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from __future__ import annotations |
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import logging |
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from llama_index import Prompt |
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from typing import List, Tuple |
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import mdtex2html |
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from presets import * |
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from llama_func import * |
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def compact_text_chunks(self, prompt: Prompt, text_chunks: List[str]) -> List[str]: |
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logging.debug("Compacting text chunks...πππ") |
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combined_str = [c.strip() for c in text_chunks if c.strip()] |
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combined_str = [f"[{index+1}] {c}" for index, c in enumerate(combined_str)] |
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combined_str = "\n\n".join(combined_str) |
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text_splitter = self.get_text_splitter_given_prompt(prompt, 1, padding=1) |
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return text_splitter.split_text(combined_str) |
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def postprocess( |
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self, y: List[Tuple[str | None, str | None]] |
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) -> List[Tuple[str | None, str | None]]: |
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""" |
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Parameters: |
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y: List of tuples representing the message and response pairs. Each message and response should be a string, which may be in Markdown format. |
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Returns: |
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List of tuples representing the message and response. Each message and response will be a string of HTML. |
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""" |
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if y is None or y == []: |
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return [] |
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tag_regex = re.compile(r"^<\w+>[^<]+</\w+>") |
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if tag_regex.search(y[-1][1]): |
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y[-1] = (y[-1][0].replace("\n", "<br>"), y[-1][1]) |
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else: |
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y[-1] = (y[-1][0].replace("\n", "<br>"), convert_mdtext(y[-1][1])) |
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return y |
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