Spaces:
Sleeping
Sleeping
| 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}") |