Create app.py

app.py

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+import json
+import os
+from typing import Optional, Dict
+import aiohttp
+import chainlit as cl
+import chainlit.data as cl_data
+import requests
+from fastgpt_data import FastgptDataLayer, now, share_id, app_name, welcome_text
+
+fastgpt_base_url = os.getenv("FASTGPT_BASE_URL")
+fastgpt_api_key = os.getenv("FASTGPT_API_KEY")
+fastgpt_api_detail = os.getenv("FASTGPT_API_DETAIL", False)
+
+cl_data._data_layer = FastgptDataLayer()
+cl.config.ui.name = app_name
+
+def download_logo():
+    local_filename = "./public/favicon.svg"
+    directory = os.path.dirname(local_filename)
+    os.makedirs(directory, exist_ok=True)
+    # Streaming, so we can iterate over the response.
+    with requests.get(f"{fastgpt_base_url}/icon/logo.svg", stream=True) as r:
+        r.raise_for_status()  # Check if the request was successful
+        with open(local_filename, 'wb') as f:
+            for chunk in r.iter_content(chunk_size=8192):
+                # If you have chunk encoded response uncomment if
+                # and set chunk_size parameter to None.
+                f.write(chunk)
+
+download_logo()
+
+@cl.on_chat_start
+async def chat_start():
+    if welcome_text:
+        # elements = [cl.Text(content=welcomeText, display="inline")]
+        await cl.Message(content=welcome_text).send()
+
+@cl.on_message
+async def handle_message(message: cl.Message):
+    msg = cl.Message(content="")
+    url = f"{fastgpt_base_url}/api/v1/chat/completions"
+    print('message.thread_id', message.thread_id)
+    headers = {
+        "Authorization": f"Bearer {fastgpt_api_key}",
+        "Content-Type": "application/json"
+    }
+    data = {
+        "messages": [{"role": "user", "content": message.content}],
+        "variables": {"cTime": now},
+        "responseChatItemId": message.uiltin.id,
+        "shareId": share_id,
+        "chatId": message.thread_id,
+        "appType": "advanced",
+        "outLinkUid": cl.context.session.user.identifier,
+        "detail": fastgpt_api_detail,
+        "stream": True
+    }
+
+    async for data in fetch_sse(url, headers=headers, data=json.dumps(data), detail=fastgpt_api_detail):
+        delta = data['choices'][0]['delta']
+        if delta:
+            await msg.stream_token(delta['content'])
+    await msg.send()
+
+@cl.header_auth_callback
+def header_auth_callback(headers: Dict) -> Optional[cl.User]:
+    print(headers)
+    # 创建一个md5 hash对象
+    md5_hash = hashlib.md5()
+    user_agent_bytes = headers.get('user-agent').encode('utf-8')
+    # 更新这个hash对象的内容
+    md5_hash.update(user_agent_bytes)
+    # 获取md5哈希值的十六进制表示形式
+    md5_hex_digest = md5_hash.hexdigest()
+    out_link_uid = md5_hex_digest
+    print("MD5加密后的结果:", md5_hex_digest)
+    return cl.User(identifier=out_link_uid, display_name="visitor")
+
+@cl.on_chat_resume
+async def on_chat_resume():
+    pass
+
+async def fetch_sse(url, headers, data, detail):
+    async with aiohttp.ClientSession() as session:
+        async with session.post(url, headers=headers, data=data) as response:
+            async for line in response.content:
+                if line:  # 过滤掉空行
+                    data = line.decode('utf-8').rstrip('\n\r')
+                    # print(f"Received: {data}")
+                    # 检查是否为数据行，并且是我们感兴趣的事件类型
+                    if detail:
+                        if data.startswith('event:'):
+                            event_type = data.split(':', 1)[1].strip()  # 提取事件类型
+                        elif data.startswith('data:') and event_type == 'flowNodeStatus':
+                            data = data.split(':', 1)[1].strip()
+                            flowNodeStatus = json.loads(data)
+                            current_step = cl.context.current_step
+                            current_step.name = flowNodeStatus['name']
+                        elif data.startswith('data:') and event_type == 'answer':
+                            data = data.split(':', 1)[1].strip()  # 提取数据内容
+                            # 如果数据包含换行符，可能需要进一步处理（这取决于你的具体需求）
+                            # 这里我们简单地打印出来
+                            if data != '[DONE]':
+                                yield json.loads(data)
+                        else:
+                            if data.startswith('data:'):
+                                data = data.split(':', 1)[1].strip()  # 提取数据内容
+                                # 如果数据包含换行符，可能需要进一步处理（这取决于你的具体需求）
+                                # 这里我们简单地打印出来
+                                if data != '[DONE]':
+                                    yield json.loads(data)