fix: emit tool call events in provider-specific LLM streaming implementations

Fixes #3982

This commit adds tool call event emission to all provider-specific LLM
streaming implementations. Previously, only text chunks were emitted
during streaming, but tool call information was missing.

Changes:
- Update BaseLLM._emit_stream_chunk_event to infer call_type from
  tool_call presence when not explicitly provided
- Add tool call event emission in OpenAI provider streaming
- Add tool call event emission in Azure provider streaming
- Add tool call event emission in Gemini provider streaming
- Add tool call event emission in Bedrock provider streaming
- Add tool call event emission in Anthropic provider streaming
- Add comprehensive tests for tool call streaming events

The fix ensures that LLMStreamChunkEvent is emitted with:
- call_type=LLMCallType.TOOL_CALL when tool calls are received
- tool_call dict containing id, function (name, arguments), type, index
- chunk containing the tool call arguments being streamed

Co-Authored-By: João <joao@crewai.com>

lib/crewai-tools/pyproject.toml

@@ -16,9 +16,9 @@ dependencies = [
     "lancedb>=0.5.4",
     "tiktoken>=0.8.0",
     "beautifulsoup4>=4.13.4",
-    "pypdf>=5.9.0",
     "python-docx>=1.2.0",
     "youtube-transcript-api>=1.2.2",
+    "pymupdf>=1.26.6",
 ]
 
 

lib/crewai-tools/src/crewai_tools/adapters/crewai_rag_adapter.py

@@ -3,8 +3,7 @@
 from __future__ import annotations
 
 import hashlib
-from pathlib import Path
-from typing import TYPE_CHECKING, Any, TypeAlias, TypedDict, cast
+from typing import TYPE_CHECKING, Any, cast
 import uuid
 
 from crewai.rag.config.types import RagConfigType
@@ -19,15 +18,13 @@ from typing_extensions import TypeIs, Unpack
 from crewai_tools.rag.data_types import DataType
 from crewai_tools.rag.misc import sanitize_metadata_for_chromadb
 from crewai_tools.tools.rag.rag_tool import Adapter
+from crewai_tools.tools.rag.types import AddDocumentParams, ContentItem
 
 
 if TYPE_CHECKING:
     from crewai.rag.qdrant.config import QdrantConfig
 
 
-ContentItem: TypeAlias = str | Path | dict[str, Any]
-
-
 def _is_qdrant_config(config: Any) -> TypeIs[QdrantConfig]:
     """Check if config is a QdrantConfig using safe duck typing.
 
@@ -46,19 +43,6 @@ def _is_qdrant_config(config: Any) -> TypeIs[QdrantConfig]:
         return False
 
 
-class AddDocumentParams(TypedDict, total=False):
-    """Parameters for adding documents to the RAG system."""
-
-    data_type: DataType
-    metadata: dict[str, Any]
-    website: str
-    url: str
-    file_path: str | Path
-    github_url: str
-    youtube_url: str
-    directory_path: str | Path
-
-
 class CrewAIRagAdapter(Adapter):
     """Adapter that uses CrewAI's native RAG system.
 
@@ -131,13 +115,26 @@ class CrewAIRagAdapter(Adapter):
     def add(self, *args: ContentItem, **kwargs: Unpack[AddDocumentParams]) -> None:
         """Add content to the knowledge base.
 
-        This method handles various input types and converts them to documents
-        for the vector database. It supports the data_type parameter for
-        compatibility with existing tools.
-
         Args:
             *args: Content items to add (strings, paths, or document dicts)
-            **kwargs: Additional parameters including data_type, metadata, etc.
+            **kwargs: Additional parameters including:
+                - data_type: DataType enum or string (e.g., "file", "pdf_file", "text")
+                - path: Path to file or directory (alternative to positional arg)
+                - file_path: Alias for path
+                - metadata: Additional metadata to attach to documents
+                - url: URL to fetch content from
+                - website: Website URL to scrape
+                - github_url: GitHub repository URL
+                - youtube_url: YouTube video URL
+                - directory_path: Path to directory
+
+        Examples:
+            rag_tool.add("path/to/document.pdf", data_type=DataType.PDF_FILE)
+
+            rag_tool.add(path="path/to/document.pdf", data_type="file")
+            rag_tool.add(file_path="path/to/document.pdf", data_type="pdf_file")
+
+            rag_tool.add("path/to/document.pdf")  # auto-detects PDF
         """
         import os
 
@@ -146,10 +143,54 @@ class CrewAIRagAdapter(Adapter):
         from crewai_tools.rag.source_content import SourceContent
 
         documents: list[BaseRecord] = []
-        data_type: DataType | None = kwargs.get("data_type")
+        raw_data_type = kwargs.get("data_type")
         base_metadata: dict[str, Any] = kwargs.get("metadata", {})
 
-        for arg in args:
+        data_type: DataType | None = None
+        if raw_data_type is not None:
+            if isinstance(raw_data_type, DataType):
+                if raw_data_type != DataType.FILE:
+                    data_type = raw_data_type
+            elif isinstance(raw_data_type, str):
+                if raw_data_type != "file":
+                    try:
+                        data_type = DataType(raw_data_type)
+                    except ValueError:
+                        raise ValueError(
+                            f"Invalid data_type: '{raw_data_type}'. "
+                            f"Valid values are: 'file' (auto-detect), or one of: "
+                            f"{', '.join(dt.value for dt in DataType)}"
+                        ) from None
+
+        content_items: list[ContentItem] = list(args)
+
+        path_value = kwargs.get("path") or kwargs.get("file_path")
+        if path_value is not None:
+            content_items.append(path_value)
+
+        if url := kwargs.get("url"):
+            content_items.append(url)
+        if website := kwargs.get("website"):
+            content_items.append(website)
+        if github_url := kwargs.get("github_url"):
+            content_items.append(github_url)
+        if youtube_url := kwargs.get("youtube_url"):
+            content_items.append(youtube_url)
+        if directory_path := kwargs.get("directory_path"):
+            content_items.append(directory_path)
+
+        file_extensions = {
+            ".pdf",
+            ".txt",
+            ".csv",
+            ".json",
+            ".xml",
+            ".docx",
+            ".mdx",
+            ".md",
+        }
+
+        for arg in content_items:
             source_ref: str
             if isinstance(arg, dict):
                 source_ref = str(arg.get("source", arg.get("content", "")))
@@ -157,6 +198,14 @@ class CrewAIRagAdapter(Adapter):
                 source_ref = str(arg)
 
             if not data_type:
+                ext = os.path.splitext(source_ref)[1].lower()
+                is_url = source_ref.startswith(("http://", "https://", "file://"))
+                if (
+                    ext in file_extensions
+                    and not is_url
+                    and not os.path.isfile(source_ref)
+                ):
+                    raise FileNotFoundError(f"File does not exist: {source_ref}")
                 data_type = DataTypes.from_content(source_ref)
 
             if data_type == DataType.DIRECTORY:

