From bbe18d0f74d0a48abda9a9a404494d44db09b55b Mon Sep 17 00:00:00 2001 From: "Dhruv Dhayal." <137479629+BlockNotes-4515@users.noreply.github.com> Date: Fri, 26 Jul 2024 18:35:32 +0530 Subject: [PATCH] =?UTF-8?q?Day-14=5FSUMMER=5FTRAINING=5FAI/ML=20?= =?UTF-8?q?=F0=9F=98=89?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit -Implementing the Working of the ChatBot. (Implementing the Random and re) Methods. --- .../Day_14_DHRUVDHAYAL_AI_ML.ipynb | 5923 +++++++++++++++++ .../day_14_dhruvdhayal_ai_ml.py | 590 ++ 2 files changed, 6513 insertions(+) create mode 100644 Day-14_SUMMER_TRAINING_AIML/Day_14_DHRUVDHAYAL_AI_ML.ipynb create mode 100644 Day-14_SUMMER_TRAINING_AIML/day_14_dhruvdhayal_ai_ml.py diff --git a/Day-14_SUMMER_TRAINING_AIML/Day_14_DHRUVDHAYAL_AI_ML.ipynb b/Day-14_SUMMER_TRAINING_AIML/Day_14_DHRUVDHAYAL_AI_ML.ipynb new file mode 100644 index 0000000..9ec6c80 --- /dev/null +++ b/Day-14_SUMMER_TRAINING_AIML/Day_14_DHRUVDHAYAL_AI_ML.ipynb @@ -0,0 +1,5923 @@ +{ + "nbformat": 4, + "nbformat_minor": 0, + "metadata": { + "colab": { + "provenance": [] + }, + "kernelspec": { + "name": "python3", + "display_name": "Python 3" + }, + "language_info": { + "name": "python" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "652374cb339740bd83cd2dc0872d203b": { + "model_module": "@jupyter-widgets/controls", + "model_name": 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"#Implementing the RealWorld ChatBot" + ], + "metadata": { + "id": "kt4LrdbREmKM" + } + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "6nyHom-tEALx", + "outputId": "3d7dd54e-5ae6-4f27-a391-2069a52503a6" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Collecting humingbird\n", + " Downloading humingbird-0.5.1-py3-none-any.whl.metadata (3.7 kB)\n", + "Requirement already satisfied: Pillow>=7.1 in /usr/local/lib/python3.10/dist-packages (from humingbird) (9.4.0)\n", + "Requirement already satisfied: transformers>=4.19.2 in /usr/local/lib/python3.10/dist-packages (from humingbird) (4.42.4)\n", + "Requirement already satisfied: torch>=1.11.0 in /usr/local/lib/python3.10/dist-packages (from humingbird) (2.3.1+cu121)\n", + "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->humingbird) (3.15.4)\n", + "Requirement 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nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.11.0->humingbird)\n", + " Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n", + "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.11.0->humingbird)\n", + " Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl.metadata (1.6 kB)\n", + "Collecting nvidia-nccl-cu12==2.20.5 (from torch>=1.11.0->humingbird)\n", + " Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl.metadata (1.8 kB)\n", + "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.11.0->humingbird)\n", + " Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl.metadata (1.7 kB)\n", + "Requirement already satisfied: triton==2.3.1 in /usr/local/lib/python3.10/dist-packages (from torch>=1.11.0->humingbird) (2.3.1)\n", + "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.11.0->humingbird)\n", + " Downloading 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nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n", + "Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n", + "Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n", + "Using cached nvidia_nccl_cu12-2.20.5-py3-none-manylinux2014_x86_64.whl (176.2 MB)\n", + "Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n", + "Downloading nvidia_nvjitlink_cu12-12.5.82-py3-none-manylinux2014_x86_64.whl (21.3 MB)\n", + "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m21.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", + "\u001b[?25hInstalling collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, humingbird\n", + "Successfully installed humingbird-0.5.1 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.20.5 nvidia-nvjitlink-cu12-12.5.82 nvidia-nvtx-cu12-12.1.105\n" + ] + } + ], + "source": [ + "#Install the HummingBird.\n", + "!pip install humingbird;" + ] + }, + { + "cell_type": "code", + "source": [ + "import humingbird; #This Import should now work." + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 557, + "referenced_widgets": [ + "652374cb339740bd83cd2dc0872d203b", + "913417270af344fcb93426dd02b8ce56", + "9bc8d5df50b14ed1a71241aa135f8ded", + "c72f8f069c9c40328964c23adf999a5e", + "3a2f2f8e3c9641cc8b31678c50d15f68", + "227563f19f4b45ffaa2996e1568a1ef6", + "211e67ba4b2c4fd8b4991d346b8670bc", + 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"5700c08f935a491fba2fcd05d7aa7f17", + "7fa44870d51b42a9adfd4ca0db559e01", + "28b2a3c7fc1b446385abea2c3133a88d", + "d74c8f0cb43147169575e536c378cf2b", + "34a60f54e31f47e38c1bf47c62aa5a35", + "b6f4df1732044572897882212df51f34" + ] + }, + "id": "E3TsrWGbE1p-", + "outputId": "ffc5c1a2-8482-4ce8-a042-b54f367a943a" + }, + "execution_count": 12, + "outputs": [ + { + "output_type": "stream", + "name": "stderr", + "text": [ + "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n", + "The secret `HF_TOKEN` does not exist in your Colab secrets.\n", + "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", + "You will be able to reuse this secret in all of your notebooks.\n", + "Please note that authentication is recommended but still optional to access public models or datasets.\n", + " warnings.warn(\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "config.json: 0%| | 0.00/4.10k [00:00max_score):\n", + " max_score=val['score']\n", + " max_val = val['score']\n", + " max_val_text = val['className']\n", + "\n", + "print(max_val,max_val_text)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "UxNRcWQeN2kF", + "outputId": "1fe436a1-11f3-41d7-e070-188508c857a6" + }, + "execution_count": 34, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "0.54 scary\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import random;\n", + "intents = {\n", + " \"greeting\":[\"Hi! how are you?\",\"Hello what's up\"],\n", + " \"goodbye\":[\"Great day ahead\",\"Nice to see you\"],\n", + " \"address\":[\"Address of the college is Near Tihar Jail Janakpuri\"],\n", + " \"courses\":[\"IITM college offers 5 graduation courses and 2 postgraduation courses\"],\n", + " \"Graduation\":[\"graduation courses are : BCA, BBA , BCOM, Btech,BJMC\"],\n", + " \"Postgraduation\":[\"Post grad courses are: MBA, MCA\"]\n", + "}\n", + "def detect_response(query):\n", + " prediction = humingbird.Text.predict(\n", + " text = query, # inferencing text\n", + " labels=[\"greeting\",\"goodbye\",\n", + " \"address\",\"courses\",\n", + " \"Graduation\",\"Postgraduation\"] # suply potential labels\n", + " )\n", + " max_score=0\n", + " for val in prediction:\n", + " if(val['score']>max_score):\n", + " max_score=val['score']\n", + " max_val = val['score']\n", + " max_val_text = val['className']\n", + " print(max_val_text)\n", + " return random.choice(intents[max_val_text])" + ], + "metadata": { + "id": "Oq6HvVBgH9Lk" + }, + "execution_count": 49, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "detect_response(\"address of the IITM\");" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "HU3vS5W6Jt3T", + "outputId": "faae9645-7876-45ff-d276-3ae2b098727e" + }, + "execution_count": 50, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "address\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "intents = {\n", + " \"greeting\":[\"Hi! how are you?