feat: add openai-agents tracing processor

examples/attachment.py

@@ -32,7 +32,7 @@ async def main():
                 "url": "https://api.github.com/repos/chainlit/chainlit",
                 "mime": "application/json",
                 "metadata": {"test": "test"},
-            }
+            },
         )
 
         print(attachment.to_dict())

examples/langchain_toolcall.py

@@ -1,15 +1,12 @@
-from literalai import LiteralClient
-
-from langchain_openai import ChatOpenAI  # type: ignore
+from dotenv import load_dotenv
+from langchain.agents import AgentExecutor, create_tool_calling_agent
+from langchain.agents.agent import BaseSingleActionAgent
 from langchain_community.tools.tavily_search import TavilySearchResults
-
-from langchain.agents import create_tool_calling_agent
-from langchain.agents import AgentExecutor
 from langchain_core.messages import AIMessage, HumanMessage
 from langchain_core.runnables.config import RunnableConfig
-from langchain.agents.agent import BaseSingleActionAgent
+from langchain_openai import ChatOpenAI  # type: ignore
 
-from dotenv import load_dotenv
+from literalai import LiteralClient
 
 # Add OPENAI_API_KEY and TAVILY_API_KEY for this example.
 load_dotenv()

examples/langchain_variable.py

@@ -1,8 +1,7 @@
+from dotenv import load_dotenv
 from langchain.chat_models import init_chat_model
-from literalai import LiteralClient
-
 
-from dotenv import load_dotenv
+from literalai import LiteralClient
 
 load_dotenv()
 

examples/llamaindex.py

@@ -1,6 +1,7 @@
-from literalai import LiteralClient
-from llama_index.core import Document, VectorStoreIndex
 from dotenv import load_dotenv
+from llama_index.core import Document, VectorStoreIndex
+
+from literalai import LiteralClient
 
 load_dotenv()
 
@@ -14,7 +15,7 @@
 questions = [
     "Tell me about LLMs",
     "How do you fine-tune a neural network ?",
-    "What is RAG ?"
+    "What is RAG ?",
 ]
 
 # No context, create a Thread (it will be named after the first user query)

examples/llamaindex_workflow.py

@@ -1,12 +1,8 @@
 import asyncio
-from llama_index.core.workflow import (
-    Event,
-    StartEvent,
-    StopEvent,
-    Workflow,
-    step,
-)
+
+from llama_index.core.workflow import Event, StartEvent, StopEvent, Workflow, step
 from llama_index.llms.openai import OpenAI
+
 from literalai.client import LiteralClient
 
 lai_client = LiteralClient()
@@ -16,7 +12,8 @@
 class JokeEvent(Event):
     joke: str
 
-class RewriteJoke(Event): 
+
+class RewriteJoke(Event):
     joke: str
 
 

examples/main.py

@@ -24,7 +24,7 @@ def get_completion(welcome_message, text):
             {
                 "role": "system",
                 "content": "Tell an inspiring quote to the user, mentioning their name. Be extremely supportive while "
-                           "keeping it short. Write one sentence per line.",
+                "keeping it short. Write one sentence per line.",
             },
             {
                 "role": "assistant",

examples/multimodal.py

@@ -1,12 +1,11 @@
 import base64
-import requests  # type: ignore
 import time
 
-from literalai import LiteralClient
-from openai import OpenAI
-
+import requests  # type: ignore
 from dotenv import load_dotenv
+from openai import OpenAI
 
+from literalai import LiteralClient
 
 load_dotenv()
 

examples/openai_agents.py

@@ -0,0 +1,27 @@
+import asyncio
+
+from agents import Agent, Runner, set_trace_processors, trace
+from dotenv import load_dotenv
+
+from literalai import LiteralClient
+
+load_dotenv()
+
+client = LiteralClient()
+
+
+async def main():
+    agent = Agent(name="Joke generator", instructions="Tell funny jokes.")
+
+    with trace("Joke workflow"):
+        first_result = await Runner.run(agent, "Tell me a joke")
+        second_result = await Runner.run(
+            agent, f"Rate this joke: {first_result.final_output}"
+        )
+        print(f"Joke: {first_result.final_output}")
+        print(f"Rating: {second_result.final_output}")
+
+
+if __name__ == "__main__":
+    set_trace_processors([client.openai_agents_tracing_processor()])
+    asyncio.run(main())

literalai/api/__init__.py

@@ -1,4 +1,4 @@
-from literalai.api.synchronous import LiteralAPI
 from literalai.api.asynchronous import AsyncLiteralAPI
+from literalai.api.synchronous import LiteralAPI
 