lib/crewai-tools/src/crewai_tools/rag/data_types.py

@@ -1,6 +1,8 @@
 from enum import Enum
+from importlib import import_module
 import os
 from pathlib import Path
+from typing import cast
 from urllib.parse import urlparse
 
 from crewai_tools.rag.base_loader import BaseLoader
@@ -8,6 +10,7 @@ from crewai_tools.rag.chunkers.base_chunker import BaseChunker
 
 
 class DataType(str, Enum):
+    FILE = "file"
     PDF_FILE = "pdf_file"
     TEXT_FILE = "text_file"
     CSV = "csv"
@@ -15,22 +18,14 @@ class DataType(str, Enum):
     XML = "xml"
     DOCX = "docx"
     MDX = "mdx"
-
-    # Database types
     MYSQL = "mysql"
     POSTGRES = "postgres"
-
-    # Repository types
     GITHUB = "github"
     DIRECTORY = "directory"
-
-    # Web types
     WEBSITE = "website"
     DOCS_SITE = "docs_site"
     YOUTUBE_VIDEO = "youtube_video"
     YOUTUBE_CHANNEL = "youtube_channel"
-
-    # Raw types
     TEXT = "text"
 
     def get_chunker(self) -> BaseChunker:
@@ -63,13 +58,11 @@ class DataType(str, Enum):
 
         try:
             module = import_module(module_path)
-            return getattr(module, class_name)()
+            return cast(BaseChunker, getattr(module, class_name)())
         except Exception as e:
             raise ValueError(f"Error loading chunker for {self}: {e}") from e
 
     def get_loader(self) -> BaseLoader:
-        from importlib import import_module
-
         loaders = {
             DataType.PDF_FILE: ("pdf_loader", "PDFLoader"),
             DataType.TEXT_FILE: ("text_loader", "TextFileLoader"),
@@ -98,7 +91,7 @@ class DataType(str, Enum):
         module_path = f"crewai_tools.rag.loaders.{module_name}"
         try:
             module = import_module(module_path)
-            return getattr(module, class_name)()
+            return cast(BaseLoader, getattr(module, class_name)())
         except Exception as e:
             raise ValueError(f"Error loading loader for {self}: {e}") from e
 

lib/crewai-tools/src/crewai_tools/rag/loaders/pdf_loader.py

@@ -2,70 +2,112 @@
 
 import os
 from pathlib import Path
-from typing import Any
+from typing import Any, cast
+from urllib.parse import urlparse
+import urllib.request
 
 from crewai_tools.rag.base_loader import BaseLoader, LoaderResult
 from crewai_tools.rag.source_content import SourceContent
 
 
 class PDFLoader(BaseLoader):
-    """Loader for PDF files."""
+    """Loader for PDF files and URLs."""
 
-    def load(self, source: SourceContent, **kwargs) -> LoaderResult:  # type: ignore[override]
-        """Load and extract text from a PDF file.
+    @staticmethod
+    def _is_url(path: str) -> bool:
+        """Check if the path is a URL."""
+        try:
+            parsed = urlparse(path)
+            return parsed.scheme in ("http", "https")
+        except Exception:
+            return False
+
+    @staticmethod
+    def _download_pdf(url: str) -> bytes:
+        """Download PDF content from a URL.
 
         Args:
-            source: The source content containing the PDF file path
+            url: The URL to download from.
 
         Returns:
-            LoaderResult with extracted text content
+            The PDF content as bytes.
 
         Raises:
-            FileNotFoundError: If the PDF file doesn't exist
-            ImportError: If required PDF libraries aren't installed
+            ValueError: If the download fails.
+        """
+
+        try:
+            with urllib.request.urlopen(url, timeout=30) as response:  # noqa: S310
+                return cast(bytes, response.read())
+        except Exception as e:
+            raise ValueError(f"Failed to download PDF from {url}: {e!s}") from e
+
+    def load(self, source: SourceContent, **kwargs: Any) -> LoaderResult:  # type: ignore[override]
+        """Load and extract text from a PDF file or URL.
+
+        Args:
+            source: The source content containing the PDF file path or URL.
+
+        Returns:
+            LoaderResult with extracted text content.
+
+        Raises:
+            FileNotFoundError: If the PDF file doesn't exist.
+            ImportError: If required PDF libraries aren't installed.
+            ValueError: If the PDF cannot be read or downloaded.
         """
         try:
-            import pypdf
-        except ImportError:
-            try:
-                import PyPDF2 as pypdf  # type: ignore[import-not-found,no-redef]  # noqa: N813
-            except ImportError as e:
-                raise ImportError(
-                    "PDF support requires pypdf or PyPDF2. Install with: uv add pypdf"
-                ) from e
+            import pymupdf  # type: ignore[import-untyped]
+        except ImportError as e:
+            raise ImportError(
+                "PDF support requires pymupdf. Install with: uv add pymupdf"
+            ) from e
 
         file_path = source.source
+        is_url = self._is_url(file_path)
 
-        if not os.path.isfile(file_path):
-            raise FileNotFoundError(f"PDF file not found: {file_path}")
+        if is_url:
+            source_name = Path(urlparse(file_path).path).name or "downloaded.pdf"
+        else:
+            source_name = Path(file_path).name
 
-        text_content = []
+        text_content: list[str] = []
         metadata: dict[str, Any] = {
-            "source": str(file_path),
-            "file_name": Path(file_path).name,
+            "source": file_path,
+            "file_name": source_name,
             "file_type": "pdf",
         }
 
         try:
-            with open(file_path, "rb") as file:
-                pdf_reader = pypdf.PdfReader(file)
-                metadata["num_pages"] = len(pdf_reader.pages)
+            if is_url:
+                pdf_bytes = self._download_pdf(file_path)
+                doc = pymupdf.open(stream=pdf_bytes, filetype="pdf")
+            else:
+                if not os.path.isfile(file_path):
+                    raise FileNotFoundError(f"PDF file not found: {file_path}")
+                doc = pymupdf.open(file_path)
 
-                for page_num, page in enumerate(pdf_reader.pages, 1):
-                    page_text = page.extract_text()
-                    if page_text.strip():
-                        text_content.append(f"Page {page_num}:\n{page_text}")
+            metadata["num_pages"] = len(doc)
+
+            for page_num, page in enumerate(doc, 1):
+                page_text = page.get_text()
+                if page_text.strip():
+                    text_content.append(f"Page {page_num}:\n{page_text}")
+
+            doc.close()
+        except FileNotFoundError:
+            raise
         except Exception as e:
-            raise ValueError(f"Error reading PDF file {file_path}: {e!s}") from e
+            raise ValueError(f"Error reading PDF from {file_path}: {e!s}") from e
 
         if not text_content:
-            content = f"[PDF file with no extractable text: {Path(file_path).name}]"
+            content = f"[PDF file with no extractable text: {source_name}]"
         else:
             content = "\n\n".join(text_content)
 
         return LoaderResult(
             content=content,
-            source=str(file_path),
+            source=file_path,
             metadata=metadata,
-            doc_id=self.generate_doc_id(source_ref=str(file_path), content=content),
+            doc_id=self.generate_doc_id(source_ref=file_path, content=content),
         )

lib/crewai-tools/src/crewai_tools/tools/rag/rag_tool.py

@@ -14,9 +14,14 @@ from pydantic import (
     field_validator,
     model_validator,
 )
-from typing_extensions import Self
+from typing_extensions import Self, Unpack
 