\",\"Hello what's up\"],\n", + " \"goodbye\":[\"Great day ahead\",\"Nice to see you\"],\n", + " \"address\":[\"Address of the college is Near Tihar Jail Janakpuri\"],\n", + " \"courses\":[\"IITM college offers 5 graduation courses and 2 postgraduation courses\"],\n", + " \"Graduation\":[\"graduation courses are : BCA, BBA , BCOM, Btech,BJMC\"],\n", + " \"Postgraduation\":[\"Post grad courses are: MBA, MCA\"]\n", + "}" + ], + "metadata": { + "id": "Egu2iXW3Omkp" + }, + "execution_count": 51, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "def detect_response(query):\n", + " prediction = humingbird.Text.predict(\n", + " text = query, # inferencing text\n", + " labels=[\"greeting\",\"goodbye\",\n", + " \"address\",\"courses\",\n", + " \"Graduation\",\"Postgraduation\"] # suply potential labels\n", + " )\n", + " max_score=0\n", + " for val in prediction:\n", + " if(val['score']>max_score):\n", + " max_score=val['score']\n", + " max_val = val['score']\n", + " max_val_text = val['className']\n", + " print(max_val_text)\n", + " return random.choice(intents[max_val_text])" + ], + "metadata": { + "id": "4fjnEZrePJtb" + }, + "execution_count": 52, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "detect_response(\"can u tell me the number of graduation in IITM\")\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 53 + }, + "id": "Fel9WScvPLdT", + "outputId": "ff05de47-3fef-4803-fa89-903044622130" + }, + "execution_count": 55, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Graduation\n" + ] + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "'graduation courses are : BCA, BBA , BCOM, Btech,BJMC'" + ], + "application/vnd.google.colaboratory.intrinsic+json": { + "type": "string" + } + }, + "metadata": {}, + "execution_count": 55 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "#Implementing on the DMRC APP (Delhi Metro)/." + ], + "metadata": { + "id": "d7KpKjs0Pnt7" + } + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "\n", + "# Define intents and their responses\n", + "intents = {\n", + " \"greeting\": [\"Hi! How can I assist you with Delhi Metro today?\", \"Hello! What information do you need about the Delhi Metro?\"],\n", + " \"goodbye\": [\"Have a great day! If you need more information, feel free to ask.\", \"Nice talking to you! Safe travels!\"],\n", + " \"address\": [\"The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi.\"],\n", + " \"routes\": [\"Delhi Metro covers a wide range of routes. For specific route details, you can visit the DMRC website or use the DMRC app.\"],\n", + " \"fares\": [\"Fare details can be found on the DMRC website or at the metro stations. Fares vary based on the distance traveled and the type of card used.\"],\n", + " \"timings\": [\"Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week.\"],\n", + " \"facilities\": [\"Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets.\"],\n", + " \"contact\": [\"For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website.\"],\n", + "}\n", + "\n", + "def detect_response(query):\n", + " # Predict the intent (this is a placeholder, replace with actual model prediction)\n", + " prediction = humingbird.Text.predict(\n", + " text=query, # inferencing text\n", + " labels=[\"greeting\", \"goodbye\", \"address\", \"routes\", \"fares\", \"timings\", \"facilities\", \"contact\"] # potential labels\n", + " )\n", + "\n", + " max_score = 0\n", + " max_val_text = None\n", + "\n", + " for val in prediction:\n", + " if val['score'] > max_score:\n", + " max_score = val['score']\n", + " max_val_text = val['className']\n", + "\n", + " if max_val_text:\n", + " print(max_val_text)\n", + " return random.choice(intents[max_val_text])\n", + " else:\n", + " return \"Sorry, I didn't understand that. Can you please provide more details?\"\n", + "\n", + "# Example usage\n", + "print(detect_response(\"What are the timings for the Delhi Metro?\"))\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ikNaeqXuQWaz", + "outputId": "a4567ec3-8cbb-41ea-b2e6-98b3e29e833f" + }, + "execution_count": 56, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "timings\n", + "Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week.\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "\n", + "# Define intents and their responses with routes and fares\n", + "intents = {\n", + " \"greeting\": [\"Hi! How can I assist you with Delhi Metro today?\", \"Hello! What information do you need about the Delhi Metro?\"],\n", + " \"goodbye\": [\"Have a great day! If you need more information, feel free to ask.\", \"Nice talking to you! Safe travels!\"],\n", + " \"address\": [\"The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi.\"],\n", + " \"routes\": [\"Delhi Metro covers a wide range of routes. For specific route details, you can visit the DMRC website or use the DMRC app.\"],\n", + " \"fares\": [\n", + " \"The fare structure is as follows:\\n\" +\n", + " \"1. For distances up to 2 km: ₹10\\n\" +\n", + " \"2. For distances between 2 km and 5 km: ₹15\\n\" +\n", + " \"3. For distances between 5 km and 12 km: ₹20\\n\" +\n", + " \"4. For distances between 12 km and 21 km: ₹30\\n\" +\n", + " \"5. For distances above 21 km: ₹40\\n\" +\n", + " \"Note: Fares may vary for different lines and depending on the type of card used.\"\n", + " ],\n", + " \"timings\": [\"Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week.\"],\n", + " \"facilities\": [\"Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets.\"],\n", + " \"contact\": [\"For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website.\"],\n", + " \"route_fare\": [\n", + " \"Here is a basic fare structure based on distance:\\n\" +\n", + " \"1. Up to 2 km: ₹10\\n\" +\n", + " \"2. 2 to 5 km: ₹15\\n\" +\n", + " \"3. 5 to 12 km: ₹20\\n\" +\n", + " \"4. 12 to 21 km: ₹30\\n\" +\n", + " \"5. Above 21 km: ₹40\\n\" +\n", + " \"For detailed route information, please provide the specific stations or route you're interested in.\"\n", + " ],\n", + "}\n", + "\n", + "def detect_response(query):\n", + " # Predict the intent (this is a placeholder, replace with actual model prediction)\n", + " prediction = humingbird.Text.predict(\n", + " text=query, # inferencing text\n", + " labels=[\"greeting\", \"goodbye\", \"address\", \"routes\", \"fares\", \"timings\", \"facilities\", \"contact\", \"route_fare\"] # potential labels\n", + " )\n", + "\n", + " max_score = 0\n", + " max_val_text = None\n", + "\n", + " for val in prediction:\n", + " if val['score'] > max_score:\n", + " max_score = val['score']\n", + " max_val_text = val['className']\n", + "\n", + " if max_val_text:\n", + " if max_val_text == \"route_fare\":\n", + " return intents[\"route_fare\"][0]\n", + " return random.choice(intents[max_val_text])\n", + " else:\n", + " return \"Sorry, I didn't understand that. Can you please provide more details?\"\n", + "\n", + "# Example usage\n", + "print(detect_response(\"What is the fare for a trip between 5 km and 12 km?\"))\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ag_8v_bSQXAz", + "outputId": "e17b1e9f-1766-4e6b-b90d-9f52dc82bf0d" + }, + "execution_count": 57, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "The fare structure is as follows:\n", + "1. For distances up to 2 km: ₹10\n", + "2. For distances between 2 km and 5 km: ₹15\n", + "3. For distances between 5 km and 12 km: ₹20\n", + "4. For distances between 12 km and 21 km: ₹30\n", + "5. For distances above 21 km: ₹40\n", + "Note: Fares may vary for different lines and depending on the type of card used.