 __all__ = ["LiteralAPI", "AsyncLiteralAPI"]

literalai/api/helpers/attachment_helpers.py

@@ -1,9 +1,8 @@
 import mimetypes
 from typing import Dict, Optional, TypedDict, Union
 
-from literalai.observability.step import Attachment
-
 from literalai.api.helpers import gql
+from literalai.observability.step import Attachment
 
 
 def create_attachment_helper(

literalai/api/helpers/prompt_helpers.py

@@ -1,18 +1,16 @@
 import logging
-from typing import TYPE_CHECKING, Optional, TypedDict, Callable
+from typing import TYPE_CHECKING, Callable, Optional, TypedDict
 
+from literalai.cache.prompt_helpers import put_prompt
 from literalai.observability.generation import GenerationMessage
 from literalai.prompt_engineering.prompt import Prompt, ProviderSettings
 
-from literalai.cache.prompt_helpers import put_prompt
-
 if TYPE_CHECKING:
     from literalai.api import LiteralAPI
     from literalai.cache.shared_cache import SharedCache
 
 from literalai.api.helpers import gql
 
-
 logger = logging.getLogger(__name__)
 
 

literalai/api/helpers/score_helpers.py

@@ -1,11 +1,10 @@
 import math
 from typing import Any, Dict, List, Optional, TypedDict
 
-from literalai.observability.filter import scores_filters, scores_order_by
-from literalai.my_types import PaginatedResponse
-from literalai.observability.step import ScoreType, ScoreDict, Score
-
 from literalai.api.helpers import gql
+from literalai.my_types import PaginatedResponse
+from literalai.observability.filter import scores_filters, scores_order_by
+from literalai.observability.step import Score, ScoreDict, ScoreType
 
 
 def get_scores_helper(

literalai/api/helpers/step_helpers.py

@@ -1,11 +1,10 @@
 from typing import Any, Dict, List, Optional, Union
 
-from literalai.observability.filter import steps_filters, steps_order_by
+from literalai.api.helpers import gql
 from literalai.my_types import PaginatedResponse
+from literalai.observability.filter import steps_filters, steps_order_by
 from literalai.observability.step import Step, StepDict, StepType
 
-from literalai.api.helpers import gql
-
 
 def create_step_helper(
     thread_id: Optional[str] = None,

literalai/api/helpers/thread_helpers.py

@@ -1,12 +1,11 @@
 from typing import Any, Dict, List, Optional
 
-from literalai.observability.filter import threads_filters, threads_order_by
+from literalai.api.helpers import gql
 from literalai.my_types import PaginatedResponse
+from literalai.observability.filter import threads_filters, threads_order_by
 from literalai.observability.step import StepType
 from literalai.observability.thread import Thread
 
-from literalai.api.helpers import gql
-
 
 def get_threads_helper(
     first: Optional[int] = None,

literalai/api/helpers/user_helpers.py

@@ -1,9 +1,8 @@
 from typing import Any, Dict, Optional
 
-from literalai.observability.filter import users_filters
-from literalai.my_types import PaginatedResponse, User
-
 from literalai.api.helpers import gql
+from literalai.my_types import PaginatedResponse, User
+from literalai.observability.filter import users_filters
 
 
 def get_users_helper(

literalai/cache/prompt_helpers.py

@@ -1,5 +1,5 @@
-from literalai.prompt_engineering.prompt import Prompt
 from literalai.cache.shared_cache import SharedCache
+from literalai.prompt_engineering.prompt import Prompt
 
 
 def put_prompt(cache: SharedCache, prompt: Prompt):

literalai/callback/langchain_callback.py

@@ -193,6 +193,8 @@ def _build_llm_settings(
             )
             model_keys = ["azure_deployment", "deployment_name", "model", "model_name"]
             model = next((settings[k] for k in model_keys if k in settings), None)
+            if isinstance(model, str):
+                model = model.replace("models/", "")
             tools = None
             if "functions" in settings:
                 tools = [