-from crewai_tools.tools.rag.types import RagToolConfig, VectorDbConfig
+from crewai_tools.tools.rag.types import (
+    AddDocumentParams,
+    ContentItem,
+    RagToolConfig,
+    VectorDbConfig,
+)
 
 
 def _validate_embedding_config(
@@ -72,6 +77,8 @@ def _validate_embedding_config(
 
 
 class Adapter(BaseModel, ABC):
+    """Abstract base class for RAG adapters."""
+
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
     @abstractmethod
@@ -86,8 +93,8 @@ class Adapter(BaseModel, ABC):
     @abstractmethod
     def add(
         self,
-        *args: Any,
-        **kwargs: Any,
+        *args: ContentItem,
+        **kwargs: Unpack[AddDocumentParams],
     ) -> None:
         """Add content to the knowledge base."""
 
@@ -102,7 +109,11 @@ class RagTool(BaseTool):
         ) -> str:
             raise NotImplementedError
 
-        def add(self, *args: Any, **kwargs: Any) -> None:
+        def add(
+            self,
+            *args: ContentItem,
+            **kwargs: Unpack[AddDocumentParams],
+        ) -> None:
             raise NotImplementedError
 
     name: str = "Knowledge base"
@@ -207,9 +218,34 @@ class RagTool(BaseTool):
 
     def add(
         self,
-        *args: Any,
-        **kwargs: Any,
+        *args: ContentItem,
+        **kwargs: Unpack[AddDocumentParams],
     ) -> None:
+        """Add content to the knowledge base.
+
+
+        Args:
+            *args: Content items to add (strings, paths, or document dicts)
+            data_type: DataType enum or string (e.g., "file", "pdf_file", "text")
+            path: Path to file or directory, alias to positional arg
+            file_path: Alias for path
+            metadata: Additional metadata to attach to documents
+            url: URL to fetch content from
+            website: Website URL to scrape
+            github_url: GitHub repository URL
+            youtube_url: YouTube video URL
+            directory_path: Path to directory
+
+        Examples:
+            rag_tool.add("path/to/document.pdf", data_type=DataType.PDF_FILE)
+
+            # Keyword argument (documented API)
+            rag_tool.add(path="path/to/document.pdf", data_type="file")
+            rag_tool.add(file_path="path/to/document.pdf", data_type="pdf_file")
+
+            # Auto-detect type from extension
+            rag_tool.add("path/to/document.pdf")  # auto-detects PDF
+        """
         self.adapter.add(*args, **kwargs)
 
     def _run(

lib/crewai-tools/src/crewai_tools/tools/rag/types.py

@@ -1,10 +1,50 @@
 """Type definitions for RAG tool configuration."""
 
-from typing import Any, Literal
+from pathlib import Path
+from typing import Any, Literal, TypeAlias
 
 from crewai.rag.embeddings.types import ProviderSpec
 from typing_extensions import TypedDict
 
+from crewai_tools.rag.data_types import DataType
+
+
+DataTypeStr: TypeAlias = Literal[
+    "file",
+    "pdf_file",
+    "text_file",
+    "csv",
+    "json",
+    "xml",
+    "docx",
+    "mdx",
+    "mysql",
+    "postgres",
+    "github",
+    "directory",
+    "website",
+    "docs_site",
+    "youtube_video",
+    "youtube_channel",
+    "text",
+]
+
+ContentItem: TypeAlias = str | Path | dict[str, Any]
+
+
+class AddDocumentParams(TypedDict, total=False):
+    """Parameters for adding documents to the RAG system."""
+
+    data_type: DataType | DataTypeStr
+    metadata: dict[str, Any]
+    path: str | Path
+    file_path: str | Path
+    website: str
+    url: str
+    github_url: str
+    youtube_url: str
+    directory_path: str | Path
+
 
 class VectorDbConfig(TypedDict):
     """Configuration for vector database provider.