\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "\n", + "# Define routes with fare information\n", + "routes_and_fares = {\n", + " \"cost\":[\n", + " \"dwarka_sector_21_to_dwarka_shahdara ₹10\"+\n", + " \"dwarka_sector_21_to_rahaund ₹40\"+\n", + " \"dwarka_sector_21_to_kashmere_gate 30\"+\n", + " \"kashmere_gate_to_central_secretariat ₹20\"+\n", + " \"central_secretariat_to_new_delhi ₹15\"+\n", + " \"new_delhi_to_rajiv_chowk ₹10\"]\n", + " # Add more routes as needed\n", + "}\n", + "\n", + "# Define intents and their responses\n", + "intents = {\n", + " \"greeting\": [\"Hi! How can I assist you with Delhi Metro today?\", \"Hello! What information do you need about the Delhi Metro?\"],\n", + " \"goodbye\": [\"Have a great day! If you need more information, feel free to ask.\", \"Nice talking to you! Safe travels!\"],\n", + " \"address\": [\"The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi.\"],\n", + " \"routes\": [\"Delhi Metro covers a wide range of routes. For specific route details, you can visit the DMRC website or use the DMRC app.\"],\n", + " \"fares\": [\n", + " \"The fare structure is as follows:\\n\" +\n", + " \"1. For distances up to 2 km: ₹10\\n\" +\n", + " \"2. For distances between 2 km and 5 km: ₹15\\n\" +\n", + " \"3. For distances between 5 km and 12 km: ₹20\\n\" +\n", + " \"4. For distances between 12 km and 21 km: ₹30\\n\" +\n", + " \"5. For distances above 21 km: ₹40\\n\" +\n", + " \"Note: Fares may vary for different lines and depending on the type of card used.\"\n", + " ],\n", + " \"timings\": [\"Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week.\"],\n", + " \"facilities\": [\"Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets.\"],\n", + " \"contact\": [\"For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website.\"],\n", + " \"route_fare\": [\n", + " \"To find the fare for a specific route, please provide the start and end stations. For example, 'Dwarka Sector 21 to Kashmere Gate'.\"\n", + " ],\n", + " \"fare_by_route\": \"For the route from {start} to {end}, the fare is {fare}.\",\n", + " \"rules\": [\n", + " \"Here are some common rules for traveling on the Delhi Metro:\\n\" +\n", + " \"1. Keep your ticket or token with you at all times.\\n\" +\n", + " \"2. Maintain silence in the metro coaches.\\n\" +\n", + " \"3. Do not eat or drink inside the coaches.\\n\" +\n", + " \"4. Avoid leaning out of the doors or windows.\\n\" +\n", + " \"5. Follow the instructions of the metro staff and use designated entry/exit points.\"\n", + " ],\n", + " \"fines\": [\n", + " \"Fines for various violations on the Delhi Metro are as follows:\\n\" +\n", + " \"1. Traveling without a valid ticket: ₹500\\n\" +\n", + " \"2. Eating or drinking inside the metro: ₹200\\n\" +\n", + " \"3. Misbehavior or creating nuisance: ₹1000\\n\" +\n", + " \"4. Damaging metro property: Variable fines based on damage.\\n\" +\n", + " \"5. Unauthorized use of reserved seating: ₹300\"\n", + " ]\n", + "}\n", + "\n", + "def detect_response(query):\n", + " # Predict the intent (this is a placeholder, replace with actual model prediction)\n", + " prediction = humingbird.Text.predict(\n", + " text=query, # inferencing text\n", + " labels=[\"greeting\", \"goodbye\", \"address\", \"routes\", \"fares\", \"timings\", \"facilities\", \"contact\", \"route_fare\", \"rules\", \"fines\"] # potential labels\n", + " )\n", + "\n", + " max_score = 0\n", + " max_val_text = None\n", + "\n", + " for val in prediction:\n", + " if val['score'] > max_score:\n", + " max_score = val['score']\n", + " max_val_text = val['className']\n", + "\n", + " if max_val_text:\n", + " if max_val_text == \"route_fare\":\n", + " return intents[\"route_fare\"][0]\n", + " elif max_val_text == \"fare_by_route\":\n", + " # Extract the start and end stations from the query\n", + " for route, fare in routes_and_fares.items():\n", + " if route in query.lower():\n", + " start, end = route.split(\"_to_\")\n", + " return intents[\"fare_by_route\"].format(start=start.replace(\"_\", \" \").title(), end=end.replace(\"_\", \" \").title(), fare=fare)\n", + " return \"Sorry, I couldn't find the fare for that route. Please check the route name and try again.\"\n", + " elif max_val_text == \"rules\":\n", + " return intents[\"rules\"][0]\n", + " elif max_val_text == \"fines\":\n", + " return intents[\"fines\"][0]\n", + "\n", + " return random.choice(intents[max_val_text])\n", + " else:\n", + " return \"Sorry, I didn't understand that. Can you please provide more details?\"\n", + "\n", + "# Example usage\n", + "print(detect_response(\"\\n For the route from {dwarka} to {rahaund}, the fare is {fare}\"));" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "hD_MokvAQwHT", + "outputId": "168bc6de-2179-4f88-aa02-f2c6d5fc0efb" + }, + "execution_count": 88, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "The fare structure is as follows:\n", + "1. For distances up to 2 km: ₹10\n", + "2. For distances between 2 km and 5 km: ₹15\n", + "3. For distances between 5 km and 12 km: ₹20\n", + "4. For distances between 12 km and 21 km: ₹30\n", + "5. For distances above 21 km: ₹40\n", + "Note: Fares may vary for different lines and depending on the type of card used.\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "\n", + "import re # To use regular expressions for extracting routes\n", + "\n", + "\n", + "\n", + "# Sample routes and fares\n", + "\n", + "routes_and_fares = {\n", + "\n", + " \"dwarka_sector_21_to_rahaund\": \"₹40\",\n", + "\n", + " \"dwarka_sector_21_to_kashmere_gate\": \"₹30\",\n", + "\n", + " \"kashmere_gate_to_central_secretariat\": \"₹20\",\n", + "\n", + " \"central_secretariat_to_new_delhi\": \"₹15\",\n", + "\n", + " \"new_delhi_to_rajiv_chowk\": \"₹10\",\n", + "\n", + " # Add more routes as needed\n", + "\n", + "}\n", + "\n", + "\n", + "\n", + "# Define intents and their responses\n", + "\n", + "intents = {\n", + "\n", + " \"greeting\": [\"Hi! How can I assist you with Delhi Metro today?\", \"Hello! What information do you need about the Delhi Metro?\"],\n", + "\n", + " \"goodbye\": [\"Have a great day! If you need more information, feel free to ask.\", \"Nice talking to you! Safe travels!\"],\n", + "\n", + " \"address\": [\"The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi.\"],\n", + "\n", + " \"routes\": [\"Delhi Metro has several key lines connecting different parts of the city. Here’s a brief overview of the main routes:\\n\"\n", + "\n", + " \"\\n1. **Red Line (Line 1)**: \"\n", + "\n", + " \"Dwarka Sector 21 to Kashmere Gate.\\n\"\n", + "\n", + " \"Major stations: Dwarka Sector 21, Dwarka Sector 13, Dwarka Sector 12, Janakpuri West, R K Ashram, Rajiv Chowk, Kashmere Gate.\\n\"\n", + "\n", + " \"\\n2. **Blue Line (Line 3 & 4)**: \"\n", + "\n", + " \"Dwarka Sector 21 to Noida City Centre/Vaishali.\\n\"\n", + "\n", + " \"Major stations: Dwarka Sector 21, Sector 21, Indira Gandhi International Airport, Dwarka Sector 8, Rajouri Garden, Kirti Nagar, Mandi House, Noida City Centre.\\n\"\n", + "\n", + " \"\\n3. **Yellow Line (Line 2)**: \"\n", + "\n", + " \"Samaypur Badli to HUDA City Centre.