add source citation

app.py

@@ -3,6 +3,7 @@ import streamlit as st
 from streamlit_chat import message
 from streamlit_extras.colored_header import colored_header
 from streamlit_extras.add_vertical_space import add_vertical_space
+from datetime import datetime
 import requests
 from gradio_client import Client
 import datetime as dt
@@ -14,9 +15,8 @@ st.set_page_config(page_title="HugChat - An LLM-powered Streamlit app")
 API_TOKEN = st.secrets['HF_TOKEN']
 API_URL = "https://api-inference.huggingface.co/models/mistralai/Mixtral-8x7B-Instruct-v0.1"
 headers = {"Authorization": f"Bearer {str(API_TOKEN)}"}
-def get_text():
-        input_text = st.text_input("You: ", "", key="input")
-        return input_text
+
+API_URL1 = "https://api-inference.huggingface.co/models/HuggingFaceH4/zephyr-7b-beta"
 
 soil_types = {
     "Sais plain": "Brown limestone, vertisols, lithosols, and regosols",
@@ -33,9 +33,11 @@ soil_types = {
     "Argan zone": "Soils are mostly lithosols and regosols, associated with fluvisols and saline soils on lowlands",
     "Presaharan soils": "Lithosols and regosols in association with sierozems and regs",
     "Saharan zone": "Yermosols, associated with sierozems, lithosols, and saline soils"
-}
-
+    }
 
+def get_text():
+    input_text = st.text_input("You: ", "", key="input")
+    return input_text
 
 def get_weather_data(city):
     base_url = "http://api.openweathermap.org/data/2.5/weather?"
@@ -69,11 +71,8 @@ def get_weather_data(city):
         print(f"Error: {e}")
         return None
 
-# Example usage
-
-
-def query(payload):
-	response = requests.post(API_URL, headers=headers, json=payload)
+def query(payload, api_url):
+	response = requests.post(api_url, headers=headers, json=payload)
 	return response.json()
 	
 def translate(text,source="English",target="Moroccan Arabic"):
@@ -87,9 +86,48 @@ def translate(text,source="English",target="Moroccan Arabic"):
     print(result)
     return result
 
+def search_url(search_query):
+    API_KEY = st.secrets['API_TOKEN']
+    SEARCH_ENGINE_ID = st.secrets['SEARCH_ENGINE_ID']
+    
+    url = 'https://www.googleapis.com/customsearch/v1'
+
+    params = {
+        'q': search_query,
+        'key': API_KEY,
+        'cx': SEARCH_ENGINE_ID,
+    }
+
+    response = requests.get(url, params=params)
+
+    results = response.json()
+
+    # print(results)
+
+    if 'items' in results:
+        for i in range(min(5, len(results['items']))):
+            print(f"Link {i + 1}: {results['items'][i]['link']}")
+        return results['items'][:5]
+    else:
+        print("No search results found.")
+        return None
+
+def get_search_query(response):
+    instruction = f'''
+        Based on these information, generate a short summarized search terms. Don't include weather specifications.
+        Information : {response} 
+        Search term keyword:
+    '''
+    
+    output = query({"inputs": instruction, "parameters":{"max_new_tokens":40, "temperature":.3, "return_full_text":False}}, API_URL1)
+    print(instruction)
+    print(output)
+    ss = output[0]['generated_text'][:output[0]['generated_text'].find('\n')]
+    print(ss)
+    return ss
 
