add CLI file input support for FILE_ANALYZER tool when running locally by madina1203 · Pull Request #172 · HolobiomicsLab/MetaboT

madina1203 · 2026-04-24T16:25:22Z

PR Type

enhancement, tests

Description

Added CLI file input support for FILE_ANALYZER tool
Introduced error handling for session file preparation
Implemented unit tests for session file preparation
Updated CLI documentation with usage examples

Diagram Walkthrough

flowchart LR
  A["main.py"] -- "Add CLI file input" --> B["_prepare_session_files"]
  B -- "Error handling" --> C["SessionFilePreparationError"]
  A -- "Add tests" --> D["test_main.py"]

File Walkthrough

Relevant files

Enhancement

main.py `Add CLI file input and error handling` app/core/main.py Added CLI support for file input Introduced `SessionFilePreparationError` for error handling Enhanced `_prepare_session_files` for file staging Updated CLI documentation with usage examples	+144/-25

Tests

test_main.py `Implement tests for session file preparation` app/core/tests/test_main.py Added tests for session file preparation Tested valid and invalid file scenarios Verified CLI API key handling Checked logger reconfiguration	+172/-0

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coderabbitai · 2026-04-24T16:25:30Z

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qodo-code-review · 2026-04-24T16:25:36Z

Review Summary by Qodo

(Agentic_describe updated until commit `1515fec`)

Add CLI file input support with session file staging and error handling

✨ Enhancement 🧪 Tests

Walkthroughs

Description

• Add CLI file input support via -f/--file argument for FILE_ANALYZER tool
• Introduce SessionFilePreparationError exception for robust file staging error handling
• Implement _prepare_session_files() function to safely copy user files into session directory
• Add comprehensive unit tests covering valid file copying and error scenarios
• Integrate session management and logger reconfiguration into CLI workflow

Diagram

flowchart LR
  CLI["CLI Arguments<br/>-f/--file"]
  PREP["_prepare_session_files()"]
  COPY["Copy files to<br/>session input dir"]
  ERROR["SessionFilePreparationError<br/>handling"]
  WORKFLOW["create_workflow()"]
  
  CLI -- "file paths" --> PREP
  PREP -- "validate & stage" --> COPY
  PREP -- "error cases" --> ERROR
  COPY -- "input_dir" --> WORKFLOW
  ERROR -- "user feedback" --> CLI

File Changes

1. app/core/main.py ✨ Enhancement +144/-25

CLI file input support and session file staging

• Add imports for shutil, configparser, Path, and session management functions
• Introduce SessionFilePreparationError custom exception class for file staging errors
• Implement _prepare_session_files() function with comprehensive validation: file existence, type
 checking, collision detection, and safe copying using shutil.copy2()
• Enhance main() function with new -f/--file CLI argument supporting multiple file paths
• Integrate session creation, logger reconfiguration, and file staging into CLI workflow
• Pass session_id and api_key to create_workflow() function

app/core/main.py

2. app/core/tests/test_main.py 🧪 Tests +172/-0

Unit tests for file staging and CLI integration

• Add DummyLogger helper class for test logging capture
• Test valid file copying with content verification
• Test rejection of directory inputs (non-file paths)
• Test collision detection for files with identical basenames from different directories
• Test rejection of files already staged in session directory
• Test CLI API key passing and logger reconfiguration during session initialization
• Test user-friendly error messages for missing files

app/core/tests/test_main.py

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qodo-code-review · 2026-04-24T16:25:38Z

Code Review by Qodo

🐞 Bugs (2) 📘 Rule violations (0) 📎 Requirement gaps (0)

1. ~~Directory copy crashes~~ ☑ 🐞 Bug ☼ Reliability

Description

_prepare_session_files() accepts any existing path and passes it to shutil.copy2(); if the user
supplies a directory (or other non-regular file), this will raise an OSError (e.g.,
IsADirectoryError) that is not caught, aborting the CLI run.

