Update app.py

app.py

@@ -8,7 +8,23 @@ import re
 import requests
 import transformers
 import chardet
-import deepeval
+#import deepeval
+try:
+    import deepeval
+    from deepeval import evaluate
+    from deepeval.metrics import AnswerRelevancyMetric
+    from deepeval.test_case import LLMTestCase
+    DEEPEVAL_AVAILABLE = True
+except Exception as e:
+    print(f"DeepEval import failed: {e}, continuing without evaluation features")
+    DEEPEVAL_AVAILABLE = False
+    # 創建備用函數
+    def evaluate(*args, **kwargs):
+        return []
+    class AnswerRelevancyMetric:
+        def __init__(self, *args, **kwargs): pass
+    class LLMTestCase:
+        def __init__(self, *args, **kwargs): pass
 import difflib
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from transformers.models.llama.configuration_llama import LlamaConfig
@@ -274,7 +290,7 @@ def rag_llama_qa(query):
 def rag_gpt4_qa(query):
     raw_answer = qa_gpt.run(query)
 
-    if SHOW_EVAL:
+    if SHOW_EVAL and DEEPEVAL_AVAILABLE:
         try:
             top_docs = retriever.get_relevant_documents(query)
             test_case = LLMTestCase(
@@ -316,7 +332,7 @@ def upload_and_chat(file, query):
         chain_type_kwargs={"prompt": custom_prompt}
     )
     raw_answer = qa_temp.run(query)
-    if SHOW_EVAL:
+    if SHOW_EVAL and DEEPEVAL_AVAILABLE:
         try:
             test_case = LLMTestCase(
                 input=query,
@@ -1212,7 +1228,7 @@ def multi_agent_chat_advanced(query: str, file=None) -> str:
                         #answer = session_graph_chain(query)["answer"]
 
                         # ✅ DeepEval 評估僅在 Tab1 文件 QA 的情況下觸發
-                        if SHOW_EVAL:
+                        if SHOW_EVAL and DEEPEVAL_AVAILABLE:
                             try:
                                 test_case = LLMTestCase(
                                     input=query,