Merge branch 'main' into stabilization

.github/workflows/notebook-gen.yml

@@ -0,0 +1,36 @@
+name: Check Generated Files
+
+on: push
+
+jobs:
+  check-diff:
+    runs-on: ubuntu-latest
+    steps:
+
+    - name: Checkout repository
+      uses: actions/checkout@v2
+
+    - name: Setup Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.11'
+
+    - name: Install Dependencies
+      if: always()
+      run: |
+        python -m pip install --upgrade pip
+        # Install your project dependencies here if necessary
+
+    - name: Run generate script
+      if: always()
+      run: python docs/v1/examples/notebooks/generate.py
+
+    - name: Check for differences
+      if: always()
+      run: |
+        if [[ `git status --porcelain` ]]; then
+          echo "Notebooks have been changed without being regenerated. Please run `python docs/v1/examples/notebooks/generate.py`."
+          exit 1
+        else
+          echo "No changes were detected. Notebooks up to date 💅🏻"
+        fi

README.md

@@ -16,7 +16,7 @@
 <p align="center">
 <a href="https://twitter.com/agentopsai/">🐦 Twitter</a>
 <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
-<a href="https://discord.gg/JHPt4C7r">📢 Discord</a>
+<a href="https://discord.gg/FagdcwwXRR">📢 Discord</a>
 <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
 <a href="https://app.agentops.ai/?ref=gh">🖇️ AgentOps</a>
 <span>&nbsp;&nbsp;•&nbsp;&nbsp;</span>
@@ -307,4 +307,4 @@ Check out our growth in the community:
 |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/109994880?s=40&v=4" width="20" height="20" alt="">  &nbsp; [bhancockio](https://github.com/bhancockio) / [chatgpt4o-analysis](https://github.com/bhancockio/chatgpt4o-analysis) | 16 |
 
 
-_Generated using [github-dependents-info](https://github.com/nvuillam/github-dependents-info), by [Nicolas Vuillamy](https://github.com/nvuillam)_
+_Generated using [github-dependents-info](https://github.com/nvuillam/github-dependents-info), by [Nicolas Vuillamy](https://github.com/nvuillam)_

agentops/llm_tracker.py

@@ -32,6 +32,9 @@ class LlmTracker:
             "5.4.0": ("chat", "chat_stream"),
         },
         "ollama": {"0.0.1": ("chat", "Client.chat", "AsyncClient.chat")},
+        "groq": {
+            "0.9.0": ("Client.chat", "AsyncClient.chat"),
+        },
     }
 
     def __init__(self, client):
@@ -487,6 +490,128 @@ def generator():
         self._safe_record(session, self.llm_event)
         return response
 
