docs: add entity mapping example for OpenTelemetry concepts

docs/dev/OTEL/entity_mapping.md

@@ -0,0 +1,74 @@
+An example of how AgentOps components could map to OpenTelemetry concepts:
+
+1. **Core Mapping**
+```mermaid
+graph LR
+    subgraph AgentOps
+        A[Session] --> B[Events]
+        B --> C[LLMEvent]
+        B --> D[ActionEvent]
+        B --> E[ToolEvent]
+    end
+
+    subgraph OpenTelemetry
+        F[Trace] --> G[Spans]
+        G --> H[LLM Spans]
+        G --> I[Action Spans]
+        G --> J[Tool Spans]
+        K[Metrics] --> L[LLM Metrics]
+    end
+
+    A -.->|Maps to| F
+    C -.->|Maps to| H
+    D -.->|Maps to| I
+    E -.->|Maps to| J
+```
+
+Let's look at specific examples:
+
+1. **Session to Trace**
+````python
+# When AgentOps starts a session:
+class Session:
+    def __init__(self):
+        # Create root span for the session
+        self.trace = tracer.start_span(
+            name="agentops.session",
+            attributes={
+                "session.id": self.session_id,
+                "agent.id": self.agent_id
+            }
+        )
+````
+
+2. **LLMEvent to Span**
+````python
+# When AgentOps records an LLM event:
+class LLMEvent:
+    def to_span(self):
+        return tracer.start_span(
+            name="llm.completion",
+            attributes={
+                "llm.model": self.model,
+                "llm.tokens.prompt": self.prompt_tokens,
+                "llm.tokens.completion": self.completion_tokens,
+                "llm.cost": self.cost
+            }
+        )
+````
+
+3. **LLM Metrics**
+````python
+# In LlmTracker:
+class LlmTracker:
+    def __init__(self):
+        self.calls_counter = meter.create_counter(
+            name="llm.calls",
+            description="Number of LLM API calls"
+        )
+
+        self.token_histogram = meter.create_histogram(
+            name="llm.tokens",
+            description="Distribution of token usage"
+        )
+````