Update app.py

app.py

@@ -1,11 +1,105 @@
-import google.generativeai as genai
 import os
+from dotenv import load_dotenv
+import google.generativeai as genai
+from pathlib import Path
+import gradio as gr
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Get the API key from the environment
+API_KEY = os.getenv("GOOGLE_API_KEY")
+
+# Set up the model with the API key
+genai.configure(api_key=API_KEY)
+
+# Set up the model
+generation_config = {
+    "temperature": 0.7,
+    "top_p": 0.9,
+    "top_k": 40,
+    "max_output_tokens": 4000,
+}
+
+safety_settings = [
+    {
+        "category": "HARM_CATEGORY_HARASSMENT",
+        "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+    },
+    {
+        "category": "HARM_CATEGORY_HATE_SPEECH",
+        "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+    },
+    {
+        "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
+        "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+    },
+    {
+        "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
+        "threshold": "BLOCK_MEDIUM_AND_ABOVE"
+    }
+]
+
+model = genai.GenerativeModel(model_name="gemini-pro-vision",
+                              generation_config=generation_config,
+                              safety_settings=safety_settings)
+
+def input_image_setup(file_loc):
+    if not (img := Path(file_loc)).exists():
+        raise FileNotFoundError(f"Could not find image: {img}")
+
+    image_parts = [
+        {
+            "mime_type": "image/jpeg",
+            "data": Path(file_loc).read_bytes()
+            }
+        ]
+    return image_parts
+
+def generate_gemini_response(input_prompt, text_input, image_loc):
+    image_prompt = input_image_setup(image_loc)
+    prompt_parts = [input_prompt + text_input, image_prompt[0]]
+    response = model.generate_content(prompt_parts)
+    return response.text
+
+input_prompt = """You are an advanced AI model specializing in generating engaging and contextually relevant captions or post content for social media platforms. 
+Given the context and an uploaded image, your task is to create a captivating caption or post content that resonates with the selected social media platform's audience.
+Please analyze the provided image and the contextual description carefully. Use the following guidelines based on the social media platform specified:
+
+1. **Instagram**: Focus on visually appealing, inspirational, and trendy content. Use relevant hashtags.
+2. **Facebook**: Craft engaging and personal stories or updates. Aim for a friendly and conversational tone.
+3. **Twitter**: Create concise, witty, and impactful tweets. Utilize popular hashtags and mentions.
+4. **LinkedIn**: Develop professional and insightful posts. Emphasize expertise, industry relevance, and networking.
+5. **Pinterest**: Write creative and informative descriptions. Highlight the aesthetic and practical aspects.
+
+Output should be one after another caption/post (bulleted in case of more than 1)
+
+The prompted message is: """
+
+def upload_file(files, text_input, social_media_platform, num_captions=1):
+    if not files:
+        return None, "Image not uploaded"
+    file_paths = [file.name for file in files]
+    response = generate_gemini_response(input_prompt + f"\nPlatform: {social_media_platform}\n"+ f"Number of Captions/Posts: {num_captions}\n", text_input, file_paths[0])
+    return file_paths[0], response
 
-genai.configure(api_key=os.environ["GOOGLE_API_KEY"])
+with gr.Blocks() as demo:
+    header = gr.Label("Captionify: From Image to Engagement - Get the Perfect Caption!")
+    text_input = gr.Textbox(label="Enter context for the image")
+    social_media_input = gr.Dropdown(choices=["Instagram", "Facebook", "Twitter", "LinkedIn", "Pinterest"], label="Select social media platform")
+    num_captions_input = gr.Number(label="Number of Captions/Posts")
+    image_output = gr.Image()
+    upload_button = gr.UploadButton("Click to upload an image", file_types=["image"], file_count="multiple")
+    generate_button = gr.Button("Generate")
+    
+    file_output = gr.Textbox(label="Generated Caption/Post Content")
+    
+    def process_generate(files, text_input, social_media_input, num_captions_input):
+        if not files:
+            return None, "Image not uploaded"
+        return upload_file(files, text_input, social_media_input, num_captions_input)
+    
+    upload_button.upload(fn=lambda files: files[0].name if files else None, inputs=[upload_button], outputs=image_output)
+    generate_button.click(fn=process_generate, inputs=[upload_button, text_input, social_media_input, num_captions_input], outputs=[image_output, file_output])
 
-model = genai.GenerativeModel('gemini-1.5-flash')
-response = model.generate_content(
-    text_input="the color of the car is ?", 
-    image_input="car.jpg"
-)
-print(response)
+demo.launch(debug=True)