Llama Chatbot with Sentiment Analysis Integration.ipynb

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The chatbot dynamically adjusts its responses based on the user's emotional state, detected through sentiment analysis. By identifying positive, negative, and neutral sentiments in user inputs, the chatbot can respond in a more personalized, supportive, or relevant manner. This project is built as part of a bounty challenge from Stackup focused on creating interactive and emotionally responsive AI systems.\n","\n","# **Features:**\n","**Sentiment Detection:** Uses Hugging Face's sentiment analysis model to categorize user inputs as positive, negative, or neutral.\n","**Adaptive Responses:** The chatbot tailors its responses based on detected sentiments, offering encouragement, support, or celebratory messages.\n","Simple Interface: Integrated with Gradio to provide a user-friendly text-based interface for interaction.\n","**Applications:** Can be used in customer support, mental health support, and educational tutoring to adjust responses based on user mood.\n","Tools and Technologies:\n","**Google Colab:** For running the notebook and the chatbot environment.\n","Python: Core language for building the chatbot logic.\n","**Hugging Face Transformers:** For integrating sentiment analysis capabilities.\n","Gradio: For creating an easy-to-use web interface for the chatbot.\n","\n","**Installation Instructions:**\n","\n","Clone the repository.\n","git clone https://github.com/your-username/llama-chatbot-sentiment.git\n","\n","Install the required dependencies\n","\n","pip install transformers torch gradio\n","\n","Run the chatbot. Open the Llama_Chatbot_Sentiment.ipynb notebook in Google Colab or locally to launch the chatbot.\n","\n","\n","**Example Use Cases:**\n","Customer Support: Automatically adjust tone to provide support if the user expresses frustration.\n","Mental Health: Detects when users are feeling down and responds with uplifting messages.\n","**Educational Tutoring:** Offers more straightforward explanations when the user is feeling frustrated.\n","**Future Enhancements:**\n","Integrating more nuanced emotional understanding (e.g., anger, excitement).\n","Expanding the dataset to support other languages for sentiment detection.\n","Adding memory to the chatbot for more contextual conversations over time.\n","\n","\n","**License:**\n","This project is licensed under the MIT License - see the LICENSE file for details."],"metadata":{"id":"G4K1Vmfy21yg"}},{"cell_type":"markdown","source":["Installation of required libraries"],"metadata":{"id":"VapFM04D0pA5"}},{"cell_type":"code","source":["!pip 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Libraries"],"metadata":{"id":"v4-wnSFr1DKe"}},{"cell_type":"code","execution_count":null,"metadata":{"id":"1B_Y6YJn9bIf"},"outputs":[],"source":["import torch\n","from transformers import pipeline\n","import gradio as gr"]},{"cell_type":"markdown","source":["Loading the Sentiment Analysis Model"],"metadata":{"id":"VkfaMzTZ1HFZ"}},{"cell_type":"code","source":["sentiment_analysis = pipeline(\"sentiment-analysis\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":356,"referenced_widgets":["a73d3408c2c34ca38f5c6e0abbc4f78f","c9ac45da009842ca819fd7295cf1117b","5baaedcf7891446a8d554f1796bd74a4","779fc4982ba648a482faf3ceb61c499e","386b04e83be7426b8ab2d3eaf7f43023","64d281321ea54e508a735f9579cd794c","5e7ebbb5b553495cba488d66e0a463f0","f290408530794fd9bd478c386a924aee","7b2b85ac90a1421abe56ce73ab581ea3","41a85a1337574862af8fcfa434dac9b7","6eefa8a7d4e74fc287184b17ef5876a2","71ee5fcd9c3c4c44b30531fe904fa36a","72d220e4fcd14a5fbb8a4549d76c5288","6c0278ca7dbf4f78b56c1530f5580085","953a0a32d7dc4422a5752ac43de8f242","a6a6ada9160345d9ad989516d69385cc","68ddffb5ee1f46f8a4ef0f660ffc214c","c9b68136bec54c89ad91402caa5851aa","8277b95ff30f4f17863866a24a2c044c","fe208b365563450f94dc952f04bf86bd","bcadea3a5f4243858241d984aea26a09","39ef3590f62645689ff1366338a929b3","872e6c8bb9274cf7bf7b311bbce85d92","87a942bfb20c478385cecd3b463edaf3","758c0b68b7ea4f0585e893771c26695d","8197cd215bbf454bb54cc0dd0b091a43","411ed5c0c0b14ff388e42ce11129a8d4","343be42febaf4e66af5af55a4e5699aa","e1f85131793645b2a4679a47eb663225","99a53cbd24084b9cb55c9c1e79e89248","e58c96cf43bd4b5cbd4e586e0d5582d6","513d4faa92ec43a1aaed996b9421916d","3b62a7fff89644a79004b25142dd3b6c","a7e639bc7866422aa6b93e64792fc0b7","f2862f81cfd0482a9bdd1577c0ed50a0","c37a1bb5fa4d415ba4b7b28c8161b654","bb9a2500434843138d5c1aa14e07fc3c","653898032c694c20a1a3d4cead67b99d","803055fedd504523a2536599d87c8804","a65a30765efc4c89af76de3d76e26808","84764a92c3fd4108b000f6eeb2c1ec9e","295d5edf102145c2abcc481be02bc0d3","a7f7acd49d0047a59a8009eddf1842fc","2b2a4049e6ef444dae5ee40bf902cd78"]},"id":"k0hN17lW9n8Z","executionInfo":{"status":"ok","timestamp":1727264389553,"user_tz":-330,"elapsed":5888,"user":{"displayName":"mrigank