Update app.py

app.py

@@ -3,7 +3,7 @@ from twilio.twiml.messaging_response import MessagingResponse
 from twilio.rest import Client
 import os
 import shutil
-
+from other_function import ConversationBufferMemory,generate_response,get_weather,get_rates,get_news,convert_img,predict_disease,predict_pest, download_and_save_as_txt,download_file,
 from bs4 import BeautifulSoup
 import requests
 from requests.auth import HTTPBasicAuth
@@ -25,19 +25,6 @@ if not os.path.exists(UPLOAD_FOLDER):
 
 app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
 
-
-class ConversationBufferMemory:
-    def __init__(self, max_size):
-        self.memory = []
-        self.max_size = max_size
-
-    def add_to_memory(self, interaction):
-        self.memory.append(interaction)
-        if len(self.memory) > self.max_size:
-            self.memory.pop(0)
-
-    def get_memory(self):
-        return self.memory
 conversation_memory = ConversationBufferMemory(max_size=2)
 
 account_sid = os.environ.get('TWILIO_ACCOUNT_SID')
@@ -52,147 +39,7 @@ Answer the question based only on the following context:
 Answer the question based on the above context: {question}
 """
 
-AI71_API_KEY = os.environ.get('AI71_API_KEY')
-
-def generate_response(query, chat_history):
-    response = ''
-    for chunk in AI71(AI71_API_KEY).chat.completions.create(
-            model="tiiuae/falcon-180b-chat",
-            messages=[
-                {"role": "system", "content": "You are the best agricultural assistant. Remember to give a response in not more than 2 sentences. Greet the user if the user greets you."},
-                {"role": "user", "content": f'''Answer the query based on history {chat_history}: {query}'''},
-            ],
-            stream=True,
-    ):
-        if chunk.choices[0].delta.content:
-            response += chunk.choices[0].delta.content
-    return response.replace("###", '').replace('\nUser:', '')
-
-def predict_pest(filepath):
-    CLIENT = InferenceHTTPClient(
-        api_url="https://detect.roboflow.com",
-        api_key="oF1aC4b1FBCDtK8CoKx7"
-    )
-    result = CLIENT.infer(filepath, model_id="pest-detection-ueoco/1")
-    return result['predictions'][0]
-    
-
-def predict_disease(filepath):
-    CLIENT = InferenceHTTPClient(
-        api_url="https://classify.roboflow.com",
-        api_key="oF1aC4b1FBCDtK8CoKx7"
-    )
-    result = CLIENT.infer(filepath, model_id="plant-disease-detection-iefbi/1")
-    return result['predicted_classes'][0]
-
-def convert_img(url, account_sid, auth_token):
-    try:
-        response = requests.get(url, auth=HTTPBasicAuth(account_sid, auth_token))
-        response.raise_for_status()
-
-        parsed_url = urlparse(url)
-        media_id = parsed_url.path.split('/')[-1]
-        filename = f"downloaded_media_{media_id}"
-
-        media_filepath = os.path.join(UPLOAD_FOLDER, filename)
-        with open(media_filepath, 'wb') as file:
-            file.write(response.content)
-        
-        print(f"Media downloaded successfully and saved as {media_filepath}")
-
-        with open(media_filepath, 'rb') as img_file:
-            image = Image.open(img_file)
-
-            converted_filename = f"image.jpg"
-            converted_filepath = os.path.join(UPLOAD_FOLDER, converted_filename)
-            image.convert('RGB').save(converted_filepath, 'JPEG')
-            return converted_filepath
-
-    except requests.exceptions.HTTPError as err:
-        print(f"HTTP error occurred: {err}")
-    except Exception as err:
-        print(f"An error occurred: {err}")
 
