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Fix make ty #29

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dd3d49f
Fix type checking errors flagged by ty
gabemontero Jul 10, 2026
03d46e7
update README to better deal with llamstack vs. app dependencies
gabemontero Jul 10, 2026
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6 changes: 6 additions & 0 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Comment on lines +74 to 77

@qodo-code-review qodo-code-review Bot Jul 10, 2026

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Remediation recommended

1. Readme dirties dependency files 🐞 Bug ⚙ Maintainability

README.md now instructs users to overwrite the tracked pyproject.toml in-place (twice) and run `uv
sync`, which can also update the tracked uv.lock and leave the repo in a dirty state. If those
changes are accidentally committed, the app container build can fail because it uses `uv sync
--frozen` and requires uv.lock to match pyproject.toml exactly.
Agent Prompt 
## Issue description
README instructions overwrite `pyproject.toml` in-place (switching between `pyproject.llama-stack.toml` and `pyproject.orig.toml`) and rerun `uv sync`. This commonly leaves modified tracked files (`pyproject.toml`, and potentially `uv.lock`) in the working tree, increasing the chance of accidental commits; those commits can break the container build because it relies on `uv sync --frozen`.

## Issue Context
- The app image build copies `pyproject.toml` + `uv.lock` and runs `uv sync --frozen`.
- The README now suggests swapping `pyproject.toml` for different dependency sets.

## Fix Focus Areas
- README.md[71-78]
- README.md[120-127]

ⓘ Copy this prompt and use it to remediate the issue with your preferred AI generation tools

```

Expand Down Expand Up @@ -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

@maysunfaisal maysunfaisal Jul 15, 2026

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SHould we delete the pyproject.toml from main? Because it is still present in the repo.

@gabemontero gabemontero Jul 16, 2026

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yeah I wasn't sure @maysunfaisal .... I suspect it is better to have one in place just in case, so that the compiling etc. of the python project is viable out of the box

I also considered creating a "run llama stack" sub directory, and just move that pyproject.toml there, and then change the directions to cd into that directory, do the other stuff, etc.

WDYT ... maybe I should pivot to the subdirectory ? Any other ideas on how to better manager this?

uv sync
source .venv/bin/activate
uv run streamlit run streamlit_app.py
```

Expand Down
38 changes: 38 additions & 0 deletions pyproject.orig.toml
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@@ -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"]
6 changes: 3 additions & 3 deletions src/ingest.py
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Expand Up @@ -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
Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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
)
Expand Down
14 changes: 7 additions & 7 deletions src/methods.py
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Expand Up @@ -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/",
Expand All @@ -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")

Expand Down Expand Up @@ -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
)
Expand Down Expand Up @@ -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,
Expand All @@ -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 "
Expand Down Expand Up @@ -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,
Expand All @@ -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 "
Expand Down
8 changes: 4 additions & 4 deletions src/workflow.py
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Expand Up @@ -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 ""

Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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")
Expand Down Expand Up @@ -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,
Expand Down
4 changes: 2 additions & 2 deletions streamlit_app.py
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Expand Up @@ -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
Expand All @@ -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,
Expand Down