\\n\"\n", + "\n", + " \"Major stations: Samaypur Badli, Jahangirpuri, Kashmere Gate, Chawri Bazar, Rajiv Chowk, Gurgaon, HUDA City Centre.\\n\"\n", + "\n", + " \"\\n4. **Green Line (Line 5)**: \"\n", + "\n", + " \"Inderlok to Brigadier Hoshier Singh.\\n\"\n", + "\n", + " \"Major stations: Inderlok, Kirti Nagar, Mandi House, Dwarka Sector 21.\\n\"\n", + "\n", + " \"\\n5. **Violet Line (Line 6)**: \"\n", + "\n", + " \"Kashmere Gate to Raja Nahar Singh.\\n\"\n", + "\n", + " \"Major stations: Kashmere Gate, Civil Lines, Vishwa Vidyalaya, Delhi University, Sukhdev Vihar, Badarpur.\\n\"\n", + "\n", + " \"\\n6. **Pink Line (Line 7 & 9)**: \"\n", + "\n", + " \"Majlis Park to Shiv Vihar.\\n\"\n", + "\n", + " \"Major stations: Majlis Park, Azadpur, Mukherjee Nagar, Pitampura, Rithala, Lajpat Nagar, Shiv Vihar.\\n\"\n", + "\n", + " \"\\n7. **Aqua Line (Noida Greater Noida Line)**: \"\n", + "\n", + " \"Noida City Centre to Depot.\\n\"\n", + "\n", + " \"Major stations: Noida City Centre, Sector 18, Greater Noida, Depot.\\n\"\n", + "\n", + " \"\\nFor more details, you can visit the DMRC website or use the DMRC app for the latest route maps and station details.\"\n", + "\n", + " ],\n", + "\n", + " \"fares\": [\n", + "\n", + " \"The fare structure is as follows:\\n\" +\n", + "\n", + " \"\\n\".join([f\"{route.replace('_to_', ' to ').replace('_', ' ').title()}: {fare}\" for route, fare in routes_and_fares.items()]) +\n", + "\n", + " \"\\nNote: Fares may vary for different lines and depending on the type of card used.\"\n", + "\n", + " ],\n", + "\n", + " \"timings\": [\"Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week.\"],\n", + "\n", + " \"facilities\": [\"Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets.\"],\n", + "\n", + " \"contact\": [\"For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website.\"],\n", + "\n", + " \"route_fare\": [\"To find the fare for a specific route, please provide the start and end stations. For example, 'Dwarka Sector 21 to Kashmere Gate'.\"],\n", + "\n", + " \"fare_by_route\": \"For the route from {start} to {end}, the fare is {fare}.\"\n", + "\n", + "}\n", + "\n", + "\n", + "\n", + "def detect_response(query):\n", + "\n", + " # Predict the intent (this is a placeholder, replace with actual model prediction)\n", + "\n", + " prediction = humingbird.Text.predict(\n", + "\n", + " text=query, # inferencing text\n", + "\n", + " labels=[\"greeting\", \"goodbye\", \"address\", \"routes\", \"fares\", \"timings\", \"facilities\", \"contact\", \"route_fare\", \"fare_by_route\"] # potential labels\n", + "\n", + " )\n", + "\n", + "\n", + "\n", + " max_score = 0\n", + "\n", + " max_val_text = None\n", + "\n", + "\n", + "\n", + " for val in prediction:\n", + "\n", + " if val['score'] > max_score:\n", + "\n", + " max_score = val['score']\n", + "\n", + " max_val_text = val['className']\n", + "\n", + "\n", + "\n", + " if max_val_text:\n", + "\n", + " if max_val_text == \"route_fare\":\n", + "\n", + " return intents[\"route_fare\"][0]\n", + "\n", + " elif max_val_text == \"fare_by_route\":\n", + "\n", + " # Extract the start and end stations from the query\n", + "\n", + " match = re.search(r'fare from (\\w+ \\w+) to (\\w+ \\w+)', query.lower())\n", + "\n", + " if match:\n", + "\n", + " start = match.group(1).replace(' ', '_').lower()\n", + "\n", + " end = match.group(2).replace(' ', '_').lower()\n", + "\n", + " route_key = f\"{start}_to_{end}\"\n", + "\n", + " fare = routes_and_fares.get(route_key)\n", + "\n", + " if fare:\n", + "\n", + " return intents[\"fare_by_route\"].format(start=start.replace('_', ' ').title(), end=end.replace('_', ' ').title(), fare=fare)\n", + "\n", + " else:\n", + "\n", + " return \"Sorry, I couldn't find the fare for that route. Please check the route name and try again.\"\n", + "\n", + "\n", + "\n", + " return random.choice(intents[max_val_text])\n", + "\n", + "\n", + "\n", + " else:\n", + "\n", + " return \"Sorry, I didn't understand that. Can you please provide more details?\"\n", + "\n", + "\n", + "\n", + "# Example usage\n", + "\n", + "print(detect_response(\"What is the fare from Dwarka Sector 21 to Kashmere Gate?\"))\n", + "\n", + "print(detect_response(\"\\n \"))\n", + "\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "gI7nYklwWlTw", + "outputId": "d2b8fa54-06dd-4390-c2ce-b1a0faa87b8b" + }, + "execution_count": 90, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "The fare structure is as follows:\n", + "Dwarka Sector 21 To Rahaund: ₹40\n", + "Dwarka Sector 21 To Kashmere Gate: ₹30\n", + "Kashmere Gate To Central Secretariat: ₹20\n", + "Central Secretariat To New Delhi: ₹15\n", + "New Delhi To Rajiv Chowk: ₹10\n", + "Note: Fares may vary for different lines and depending on the type of card used.\n", + "Hello! What information do you need about the Delhi Metro?\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "import random\n", + "import re; # To use regular expressions for extracting routes\n", + "\n", + "# Sample routes and fares\n", + "routes_and_fares = {\n", + " \"dwarka_sector_21_to_rahaund\": \"₹40\",\n", + " \"dwarka_sector_21_to_kashmere_gate\": \"₹30\",\n", + " \"kashmere_gate_to_central_secretariat\": \"₹20\",\n", + " \"central_secretariat_to_new_delhi\": \"₹15\",\n", + " \"new_delhi_to_rajiv_chowk\": \"₹10\",\n", + " # Add more routes as needed\n", + "}\n", + "\n", + "# Define intents and their responses\n", + "intents = {\n", + " \"greeting\": [\"Hi! How can I assist you with Delhi Metro today?\", \"Hello! What information do you need about the Delhi Metro?\"],\n", + " \"goodbye\": [\"Have a great day! If you need more information, feel free to ask.\", \"Nice talking to you! Safe travels!\"],\n", + " \"address\": [\"The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi.\"],\n", + " \"routes\": [\"Delhi Metro has several key lines connecting different parts of the city. Here’s a brief overview of the main routes:\\n\"\n", + " \"\\n1. **Red Line (Line 1)**: Dwarka Sector 21 to Kashmere Gate.\\n\"\n", + " \"Major stations: Dwarka Sector 21, Dwarka Sector 13, Dwarka Sector 12, Janakpuri West, R K Ashram, Rajiv Chowk, Kashmere Gate.\\n\"\n", + " \"\\n2. **Blue Line (Line 3 & 4)**: Dwarka Sector 21 to Noida City Centre/Vaishali.\\n\"\n", + " \"Major stations: Dwarka Sector 21, Sector 21, Indira Gandhi International Airport, Dwarka Sector 8, Rajouri Garden, Kirti Nagar, Mandi House, Noida City Centre.\\n\"\n", + " \"\\n3. **Yellow Line (Line 2)**: Samaypur Badli to HUDA City Centre.\\n\"\n", + " \"Major stations: Samaypur Badli, Jahangirpuri, Kashmere Gate, Chawri Bazar, Rajiv Chowk, Gurgaon, HUDA City Centre.\\n\"\n", + " \"\\n4. **Green Line (Line 5)**: Inderlok to Brigadier Hoshier Singh.\\n\"\n", + " \"Major stations: Inderlok, Kirti Nagar, Mandi House, Dwarka Sector 21.\\n\"\n", + " \"\\n5. **Violet Line (Line 6)**: Kashmere Gate to Raja Nahar Singh.\\n\"\n", + " \"Major stations: Kashmere Gate, Civil Lines, Vishwa Vidyalaya, Delhi University, Sukhdev Vihar, Badarpur.\\n\"\n", + " \"\\n6. **Pink Line (Line 7 & 9)**: Majlis Park to Shiv Vihar.\\n\"\n", + " \"Major stations: Majlis Park, Azadpur, Mukherjee Nagar, Pitampura, Rithala, Lajpat Nagar, Shiv Vihar.\\n\"\n", + " \"\\n7. **Aqua Line (Noida Greater Noida Line)**: Noida City Centre to Depot.\\n\"\n", + " \"Major stations: Noida City Centre, Sector 18, Greater Noida, Depot.