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        "outputId": "7aa0e836-a9fb-41d9-b2a3-4b0e78ec600e"
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      "source": [
        "# !pip install -q ctransformers langchain"
      ]
    },
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      "execution_count": 2,
      "metadata": {
        "id": "5jMCN_Whrp3h"
      },
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      "source": [
        "from langchain.llms import CTransformers\n",
        "from langchain import PromptTemplate, LLMChain\n",
        "from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler"
      ]
    },
    {
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              "Fetching 1 files:   0%|          | 0/1 [00:00<?, ?it/s]"
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      "source": [
        "llm = CTransformers(model=\"TheBloke/Llama-2-7B-Chat-GGML\", model_file = 'llama-2-7b-chat.ggmlv3.q2_K.bin', callbacks=[StreamingStdOutCallbackHandler()])"
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      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "ixcszGAPrrVN"
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      "source": [
        "template = \"\"\"\n",
        "[INST] <<SYS>>\n",
        "You are a helpful developed by Mohammed Vasim, respectful and honest assistant. Your answers are always brief.\n",
        "<</SYS>>\n",
        "{text}[/INST]\n",
        "\"\"\"\n",
        "\n",
        "prompt = PromptTemplate(template=template, input_variables=[\"text\"])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "5Up06ctlr21v"
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      "source": [
        "llm_chain = LLMChain(prompt=prompt, llm=llm)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
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        "id": "kwrWVBtXrZs1",
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          "name": "stdout",
          "output_type": "stream",
          "text": [
            "*blinks* My apologies, I'm just an AI and do not have access to personal information such as your name. However, it is nice to meet you! *smiling*"
          ]
        }
      ],
      "source": [
        "response = llm_chain.run(\"What is my name\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [],
      "source": [
        "def answer_query(message, history):\n",
        "    message = llm_chain.run(message)\n",
        "    return message"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "Mfx-saC3rz0r"
      },
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      "source": [
        "import gradio as gr "
      ]
    },
    {
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      "execution_count": 15,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Running on local URL:  http://127.0.0.1:7860\n",
            "\n",
            "To create a public link, set `share=True` in `launch()`.\n"
          ]
        },
        {
          "data": {
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              "<div><iframe src=\"http://127.0.0.1:7860/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
            ],
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          },
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        },
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          "text": [
            "Hello! *giggles* How can I help you today?Mohammed Vasim developed me.Mohammed Vasim is a highly skilled software developer who created me, his trustworthy and polite digital assistant."
          ]
        }
      ],
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        "llamabot = gr.ChatInterface(answer_query).queue().launch()"
      ]
    },
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