feat: add prompt observability code (#2027)

* feat: add prompt observability code

* feat: improve logic for llm call

* feat: add tests for traces

* feat: remove unused improt

* feat: add function to clear and add task traces

* feat: fix import

* feat:  chagne time

* feat: fix type checking issues

* feat: add fixed time to fix test

* feat: fix datetime test issue

* feat: add add task traces function

* feat: add same logic as entp

* feat: add start_time as reference for duplication of tool call

* feat: add max_depth

* feat: add protocols file to properly import on LLM

---------

Co-authored-by: Brandon Hancock (bhancock_ai) <109994880+bhancockio@users.noreply.github.com>

src/crewai/traces/models.py

@@ -0,0 +1,89 @@
+from datetime import datetime
+from typing import Any, Dict, List, Optional
+
+from pydantic import BaseModel, Field
+
+
+class ToolCall(BaseModel):
+    """Model representing a tool call during execution"""
+
+    name: str
+    arguments: Dict[str, Any]
+    output: str
+    start_time: datetime
+    end_time: Optional[datetime] = None
+    latency_ms: Optional[int] = None
+    error: Optional[str] = None
+
+
+class LLMRequest(BaseModel):
+    """Model representing the LLM request details"""
+
+    model: str
+    messages: List[Dict[str, str]]
+    temperature: Optional[float] = None
+    max_tokens: Optional[int] = None
+    stop_sequences: Optional[List[str]] = None
+    additional_params: Dict[str, Any] = Field(default_factory=dict)
+
+
+class LLMResponse(BaseModel):
+    """Model representing the LLM response details"""
+
+    content: str
+    finish_reason: Optional[str] = None
+
+
+class FlowStepIO(BaseModel):
+    """Model representing flow step input/output details"""
+
+    function_name: str
+    inputs: Dict[str, Any] = Field(default_factory=dict)
+    outputs: Any
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+
+
+class CrewTrace(BaseModel):
+    """Model for tracking detailed information about LLM interactions and Flow steps"""
+
+    deployment_instance_id: Optional[str] = Field(
+        description="ID of the deployment instance"
+    )
+    trace_id: str = Field(description="Unique identifier for this trace")
+    run_id: str = Field(description="Identifier for the execution run")
+    agent_role: Optional[str] = Field(description="Role of the agent")
+    task_id: Optional[str] = Field(description="ID of the current task being executed")
+    task_name: Optional[str] = Field(description="Name of the current task")
+    task_description: Optional[str] = Field(
+        description="Description of the current task"
+    )
+    trace_type: str = Field(description="Type of the trace")
+    crew_type: str = Field(description="Type of the crew")
+    run_type: str = Field(description="Type of the run")
+
+    # Timing information
+    start_time: Optional[datetime] = None
+    end_time: Optional[datetime] = None
+    latency_ms: Optional[int] = None
+
+    # Request/Response for LLM calls
+    request: Optional[LLMRequest] = None
+    response: Optional[LLMResponse] = None
+
+    # Input/Output for Flow steps
+    flow_step: Optional[FlowStepIO] = None
+
+    # Tool usage
+    tool_calls: List[ToolCall] = Field(default_factory=list)
+
+    # Metrics
+    tokens_used: Optional[int] = None
+    prompt_tokens: Optional[int] = None
+    completion_tokens: Optional[int] = None
+    cost: Optional[float] = None
+
+    # Additional metadata
+    status: str = "running"  # running, completed, error
+    error: Optional[str] = None
+    metadata: Dict[str, Any] = Field(default_factory=dict)
+    tags: List[str] = Field(default_factory=list)