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739cf2e
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Parent(s):
clean
Browse files- .gitattributes +35 -0
- README.md +17 -0
- app.py +149 -0
- requirements.in +4 -0
- requirements.txt +438 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md
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@@ -0,0 +1,17 @@
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---
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title: Corpus Creator
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emoji: 🦀
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colorFrom: pink
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colorTo: gray
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sdk: gradio
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sdk_version: 4.36.1
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app_file: app.py
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pinned: false
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hf_oauth_scopes:
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- read-repos
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- write-repos
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- manage-repos
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hf_oauth: true
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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app.py
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import logging
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from functools import lru_cache
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from pathlib import Path
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import gradio as gr
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from datasets import Dataset
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from gradio_log import Log
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from huggingface_hub import DatasetCard
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from llama_index.core import SimpleDirectoryReader
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from llama_index.core.node_parser import SentenceSplitter
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from llama_index.core.schema import MetadataMode
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from tqdm.auto import tqdm
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log_file = "logs.txt"
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Path(log_file).touch(exist_ok=True)
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logging.basicConfig(filename="logs.txt", level=logging.INFO)
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logging.getLogger().addHandler(logging.FileHandler(log_file))
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def load_corpus(files, chunk_size=256, chunk_overlap=0, verbose=True):
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if verbose:
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gr.Info("Loading files...")
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reader = SimpleDirectoryReader(input_files=files)
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docs = reader.load_data()
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if verbose:
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print(f"Loaded {len(docs)} docs")
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parser = SentenceSplitter.from_defaults(
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chunk_size=chunk_size, chunk_overlap=chunk_overlap
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)
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nodes = parser.get_nodes_from_documents(docs, show_progress=verbose)
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if verbose:
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print(f"Parsed {len(nodes)} nodes")
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docs = {
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node.node_id: node.get_content(metadata_mode=MetadataMode.NONE)
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| 39 |
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for node in tqdm(nodes)
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}
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# remove empty docs
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docs = {k: v for k, v in docs.items() if v}
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return docs
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def upload_file(
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files,
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chunk_size: int = 256,
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chunk_overlap: int = 0,
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hub_id: str = None,
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private: bool = False,
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oauth_token: gr.OAuthToken = None,
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):
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print("loading files")
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file_paths = [file.name for file in files]
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print("parsing into sentences")
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corpus = load_corpus(file_paths, chunk_size=chunk_size, chunk_overlap=chunk_overlap)
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print("Creating dataset")
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dataset = Dataset.from_dict({"ids": corpus.keys(), "texts": corpus.values()})
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message = f"Dataset created has: \n - {len(dataset)} rows"
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if hub_id:
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if oauth_token is not None:
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gr.Info("Uploading to Hugging Face Hub")
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| 64 |
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dataset.push_to_hub(hub_id, token=oauth_token.token, private=private)
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| 65 |
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update_dataset_card(hub_id, oauth_token.token, chunk_size, chunk_overlap)
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| 66 |
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message += f"\n\nUploaded to [{hub_id}](https://huggingface.co/{hub_id}"
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else:
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raise gr.Error("Please login to Hugging Face Hub to push to hub")
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return dataset.to_pandas(), message
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+
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def update_dataset_card(
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| 74 |
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hub_id,
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token,
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chunk_size,
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chunk_overlap,
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):
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card = DatasetCard.load(hub_id, token=token)
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if not card.text:
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# add template description to card text
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card.text += f"""This dataset was created using [Corpus Creator](https://huggingface.co/spaces/davanstrien/corpus-creator). This dataset was created by parsing a corpus of text files into chunks of sentences using Llama Index.
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This processing was done with a chunk size of {chunk_size} and a chunk overlap of {chunk_overlap}."""
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tags = card.data.get("tags", [])
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tags.append("corpus-creator")
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card.data["tags"] = tags
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card.push_to_hub(hub_id, token=token)
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description = """
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Corpus Creator is a tool designed to help you easily convert a collection of text files into a dataset suitable for various natural language processing (NLP) tasks.
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In particular the app is focused on splitting texts into chunks of a specified size and overlap. This can be useful for preparing data for synthetic data generation, pipelines or annotation tasks.
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| 93 |
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The resulting text chunks are stored in a dataset that can be previewed and uploaded to the Hugging Face Hub for easy sharing and access by the community.
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| 94 |
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The chunking is done using `Llama-index`'s [`SentenceSplitter`](https://docs.llamaindex.ai/en/stable/module_guides/loading/node_parsers/modules/?h=sentencesplitter#sentencesplitter) classes.