lib/crewai-tools/tests/tools/rag/test_rag_tool_add_data_type.py

@@ -0,0 +1,471 @@
+"""Tests for RagTool.add() method with various data_type values."""
+
+from pathlib import Path
+from tempfile import TemporaryDirectory
+from unittest.mock import MagicMock, Mock, patch
+
+import pytest
+
+from crewai_tools.rag.data_types import DataType
+from crewai_tools.tools.rag.rag_tool import RagTool
+
+
+@pytest.fixture
+def mock_rag_client() -> MagicMock:
+    """Create a mock RAG client for testing."""
+    mock_client = MagicMock()
+    mock_client.get_or_create_collection = MagicMock(return_value=None)
+    mock_client.add_documents = MagicMock(return_value=None)
+    mock_client.search = MagicMock(return_value=[])
+    return mock_client
+
+
+@pytest.fixture
+def rag_tool(mock_rag_client: MagicMock) -> RagTool:
+    """Create a RagTool instance with mocked client."""
+    with (
+        patch(
+            "crewai_tools.adapters.crewai_rag_adapter.get_rag_client",
+            return_value=mock_rag_client,
+        ),
+        patch(
+            "crewai_tools.adapters.crewai_rag_adapter.create_client",
+            return_value=mock_rag_client,
+        ),
+    ):
+        return RagTool()
+
+
+class TestDataTypeFileAlias:
+    """Tests for data_type='file' alias."""
+
+    def test_file_alias_with_existing_file(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test that data_type='file' works with existing files."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.txt"
+            test_file.write_text("Test content for file alias.")
+
+            rag_tool.add(path=str(test_file), data_type="file")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_file_alias_with_nonexistent_file_raises_error(
+        self, rag_tool: RagTool
+    ) -> None:
+        """Test that data_type='file' raises FileNotFoundError for missing files."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add(path="nonexistent/path/to/file.pdf", data_type="file")
+
+    def test_file_alias_with_path_keyword(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test that path keyword argument works with data_type='file'."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "document.txt"
+            test_file.write_text("Content via path keyword.")
+
+            rag_tool.add(data_type="file", path=str(test_file))
+
+            assert mock_rag_client.add_documents.called
+
+    def test_file_alias_with_file_path_keyword(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test that file_path keyword argument works with data_type='file'."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "document.txt"
+            test_file.write_text("Content via file_path keyword.")
+
+            rag_tool.add(data_type="file", file_path=str(test_file))
+
+            assert mock_rag_client.add_documents.called
+
+
+class TestDataTypeStringValues:
+    """Tests for data_type as string values matching DataType enum."""
+
+    def test_pdf_file_string(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test data_type='pdf_file' with existing PDF file."""
+        with TemporaryDirectory() as tmpdir:
+            # Create a minimal valid PDF file
+            test_file = Path(tmpdir) / "test.pdf"
+            test_file.write_bytes(
+                b"%PDF-1.4\n1 0 obj\n<<\n/Type /Catalog\n>>\nendobj\ntrailer\n"
+                b"<<\n/Root 1 0 R\n>>\n%%EOF"
+            )
+
+            # Mock the PDF loader to avoid actual PDF parsing
+            with patch(
+                "crewai_tools.adapters.crewai_rag_adapter.DataType.get_loader"
+            ) as mock_loader:
+                mock_loader_instance = MagicMock()
+                mock_loader_instance.load.return_value = MagicMock(
+                    content="PDF content", metadata={}, doc_id="test-id"
+                )
+                mock_loader.return_value = mock_loader_instance
+
+                rag_tool.add(path=str(test_file), data_type="pdf_file")
+
+                assert mock_rag_client.add_documents.called
+
+    def test_text_file_string(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test data_type='text_file' with existing text file."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.txt"
+            test_file.write_text("Plain text content.")
+
+            rag_tool.add(path=str(test_file), data_type="text_file")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_csv_string(self, rag_tool: RagTool, mock_rag_client: MagicMock) -> None:
+        """Test data_type='csv' with existing CSV file."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.csv"
+            test_file.write_text("name,value\nfoo,1\nbar,2")
+
+            rag_tool.add(path=str(test_file), data_type="csv")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_json_string(self, rag_tool: RagTool, mock_rag_client: MagicMock) -> None:
+        """Test data_type='json' with existing JSON file."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.json"
+            test_file.write_text('{"key": "value", "items": [1, 2, 3]}')
+
+            rag_tool.add(path=str(test_file), data_type="json")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_xml_string(self, rag_tool: RagTool, mock_rag_client: MagicMock) -> None:
+        """Test data_type='xml' with existing XML file."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.xml"
+            test_file.write_text('<?xml version="1.0"?><root><item>value</item></root>')
+
+            rag_tool.add(path=str(test_file), data_type="xml")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_mdx_string(self, rag_tool: RagTool, mock_rag_client: MagicMock) -> None:
+        """Test data_type='mdx' with existing MDX file."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.mdx"
+            test_file.write_text("# Heading\n\nSome markdown content.")
+
+            rag_tool.add(path=str(test_file), data_type="mdx")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_text_string(self, rag_tool: RagTool, mock_rag_client: MagicMock) -> None:
+        """Test data_type='text' with raw text content."""
+        rag_tool.add("This is raw text content.", data_type="text")
+
+        assert mock_rag_client.add_documents.called
+
+    def test_directory_string(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test data_type='directory' with existing directory."""
+        with TemporaryDirectory() as tmpdir:
+            # Create some files in the directory
+            (Path(tmpdir) / "file1.txt").write_text("Content 1")
+            (Path(tmpdir) / "file2.txt").write_text("Content 2")
+
+            rag_tool.add(path=tmpdir, data_type="directory")
+
+            assert mock_rag_client.add_documents.called
+
+
+class TestDataTypeEnumValues:
+    """Tests for data_type as DataType enum values."""
+
+    def test_datatype_file_enum_with_existing_file(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test data_type=DataType.FILE with existing file (auto-detect)."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.txt"
+            test_file.write_text("File enum auto-detect content.")
+
+            rag_tool.add(str(test_file), data_type=DataType.FILE)
+
+            assert mock_rag_client.add_documents.called
+
+    def test_datatype_file_enum_with_nonexistent_file_raises_error(
+        self, rag_tool: RagTool
+    ) -> None:
+        """Test data_type=DataType.FILE raises FileNotFoundError for missing files."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add("nonexistent/file.pdf", data_type=DataType.FILE)
+
+    def test_datatype_pdf_file_enum(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test data_type=DataType.PDF_FILE with existing file."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.pdf"
+            test_file.write_bytes(
+                b"%PDF-1.4\n1 0 obj\n<<\n/Type /Catalog\n>>\nendobj\ntrailer\n"
+                b"<<\n/Root 1 0 R\n>>\n%%EOF"
+            )
+
+            with patch(
+                "crewai_tools.adapters.crewai_rag_adapter.DataType.get_loader"
+            ) as mock_loader:
+                mock_loader_instance = MagicMock()
+                mock_loader_instance.load.return_value = MagicMock(
+                    content="PDF content", metadata={}, doc_id="test-id"
+                )
+                mock_loader.return_value = mock_loader_instance
+
+                rag_tool.add(str(test_file), data_type=DataType.PDF_FILE)
+
+                assert mock_rag_client.add_documents.called
+
+    def test_datatype_text_file_enum(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test data_type=DataType.TEXT_FILE with existing file."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.txt"
+            test_file.write_text("Text file content.")
+
+            rag_tool.add(str(test_file), data_type=DataType.TEXT_FILE)
+
+            assert mock_rag_client.add_documents.called
+
+    def test_datatype_text_enum(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test data_type=DataType.TEXT with raw text."""
+        rag_tool.add("Raw text using enum.", data_type=DataType.TEXT)
+
+        assert mock_rag_client.add_documents.called
+
+    def test_datatype_directory_enum(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test data_type=DataType.DIRECTORY with existing directory."""
+        with TemporaryDirectory() as tmpdir:
+            (Path(tmpdir) / "file.txt").write_text("Directory file content.")
+
+            rag_tool.add(tmpdir, data_type=DataType.DIRECTORY)
+
+            assert mock_rag_client.add_documents.called
+
+
+class TestInvalidDataType:
+    """Tests for invalid data_type values."""
+
+    def test_invalid_string_data_type_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that invalid string data_type raises ValueError."""
+        with pytest.raises(ValueError, match="Invalid data_type"):
+            rag_tool.add("some content", data_type="invalid_type")
+
+    def test_invalid_data_type_error_message_contains_valid_values(
+        self, rag_tool: RagTool
+    ) -> None:
+        """Test that error message lists valid data_type values."""
+        with pytest.raises(ValueError) as exc_info:
+            rag_tool.add("some content", data_type="not_a_type")
+
+        error_message = str(exc_info.value)
+        assert "file" in error_message
+        assert "pdf_file" in error_message
+        assert "text_file" in error_message
+
+
+class TestFileExistenceValidation:
+    """Tests for file existence validation."""
+
+    def test_pdf_file_not_found_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that non-existent PDF file raises FileNotFoundError."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add(path="nonexistent.pdf", data_type="pdf_file")
+
+    def test_text_file_not_found_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that non-existent text file raises FileNotFoundError."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add(path="nonexistent.txt", data_type="text_file")
+
+    def test_csv_file_not_found_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that non-existent CSV file raises FileNotFoundError."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add(path="nonexistent.csv", data_type="csv")
+
+    def test_json_file_not_found_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that non-existent JSON file raises FileNotFoundError."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add(path="nonexistent.json", data_type="json")
+
+    def test_xml_file_not_found_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that non-existent XML file raises FileNotFoundError."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add(path="nonexistent.xml", data_type="xml")
+
+    def test_docx_file_not_found_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that non-existent DOCX file raises FileNotFoundError."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add(path="nonexistent.docx", data_type="docx")
+
+    def test_mdx_file_not_found_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that non-existent MDX file raises FileNotFoundError."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add(path="nonexistent.mdx", data_type="mdx")
+
+    def test_directory_not_found_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that non-existent directory raises ValueError."""
+        with pytest.raises(ValueError, match="Directory does not exist"):
+            rag_tool.add(path="nonexistent/directory", data_type="directory")
+
+
+class TestKeywordArgumentVariants:
+    """Tests for different keyword argument combinations."""
+
+    def test_positional_argument_with_data_type(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test positional argument with data_type."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.txt"
+            test_file.write_text("Positional arg content.")
+
+            rag_tool.add(str(test_file), data_type="text_file")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_path_keyword_with_data_type(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test path keyword argument with data_type."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.txt"
+            test_file.write_text("Path keyword content.")
+
+            rag_tool.add(path=str(test_file), data_type="text_file")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_file_path_keyword_with_data_type(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test file_path keyword argument with data_type."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.txt"
+            test_file.write_text("File path keyword content.")
+
+            rag_tool.add(file_path=str(test_file), data_type="text_file")
+
+            assert mock_rag_client.add_documents.called
+
+    def test_directory_path_keyword(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test directory_path keyword argument."""
+        with TemporaryDirectory() as tmpdir:
+            (Path(tmpdir) / "file.txt").write_text("Directory content.")
+
+            rag_tool.add(directory_path=tmpdir)
+
+            assert mock_rag_client.add_documents.called
+
+
+class TestAutoDetection:
+    """Tests for auto-detection of data type from content."""
+
+    def test_auto_detect_nonexistent_file_raises_error(self, rag_tool: RagTool) -> None:
+        """Test that auto-detection raises FileNotFoundError for missing files."""
+        with pytest.raises(FileNotFoundError, match="File does not exist"):
+            rag_tool.add("path/to/document.pdf")
+
+    def test_auto_detect_txt_file(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test auto-detection of .txt file type."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "auto.txt"
+            test_file.write_text("Auto-detected text file.")
+
+            # No data_type specified - should auto-detect
+            rag_tool.add(str(test_file))
+
+            assert mock_rag_client.add_documents.called
+
+    def test_auto_detect_csv_file(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test auto-detection of .csv file type."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "auto.csv"
+            test_file.write_text("col1,col2\nval1,val2")
+
+            rag_tool.add(str(test_file))
+
+            assert mock_rag_client.add_documents.called
+
+    def test_auto_detect_json_file(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test auto-detection of .json file type."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "auto.json"
+            test_file.write_text('{"auto": "detected"}')
+
+            rag_tool.add(str(test_file))
+
+            assert mock_rag_client.add_documents.called
+
+    def test_auto_detect_directory(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test auto-detection of directory type."""
+        with TemporaryDirectory() as tmpdir:
+            (Path(tmpdir) / "file.txt").write_text("Auto-detected directory.")
+
+            rag_tool.add(tmpdir)
+
+            assert mock_rag_client.add_documents.called
+
+    def test_auto_detect_raw_text(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test auto-detection of raw text (non-file content)."""
+        rag_tool.add("Just some raw text content")
+
+        assert mock_rag_client.add_documents.called
+
+
+class TestMetadataHandling:
+    """Tests for metadata handling with data_type."""
+
+    def test_metadata_passed_to_documents(
+        self, rag_tool: RagTool, mock_rag_client: MagicMock
+    ) -> None:
+        """Test that metadata is properly passed to documents."""
+        with TemporaryDirectory() as tmpdir:
+            test_file = Path(tmpdir) / "test.txt"
+            test_file.write_text("Content with metadata.")
+
+            rag_tool.add(
+                path=str(test_file),
+                data_type="text_file",
+                metadata={"custom_key": "custom_value"},
+            )
+
+            assert mock_rag_client.add_documents.called
+            call_args = mock_rag_client.add_documents.call_args
+            documents = call_args.kwargs.get("documents", call_args.args[0] if call_args.args else [])
+
+            # Check that at least one document has the custom metadata
+            assert any(
+                doc.get("metadata", {}).get("custom_key") == "custom_value"
+                for doc in documents
+            )

