Upload 4 files

branding.json

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+{
+    "brand":
+    {
+        "organizationName": "HERE AND NOW AI",
+        "website": "https://hereandnowai.com",
+        "email": "info@hereandnowai.com",
+        "mobile": "+91 996 296 1000",
+        "slogan": "designed with passion for innovation",
+        "colors": {"primary": "#FFDF00", "secondary": "#004040"},
+        "logo":
+            {
+                "title": "https://raw.githubusercontent.com/hereandnowai/images/refs/heads/main/logos/logo-of-here-and-now-ai.png",
+                "favicon": "https://raw.githubusercontent.com/hereandnowai/images/refs/heads/main/logos/favicon-logo-with-name.png"}, "chatbot": {"avatar": "https://raw.githubusercontent.com/hereandnowai/images/refs/heads/main/logos/caramel.jpeg", "face": "https://raw.githubusercontent.com/hereandnowai/images/refs/heads/main/logos/caramel-face.jpeg"
+            },
+        
+        "socialMedia":
+            {
+                "blog": "https://hereandnowai.com/blog",
+                "linkedin": "https://www.linkedin.com/company/hereandnowai/",
+                "instagram": "https://instagram.com/hereandnow_ai",
+                "github": "https://github.com/hereandnowai",
+                "x": "https://x.com/hereandnow_ai",
+                "youtube": "https://youtube.com/@hereandnow_ai"
+            }
+    }
+}

requirements.txt

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+openai
+python-dotenv
+gradio

text_rag.py

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+from openai import OpenAI
+from dotenv import load_dotenv
+import os
+import requests 
+
+load_dotenv()
+api_key = os.getenv("GEMINI_API_KEY")
+model = "gemini-2.5-flash-lite"
+base_url = "https://generativelanguage.googleapis.com/v1beta/openai/"
+
+client = OpenAI(base_url=base_url, api_key=api_key)
+
+url="https://raw.githubusercontent.com/hereandnowai/vac/refs/heads/master/prospectus-context.txt"
+response = requests.get(url)
+
+script_dir = os.path.dirname(os.path.abspath(__file__))
+file_path = os.path.join(script_dir, "profile-of-hereandnowai.txt")
+
+with open(file_path, "wb") as f:
+    f.write(response.content)
+
+text_path =file_path
+
+try:
+    with open(text_path, "r",encoding="utf-8") as file:
+        text_lines = file.readlines()
+        text_content = "\n".join([line.strip() for line in text_lines if line.strip()])
+except Exception as e:
+    print(f"Error reading the text file: {e}")
+    text_content = "Error extracting text from text file."
+
+system_prompt =f"""You are Caramel AI, ai assistant build by Here and Now AI.Answer the user's question based only on the following context:\n\n{text_content}"""
+
+def get_response(message, history):
+    messages = [{"role": "system", "content": system_prompt}]
+    messages.extend(history)
+    messages.append({"role": "user", "content": message})
+    response = client.chat.completions.create(model=model, messages=messages)
+    ai_response = response.choices[0].message.content
+    return ai_response
+
+print(get_response("who is the ceo of here and now ai?", []))    

ui-project-3.py

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+import gradio as gr
+from text_rag import get_response
+import json
+import os
+
+with open(os.path.abspath(os.path.join(os.path.dirname(__file__), "branding.json"))) as f:
+    brand_info = json.load(f)["brand"]
+
+with gr.Blocks(theme="default", title=brand_info["organizationName"]) as rag_bot:
+    gr.HTML(f"""
+            <div style="display: flex; justify-content:center; margin-bottom:20px">
+            <img src="{brand_info["logo"]["title"]}" alt="{brand_info["organizationName"]} Logo" style="width:200px;height:40px">
+            </div> """)
+    
+    gr.ChatInterface(
+        fn=get_response,
+        chatbot=gr.Chatbot(height=500, avatar_images=(None, brand_info["chatbot"]["avatar"]), type="messages"),
+        title=brand_info["organizationName"],
+        description=brand_info["slogan"],
+        type="messages",
+        examples=[
+            ["Who is the CEO of Here and Now AI?"],
+            ["What is the mission of Here and Now AI?"],
+            ["Tell me about the team behind Here and Now AI."]
+           
+        ]
+    )    
+
+if __name__ == "__main__":
+    rag_bot.launch()