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### Usage:
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- Login: Start by logging in to your Hugging Face account using the provided login button.
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- Set Parameters: Customize the chunk size and overlap according to your requirements.
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- Upload Files: Use the upload button to load file(s) for processing.
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- Preview Dataset: View the created dataset in a dataframe format before uploading it to the Hugging Face Hub.
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- Upload to Hub: Optionally, specify the Hub ID and choose whether to make the dataset private before pushing it to the Hugging Face Hub."""
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with gr.Blocks() as demo:
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gr.HTML(
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"""<h1 style='text-align: center;'> Corpus Creator</h1>
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<center><i> 📁 From random files to a Hugging Face dataset in a single step 📁 </i></center>"""
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)
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gr.Markdown(description)
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with gr.Row():
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gr.LoginButton()
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with gr.Column():
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gr.Markdown(
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"To upload to the Hub, add an ID for where you want to push the dataset"
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)
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hub_id = gr.Textbox(value=None, label="Hub ID")
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with gr.Row():
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chunk_size = gr.Number(
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256,
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label="Chunk size (size to split text into)",
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minimum=10,
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maximum=4096,
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step=1,
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)
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chunk_overlap = gr.Number(
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0,
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label="Chunk overlap (overlap size between chunks)",
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minimum=0,
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maximum=4096,
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step=1,
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)
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private = gr.Checkbox(False, label="Upload dataset to a private repo?")
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upload_button = gr.UploadButton(
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"Load files to corpus",
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file_types=[
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"text",