lib/crewai/src/crewai/cli/config.py

@@ -73,6 +73,7 @@ CLI_SETTINGS_KEYS = [
     "oauth2_audience",
     "oauth2_client_id",
     "oauth2_domain",
+    "oauth2_extra",
 ]
 
 # Default values for CLI settings
@@ -82,6 +83,7 @@ DEFAULT_CLI_SETTINGS = {
     "oauth2_audience": CREWAI_ENTERPRISE_DEFAULT_OAUTH2_AUDIENCE,
     "oauth2_client_id": CREWAI_ENTERPRISE_DEFAULT_OAUTH2_CLIENT_ID,
     "oauth2_domain": CREWAI_ENTERPRISE_DEFAULT_OAUTH2_DOMAIN,
+    "oauth2_extra": {},
 }
 
 # Readonly settings - cannot be set by the user

lib/crewai/src/crewai/llms/base_llm.py

@@ -316,11 +316,33 @@ class BaseLLM(ABC):
         from_task: Task | None = None,
         from_agent: Agent | None = None,
         tool_call: dict[str, Any] | None = None,
+        call_type: LLMCallType | None = None,
     ) -> None:
-        """Emit stream chunk event."""
+        """Emit stream chunk event.
+
+        Args:
+            chunk: The text content of the chunk
+            from_task: Optional task that initiated the call
+            from_agent: Optional agent that initiated the call
+            tool_call: Optional tool call information as a dict with keys:
+                - id: Tool call ID
+                - function: Dict with 'name' and 'arguments'
+                - type: Tool call type (e.g., 'function')
+                - index: Index of the tool call
+            call_type: Optional call type. If not provided, it will be inferred
+                from the presence of tool_call (TOOL_CALL if tool_call is present,
+                LLM_CALL otherwise)
+        """
         if not hasattr(crewai_event_bus, "emit"):
             raise ValueError("crewai_event_bus does not have an emit method") from None
 
+        # Infer call_type from tool_call presence if not explicitly provided
+        effective_call_type = call_type
+        if effective_call_type is None:
+            effective_call_type = (
+                LLMCallType.TOOL_CALL if tool_call is not None else LLMCallType.LLM_CALL
+            )
+
         crewai_event_bus.emit(
             self,
             event=LLMStreamChunkEvent(
@@ -328,6 +350,7 @@ class BaseLLM(ABC):
                 tool_call=tool_call,
                 from_task=from_task,
                 from_agent=from_agent,
+                call_type=effective_call_type,
             ),
         )
 

lib/crewai/src/crewai/llms/providers/anthropic/completion.py

@@ -450,9 +450,14 @@ class AnthropicCompletion(BaseLLM):
         # (the SDK sets it internally)
         stream_params = {k: v for k, v in params.items() if k != "stream"}
 