+    def _handle_response_groq(
+        self, response, kwargs, init_timestamp, session: Optional[Session] = None
+    ):
+        """Handle responses for OpenAI versions >v1.0.0"""
+        from groq import AsyncStream, Stream
+        from groq.resources.chat import AsyncCompletions
+        from groq.types.chat import ChatCompletionChunk
+
+        self.llm_event = LLMEvent(init_timestamp=init_timestamp, params=kwargs)
+        if session is not None:
+            self.llm_event.session_id = session.session_id
+
+        def handle_stream_chunk(chunk: ChatCompletionChunk):
+            # NOTE: prompt/completion usage not returned in response when streaming
+            # We take the first ChatCompletionChunk and accumulate the deltas from all subsequent chunks to build one full chat completion
+            if self.llm_event.returns == None:
+                self.llm_event.returns = chunk
+
+            try:
+                accumulated_delta = self.llm_event.returns.choices[0].delta
+                self.llm_event.agent_id = check_call_stack_for_agent_id()
+                self.llm_event.model = chunk.model
+                self.llm_event.prompt = kwargs["messages"]
+
+                # NOTE: We assume for completion only choices[0] is relevant
+                choice = chunk.choices[0]
+
+                if choice.delta.content:
+                    accumulated_delta.content += choice.delta.content
+
+                if choice.delta.role:
+                    accumulated_delta.role = choice.delta.role
+
+                if choice.delta.tool_calls:
+                    accumulated_delta.tool_calls = choice.delta.tool_calls
+
+                if choice.delta.function_call:
+                    accumulated_delta.function_call = choice.delta.function_call
+
+                if choice.finish_reason:
+                    # Streaming is done. Record LLMEvent
+                    self.llm_event.returns.choices[0].finish_reason = (
+                        choice.finish_reason
+                    )
+                    self.llm_event.completion = {
+                        "role": accumulated_delta.role,
+                        "content": accumulated_delta.content,
+                        "function_call": accumulated_delta.function_call,
+                        "tool_calls": accumulated_delta.tool_calls,
+                    }
+                    self.llm_event.end_timestamp = get_ISO_time()
+
+                    self._safe_record(session, self.llm_event)
+            except Exception as e:
+                self._safe_record(
+                    session, ErrorEvent(trigger_event=self.llm_event, exception=e)
+                )
+
+                kwargs_str = pprint.pformat(kwargs)
+                chunk = pprint.pformat(chunk)
+                logger.warning(
+                    f"Unable to parse a chunk for LLM call. Skipping upload to AgentOps\n"
+                    f"chunk:\n {chunk}\n"
+                    f"kwargs:\n {kwargs_str}\n"
+                )
+
+        # if the response is a generator, decorate the generator
+        if isinstance(response, Stream):
+
+            def generator():
+                for chunk in response:
+                    handle_stream_chunk(chunk)
+                    yield chunk
+
+            return generator()
+
+        # For asynchronous AsyncStream
+        elif isinstance(response, AsyncStream):
+
+            async def async_generator():
+                async for chunk in response:
+                    handle_stream_chunk(chunk)
+                    yield chunk
+
+            return async_generator()
+
+        # For async AsyncCompletion
+        elif isinstance(response, AsyncCompletions):
+
+            async def async_generator():
+                async for chunk in response:
+                    handle_stream_chunk(chunk)
+                    yield chunk
+
+            return async_generator()
+
+        # v1.0.0+ responses are objects
+        try:
+            self.llm_event.returns = response.model_dump()
+            self.llm_event.agent_id = check_call_stack_for_agent_id()
+            self.llm_event.prompt = kwargs["messages"]
+            self.llm_event.prompt_tokens = response.usage.prompt_tokens
+            self.llm_event.completion = response.choices[0].message.model_dump()
+            self.llm_event.completion_tokens = response.usage.completion_tokens
+            self.llm_event.model = response.model
+
+            self._safe_record(session, self.llm_event)
+        except Exception as e:
+            self._safe_record(
+                session, ErrorEvent(trigger_event=self.llm_event, exception=e)
+            )
+
+            kwargs_str = pprint.pformat(kwargs)
+            response = pprint.pformat(response)
+            logger.warning(
+                f"Unable to parse response for LLM call. Skipping upload to AgentOps\n"
+                f"response:\n {response}\n"
+                f"kwargs:\n {kwargs_str}\n"
+            )
+
+        return response
+
     def override_openai_v1_completion(self):
         from openai.resources.chat import completions
 
@@ -645,6 +770,39 @@ async def patched_function(*args, **kwargs):
         # Override the original method with the patched one
         AsyncClient.chat = patched_function
 