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],
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file_count="multiple",
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)
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summary = gr.Markdown()
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| 141 |
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with gr.Accordion("detailed logs", open=False):
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Log(log_file, dark=True, xterm_font_size=12)
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corpus_preview_df = gr.DataFrame()
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upload_button.upload(
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upload_file,
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inputs=[upload_button, chunk_size, chunk_overlap, hub_id, private],
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outputs=[corpus_preview_df, summary],
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)
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demo.launch(debug=True)
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requirements.in
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gradio[oauth]
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llama_index
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gradio_log
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datasets
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requirements.txt
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|
| 1 |
+
# This file was autogenerated by uv via the following command:
|
| 2 |
+
# uv pip compile requirements.in -o requirements.txt
|
| 3 |
+
aiofiles==23.2.1
|
| 4 |
+
# via gradio
|
| 5 |
+
aiohttp==3.9.5
|
| 6 |
+
# via
|
| 7 |
+
# datasets
|
| 8 |
+
# fsspec
|
| 9 |
+
# llama-index-core
|
| 10 |
+
# llama-index-legacy
|
| 11 |
+
aiosignal==1.3.1
|
| 12 |
+
# via aiohttp
|
| 13 |
+
altair==5.3.0
|
| 14 |
+
# via gradio
|
| 15 |
+
annotated-types==0.7.0
|
| 16 |
+
# via pydantic
|
| 17 |
+
anyio==4.4.0
|
| 18 |
+
# via
|
| 19 |
+
# httpx
|
| 20 |
+
# openai
|
| 21 |
+
# starlette
|
| 22 |
+
# watchfiles
|
| 23 |
+
attrs==23.2.0
|
| 24 |
+
# via
|
| 25 |
+
# aiohttp
|
| 26 |
+
# jsonschema
|
| 27 |
+
# referencing
|
| 28 |
+
authlib==1.3.1
|
| 29 |
+
# via gradio
|
| 30 |
+
beautifulsoup4==4.12.3
|
| 31 |
+
# via llama-index-readers-file
|
| 32 |
+
certifi==2024.6.2
|
| 33 |
+
# via
|
| 34 |
+
# httpcore
|
| 35 |
+
# httpx
|
| 36 |
+
# requests
|
| 37 |
+
cffi==1.16.0
|
| 38 |
+
# via cryptography
|
| 39 |
+
charset-normalizer==3.3.2
|
| 40 |
+
# via requests
|
| 41 |
+
click==8.1.7
|
| 42 |
+
# via
|
| 43 |
+
# nltk
|
| 44 |
+
# typer
|
| 45 |
+
# uvicorn
|
| 46 |
+
contourpy==1.2.1
|
| 47 |
+
# via matplotlib
|
| 48 |
+
cryptography==42.0.8
|
| 49 |
+
# via authlib
|
| 50 |
+
cycler==0.12.1
|
| 51 |
+
# via matplotlib
|
| 52 |
+
dataclasses-json==0.6.7
|
| 53 |
+
# via
|
| 54 |
+
# llama-index-core
|
| 55 |
+
# llama-index-legacy
|
| 56 |
+
datasets==2.20.0
|
| 57 |
+
# via -r requirements.in
|
| 58 |
+
deprecated==1.2.14
|
| 59 |
+
# via
|
| 60 |
+
# llama-index-core
|
| 61 |
+
# llama-index-legacy
|
| 62 |
+
dill==0.3.8
|
| 63 |
+
# via
|
| 64 |
+
# datasets
|
| 65 |
+
# multiprocess
|
| 66 |
+
dirtyjson==1.0.8
|
| 67 |
+
# via
|
| 68 |
+
# llama-index-core
|
| 69 |
+
# llama-index-legacy
|
| 70 |
+
distro==1.9.0
|
| 71 |
