Create app.py

app.py

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+from dotenv import load_dotenv
+import streamlit as st
+import os
+from groq import Groq 
+
+# Load environment variables from the .env file
+load_dotenv()
+
+# Securely get the GROQ API key from environment variables
+groq_api_key = os.getenv("GROQ_API_KEY")
+if not groq_api_key:
+    raise ValueError("GROQ_API_KEY environment variable not set.")
+
+# Initialize the client with the API key
+client = Groq(api_key=groq_api_key)
+
+
+# Function to get a response from Groq API
+def get_groq_response(prompt):
+    try:
+        chat_completion = client.chat.completions.create(
+            messages=[{"role": "user", "content": prompt}],
+            model="llama3-8b-8192"
+        )
+        return chat_completion.choices[0].message.content
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Streamlit app layout
+st.title("Crop Advisory Chatbot")
+st.write("Provide your details to get personalized crop advice.")
+
+# Input fields for user details
+soil_type = st.text_input("Soil type (e.g., sandy, clay, loamy):")
+climate = st.text_input("Climate (e.g., hot, moderate, cold):")
+area_size = st.number_input("Area size in acres:", min_value=0.1, step=0.1)
+season = st.selectbox("Current season:", ["Select", "Summer", "Winter", "Rainy", "Autumn", "Spring"])
+
+if st.button("Get Advisory"):
+    # Check if all fields are filled
+    if soil_type and climate and area_size and season != "Select":
+        # Prompts for different advisory features
+        crop_recommendation_prompt = (
+            f"Suggest suitable crops for soil type '{soil_type}', climate '{climate}', "
+            f"area size '{area_size}' acres, and season '{season}'."
+        )
+
+        fertilizer_prompt = (
+            f"Provide fertilizer recommendations for crops suitable in soil '{soil_type}' "
+            f"and climate '{climate}'."
+        )
+
+        irrigation_prompt = (
+            f"Suggest irrigation methods and water requirements for crops in "
+            f"'{soil_type}' soil with '{climate}' climate."
+        )
+
+        harvest_prompt = (
+            f"When is the best harvesting time for crops in '{climate}' climate during the '{season}' season?"
+        )
+
+        # Fetch responses from Groq API
+        with st.spinner("Fetching advisory..."):
+            crop_recommendation = get_groq_response(crop_recommendation_prompt)
+            fertilizer_advice = get_groq_response(fertilizer_prompt)
+            irrigation_advice = get_groq_response(irrigation_prompt)
+            harvest_advice = get_groq_response(harvest_prompt)
+
+        # Display results
+        st.subheader("Crop Recommendations")
+        st.write(crop_recommendation)
+        
+        st.subheader("Fertilizer Recommendations")
+        st.write(fertilizer_advice)
+        
+        st.subheader("Irrigation Advice")
+        st.write(irrigation_advice)
+        
+        st.subheader("Harvesting Advice")
+        st.write(harvest_advice)
+
+    else:
+        st.warning("Please fill in all the details to get the advisory.")
+
+# To run the app in Colab, you need to use ngrok or run it locally with:
+# `streamlit run app.py`