Update app.py

app.py

@@ -28,12 +28,15 @@ import re
 list_llm = ["mistralai/Mistral-7B-Instruct-v0.2", "mistralai/Mixtral-8x7B-Instruct-v0.1", "mistralai/Mistral-7B-Instruct-v0.1", \
     "google/gemma-7b-it","google/gemma-2b-it", \
     "HuggingFaceH4/zephyr-7b-beta", "HuggingFaceH4/zephyr-7b-gemma-v0.1", \
-    "meta-llama/Llama-2-7b-chat-hf", "microsoft/phi-2", \
+    "meta-llama/Meta-Llama-3.1-8B-Instruct", "microsoft/phi-2", \
     "TinyLlama/TinyLlama-1.1B-Chat-v1.0", "mosaicml/mpt-7b-instruct", "tiiuae/falcon-7b-instruct", \
     "google/flan-t5-xxl"
 ]
 list_llm_simple = [os.path.basename(llm) for llm in list_llm]
 
+
+
+
 @spaces.GPU
 # Load PDF document and create doc splits
 def load_doc(list_file_path, chunk_size, chunk_overlap):
@@ -139,7 +142,7 @@ def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vector_db, pr
             max_new_tokens = 250,
             top_k = top_k,
         )
-    elif llm_model == "meta-llama/Llama-2-7b-chat-hf":
+    elif llm_model == "meta-llama/Meta-Llama-3.1-8B-Instruct":
         raise gr.Error("Llama-2-7b-chat-hf model requires a Pro subscription...")
         llm = HuggingFaceEndpoint(
             repo_id=llm_model,