feat: attempt to make embedchain optional (#450)

* fix: attempt to make embedchain optional

* fix: drop pydantic_settings dependency

* fix: ensure the package is importable without any extra dependency

After making embedchain option many packages were unstalled which caused errors in some tools due to failing import directives

src/crewai_tools/adapters/embedchain_adapter.py

@@ -1,14 +1,23 @@
 from typing import Any
 
-from embedchain import App
-
 from crewai_tools.tools.rag.rag_tool import Adapter
 
+try:
+    from embedchain import App
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 
 class EmbedchainAdapter(Adapter):
-    embedchain_app: App
+    embedchain_app: Any  # Will be App when embedchain is available
     summarize: bool = False
 
+    def __init__(self, **data):
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
+        super().__init__(**data)
+
     def query(self, question: str) -> str:
         result, sources = self.embedchain_app.query(
             question, citations=True, dry_run=(not self.summarize)

src/crewai_tools/adapters/pdf_embedchain_adapter.py

@@ -1,15 +1,24 @@
 from typing import Any, Optional
 
-from embedchain import App
-
 from crewai_tools.tools.rag.rag_tool import Adapter
 
+try:
+    from embedchain import App
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 
 class PDFEmbedchainAdapter(Adapter):
-    embedchain_app: App
+    embedchain_app: Any  # Will be App when embedchain is available
     summarize: bool = False
     src: Optional[str] = None
 
+    def __init__(self, **data):
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
+        super().__init__(**data)
+
     def query(self, question: str) -> str:
         where = (
             {"app_id": self.embedchain_app.config.id, "source": self.src}

src/crewai_tools/tools/brightdata_tool/brightdata_dataset.py

@@ -5,15 +5,19 @@ from typing import Any, Dict, Optional, Type
 import aiohttp
 from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
-from pydantic_settings import BaseSettings
 
-class BrightDataConfig(BaseSettings):
+class BrightDataConfig(BaseModel):
     API_URL: str = "https://api.brightdata.com"
     DEFAULT_TIMEOUT: int = 600
     DEFAULT_POLLING_INTERVAL: int = 1
 
-    class Config:
-        env_prefix = "BRIGHTDATA_"
+    @classmethod
+    def from_env(cls):
+        return cls(
+            API_URL=os.environ.get("BRIGHTDATA_API_URL", "https://api.brightdata.com"),
+            DEFAULT_TIMEOUT=int(os.environ.get("BRIGHTDATA_DEFAULT_TIMEOUT", "600")),
+            DEFAULT_POLLING_INTERVAL=int(os.environ.get("BRIGHTDATA_DEFAULT_POLLING_INTERVAL", "1"))
+        )
 class BrightDataDatasetToolException(Exception):
     """Exception raised for custom error in the application."""
 
@@ -48,7 +52,7 @@ class BrightDataDatasetToolSchema(BaseModel):
         default=None, description="Additional params if any"
     )
 
-config = BrightDataConfig()
+config = BrightDataConfig.from_env()
 
 BRIGHTDATA_API_URL = config.API_URL
 timeout = config.DEFAULT_TIMEOUT

src/crewai_tools/tools/brightdata_tool/brightdata_serp.py

@@ -5,12 +5,15 @@ from typing import Any, Optional, Type
 import requests
 from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
-from pydantic_settings import BaseSettings
 
-class BrightDataConfig(BaseSettings):
+class BrightDataConfig(BaseModel):
     API_URL: str = "https://api.brightdata.com/request"
-    class Config:
-        env_prefix = "BRIGHTDATA_"
+
+    @classmethod
+    def from_env(cls):
+        return cls(
+            API_URL=os.environ.get("BRIGHTDATA_API_URL", "https://api.brightdata.com/request")
+        )
 
 class BrightDataSearchToolSchema(BaseModel):
     """
@@ -73,7 +76,7 @@ class BrightDataSearchTool(BaseTool):
     name: str = "Bright Data SERP Search"
     description: str = "Tool to perform web search using Bright Data SERP API."
     args_schema: Type[BaseModel] = BrightDataSearchToolSchema
-    _config = BrightDataConfig() 
+    _config = BrightDataConfig.from_env()
     base_url: str = ""
     api_key: str = ""
     zone: str = ""

src/crewai_tools/tools/brightdata_tool/brightdata_unlocker.py

@@ -4,12 +4,15 @@ from typing import Any, Optional, Type
 import requests
 from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
-from pydantic_settings import BaseSettings
 
