPT = \"Use the following pieces of context to answer the question at the end. If you don't know the answer, just say that you don't know, don't try to make up an answer. and include not more than 1 logical short follow up question that can be asked by the user, include it in the answer in the end saying you can also ask these follow up questions :\"\n",
        "\n",
        "template = generate_prompt(\n",
        "    \"\"\"\n",
        "\n",
        "Context : {context}\n",
        "Conversation_history : {chat_history}\n",
        "Question: {question}\n",
        "\"\"\",\n",
        "    system_prompt=SYSTEM_PROMPT,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "7npxyITYiCYV",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "outputId": "cee4c0cd-38c6-440e-d9d3-530512bdaf31"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "  <style>\n",
              "    pre {\n",
              "        white-space: pre-wrap;\n",
              "    }\n",
              "\n",
              "  </style>\n",
              "  "
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "prompt = PromptTemplate(template=template, input_variables=[\"chat_history\",\"context\", \"question\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8VRQLn_3AkoF"
      },
      "outputs": [],
      "source": [
        "retriever = vstore.as_retriever(search_kwargs={\"k\": 3})"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **MAIN FUNCTION**"
      ],
      "metadata": {
        "id": "ogHsSM_xRKCZ"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "uzW5eUWQCwM3"
      },
      "outputs": [],
      "source": [
        "def generate_answer(user_question):\n",
        "  relevant_docs = vstore.similarity_search(user_question, astra_db_application_token=\"AstraCS:caMHvgsIrkHpjTCAoyhRnsRK:945bdbb46d23f616e73a5a3675bcbfa6353152446500bec0e2ab1185119736f3\",search_kwargs={\"k\": 2})\n",
        "  chain = load_qa_chain(llm, chain_type=\"stuff\",memory=memory, prompt=prompt)\n",
        "  response = chain({\"input_documents\": relevant_docs, \"question\": user_question}, return_only_outputs=True)\n",
        "  print(chain.memory.buffer)\n",
        "  return response\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fU2FIuKdcD3x"
      },
      "outputs": [],
      "source": [
        "result = generate_answer(\"What is the revenue for Meta during 2023?\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LQcOzUGhcYkI"
      },
      "outputs": [],
      "source": [
        "print(result)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **SETTING UP API ENDPOINT**"
      ],
      "metadata": {
        "id": "0dREHNC-RPVh"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jf9rQskEiT8F"
      },
      "outputs": [],
      "source": [
        "from fastapi import Request\n",
        "@app.post('/answer/')\n",
        "async def get_answer1(request: Request):\n",
        "  question = await request.json()\n",
        "  user_question = question.get(\"question\", \"\")\n",
        "  result =await generate_answer(user_question)\n",
        "  return {\"answer\":result['output_text']}"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "**DEBUGGER FOR UTF-8 ERROR**"
      ],
      "metadata": {
        "id": "TdzjRuZrRYPG"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ViVTbFzodYvd"
      },
      "outputs": [],
      "source": [
        "import locale\n",
        "locale.getpreferredencoding = lambda: \"UTF-8\""
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **FOR STARTING SERVER**"
      ],
      "metadata": {
        "id": "7eVwojrVRiUo"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.environ[\"NGROK_AUTH_TOKEN\"] = \"2clej493G1s6VnuKLG2o05CvOoa_Xco8eB85k5CjJDzhmHhx\"\n",
        "!ngrok authtoken 2clej493G1s6VnuKLG2o05CvOoa_Xco8eB85k5CjJDzhmHhx\n",
        "ngrok_tunnel = ngrok.connect(8000)\n",
        "print('Public URL:', ngrok_tunnel.public_url)\n",
        "nest_asyncio.apply()\n",
        "uvicorn.run(app, port=8000)"
      ],
      "metadata": {
        "id": "kEbQqxnNRhde"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **TERMINAL STOCKBOT**"
      ],
      "metadata": {
        "id": "FMhQ1GajpsaO"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "**setting terminal wrapper**"
      ],
      "metadata": {
        "id": "r1r4NrLOH2Tg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import HTML, display\n",
        "\n",
        "def set_css():\n",
        "  display(HTML('''\n",
        "  <style>\n",
        "    pre {\n",
        "        white-space: pre-wrap;\n",
        "    }\n",
        "\n",
        "  </style>\n",
        "  '''))\n",
        "get_ipython().events.register('pre_run_cell', set_css)"
      ],
      "metadata": {
        "id": "xZkRei7VEPk7"
      },
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def generate_answer(user_question):\n",
        "  relevant_docs = vstore.similarity_search(user_question, astra_db_application_token=\"AstraCS:caMHvgsIrkHpjTCAoyhRnsRK:945bdbb46d23f616e73a5a3675bcbfa6353152446500bec0e2ab1185119736f3\",search_kwargs={\"k\": 2})\n",
        "  chain = load_qa_chain(llm, chain_type=\"stuff\",memory=memory, prompt=prompt)\n",
        "  print(\"StockBot : \")\n",
        "  response = chain({\"input_documents\": relevant_docs, \"question\": user_question}, return_only_outputs=True)"
      ],
      "metadata": {
        "id": "IRhv-HwcxPoW",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17
        },
        "outputId": "990e1bf3-96e8-4023-c4ab-f19fc628440c"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "  <style>\n",
              "    pre {\n",
              "        white-space: pre-wrap;\n",
              "    }\n",
              "\n",
              "  </style>\n",
              "  "
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "def welcome_message():\n",
        "    print(\"\\n\")\n",
        "    print(\"-\" * 50)\n",
        "    print(\"\\n\")\n",
