diff --git a/README.md b/README.md
index 419addb..a1eb063 100644
--- a/README.md
+++ b/README.md
@@ -71,6 +71,9 @@ source .venv/bin/activate
 We have provided a custom run.yaml file to specify the required providers. Use the following command to run the Llama Stack with the custom configuration file.
 
 ```
+cp pyproject.llama-stack.toml pyproject.toml
+uv sync
+source .venv/bin/activate
 uv run llama stack run run.yaml
 ```
 
@@ -117,6 +120,9 @@ uv run llama-stack-client configure --endpoint http://localhost:8321 --api-key n
 ## Run the application Code
 
 ```bash
+cp pyproject.orig.toml pyproject.toml
+uv sync
+source .venv/bin/activate
 uv run streamlit run streamlit_app.py
 ```
 
diff --git a/pyproject.orig.toml b/pyproject.orig.toml
new file mode 100644
index 0000000..556bdb1
--- /dev/null
+++ b/pyproject.orig.toml
@@ -0,0 +1,38 @@
+[project]
+name = "llama-stack-agentic-sample"
+version = "0.1.0"
+description = "Llama-Stack LangGraph Customer Service Example"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "docling>=2.63.0",
+    "llama-stack-client>=0.3.1",
+    "llama-stack>=0.3.1",
+    "pygithub>=2.8.1",
+    "pyyaml>=6.0.3",
+    "langgraph>=1.0.4",
+    "ollama>=0.6.1",
+    "mcp>=1.23.1",
+    "chardet>=5.2.0",
+    "streamlit>=1.52.1",
+    "grandalf>=0.8",
+]
+
+[tool.setuptools.packages.find]
+where = ["src"]
+
+[dependency-groups]
+dev = ["ruff>=0.8.0", "pytest>=7.4.0", "pre-commit>=3.5.0"]
+
+[tool.ruff]
+line-length = 88
+target-version = "py312"
+exclude = ["tests", "*.pyi"]
+include = ["src/**/*.py", "streamlit_app.py"]
+
+[tool.ruff.lint]
+select = ["E", "F", "I"]
+ignore = []
+
+[tool.ruff.lint.isort]
+known-first-party = ["src"]
diff --git a/src/ingest.py b/src/ingest.py
index 0d56278..32c8aba 100644
--- a/src/ingest.py
+++ b/src/ingest.py
@@ -5,7 +5,7 @@
 import tempfile
 import time
 from pathlib import Path
-from typing import Any
+from typing import Any, cast
 
 import requests
 import yaml
@@ -293,7 +293,7 @@ def _fetch_github_dir_contents(
                             if isinstance(c, ContentFile):
                                 contents_list.append(c)
                             elif hasattr(c, "type") and hasattr(c, "name"):
-                                contents_list.append(c)  # type: ignore[arg-type]
+                                contents_list.append(cast(ContentFile, c))
                         pdf_files.extend(
                             self._fetch_github_dir_contents(
                                 repo, contents_list, branch, path, download_dir
@@ -384,7 +384,7 @@ def fetch_from_github(
                     if isinstance(c, ContentFile):
                         contents_list.append(c)
                     elif hasattr(c, "type") and hasattr(c, "name"):
-                        contents_list.append(c)  # type: ignore[arg-type]
+                        contents_list.append(cast(ContentFile, c))
                 pdf_files = self._fetch_github_dir_contents(
                     repo, contents_list, branch, path, download_dir
                 )
diff --git a/src/methods.py b/src/methods.py
index 36186a7..fa91eeb 100644
--- a/src/methods.py
+++ b/src/methods.py
@@ -300,7 +300,7 @@ def git_agent(
     if not tools_llm:
         raise AgentRunMethodParameterError("tools_llm is required in git agent")
 
-    openai_mcp_tool: "dict[str, Any]" = {
+    openai_mcp_tool: "Any" = {
         "type": "mcp",
         "server_label": "github",
         "server_url": "https://api.githubcopilot.com/mcp/",
@@ -319,7 +319,7 @@ def git_agent(
                 sub_id=state["submission_id"],
                 user_question=state["input"],
             ),
-            tools=[openai_mcp_tool],  # type: ignore[arg-type]
+            tools=[openai_mcp_tool],
         )
         logger.debug("git_agent response returned")
 
@@ -371,7 +371,7 @@ def git_agent(
                         issue_id=gh_issue,
                         comment_body=body_as_string,
                     ),
-                    tools=[openai_mcp_tool],  # type: ignore[arg-type]
+                    tools=[openai_mcp_tool],
                     timeout=240.0,  # the bigger comment calls can take
                     # especially long ... put a cap on it
                 )
@@ -440,7 +440,7 @@ def pod_agent(
     if not tools_llm:
         raise AgentRunMethodParameterError("tools_llm is required in git agent")
 
