Update other_function.py

other_function.py

@@ -1,64 +1,83 @@
-import os
-import requests
-from requests.auth import HTTPBasicAuth
-from PIL import Image
-from io import BytesIO
-from urllib.parse import urlparse
-import os
-
-
-from inference_sdk import InferenceHTTPClient
-import base64
-UPLOAD_FOLDER = '/code/uploads'
-if not os.path.exists(UPLOAD_FOLDER):
-    os.makedirs(UPLOAD_FOLDER)
-
-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['predicted_classes'][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:
-        # Make the request to the media URL with authentication
-        response = requests.get(url, auth=HTTPBasicAuth(account_sid, auth_token))
-        response.raise_for_status()  # Raise an error for bad responses
-
-        # Determine a filename from the URL
-        parsed_url = urlparse(url)
-        media_id = parsed_url.path.split('/')[-1]  # Get the last part of the URL path
-        filename = f"downloaded_media_{media_id}"
-
-        # Save the media content to a file
-        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}")
-
-        # Convert the saved media file to an image
-        with open(media_filepath, 'rb') as img_file:
-            image = Image.open(img_file)
-
-            # Optionally, convert the image to JPG and save in UPLOAD_FOLDER
-            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:
+import os
+import requests
+from requests.auth import HTTPBasicAuth
+from PIL import Image
+from io import BytesIO
+from urllib.parse import urlparse
+import os
+from pypdf import PdfReader
+from ai71 import AI71
+import os
+
+from inference_sdk import InferenceHTTPClient
+import base64
+UPLOAD_FOLDER = '/code/uploads'
+if not os.path.exists(UPLOAD_FOLDER):
+    os.makedirs(UPLOAD_FOLDER)
+
+AI71_API_KEY = os.environ.get('AI71_API_KEY')
+def generate_response(query):
+    response = ''
+    for chunk in AI71(AI71_API_KEY).chat.completions.create(
+            model="tiiuae/falcon-180b-chat",
+            messages=[
+                {"role": "system", "content": "You are a best agricultural assistant.Remember to give response not more than 2 sentence"},
+                {"role": "user",
+                 "content": f'''Answer the query:{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['predicted_classes'][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:
+        # Make the request to the media URL with authentication
+        response = requests.get(url, auth=HTTPBasicAuth(account_sid, auth_token))
+        response.raise_for_status()  # Raise an error for bad responses
+
+        # Determine a filename from the URL
+        parsed_url = urlparse(url)
+        media_id = parsed_url.path.split('/')[-1]  # Get the last part of the URL path
+        filename = f"downloaded_media_{media_id}"
+
+        # Save the media content to a file
+        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}")
+
+        # Convert the saved media file to an image
+        with open(media_filepath, 'rb') as img_file:
+            image = Image.open(img_file)
+
+            # Optionally, convert the image to JPG and save in UPLOAD_FOLDER
+            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}")