+        # Track tool use blocks during streaming
+        current_tool_use: dict[str, Any] = {}
+        tool_use_index = 0
+
         # Make streaming API call
         with self.client.messages.stream(**stream_params) as stream:
             for event in stream:
+                # Handle text content
                 if hasattr(event, "delta") and hasattr(event.delta, "text"):
                     text_delta = event.delta.text
                     full_response += text_delta
@@ -462,6 +467,55 @@ class AnthropicCompletion(BaseLLM):
                         from_agent=from_agent,
                     )
 
+                # Handle tool use start (content_block_start event with tool_use type)
+                if hasattr(event, "content_block") and hasattr(event.content_block, "type"):
+                    if event.content_block.type == "tool_use":
+                        current_tool_use = {
+                            "id": getattr(event.content_block, "id", None),
+                            "name": getattr(event.content_block, "name", ""),
+                            "input": "",
+                            "index": tool_use_index,
+                        }
+                        tool_use_index += 1
+                        # Emit tool call start event
+                        tool_call_event_data = {
+                            "id": current_tool_use["id"],
+                            "function": {
+                                "name": current_tool_use["name"],
+                                "arguments": "",
+                            },
+                            "type": "function",
+                            "index": current_tool_use["index"],
+                        }
+                        self._emit_stream_chunk_event(
+                            chunk="",
+                            from_task=from_task,
+                            from_agent=from_agent,
+                            tool_call=tool_call_event_data,
+                        )
+
+                # Handle tool use input delta (input_json events)
+                if hasattr(event, "delta") and hasattr(event.delta, "partial_json"):
+                    partial_json = event.delta.partial_json
+                    if current_tool_use and partial_json:
+                        current_tool_use["input"] += partial_json
+                        # Emit tool call delta event
+                        tool_call_event_data = {
+                            "id": current_tool_use["id"],
+                            "function": {
+                                "name": current_tool_use["name"],
+                                "arguments": partial_json,
+                            },
+                            "type": "function",
+                            "index": current_tool_use["index"],
+                        }
+                        self._emit_stream_chunk_event(
+                            chunk=partial_json,
+                            from_task=from_task,
+                            from_agent=from_agent,
+                            tool_call=tool_call_event_data,
+                        )
+
             final_message: Message = stream.get_final_message()
 
         usage = self._extract_anthropic_token_usage(final_message)

lib/crewai/src/crewai/llms/providers/azure/completion.py

@@ -503,8 +503,10 @@ class AzureCompletion(BaseLLM):
                             call_id = tool_call.id or "default"
                             if call_id not in tool_calls:
                                 tool_calls[call_id] = {
+                                    "id": call_id,
                                     "name": "",
                                     "arguments": "",
+                                    "index": getattr(tool_call, "index", 0) or 0,
                                 }
 
                             if tool_call.function and tool_call.function.name:
@@ -514,6 +516,23 @@ class AzureCompletion(BaseLLM):
                                     tool_call.function.arguments
                                 )
 
+                            # Emit tool call streaming event
+                            tool_call_event_data = {
+                                "id": tool_calls[call_id]["id"],
+                                "function": {
+                                    "name": tool_calls[call_id]["name"],
+                                    "arguments": tool_call.function.arguments if tool_call.function and tool_call.function.arguments else "",
+                                },
+                                "type": "function",
+                                "index": tool_calls[call_id]["index"],
+                            }
+                            self._emit_stream_chunk_event(
+                                chunk=tool_call.function.arguments if tool_call.function and tool_call.function.arguments else "",
+                                from_task=from_task,
+                                from_agent=from_agent,
+                                tool_call=tool_call_event_data,
+                            )
+
         # Handle completed tool calls
         if tool_calls and available_functions:
             for call_data in tool_calls.values():

lib/crewai/src/crewai/llms/providers/bedrock/completion.py

@@ -567,12 +567,31 @@ class BedrockCompletion(BaseLLM):
 
                     elif "contentBlockStart" in event:
                         start = event["contentBlockStart"].get("start", {})
+                        block_index = event["contentBlockStart"].get("contentBlockIndex", 0)
                         if "toolUse" in start:
                             current_tool_use = start["toolUse"]
+                            current_tool_use["_block_index"] = block_index
+                            current_tool_use["_accumulated_input"] = ""
                             tool_use_id = current_tool_use.get("toolUseId")
                             logging.debug(
                                 f"Tool use started in stream: {current_tool_use.get('name')} (ID: {tool_use_id})"
                             )
+                            # Emit tool call start event
+                            tool_call_event_data = {
+                                "id": tool_use_id,
+                                "function": {
+                                    "name": current_tool_use.get("name", ""),
+                                    "arguments": "",
+                                },
+                                "type": "function",
+                                "index": block_index,
+                            }
+                            self._emit_stream_chunk_event(
+                                chunk="",
+                                from_task=from_task,
+                                from_agent=from_agent,
+                                tool_call=tool_call_event_data,
+                            )
 
                     elif "contentBlockDelta" in event:
                         delta = event["contentBlockDelta"]["delta"]
@@ -589,6 +608,23 @@ class BedrockCompletion(BaseLLM):
                             tool_input = delta["toolUse"].get("input", "")
                             if tool_input:
                                 logging.debug(f"Tool input delta: {tool_input}")
+                                current_tool_use["_accumulated_input"] += tool_input
+                                # Emit tool call delta event
+                                tool_call_event_data = {
+                                    "id": current_tool_use.get("toolUseId"),
+                                    "function": {
+                                        "name": current_tool_use.get("name", ""),
+                                        "arguments": tool_input,
+                                    },
+                                    "type": "function",
+                                    "index": current_tool_use.get("_block_index", 0),
+                                }
+                                self._emit_stream_chunk_event(
+                                    chunk=tool_input,
+                                    from_task=from_task,
+                                    from_agent=from_agent,
+                                    tool_call=tool_call_event_data,
+                                )
 
                     # Content block stop - end of a content block
                     elif "contentBlockStop" in event:

lib/crewai/src/crewai/llms/providers/gemini/completion.py

@@ -1,3 +1,4 @@
+import json
 import logging
 import os
 import re
@@ -496,7 +497,7 @@ class GeminiCompletion(BaseLLM):
             if hasattr(chunk, "candidates") and chunk.candidates:
                 candidate = chunk.candidates[0]
                 if candidate.content and candidate.content.parts:
-                    for part in candidate.content.parts:
+                    for part_index, part in enumerate(candidate.content.parts):
                         if hasattr(part, "function_call") and part.function_call:
                             call_id = part.function_call.name or "default"
                             if call_id not in function_calls:
@@ -505,8 +506,27 @@ class GeminiCompletion(BaseLLM):
                                     "args": dict(part.function_call.args)
                                     if part.function_call.args
                                     else {},
+                                    "index": part_index,
                                 }
 