\\n\"\n", + " \"\\nFor more details, you can visit the DMRC website or use the DMRC app for the latest route maps and station details.\"\n", + " ],\n", + " \"fares\": [\n", + " \"The fare structure is as follows:\\n\" +\n", + " \"\\n\".join([f\"{route.replace('_to_', ' to ').replace('_', ' ').title()}: {fare}\" for route, fare in routes_and_fares.items()]) +\n", + " \"\\nNote: Fares may vary for different lines and depending on the type of card used.\"\n", + " ],\n", + " \"timings\": [\"Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week.\"],\n", + " \"facilities\": [\"Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets.\"],\n", + " \"contact\": [\"For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website.\"],\n", + " \"route_fare\": [\"To find the fare for a specific route, please provide the start and end stations. For example, 'Dwarka Sector 21 to Kashmere Gate'.\"],\n", + " \"fare_by_route\": \"For the route from {start} to {end}, the fare is {fare}.\"\n", + "}\n", + "\n", + "def detect_response(query):\n", + " # Normalize query for easier matching\n", + " query = query.lower()\n", + "\n", + " # Predict the intent (this is a placeholder, replace with actual model prediction)\n", + " prediction = humingbird.Text.predict(\n", + " text=query, # inferencing text\n", + " labels=[\"greeting\", \"goodbye\", \"address\", \"routes\", \"fares\", \"timings\", \"facilities\", \"contact\", \"route_fare\", \"fare_by_route\"] # potential labels\n", + " )\n", + "\n", + " max_score = 0\n", + " max_val_text = None\n", + "\n", + " for val in prediction:\n", + " if val['score'] > max_score:\n", + " max_score = val['score']\n", + " max_val_text = val['className']\n", + "\n", + " if max_val_text:\n", + " if max_val_text == \"route_fare\":\n", + " return intents[\"route_fare\"][0]\n", + " elif max_val_text == \"fare_by_route\":\n", + " # Extract the start and end stations from the query\n", + " match = re.search(r'fare from (\\w+ \\w+) to (\\w+ \\w+)', query)\n", + " if match:\n", + " start = match.group(1).replace(' ', '_').lower()\n", + " end = match.group(2).replace(' ', '_').lower()\n", + " route_key = f\"{start}_to_{end}\"\n", + " fare = routes_and_fares.get(route_key)\n", + " if fare:\n", + " return intents[\"fare_by_route\"].format(start=start.replace('_', ' ').title(), end=end.replace('_', ' ').title(), fare=fare)\n", + " else:\n", + " return \"Sorry, I couldn't find the fare for that route. Please check the route name and try again.\"\n", + " return random.choice(intents[max_val_text])\n", + " else:\n", + " return \"Sorry, I didn't understand that. Can you please provide more details?\"\n", + "\n", + "def main():\n", + " print(\"Welcome to the Delhi Metro Query System! Type 'exit' to quit.\")\n", + "\n", + " while True:\n", + " # Get user input\n", + " user_input = input(\"\\n --> You: \")\n", + "\n", + " # Check if user wants to exit\n", + " if user_input.lower() == 'exit':\n", + " print(\"Goodbye! Have a great day.\")\n", + " break\n", + "\n", + " # Process the input and provide response\n", + " response = detect_response(user_input)\n", + " print(f\"\\n-->Bot: {response}\")\n", + "\n", + "if __name__ == \"__main__\":\n", + " main()\n" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "fcdbaGAYXa2p", + "outputId": "02e69acb-ec78-49f6-cdbe-2fb766ecbf11" + }, + "execution_count": 93, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Welcome to the Delhi Metro Query System! Type 'exit' to quit.\n", + "\n", + " --> You: hi\n", + "\n", + "-->Bot: Hello! What information do you need about the Delhi Metro?\n", + "\n", + " --> You: timmings of the delhi metroi\n", + "\n", + "-->Bot: Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week.\n", + "\n", + " --> You: fare\n", + "\n", + "-->Bot: The fare structure is as follows:\n", + "Dwarka Sector 21 To Rahaund: ₹40\n", + "Dwarka Sector 21 To Kashmere Gate: ₹30\n", + "Kashmere Gate To Central Secretariat: ₹20\n", + "Central Secretariat To New Delhi: ₹15\n", + "New Delhi To Rajiv Chowk: ₹10\n", + "Note: Fares may vary for different lines and depending on the type of card used.\n", + "\n", + " --> You: routes\n", + "\n", + "-->Bot: Delhi Metro has several key lines connecting different parts of the city. Here’s a brief overview of the main routes:\n", + "\n", + "1. **Red Line (Line 1)**: Dwarka Sector 21 to Kashmere Gate.\n", + "Major stations: Dwarka Sector 21, Dwarka Sector 13, Dwarka Sector 12, Janakpuri West, R K Ashram, Rajiv Chowk, Kashmere Gate.\n", + "\n", + "2. **Blue Line (Line 3 & 4)**: Dwarka Sector 21 to Noida City Centre/Vaishali.\n", + "Major stations: Dwarka Sector 21, Sector 21, Indira Gandhi International Airport, Dwarka Sector 8, Rajouri Garden, Kirti Nagar, Mandi House, Noida City Centre.\n", + "\n", + "3. **Yellow Line (Line 2)**: Samaypur Badli to HUDA City Centre.\n", + "Major stations: Samaypur Badli, Jahangirpuri, Kashmere Gate, Chawri Bazar, Rajiv Chowk, Gurgaon, HUDA City Centre.\n", + "\n", + "4. **Green Line (Line 5)**: Inderlok to Brigadier Hoshier Singh.\n", + "Major stations: Inderlok, Kirti Nagar, Mandi House, Dwarka Sector 21.\n", + "\n", + "5. **Violet Line (Line 6)**: Kashmere Gate to Raja Nahar Singh.\n", + "Major stations: Kashmere Gate, Civil Lines, Vishwa Vidyalaya, Delhi University, Sukhdev Vihar, Badarpur.\n", + "\n", + "6. **Pink Line (Line 7 & 9)**: Majlis Park to Shiv Vihar.\n", + "Major stations: Majlis Park, Azadpur, Mukherjee Nagar, Pitampura, Rithala, Lajpat Nagar, Shiv Vihar.\n", + "\n", + "7. **Aqua Line (Noida Greater Noida Line)**: Noida City Centre to Depot.\n", + "Major stations: Noida City Centre, Sector 18, Greater Noida, Depot.\n", + "\n", + "For more details, you can visit the DMRC website or use the DMRC app for the latest route maps and station details.\n", + "\n", + " --> You: fines \n", + "\n", + "-->Bot: Delhi Metro has several key lines connecting different parts of the city. Here’s a brief overview of the main routes:\n", + "\n", + "1. **Red Line (Line 1)**: Dwarka Sector 21 to Kashmere Gate.\n", + "Major stations: Dwarka Sector 21, Dwarka Sector 13, Dwarka Sector 12, Janakpuri West, R K Ashram, Rajiv Chowk, Kashmere Gate.\n", + "\n", + "2. **Blue Line (Line 3 & 4)**: Dwarka Sector 21 to Noida City Centre/Vaishali.\n", + "Major stations: Dwarka Sector 21, Sector 21, Indira Gandhi International Airport, Dwarka Sector 8, Rajouri Garden, Kirti Nagar, Mandi House, Noida City Centre.\n", + "\n", + "3. **Yellow Line (Line 2)**: Samaypur Badli to HUDA City Centre.\n", + "Major stations: Samaypur Badli, Jahangirpuri, Kashmere Gate, Chawri Bazar, Rajiv Chowk, Gurgaon, HUDA City Centre.\n", + "\n", + "4. **Green Line (Line 5)**: Inderlok to Brigadier Hoshier Singh.\n", + "Major stations: Inderlok, Kirti Nagar, Mandi House, Dwarka Sector 21.\n", + "\n", + "5. **Violet Line (Line 6)**: Kashmere Gate to Raja Nahar Singh.\n", + "Major stations: Kashmere Gate, Civil Lines, Vishwa Vidyalaya, Delhi University, Sukhdev Vihar, Badarpur.\n", + "\n", + "6. **Pink Line (Line 7 & 9)**: Majlis Park to Shiv Vihar.\n", + "Major stations: Majlis Park, Azadpur, Mukherjee Nagar, Pitampura, Rithala, Lajpat Nagar, Shiv Vihar.\n", + "\n", + "7. **Aqua Line (Noida Greater Noida Line)**: Noida City Centre to Depot.\n", + "Major stations: Noida City Centre, Sector 18, Greater Noida, Depot.\n", + "\n", + "For more details, you can visit the DMRC website or use the DMRC app for the latest route maps and station details.