doc updats

README.md

@@ -64,11 +64,7 @@ Initialize the AgentOps client and automatically get analytics on every LLM call
 import agentops
 
 # Beginning of program's code (i.e. main.py, __init__.py)
-agentops.init( < INSERT
-YOUR
-API
-KEY
-HERE >)
+agentops.init( < INSERT YOUR API KEY HERE >)
 
 ...
 

agentops/decorators.py

@@ -39,7 +39,7 @@ async def async_wrapper(*args, session: Optional[Session] = None, **kwargs):
                 if session is None:
                     if Client().is_multi_session:
                         raise ValueError(
-                            "If multiple sessions exists, `session` is a required parameter in the function decorated by @record_function"
+                            "If multiple sessions exists, `session` is a required parameter in the function decorated by @record_action"
                         )
                 func_args = inspect.signature(func).parameters
                 arg_names = list(func_args.keys())
@@ -100,7 +100,7 @@ def sync_wrapper(*args, session: Optional[Session] = None, **kwargs):
                 if session is None:
                     if Client().is_multi_session:
                         raise ValueError(
-                            "If multiple sessions exists, `session` is a required parameter in the function decorated by @record_function"
+                            "If multiple sessions exists, `session` is a required parameter in the function decorated by @record_action"
                         )
                 func_args = inspect.signature(func).parameters
                 arg_names = list(func_args.keys())

docs/v1/concepts/events.mdx

@@ -26,14 +26,14 @@ The `ActionEvent` is a generic event for recording events that do not fit into t
 | logs        | str  | None    | "Executed action successfully" | Logs generated during the action event              |
 | screenshot  | str  | None    | "/path/to/screenshot.png"      | Path to screenshot captured during the action event |
 
-An action event can be used the [same way as other events](/v1/usage/recording-events) but also with the `record_function`
-decorator.
+An action or tool event can be used the [same way as other events](/v1/usage/recording-events) but also with the `record_action` or `record_tool`
+decorators.
 
 <CodeGroup>
 ```python python
-from agentops import record_function
+from agentops import record_action
 
-@record_function()
+@record_action()
 def some_action(params):
     return "some response"
 ```

docs/v1/examples/notebooks/openai-gpt.html

@@ -307,10 +307,10 @@ <h1 id="events">Events</h1>
 </div>
 <div id="b45754a57148eed1" class="cell code" data-collapsed="false">
 <div class="sourceCode" id="cb7"><pre
-class="sourceCode python"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> agentops <span class="im">import</span> record_function</span>
+class="sourceCode python"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" aria-hidden="true" tabindex="-1"></a><span class="im">from</span> agentops <span class="im">import</span> record_action</span>
 <span id="cb7-2"><a href="#cb7-2" aria-hidden="true" tabindex="-1"></a></span>
 <span id="cb7-3"><a href="#cb7-3" aria-hidden="true" tabindex="-1"></a></span>
-<span id="cb7-4"><a href="#cb7-4" aria-hidden="true" tabindex="-1"></a><span class="at">@record_function</span>(<span class="st">&quot;add numbers&quot;</span>)</span>
+<span id="cb7-4"><a href="#cb7-4" aria-hidden="true" tabindex="-1"></a><span class="at">@record_action</span>(<span class="st">&quot;add numbers&quot;</span>)</span>
 <span id="cb7-5"><a href="#cb7-5" aria-hidden="true" tabindex="-1"></a><span class="kw">def</span> add(x, y):</span>
 <span id="cb7-6"><a href="#cb7-6" aria-hidden="true" tabindex="-1"></a>    <span class="cf">return</span> x <span class="op">+</span> y</span>
 <span id="cb7-7"><a href="#cb7-7" aria-hidden="true" tabindex="-1"></a></span>

docs/v1/quickstart.mdx

@@ -47,12 +47,12 @@ import EnvTooltip from '/snippets/add-env-tooltip.mdx'
 <CardGroup cols={1}>
 
 <Card icon="code" title="Decorate Functions">
-  You can instrument other functions inside your code with the handy `@record_function`
+  You can instrument other functions inside your code with the handy `@record_action`
   decorator, which will record an `action_type`, the parameters, and the returns. You
   will see these function calls alongside your LLM calls from instantiating the AgentOps client.
   ```python python
   # (record specific functions)
-  @agentops.record_function('sample function being record')
+  @agentops.record_action('sample function being record')
   def sample_function(...):
     ...
 ```
@@ -94,7 +94,7 @@ import agentops
 agentops.init(<INSERT YOUR API KEY HERE>)
 
 # (record specific functions)
-@agentops.record_function('sample function being record')
+@agentops.record_action('sample function being record')
 def sample_function(...):
   ...
 

docs/v1/usage/recording-events.mdx

@@ -6,12 +6,12 @@ description: "Log events such as agent actions, LLM calls, tool calls, and error
 To get the most out of AgentOps, it is best to carefully consider what events to record -
 not simply record whatever your agent is logging. AgentOps offers two ways to record events:
 
-## `@record_function` Decorator
+## `@record_action` Decorator
 
 - **`event_type`** (str): Type of the event.
 
-To make AgentOps easier to integrate, we also provide a function decorator to automatically creates
-and records an event for your function.
+To make AgentOps easier to integrate, we also provide a function decorator to automatically create
+and record an event for your function.
 
 ```python python
 from agentops import record_action
@@ -23,6 +23,23 @@ def sample_function(...):
 
 The decorator will record the function's parameters, returns, and the time duration. We suggest using this on functions that take a long time and contain nested functions. For example, if you decorate a function that makes several openai calls, then each openai call will show in the replay graph as a child of the decorated function.
 
+## `@record_tool` Decorator
+
+- **`tool_name`** (str): The name of the tool represented by the python function
+
+Additionally, we provide a function decorator to automatically create tool events for python functions.
+
+```python python
+from agentops import record_tool
+
+@record_tool('SampleToolName')
+def sample_tool(...):
+    ...
+```
+
+The decorator will record the function's parameters, returns, and the time duration. We suggest using this on functions that take a long time and contain nested functions. For example, if you decorate a function that makes several openai calls, then each openai call will show in the replay graph as a child of the decorated function.
+
+
 ## `record()` Method
 
 From this point, simply call the .record() method in the AgentOps client:

examples/openai-gpt.ipynb

@@ -182,10 +182,10 @@
    },
    "outputs": [],
    "source": [
-    "from agentops import record_function\n",
+    "from agentops import record_action\n",
     "\n",
     "\n",
-    "@record_function(\"add numbers\")\n",
+    "@record_action(\"add numbers\")\n",
     "def add(x, y):\n",
     "    return x + y\n",
     "\n",

examples/recording-events.ipynb

@@ -66,10 +66,10 @@
    },
    "outputs": [],
    "source": [
-    "from agentops import record_function\n",
+    "from agentops import record_action\n",
     "\n",
     "\n",
-    "@record_function(\"add numbers\")\n",
+    "@record_action(\"add numbers\")\n",
     "def add(x, y):\n",
     "    return x + y\n",
     "\n",