degbu embeddings

app.py

@@ -71,22 +71,7 @@ with st.sidebar:
         step=0.05, 
     )
 
-    max_output_tokens = 4096
-
-    # Create LLM
-    if provider == 'openai':
-        llm = OpenAI(
-            model=llm_name, 
-            temperature=temperature,
-            max_tokens=max_tokens
-        )
-        # Global tokenization needs to be consistent with LLM
-        # https://docs.llamaindex.ai/en/stable/module_guides/models/llms/
-        Settings.tokenizer = tiktoken.encoding_for_model(llm_name).encode
-        Settings.num_output = max_tokens
-        Settings.context_window = 4096 # max possible
-        Settings.embed_model = OpenAIEmbedding()
-    
+    max_output_tokens = 4096  
 
     # Enter LLM Token
     llm_token = st.text_input(
@@ -98,6 +83,21 @@ with st.sidebar:
     elif provider == 'huggingface':
         os.environ['HFTOKEN'] = llm_token
 
+    # Create LLM
+    if llm_token is not None:
+        if provider == 'openai':
+            llm = OpenAI(
+                model=llm_name, 
+                temperature=temperature,
+                max_tokens=max_tokens
+            )
+            # Global tokenization needs to be consistent with LLM
+            # https://docs.llamaindex.ai/en/stable/module_guides/models/llms/
+            Settings.tokenizer = tiktoken.encoding_for_model(llm_name).encode
+            Settings.num_output = max_tokens
+            Settings.context_window = 4096 # max possible
+            Settings.embed_model = OpenAIEmbedding()
+
     # Enter parsing Token
     parse_token = st.text_input(
         "Enter your LlamaParse token",