-    openai_mcp_tool: "dict[str, Any]" = {
+    openai_mcp_tool: "Any" = {
         "type": "mcp",
         "server_label": "OpenShift / Kubernetes MCP Tools",
         "server_url": MCP_SERVER_URL,
@@ -455,7 +455,7 @@ def pod_agent(
         resp = openai_client.responses.create(
             model=tools_llm,
             input=WorkflowAgentPrompts.POD_PROMPT.format(namespace=state["namespace"]),
-            tools=[openai_mcp_tool],  # type: ignore[arg-type]
+            tools=[openai_mcp_tool],
         )
         logger.debug(
             f"K8S Agent successful return MCP request "
@@ -518,7 +518,7 @@ def perf_agent(
     if not tools_llm:
         raise AgentRunMethodParameterError("tools_llm is required in git agent")
 
-    openai_mcp_tool: "dict[str, Any]" = {
+    openai_mcp_tool: "Any" = {
         "type": "mcp",
         "server_label": "OpenShift / Kubernetes MCP Tools",
         "server_url": MCP_SERVER_URL,
@@ -534,7 +534,7 @@ def perf_agent(
         resp = openai_client.responses.create(
             model=tools_llm,
             input=WorkflowAgentPrompts.PERF_PROMPT.format(namespace=state["namespace"]),
-            tools=[openai_mcp_tool],  # type: ignore[arg-type]
+            tools=[openai_mcp_tool],
         )
         logger.debug(
             f"K8S perf Agent successful return MCP request "
diff --git a/src/workflow.py b/src/workflow.py
index 27df3c1..e028bab 100644
--- a/src/workflow.py
+++ b/src/workflow.py
@@ -72,7 +72,7 @@ def _call_openai_llm(self, state: "WorkflowState") -> "str":
         messages = self._convert_messages_to_openai_format(state)
         completion = self.rag_service.openai_client.chat.completions.create(
             model=INFERENCE_MODEL,
-            messages=messages,  # type: ignore[invalid-argument-type]
+            messages=cast("Any", messages),
         )
         return completion.choices[0].message.content or ""
 
@@ -206,7 +206,7 @@ def llm_node(state: "WorkflowState") -> "WorkflowState":
                     rag_response = client_to_use.responses.create(
                         model=INFERENCE_MODEL,
                         input=rag_prompt,
-                        tools=[file_search_tool],  # type: ignore[invalid-argument-type]
+                        tools=cast("Any", [file_search_tool]),
                     )
                     rag_end_time = time.time()
                     state["rag_query_time"] = rag_end_time - rag_start_time
@@ -290,7 +290,7 @@ def llm_node(state: "WorkflowState") -> "WorkflowState":
 
             return state
 
-        agent_builder = StateGraph(WorkflowState)  # type: ignore[arg-type]
+        agent_builder = StateGraph(cast("Any", WorkflowState))
         agent_builder.add_node(f"{department_name}_set_message", init_message)
         agent_builder.add_node("llm_node", llm_node)
         agent_builder.add_edge(START, f"{department_name}_set_message")
@@ -450,7 +450,7 @@ def perf_agent_node(state: "WorkflowState") -> "WorkflowState":
                 tools_llm=tools_llm,
             )
 
-        overall_workflow = StateGraph(WorkflowState)  # type: ignore[arg-type]
+        overall_workflow = StateGraph(cast("Any", WorkflowState))
         overall_workflow.add_node(
             "classification_agent",
             classification_node,
diff --git a/streamlit_app.py b/streamlit_app.py
index f441169..97e34a8 100644
--- a/streamlit_app.py
+++ b/streamlit_app.py
@@ -586,7 +586,7 @@ def _run_async_in_thread(coro):
 
 
 async def run_workflow_task_async(
-    workflow: "Workflow", question: "str", submission_id: "str"
+    workflow: "Any", question: "str", submission_id: "str"
 ) -> "None":
     """
     async task to run a single workflow with concurrent operations
@@ -599,7 +599,7 @@ async def run_workflow_task_async(
         # the question through appropriate agents (classification -> dept agents)
         # Note: workflow.invoke is synchronous but we're in an async context
         # to allow future async operations within the workflow
-        result = workflow.invoke(  # type: ignore[attr-defined]
+        result = workflow.invoke(
             {
                 "input": question,
                 "submission_id": submission_id,