separated llm tracker by model (#346)

* separated llm tracker by model * llm refactor progress * working for openai * groq provider * cohere provider * ollama provider * remove support for openai v0 * cohere support * test import fix * test import fix * groq test fix * ollama tests * litellm tests * dont import litellm * cohere fixes and tests * oai version <0.1 better deprecation warning * [FEATURE] Add Anthropic LLM support via `anthropic` Python SDK (#332) * fix typo * add anthropic support * add example file * fixed linting using black * add time travel support for anthropic * linting * fix kwargs key to get prompt * fix for extracting tokens from Message.usage * minor fix for output tokens * remove anthropic example python file * fix completions not show in session * some more fixes and cleanup * add Message object to pydantic models * fix typo * overhaul anthropic code * linting * add anthropic example notebook * linting * added readme examples * fix incorrect attribute access for the model content * add async example * refactor code * fix function name * linting * add provider tests --------- Co-authored-by: reibs <[email protected]> * added undo to canaries * added anthropic tests * undo instrumenting for litellm * cohere considerations --------- Co-authored-by: Pratyush Shukla <[email protected]> Co-authored-by: reibs <[email protected]>
AgentOps-AI · Aug 20, 2024 · caaacc3 · caaacc3
1 parent 06657e1
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diff --git a/README.md b/README.md
@@ -249,7 +249,113 @@ agentops.end_session('Success')
 </details>
 
 
-### LiteLLM
+### Anthropic ﹨
+
+Track agents built with the Anthropic Python SDK (>=0.32.0).
+
+- [AgentOps integration example](./examples/anthropic/anthropic_example.ipynb)
+- [Official Anthropic documentation](https://docs.anthropic.com/en/docs/welcome)
+
+<details>
+  <summary>Installation</summary>
+
+```bash
+pip install anthropic
+```
+
+```python python
+import anthropic
+import agentops
+
+# Beginning of program's code (i.e. main.py, __init__.py)
+agentops.init(<INSERT YOUR API KEY HERE>)
+
+client = anthropic.Anthropic(
+    # This is the default and can be omitted
+    api_key=os.environ.get("ANTHROPIC_API_KEY"),
+)
+
+message = client.messages.create(
+        max_tokens=1024,
+        messages=[
+            {
+                "role": "user",
+                "content": "Tell me a cool fact about AgentOps",
+            }
+        ],
+        model="claude-3-opus-20240229",
+    )
+print(message.content)
+
+agentops.end_session('Success')
+```
+
+Streaming
+```python python
+import anthropic
+import agentops
+
+# Beginning of program's code (i.e. main.py, __init__.py)
+agentops.init(<INSERT YOUR API KEY HERE>)
+
+client = anthropic.Anthropic(
+    # This is the default and can be omitted
+    api_key=os.environ.get("ANTHROPIC_API_KEY"),
+)
+
+stream = client.messages.create(
+    max_tokens=1024,
+    model="claude-3-opus-20240229",
+    messages=[
+        {
+            "role": "user",
+            "content": "Tell me something cool about streaming agents",
+        }
+    ],
+    stream=True,
+)
+
+response = ""
+for event in stream:
+    if event.type == "content_block_delta":
+        response += event.delta.text
+    elif event.type == "message_stop":
+        print("\n")
+        print(response)
+        print("\n")
+```
+
+Async
+
+```python python
+import asyncio
+from anthropic import AsyncAnthropic
+
+client = AsyncAnthropic(
+    # This is the default and can be omitted
+    api_key=os.environ.get("ANTHROPIC_API_KEY"),
+)
+
+
+async def main() -> None:
+    message = await client.messages.create(
+        max_tokens=1024,
+        messages=[
+            {
+                "role": "user",
+                "content": "Tell me something interesting about async agents",
+            }
+        ],
+        model="claude-3-opus-20240229",
+    )
+    print(message.content)
+
+
+await main()
+```
+</details>
+
+### LiteLLM 🚅
 
 AgentOps provides support for LiteLLM(>=1.3.1), allowing you to call 100+ LLMs using the same Input/Output Format. 
 

diff --git a/agentops/client.py b/agentops/client.py
@@ -19,15 +19,15 @@
 from termcolor import colored
 
 from .event import Event, ErrorEvent
-from .helpers import (
+from .singleton import (
     conditional_singleton,
 )
 from .session import Session, active_sessions
 from .host_env import get_host_env
 from .log_config import logger
 from .meta_client import MetaClient
 from .config import Configuration
-from .llm_tracker import LlmTracker
+from .llms import LlmTracker
 
 
 @conditional_singleton

diff --git a/agentops/event.py b/agentops/event.py
@@ -70,7 +70,7 @@ class LLMEvent(Event):
     thread_id(UUID, optional): The unique identifier of the contextual thread that a message pertains to.
     prompt(str, list, optional): The message or messages that were used to prompt the LLM. Preferably in ChatML format which is more fully supported by AgentOps.
     prompt_tokens(int, optional): The number of tokens in the prompt message.
-    completion(str, object, optional): The message or returned by the LLM. Preferably in ChatML format which is more fully supported by AgentOps.
+    completion(str, object, optional): The message or messages returned by the LLM. Preferably in ChatML format which is more fully supported by AgentOps.
     completion_tokens(int, optional): The number of tokens in the completion message.
     model(str, optional): LLM model e.g. "gpt-4", "gpt-3.5-turbo".
 

diff --git a/agentops/helpers.py b/agentops/helpers.py
@@ -1,7 +1,6 @@
 from pprint import pformat
 from functools import wraps
 from datetime import datetime, timezone
-import json
 import inspect
 from typing import Union
 import http.client
@@ -11,38 +10,6 @@
 from .log_config import logger
 from uuid import UUID
 from importlib.metadata import version
-import subprocess
-
-ao_instances = {}
-
-
-def singleton(class_):
-
-    def getinstance(*args, **kwargs):
-        if class_ not in ao_instances:
-            ao_instances[class_] = class_(*args, **kwargs)
-        return ao_instances[class_]
-
-    return getinstance
-
-
-def conditional_singleton(class_):
-
-    def getinstance(*args, **kwargs):
-        use_singleton = kwargs.pop("use_singleton", True)
-        if use_singleton:
-            if class_ not in ao_instances:
-                ao_instances[class_] = class_(*args, **kwargs)
-            return ao_instances[class_]
-        else:
-            return class_(*args, **kwargs)
-
-    return getinstance
-
-
-def clear_singletons():
-    global ao_instances
-    ao_instances = {}
 
 
 def get_ISO_time():