\n", + "\n", + " --> You: exit\n", + "Goodbye! Have a great day.\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [], + "metadata": { + "id": "abcmMWpwXrFr" + }, + "execution_count": null, + "outputs": [] + } + ] +} \ No newline at end of file diff --git a/Day-14_SUMMER_TRAINING_AIML/day_14_dhruvdhayal_ai_ml.py b/Day-14_SUMMER_TRAINING_AIML/day_14_dhruvdhayal_ai_ml.py new file mode 100644 index 0000000..8509435 --- /dev/null +++ b/Day-14_SUMMER_TRAINING_AIML/day_14_dhruvdhayal_ai_ml.py @@ -0,0 +1,590 @@ +# -*- coding: utf-8 -*- +"""Day-14_DHRUVDHAYAL_AI/ML.ipynb + +Automatically generated by Colab. + +Original file is located at + https://colab.research.google.com/drive/10Segcq-faKjXkPtfCFAgMiFxMEcc8uT0 + +#Implementing the RealWorld ChatBot +""" + +#Install the HummingBird. +!pip install humingbird; + +import humingbird; #This Import should now work. + +prediction = humingbird.Text.predict( + text="Robots will take over Humans.", #Infrensing Text. + labels=["true","false","no-idea"] #Supply Potential Labels. #Corrected argument name to 'labels' +) +print(prediction); + +prediction = humingbird.Text.predict( + text="You are Dumb", #Infrensing Text. + labels=["true","false","no-idea"] #Supply Potential Labels. #Corrected argument name to 'labels' +) +print(prediction); + +prediction = humingbird.Text.predict( + text="Htler was right?", #Infrensing Text. + labels=["true","false","no-idea"] #Supply Potential Labels. #Corrected argument name to 'labels' +) +print(prediction); + +prediction = humingbird.Text.predict( + text="should I have a Girlfriend in future", #Infrensing Text. + labels=["true","false","no-idea"] #Supply Potential Labels. #Corrected argument name to 'labels' +) +print(prediction); + +prediction = humingbird.Text.predict( + text="RCB won the next IPL .", #Infrensing Text. + labels=["true","false","no-idea"] #Supply Potential Labels. #Corrected argument name to 'labels' +) +print(prediction); + +prediction = humingbird.Text.predict( + text = "AI will take over humans.", # inferencing text + labels=["exciting","scary","dont care"] # suply potential labels +) +max_score=0 +for val in prediction: + if(val['score']>max_score): + max_score=val['score'] + max_val = val['score'] + max_val_text = val['className'] + +print(max_val,max_val_text) + +import random; +intents = { + "greeting":["Hi! how are you?","Hello what's up"], + "goodbye":["Great day ahead","Nice to see you"], + "address":["Address of the college is Near Tihar Jail Janakpuri"], + "courses":["IITM college offers 5 graduation courses and 2 postgraduation courses"], + "Graduation":["graduation courses are : BCA, BBA , BCOM, Btech,BJMC"], + "Postgraduation":["Post grad courses are: MBA, MCA"] +} +def detect_response(query): + prediction = humingbird.Text.predict( + text = query, # inferencing text + labels=["greeting","goodbye", + "address","courses", + "Graduation","Postgraduation"] # suply potential labels + ) + max_score=0 + for val in prediction: + if(val['score']>max_score): + max_score=val['score'] + max_val = val['score'] + max_val_text = val['className'] + print(max_val_text) + return random.choice(intents[max_val_text]) + +detect_response("address of the IITM"); + +import random +intents = { + "greeting":["Hi! how are you?","Hello what's up"], + "goodbye":["Great day ahead","Nice to see you"], + "address":["Address of the college is Near Tihar Jail Janakpuri"], + "courses":["IITM college offers 5 graduation courses and 2 postgraduation courses"], + "Graduation":["graduation courses are : BCA, BBA , BCOM, Btech,BJMC"], + "Postgraduation":["Post grad courses are: MBA, MCA"] +} + +def detect_response(query): + prediction = humingbird.Text.predict( + text = query, # inferencing text + labels=["greeting","goodbye", + "address","courses", + "Graduation","Postgraduation"] # suply potential labels + ) + max_score=0 + for val in prediction: + if(val['score']>max_score): + max_score=val['score'] + max_val = val['score'] + max_val_text = val['className'] + print(max_val_text) + return random.choice(intents[max_val_text]) + +detect_response("can u tell me the number of graduation in IITM") + +"""#Implementing on the DMRC APP (Delhi Metro)/.""" + +import random + +# Define intents and their responses +intents = { + "greeting": ["Hi! How can I assist you with Delhi Metro today?", "Hello! What information do you need about the Delhi Metro?"], + "goodbye": ["Have a great day! If you need more information, feel free to ask.", "Nice talking to you! Safe travels!"], + "address": ["The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi."], + "routes": ["Delhi Metro covers a wide range of routes. For specific route details, you can visit the DMRC website or use the DMRC app."], + "fares": ["Fare details can be found on the DMRC website or at the metro stations. Fares vary based on the distance traveled and the type of card used."], + "timings": ["Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week."], + "facilities": ["Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets."], + "contact": ["For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website."], +} + +def detect_response(query): + # Predict the intent (this is a placeholder, replace with actual model prediction) + prediction = humingbird.Text.predict( + text=query, # inferencing text + labels=["greeting", "goodbye", "address", "routes", "fares", "timings", "facilities", "contact"] # potential labels + ) + + max_score = 0 + max_val_text = None + + for val in prediction: + if val['score'] > max_score: + max_score = val['score'] + max_val_text = val['className'] + + if max_val_text: + print(max_val_text) + return random.choice(intents[max_val_text]) + else: + return "Sorry, I didn't understand that. Can you please provide more details?" + +# Example usage +print(detect_response("What are the timings for the Delhi Metro?")) + +import random + +# Define intents and their responses with routes and fares +intents = { + "greeting": ["Hi! How can I assist you with Delhi Metro today?", "Hello! What information do you need about the Delhi Metro?"], + "goodbye": ["Have a great day! If you need more information, feel free to ask.", "Nice talking to you! Safe travels!"], + "address": ["The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi."], + "routes": ["Delhi Metro covers a wide range of routes. For specific route details, you can visit the DMRC website or use the DMRC app."], + "fares": [ + "The fare structure is as follows:\n" + + "1. For distances up to 2 km: ₹10\n" + + "2. For distances between 2 km and 5 km: ₹15\n" + + "3. For distances between 5 km and 12 km: ₹20\n" + + "4. For distances between 12 km and 21 km: ₹30\n" + + "5. For distances above 21 km: ₹40\n" + + "Note: Fares may vary for different lines and depending on the type of card used." + ], + "timings": ["Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week."], + "facilities": ["Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets."], + "contact": ["For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website."], + "route_fare": [ + "Here is a basic fare structure based on distance:\n" + + "1. Up to 2 km: ₹10\n" + + "2. 2 to 5 km: ₹15\n" + + "3. 5 to 12 km: ₹20\n" + + "4. 