Update app.py

app.py

@@ -131,11 +131,11 @@ def wandb_trace(rag_option, prompt, prompt_template, result, completion, chain_n
         },
         start_time_ms = start_time_ms,
         end_time_ms = end_time_ms,
-        inputs = {"rag_option": rag_option, "prompt": str(prompt), "prompt_template": str(prompt_template)},
-        outputs = {"result": str(result), "completion": str(completion)},
+        inputs = {{"rag_option": rag_option}, {"prompt": str(prompt)}, {"prompt_template": str(prompt_template)}},
+        outputs = {{"result": str(result)}, {"completion": str(completion)}},
         #model_dict = {"llm": str(llm)}
     )
-    trace.log("test")
+    trace.log("eval")
     wandb.finish()
 
 def invoke(openai_api_key, rag_option, prompt):
@@ -205,7 +205,7 @@ description = """<strong>Overview:</strong> Context-aware multimodal reasoning a
                  <strong>Speech-to-text</strong> via <a href='https://openai.com/research/whisper'>whisper-1</a> model, <strong>text embedding</strong> via 
                  <a href='https://openai.com/blog/new-and-improved-embedding-model'>text-embedding-ada-002</a> model, and <strong>text generation</strong> via 
                  <a href='""" + WEB_URL + """'>gpt-4</a> model. Implementation via AI-first <a href='https://www.langchain.com/'>LangChain</a> toolkit. 
-                 RAG evaluation via <a href='https://wandb.ai/bstraehle/openai-llm-rag/workspace'>Weights & Biases</a>."""
+                 Evaluation via <a href='https://wandb.ai/bstraehle/openai-llm-rag/workspace'>Weights & Biases</a>."""
 
 gr.close_all()
 demo = gr.Interface(fn=invoke,