Upload 4 files

app.py

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+import gradio as gr
+from pdf_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 app:
+    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__":
+    app.launch(share=True)

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"
+            }
+    }
+}

pdf_rag.py

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+from openai import OpenAI
+from dotenv import load_dotenv
+import os
+import requests
+import PyPDF2
+
+
+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/sathyabama-be-cse-ai-pt1-07-2025-hands-on-professional-training-on-genai-and-ai-agents/main/general-profile-of-hereandnowai.pdf"
+response = requests.get(url)
+
+PDF_FILE_NAME ="profile-of-hereandnowai.pdf"
+PDF_DIR = os.path.dirname(__file__)
+PDF_PATH = os.path.join(PDF_DIR, PDF_FILE_NAME)
+
+with open(PDF_PATH, "wb") as f:
+    f.write(response.content)
+
+try:
+  with open(PDF_PATH, "rb") as file:
+    reader = PyPDF2.PdfReader(file)
+    pdf_text_chunks = []
+    for page in reader.pages:
+        page_text = page.extract_text()
+        if page_text:
+            pdf_text_chunks.append(page_text.strip())
+    pdf_context = "\n".join(pdf_text_chunks) if pdf_text_chunks else "Error extracting text from PDF file."
+except Exception as e:
+   print(f"Error reading the PDF file: {e}")
+   pdf_context = "Error extracting text from PDF file."  
+
+
+
+def get_response(message, history):
+   system_prompt = f"""context from {PDF_PATH}:\n{pdf_context}
+         \n\n Qustion:{message}
+         \n\n Answer based only on the context:"""
+   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?", []))

requirements.txt

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+openai
+python-dotenv
+gradio
+PyPDF2