Marketing tips feature

main.py

@@ -18,7 +18,8 @@ from pandasai.responses.response_parser import  ResponseParser
 import matplotlib.pyplot as plt
 from wordcloud import WordCloud
 import random
-
+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
 from dotenv import load_dotenv
 import json
 
@@ -28,6 +29,8 @@ from dotenv import load_dotenv
 load_dotenv()
 
 
+
+
 app = Flask(__name__)
 cors = CORS(app)
 
@@ -119,6 +122,32 @@ def bot():
     
     return jsonify(resp)
 
+@app.route("/mrec", methods=["POST"])
+@cross_origin()
+def marketing_rec():
+    user_id = request.json.get("user_id")
+
+    transactions_ref = db.collection("system_users").document(user_id).collection('transactions')
+    transactions_list = []
+    for doc in transactions_ref.stream():
+        a = doc.to_dict()
+        transactions_list.append(a)
+
+    transactions_df = pd.DataFrame(transactions_list)
+    # Set up a prompt template
+    prompt = PromptTemplate.from_template('You are a business analyst. Write some marketing tips suitable for a small mobile dashboard based on this transactions dataframe {data_frame}')
+
+# Create a chain that utilizes both the LLM and the prompt template
+    chain = LLMChain(llm=llm, prompt=prompt, verbose=True)
+    data_frame = transactions_df
+    response = chain.invoke(input=data_frame)
+    print(response)
+
+    resp = str(response)
+
+    return jsonify(resp)
+
+
 
 if __name__ == "__main__":
     app.run(debug=True,host="0.0.0.0", port=7860)