上传文件至「/」

.env

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+api_key=sk-69e030825cd84c7ab2b5d217d92c98ef
+base_url=https://api.deepseek.com/v1/chat/completions

DeepseekAi.py

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+import requests
+import json
+
+
+def get_response(messages, api_key, base_url):
+    """原有非流式调用（保留兼容）"""
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}"
+    }
+    data = {
+        "model": "deepseek-chat",
+        "messages": messages,
+        "temperature": 0.7,
+        "max_tokens": 2048
+    }
+
+    try:
+        response = requests.post(base_url, headers=headers, json=data, timeout=30)
+        response.raise_for_status()
+        result = response.json()
+        return result["choices"][0]["message"]["content"]
+    except requests.exceptions.HTTPError as e:
+        return f"API请求失败（HTTP错误）：{str(e)}，请检查API密钥是否正确"
+    except requests.exceptions.ConnectionError:
+        return "网络连接失败，请检查网络或API地址是否正确"
+    except Exception as e:
+        return f"请求异常：{str(e)}"
+
+
+def get_response_stream(messages, api_key, base_url):
+    """流式调用DeepSeek API"""
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}"
+    }
+    data = {
+        "model": "deepseek-chat",
+        "messages": messages,
+        "temperature": 0.7,
+        "max_tokens": 2048,
+        "stream": True  # 开启流式输出
+    }
+
+    try:
+        response = requests.post(
+            base_url,
+            headers=headers,
+            json=data,
+            timeout=30,
+            stream=True
+        )
+        response.raise_for_status()
+
+        for line in response.iter_lines():
+            if line:
+                line = line.decode("utf-8").strip()
+                if line.startswith("data: "):
+                    line = line[6:]
+                    if line == "[DONE]":
+                        break
+                    try:
+                        chunk = json.loads(line)
+                        if "choices" in chunk and len(chunk["choices"]) > 0:
+                            content = chunk["choices"][0]["delta"].get("content", "")
+                            if content:
+                                yield content
+                    except json.JSONDecodeError:
+                        continue
+    except requests.exceptions.HTTPError as e:
+        yield f"API请求失败（HTTP错误）：{str(e)}，请检查API密钥是否正确"
+    except requests.exceptions.ConnectionError:
+        yield "网络连接失败，请检查网络或API地址是否正确"
+    except Exception as e:
+        yield f"请求异常：{str(e)}"

app_stream.py

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+import streamlit as st
+import os
+from dotenv import load_dotenv
+from DeepseekAi import get_response_stream  # 导入流式函数
+
+# 第一步：加载.env配置（必须放在最前面）
+load_dotenv()
+API_KEY = os.getenv('api_key')
+BASE_URL = os.getenv('base_url')
+
+# 检查配置完整性
+if not API_KEY or not BASE_URL:
+    st.error("❌ 配置缺失：请检查.env文件中的 api_key 和 base_url 是否填写正确！")
+    st.stop()
+
+# 页面标题
+st.title("智聊机器人")
+
+# 初始化会话状态
+if "messages" not in st.session_state:
+    st.session_state["messages"] = [{"role": "assistant", "content": "你好，我是智聊机器人，有什么可以帮助你的么？"}]
+
+# 显示历史对话
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.write(message["content"])
+
+# 处理用户输入
+user_input = st.chat_input("请输入你的问题：")
+
+if user_input:
+    # 1. 添加用户消息到会话状态并显示
+    st.session_state.messages.append({"role": "user", "content": user_input})
+    with st.chat_message("user"):
+        st.write(user_input)
+
+    # 2. 流式输出AI回复
+    full_response = ""  # 存储完整回复
+    with st.chat_message("assistant"):
+        # 初始化思考状态（赋值给status变量，用于后续修改）
+        with st.status(label="🤔 正在思考中...", expanded=True) as status:
+            response_placeholder = st.empty()  # 只创建一次占位符
+
+            # 逐段获取流式内容
+            for chunk in get_response_stream(st.session_state.messages, api_key=API_KEY, base_url=BASE_URL):
+                full_response += chunk
+                # 实时更新占位符，加光标模拟打字效果
+                response_placeholder.markdown(full_response + "|")
+
+            # 核心修改：思考完成后更新状态文本
+            status.update(label="✅ 思考结束", state="complete", expanded=False)
+
+        # 3. 最终展示完整回复（保留你原有逻辑，未修改DOM渲染）
+        st.markdown(full_response)
+
+    # 4. 把完整回复存入会话状态
+    st.session_state.messages.append({"role": "assistant", "content": full_response})

requiremenm.txt

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+openai
+python-dotenv