+
# via openai
|
| 72 |
+
dnspython==2.6.1
|
| 73 |
+
# via email-validator
|
| 74 |
+
email-validator==2.1.2
|
| 75 |
+
# via fastapi
|
| 76 |
+
fastapi==0.111.0
|
| 77 |
+
# via gradio
|
| 78 |
+
fastapi-cli==0.0.4
|
| 79 |
+
# via fastapi
|
| 80 |
+
ffmpy==0.3.2
|
| 81 |
+
# via gradio
|
| 82 |
+
filelock==3.15.1
|
| 83 |
+
# via
|
| 84 |
+
# datasets
|
| 85 |
+
# huggingface-hub
|
| 86 |
+
fonttools==4.53.0
|
| 87 |
+
# via matplotlib
|
| 88 |
+
frozenlist==1.4.1
|
| 89 |
+
# via
|
| 90 |
+
# aiohttp
|
| 91 |
+
# aiosignal
|
| 92 |
+
fsspec==2024.5.0
|
| 93 |
+
# via
|
| 94 |
+
# datasets
|
| 95 |
+
# gradio-client
|
| 96 |
+
# huggingface-hub
|
| 97 |
+
# llama-index-core
|
| 98 |
+
# llama-index-legacy
|
| 99 |
+
gradio==4.36.1
|
| 100 |
+
# via
|
| 101 |
+
# -r requirements.in
|
| 102 |
+
# gradio-log
|
| 103 |
+
gradio-client==1.0.1
|
| 104 |
+
# via gradio
|
| 105 |
+
gradio-log==0.0.4
|
| 106 |
+
# via -r requirements.in
|
| 107 |
+
greenlet==3.0.3
|
| 108 |
+
# via sqlalchemy
|
| 109 |
+
h11==0.14.0
|
| 110 |
+
# via
|
| 111 |
+
# httpcore
|
| 112 |
+
# uvicorn
|
| 113 |
+
httpcore==1.0.5
|
| 114 |
+
# via httpx
|
| 115 |
+
httptools==0.6.1
|
| 116 |
+
# via uvicorn
|
| 117 |
+
httpx==0.27.0
|
| 118 |
+
# via
|
| 119 |
+
# fastapi
|
| 120 |
+
# gradio
|
| 121 |
+
# gradio-client
|
| 122 |
+
# llama-index-core
|
| 123 |
+
# llama-index-legacy
|
| 124 |
+
# llamaindex-py-client
|
| 125 |
+
# openai
|
| 126 |
+
huggingface-hub==0.23.4
|
| 127 |
+
# via
|
| 128 |
+
# datasets
|
| 129 |
+
# gradio
|
| 130 |
+
# gradio-client
|
| 131 |
+
idna==3.7
|
| 132 |
+
# via
|
| 133 |
+
# anyio
|
| 134 |
+
# email-validator
|
| 135 |
+
# httpx
|
| 136 |
+
# requests
|
| 137 |
+
# yarl
|
| 138 |
+
importlib-resources==6.4.0
|
| 139 |
+
# via gradio
|
| 140 |
+
itsdangerous==2.2.0
|
| 141 |
+
# via gradio
|
| 142 |
+
jinja2==3.1.4
|
| 143 |
+
# via
|
| 144 |
+
# altair
|
| 145 |
+
# fastapi
|
| 146 |
+
# gradio
|
| 147 |
+
joblib==1.4.2
|
| 148 |
+
# via nltk
|
| 149 |
+
jsonschema==4.22.0
|
| 150 |
+
# via altair
|
| 151 |
+
jsonschema-specifications==2023.12.1
|
| 152 |
+
# via jsonschema
|
| 153 |
+
kiwisolver==1.4.5
|
| 154 |
+
# via matplotlib
|
| 155 |
+
llama-index==0.10.45
|
| 156 |
+
# via -r requirements.in
|
| 157 |
+
llama-index-agent-openai==0.2.7
|
| 158 |
+
# via
|
| 159 |
+
# llama-index
|
| 160 |
+
# llama-index-program-openai
|
| 161 |
+
llama-index-cli==0.1.12
|
| 162 |
+
# via llama-index
|
| 163 |
+
llama-index-core==0.10.44
|
| 164 |
+
# via
|
| 165 |
+
# llama-index
|
| 166 |
+
# llama-index-agent-openai
|
| 167 |
+
# llama-index-cli
|
| 168 |
+
# llama-index-embeddings-openai
|
| 169 |
+
# llama-index-indices-managed-llama-cloud
|
| 170 |
+
# llama-index-llms-openai
|
| 171 |
+
# llama-index-multi-modal-llms-openai
|
| 172 |
+
# llama-index-program-openai
|
| 173 |
+
# llama-index-question-gen-openai
|
| 174 |
+
# llama-index-readers-file
|
| 175 |
+
# llama-index-readers-llama-parse
|
| 176 |
+
# llama-parse
|
| 177 |
+
llama-index-embeddings-openai==0.1.10
|
| 178 |
+
# via
|
| 179 |
+
# llama-index
|
| 180 |
+
# llama-index-cli
|
| 181 |
+
llama-index-indices-managed-llama-cloud==0.1.6
|
| 182 |
+
# via llama-index
|
| 183 |
+
llama-index-legacy==0.9.48
|
| 184 |
+
# via llama-index
|
| 185 |
+
llama-index-llms-openai==0.1.22
|
| 186 |
+
# via
|
| 187 |
+
# llama-index
|
| 188 |
+
# llama-index-agent-openai
|
