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app.py
CHANGED
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@@ -334,18 +334,23 @@ query_generator_template_llama2 = f"<s>[INST] <<SYS>>{query_generator_message}<<
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# 2. ็ๆใใใ่ณชๅๆใ็จใใฆใๅ่ๆ็ฎใ่ฆ็ดใใchain ใฎใใญใณใใ
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question_prompt_message = """
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-
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and summarize it in a natural English sentence with clear subject, verb, object,
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do not summarize and simply answer "NO INFO"
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""".replace("\n", "")
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question_prompt_common_format = """
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===
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[Question] {query}
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[references] {context}
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[
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question_prompt_template_std = f"{question_prompt_message}{question_prompt_common_format}"
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question_prompt_template_llama2 = f"<s>[INST] <<SYS>>{question_prompt_message}<</SYS>>{question_prompt_common_format}[/INST]"
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@@ -570,7 +575,7 @@ def set_chains(ss: SessionState, summarization_mode) -> SessionState:
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ss.conversation_chain = ConversationChain(
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llm = ss.llm,
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prompt = chat_prompt,
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memory = ss.memory,
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input_key = "query",
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output_key = "output_text",
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verbose = True,
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# 2. ็ๆใใใ่ณชๅๆใ็จใใฆใๅ่ๆ็ฎใ่ฆ็ดใใchain ใฎใใญใณใใ
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# question_prompt_message = """
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# From the following references, extract key information relevant to the question
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# and summarize it in a natural English sentence with clear subject, verb, object,
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# and complement. If there is no information in the reference that answers the question,
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# do not summarize and simply answer "NO INFO"
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# """.replace("\n", "")
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question_prompt_message = """
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1. Determine if any of the following references provide information that answers the Question, and if there is no information, answer "NO INFO" and stop.
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2. From the following references, extract key information relevant to the question and summarize it in a natural English sentence with clear subject, verb, object,ใand complement.
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""".strip()
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question_prompt_common_format = """
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===
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[Question] {query}
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[references] {context}
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[Answer]"""
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question_prompt_template_std = f"{question_prompt_message}{question_prompt_common_format}"
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question_prompt_template_llama2 = f"<s>[INST] <<SYS>>{question_prompt_message}<</SYS>>{question_prompt_common_format}[/INST]"
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ss.conversation_chain = ConversationChain(
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llm = ss.llm,
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prompt = chat_prompt,
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# memory = ss.memory,
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input_key = "query",
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output_key = "output_text",
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verbose = True,
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