+                            # Emit tool call streaming event
+                            args_str = json.dumps(function_calls[call_id]["args"]) if function_calls[call_id]["args"] else ""
+                            tool_call_event_data = {
+                                "id": call_id,
+                                "function": {
+                                    "name": function_calls[call_id]["name"],
+                                    "arguments": args_str,
+                                },
+                                "type": "function",
+                                "index": function_calls[call_id]["index"],
+                            }
+                            self._emit_stream_chunk_event(
+                                chunk=args_str,
+                                from_task=from_task,
+                                from_agent=from_agent,
+                                tool_call=tool_call_event_data,
+                            )
+
         # Handle completed function calls
         if function_calls and available_functions:
             for call_data in function_calls.values():

lib/crewai/src/crewai/llms/providers/openai/completion.py

@@ -510,8 +510,10 @@ class OpenAICompletion(BaseLLM):
                     call_id = tool_call.id or "default"
                     if call_id not in tool_calls:
                         tool_calls[call_id] = {
+                            "id": call_id,
                             "name": "",
                             "arguments": "",
+                            "index": tool_call.index if tool_call.index is not None else 0,
                         }
 
                     if tool_call.function and tool_call.function.name:
@@ -519,6 +521,23 @@ class OpenAICompletion(BaseLLM):
                     if tool_call.function and tool_call.function.arguments:
                         tool_calls[call_id]["arguments"] += tool_call.function.arguments
 
+                    # Emit tool call streaming event
+                    tool_call_event_data = {
+                        "id": tool_calls[call_id]["id"],
+                        "function": {
+                            "name": tool_calls[call_id]["name"],
+                            "arguments": tool_call.function.arguments if tool_call.function and tool_call.function.arguments else "",
+                        },
+                        "type": "function",
+                        "index": tool_calls[call_id]["index"],
+                    }
+                    self._emit_stream_chunk_event(
+                        chunk=tool_call.function.arguments if tool_call.function and tool_call.function.arguments else "",
+                        from_task=from_task,
+                        from_agent=from_agent,
+                        tool_call=tool_call_event_data,
+                    )
+
         if tool_calls and available_functions:
             for call_data in tool_calls.values():
                 function_name = call_data["name"]

lib/crewai/src/crewai/mcp/transports/sse.py

@@ -66,7 +66,6 @@ class SSETransport(BaseTransport):
             self._transport_context = sse_client(
                 self.url,
                 headers=self.headers if self.headers else None,
-                terminate_on_close=True,
             )
 
             read, write = await self._transport_context.__aenter__()

lib/crewai/tests/cli/test_config.py

@@ -72,7 +72,8 @@ class TestSettings(unittest.TestCase):
     @patch("crewai.cli.config.TokenManager")
     def test_reset_settings(self, mock_token_manager):
         user_settings = {key: f"value_for_{key}" for key in USER_SETTINGS_KEYS}
-        cli_settings = {key: f"value_for_{key}" for key in CLI_SETTINGS_KEYS}
+        cli_settings = {key: f"value_for_{key}" for key in CLI_SETTINGS_KEYS if key != "oauth2_extra"}
+        cli_settings["oauth2_extra"] = {"scope": "xxx", "other": "yyy"}
 
         settings = Settings(
             config_path=self.config_path, **user_settings, **cli_settings

lib/crewai/tests/mcp/test_sse_transport.py

@@ -0,0 +1,22 @@
+"""Tests for SSE transport."""
+
+import pytest
+
+from crewai.mcp.transports.sse import SSETransport
+
+
+@pytest.mark.asyncio
+async def test_sse_transport_connect_does_not_pass_invalid_args():
+    """Test that SSETransport.connect() doesn't pass invalid args to sse_client.
+
+    The sse_client function does not accept terminate_on_close parameter.
+    """
+    transport = SSETransport(
+        url="http://localhost:9999/sse",
+        headers={"Authorization": "Bearer test"},
+    )
+
+    with pytest.raises(ConnectionError) as exc_info:
+        await transport.connect()
+
+    assert "unexpected keyword argument" not in str(exc_info.value)

