Upload 2 files

app.py

@@ -1,64 +1,71 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from transformers import pipeline
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# Initialize the model
+chatbot = pipeline("text-generation", model="microsoft/DialoGPT-medium")
 
+# Dictionary of scientist information
+SCIENTISTS = {
+    "Albert Einstein": {
+        "intro": "theoretical physicist known for the theory of relativity",
+        "style": "I speak with enthusiasm about physics and use thought experiments to explain complex ideas.",
+    },
+    "Marie Curie": {
+        "intro": "physicist and chemist who conducted pioneering research on radioactivity",
+        "style": "I am precise in my explanations and passionate about scientific research.",
+    },
+    "Nikola Tesla": {
+        "intro": "inventor and electrical engineer",
+        "style": "I share my visions about electricity and the future of technology with great enthusiasm.",
+    }
+}
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+def chat_with_scientist(scientist, question):
+    # Create a prompt based on the scientist
+    info = SCIENTISTS[scientist]
+    prompt = f"""You are {scientist}, {info['intro']}. {info['style']}
+    
+    Question: {question}
+    Answer as {scientist}:"""
+    
+    # Generate response
+    response = chatbot(
+        prompt,
+        max_length=150,
+        num_return_sequences=1,
+        temperature=0.7,
+        do_sample=True
+    )
+    
+    return response[0]['generated_text']
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=chat_with_scientist,
+    inputs=[
+        gr.Dropdown(
+            choices=list(SCIENTISTS.keys()),
+            label="Choose a Scientist",
+            value="Albert Einstein"
         ),
+        gr.Textbox(
+            placeholder="Ask your question here...",
+            label="Your Question"
+        )
     ],
+    outputs=gr.Textbox(label="Scientist's Response"),
+    title="Chat with Historical Scientists",
+    description="""Welcome to the Scientific Time Machine! 
+    Choose a scientist and ask them questions about their work, life, or scientific concepts.
+    This is an educational tool to help students engage with historical scientists.""",
+    examples=[
+        ["Albert Einstein", "Can you explain E=mc² in simple terms?"],
+        ["Marie Curie", "What inspired you to study radioactivity?"],
+        ["Nikola Tesla", "Tell me about your work with electricity."]
+    ],
+    theme=gr.themes.Soft()
 )
 
-
+# Launch the app
 if __name__ == "__main__":
     demo.launch()

requirements.txt

@@ -1 +1,3 @@
-huggingface_hub==0.25.2
+gradio
+transformers
+torch