coding

app.py

@@ -58,6 +58,15 @@ if "temperature" not in st.session_state:
     st.session_state.temperature = ''
 if "max_length" not in st.session_state:
     st.session_state.max_length = ''
+
+def get_answer(prompt):
+    answer = st.session_state.llm.invoke(prompt)
+    # 去掉 prompt 的内容
+    answer = answer.replace(prompt, "").strip()
+    st.success("答案已经生成！")
+    print("答案已经生成！")
+    return answer
+
 def answer_question(repo_id, temperature, max_length, question):
     # 初始化 Gemma 模型
     if repo_id != st.session_state.repo_id or temperature != st.session_state.temperature or max_length != st.session_state.max_length:
@@ -91,12 +100,9 @@ def answer_question(repo_id, temperature, max_length, question):
             print("本地数据集筛选完成！")
 
         with st.spinner("正在生成答案..."):
-            answer = st.session_state.llm.invoke(prompt)
-            # 去掉 prompt 的内容
-            answer = answer.replace(prompt, "").strip()
-            st.success("答案已经生成！")
-            print("答案已经生成！")
-        return {"prompt": prompt, "answer": answer}
+            pure_answer = get_answer(question)
+            answer = get_answer(prompt)
+        return {"prompt": prompt, "answer": answer, "pure_answer": pure_answer}
     except Exception as e:
         st.error(f"问答过程出错：{e}")
         return {"prompt": "", "answer": "An error occurred during the answering process."}
@@ -117,6 +123,10 @@ def generate_answer(repo_id, temperature, max_length, question):
     result = answer_question(repo_id, float(temperature), int(max_length), question)
     print('prompt: ' + result["prompt"])
     print('answer: ' + result["answer"])
+    print('pure_answer: ' + result["pure_answer"])
+    st.write("生成答案(无参考)：")
+    st.write(result["pure_answer"])
+    st.divider()
     st.write("参考文字：")
     st.markdown(result["prompt"].replace('\n', '<br/>'))
     st.write("生成答案：")