| 189 |
+
# llama-index-cli
|
| 190 |
+
# llama-index-multi-modal-llms-openai
|
| 191 |
+
# llama-index-program-openai
|
| 192 |
+
# llama-index-question-gen-openai
|
| 193 |
+
llama-index-multi-modal-llms-openai==0.1.6
|
| 194 |
+
# via llama-index
|
| 195 |
+
llama-index-program-openai==0.1.6
|
| 196 |
+
# via
|
| 197 |
+
# llama-index
|
| 198 |
+
# llama-index-question-gen-openai
|
| 199 |
+
llama-index-question-gen-openai==0.1.3
|
| 200 |
+
# via llama-index
|
| 201 |
+
llama-index-readers-file==0.1.25
|
| 202 |
+
# via llama-index
|
| 203 |
+
llama-index-readers-llama-parse==0.1.4
|
| 204 |
+
# via llama-index
|
| 205 |
+
llama-parse==0.4.4
|
| 206 |
+
# via llama-index-readers-llama-parse
|
| 207 |
+
llamaindex-py-client==0.1.19
|
| 208 |
+
# via
|
| 209 |
+
# llama-index-core
|
| 210 |
+
# llama-index-indices-managed-llama-cloud
|
| 211 |
+
markdown-it-py==3.0.0
|
| 212 |
+
# via rich
|
| 213 |
+
markupsafe==2.1.5
|
| 214 |
+
# via
|
| 215 |
+
# gradio
|
| 216 |
+
# jinja2
|
| 217 |
+
marshmallow==3.21.3
|
| 218 |
+
# via dataclasses-json
|
| 219 |
+
matplotlib==3.9.0
|
| 220 |
+
# via gradio
|
| 221 |
+
mdurl==0.1.2
|
| 222 |
+
# via markdown-it-py
|
| 223 |
+
multidict==6.0.5
|
| 224 |
+
# via
|
| 225 |
+
# aiohttp
|
| 226 |
+
# yarl
|
| 227 |
+
multiprocess==0.70.16
|
| 228 |
+
# via datasets
|
| 229 |
+
mypy-extensions==1.0.0
|
| 230 |
+
# via typing-inspect
|
| 231 |
+
nest-asyncio==1.6.0
|
| 232 |
+
# via
|
| 233 |
+
# llama-index-core
|
| 234 |
+
# llama-index-legacy
|
| 235 |
+
networkx==3.3
|
| 236 |
+
# via
|
| 237 |
+
# llama-index-core
|
| 238 |
+
# llama-index-legacy
|
| 239 |
+
nltk==3.8.1
|
| 240 |
+
# via
|
| 241 |
+
# llama-index-core
|
| 242 |
+
# llama-index-legacy
|
| 243 |
+
numpy==2.0.0
|
| 244 |
+
# via
|
| 245 |
+
# altair
|
| 246 |
+
# contourpy
|
| 247 |
+
# datasets
|
| 248 |
+
# gradio
|
| 249 |
+
# llama-index-core
|
| 250 |
+
# llama-index-legacy
|
| 251 |
+
# matplotlib
|
| 252 |
+
# pandas
|
| 253 |
+
# pyarrow
|
| 254 |
+
openai==1.34.0
|
| 255 |
+
# via
|
| 256 |
+
# llama-index-agent-openai
|
| 257 |
+
# llama-index-core
|
| 258 |
+
# llama-index-legacy
|
| 259 |
+
orjson==3.10.5
|
| 260 |
+
# via
|
| 261 |
+
# fastapi
|
| 262 |
+
# gradio
|
| 263 |
+
packaging==24.1
|
| 264 |
+
# via
|
| 265 |
+
# altair
|
| 266 |
+
# datasets
|
| 267 |
+
# gradio
|
| 268 |
+
# gradio-client
|
| 269 |
+
# huggingface-hub
|
| 270 |
+
# marshmallow
|
| 271 |
+
# matplotlib
|
| 272 |
+
pandas==2.2.2
|
| 273 |
+
# via
|
| 274 |
+
# altair
|
| 275 |
+
# datasets
|
| 276 |
+
# gradio
|
| 277 |
+
# llama-index-core
|
| 278 |
+
# llama-index-legacy
|
| 279 |
+
pillow==10.3.0
|
| 280 |
+
# via
|
| 281 |
+
# gradio
|
| 282 |
+
# llama-index-core
|
| 283 |
+
# matplotlib
|
| 284 |
+
pyarrow==16.1.0
|
| 285 |
+
# via datasets
|
| 286 |
+
pyarrow-hotfix==0.6
|
| 287 |
+
# via datasets
|
| 288 |
+
pycparser==2.22
|
| 289 |
+
# via cffi
|
| 290 |
+
pydantic==2.7.4
|
| 291 |
+
# via
|
| 292 |
+
# fastapi
|
| 293 |
+
# gradio
|
| 294 |
+
# llamaindex-py-client
|
| 295 |
+
# openai
|
| 296 |
+
pydantic-core==2.18.4
|
| 297 |
+
# via pydantic
|
| 298 |
+
pydub==0.25.1
|
| 299 |
+
# via gradio
|
| 300 |
+
pygments==2.18.0
|
| 301 |
+
# via rich
|
| 302 |
+
pyparsing==3.1.2
|
| 303 |
+
# via matplotlib
|
| 304 |
+
pypdf==4.2.0
|
| 305 |
+
# via llama-index-readers-file
|
| 306 |
+
python-dateutil==2.9.0.post0
|
| 307 |
