77 lines
2.6 KiB
Python
77 lines
2.6 KiB
Python
import hashlib
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import json
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import os
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import re
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import requests
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from embedchain.loaders.base_loader import BaseLoader
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from embedchain.utils import clean_string, is_valid_json_string
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VALID_URL_PATTERN = "^https:\/\/[0-9A-z.]+.[0-9A-z.]+.[a-z]+\/.*\.json$"
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class JSONLoader(BaseLoader):
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@staticmethod
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def _get_llama_hub_loader():
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try:
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from llama_hub.jsondata.base import \
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JSONDataReader as LLHUBJSONLoader
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except ImportError as e:
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raise Exception(
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f"Failed to install required packages: {e}, \
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install them using `pip install --upgrade 'embedchain[json]`"
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)
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return LLHUBJSONLoader()
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@staticmethod
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def _check_content(content):
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if not isinstance(content, str):
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raise ValueError(
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"Invaid content input. \
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If you want to upload (list, dict, etc.), do \
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`json.dump(data, indent=0)` and add the stringified JSON. \
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Check - `https://docs.embedchain.ai/data-sources/json`"
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)
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@staticmethod
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def load_data(content):
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"""Load a json file. Each data point is a key value pair."""
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JSONLoader._check_content(content)
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loader = JSONLoader._get_llama_hub_loader()
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data = []
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data_content = []
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content_url_str = content
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# Load json data from various sources.
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if os.path.isfile(content):
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with open(content, "r", encoding="utf-8") as json_file:
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json_data = json.load(json_file)
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elif re.match(VALID_URL_PATTERN, content):
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response = requests.get(content)
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if response.status_code == 200:
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json_data = response.json()
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else:
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raise ValueError(
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f"Loading data from the given url: {content} failed. \
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Make sure the url is working."
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)
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elif is_valid_json_string(content):
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json_data = content
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content_url_str = hashlib.sha256((content).encode("utf-8")).hexdigest()
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else:
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raise ValueError(f"Invalid content to load json data from: {content}")
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docs = loader.load_data(json_data)
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for doc in docs:
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doc_content = clean_string(doc.text)
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data.append({"content": doc_content, "meta_data": {"url": content_url_str}})
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data_content.append(doc_content)
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doc_id = hashlib.sha256((content_url_str + ", ".join(data_content)).encode()).hexdigest()
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return {"doc_id": doc_id, "data": data}
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