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https://github.com/hwchase17/langchain.git
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0fdbaf4a8d
Fixes for Eden AI Custom tools and ChatEdenAI: - add missing import in __init__ of chat_models - add `args_schema` to custom tools. otherwise '__arg1' would sometimes be passed to the `run` method - fix IndexError when no human msg is added in ChatEdenAI
79 lines
2.4 KiB
Python
79 lines
2.4 KiB
Python
from __future__ import annotations
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import logging
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from typing import Optional, Type
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from langchain_core.callbacks import CallbackManagerForToolRun
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from langchain_core.pydantic_v1 import BaseModel, Field, HttpUrl
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from langchain_community.tools.edenai.edenai_base_tool import EdenaiTool
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logger = logging.getLogger(__name__)
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class InvoiceParsingInput(BaseModel):
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query: HttpUrl = Field(description="url of the document to parse")
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class EdenAiParsingInvoiceTool(EdenaiTool):
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"""Tool that queries the Eden AI Invoice parsing API.
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for api reference check edenai documentation:
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https://docs.edenai.co/reference/ocr_invoice_parser_create.
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To use, you should have
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the environment variable ``EDENAI_API_KEY`` set with your API token.
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You can find your token here: https://app.edenai.run/admin/account/settings
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"""
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name: str = "edenai_invoice_parsing"
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description: str = (
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"A wrapper around edenai Services invoice parsing. "
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"""Useful for when you have to extract information from
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an image it enables to take invoices
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in a variety of formats and returns the data in contains
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(items, prices, addresses, vendor name, etc.)
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in a structured format to automate the invoice processing """
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"Input should be the string url of the document to parse."
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)
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args_schema: Type[BaseModel] = InvoiceParsingInput
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language: Optional[str] = None
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"""
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language of the image passed to the model.
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"""
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feature: str = "ocr"
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subfeature: str = "invoice_parser"
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def _parse_response(self, response: list) -> str:
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formatted_list: list = []
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if len(response) == 1:
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self._parse_json_multilevel(
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response[0]["extracted_data"][0], formatted_list
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)
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else:
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for entry in response:
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if entry.get("provider") == "eden-ai":
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self._parse_json_multilevel(
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entry["extracted_data"][0], formatted_list
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)
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return "\n".join(formatted_list)
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def _run(
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self,
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query: str,
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run_manager: Optional[CallbackManagerForToolRun] = None,
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) -> str:
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"""Use the tool."""
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query_params = {
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"file_url": query,
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"language": self.language,
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"attributes_as_list": False,
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}
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return self._call_eden_ai(query_params)
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