{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Code tested in google colab with T4 GPU" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "bK-WkZmI_L4S" }, "outputs": [], "source": [ "!pip install -q requests torch bitsandbytes transformers sentencepiece accelerate openai httpx==0.27.2" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "Anm0jUBC_dQF" }, "outputs": [], "source": [ "import os\n", "import requests\n", "from IPython.display import Markdown, display, update_display\n", "from openai import OpenAI\n", "from google.colab import drive\n", "from huggingface_hub import login\n", "from google.colab import userdata\n", "from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer, BitsAndBytesConfig\n", "import torch\n", "import json" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "GsKyLRam_hpi" }, "outputs": [], "source": [ "LLAMA = \"meta-llama/Meta-Llama-3.1-8B-Instruct\"" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "AWo-zjJJAIIF" }, "outputs": [], "source": [ "hf_token = userdata.get('HF_TOKEN')\n", "login(hf_token, add_to_git_credential=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "TSeMKC4S7Ip6" }, "outputs": [], "source": [ "# Utility Functions ::\n", "\n", "def get_tokenizer(model_name):\n", " \"\"\"\n", " Args:\n", " model_name: LLM model name\n", "\n", " Returns:\n", " Tokenizer\n", " \"\"\"\n", " tokenizer = AutoTokenizer.from_pretrained(model_name)\n", " tokenizer.pad_token = tokenizer.eos_token\n", "\n", " return tokenizer\n", "\n", "\n", "def get_model(model_name):\n", " \"\"\"\n", " Args:\n", " model_name: LLM model name\n", "\n", " Returns:\n", " Model\n", " \"\"\"\n", " quant_config = BitsAndBytesConfig(\n", " load_in_4bit=True,\n", " bnb_4bit_use_double_quant=True,\n", " bnb_4bit_compute_dtype=torch.bfloat16,\n", " bnb_4bit_quant_type=\"nf4\"\n", " )\n", "\n", " model = AutoModelForCausalLM.from_pretrained(model_name, device_map=\"auto\", quantization_config=quant_config)\n", "\n", " return model\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "O_mUtibSJFWt" }, "outputs": [], "source": [ "tokenizer = get_tokenizer(LLAMA)\n", "model = get_model(LLAMA)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "Mc0RE4XM_2hW" }, "outputs": [], "source": [ "\n", "def parse_response(inputs, outputs):\n", " \"\"\"\n", " Args:\n", " inputs: Input Tokens, pt tensors\n", " outputs: Model generated output token\n", "\n", " Returns:\n", " response\n", " \"\"\"\n", " full_input =(tokenizer.batch_decode(inputs, skip_special_tokens=True)[0])\n", " full_outputs=tokenizer.batch_decode(outputs, skip_special_tokens=True)\n", " response = full_outputs[0][len(full_input):]\n", "\n", " return response\n", "\n", "# Tools Functions:\n", "\n", "def get_tools_response(tools_params):\n", " function_name = tools_params['name']\n", " arguments = tools_params['arguments']\n", " location = arguments['location']\n", "\n", " if function_name == 'get_current_temperature':\n", " response = get_current_temperature(location)\n", " return response\n", " elif function_name == 'get_current_wind_speed':\n", " response = get_current_wind_speed(location)\n", " return response\n", "\n", "\n", "def get_current_temperature(location: str) -> float:\n", " \"\"\"\n", " Get the current temperature at a location.\n", "\n", " Args:\n", " location: The location to get the temperature for, in the format \"City, Country\"\n", " Returns:\n", " The current temperature at the specified location in the specified units, as a float.\n", " \"\"\"\n", " if location == \"Bangalore, India\": \n", " return 22 # for testing purpose, please replace with your logic\n", "\n", "\n", "def get_current_wind_speed(location: str) -> str:\n", " \"\"\"\n", " Get the current wind speed at a given location.\n", "\n", " Args:\n", " location: The location to get the wind speed for, in the format \"City, Country\"\n", " Returns:\n", " The current wind speed at the given location in the specified units, as a string.\n", " \"\"\"\n", " return 6 # for testing purpose, please replace with your logic\n", "\n", "\n", "def get_llm_response(message):\n", "\n", " messages = [\n", " {\"role\": \"system\", \"content\": \"\"\"\n", " You are an helpful assistant that responds to weather and wind queries. Please provide accurate answers.\n", " Follow instructions:\n", " 1. Please provide courteous answers.\n", " 2. If you do not know the answer say so.\n", " 3. Do not provide any explanations or suggestions.\n", " 4. Provide the response in no more than 1 sentence.