With streamlit

Author: aabmass

instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/langgraph-chatbot-demo/docker-compose.yaml

@@ -11,9 +11,12 @@ services:
         ENV PATH="/app/.venv/bin:$PATH"
         COPY . /app
         ENTRYPOINT []
-        CMD ["opentelemetry-instrument", "python", "chatbot.py"]
+        # CMD ["opentelemetry-instrument", "python", "chatbot.py"]
+        CMD ["opentelemetry-instrument", "streamlit", "run", "--server.port=8501", "langchain_history.py"]
     volumes:
       - ${GOOGLE_APPLICATION_CREDENTIALS:-/dev/null}:${GOOGLE_APPLICATION_CREDENTIALS:-/dev/null}:ro
+    ports:
+      - 8501:8501
     environment:
       - OTEL_EXPORTER_OTLP_ENDPOINT=http://otelcol:4317
       - OTEL_SERVICE_NAME=langgraph-chatbot-demo

instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/langgraph-chatbot-demo/langchain_history.py

@@ -0,0 +1,82 @@
+"""Adapted from https://github.com/langchain-ai/streamlit-agent/blob/main/streamlit_agent/basic_memory.py"""
+
+from os import environ
+
+from opentelemetry import trace
+import streamlit as st
+from langchain_community.chat_message_histories import (
+    StreamlitChatMessageHistory,
+)
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.runnables.history import RunnableWithMessageHistory
+from langchain_google_vertexai import ChatVertexAI
+
+tracer = trace.get_tracer(__name__)
+
+st.set_page_config(page_title="StreamlitChatMessageHistory", page_icon="📖")
+st.title("📖 StreamlitChatMessageHistory")
+
+
+"""
+A basic example of using StreamlitChatMessageHistory to help LLMChain remember messages in a conversation.
+The messages are stored in Session State across re-runs automatically. You can view the contents of Session State
+in the expander below. View the
+[source code for this app](https://github.com/langchain-ai/streamlit-agent/blob/main/streamlit_agent/basic_memory.py).
+"""
+
+# Set up memory
+msgs = StreamlitChatMessageHistory(key="langchain_messages")
+if len(msgs.messages) == 0:
+    msgs.add_ai_message("How can I help you?")
+
+view_messages = st.expander("View the message contents in session state")
+
+# Set up the LangChain, passing in Message History
+
+prompt = ChatPromptTemplate.from_messages(
+    [
+        (
+            "system",
+            "You are an AI chatbot having a conversation with a human.",
+        ),
+        MessagesPlaceholder(variable_name="history"),
+        ("human", "{question}"),
+    ]
+)
+
+llm = ChatVertexAI(
+    model="gemini-1.5-flash",
+    project=environ.get("GOOGLE_CLOUD_PROJECT", None),
+)
+chain = prompt | llm
+chain_with_history = RunnableWithMessageHistory(
+    chain,
+    lambda session_id: msgs,
+    input_messages_key="question",
+    history_messages_key="history",
+)
+
+# Render current messages from StreamlitChatMessageHistory
+for msg in msgs.messages:
+    st.chat_message(msg.type).write(msg.content)
+
+# If user inputs a new prompt, generate and draw a new response
+if prompt := st.chat_input():
+    st.chat_message("human").write(prompt)
+    # Note: new messages are saved to history automatically by Langchain during run
+    config = {"configurable": {"session_id": "any"}}
+    with tracer.start_as_current_span("chain invoke"):
+        response = chain_with_history.invoke({"question": prompt}, config)
+    st.chat_message("ai").write(response.content)
+
+# Draw the messages at the end, so newly generated ones show up immediately
+with view_messages:
+    """
+    Message History initialized with:
+    ```python
+    msgs = StreamlitChatMessageHistory(key="langchain_messages")
+    ```
+
+    Contents of `st.session_state.langchain_messages`:
+    """
+    view_messages.json(st.session_state.langchain_messages)

instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/langgraph-chatbot-demo/pyproject.toml

@@ -5,18 +5,30 @@ description = "Add your description here"
 readme = "README.md"
 requires-python = ">=3.9"
 dependencies = [
+    "duckduckgo-search>=7.3.0",
+    "langchain-community>=0.3.16",
     "langchain-core>=0.3.31",
     "langchain-google-vertexai>=2.0.7",
     "langgraph>0.2.27",
     "opentelemetry-distro>=0.50b0",
+    "opentelemetry-exporter-gcp-logging",
+    "opentelemetry-exporter-gcp-trace>=1.8.0",
     "opentelemetry-exporter-otlp-proto-grpc>=1.29.0",
+    "opentelemetry-instrumentation-aiohttp-client>=0.50b0",
+    "opentelemetry-instrumentation-httpx>=0.50b0",
+    "opentelemetry-instrumentation-requests>=0.50b0",
+    "opentelemetry-instrumentation-urllib>=0.50b0",
+    "opentelemetry-instrumentation-urllib3>=0.50b0",
     "opentelemetry-instrumentation-vertexai",
+    "streamlit>=1.41.1",
 ]
 
 [tool.uv.sources]
 opentelemetry-instrumentation-vertexai = { git = "https://github.com/aabmass/opentelemetry-python-contrib.git", subdirectory = "instrumentation-genai/opentelemetry-instrumentation-vertexai", branch = "vertex-langgraph" }
+opentelemetry-exporter-gcp-logging = { git = "https://github.com/DylanRussell/opentelemetry-operations-python.git", subdirectory = "opentelemetry-exporter-gcp-logging", branch = "logging_exporter" }
 
 [dependency-groups]
 dev = [
+    "ipython>=8.18.1",
     "ruff>=0.9.2",
 ]

instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/langgraph-chatbot-demo/run_streamlit.py

@@ -0,0 +1,39 @@
+import os
+import subprocess
+
+import google.auth
+import google.auth.transport
+import google.auth.transport.requests
+
+creds, project_id = google.auth.default()
+creds.refresh(google.auth.transport.requests.Request())
+
+
+def setenv_default(k: str, v: str) -> None:
+    if k not in os.environ:
+        os.environ[k] = v
+
+
+setenv_default(
+    "OTEL_EXPORTER_OTLP_ENDPOINT", "https://telemetry.googleapis.com:443"
+)
+setenv_default("OTEL_SERVICE_NAME", "langgraph-chatbot-demo")
+setenv_default("OTEL_PYTHON_LOGGING_AUTO_INSTRUMENTATION_ENABLED", "true")
+setenv_default("OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT", "true")
+setenv_default("OTEL_LOGS_EXPORTER", "gcp_logging")
+setenv_default("OTEL_RESOURCE_ATTRIBUTES", f"gcp.project_id={project_id}")
+setenv_default(
+    "OTEL_EXPORTER_OTLP_HEADERS",
+    f"authorization=Bearer {creds.token},x-goog-user-project={project_id}",
+)
+
+print(os.environ)
+subprocess.run(
+    [
+        "opentelemetry-instrument",
+        "streamlit",
+        "run",
+        "langchain_history.py",
+    ],
+    check=True,
+)