        "    print(\"Welcome to StockBot, your personal AI-powered investment assistant StockGro. We believe in making investments social, and StockBot is here to revolutionize the way you interact with financial information.\")\n",
        "    print(\"\\n\")\n",
        "    print(\"-\" * 50)\n",
        "    print(\"\\n\")\n",
        "\n",
        "\n",
        "def ask_question():\n",
        "    return input(\"USER: \").strip()\n",
        "\n",
        "def main():\n",
        "    welcome_message()\n",
        "    conversation_active = True\n",
        "    while conversation_active:\n",
        "        user_question = ask_question()\n",
        "        if user_question:\n",
        "            if user_question.lower() == \"end\":\n",
        "                conversation_active = False\n",
        "                print(\"\\n\")\n",
        "                print(\"-\" * 50)\n",
        "                print(\"\\n\")\n",
        "                print(\"Thank you for using StockBot. Goodbye!\")\n",
        "            else:\n",
        "                print(\"-\" * 50)\n",
        "                response = generate_answer(user_question)\n",
        "                print(\"-\" * 50)\n",
        "                print(\"\\n\")\n",
        "        else:\n",
        "            print(\"Please enter a question.\")\n",
        "\n",
        "if __name__ == \"__main__\":\n",
        "    main()\n"
      ],
      "metadata": {
        "id": "dTyyqimkw1qt",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 919
        },
        "outputId": "5064fa02-66c5-40cd-f6d2-c584d2cb4d6d"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "  <style>\n",
              "    pre {\n",
              "        white-space: pre-wrap;\n",
              "    }\n",
              "\n",
              "  </style>\n",
              "  "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "--------------------------------------------------\n",
            "\n",
            "\n",
            "Welcome to StockBot, your personal AI-powered investment assistant StockGro. We believe in making investments social, and StockBot is here to revolutionize the way you interact with financial information.\n",
            "\n",
            "\n",
            "--------------------------------------------------\n",
            "\n",
            "\n",
            "USER: If i am a beginner in investing, which stock is better to invest in Meta, tesla or Nvidia?\n",
            "--------------------------------------------------\n",
            "StockBot : \n",
            " Based on the information provided, it seems like you are interested in investing in stocks but are unsure which one to choose, especially between Meta, Tesla, and Nvidia. As a beginner, it's essential to understand the basics of investing and the companies you are considering investing in. Here's some general advice:\n",
            "1. Research and Understand the Companies: Before investing in any stock, research the company's financials, products, services, competition, market trends, and growth potential. Look for companies with strong fundamentals, a competitive advantage, and a proven track record of success.\n",
            "2. Diversify Your Portfolio: As a beginner, it's crucial to diversify your portfolio across various industries and sectors to minimize risk. By investing in different types of stocks, you can spread out your risk and potentially increase returns over the long term.\n",
            "3. Start Small: Consider starting small and gradually increasing your investment amount as you become more comfortable with the process. This approach can help you manage risk and avoid significant losses if things don't go as planned.\n",
            "4. Don't Chase Hot Stocks: Avoid chasing hot stocks or investing solely based on short-term performance. Instead, focus on long-term growth potential and stability. Look for companies with consistent revenue growth, solid balance sheets, and experienced management teams.\n",
            "5. Seek Professional Advice: If you're still unsure about which stocks to invest in, consider consulting a financial advisor or using robo-advisory services. These platforms can provide personalized recommendations based on your investment goals and risk tolerance.\n",
            "In conclusion, investing in stocks requires careful consideration and thorough research. Take your time to evaluate the companies you're interested in, diversify your portfolio, start small, avoid chasing hot stocks, and seek professional advice if needed. Good luck with your investment journey!\n",
            "--------------------------------------------------\n",
            "\n",
            "\n",
            "USER: what is StockGro?\n",
            "--------------------------------------------------\n",
            "StockBot : \n",
            " Sure, I'd be happy to help! Based on the information provided, here are some possible answers to your question:\n",
            "What is StockGro?\n",
            "StockGro is an online platform that allows users to learn about trading and investing through a simulated environment. It provides a unique blend of social networking, investment education, and trading opportunities in multiple asset classes. The platform offers a risk-free environment where users can practice trading and investing without any financial risk. Additionally, StockGro has a built-in community feature that enables users to connect with other investors, share ideas, and collaborate on investment strategies. Overall, StockGro aims to demystify the stock market and make it accessible to everyone through its innovative and engaging approach.\n",
            "I hope this helps! Let me know if you have any further questions.\n",
            "--------------------------------------------------\n",
            "\n",
            "\n",
            "USER: end\n",
            "\n",
            "\n",
            "--------------------------------------------------\n",
            "\n",
