Update app.py

app.py

@@ -3,15 +3,14 @@ from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
 import PyPDF2
 import torch
 
-st.set_page_config(page_title="Perplexity-style Q&A (Mistral)", layout="wide")
-st.title("🧠 Perplexity-style AI Study Assistant using Mistral 7B")
+st.set_page_config(page_title="Perplexity-style Q&A (OpenHermes)", layout="wide")
+st.title("🧠 Perplexity-style Study Assistant with OpenHermes-2.5")
 
-# Load Mistral model and tokenizer
 @st.cache_resource
 def load_model():
-    tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
+    tokenizer = AutoTokenizer.from_pretrained("teknium/OpenHermes-2.5-Mistral-7B")
     model = AutoModelForCausalLM.from_pretrained(
-        "mistralai/Mistral-7B-Instruct-v0.1",
+        "teknium/OpenHermes-2.5-Mistral-7B",
         torch_dtype=torch.float16,
         device_map="auto"
     )
@@ -20,17 +19,11 @@ def load_model():
 
 textgen = load_model()
 
-# Extract text from uploaded PDF
 def extract_text_from_pdf(file):
     reader = PyPDF2.PdfReader(file)
-    text = ""
-    for page in reader.pages:
-        text += page.extract_text() + "\n"
-    return text.strip()
+    return "\n".join([p.extract_text() for p in reader.pages if p.extract_text()])
 
-# UI Layout
 query = st.text_input("Ask a question or enter a topic:")
-
 uploaded_file = st.file_uploader("Or upload a PDF to use as context:", type=["pdf"])
 
 context = ""
@@ -39,12 +32,9 @@ if uploaded_file:
     st.text_area("📄 Extracted PDF Text", context, height=200)
 
 if st.button("Generate Answer"):
-    with st.spinner("Generating answer with Mistral 7B..."):
-        prompt = query
-        if context:
-            prompt = f"[INST] Use the following context to answer the question:\n\n{context}\n\nQuestion: {query} [/INST]"
-        else:
-            prompt = f"[INST] {query} [/INST]"
-        output = textgen(prompt)[0]["generated_text"]
+    with st.spinner("Generating answer..."):
+        prompt = f"<|system|>You are a helpful study assistant.<|user|>Context:\n{context}\n\nQuestion: {query}<|assistant|>"
+        result = textgen(prompt)[0]["generated_text"]
+        answer = result.replace(prompt, "").strip()
         st.success("Answer:")
-        st.write(output.replace(prompt, "").strip())
+        st.write(answer)