+    def override_groq_chat(self):
+        from groq.resources.chat import completions
+
+        original_create = completions.Completions.create
+
+        def patched_function(*args, **kwargs):
+            # Call the original function with its original arguments
+            init_timestamp = get_ISO_time()
+            session = kwargs.get("session", None)
+            if "session" in kwargs.keys():
+                del kwargs["session"]
+            result = original_create(*args, **kwargs)
+            return self._handle_response_groq(
+                result, kwargs, init_timestamp, session=session
+            )
+
+        # Override the original method with the patched one
+        completions.Completions.create = patched_function
+
+    def override_groq_chat_stream(self):
+        from groq.resources.chat import completions
+
+        original_create = completions.AsyncCompletions.create
+
+        def patched_function(*args, **kwargs):
+            # Call the original function with its original arguments
+            init_timestamp = get_ISO_time()
+            result = original_create(*args, **kwargs)
+            return self._handle_response_groq(result, kwargs, init_timestamp)
+
+        # Override the original method with the patched one
+        completions.AsyncCompletions.create = patched_function
+
     def _override_method(self, api, method_path, module):
         def handle_response(result, kwargs, init_timestamp):
             if api == "openai":
@@ -746,6 +904,17 @@ def override_api(self):
                             f"Only Ollama>=0.0.1 supported. v{module_version} found."
                         )
 
+                if api == "groq":
+                    module_version = version(api)
+
+                    if Version(module_version) >= parse("0.9.0"):
+                        self.override_groq_chat()
+                        self.override_groq_chat_stream()
+                    else:
+                        logger.warning(
+                            f"Only Groq>=0.9.0 supported. v{module_version} found."
+                        )
+
     def stop_instrumenting(self):
         self.undo_override_openai_v1_async_completion()
         self.undo_override_openai_v1_completion()

agentops/session.py

@@ -193,7 +193,7 @@ def record(self, event: Union[Event, ErrorEvent]):
 
                 event.trigger_event_id = event.trigger_event.id
                 event.trigger_event_type = event.trigger_event.event_type
-                self.record(event)
+                self._add_event(event.trigger_event.__dict__)
                 event.trigger_event = None  # removes trigger_event from serialization
 
         self._add_event(event.__dict__)

docs/mint.json

@@ -61,7 +61,7 @@
       "group": "Getting Started",
       "pages": [
         "v1/quickstart",
-        "v1/examples"
+        "v1/examples/examples"
       ]
     },
     {
@@ -93,7 +93,8 @@
         "v1/integrations/autogen",
         "v1/integrations/langchain",
         "v1/integrations/cohere",
-        "v1/integrations/litellm"
+        "v1/integrations/litellm",
+        "v1/integrations/multion"
       ]
     },
     {

docs/v1/examples.mdx → docs/v1/examples/examples.mdx

@@ -7,7 +7,7 @@ mode: "wide"
 ## Explore our example code to see AgentOps in action!
 
 <CardGroup cols={2}>
-    <Card title="Simple Agent" icon="person-carry-box" iconType="solid" href="https://github.com/AgentOps-AI/agentops-py/blob/main/examples/openai-gpt.ipynb">
+    <Card title="Simple Agent" icon="microchip-ai" iconType="solid" href="https://github.com/AgentOps-AI/agentops-py/blob/main/examples/openai-gpt.ipynb">
         Jupyter Notebook with sample code that you can run! Start here!
     </Card>
     <Card title="Crew.ai Example" icon="ship" href="/v1/integrations/crewai">
@@ -16,15 +16,21 @@ mode: "wide"
     <Card title="AutoGen" icon="microsoft" href="/v1/integrations/autogen">
         AutoGen multi-agent conversible workflow with tool usage
     </Card>
-    <Card title="Multi-Agent Code Example" icon="people-arrows" iconType="duotone" href="https://github.com/AgentOps-AI/agentops-py/blob/main/examples/multi_agent_example.ipynb">
+    <Card title="Multi-Agent Code Example" icon="people-arrows" iconType="duotone" href="/v1/examples/multi_agent">
         Jupyter Notebook with a simple multi-agent design
     </Card>
-    <Card title="LangChain Example" icon="link" href="https://github.com/AgentOps-AI/agentops-py/blob/main/examples/langchain_examples.ipynb">
+    <Card title="LangChain Example" icon="crow" href="/v1/examples/langchain">
         Jupyter Notebook with a sample LangChain integration
     </Card>
-    <Card title="FastAPI Example" icon="computer" href="/v1/examples/fastapi">
+    <Card title="FastAPI Example" icon="bolt-lightning" href="/v1/examples/fastapi">
         Create a REST server that performs and observes agent tasks
     </Card>
+    <Card title="Multi Session Example" icon="computer" href="/v1/examples/multi_session">
+        Manage multiple sessions at the same time
+    </Card>
+    <Card title="MultiOn Example" icon="atom" href="/v1/examples/multion">
+        Create an autonomous browser agent capable of navigating the web and extracting information
+    </Card>
 </CardGroup>
 