-class BrightDataConfig(BaseSettings):
+class BrightDataConfig(BaseModel):
     API_URL: str = "https://api.brightdata.com/request"
-    class Config:
-        env_prefix = "BRIGHTDATA_"
+
+    @classmethod
+    def from_env(cls):
+        return cls(
+            API_URL=os.environ.get("BRIGHTDATA_API_URL", "https://api.brightdata.com/request")
+        )
 
 class BrightDataUnlockerToolSchema(BaseModel):
     """
@@ -57,7 +60,7 @@ class BrightDataWebUnlockerTool(BaseTool):
     name: str = "Bright Data Web Unlocker Scraping"
     description: str = "Tool to perform web scraping using Bright Data Web Unlocker"
     args_schema: Type[BaseModel] = BrightDataUnlockerToolSchema
-    _config = BrightDataConfig() 
+    _config = BrightDataConfig.from_env()
     base_url: str = ""
     api_key: str = ""
     zone: str = ""

src/crewai_tools/tools/code_docs_search_tool/code_docs_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Any, Optional, Type
 
-from embedchain.models.data_type import DataType
+try:
+    from embedchain.models.data_type import DataType
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool
@@ -37,6 +42,8 @@ class CodeDocsSearchTool(RagTool):
             self._generate_description()
 
     def add(self, docs_url: str) -> None:
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().add(docs_url, data_type=DataType.DOCS_SITE)
 
     def _run(

src/crewai_tools/tools/csv_search_tool/csv_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Optional, Type
 
-from embedchain.models.data_type import DataType
+try:
+    from embedchain.models.data_type import DataType
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool
@@ -37,6 +42,8 @@ class CSVSearchTool(RagTool):
             self._generate_description()
 
     def add(self, csv: str) -> None:
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().add(csv, data_type=DataType.CSV)
 
     def _run(

src/crewai_tools/tools/directory_search_tool/directory_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Optional, Type
 
-from embedchain.loaders.directory_loader import DirectoryLoader
+try:
+    from embedchain.loaders.directory_loader import DirectoryLoader
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool
@@ -29,6 +34,8 @@ class DirectorySearchTool(RagTool):
     args_schema: Type[BaseModel] = DirectorySearchToolSchema
 
     def __init__(self, directory: Optional[str] = None, **kwargs):
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().__init__(**kwargs)
         if directory is not None:
             self.add(directory)

src/crewai_tools/tools/docx_search_tool/docx_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Any, Optional, Type
 
-from embedchain.models.data_type import DataType
+try:
+    from embedchain.models.data_type import DataType
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool
@@ -43,6 +48,8 @@ class DOCXSearchTool(RagTool):
             self._generate_description()
 
     def add(self, docx: str) -> None:
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().add(docx, data_type=DataType.DOCX)
 
     def _run(

src/crewai_tools/tools/github_search_tool/github_search_tool.py

@@ -1,6 +1,11 @@
-from typing import List, Optional, Type
+from typing import List, Optional, Type, Any
+
+try:
+    from embedchain.loaders.github import GithubLoader
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
 
-from embedchain.loaders.github import GithubLoader
 from pydantic import BaseModel, Field, PrivateAttr
 
 from ..rag.rag_tool import RagTool
@@ -37,7 +42,7 @@ class GithubSearchTool(RagTool):
         default_factory=lambda: ["code", "repo", "pr", "issue"],
         description="Content types you want to be included search, options: [code, repo, pr, issue]",
     )
-    _loader: GithubLoader | None = PrivateAttr(default=None)
+    _loader: Any | None = PrivateAttr(default=None)
 
     def __init__(
         self,
@@ -45,6 +50,8 @@ class GithubSearchTool(RagTool):
         content_types: Optional[List[str]] = None,
         **kwargs,
     ):
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().__init__(**kwargs)
         self._loader = GithubLoader(config={"token": self.gh_token})
 

src/crewai_tools/tools/mdx_search_tool/mdx_search_tool.py

@@ -1,8 +1,13 @@
 from typing import Optional, Type
 
-from embedchain.models.data_type import DataType
 from pydantic import BaseModel, Field
 