+
# via
|
| 308 |
+
# matplotlib
|
| 309 |
+
# pandas
|
| 310 |
+
python-dotenv==1.0.1
|
| 311 |
+
# via uvicorn
|
| 312 |
+
python-multipart==0.0.9
|
| 313 |
+
# via
|
| 314 |
+
# fastapi
|
| 315 |
+
# gradio
|
| 316 |
+
pytz==2024.1
|
| 317 |
+
# via pandas
|
| 318 |
+
pyyaml==6.0.1
|
| 319 |
+
# via
|
| 320 |
+
# datasets
|
| 321 |
+
# gradio
|
| 322 |
+
# huggingface-hub
|
| 323 |
+
# llama-index-core
|
| 324 |
+
# uvicorn
|
| 325 |
+
referencing==0.35.1
|
| 326 |
+
# via
|
| 327 |
+
# jsonschema
|
| 328 |
+
# jsonschema-specifications
|
| 329 |
+
regex==2024.5.15
|
| 330 |
+
# via
|
| 331 |
+
# nltk
|
| 332 |
+
# tiktoken
|
| 333 |
+
requests==2.32.3
|
| 334 |
+
# via
|
| 335 |
+
# datasets
|
| 336 |
+
# huggingface-hub
|
| 337 |
+
# llama-index-core
|
| 338 |
+
# llama-index-legacy
|
| 339 |
+
# tiktoken
|
| 340 |
+
rich==13.7.1
|
| 341 |
+
# via typer
|
| 342 |
+
rpds-py==0.18.1
|
| 343 |
+
# via
|
| 344 |
+
# jsonschema
|
| 345 |
+
# referencing
|
| 346 |
+
ruff==0.4.9
|
| 347 |
+
# via gradio
|
| 348 |
+
semantic-version==2.10.0
|
| 349 |
+
# via gradio
|
| 350 |
+
shellingham==1.5.4
|
| 351 |
+
# via typer
|
| 352 |
+
six==1.16.0
|
| 353 |
+
# via python-dateutil
|
| 354 |
+
sniffio==1.3.1
|
| 355 |
+
# via
|
| 356 |
+
# anyio
|
| 357 |
+
# httpx
|
| 358 |
+
# openai
|
| 359 |
+
soupsieve==2.5
|
| 360 |
+
# via beautifulsoup4
|
| 361 |
+
sqlalchemy==2.0.30
|
| 362 |
+
# via
|
| 363 |
+
# llama-index-core
|
| 364 |
+
# llama-index-legacy
|
| 365 |
+
starlette==0.37.2
|
| 366 |
+
# via fastapi
|
| 367 |
+
striprtf==0.0.26
|
| 368 |
+
# via llama-index-readers-file
|
| 369 |
+
tenacity==8.4.1
|
| 370 |
+
# via
|
| 371 |
+
# llama-index-core
|
| 372 |
+
# llama-index-legacy
|
| 373 |
+
tiktoken==0.7.0
|
| 374 |
+
# via
|
| 375 |
+
# llama-index-core
|
| 376 |
+
# llama-index-legacy
|
| 377 |
+
tomlkit==0.12.0
|
| 378 |
+
# via gradio
|
| 379 |
+
toolz==0.12.1
|
| 380 |
+
# via altair
|
| 381 |
+
tqdm==4.66.4
|
| 382 |
+
# via
|
| 383 |
+
# datasets
|
| 384 |
+
# huggingface-hub
|
| 385 |
+
# llama-index-core
|
| 386 |
+
# nltk
|
| 387 |
+
# openai
|
| 388 |
+
typer==0.12.3
|
| 389 |
+
# via
|
| 390 |
+
# fastapi-cli
|
| 391 |
+
# gradio
|
| 392 |
+
typing-extensions==4.12.2
|
| 393 |
+
# via
|
| 394 |
+
# fastapi
|
| 395 |
+
# gradio
|
| 396 |
+
# gradio-client
|
| 397 |
+
# huggingface-hub
|
| 398 |
+
# llama-index-core
|
| 399 |
+
# llama-index-legacy
|
| 400 |
+
# openai
|
| 401 |
+
# pydantic
|
| 402 |
+
# pydantic-core
|
| 403 |
+
# sqlalchemy
|
| 404 |
+
# typer
|
| 405 |
+
# typing-inspect
|
| 406 |
+
typing-inspect==0.9.0
|
| 407 |
+
# via
|
| 408 |
+
# dataclasses-json
|
| 409 |
+
# llama-index-core
|
| 410 |
+
# llama-index-legacy
|
| 411 |
+
tzdata==2024.1
|
| 412 |
+
# via pandas
|
| 413 |
+
ujson==5.10.0
|
| 414 |
+
# via fastapi
|
| 415 |
+
urllib3==2.2.2
|
| 416 |
+
# via
|
| 417 |
+
# gradio
|
| 418 |
+
# requests
|
| 419 |
+
uvicorn==0.30.1
|
| 420 |
+
# via
|
| 421 |
+
# fastapi
|
| 422 |
+
# gradio
|
| 423 |
+
uvloop==0.19.0
|
| 424 |
+
# via uvicorn
|
| 425 |
+
watchfiles==0.22.0
|
| 426 |
+
# via uvicorn
|
| 427 |
+
websockets==11.0.3
|
| 428 |
+
# via
|
| 429 |
+
# gradio-client
|
| 430 |
+
# uvicorn
|
| 431 |
+
wrapt==1.16.0
|
| 432 |
+
# via
|
| 433 |
+
# deprecated
|
| 434 |
+
# llama-index-core
|
| 435 |
+
xxhash==3.4.1
|
| 436 |
+
# via datasets
|
| 437 |
+
yarl==1.9.4
|
| 438 |
+
# via aiohttp
|