 # Function to generate a response from the chatbot
-def generate_response(user_input,region):
+def generate_response(user_input, region, date):
 
     city = "Fez"
     weather_info = get_weather_data(city)
@@ -97,8 +135,8 @@ def generate_response(user_input,region):
         print(weather_info)
         
     user_input_translated = str(translate(user_input, "Moroccan Arabic", "English"))
-    name = 'Fellah(a)'
-    date = 'December'
+    name = 'Fellah'
+    date = date
     location = 'Fes, Morocco'
     soil_type = soil_types[region]  # Use the selected region's soil type
     humidity = weather_info["humidity"]
@@ -111,29 +149,16 @@ def generate_response(user_input,region):
 
     instruction = f'''
     <s> [INST] You are an agriculture expert, and my name is {name} Given the following informations, prevailing weather conditions, specific land type, chosen type of agriculture, and soil composition of a designated area, answer the question below
-Location: {location},
-Current Month : {date}
-land type: {soil_types[region]}
-humidity: {humidity}
-weather: {weather}
-temperature: {temp}
- Question: {user_input_translated}[/INST]</s>
-    '''
-    prompt = f'''
-    You are an agriculture expert, Given the following informations, geographical coordinates (latitude and longitude), prevailing weather conditions, specific land type, chosen type of agriculture, and soil composition of a designated area, request the LLM to provide detailed insights and predictions on optimal agricultural practices, potential crop yields, and recommended soil management strategies, or answer the question below
-Location: {location},
-land type: {soil_type}
-humidity: {humidity}
-weather: {weather}
-temperature: {temp}
+    Location: {location},
+    Current Month : {date}
+    land type: {soil_types[region]}
+    humidity: {humidity}
+    weather: {weather}
+    temperature: {temp}
+    Question: {user_input_translated}[/INST]</s>
     '''
-#     output = query({"inputs": f'''
-# PROMPT: {prompt}
-# QUESTION: {user_input}
-# ANSWER: 
-# ''',})
 
-    output = query({"inputs": instruction, "parameters":{"max_new_tokens":250, "temperature":1, "return_full_text":False}})
+    output = query({"inputs": instruction, "parameters":{"max_new_tokens":250, "temperature":1, "return_full_text":False}}, API_URL)
     # print(headers)
     print(instruction)
     print(output)
@@ -165,10 +190,7 @@ def main():
         💡 Note: No API key required!
         ''')
         add_vertical_space(5)
-        st.write('Made with ❤️ by [llama-crew](https://huggingface.co/llama-crew)')
-        #st.write('Made with ❤️ by [llama-crew](https://hf.co/medmac01)')
-
-        
+        st.write('Made with ❤️ by [llama-crew](https://huggingface.co/smart-fellah)')
 
     # Generate empty lists for generated and past.
     ## generated stores AI generated responses
@@ -189,6 +211,8 @@ def main():
 
     colored_header(label='', description='', color_name='blue-30')
     response_container = st.container()
+    
+    date = datetime.now().month
 
     # User input
     ## Function for taking user provided prompt as input
@@ -203,7 +227,7 @@ def main():
     ## Conditional display of AI generated responses as a function of user provided prompts
     with response_container:
         if user_input:
-            response = generate_response(user_input,str(selected_region))
+            response = generate_response(user_input,str(selected_region), str(date))
             st.session_state.past.append(user_input)
             st.session_state.generated.append(response)
             
@@ -212,5 +236,18 @@ def main():
                 message(st.session_state['past'][i], is_user=True, key=str(i) + '_user', logo="https://i.pinimg.com/originals/d5/b2/13/d5b21384ccaaa6f9ef32986f17c50638.png")
                 message(st.session_state["generated"][i], key=str(i), logo= "https://emojiisland.com/cdn/shop/products/Robot_Emoji_Icon_7070a254-26f7-4a54-8131-560e38e34c2e_large.png?v=1571606114")
 
+                # Add Google icon button to retrieve links
+                if st.button(f"Double-Check Response", key=f"google_button_{i}"):
+                    search_query = get_search_query(st.session_state['generated'][i])
+                    retrieved_links = search_url(search_query)
+                    if retrieved_links:
+                        st.markdown("**Google Search Results:**")
+                        for j, link in enumerate(retrieved_links):
+                            st.markdown(f"{j + 1}. [{link['title']}]({link['link']})")
+
+                            # Display Google logo
+                            google_logo_url = "https://www.gstatic.com/webp/gallery/2.jpg"
+                            st.image(google_logo_url, width=50, caption="Google Logo")
+        
 if __name__ == "__main__":
     main()