import dataclasses
import os
from typing import Any, Iterator, Literal, Optional
from langchain_core.document_loaders import BaseLoader
from langchain_core.documents import Document
from langchain_core.utils import get_from_env
[docs]
class FireCrawlLoader(BaseLoader):
"""
FireCrawlLoader document loader integration
Setup:
Install ``firecrawl-py``,``langchain_community`` and set environment variable ``FIRECRAWL_API_KEY``.
.. code-block:: bash
pip install -U firecrawl-py langchain_community
export FIRECRAWL_API_KEY="your-api-key"
Instantiate:
.. code-block:: python
from langchain_community.document_loaders import FireCrawlLoader
loader = FireCrawlLoader(
url = "https://firecrawl.dev",
mode = "crawl"
# other params = ...
)
Lazy load:
.. code-block:: python
docs = []
docs_lazy = loader.lazy_load()
# async variant:
# docs_lazy = await loader.alazy_load()
for doc in docs_lazy:
docs.append(doc)
print(docs[0].page_content[:100])
print(docs[0].metadata)
.. code-block:: python
Introducing [Smart Crawl!](https://www.firecrawl.dev/smart-crawl)
Join the waitlist to turn any web
{'ogUrl': 'https://www.firecrawl.dev/', 'title': 'Home - Firecrawl', 'robots': 'follow, index', 'ogImage': 'https://www.firecrawl.dev/og.png?123', 'ogTitle': 'Firecrawl', 'sitemap': {'lastmod': '2024-08-12T00:28:16.681Z', 'changefreq': 'weekly'}, 'keywords': 'Firecrawl,Markdown,Data,Mendable,Langchain', 'sourceURL': 'https://www.firecrawl.dev/', 'ogSiteName': 'Firecrawl', 'description': 'Firecrawl crawls and converts any website into clean markdown.', 'ogDescription': 'Turn any website into LLM-ready data.', 'pageStatusCode': 200, 'ogLocaleAlternate': []}
Async load:
.. code-block:: python
docs = await loader.aload()
print(docs[0].page_content[:100])
print(docs[0].metadata)
.. code-block:: python
Introducing [Smart Crawl!](https://www.firecrawl.dev/smart-crawl)
Join the waitlist to turn any web
{'ogUrl': 'https://www.firecrawl.dev/', 'title': 'Home - Firecrawl', 'robots': 'follow, index', 'ogImage': 'https://www.firecrawl.dev/og.png?123', 'ogTitle': 'Firecrawl', 'sitemap': {'lastmod': '2024-08-12T00:28:16.681Z', 'changefreq': 'weekly'}, 'keywords': 'Firecrawl,Markdown,Data,Mendable,Langchain', 'sourceURL': 'https://www.firecrawl.dev/', 'ogSiteName': 'Firecrawl', 'description': 'Firecrawl crawls and converts any website into clean markdown.', 'ogDescription': 'Turn any website into LLM-ready data.', 'pageStatusCode': 200, 'ogLocaleAlternate': []}
""" # noqa: E501
# No legacy support in v2-only implementation
[docs]
def __init__(
self,
url: Optional[str] = None,
*,
query: Optional[str] = None,
api_key: Optional[str] = None,
api_url: Optional[str] = None,
mode: Literal["crawl", "scrape", "map", "extract", "search"] = "crawl",
params: Optional[dict] = None,
):
"""Initialize with API key and url.
Args:
url: The url to be crawled.
api_key: The Firecrawl API key. If not specified will be read from env var
FIRECRAWL_API_KEY. Get an API key
api_url: The Firecrawl API URL. If not specified will be read from env var
FIRECRAWL_API_URL or defaults to https://api.firecrawl.dev.
mode: The mode to run the loader in. Default is "crawl".
Options include "scrape" (single url),
"crawl" (all accessible sub pages),
"map" (returns list of links that are semantically related).
"extract" (extracts structured data from a page).
"search" (search for data across the web).
params: The parameters to pass to the Firecrawl API.
Examples include crawlerOptions.
For more details, visit: https://github.com/mendableai/firecrawl-py
"""
try:
from firecrawl import FirecrawlApp
except ImportError:
raise ImportError(
"`firecrawl` package not found, please run `pip install firecrawl-py`"
)
if mode not in ("crawl", "scrape", "search", "map", "extract", "search"):
raise ValueError(
f"""Invalid mode '{mode}'.
