langchain/docs/versioned_docs/version-0.2.x/integrations/document_loaders/airbyte_cdk.ipynb

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   "metadata": {},
   "source": [
    "# Airbyte CDK (Deprecated)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "35ac77b1-449b-44f7-b8f3-3494d55c286e",
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   "source": [
    "Note: `AirbyteCDKLoader` is deprecated. Please use [`AirbyteLoader`](/docs/integrations/document_loaders/airbyte) instead.\n",
    "\n",
    ">[Airbyte](https://github.com/airbytehq/airbyte) is a data integration platform for ELT pipelines from APIs, databases & files to warehouses & lakes. It has the largest catalog of ELT connectors to data warehouses and databases.\n",
    "\n",
    "A lot of source connectors are implemented using the [Airbyte CDK](https://docs.airbyte.com/connector-development/cdk-python/). This loader allows to run any of these connectors and return the data as documents."
   ]
  },
  {
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   "metadata": {},
   "source": [
    "## Installation"
   ]
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   "source": [
    "First, you need to install the `airbyte-cdk` python package."
   ]
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  {
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   "source": [
    "%pip install --upgrade --quiet  airbyte-cdk"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "085aa658",
   "metadata": {},
   "source": [
    "Then, either install an existing connector from the [Airbyte Github repository](https://github.com/airbytehq/airbyte/tree/master/airbyte-integrations/connectors) or create your own connector using the [Airbyte CDK](https://docs.airbyte.io/connector-development/connector-development).\n",
    "\n",
    "For example, to install the Github connector, run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6d04ef4",
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   "outputs": [],
   "source": [
    "%pip install --upgrade --quiet  \"source_github@git+https://github.com/airbytehq/airbyte.git@master#subdirectory=airbyte-integrations/connectors/source-github\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "36069b74",
   "metadata": {},
   "source": [
    "Some sources are also published as regular packages on PyPI"
   ]
  },
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   "metadata": {},
   "source": [
    "## Example"
   ]
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   "source": [
    "Now you can create an `AirbyteCDKLoader` based on the imported source. It takes a `config` object that's passed to the connector. You also have to pick the stream you want to retrieve records from by name (`stream_name`). Check the connectors documentation page and spec definition for more information on the config object and available streams. For the Github connectors these are:\n",
    "\n",
    "* [https://github.com/airbytehq/airbyte/blob/master/airbyte-integrations/connectors/source-github/source_github/spec.json](https://github.com/airbytehq/airbyte/blob/master/airbyte-integrations/connectors/source-github/source_github/spec.json).\n",
    "* [https://docs.airbyte.com/integrations/sources/github/](https://docs.airbyte.com/integrations/sources/github/)"
   ]
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  {
   "cell_type": "code",
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   "source": [
    "from langchain_community.document_loaders.airbyte import AirbyteCDKLoader\n",
    "from source_github.source import SourceGithub  # plug in your own source here\n",
    "\n",
    "config = {\n",
    "    # your github configuration\n",
    "    \"credentials\": {\"api_url\": \"api.github.com\", \"personal_access_token\": \"<token>\"},\n",
    "    \"repository\": \"<repo>\",\n",
    "    \"start_date\": \"<date from which to start retrieving records from in ISO format, e.g. 2020-10-20T00:00:00Z>\",\n",
    "}\n",
    "\n",
    "issues_loader = AirbyteCDKLoader(\n",
    "    source_class=SourceGithub, config=config, stream_name=\"issues\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2cea23fc",
   "metadata": {},
   "source": [
    "Now you can load documents the usual way"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dae75cdb",
   "metadata": {},
   "outputs": [],
   "source": [
    "docs = issues_loader.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a93dc2a",
   "metadata": {},
   "source": [
    "As `load` returns a list, it will block until all documents are loaded. To have better control over this process, you can also you the `lazy_load` method which returns an iterator instead:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1782db09",
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   "source": [
    "docs_iterator = issues_loader.lazy_load()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a124086",
   "metadata": {},
   "source": [
    "Keep in mind that by default the page content is empty and the metadata object contains all the information from the record. To create documents in a different, pass in a record_handler function when creating the loader:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5671395d",
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   "source": [
    "from langchain.docstore.document import Document\n",
    "\n",
    "\n",
    "def handle_record(record, id):\n",
    "    return Document(\n",
    "        page_content=record.data[\"title\"] + \"\\n\" + (record.data[\"body\"] or \"\"),\n",
    "        metadata=record.data,\n",
    "    )\n",
    "\n",
    "\n",
    "issues_loader = AirbyteCDKLoader(\n",
    "    source_class=SourceGithub,\n",
    "    config=config,\n",
    "    stream_name=\"issues\",\n",
    "    record_handler=handle_record,\n",
    ")\n",
    "\n",
    "docs = issues_loader.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "223eb8bc",
   "metadata": {},
   "source": [
    "## Incremental loads\n",
    "\n",
    "Some streams allow incremental loading, this means the source keeps track of synced records and won't load them again. This is useful for sources that have a high volume of data and are updated frequently.\n",
    "\n",
    "To take advantage of this, store the `last_state` property of the loader and pass it in when creating the loader again. This will ensure that only new records are loaded."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7061e735",
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   "outputs": [],
   "source": [
    "last_state = issues_loader.last_state  # store safely\n",
    "\n",
    "incremental_issue_loader = AirbyteCDKLoader(\n",
    "    source_class=SourceGithub, config=config, stream_name=\"issues\", state=last_state\n",
    ")\n",
    "\n",
    "new_docs = incremental_issue_loader.load()"
   ]
  }
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