12 to 21 km: ₹30\n" + + "5. Above 21 km: ₹40\n" + + "For detailed route information, please provide the specific stations or route you're interested in." + ], +} + +def detect_response(query): + # Predict the intent (this is a placeholder, replace with actual model prediction) + prediction = humingbird.Text.predict( + text=query, # inferencing text + labels=["greeting", "goodbye", "address", "routes", "fares", "timings", "facilities", "contact", "route_fare"] # potential labels + ) + + max_score = 0 + max_val_text = None + + for val in prediction: + if val['score'] > max_score: + max_score = val['score'] + max_val_text = val['className'] + + if max_val_text: + if max_val_text == "route_fare": + return intents["route_fare"][0] + return random.choice(intents[max_val_text]) + else: + return "Sorry, I didn't understand that. Can you please provide more details?" + +# Example usage +print(detect_response("What is the fare for a trip between 5 km and 12 km?")) + +import random + +# Define routes with fare information +routes_and_fares = { + "cost":[ + "dwarka_sector_21_to_dwarka_shahdara ₹10"+ + "dwarka_sector_21_to_rahaund ₹40"+ + "dwarka_sector_21_to_kashmere_gate 30"+ + "kashmere_gate_to_central_secretariat ₹20"+ + "central_secretariat_to_new_delhi ₹15"+ + "new_delhi_to_rajiv_chowk ₹10"] + # Add more routes as needed +} + +# Define intents and their responses +intents = { + "greeting": ["Hi! How can I assist you with Delhi Metro today?", "Hello! What information do you need about the Delhi Metro?"], + "goodbye": ["Have a great day! If you need more information, feel free to ask.", "Nice talking to you! Safe travels!"], + "address": ["The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi."], + "routes": ["Delhi Metro covers a wide range of routes. For specific route details, you can visit the DMRC website or use the DMRC app."], + "fares": [ + "The fare structure is as follows:\n" + + "1. For distances up to 2 km: ₹10\n" + + "2. For distances between 2 km and 5 km: ₹15\n" + + "3. For distances between 5 km and 12 km: ₹20\n" + + "4. For distances between 12 km and 21 km: ₹30\n" + + "5. For distances above 21 km: ₹40\n" + + "Note: Fares may vary for different lines and depending on the type of card used." + ], + "timings": ["Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week."], + "facilities": ["Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets."], + "contact": ["For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website."], + "route_fare": [ + "To find the fare for a specific route, please provide the start and end stations. For example, 'Dwarka Sector 21 to Kashmere Gate'." + ], + "fare_by_route": "For the route from {start} to {end}, the fare is {fare}.", + "rules": [ + "Here are some common rules for traveling on the Delhi Metro:\n" + + "1. Keep your ticket or token with you at all times.\n" + + "2. Maintain silence in the metro coaches.\n" + + "3. Do not eat or drink inside the coaches.\n" + + "4. Avoid leaning out of the doors or windows.\n" + + "5. Follow the instructions of the metro staff and use designated entry/exit points." + ], + "fines": [ + "Fines for various violations on the Delhi Metro are as follows:\n" + + "1. Traveling without a valid ticket: ₹500\n" + + "2. Eating or drinking inside the metro: ₹200\n" + + "3. Misbehavior or creating nuisance: ₹1000\n" + + "4. Damaging metro property: Variable fines based on damage.\n" + + "5. Unauthorized use of reserved seating: ₹300" + ] +} + +def detect_response(query): + # Predict the intent (this is a placeholder, replace with actual model prediction) + prediction = humingbird.Text.predict( + text=query, # inferencing text + labels=["greeting", "goodbye", "address", "routes", "fares", "timings", "facilities", "contact", "route_fare", "rules", "fines"] # potential labels + ) + + max_score = 0 + max_val_text = None + + for val in prediction: + if val['score'] > max_score: + max_score = val['score'] + max_val_text = val['className'] + + if max_val_text: + if max_val_text == "route_fare": + return intents["route_fare"][0] + elif max_val_text == "fare_by_route": + # Extract the start and end stations from the query + for route, fare in routes_and_fares.items(): + if route in query.lower(): + start, end = route.split("_to_") + return intents["fare_by_route"].format(start=start.replace("_", " ").title(), end=end.replace("_", " ").title(), fare=fare) + return "Sorry, I couldn't find the fare for that route. Please check the route name and try again." + elif max_val_text == "rules": + return intents["rules"][0] + elif max_val_text == "fines": + return intents["fines"][0] + + return random.choice(intents[max_val_text]) + else: + return "Sorry, I didn't understand that. Can you please provide more details?" + +# Example usage +print(detect_response("\n For the route from {dwarka} to {rahaund}, the fare is {fare}")); + +import random + +import re # To use regular expressions for extracting routes + + + +# Sample routes and fares + +routes_and_fares = { + + "dwarka_sector_21_to_rahaund": "₹40", + + "dwarka_sector_21_to_kashmere_gate": "₹30", + + "kashmere_gate_to_central_secretariat": "₹20", + + "central_secretariat_to_new_delhi": "₹15", + + "new_delhi_to_rajiv_chowk": "₹10", + + # Add more routes as needed + +} + + + +# Define intents and their responses + +intents = { + + "greeting": ["Hi! How can I assist you with Delhi Metro today?", "Hello! What information do you need about the Delhi Metro?"], + + "goodbye": ["Have a great day! If you need more information, feel free to ask.", "Nice talking to you! Safe travels!"], + + "address": ["The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi."], + + "routes": ["Delhi Metro has several key lines connecting different parts of the city. Here’s a brief overview of the main routes:\n" + + "\n1. **Red Line (Line 1)**: " + + "Dwarka Sector 21 to Kashmere Gate.\n" + + "Major stations: Dwarka Sector 21, Dwarka Sector 13, Dwarka Sector 12, Janakpuri West, R K Ashram, Rajiv Chowk, Kashmere Gate.\n" + + "\n2. **Blue Line (Line 3 & 4)**: " + + "Dwarka Sector 21 to Noida City Centre/Vaishali.\n" + + "Major stations: Dwarka Sector 21, Sector 21, Indira Gandhi International Airport, Dwarka Sector 8, Rajouri Garden, Kirti Nagar, Mandi House, Noida City Centre.\n" + + "\n3. **Yellow Line (Line 2)**: " + + "Samaypur Badli to HUDA City Centre.\n" + + "Major stations: Samaypur Badli, Jahangirpuri, Kashmere Gate, Chawri Bazar, Rajiv Chowk, Gurgaon, HUDA City Centre.\n" + + "\n4. **Green Line (Line 5)**: " + + "Inderlok to Brigadier Hoshier Singh.\n" + + "Major stations: Inderlok, Kirti Nagar, Mandi House, Dwarka Sector 21.\n" + + "\n5. **Violet Line (Line 6)**: " + + "Kashmere Gate to Raja Nahar Singh.\n" + + "Major stations: Kashmere Gate, Civil Lines, Vishwa Vidyalaya, Delhi University, Sukhdev Vihar, Badarpur.\n" + + "\n6. **Pink Line (Line 7 & 9)**: " + + "Majlis Park to Shiv Vihar.\n" + + "Major stations: Majlis Park, Azadpur, Mukherjee Nagar, Pitampura, Rithala, Lajpat Nagar, Shiv Vihar.\n" + + "\n7. **Aqua Line (Noida Greater Noida Line)**: " + + "Noida City Centre to Depot.\n" + + "Major stations: Noida City Centre, Sector 18, Greater Noida, Depot.