support multiturn training like FastChat
Former-commit-id: 629cafb1a09924e82d7ea1f9fba318d3f5593196
This commit is contained in:
hiyouga
@@ -1,4 +1,4 @@
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from typing import Optional
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from typing import List, Optional
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from dataclasses import dataclass
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@@ -8,89 +8,131 @@ class Template:
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name: str
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def __post_init__(self):
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assert hasattr(self, "_format_{}".format(self.name)), "Template {} does not exist.".format(self.name)
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if self.name == "vanilla":
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r"""
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Supports language model inference without histories.
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"""
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self._register_template(
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prefix="",
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prompt="",
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sep="",
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use_history=False
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)
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elif self.name == "alpaca":
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r"""
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Supports: https://huggingface.co/tatsu-lab/alpaca-7b-wdiff
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https://github.com/ymcui/Chinese-LLaMA-Alpaca
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"""
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self._register_template(
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prefix="Below is an instruction that describes a task. "
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"Write a response that appropriately completes the request.\n\n",
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prompt="### Instruction:\n{query}\n\n### Response:\n",
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sep="\n\n",
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use_history=True
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)
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elif self.name == "vicuna":
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r"""
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Supports: https://huggingface.co/lmsys/vicuna-7b-delta-v1.1
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https://huggingface.co/lmsys/vicuna-13b-delta-v1.1
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"""
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self._register_template(
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prefix="A chat between a curious user and an artificial intelligence assistant. "
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"The assistant gives helpful, detailed, and polite answers to the user's questions.",
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prompt="USER: {query} ASSISTANT: ",
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sep="</s>",
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use_history=True
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)
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elif self.name == "belle":
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r"""
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Supports: https://huggingface.co/BelleGroup/BELLE-LLaMA-EXT-13B
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"""
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self._register_template(
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prefix="",
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prompt="Human: {query}\n\nBelle: ",
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sep="\n\n",
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use_history=True
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)
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elif self.name == "linly":
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r"""
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Supports: https://github.com/CVI-SZU/Linly
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"""
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self._register_template(
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prefix="",
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prompt="User: {query}\nBot: ",
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sep="\n",
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use_history=True
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)
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elif self.name == "billa":
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r"""
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Supports: https://github.com/Neutralzz/BiLLa
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"""
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self._register_template(
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prefix="",
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prompt="Human: {query}\nAssistant: ",
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sep="\n",
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use_history=True
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)
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elif self.name == "ziya":
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r"""
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Supports: https://huggingface.co/IDEA-CCNL/Ziya-LLaMA-13B-v1
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"""
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self._register_template(
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prefix="",
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prompt="<human>:{query}\n<bot>:",
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sep="\n",
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use_history=True
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)
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elif self.name == "aquila":
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r"""
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Supports: https://huggingface.co/qhduan/aquilachat-7b
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"""
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self._register_template(
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prefix="A chat between a curious human and an artificial intelligence assistant. "
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"The assistant gives helpful, detailed, and polite answers to the human's questions.",
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prompt="Human: {query}\nAssistant: ",
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sep="###",
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use_history=True
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)
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else:
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raise ValueError("Template {} does not exist.".format(self.name))
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def get_prompt(self, query: str, history: Optional[list] = None, prefix: Optional[str] = "") -> str:
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return getattr(self, "_format_{}".format(self.name))(query, history, prefix)
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def _format_vanilla(self, query: str, history: Optional[list], prefix: Optional[str] = "") -> str:
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r"""
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Use for language model inference without histories.
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Returns a string containing prompt without response.
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"""
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return query
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return "".join(self._format_example(query, history, prefix))
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def _format_alpaca(self, query: str, history: Optional[list], prefix: Optional[str] = "") -> str:
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def get_dialog(self, query: str, resp: str, history: Optional[list] = None, prefix: Optional[str] = "") -> List[str]:
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r"""
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Supports: https://huggingface.co/tatsu-lab/alpaca-7b-wdiff
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https://github.com/ymcui/Chinese-LLaMA-Alpaca
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Returns a list containing 2 * n elements where the 2k-th is a query and the (2k+1)-th is a response.
