Update streamlit_app.py

streamlit_app.py

@@ -294,7 +294,7 @@ if active_df is not None and not active_df.empty:
                     
                     messages = [{"role": "user", "content": prompt}]
                     try:
-                        briefing_client = InferenceClient("meta-llama/Llama-3.1-8B-Instruct", token=os.getenv("HF_TOKEN"))
+                        briefing_client = InferenceClient("Qwen/Qwen2.5-7B-Instruct", token=os.getenv("HF_TOKEN"))
                         response = briefing_client.chat_completion(messages, max_tokens=500, temperature=0.2)
                         st.session_state.exec_briefing = response.choices[0].message.content
                         st.rerun()
@@ -331,7 +331,7 @@ if active_df is not None and not active_df.empty:
                     hf_token = os.getenv("HF_TOKEN")
                     
                     if hf_token:
-                        ui_client = InferenceClient("meta-llama/Llama-3.1-8B-Instruct", token=hf_token)
+                        ui_client = InferenceClient("Qwen/Qwen2.5-7B-Instruct", token=hf_token)
                         for i in range(num_clusters):
                             cluster_df = weekly_df[weekly_df['cluster'] == i]
                             sample_texts = "\n".join(cluster_df['title'].head(8).tolist())