\n" + + "\nFor more details, you can visit the DMRC website or use the DMRC app for the latest route maps and station details." + + ], + + "fares": [ + + "The fare structure is as follows:\n" + + + "\n".join([f"{route.replace('_to_', ' to ').replace('_', ' ').title()}: {fare}" for route, fare in routes_and_fares.items()]) + + + "\nNote: Fares may vary for different lines and depending on the type of card used." + + ], + + "timings": ["Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week."], + + "facilities": ["Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets."], + + "contact": ["For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website."], + + "route_fare": ["To find the fare for a specific route, please provide the start and end stations. For example, 'Dwarka Sector 21 to Kashmere Gate'."], + + "fare_by_route": "For the route from {start} to {end}, the fare is {fare}." + +} + + + +def detect_response(query): + + # Predict the intent (this is a placeholder, replace with actual model prediction) + + prediction = humingbird.Text.predict( + + text=query, # inferencing text + + labels=["greeting", "goodbye", "address", "routes", "fares", "timings", "facilities", "contact", "route_fare", "fare_by_route"] # potential labels + + ) + + + + max_score = 0 + + max_val_text = None + + + + for val in prediction: + + if val['score'] > max_score: + + max_score = val['score'] + + max_val_text = val['className'] + + + + if max_val_text: + + if max_val_text == "route_fare": + + return intents["route_fare"][0] + + elif max_val_text == "fare_by_route": + + # Extract the start and end stations from the query + + match = re.search(r'fare from (\w+ \w+) to (\w+ \w+)', query.lower()) + + if match: + + start = match.group(1).replace(' ', '_').lower() + + end = match.group(2).replace(' ', '_').lower() + + route_key = f"{start}_to_{end}" + + fare = routes_and_fares.get(route_key) + + if fare: + + return intents["fare_by_route"].format(start=start.replace('_', ' ').title(), end=end.replace('_', ' ').title(), fare=fare) + + else: + + return "Sorry, I couldn't find the fare for that route. Please check the route name and try again." + + + + return random.choice(intents[max_val_text]) + + + + else: + + return "Sorry, I didn't understand that. Can you please provide more details?" + + + +# Example usage + +print(detect_response("What is the fare from Dwarka Sector 21 to Kashmere Gate?")) + +print(detect_response("\n ")) + +import random +import re; # To use regular expressions for extracting routes + +# Sample routes and fares +routes_and_fares = { + "dwarka_sector_21_to_rahaund": "₹40", + "dwarka_sector_21_to_kashmere_gate": "₹30", + "kashmere_gate_to_central_secretariat": "₹20", + "central_secretariat_to_new_delhi": "₹15", + "new_delhi_to_rajiv_chowk": "₹10", + # Add more routes as needed +} + +# Define intents and their responses +intents = { + "greeting": ["Hi! How can I assist you with Delhi Metro today?", "Hello! What information do you need about the Delhi Metro?"], + "goodbye": ["Have a great day! If you need more information, feel free to ask.", "Nice talking to you! Safe travels!"], + "address": ["The address of the Delhi Metro headquarters is at Barakhamba Road, Delhi."], + "routes": ["Delhi Metro has several key lines connecting different parts of the city. Here’s a brief overview of the main routes:\n" + "\n1. **Red Line (Line 1)**: Dwarka Sector 21 to Kashmere Gate.\n" + "Major stations: Dwarka Sector 21, Dwarka Sector 13, Dwarka Sector 12, Janakpuri West, R K Ashram, Rajiv Chowk, Kashmere Gate.\n" + "\n2. **Blue Line (Line 3 & 4)**: Dwarka Sector 21 to Noida City Centre/Vaishali.\n" + "Major stations: Dwarka Sector 21, Sector 21, Indira Gandhi International Airport, Dwarka Sector 8, Rajouri Garden, Kirti Nagar, Mandi House, Noida City Centre.\n" + "\n3. **Yellow Line (Line 2)**: Samaypur Badli to HUDA City Centre.\n" + "Major stations: Samaypur Badli, Jahangirpuri, Kashmere Gate, Chawri Bazar, Rajiv Chowk, Gurgaon, HUDA City Centre.\n" + "\n4. **Green Line (Line 5)**: Inderlok to Brigadier Hoshier Singh.\n" + "Major stations: Inderlok, Kirti Nagar, Mandi House, Dwarka Sector 21.\n" + "\n5. **Violet Line (Line 6)**: Kashmere Gate to Raja Nahar Singh.\n" + "Major stations: Kashmere Gate, Civil Lines, Vishwa Vidyalaya, Delhi University, Sukhdev Vihar, Badarpur.\n" + "\n6. **Pink Line (Line 7 & 9)**: Majlis Park to Shiv Vihar.\n" + "Major stations: Majlis Park, Azadpur, Mukherjee Nagar, Pitampura, Rithala, Lajpat Nagar, Shiv Vihar.\n" + "\n7. **Aqua Line (Noida Greater Noida Line)**: Noida City Centre to Depot.\n" + "Major stations: Noida City Centre, Sector 18, Greater Noida, Depot.\n" + "\nFor more details, you can visit the DMRC website or use the DMRC app for the latest route maps and station details." + ], + "fares": [ + "The fare structure is as follows:\n" + + "\n".join([f"{route.replace('_to_', ' to ').replace('_', ' ').title()}: {fare}" for route, fare in routes_and_fares.items()]) + + "\nNote: Fares may vary for different lines and depending on the type of card used." + ], + "timings": ["Delhi Metro services generally run from 6 AM to 11 PM. However, timings may vary depending on the line and day of the week."], + "facilities": ["Delhi Metro stations are equipped with various facilities including elevators, escalators, and ticket vending machines. Some stations also have retail shops and food outlets."], + "contact": ["For more information, you can contact Delhi Metro's customer care at 155370 or visit their official website."], + "route_fare": ["To find the fare for a specific route, please provide the start and end stations. For example, 'Dwarka Sector 21 to Kashmere Gate'."], + "fare_by_route": "For the route from {start} to {end}, the fare is {fare}." +} + +def detect_response(query): + # Normalize query for easier matching + query = query.lower() + + # Predict the intent (this is a placeholder, replace with actual model prediction) + prediction = humingbird.Text.predict( + text=query, # inferencing text + labels=["greeting", "goodbye", "address", "routes", "fares", "timings", "facilities", "contact", "route_fare", "fare_by_route"] # potential labels + ) + + max_score = 0 + max_val_text = None + + for val in prediction: + if val['score'] > max_score: + max_score = val['score'] + max_val_text = val['className'] + + if max_val_text: + if max_val_text == "route_fare": + return intents["route_fare"][0] + elif max_val_text == "fare_by_route": + # Extract the start and end stations from the query + match = re.search(r'fare from (\w+ \w+) to (\w+ \w+)', query) + if match: + start = match.group(1).replace(' ', '_').lower() + end = match.group(2).replace(' ', '_').lower() + route_key = f"{start}_to_{end}" + fare = routes_and_fares.get(route_key) + if fare: + return intents["fare_by_route"].format(start=start.replace('_', ' ').title(), end=end.replace('_', ' ').title(), fare=fare) + else: + return "Sorry, I couldn't find the fare for that route. Please check the route name and try again." + return random.choice(intents[max_val_text]) + else: + return "Sorry, I didn't understand that. Can you please provide more details?" + +def main(): + print("Welcome to the Delhi Metro Query System! Type 'exit' to quit.") + + while True: + # Get user input + user_input = input("\n --> You: ") + + # Check if user wants to exit + if user_input.lower() == 'exit': + print("Goodbye! Have a great day.") + break + + # Process the input and provide response + response = detect_response(user_input) + print(f"\n-->Bot: {response}") + +if __name__ == "__main__": + main() +