+try:
+    from embedchain.models.data_type import DataType
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from ..rag.rag_tool import RagTool
 
 
@@ -37,6 +42,8 @@ class MDXSearchTool(RagTool):
             self._generate_description()
 
     def add(self, mdx: str) -> None:
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().add(mdx, data_type=DataType.MDX)
 
     def _run(

src/crewai_tools/tools/mysql_search_tool/mysql_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Any, Type
 
-from embedchain.loaders.mysql import MySQLLoader
+try:
+    from embedchain.loaders.mysql import MySQLLoader
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool
@@ -22,6 +27,8 @@ class MySQLSearchTool(RagTool):
     db_uri: str = Field(..., description="Mandatory database URI")
 
     def __init__(self, table_name: str, **kwargs):
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().__init__(**kwargs)
         kwargs["data_type"] = "mysql"
         kwargs["loader"] = MySQLLoader(config=dict(url=self.db_uri))

src/crewai_tools/tools/nl2sql/nl2sql_tool.py

@@ -2,8 +2,13 @@ from typing import Any, Type, Union
 
 from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
-from sqlalchemy import create_engine, text
-from sqlalchemy.orm import sessionmaker
+
+try:
+    from sqlalchemy import create_engine, text
+    from sqlalchemy.orm import sessionmaker
+    SQLALCHEMY_AVAILABLE = True
+except ImportError:
+    SQLALCHEMY_AVAILABLE = False
 
 
 class NL2SQLToolInput(BaseModel):
@@ -25,6 +30,9 @@ class NL2SQLTool(BaseTool):
     args_schema: Type[BaseModel] = NL2SQLToolInput
 
     def model_post_init(self, __context: Any) -> None:
+        if not SQLALCHEMY_AVAILABLE:
+            raise ImportError("sqlalchemy is not installed. Please install it with `pip install crewai-tools[sqlalchemy]`")
+
         data = {}
         tables = self._fetch_available_tables()
 
@@ -58,6 +66,9 @@ class NL2SQLTool(BaseTool):
         return data
 
     def execute_sql(self, sql_query: str) -> Union[list, str]:
+        if not SQLALCHEMY_AVAILABLE:
+            raise ImportError("sqlalchemy is not installed. Please install it with `pip install crewai-tools[sqlalchemy]`")
+
         engine = create_engine(self.db_uri)
         Session = sessionmaker(bind=engine)
         session = Session()

src/crewai_tools/tools/pdf_search_tool/pdf_search_tool.py

@@ -1,8 +1,13 @@
 from typing import Optional, Type
 
-from embedchain.models.data_type import DataType
 from pydantic import BaseModel, Field
 
+try:
+    from embedchain.models.data_type import DataType
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from ..rag.rag_tool import RagTool
 
 
@@ -36,6 +41,8 @@ class PDFSearchTool(RagTool):
             self._generate_description()
 
     def add(self, pdf: str) -> None:
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().add(pdf, data_type=DataType.PDF_FILE)
 
     def _run(

src/crewai_tools/tools/pg_search_tool/pg_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Any, Type
 