            "\n",
            "Thank you for using StockBot. Goodbye!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **SETTING UP STREAMING**"
      ],
      "metadata": {
        "id": "ZPHi7Ar5pZBF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **-----------------------------------------------------------------------------**"
      ],
      "metadata": {
        "id": "kHxx8qkVICK9"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rSfy6pNNjaGr",
        "outputId": "90840ea5-9738-4d8e-aae4-a4b3aa12ef8c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " I cannot determine which company is more profitable during 2023 between Meta, Nvidia, and Tesla based on the information provided. The passage only discusses Nvidia's financial condition and results of operations but does not provide any information about Meta or Tesla's financial performance during 2023. Additionally, it is important to note that profitability can be influenced by various factors such as market conditions, product offerings, competition, and economic conditions, among others. Therefore, without access to the financial statements of all three companies, it is not possible to accurately compare their profitability during 2023.\n"
          ]
        }
      ],
      "source": [
        "result = qa_chain( \"Which company is more profitable during 2023 Meta, Nvidia or Tesla and why?\" )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Nzc8I4TdBjma",
        "outputId": "afbc22d7-69eb-42c8-c299-d31685cf6ea1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " I cannot provide personalized investment advice, nor can I guarantee the safety of any particular stock. However, based on the information provided, NVIDIA Corporation might be a safer stock to consider for beginners compared to Tesla, Inc. (TSLA) and Meta Platforms, Inc. (META). Here's why:\n",
            "\n",
            "1. Revenue stability: NVIDIA has demonstrated a stable revenue stream over the years, primarily due to its strong presence in the GPU market and increasing demand for its AI and data center solutions. In contrast, Tesla's revenue is heavily dependent on the volatile automotive industry, while Meta's primary source of income is advertising, which can be affected by economic fluctuations.\n",
            "2. Profitability: NVIDIA has consistently reported net income and maintained profitability over the past few years, whereas Tesla and Meta have struggled with profitability, particularly in recent years.\n",
            "3. Cash reserves: NVIDIA has a significant cash reserve of $7.23 billion available for share repurchases until December 2023, indicating a strong financial position. In comparison, Tesla and Meta have lesser cash reserves relative to their market capitalization.\n",
            "4. Dividend payments: NVIDIA has a history of paying consistent quarterly cash dividends, providing a relatively safe source of return for investors. Tesla and Meta do not currently pay dividends.\n",
            "5. Industry trends: The technology sector, specifically the AI and data center industries, are expected to continue growing in the long term, which bodes well for NVIDIA's prospects. While both Tesla and Meta operate in promising sectors (electric vehicles and social media, respectively), their growth potential may be more uncertain than NVIDIA's.\n",
            "\n",
            "Please keep in mind that no stock is completely risk-free, and it's essential to conduct thorough research, consult with financial experts, and assess your own risk tolerance before making any investment decisions.\n"
          ]
        }
      ],
      "source": [
        "result = qa_chain( \"if i am a beginner in investing, what is the safest stock to buy, tesla, nvidia or meta and why?\" )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PTncogOro45u",
        "outputId": "01644213-5152-4641-8a77-4aa09c8a417e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            " Based on the provided financial statements for Tesla, Inc., here are some key statistics:\n",
            "\n",
            "| Category | Assets | Liabilities | Equity |\n",
            "| --- | --- | --- |\n",
            "| Total Current Assets | $43,875 million | $16,253 million | $90,591 million |\n",
            "| Operating Lease Vehicles, Net | $5,935 million | $5,035 million | $5,489 million |\n",
            "| Solar Energy Systems, Net | $5,365 million | $5,035 million | $5,489 million |\n",
            "| Property, Plant, and Equipment, Net | $26,389 million | $23,548 million | $21,548 million |\n",
            "| Intangible Assets, Net | $202 million | $184 million | $184 million |\n",
            "| Goodwill | $263 million | $263 million | $263 million |\n",
            "| Other Non-Current Assets | $5,026 million | $4,193 million | $4,193 million |\n",
            "| Total Liabilities | $16,253 million | $16,253 million | $16,253 million |\n",
            "| Stockholders' Equity | $90,591 million | $82,338 million | $82,338 million |\n",
            "\n",
            "These statistics provide information about Tesla's balance sheet as of June 30, 2023, including its total assets, liabilities, and equity. The company has significant investments in operating lease vehicles, solar energy systems, property, plant, and equipment, intangible assets, goodwill, and other non-current assets. Its liabilities primarily consist of accounts payable, accrued expenses, and operating lease obligations. Its stockholders' equity represents the residual interest in the company after deducting its liabilities.\n"
          ]
        }
      ],
      "source": [
        "result = qa_chain( \"Give me a table which shows stats for tesla\" )"
      ]
    }
  ],
  "metadata": {
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    "colab": {
      "gpuType": "V100",
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
    },
    "language_info": {
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}