lib/crewai/tests/test_streaming.py

@@ -715,3 +715,243 @@ class TestStreamingImports:
         assert StreamChunk is not None
         assert StreamChunkType is not None
         assert ToolCallChunk is not None
+
+
+class TestLLMStreamChunkEventToolCall:
+    """Tests for LLMStreamChunkEvent with tool call information."""
+
+    def test_llm_stream_chunk_event_with_tool_call(self) -> None:
+        """Test that LLMStreamChunkEvent correctly handles tool call data."""
+        from crewai.events.types.llm_events import (
+            LLMCallType,
+            LLMStreamChunkEvent,
+            ToolCall,
+            FunctionCall,
+        )
+
+        # Create a tool call event
+        tool_call = ToolCall(
+            id="call-123",
+            function=FunctionCall(
+                name="search",
+                arguments='{"query": "test"}',
+            ),
+            type="function",
+            index=0,
+        )
+
+        event = LLMStreamChunkEvent(
+            chunk='{"query": "test"}',
+            tool_call=tool_call,
+            call_type=LLMCallType.TOOL_CALL,
+        )
+
+        assert event.chunk == '{"query": "test"}'
+        assert event.tool_call is not None
+        assert event.tool_call.id == "call-123"
+        assert event.tool_call.function.name == "search"
+        assert event.tool_call.function.arguments == '{"query": "test"}'
+        assert event.call_type == LLMCallType.TOOL_CALL
+
+    def test_llm_stream_chunk_event_with_dict_tool_call(self) -> None:
+        """Test that LLMStreamChunkEvent correctly handles tool call as dict."""
+        from crewai.events.types.llm_events import (
+            LLMCallType,
+            LLMStreamChunkEvent,
+        )
+
+        # Create a tool call event using dict (as providers emit)
+        tool_call_dict = {
+            "id": "call-456",
+            "function": {
+                "name": "get_weather",
+                "arguments": '{"location": "NYC"}',
+            },
+            "type": "function",
+            "index": 1,
+        }
+
+        event = LLMStreamChunkEvent(
+            chunk='{"location": "NYC"}',
+            tool_call=tool_call_dict,
+            call_type=LLMCallType.TOOL_CALL,
+        )
+
+        assert event.chunk == '{"location": "NYC"}'
+        assert event.tool_call is not None
+        assert event.tool_call.id == "call-456"
+        assert event.tool_call.function.name == "get_weather"
+        assert event.tool_call.function.arguments == '{"location": "NYC"}'
+        assert event.call_type == LLMCallType.TOOL_CALL
+
+    def test_llm_stream_chunk_event_text_only(self) -> None:
+        """Test that LLMStreamChunkEvent works for text-only chunks."""
+        from crewai.events.types.llm_events import (
+            LLMCallType,
+            LLMStreamChunkEvent,
+        )
+
+        event = LLMStreamChunkEvent(
+            chunk="Hello, world!",
+            tool_call=None,
+            call_type=LLMCallType.LLM_CALL,
+        )
+
+        assert event.chunk == "Hello, world!"
+        assert event.tool_call is None
+        assert event.call_type == LLMCallType.LLM_CALL
+
+
+class TestBaseLLMEmitStreamChunkEvent:
+    """Tests for BaseLLM._emit_stream_chunk_event method."""
+
+    def test_emit_stream_chunk_event_infers_tool_call_type(self) -> None:
+        """Test that _emit_stream_chunk_event infers TOOL_CALL type when tool_call is present."""
+        from unittest.mock import MagicMock, patch
+        from crewai.llms.base_llm import BaseLLM
+        from crewai.events.types.llm_events import LLMCallType, LLMStreamChunkEvent
+
+        # Create a mock BaseLLM instance
+        with patch.object(BaseLLM, "__abstractmethods__", set()):
+            llm = BaseLLM(model="test-model")  # type: ignore
+
+        captured_events: list[LLMStreamChunkEvent] = []
+
+        def capture_emit(source: Any, event: Any) -> None:
+            if isinstance(event, LLMStreamChunkEvent):
+                captured_events.append(event)
+
+        with patch("crewai.llms.base_llm.crewai_event_bus") as mock_bus:
+            mock_bus.emit = capture_emit
+
+            # Emit with tool_call - should infer TOOL_CALL type
+            tool_call_dict = {
+                "id": "call-789",
+                "function": {
+                    "name": "test_tool",
+                    "arguments": '{"arg": "value"}',
+                },
+                "type": "function",
+                "index": 0,
+            }
+            llm._emit_stream_chunk_event(
+                chunk='{"arg": "value"}',
+                tool_call=tool_call_dict,
+            )
+
+            assert len(captured_events) == 1
+            assert captured_events[0].call_type == LLMCallType.TOOL_CALL
+            assert captured_events[0].tool_call is not None
+
+    def test_emit_stream_chunk_event_infers_llm_call_type(self) -> None:
+        """Test that _emit_stream_chunk_event infers LLM_CALL type when tool_call is None."""
+        from unittest.mock import patch
+        from crewai.llms.base_llm import BaseLLM
+        from crewai.events.types.llm_events import LLMCallType, LLMStreamChunkEvent
+
+        # Create a mock BaseLLM instance
+        with patch.object(BaseLLM, "__abstractmethods__", set()):
+            llm = BaseLLM(model="test-model")  # type: ignore
+
+        captured_events: list[LLMStreamChunkEvent] = []
+
+        def capture_emit(source: Any, event: Any) -> None:
+            if isinstance(event, LLMStreamChunkEvent):
+                captured_events.append(event)
+
+        with patch("crewai.llms.base_llm.crewai_event_bus") as mock_bus:
+            mock_bus.emit = capture_emit
+
+            # Emit without tool_call - should infer LLM_CALL type
+            llm._emit_stream_chunk_event(
+                chunk="Hello, world!",
+                tool_call=None,
+            )
+
+            assert len(captured_events) == 1
+            assert captured_events[0].call_type == LLMCallType.LLM_CALL
+            assert captured_events[0].tool_call is None
+
+    def test_emit_stream_chunk_event_respects_explicit_call_type(self) -> None:
+        """Test that _emit_stream_chunk_event respects explicitly provided call_type."""
+        from unittest.mock import patch
+        from crewai.llms.base_llm import BaseLLM
+        from crewai.events.types.llm_events import LLMCallType, LLMStreamChunkEvent
+
+        # Create a mock BaseLLM instance
+        with patch.object(BaseLLM, "__abstractmethods__", set()):
+            llm = BaseLLM(model="test-model")  # type: ignore
+
+        captured_events: list[LLMStreamChunkEvent] = []
+
+        def capture_emit(source: Any, event: Any) -> None:
+            if isinstance(event, LLMStreamChunkEvent):
+                captured_events.append(event)
+
+        with patch("crewai.llms.base_llm.crewai_event_bus") as mock_bus:
+            mock_bus.emit = capture_emit
+
+            # Emit with explicit call_type - should use provided type
+            llm._emit_stream_chunk_event(
+                chunk="test",
+                tool_call=None,
+                call_type=LLMCallType.TOOL_CALL,  # Explicitly set even though no tool_call
+            )
+
+            assert len(captured_events) == 1
+            assert captured_events[0].call_type == LLMCallType.TOOL_CALL
+
+
+class TestStreamingToolCallExtraction:
+    """Tests for tool call extraction from streaming events."""
+
+    def test_extract_tool_call_info_from_event(self) -> None:
+        """Test that tool call info is correctly extracted from LLMStreamChunkEvent."""
+        from crewai.utilities.streaming import _extract_tool_call_info
+        from crewai.events.types.llm_events import (
+            LLMStreamChunkEvent,
+            ToolCall,
+            FunctionCall,
+        )
+        from crewai.types.streaming import StreamChunkType
+
+        # Create event with tool call
+        tool_call = ToolCall(
+            id="call-extract-test",
+            function=FunctionCall(
+                name="extract_test",
+                arguments='{"key": "value"}',
+            ),
+            type="function",
+            index=2,
+        )
+
+        event = LLMStreamChunkEvent(
+            chunk='{"key": "value"}',
+            tool_call=tool_call,
+        )
+
+        chunk_type, tool_call_chunk = _extract_tool_call_info(event)
+
+        assert chunk_type == StreamChunkType.TOOL_CALL
+        assert tool_call_chunk is not None
+        assert tool_call_chunk.tool_id == "call-extract-test"
+        assert tool_call_chunk.tool_name == "extract_test"
+        assert tool_call_chunk.arguments == '{"key": "value"}'
+        assert tool_call_chunk.index == 2
+
+    def test_extract_tool_call_info_returns_text_for_no_tool_call(self) -> None:
+        """Test that TEXT type is returned when no tool call is present."""
+        from crewai.utilities.streaming import _extract_tool_call_info
+        from crewai.events.types.llm_events import LLMStreamChunkEvent
+        from crewai.types.streaming import StreamChunkType
+
+        event = LLMStreamChunkEvent(
+            chunk="Just text content",
+            tool_call=None,
+        )
+
+        chunk_type, tool_call_chunk = _extract_tool_call_info(event)
+
+        assert chunk_type == StreamChunkType.TEXT
+        assert tool_call_chunk is None

uv.lock

@@ -1225,7 +1225,7 @@ dependencies = [
     { name = "crewai" },
     { name = "docker" },
     { name = "lancedb" },
-    { name = "pypdf" },
+    { name = "pymupdf" },
     { name = "python-docx" },
     { name = "pytube" },
     { name = "requests" },
@@ -1382,8 +1382,8 @@ requires-dist = [
     { name = "psycopg2-binary", marker = "extra == 'postgresql'", specifier = ">=2.9.10" },
     { name = "pygithub", marker = "extra == 'github'", specifier = "==1.59.1" },
     { name = "pymongo", marker = "extra == 'mongodb'", specifier = ">=4.13" },
+    { name = "pymupdf", specifier = ">=1.26.6" },
     { name = "pymysql", marker = "extra == 'mysql'", specifier = ">=1.1.1" },
-    { name = "pypdf", specifier = ">=5.9.0" },
     { name = "python-docx", specifier = ">=1.2.0" },
     { name = "python-docx", marker = "extra == 'rag'", specifier = ">=1.1.0" },
     { name = "pytube", specifier = ">=15.0.0" },
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