Allowed: 'crawl', 'scrape', 'search', 'map', 'extract', 'search'."""
)
if mode in ("scrape", "crawl", "map", "extract") and not url:
raise ValueError("Url must be provided for modes other than 'search'")
if mode == "search" and not (query or (params and params.get("query"))):
raise ValueError("Query must be provided for search mode")
api_key = api_key or get_from_env("api_key", "FIRECRAWL_API_KEY")
# Ensure we never pass None for api_url (v2 client validates as str).
# Avoid get_from_env to prevent raising.
resolved_api_url = (
api_url or os.getenv("FIRECRAWL_API_URL") or "https://api.firecrawl.dev"
)
self.firecrawl = FirecrawlApp(api_key=api_key, api_url=resolved_api_url)
self.url = url or ""
self.mode = mode
self.params = params or {}
if query is not None:
self.params["query"] = query
[docs]
def lazy_load(self) -> Iterator[Document]:
# Prepare integration tag and filter params per method
firecrawl_docs: list[Any] = []
if self.mode == "scrape":
allowed = {
"formats",
"headers",
"include_tags",
"exclude_tags",
"only_main_content",
"timeout",
"wait_for",
"mobile",
"parsers",
"actions",
"location",
"skip_tls_verification",
"remove_base64_images",
"fast_mode",
"use_mock",
"block_ads",
"proxy",
"max_age",
"store_in_cache",
}
kwargs = {k: v for k, v in self.params.items() if k in allowed}
kwargs["integration"] = "langchain"
firecrawl_docs = [self.firecrawl.scrape(self.url, **kwargs)]
elif self.mode == "crawl":
if not self.url:
raise ValueError("URL is required for crawl mode")
allowed = {
"prompt",
"exclude_paths",
"include_paths",
"max_discovery_depth",
"ignore_sitemap",
"ignore_query_parameters",
"limit",
"crawl_entire_domain",
"allow_external_links",
"allow_subdomains",
"delay",
"max_concurrency",
"webhook",
"scrape_options",
"zero_data_retention",
"poll_interval",
"timeout",
}
kwargs = {k: v for k, v in self.params.items() if k in allowed}
kwargs["integration"] = "langchain"
crawl_response = self.firecrawl.crawl(self.url, **kwargs)
# Support dict or object with 'data'
if isinstance(crawl_response, dict):
data = crawl_response.get("data", [])
firecrawl_docs = list(data) if isinstance(data, list) else []
else:
data = getattr(crawl_response, "data", [])
firecrawl_docs = list(data) if isinstance(data, list) else []
elif self.mode == "map":
if not self.url:
raise ValueError("URL is required for map mode")
allowed = {
"search",
"include_subdomains",
"limit",
"sitemap",
"timeout",
"location",
}
kwargs = {k: v for k, v in self.params.items() if k in allowed}
kwargs["integration"] = "langchain"
map_response = self.firecrawl.map(self.url, **kwargs)
# Firecrawl v2 (>=4.3.6) returns an object with a `links` array
# Fallback to legacy list response if needed
if isinstance(map_response, dict):
links = map_response.get("links")
firecrawl_docs = list(links) if isinstance(links, list) else []
elif hasattr(map_response, "links"):
links = getattr(map_response, "links")
firecrawl_docs = list(links) if isinstance(links, list) else []
else:
is_list = isinstance(map_response, list)
firecrawl_docs = list(map_response) if is_list else []
elif self.mode == "extract":
if not self.url:
raise ValueError("URL is required for extract mode")
allowed = {
"prompt",
"schema",
"system_prompt",
"allow_external_links",
"enable_web_search",
"show_sources",
"scrape_options",
"ignore_invalid_urls",
"poll_interval",
"timeout",
"agent",
}
kwargs = {k: v for k, v in self.params.items() if k in allowed}
kwargs["integration"] = "langchain"
firecrawl_docs = [str(self.firecrawl.extract([self.url], **kwargs))]
elif self.mode == "search":
allowed = {
"sources",
"categories",
"limit",
"tbs",
"location",
"ignore_invalid_urls",
"timeout",
"scrape_options",
}
kwargs = {k: v for k, v in self.params.items() if k in allowed}
kwargs["integration"] = "langchain"
search_data = self.firecrawl.search(
query=self.params.get("query"), **kwargs
