Update app.py

app.py

@@ -45,15 +45,21 @@ def create_vector_store(chunks):
     embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
     return FAISS.from_documents(documents, embeddings)
 
-def summarize_text(text):
-    response = client.chat.completions.create(
-        model=GROQ_MODEL,
-        messages=[
-            {"role": "system", "content": "You are an AI that summarizes documents."},
-            {"role": "user", "content": f"Summarize this:\n{text}"}
-        ]
-    )
-    return response.choices[0].message.content
+def summarize_chunks(chunks):
+    chunk_summaries = []
+    for i, chunk in enumerate(chunks):
+        try:
+            response = client.chat.completions.create(
+                model=GROQ_MODEL,
+                messages=[
+                    {"role": "system", "content": "You are an AI that summarizes documents."},
+                    {"role": "user", "content": f"Summarize this chunk:\n{chunk}"}
+                ]
+            )
+            chunk_summaries.append(response.choices[0].message.content)
+        except Exception as e:
+            chunk_summaries.append(f"[Error summarizing chunk {i}]: {str(e)}")
+    return "\n".join(chunk_summaries)
 
 def ask_question(vectorstore, question):
     docs = vectorstore.similarity_search(question, k=3)
@@ -98,7 +104,7 @@ if uploaded_files:
     vectorstore = create_vector_store(chunks)
 
     st.write("📄 Generating summary...")
-    summary = summarize_text(all_text)
+    summary = summarize_chunks(chunks)
     st.success(summary)
     make_download_button(summary)