shekhar chaubey","userId":"08654698187572642905"}},"outputId":"7a06174a-e0a1-459c-b1b2-db97fe88c76c"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stderr","text":["No model was supplied, defaulted to distilbert/distilbert-base-uncased-finetuned-sst-2-english and revision af0f99b (https://huggingface.co/distilbert/distilbert-base-uncased-finetuned-sst-2-english).\n","Using a pipeline without specifying a model name and revision in production is not recommended.\n","/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%|          | 0.00/629 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"a73d3408c2c34ca38f5c6e0abbc4f78f"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["model.safetensors:   0%|          | 0.00/268M [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"71ee5fcd9c3c4c44b30531fe904fa36a"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["tokenizer_config.json:   0%|          | 0.00/48.0 [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"872e6c8bb9274cf7bf7b311bbce85d92"}},"metadata":{}},{"output_type":"display_data","data":{"text/plain":["vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"a7e639bc7866422aa6b93e64792fc0b7"}},"metadata":{}},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n","  warnings.warn(\n","Hardware accelerator e.g. GPU is available in the environment, but no `device` argument is passed to the `Pipeline` object. Model will be on CPU.\n"]}]},{"cell_type":"markdown","source":["Defining the chatbot logic by creating the function to perform sentiment analysis"],"metadata":{"id":"KmB0uCuM1TPU"}},{"cell_type":"code","source":["def mental_health_chatbot(user_input):\n","    # Analyze the sentiment of the user input\n","    result = sentiment_analysis(user_input)[0]\n","\n","    # Check the sentiment and give nuanced responses\n","    if result['label'] == 'NEGATIVE':\n","        if result['score'] > 0.75:\n","            response = \"It sounds like you're really going through a tough time. Please don't hesitate to reach out to someone who can help.\"\n","        elif result['score'] > 0.5:\n","            response = \"I'm sorry you're feeling down. It's okay to ask for support.\"\n","        else:\n","            response = \"It seems like you're having a rough day. I'm here if you want to talk.\"\n","\n","    elif result['label'] == 'POSITIVE':\n","        if result['score'] > 0.75:\n","            response = \"That's amazing! Keep holding on to those positive feelings.\"\n","        else:\n","            response = \"I'm glad you're doing well. Keep up the great energy.\"\n","\n","    else:  # Neutral or mixed sentiment\n","        response = \"Thank you for sharing. I'm here if you need anything.\"\n","\n","    return response\n","\n","\n"],"metadata":{"id":"xJhFoNoK-3Tb"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["Creating Gradio interface for human interaction"],"metadata":{"id":"ymDsJFxf13G4"}},{"cell_type":"code","source":["# Gradio interface function\n","def chat_interface(user_input):\n","    return mental_health_chatbot(user_input)\n","\n","# Create the Gradio interface\n","iface = gr.Interface(\n","    fn=chat_interface,\n","    inputs=\"text\",\n","    outputs=\"text\",\n","    title=\"Mental Health Assistant\",\n","    description=\"A chatbot that detects sentiment and provides supportive messages.\"\n",")\n","\n","# Launch the interface\n","iface.launch()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":626},"id":"PCq5okX-ChYn","executionInfo":{"status":"ok","timestamp":1727265386586,"user_tz":-330,"elapsed":2120,"user":{"displayName":"mrigank shekhar chaubey","userId":"08654698187572642905"}},"outputId":"704e091b-8a66-41ed-b1d2-5e84c9748b6d"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n","\n","Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n","Running on public URL: https://4f3c1c528a1766954a.gradio.live\n","\n","This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.HTML object>"],"text/html":["<div><iframe src=\"https://4f3c1c528a1766954a.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"]},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":[]},"metadata":{},"execution_count":20}]}]}