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app.py

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+"""TravellerBuddy.ipynb
+
+Shareable file is located at
+    https://colab.research.google.com/drive/1kxJ6352BrFxdCTnQqN9maEPkGMI1FESy?usp=sharing
+
+# Gen AI
+
+---                   
+                                                              BY: SATYAM PRAKASH
+---
+"""
+
+# !pip install langchain
+# !pip install openai
+# !pip install gradio
+# !pip install huggingface_hub
+# !pip install langchain_community
+# !pip install langchain-google-genai
+
+import os
+import gradio as gr
+from langchain.chat_models import ChatOpenAI
+from langchain import LLMChain, PromptTemplate
+from langchain.memory import ConversationBufferMemory
+from langchain_google_genai import ChatGoogleGenerativeAI
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+os.environ["GOOGLE_API_KEY"] = os.getenv("GOOGLE_API_KEY")
+
+
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+# Try creating a Gemini Flash 2.0 model
+try:
+    llm = ChatGoogleGenerativeAI(model="gemini-2.5-flash", temperature=0)
+    response = llm.invoke("Hello Gemini, can you hear me?")
+    print("✅ API is working!")
+    print("Response:", response.content)
+except Exception as e:
+    print("❌ API Error:", str(e))
+
+template = """As an adventurous and globetrotting college student, you're constantly on the lookout for new cultures, experiences, and breathtaking landscapes. You've visited numerous countries, immersing yourself in local traditions, and you're always eager to swap travel stories and offer tips on exciting destinations
+{chat_history}
+User: {user_message}
+Chatbot:"""
+
+prompt = PromptTemplate(
+    input_variables=["chat_history", "user_message"], template=template
+)
+
+
+from langchain.memory import ConversationBufferMemory
+memory = ConversationBufferMemory(memory_key="chat_history")
+
+llm_chain = LLMChain(
+    llm=llm,
+    prompt=prompt,
+    memory=memory
+)
+
+def get_text_response(user_message, history):
+    # LangChain memory handles the history internally
+    response = llm_chain.predict(user_message=user_message)
+    return response
+
+# # Gradio Chat Interface
+# demo = gr.ChatInterface(
+#     fn=get_text_response,
+#     examples=[
+#         "How are you doing?",
+#         "What are your interests?",
+#         "Which places do you like to visit?"
+#     ]
+# )
+
+demo = gr.ChatInterface(get_text_response, examples=["How are you doing?","What are your interests?","Which places do you like to visit?"], type='messages')
+
+if __name__ == "__main__":
+    demo.launch() #To create a public link, set `share=True` in `launch()`. To enable errors and logs, set `debug=True` in `launch()`.