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https://github.com/hwchase17/langchain.git
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bc7e56e8df
Supporting asyncio in langchain primitives allows for users to run them concurrently and creates more seamless integration with asyncio-supported frameworks (FastAPI, etc.) Summary of changes: **LLM** * Add `agenerate` and `_agenerate` * Implement in OpenAI by leveraging `client.Completions.acreate` **Chain** * Add `arun`, `acall`, `_acall` * Implement them in `LLMChain` and `LLMMathChain` for now **Agent** * Refactor and leverage async chain and llm methods * Add ability for `Tools` to contain async coroutine * Implement async SerpaPI `arun` Create demo notebook. Open questions: * Should all the async stuff go in separate classes? I've seen both patterns (keeping the same class and having async and sync methods vs. having class separation)
37 lines
1.1 KiB
Python
37 lines
1.1 KiB
Python
"""Handle chained inputs."""
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from typing import Dict, List, Optional
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_TEXT_COLOR_MAPPING = {
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"blue": "36;1",
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"yellow": "33;1",
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"pink": "38;5;200",
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"green": "32;1",
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"red": "31;1",
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}
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def get_color_mapping(
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items: List[str], excluded_colors: Optional[List] = None
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) -> Dict[str, str]:
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"""Get mapping for items to a support color."""
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colors = list(_TEXT_COLOR_MAPPING.keys())
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if excluded_colors is not None:
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colors = [c for c in colors if c not in excluded_colors]
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color_mapping = {item: colors[i % len(colors)] for i, item in enumerate(items)}
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return color_mapping
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def get_colored_text(text: str, color: str) -> str:
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"""Get colored text."""
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color_str = _TEXT_COLOR_MAPPING[color]
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return f"\u001b[{color_str}m\033[1;3m{text}\u001b[0m"
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def print_text(text: str, color: Optional[str] = None, end: str = "") -> None:
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"""Print text with highlighting and no end characters."""
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if color is None:
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text_to_print = text
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else:
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text_to_print = get_colored_text(text, color)
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print(text_to_print, end=end)
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