Upload gitaAssis-grad.py

gitaAssis-grad.py

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+import gradio as gr
+from langchain_core.messages import HumanMessage, AIMessage, SystemMessage
+from langchain_groq import ChatGroq
+
+# Session-wide context
+conversation_history = [SystemMessage(content="You are a Spiritual Gita AI assistant")]
+
+def gita_chat(api_key, user_input):
+    if not api_key:
+        return "⚠️ Please enter your Groq API key.", ""
+
+    # Initialize model using the API key
+    chat = ChatGroq(model="gemma2-9b-it", temperature=0.5, api_key=api_key)
+
+    # Add user message
+    conversation_history.append(HumanMessage(content=user_input))
+    
+    # Generate response
+    response = chat.invoke(conversation_history)
+    
+    # Add bot message
+    conversation_history.append(AIMessage(content=response.content))
+
+    # Format full chat log
+    chat_log = ""
+    for msg in conversation_history:
+        if isinstance(msg, SystemMessage):
+            chat_log += f"⚙️ *System Role*: {msg.content}\n\n"
+        elif isinstance(msg, HumanMessage):
+            chat_log += f"👤 **User**: {msg.content}\n\n"
+        elif isinstance(msg, AIMessage):
+            chat_log += f"🤖 **Bot**: {msg.content}\n\n"
+    
+    return response.content, chat_log
+
+# Build Gradio UI
+with gr.Blocks() as demo:
+    gr.Markdown("# 🕉️ Conversational Gita Assistant")
+    gr.Markdown(
+        "This chatbot is designed to offer spiritual guidance, inspired by the teachings of the **Bhagavad Gita**. 🌿\n\n"
+        "It has been initialized as a **Spiritual Gita AI assistant** — ready to answer questions and share verses with a compassionate and thoughtful tone. ✨\n\n"
+        "Enter your Groq API key to begin the conversation:"
+    )
+
+    api_key_input = gr.Textbox(label="🔐 Groq API Key", type="password")
+    user_input = gr.Textbox(label="🧘 Your Question or Prompt")
+    ask_button = gr.Button("Ask")
+
+    bot_response = gr.Textbox(label="📖 Response", interactive=False)
+    full_history = gr.Markdown()
+
+    ask_button.click(
+        fn=gita_chat,
+        inputs=[api_key_input, user_input],
+        outputs=[bot_response, full_history]
+    )
+
+demo.launch()