Update app.py

app.py

@@ -1,64 +1,54 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+import requests
+import os
 
-"""
-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")
+# Set your Groq API key (store it as an environment variable or replace directly here)
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
 
+def explain_term(term):
+    prompt = f"""
+You are EngGloss, an expert AI tutor who explains engineering terms in a clear, structured, and beginner-friendly way. 
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+When given an engineering term, respond using this exact format and tone:
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+🔍 Term: {term}
 
-    messages.append({"role": "user", "content": message})
+📘 Simple Explanation: Give a short, easy-to-understand explanation suitable for beginners. Avoid technical jargon and keep it clear and friendly.
 
-    response = ""
+🧠 Real-World Analogy: Provide a simple, relatable analogy from everyday life that helps make the concept intuitive.
 
-    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
+📐 Typical Formula: If a standard formula is associated with the term, include it. Then explain each variable briefly. If no common formula exists, say: “No standard formula is commonly used for this term.”
 
-        response += token
-        yield response
+🏗️ Engineering Applications: List 2–3 fields of engineering where this term is frequently used or applied.
 
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+Keep the entire explanation concise, well-organized, and ideally under 150 words. Do not add any extra sections or commentary.
 """
-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)",
-        ),
-    ],
-)
 
+    headers = {
+        "Authorization": f"Bearer {GROQ_API_KEY}",
+        "Content-Type": "application/json"
+    }
+
+    data = {
+        "model": "llama3-8b-8192",
+        "messages": [{"role": "user", "content": prompt}],
+        "temperature": 0.7
+    }
+
+    response = requests.post("https://api.groq.com/openai/v1/chat/completions", headers=headers, json=data)
+    result = response.json()
+
+    return result["choices"][0]["message"]["content"]
+
+# Gradio Interface
+demo = gr.Interface(
+    fn=explain_term,
+    inputs=gr.Textbox(label="Enter an Engineering Term"),
+    outputs=gr.Markdown(label="Explanation"),
+    title="EngGloss - Engineering Term Explainer",
+    description="Get a beginner-friendly explanation for any engineering term.",
+)
 
 if __name__ == "__main__":
     demo.launch()
+