Upload 3 files

app.py

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+import gradio as gr
+import os
+from dataset_loader import load_dataset
+from dotenv import load_dotenv
+
+load_dotenv()
+
+if not os.path.isdir("cytron_recommendation_chatbot_data"):
+    load_dataset()
+
+from cytron_recommendation_chatbot_data.utils import run_conversation
+
+
+# Initialize the conversation
+conversation = []
+
+
+def respond_to_input(user_input):
+    response = run_conversation(user_input)
+
+    return response
+
+
+# Create the Gradio interface
+iface = gr.Interface(
+    title="Cytron Chatbot",
+    fn=respond_to_input,
+    inputs="text",
+    outputs="text",
+    description=(
+        "This is a chatbot for Cytron Technologies. Ask me anything related to electronics for projects!\n\n"
+        "Note: This chatbot does not implement memory module, ask specific questions and don't expect it to remember previous conversation.\n"
+    ),
+)
+
+# Launch the app
+iface.launch()

dataset_loader.py

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+from huggingface_hub import Repository
+from huggingface_hub import login
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+
+def load_dataset():
+    login(token=os.getenv("HUB_TOKEN"))
+
+    repo = Repository(
+        local_dir="cytron_recommendation_chatbot_data",
+        repo_type="dataset",
+        clone_from="cjzhi98/cytron_recommendation_chatbot",
+        token=True,
+    )
+    repo.git_pull()

requirements.txt

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+openai
+python-dotenv
+numpy
+boto3
+gradio
+prettyprint