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Ray based document parsing of more file types (jupyterlab#94)
* Ray based document parsing of more file types. * Renaming to learn/ask to make for human centered. * Improvements to the learn/ask commands. * fix typo Co-authored-by: Jason Weill <[email protected]> * improve grammar Co-authored-by: Jason Weill <[email protected]> * improve wording Co-authored-by: Jason Weill <[email protected]> * Adding new extensions and excludes. * Update langchain to version 0.144. --------- Co-authored-by: david qiu <[email protected]> Co-authored-by: Jason Weill <[email protected]>
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,119 @@ | ||
| import os | ||
| import traceback | ||
| from collections import Counter | ||
| import argparse | ||
|
|
||
| import ray | ||
| from ray.util.queue import Queue | ||
|
|
||
| from jupyter_core.paths import jupyter_data_dir | ||
|
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| from langchain import FAISS | ||
| from langchain.embeddings.openai import OpenAIEmbeddings | ||
| from langchain.text_splitter import ( | ||
| RecursiveCharacterTextSplitter, PythonCodeTextSplitter, | ||
| MarkdownTextSplitter, LatexTextSplitter | ||
| ) | ||
|
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||
| from jupyter_ai.models import HumanChatMessage | ||
| from jupyter_ai.actors.base import BaseActor, Logger | ||
| from jupyter_ai_magics.providers import ChatOpenAINewProvider | ||
| from jupyter_ai.document_loaders.directory import RayRecursiveDirectoryLoader | ||
| from jupyter_ai.document_loaders.splitter import ExtensionSplitter, NotebookSplitter | ||
|
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| @ray.remote | ||
| class LearnActor(BaseActor): | ||
|
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| def __init__(self, reply_queue: Queue, log: Logger, root_dir: str): | ||
| super().__init__(reply_queue=reply_queue, log=log) | ||
| self.root_dir = root_dir | ||
| self.index_save_dir = os.path.join(jupyter_data_dir(), 'jupyter_ai', 'indices') | ||
| self.chunk_size = 2000 | ||
| self.chunk_overlap = 100 | ||
| self.parser.prog = '/learn' | ||
| self.parser.add_argument('-v', '--verbose', action='store_true') | ||
| self.parser.add_argument('-d', '--delete', action='store_true') | ||
| self.parser.add_argument('path', nargs=argparse.REMAINDER) | ||
| self.index_name = 'default' | ||
| self.index = None | ||
|
|
||
| if ChatOpenAINewProvider.auth_strategy.name not in os.environ: | ||
| return | ||
|
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| if not os.path.exists(self.index_save_dir): | ||
| os.makedirs(self.index_save_dir) | ||
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| self.load_or_create() | ||
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| def _process_message(self, message: HumanChatMessage): | ||
| args = self.parse_args(message) | ||
| if args is None: | ||
| return | ||
|
|
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| if args.delete: | ||
| self.delete() | ||
| self.reply(f"👍 I have deleted everything I previously learned.", message) | ||
| return | ||
|
|
||
| # Make sure the path exists. | ||
| if not len(args.path) == 1: | ||
| self.reply(f"{self.parser.format_usage()}", message) | ||
| return | ||
| short_path = args.path[0] | ||
| load_path = os.path.join(self.root_dir, short_path) | ||
| if not os.path.exists(load_path): | ||
| response = f"Sorry, that path doesn't exist: {load_path}" | ||
| self.reply(response, message) | ||
| return | ||
|
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| if args.verbose: | ||
| self.reply(f"Loading and splitting files for {load_path}", message) | ||
|
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| splitters={ | ||
| '.py': PythonCodeTextSplitter(chunk_size=self.chunk_size, chunk_overlap=self.chunk_overlap), | ||
| '.md': MarkdownTextSplitter(chunk_size=self.chunk_size, chunk_overlap=self.chunk_overlap), | ||
| '.tex': LatexTextSplitter(chunk_size=self.chunk_size, chunk_overlap=self.chunk_overlap), | ||
| '.ipynb': NotebookSplitter(chunk_size=self.chunk_size, chunk_overlap=self.chunk_overlap) | ||
| } | ||
| splitter = ExtensionSplitter( | ||
| splitters=splitters, | ||
| default_splitter=RecursiveCharacterTextSplitter(chunk_size=self.chunk_size, chunk_overlap=self.chunk_overlap) | ||
| ) | ||
|
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| loader = RayRecursiveDirectoryLoader(load_path) | ||
| texts = loader.load_and_split(text_splitter=splitter) | ||
| self.index.add_documents(texts) | ||
| self.save() | ||
|
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||
| response = f"""🎉 I have indexed documents at **{load_path}** and I am ready to answer questions about them. | ||
| You can ask questions about these docs by prefixing your message with **/ask**.""" | ||
| self.reply(response, message) | ||
|
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| def get_index(self): | ||
| return self.index | ||
|
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| def delete(self): | ||
| self.index = None | ||
| paths = [os.path.join(self.index_save_dir, self.index_name+ext) for ext in ['.pkl', '.faiss']] | ||
| for path in paths: | ||
| if os.path.isfile(path): | ||
| os.remove(path) | ||
| self.create() | ||
|
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| def create(self): | ||
| embeddings = OpenAIEmbeddings() | ||
| self.index = FAISS.from_texts(["Jupyter AI knows about your filesystem, to ask questions first use the /learn command."], embeddings) | ||
| self.save() | ||
|
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| def save(self): | ||
| if self.index is not None: | ||
| self.index.save_local(self.index_save_dir, index_name=self.index_name) | ||
|
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| def load_or_create(self): | ||
| embeddings = OpenAIEmbeddings() | ||
| if self.index is None: | ||
| try: | ||
| self.index = FAISS.load_local(self.index_save_dir, embeddings, index_name=self.index_name) | ||
| except Exception as e: | ||
| self.create() |
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