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"""
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if prefix:
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prompt = prefix
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else:
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prompt = "Below is an instruction that describes a task. "
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prompt += "Write a response that appropriately completes the request.\n\n"
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if history:
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for old_query, response in history:
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prompt += "### Instruction:\n{}\n\n### Response:\n{}\n\n".format(old_query, response)
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prompt += "### Instruction:\n{}\n\n### Response:\n".format(query)
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return prompt
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return self._format_example(query, history, prefix) + [resp]
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def _format_vicuna(self, query: str, history: Optional[list], prefix: Optional[str] = "") -> str:
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r"""
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Supports: https://huggingface.co/lmsys/vicuna-7b-delta-v1.1
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https://huggingface.co/lmsys/vicuna-13b-delta-v1.1
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"""
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if prefix:
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prompt = prefix
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else:
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prompt = "A chat between a curious user and an artificial intelligence assistant. "
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prompt += "The assistant gives helpful, detailed, and polite answers to the user's questions. "
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if history:
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for old_query, response in history:
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prompt += "USER: {} ASSISTANT: {}</s>".format(old_query, response)
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prompt += "USER: {} ASSISTANT: ".format(query)
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return prompt
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def _register_template(self, prefix: str, prompt: str, sep: str, use_history: Optional[bool] = True) -> None:
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self.prefix = prefix
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self.prompt = prompt
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self.sep = sep
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self.use_history = use_history
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def _format_belle(self, query: str, history: Optional[list], prefix: Optional[str] = "") -> str:
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r"""
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Supports: https://huggingface.co/BelleGroup/BELLE-LLaMA-EXT-13B
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"""
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prompt = prefix
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if history:
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for old_query, response in history:
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prompt += "Human: {}\n\nBelle: {}\n\n".format(old_query, response)
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prompt += "Human: {}\n\nBelle: ".format(query)
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return prompt
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def _format_linly(self, query: str, history: Optional[list], prefix: Optional[str] = "") -> str:
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r"""
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Supports: https://github.com/CVI-SZU/Linly
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"""
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prompt = prefix
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if history:
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for old_query, response in history:
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prompt += "User: {}\nBot: {}\n".format(old_query, response)
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prompt += "User: {}\nBot: ".format(query)
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return prompt
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def _format_billa(self, query: str, history: Optional[list], prefix: Optional[str] = "") -> str:
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r"""
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Supports: https://github.com/Neutralzz/BiLLa
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"""
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prompt = prefix
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if history:
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for old_query, response in history:
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prompt += "Human: {}\nAssistant: {}\n".format(old_query, response)
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prompt += "Human: {}\nAssistant: ".format(query)
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return prompt
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def _format_ziya(self, query: str, history: Optional[list], prefix: Optional[str] = "") -> str:
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r"""
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Supports: https://huggingface.co/IDEA-CCNL/Ziya-LLaMA-13B-v1
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"""
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prompt = prefix
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if history:
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for old_query, response in history:
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prompt += "<human>:{}\n<bot>:{}\n".format(old_query, response)
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prompt += "<human>:{}\n<bot>:".format(query)
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return prompt
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def _format_example(self, query: str, history: Optional[list] = None, prefix: Optional[str] = "") -> List[str]:
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prefix = prefix if prefix else self.prefix
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history = history if (history and self.use_history) else []
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history = history + [(query, "<dummy>")]
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convs = []
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for turn_idx, (user_query, bot_resp) in enumerate(history):
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if turn_idx == 0:
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convs.append(prefix + self.prompt.format(query=user_query))
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convs.append(bot_resp)
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else:
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convs.append(self.sep + self.prompt.format(query=user_query))
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convs.append(bot_resp)
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return convs[:-1] # drop last
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