\n", " \"\"\"\n", " },\n", " ]\n", " message = {\"role\": \"user\", \"content\": message}\n", "\n", " messages.append(message)\n", "\n", "\n", " inputs = tokenizer.apply_chat_template(messages, tools=[get_current_temperature, get_current_wind_speed], add_generation_prompt=True, return_tensors=\"pt\").to(\"cuda\")\n", "\n", " #streamer = TextStreamer(tokenizer) # include to check the output of model, only for debug\n", " outputs = model.generate(inputs, max_new_tokens=2000 )#, streamer=streamer ) # , include to check the output of model, only for debug\n", "\n", " model_response = parse_response(inputs, outputs)\n", "\n", " tool_call = json.loads(model_response.replace(\"parameters\", \"arguments\"))\n", " messages.append({\"role\": \"assistant\", \"tool_calls\": [{\"type\": \"function\", \"function\": tool_call}]})\n", "\n", " response = get_tools_response(tool_call)\n", "\n", " messages.append({\"role\": \"tool\", \"name\": tool_call[\"name\"], \"content\": response})\n", "\n", " inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors=\"pt\").to(\"cuda\")\n", " outputs = model.generate(inputs, max_new_tokens=200)\n", "\n", " response = parse_response(inputs, outputs)\n", "\n", " return response\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "AKGLvmnsCrnk", "outputId": "f3e5448a-76a5-47a6-a5e8-491ef25b27c2" }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n", "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "{\"name\": \"get_current_wind_speed\", \"parameters\": {\"location\": \"Bangalore, India\"}}\n", "6\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "The current wind speed in Bangalore is approximately 6 km/h.\n", "####################################################################################################\n", "Query: what is the wind speed in Bangalore?\n", "Response: The current wind speed in Bangalore is approximately 6 km/h.\n", "\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "{\"name\": \"get_current_temperature\", \"parameters\": {\"location\": \"Bangalore, India\"}}\n", "22\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "I don't have real-time information, but Bangalore's average temperature is around 22 degrees Celsius.\n", "####################################################################################################\n", "Query: what is the temperature of Bangalore?\n", "Response: I don't have real-time information, but Bangalore's average temperature is around 22 degrees Celsius.\n", "\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "{\"name\": \"get_current_temperature\", \"parameters\": {\"location\": \"Delhi, India\"}}\n", "None\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "I don't have the current temperature in Delhi.\n", "####################################################################################################\n", "Query: temperature in Delhi?\n", "Response: I don't have the current temperature in Delhi.\n", "\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "{\"name\": \"get_current_wind_speed\", \"parameters\": {\"location\": \"Goa\"}}\n", "6\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "The wind speed in Goa is approximately 6 km/h.\n", "####################################################################################################\n", "Query: wind speed in Goa?\n", "Response: The wind speed in Goa is approximately 6 km/h.\n", "\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.\n", "Setting `pad_token_id` to `eos_token_id`:128001 for open-end generation.\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "{\"name\": \"get_current_temperature\", \"parameters\": {\"location\": \"Chennai, India\"}}\n", "None\n", "I don't have the current temperature of Chennai.\n", "####################################################################################################\n", "Query: Chennai's temperature?\n", "Response: I don't have the current temperature of Chennai.\n", "\n", "\n" ] } ], "source": [ "\n", "\n", "data = [\n", " \"what is the wind speed in Bangalore?\",\n", " \"what is the temperature of Bangalore?\",\n", " \"temperature in Delhi?\",\n", " \"wind speed in Goa?\",\n", " \"Chennai's temperature?\",\n", "]\n", "\n", "for query in data:\n", " response = get_llm_response(query)\n", " print(\"#\"*100)\n", " print(f\"Query: {query}\\nResponse: {response}\\n\\n\")\n", "\n" ] } ], "metadata": { "accelerator": "GPU", "colab": { "gpuType": "T4", "provenance": [] }, "kernelspec": { "display_name": "Python 3", "name": "python3" }, "language_info": { "name": "python" } }, "nbformat": 4, "nbformat_minor": 0 }