Update utils/doi.py

utils/doi.py

@@ -1,97 +1,97 @@
-import base64
-import requests
-import os
-import logging
-from dotenv import load_dotenv
-
-# Load environment variables
-load_dotenv()
-
-# Configure logging
-logging.basicConfig(
-    level=logging.INFO,
-    format="%(asctime)s - %(levelname)s - %(message)s",
-    handlers=[
-        logging.StreamHandler(),  # Log to console
-        logging.FileHandler("api_request_logs.log")  # Log to a file
-    ]
-)
-
-# Get the API key from environment variable
-GROQ_API_KEY = "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"
-if not GROQ_API_KEY:
-    raise ValueError("GROQ_API_KEY is not set in the .env file")
-
-def process_image_and_get_description(image_path, model="llama-3.2-90b-vision-preview", retries=3):
-    """
-    Process the image using the Groq API and get a description.
-    Retries in case of failure.
-
-    Args:
-        image_path (str): Path to the image.
-        model (str): Model to use for processing.
-        retries (int): Number of retries before giving up.
-
-    Returns:
-        str: Description of the image or an error message.
-    """
-    encoded_image = image_path
-    # # Encode the image to base64
-    # try:
-    #     with open(image_path, "rb") as image_file:
-    #         encoded_image = base64.b64encode(image_file.read()).decode("utf-8")
-    #     logging.info("Successfully encoded the image to base64.")
-    # except Exception as e:
-    #     logging.error(f"Error encoding the image: {e}")
-    #     return "Error encoding the image."
-
-    # Prepare the message payload
-    messages = [
-        {
-            "role": "user",
-            "content": [
-                {"type": "text", "text": "Analyze the image to identify what is happening, describe the overall context, and perform OCR to extract any visible text. Additionally, specify whether the subject is a human, animal, or object, and provide a detailed description of any object the human is holding or their specific actions."},
-                {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"}}
-            ]
-        }
-    ]
-
-    for attempt in range(1, retries + 1):
-        try:
-            logging.info(f"Attempt {attempt} to process the image with Groq API.")
-
-            # Make the API request
-            response = requests.post(
-                "https://api.groq.com/openai/v1/chat/completions",
-                json={
-                    "model": model,
-                    "messages": messages,
-                    "max_tokens": 4096,
-                    "stop": None,
-                    "stream": False
-                },
-                headers={
-                    "Authorization": f"Bearer {GROQ_API_KEY}",
-                    "Content-Type": "application/json"
-                },
-                timeout=30
-            )
-
-            # Process the response
-            if response.status_code == 200:
-                result = response.json()
-                answer = result["choices"][0]["message"]["content"]
-                logging.info("Successfully processed the image and received a response.")
-                return answer
-            else:
-                logging.warning(f"Received error response: {response.status_code} - {response.text}")
-        except requests.RequestException as e:
-            logging.error(f"RequestException on attempt {attempt}: {e}")
-
-    logging.error("All attempts to process the image failed.")
-    return "Error: Unable to process the image after multiple attempts."
-
-# # Example usage
-# image_path = r"/content/temp.jpeg"
-# description = process_image_and_get_description(image_path)
-# print(description)
+import base64
+import requests
+import os
+import logging
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+# Configure logging
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s",
+    handlers=[
+        logging.StreamHandler(),  # Log to console
+        logging.FileHandler("api_request_logs.log")  # Log to a file
+    ]
+)
+
+# Get the API key from environment variable
+GROQ_API_KEY = os.getenv("GROQ_API_KEY2")
+if not GROQ_API_KEY:
+    raise ValueError("GROQ_API_KEY is not set in the .env file")
+
+def process_image_and_get_description(image_path, model="llama-3.2-90b-vision-preview", retries=3):
+    """
+    Process the image using the Groq API and get a description.
+    Retries in case of failure.
+
+    Args:
+        image_path (str): Path to the image.
+        model (str): Model to use for processing.
+        retries (int): Number of retries before giving up.
+
+    Returns:
+        str: Description of the image or an error message.
+    """
+    encoded_image = image_path
+    # # Encode the image to base64
+    # try:
+    #     with open(image_path, "rb") as image_file:
+    #         encoded_image = base64.b64encode(image_file.read()).decode("utf-8")
+    #     logging.info("Successfully encoded the image to base64.")
+    # except Exception as e:
+    #     logging.error(f"Error encoding the image: {e}")
+    #     return "Error encoding the image."
+
+    # Prepare the message payload
+    messages = [
+        {
+            "role": "user",
+            "content": [
+                {"type": "text", "text": "Analyze the image to identify what is happening, describe the overall context, and perform OCR to extract any visible text. Additionally, specify whether the subject is a human, animal, or object, and provide a detailed description of any object the human is holding or their specific actions."},
+                {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{encoded_image}"}}
+            ]
+        }
+    ]
+
+    for attempt in range(1, retries + 1):
+        try:
+            logging.info(f"Attempt {attempt} to process the image with Groq API.")
+
+            # Make the API request
+            response = requests.post(
+                "https://api.groq.com/openai/v1/chat/completions",
+                json={
+                    "model": model,
+                    "messages": messages,
+                    "max_tokens": 4096,
+                    "stop": None,
+                    "stream": False
+                },
+                headers={
+                    "Authorization": f"Bearer {GROQ_API_KEY}",
+                    "Content-Type": "application/json"
+                },
+                timeout=30
+            )
+
+            # Process the response
+            if response.status_code == 200:
+                result = response.json()
+                answer = result["choices"][0]["message"]["content"]
+                logging.info("Successfully processed the image and received a response.")
+                return answer
+            else:
+                logging.warning(f"Received error response: {response.status_code} - {response.text}")
+        except requests.RequestException as e:
+            logging.error(f"RequestException on attempt {attempt}: {e}")
+
+    logging.error("All attempts to process the image failed.")
+    return "Error: Unable to process the image after multiple attempts."
+
+# # Example usage
+# image_path = r"/content/temp.jpeg"
+# description = process_image_and_get_description(image_path)
+# print(description)