Merge branch 'main' into timetravel-fixes

.github/workflows/test-notebooks.yml

@@ -1,9 +1,11 @@
 name: Test Notebooks
 on:
+  pull_request_target: # Allows manual triggering from PR UI
   push:
-    branches: [ main ]
-  pull_request:
-    branches: [ main ]
+    branches:
+      - main
+    paths-ignore:
+      - 'docs/**'
 jobs:
   test-notebooks:
     runs-on: ubuntu-latest

README.md

@@ -141,7 +141,7 @@ To use the handler, import and set
 import os
 from langchain.chat_models import ChatOpenAI
 from langchain.agents import initialize_agent, AgentType
-from agentops.langchain_callback_handler import LangchainCallbackHandler
+from agentops.partners.langchain_callback_handler import LangchainCallbackHandler
 
 AGENTOPS_API_KEY = os.environ['AGENTOPS_API_KEY']
 handler = LangchainCallbackHandler(api_key=AGENTOPS_API_KEY, tags=['Langchain Example'])

agentops/cli.py

@@ -35,7 +35,3 @@ def main():
             set_time_travel_active_state(True)
         if args.off:
             set_time_travel_active_state(False)
-
-
-if __name__ == "__main__":
-    main()

agentops/client.py

@@ -82,6 +82,9 @@ def configure(
         )
 
     def initialize(self) -> Union[Session, None]:
+        if self.is_initialized:
+            return
+
         self.unsuppress_logs()
 
         if self._config.api_key is None:
@@ -348,7 +351,7 @@ def handle_exception(exc_type, exc_value, exc_traceback):
             atexit.register(
                 lambda: cleanup(
                     end_state="Indeterminate",
-                    end_state_reason="Process exited without calling end_session()",
+                    end_state_reason="N/A (process exited without calling agentops.end_session(...))",
                 )
             )
             signal.signal(signal.SIGINT, signal_handler)

agentops/partners/langchain_callback_handler.py

@@ -46,9 +46,8 @@ def __init__(
         endpoint: Optional[str] = None,
         max_wait_time: Optional[int] = None,
         max_queue_size: Optional[int] = None,
-        tags: Optional[List[str]] = None,
+        default_tags: Optional[List[str]] = None,
     ):
-
         logging_level = os.getenv("AGENTOPS_LOGGING_LEVEL")
         log_levels = {
             "CRITICAL": logging.CRITICAL,
@@ -64,12 +63,19 @@ def __init__(
             "endpoint": endpoint,
             "max_wait_time": max_wait_time,
             "max_queue_size": max_queue_size,
-            "tags": tags,
+            "default_tags": default_tags,
         }
 
-        self.ao_client = AOClient(
-            **{k: v for k, v in client_params.items() if v is not None}, override=False
-        )
+        self.ao_client = AOClient()
+        if self.ao_client.session_count == 0:
+            self.ao_client.configure(
+                **{k: v for k, v in client_params.items() if v is not None},
+                instrument_llm_calls=False,
+            )
+
+        if not self.ao_client.is_initialized:
+            self.ao_client.initialize()
+
         self.agent_actions: Dict[UUID, List[ActionEvent]] = defaultdict(list)
         self.events = Events()
 
@@ -93,7 +99,6 @@ def on_llm_start(
             },  # TODO: params is inconsistent, in ToolEvent we put it in logs
             model=get_model_from_kwargs(kwargs),
             prompt=prompts[0],
-            # tags=tags # TODO
         )
 
     @debug_print_function_params
@@ -156,15 +161,18 @@ def on_chain_start(
         metadata: Optional[Dict[str, Any]] = None,
         **kwargs: Any,
     ) -> Any:
-        self.events.chain[str(run_id)] = ActionEvent(
-            params={
-                **serialized,
-                **inputs,
-                **({} if metadata is None else metadata),
-                **kwargs,
-            },
-            action_type="chain",
-        )
+        try:
+            self.events.chain[str(run_id)] = ActionEvent(
+                params={
+                    **serialized,
+                    **inputs,
+                    **({} if metadata is None else metadata),
+                    **kwargs,
+                },
+                action_type="chain",
+            )
+        except Exception as e:
+            logger.warning(e)
 
     @debug_print_function_params
     def on_chain_end(
@@ -240,6 +248,8 @@ def on_tool_end(
                 details=output,
             )
             self.ao_client.record(error_event)
+        else:
+            self.ao_client.record(tool_event)
 
     @debug_print_function_params
     def on_tool_error(
@@ -357,7 +367,13 @@ def on_retry(
 
     @property
     def session_id(self):
-        return self.ao_client.current_session_id
+        raise DeprecationWarning(
+            "session_id is deprecated in favor of current_session_ids"
+        )
+
+    @property
+    def current_session_ids(self):
+        return self.ao_client.current_session_ids
 
 
 class AsyncLangchainCallbackHandler(AsyncCallbackHandler):

agentops/session.py

@@ -268,7 +268,7 @@ def _flush_queue(self) -> None:
         if not self.is_running:
             return
         with self.lock:
-            queue_copy = copy.deepcopy(self.queue)  # Copy the current items
+            queue_copy = self.queue[:]  # Copy the current items
             self.queue = []
 
             if len(queue_copy) > 0:

agentops/time_travel.py

@@ -1,10 +1,9 @@
 import json
 import yaml
+import os
 from .http_client import HttpClient
 from .exceptions import ApiServerException
-import os
 from .helpers import singleton
-from os import environ
 
 
 @singleton
@@ -32,7 +31,7 @@ def __init__(self):
 
 def fetch_time_travel_id(ttd_id):
     try:
-        endpoint = environ.get("AGENTOPS_API_ENDPOINT", "https://api.agentops.ai")
+        endpoint = os.environ.get("AGENTOPS_API_ENDPOINT", "https://api.agentops.ai")
         ttd_res = HttpClient.get(f"{endpoint}/v2/ttd/{ttd_id}")
         if ttd_res.code != 200:
             raise Exception(f"Failed to fetch TTD with status code {ttd_res.code}")

docs/v0/logger.mdx

@@ -7,7 +7,7 @@ description: 'This document explains the use of the AgentOpsLogger
 
 ## AgentOps logger
 
-The AgentsOps logger is quick and simple way of integrating your existing 
+The AgentOps logger is quick and simple way of integrating your existing 
 agent codebase with AgentOps. It allows you to use your current logs as events 
 by extending the built-in Python logging system to emit events to AgentOps.
 

docs/v0/recording-events.mdx

@@ -35,7 +35,7 @@ From this point, simply call the .record() method in the AgentOps client:
 ao_client.record(Event("event_type1"))
 ```
 
-In AgentsOps, each session is associated with a number of "Events". Events have 
+In AgentOps, each session is associated with a number of "Events". Events have 
 must have an "event_type" which is any abitrary string of your choice. It might be something
 like "OpenAI Call". Events can also have other information such as the parameters of the operation,
 the returned data, alongside tags, etc.