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https://github.com/csunny/DB-GPT.git
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model server fix message model
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@@ -13,14 +13,16 @@ logger = build_logger("webserver", LOGDIR + "DbChatOutputParser.log")
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class PluginAction(NamedTuple):
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command: Dict
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thoughts: Dict
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speak: str
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reasoning:str
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thoughts: str
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class PluginChatOutputParser(BaseOutputParser):
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def parse_prompt_response(self, model_out_text) -> T:
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response = json.loads(super().parse_prompt_response(model_out_text))
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command, thoughts = response["command"], response["thoughts"]
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return PluginAction(command, thoughts)
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command, thoughts, speak, reasoning = response["command"], response["thoughts"], response["speak"], response["reasoning"]
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return PluginAction(command, speak, reasoning, thoughts)
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def parse_view_response(self, speak, data) -> str:
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### tool out data to table view
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@@ -37,13 +37,9 @@ Ensure the response is correct json and can be parsed by Python json.loads
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"""
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RESPONSE_FORMAT = {
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"thoughts": {
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"text": "thought",
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"reasoning": "reasoning",
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"plan": "- short bulleted\n- list that conveys\n- long-term plan",
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"criticism": "constructive self-criticism",
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"speak": "thoughts summary to say to user",
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},
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"thoughts": "thought text",
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"reasoning": "reasoning",
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"speak": "thoughts summary to say to user",
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"command": {"name": "command name", "args": {"arg name": "value"}},
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}
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@@ -8,6 +8,8 @@ from pilot.common.schema import SeparatorStyle
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from pilot.scene.chat_normal.out_parser import NormalChatOutputParser
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PROMPT_SCENE_DEFINE = """A chat between a curious user and an artificial intelligence assistant, who very familiar with database related knowledge.
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The assistant gives helpful, detailed, professional and polite answers to the user's questions. """
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CFG = Config()
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@@ -19,7 +21,7 @@ prompt = PromptTemplate(
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template_scene=ChatScene.ChatNormal.value,
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input_variables=["input"],
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response_format=None,
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template_define=None,
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template_define=PROMPT_SCENE_DEFINE,
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template=None,
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stream_out=PROMPT_NEED_NEED_STREAM_OUT,
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output_parser=NormalChatOutputParser(
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@@ -27,5 +29,4 @@ prompt = PromptTemplate(
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),
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)
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CFG.prompt_templates.update({prompt.template_scene: prompt})
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