-from embedchain.loaders.postgres import PostgresLoader
+try:
+    from embedchain.loaders.postgres import PostgresLoader
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool
@@ -22,6 +27,8 @@ class PGSearchTool(RagTool):
     db_uri: str = Field(..., description="Mandatory database URI")
 
     def __init__(self, table_name: str, **kwargs):
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().__init__(**kwargs)
         kwargs["data_type"] = "postgres"
         kwargs["loader"] = PostgresLoader(config=dict(url=self.db_uri))

src/crewai_tools/tools/rag/rag_tool.py

@@ -40,7 +40,11 @@ class RagTool(BaseTool):
     @model_validator(mode="after")
     def _set_default_adapter(self):
         if isinstance(self.adapter, RagTool._AdapterPlaceholder):
+            try:
                 from embedchain import App
+            except ImportError:
+                raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
+
             from crewai_tools.adapters.embedchain_adapter import EmbedchainAdapter
 
             with portalocker.Lock("crewai-rag-tool.lock", timeout=10):

src/crewai_tools/tools/scrape_element_from_website/scrape_element_from_website.py

@@ -2,10 +2,15 @@ import os
 from typing import Any, Optional, Type
 
 import requests
-from bs4 import BeautifulSoup
 from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
 
+try:
+    from bs4 import BeautifulSoup
+    BEAUTIFULSOUP_AVAILABLE = True
+except ImportError:
+    BEAUTIFULSOUP_AVAILABLE = False
+
 
 class FixedScrapeElementFromWebsiteToolSchema(BaseModel):
     """Input for ScrapeElementFromWebsiteTool."""
@@ -61,6 +66,9 @@ class ScrapeElementFromWebsiteTool(BaseTool):
         self,
         **kwargs: Any,
     ) -> Any:
+        if not BEAUTIFULSOUP_AVAILABLE:
+            raise ImportError("beautifulsoup4 is not installed. Please install it with `pip install crewai-tools[beautifulsoup4]`")
+
         website_url = kwargs.get("website_url", self.website_url)
         css_element = kwargs.get("css_element", self.css_element)
         page = requests.get(

src/crewai_tools/tools/scrape_website_tool/scrape_website_tool.py

@@ -3,7 +3,11 @@ import re
 from typing import Any, Optional, Type
 
 import requests
-from bs4 import BeautifulSoup
+try:
+    from bs4 import BeautifulSoup
+    BEAUTIFULSOUP_AVAILABLE = True
+except ImportError:
+    BEAUTIFULSOUP_AVAILABLE = False
 from crewai.tools import BaseTool
 from pydantic import BaseModel, Field
 
@@ -40,6 +44,9 @@ class ScrapeWebsiteTool(BaseTool):
         **kwargs,
     ):
         super().__init__(**kwargs)
+        if not BEAUTIFULSOUP_AVAILABLE:
+            raise ImportError("beautifulsoup4 is not installed. Please install it with `pip install crewai-tools[beautifulsoup4]`")
+
         if website_url is not None:
             self.website_url = website_url
             self.description = (

src/crewai_tools/tools/website_search/website_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Any, Optional, Type
 
-from embedchain.models.data_type import DataType
+try:
+    from embedchain.models.data_type import DataType
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool
@@ -39,6 +44,8 @@ class WebsiteSearchTool(RagTool):
             self._generate_description()
 
     def add(self, website: str) -> None:
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().add(website, data_type=DataType.WEB_PAGE)
 
     def _run(

src/crewai_tools/tools/youtube_channel_search_tool/youtube_channel_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Any, Optional, Type
 
-from embedchain.models.data_type import DataType
+try:
+    from embedchain.models.data_type import DataType
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool

src/crewai_tools/tools/youtube_video_search_tool/youtube_video_search_tool.py

@@ -1,6 +1,11 @@
 from typing import Any, Optional, Type
 
-from embedchain.models.data_type import DataType
+try:
+    from embedchain.models.data_type import DataType
+    EMBEDCHAIN_AVAILABLE = True
+except ImportError:
+    EMBEDCHAIN_AVAILABLE = False
+
 from pydantic import BaseModel, Field
 
 from ..rag.rag_tool import RagTool
@@ -39,6 +44,8 @@ class YoutubeVideoSearchTool(RagTool):
             self._generate_description()
 
     def add(self, youtube_video_url: str) -> None:
+        if not EMBEDCHAIN_AVAILABLE:
+            raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
         super().add(youtube_video_url, data_type=DataType.YOUTUBE_VIDEO)
 
     def _run(