)
# If SDK already returns a list[dict], use it directly
if isinstance(search_data, list):
firecrawl_docs = list(search_data)
else:
# Normalize typed SearchData into list of dicts with markdown + metadata
results: list[dict[str, Any]] = []
containers = []
if isinstance(search_data, dict):
containers = [
search_data.get("web"),
search_data.get("news"),
search_data.get("images"),
]
else:
containers = [
getattr(search_data, "web", None),
getattr(search_data, "news", None),
getattr(search_data, "images", None),
]
for kind, items in (
("web", containers[0]),
("news", containers[1]),
("images", containers[2]),
):
if not items:
continue
for item in items:
url_val = (
getattr(item, "url", None)
if not isinstance(item, dict)
else item.get("url")
)
title_val = (
getattr(item, "title", None)
if not isinstance(item, dict)
else item.get("title")
)
desc_val = (
getattr(item, "description", None)
if not isinstance(item, dict)
else item.get("description")
)
content_val = desc_val or title_val or url_val or ""
metadata_val = {
k: v
for k, v in {
"url": url_val,
"title": title_val,
"category": getattr(item, "category", None)
if not isinstance(item, dict)
else item.get("category"),
"type": kind,
}.items()
if v is not None
}
results.append(
{"markdown": content_val, "metadata": metadata_val}
)
firecrawl_docs = results
else:
raise ValueError(
f"""Invalid mode '{self.mode}'.
Allowed: 'crawl', 'scrape', 'map', 'extract', 'search'."""
)
for doc in firecrawl_docs:
if self.mode == "map":
# Support both legacy string list and v2 link objects
if isinstance(doc, str):
page_content: str = doc
meta: dict[str, Any] = {}
elif isinstance(doc, dict):
page_content_value = doc.get("url") or doc.get("href") or ""
page_content = (
page_content_value
if isinstance(page_content_value, str)
else str(page_content_value or "")
)
meta = {
k: v
for k, v in {
"title": doc.get("title"),
"description": doc.get("description"),
}.items()
if v is not None
}
elif hasattr(doc, "url") or hasattr(doc, "title"):
page_content_value = getattr(doc, "url", "") or getattr(
doc, "href", ""
)
page_content = (
page_content_value
if isinstance(page_content_value, str)
else str(page_content_value or "")
)
meta = {}
title = getattr(doc, "title", None)
description = getattr(doc, "description", None)
if title is not None:
meta["title"] = title
if description is not None:
meta["description"] = description
else:
page_content = str(doc)
meta = {}
elif self.mode == "extract":
page_content = str(doc)
meta = {}
elif self.mode == "search":
# Already normalized to dicts with markdown/metadata above
if isinstance(doc, dict):
markdown_value = doc.get("markdown") or ""
page_content = (
markdown_value
if isinstance(markdown_value, str)
else str(markdown_value or "")
)
metadata_obj = doc.get("metadata", {})
meta = metadata_obj if isinstance(metadata_obj, dict) else {}
else:
page_content = str(doc)
meta = {}
else:
if isinstance(doc, dict):
content_value = (
doc.get("markdown") or doc.get("html") or doc.get("rawHtml", "")
)
page_content = (
content_value
if isinstance(content_value, str)
else str(content_value or "")
)
meta = doc.get("metadata", {})
else:
content_value = (
getattr(doc, "markdown", None)
or getattr(doc, "html", None)
or getattr(doc, "rawHtml", "")
)
page_content = (
content_value
if isinstance(content_value, str)
else str(content_value or "")
)
meta = getattr(doc, "metadata", {}) or {}
# Normalize metadata to plain dict for LangChain Document
if not isinstance(meta, dict):
if hasattr(meta, "model_dump") and callable(meta.model_dump):
meta = meta.model_dump()
elif dataclasses.is_dataclass(meta):
meta = dataclasses.asdict(meta) # type: ignore[arg-type]
elif hasattr(meta, "__dict__"):
meta = dict(vars(meta))
else:
meta = {"value": str(meta)}
if not page_content:
continue
yield Document(
page_content=page_content,
metadata=meta,
)