 ## Video Guides

docs/v1/examples/fastapi.mdx

@@ -25,9 +25,6 @@ mode: "wide"
 			poetry add agentops
 			```
 		</CodeGroup>
-		<Check>
-			[Give us a star](https://github.com/AgentOps-AI/agentops) on GitHub while you're at it (you may be our 2,000th 😊)
-		</Check>
 	</Step>
 	<Step title="Install Crew from the AgentOps fork">
 		<Warning>

docs/v1/examples/langchain.mdx

@@ -0,0 +1,10 @@
+---
+title: 'Langchain Example'
+description: 'Using the Langchain Callback Handler'
+mode: "wide"
+---
+_View Notebook on <a href={'https://github.com/AgentOps-AI/agentops/blob/48ae12d4e4e085eed57346f1c40a054097431937/examples/langchain_examples.ipynb'} target={'_blank'}>Github</a>_
+
+<iframe id="iframe" src={'notebooks/langchain_examples.html'}></iframe>
+
+<script type="module" src="/scripts/full_iframe.js"></script>

docs/v1/examples/multi_agent.mdx

@@ -0,0 +1,10 @@
+---
+title: 'Multi-Agent Example'
+description: 'How to track events from multiple different agents'
+mode: "wide"
+---
+_View Notebook on <a href={'https://github.com/AgentOps-AI/agentops/blob/main/examples/multi_agent_example.ipynb'} target={'_blank'}>Github</a>_
+
+<iframe id="iframe" src={'notebooks/multi_agent_example.html'}></iframe>
+
+<script type="module" src="/scripts/full_iframe.js"></script>

docs/v1/examples/multi_session.mdx

@@ -0,0 +1,10 @@
+---
+title: 'Multi-Session Example'
+description: 'Handling multiple sessions at the same time'
+mode: "wide"
+---
+_View Notebook on <a href={'https://github.com/AgentOps-AI/agentops/blob/48ae12d4e4e085eed57346f1c40a054097431937/examples/multi_session_llm.ipynb'} target={'_blank'}>Github</a>_
+
+<iframe id="iframe" src={'notebooks/multi_session_llm.html'}></iframe>
+
+<script type="module" src="/scripts/full_iframe.js"></script>

docs/v1/examples/multion.mdx

@@ -0,0 +1,12 @@
+---
+title: 'Multion Examples'
+description: 'Tracking Multion usage with AgentOps'
+mode: "wide"
+---
+
+<iframe id="iframe" src={'notebooks/multion/Autonomous_web_browsing.html'}></iframe>
+<iframe id="iframe" src={'notebooks/multion/Sample_browsing_agent.html'}></iframe>
+<iframe id="iframe" src={'notebooks/multion/Step_by_step_web_browsing.html'}></iframe>
+<iframe id="iframe" src={'notebooks/multion/Webpage_data_retrieval.html'}></iframe>
+
+<script type="module" src="/scripts/full_iframe.js"></script>

docs/v1/examples/notebooks/README.md

@@ -0,0 +1,8 @@
+# Generate Notebooks in Docs
+
+1. `brew install pandoc`
+2. `python generate.py`
+
+This generates HTML versions of the notebooks.
+
+Make sure there is a corresponding