Restructure to a packaged app

Author: aabmass

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

@@ -28,7 +28,8 @@ opentelemetry-instrumentation-vertexai = { git = "https://github.com/aabmass/ope
 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",
-]
+dev = ["ipython>=8.18.1", "ruff>=0.9.2"]
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"

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

@@ -1,4 +1,15 @@
+# /// script
+# requires-python = ">=3.13"
+# dependencies = [
+#     "langgraph-chatbot-demo",
+# ]
+#
+# [tool.uv.sources]
+# langgraph-chatbot-demo = { path = "." }
+# ///
+
 import os
+import importlib.util
 import subprocess
 
 import google.auth
@@ -27,13 +38,18 @@ def setenv_default(k: str, v: str) -> None:
     f"authorization=Bearer {creds.token},x-goog-user-project={project_id}",
 )
 
-print(os.environ)
+langchain_app_spec = importlib.util.find_spec(
+    "langgraph_chatbot_demo.langchain_history"
+)
+if not (langchain_app_spec and langchain_app_spec.origin):
+    raise Exception("Could not find langchain_history.py")
+
 subprocess.run(
     [
         "opentelemetry-instrument",
         "streamlit",
         "run",
-        "langchain_history.py",
+        langchain_app_spec.origin,
     ],
     check=True,
 )

instrumentation-genai/opentelemetry-instrumentation-vertexai/examples/langgraph-chatbot-demo/src/langgraph_chatbot_demo/__init__.py

@@ -0,0 +1,56 @@
+"""Adapated from https://github.com/streamlit/llm-examples/blob/main/pages/2_Chat_with_search.py"""
+
+from os import environ
+
+import streamlit as st
+from langchain.agents import AgentType, initialize_agent
+from langchain.callbacks import StreamlitCallbackHandler
+from langchain_community.tools import DuckDuckGoSearchRun
+from langchain_google_vertexai import ChatVertexAI
+
+st.title("🔎 LangChain - Chat with search")
+
+"""
+In this example, we're using `StreamlitCallbackHandler` to display the thoughts and actions of an agent in an interactive Streamlit app.
+Try more LangChain 🤝 Streamlit Agent examples at [github.com/langchain-ai/streamlit-agent](https://github.com/langchain-ai/streamlit-agent).
+"""
+
+if "messages" not in st.session_state:
+    st.session_state["messages"] = [
+        {
+            "role": "assistant",
+            "content": "Hi, I'm a chatbot who can search the web. How can I help you?",
+        }
+    ]
+
+for msg in st.session_state.messages:
+    st.chat_message(msg["role"]).write(msg["content"])
+
+if prompt := st.chat_input(
+    placeholder="Who won the Women's U.S. Open in 2018?"
+):
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    st.chat_message("user").write(prompt)
+
+    llm = ChatVertexAI(
+        model="gemini-1.5-flash",
+        project=environ.get("GOOGLE_CLOUD_PROJECT", None),
+    )
+    search = DuckDuckGoSearchRun(name="Search")
+    search_agent = initialize_agent(
+        [search],
+        llm,
+        agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
+        handle_parsing_errors=True,
+    )
+    with st.chat_message("assistant"):
+        st_cb = StreamlitCallbackHandler(
+            st.container(), expand_new_thoughts=False
+        )
+        response = search_agent.run(
+            st.session_state.messages, callbacks=[st_cb]
+        )
+        st.session_state.messages.append(
+            {"role": "assistant", "content": response}
+        )
+        st.write(response)