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.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+templates/TaskBot[[:space:]]logo.png filter=lfs diff=lfs merge=lfs -text

Dockerfile

@@ -0,0 +1,14 @@
+FROM python:3.9
+
+WORKDIR /app
+COPY . /app
+RUN pip install --no-cache-dir -r requirements.txt
+
+ENV HF_HOME=/app/hf_cache
+ENV TRANSFORMERS_CACHE=/app/hf_cache
+RUN mkdir -p /app/hf_cache && chmod -R 777 /app/hf_cache
+
+EXPOSE 7860
+
+# Run Gunicorn with 4 worker processes on port 7860
+CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:7860", "app:app"]

app.py

@@ -0,0 +1,39 @@
+#Downloading and importing all the modules required for this TaskBot v1 AI
+import google.generativeai as genai
+import os
+import json
+import requests
+from flask import Flask, request, jsonify, render_template
+import torch
+
+#Connect to index.html
+app = Flask(__name__)
+@app.route("/")
+def index():
+    return render_template("index.html")
+
+@app.route("/ask", methods=["POST"])
+def ask():
+    #getting the question from the form
+    question = request.form.get("question", "").strip()
+    if not question:
+        return jsonify({"error": "Please provide a question."}), 400
+
+    genai.configure(api_key="AIzaSyA5FFcaVCfVmwf7X5C59n4xWc96xWR-A_4")
+
+    try:
+        # use Google's Gemini-2.0-Flash nodle for generating content
+        model = genai.GenerativeModel('gemini-2.0-flash')
+        response = model.generate_content(f"You are TaskBot AI created and trained by Advay Singh and Astrumix. Remember that and just anser me this question in detail- {question}. And don't reply on that message. Just answer me the question.")
+        answer = response.text
+
+        # Log the question and answer for debugging
+        print(f"Question: {question}\n------------------------- \n {answer} \n -------------------------")
+        # Return the answer as JSON
+        return jsonify({"answer": answer})
+    except Exception as e:
+        print(f"Error: {e}")
+        return jsonify({"error": "An error occurred while processing your request."}), 500
+
+if __name__ == "__main__":
+    app.run(port=5000, host="0.0.0.0")