MIXSHARE
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Parent(s):
6453f68
Update app.py
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app.py
CHANGED
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@@ -2,23 +2,13 @@ import gradio as gr
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import os
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import openai
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# 请记得要把 api 的 key 放到 settings 下面的 Repository Secrets 里。
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openai.api_key = os.getenv("openai_key")
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# 如果你只打算通过 prompt 来定制机器人的行为,只需要修改这段 prompt 就够了。
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prompt = '请你调用你能获取的所有的博物百科资源库,用小助手的口吻来回答问题,开头第一句是你好啊,好奇宝宝!结尾是有没有解答你的疑惑呢?欢迎继续提问!由于是面向青少年儿童,请务必做到内容有理有据语言风格有趣生动,附上来源出处'
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history = {}
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# p: 对机器人说话的内容
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# qid: 当前消息的唯一标识。例如 `'bxqid-cManAtRMszw...'`。由平台生成并传递给机器人,以便机器人区分单个问题(写日志、追踪调试、异步回调等)。同步调用可忽略。
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# uid: 用户的唯一标识。例如`'bxuid-Aj8Spso8Xsp...'`。由平台生成并传递给机器人,以便机器人区分用户。可被用于实现多轮对话的功能。
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# 返回值:[type, content]
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# 详见 https://huggingface.co/spaces/baixing/hackathon_test/blob/main/bot-api.md
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def chat(p, qid, uid):
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# 找出该 uid 对应的历史对话
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global history
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if uid in history:
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msgs = history[uid]
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@@ -26,19 +16,22 @@ def chat(p, qid, uid):
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msgs = []
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response = callapi(p, msgs)
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def callapi(p, msgs):
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if (len(msgs) > 8):
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msgs = msgs[-8:]
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data = [{"role":"system", "content":prompt}]
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for m in msgs:
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data = data + [
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{"role":"user", "content":m[
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{"role":"assistant", "content":m[
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]
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data = data + [{"role":"user", "content":p}]
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response = openai.ChatCompletion.create(
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@@ -52,10 +45,9 @@ def callapi(p, msgs):
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return response
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iface = gr.Interface(fn=chat,
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inputs=["text", "text", "text"],
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outputs=["text", "text"],
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description="""这是一个面向青少年儿童的博物百科全书问答助手,希望能够让你天马行空的想象力和好奇心得到满足!
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""")
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import os
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import openai
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openai.api_key = os.getenv("openai_key")
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prompt = '请你调用你能获取的所有的博物百科资源库,用小助手的口吻来回答问题,开头第一句是你好啊,好奇宝宝!结尾是有没有解答你的疑惑呢?欢迎继续提问!由于是面向青少年儿童,请务必做到内容有理有据语言风格有趣生动,附上来源出处'
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history = {}
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def chat(p, qid, uid, rating=None):
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global history
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if uid in history:
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msgs = history[uid]
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msgs = []
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response = callapi(p, msgs)
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if rating is not None and len(msgs) > 0:
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msgs[-1]["rating"] = rating
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history[uid] = msgs + [{"question": p, "answer": response}]
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return ["text", response]
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def callapi(p, msgs):
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if (len(msgs) > 8):
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msgs = msgs[-8:]
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data = [{"role":"system", "content":prompt}]
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for m in msgs:
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data = data + [
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{"role":"user", "content":m["question"]},
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{"role":"assistant", "content":m["answer"]}
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]
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data = data + [{"role":"user", "content":p}]
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response = openai.ChatCompletion.create(
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return response
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iface = gr.Interface(fn=chat,
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inputs=["text", "text", "text", gr.inputs.Slider(minimum=1, maximum=5, step=1, default=None, label="评分")],
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outputs=["text", "text"],
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description="""这是一个面向青少年儿童的博物百科全书问答助手,希望能够让你天马行空的想象力和好奇心得到满足!
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""")
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iface.launch()
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