Adding new tool usage and parsing logic

src/crewai/utilities/__init__.py

@@ -1,4 +1,5 @@
 from .i18n import I18N
+from .instructor import Instructor
 from .logger import Logger
 from .printer import Printer
 from .prompts import Prompts

src/crewai/utilities/instructor.py

@@ -0,0 +1,51 @@
+from typing import Any, Optional, Type
+
+import instructor
+from pydantic import BaseModel, Field, PrivateAttr, model_validator
+
+
+class Instructor(BaseModel):
+    """Class that wraps an agent llm with instructor."""
+
+    _client: Any = PrivateAttr()
+    content: str = Field(description="Content to be sent to the instructor.")
+    agent: Optional[Any] = Field(
+        description="The agent that needs to use instructor.", default=None
+    )
+    llm: Optional[Any] = Field(
+        description="The agent that needs to use instructor.", default=None
+    )
+    instructions: Optional[str] = Field(
+        description="Instructions to be sent to the instructor.",
+        default=None,
+    )
+    model: Type[BaseModel] = Field(
+        description="Pydantic model to be used to create an output."
+    )
+
+    @model_validator(mode="after")
+    def set_instructor(self):
+        """Set instructor."""
+        if self.agent and not self.llm:
+            self.llm = self.agent.function_calling_llm or self.agent.llm
+
+        self._client = instructor.patch(
+            self.llm.client._client,
+            mode=instructor.Mode.TOOLS,
+        )
+        return self
+
+    def to_json(self):
+        model = self.to_pydantic()
+        return model.model_dump_json(indent=2)
+
+    def to_pydantic(self):
+        messages = [{"role": "user", "content": self.content}]
+        if self.instructions:
+            messages.append({"role": "system", "content": self.instructions})
+
+        model = self._client.chat.completions.create(
+            model=self.llm.model_name, response_model=self.model, messages=messages
+        )
+
+        return model

src/crewai/utilities/prompts.py

@@ -1,6 +1,6 @@
-from typing import ClassVar
+from typing import Any, ClassVar
 
-from langchain.prompts import PromptTemplate, BasePromptTemplate
+from langchain.prompts import BasePromptTemplate, PromptTemplate
 from pydantic import BaseModel, Field
 
 from crewai.utilities import I18N
@@ -10,12 +10,18 @@ class Prompts(BaseModel):
     """Manages and generates prompts for a generic agent with support for different languages."""
 
     i18n: I18N = Field(default=I18N())
-
+    tools: list[Any] = Field(default=[])
     SCRATCHPAD_SLICE: ClassVar[str] = "\n{agent_scratchpad}"
 
     def task_execution_with_memory(self) -> BasePromptTemplate:
         """Generate a prompt for task execution with memory components."""
-        return self._build_prompt(["role_playing", "tools", "memory", "task"])
+        slices = ["role_playing"]
+        if len(self.tools) > 0:
+            slices.append("tools")
+        else:
+            slices.append("no_tools")
+        slices.extend(["memory", "task"])
+        return self._build_prompt(slices)
 
     def task_execution_without_tools(self) -> BasePromptTemplate:
         """Generate a prompt for task execution without tools components."""
@@ -23,10 +29,17 @@ class Prompts(BaseModel):
 
     def task_execution(self) -> BasePromptTemplate:
         """Generate a standard prompt for task execution."""
-        return self._build_prompt(["role_playing", "tools", "task"])
+        slices = ["role_playing"]
+        if len(self.tools) > 0:
+            slices.append("tools")
+        else:
+            slices.append("no_tools")
+        slices.append("task")
+        return self._build_prompt(slices)
 
     def _build_prompt(self, components: list[str]) -> BasePromptTemplate:
         """Constructs a prompt string from specified components."""
         prompt_parts = [self.i18n.slice(component) for component in components]
         prompt_parts.append(self.SCRATCHPAD_SLICE)
-        return PromptTemplate.from_template("".join(prompt_parts))
+        prompt = PromptTemplate.from_template("".join(prompt_parts))
+        return prompt