-def get_weather(city):
-    city = city.strip().replace(' ', '+')
-    r = requests.get(f'https://www.google.com/search?q=weather+in+{city}')
-    soup = BeautifulSoup(r.text, 'html.parser')
-    temperature = soup.find('div', attrs={'class': 'BNeawe iBp4i AP7Wnd'}).text
-    return temperature
-
-from zenrows import ZenRowsClient
-Zenrow_api = os.environ.get('Zenrow_api')
-zenrows_client = ZenRowsClient(Zenrow_api)
-
-def get_rates():
-    url = "https://www.kisandeals.com/mandiprices/ALL/TAMIL-NADU/ALL"
-    response = zenrows_client.get(url)
-
-    if response.status_code == 200:
-        soup = BeautifulSoup(response.content, 'html.parser')
-        rows = soup.select('table tbody tr')
-        data = {}
-        for row in rows:
-            columns = row.find_all('td')
-            if len(columns) >= 2:
-                commodity = columns[0].get_text(strip=True)
-                price = columns[1].get_text(strip=True)
-                if '₹' in price:
-                    data[commodity] = price
-    return str(data) + " These are the prices for 1 kg"
-
-def get_news():
-    news = []
-    url = "https://economictimes.indiatimes.com/news/economy/agriculture?from=mdr"
-    response = zenrows_client.get(url)
-
-    if response.status_code == 200:
-        soup = BeautifulSoup(response.content, 'html.parser')
-        headlines = soup.find_all("div", class_="eachStory")
-        for story in headlines:
-            headline = story.find('h3').text.strip()
-            news.append(headline)
-    return news
-
-def download_and_save_as_txt(url, account_sid, auth_token):
-    try:
-        response = requests.get(url, auth=HTTPBasicAuth(account_sid, auth_token))
-        response.raise_for_status()
-
-        parsed_url = urlparse(url)
-        media_id = parsed_url.path.split('/')[-1]
-        filename = f"pdf_file.pdf"
-
-        txt_filepath = os.path.join(UPLOAD_FOLDER, filename)
-        with open(txt_filepath, 'wb') as file:
-            file.write(response.content)
-        
-        print(f"Media downloaded successfully and saved as {txt_filepath}")
-        return txt_filepath
-
-    except requests.exceptions.HTTPError as err:
-        print(f"HTTP error occurred: {err}")
-    except Exception as err:
-        print(f"An error occurred: {err}")
-
-def download_file(url, extension):
-    try:
-        response = requests.get(url)
-        response.raise_for_status()
-        filename = f"{uuid.uuid4()}{extension}"
-        file_path = os.path.join(UPLOAD_FOLDER, filename)
-        
-        with open(file_path, 'wb') as file:
-            file.write(response.content)
-        
-        print(f"File downloaded and saved as {file_path}")
-        return file_path
-
-    except requests.exceptions.HTTPError as err:
-        print(f"HTTP error occurred: {err}")
-    except Exception as err:
-        print(f"An error occurred: {err}")
-        return None
 
 @app.route('/whatsapp', methods=['POST'])
 def whatsapp_webhook():
@@ -209,7 +56,14 @@ def whatsapp_webhook():
         if content_type.startswith('image/'):
             # Handle image processing (disease/pest detection)
             filepath = convert_img(media_url, account_sid, auth_token)
-            response_text = handle_image(filepath)
+            if predict_disease(filepath):
+                
+                response_text = predict_disease(filepath)
+            elif predict_pest(filepath):
+                response_text=predict_pest(filepath)
+            else:
+                response_text = "Please upload other image with good quality."
+
         else:
             # Handle PDF processing
             filepath = download_and_save_as_txt(media_url, account_sid, auth_token)
@@ -233,28 +87,7 @@ def whatsapp_webhook():
     send_message(sender, response_text)
     return '', 204
 
-def handle_image(filepath):
-    try:
-        disease = predict_disease(filepath)
-    except:
-        disease = None
-    try:
-        pest = predict_pest(filepath)
-    except:
-        pest = None
 
-    if disease:
-        response_text = f"Detected disease: {disease}"
-        disease_info = generate_response(f"Provide brief information about {disease} in agriculture", "")
-        response_text += "\n" + disease_info
-    elif pest:
-        response_text = f"Detected pest: {pest}"
-        pest_info = generate_response(f"Provide brief information about {pest} in agriculture", "")
-        response_text += "\n" + pest_info
-    else:
-        response_text = "Sorry, I couldn't detect any disease or pest. Please try another image."
-
-    return response_text
 
 def process_and_query_pdf(filepath):
     # Read and process the PDF