Code

app/core/main.py[R222-228]

+    for raw_path in file_paths:
+        src = Path(raw_path).resolve()
+        if not src.exists():
+            raise FileNotFoundError(f"File not found: {src}")
+        dest = input_dir / src.name
+        shutil.copy2(str(src), str(dest))
+        logger.info(f"Copied '{src}' -> '{dest}'")

Evidence

The new file-staging loop only checks src.exists() before calling shutil.copy2(), which will fail
for directories/special files. main() only catches FileNotFoundError around
_prepare_session_files(), so other copy-related exceptions will propagate and crash the program.

app/core/main.py[205-230]
app/core/main.py[299-307]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
`_prepare_session_files()` checks only `Path.exists()` and then calls `shutil.copy2()`. Passing a directory, unreadable file, or same-file destination can raise exceptions that are not handled by the CLI, causing the run to abort.
### Issue Context
The CLI accepts `-f/--file` to stage files for `FILE_ANALYZER`. This path should fail fast with a clear message for invalid inputs and should not crash the whole workflow.
### Fix Focus Areas
- app/core/main.py[205-230]
- app/core/main.py[299-307]
### Suggested fix
- Validate each path with `src.is_file()` (and optionally reject symlinks with `src.is_symlink()` if desired).
- Wrap `shutil.copy2(...)` in a `try/except` for `OSError` (including `IsADirectoryError`, `PermissionError`, `shutil.SameFileError`) and re-raise as a user-friendly exception that `main()` handles.
- Expand the `except` in `main()` to catch these failures and print a helpful error per bad path.

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

2. ~~Filename collisions overwrite~~ ☑ 🐞 Bug ≡ Correctness

Description

_prepare_session_files() stages files as input_dir/src.name, so two different source paths with the
same basename will silently overwrite each other, causing FILE_ANALYZER to analyze the wrong
content.

Code

app/core/main.py[R226-228]

+        dest = input_dir / src.name
+        shutil.copy2(str(src), str(dest))
+        logger.info(f"Copied '{src}' -> '{dest}'")

Evidence

Destination paths are derived only from src.name (basename), so collisions overwrite previous
copies without warning. FILE_ANALYZER lists and analyzes whatever ends up in the input folder, so a
later collision changes the analyzed file set silently.

app/core/main.py[220-229]
app/core/agents/entry/tool_filesparser.py[41-54]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
Staging uses `dest = input_dir / src.name`, which is not unique across different directories. If users pass two files named the same, the second overwrites the first and the analysis becomes incorrect.
### Issue Context
The CLI supports multiple inputs (`nargs='+'`). Collisions are plausible (e.g., `results.csv` from two folders).
### Fix Focus Areas
- app/core/main.py[205-230]
### Suggested fix
Implement one of:
- **Fail on collision**: if `dest.exists()` then raise a clear error instructing the user to rename/choose a different file.
- **Collision-resistant naming**: append a short hash of the full resolved path (or file content) to the filename (e.g., `results__a1b2c3.csv`).
- **Preserve directory structure**: copy into subfolders derived from the source parent (sanitized) so basenames can repeat safely.

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

3. API key CLI not applied 🐞 Bug ☼ Reliability

Description

The CLI accepts --api-key but does not pass it to llm_creation(), so model initialization may still
rely on environment variables and fail even when the user supplies a key.

Code

app/core/main.py[R292-294]

+    # Initialize language models
  models = llm_creation()

Evidence

llm_creation() explicitly supports an api_key parameter, but main() calls it with no arguments.
Meanwhile, the CLI defines --api-key, meaning the supplied key may not be used to build the LLM
clients created in llm_creation().

app/core/main.py[262-265]
app/core/main.py[292-294]
app/core/main.py[101-160]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
`--api-key` is parsed but not used when creating the LLM instances via `llm_creation()`. This can break local CLI usage when the environment variables are not set.
### Issue Context
`llm_creation(api_key=None, ...)` is designed to accept an explicit key. The CLI already exposes `--api-key`.
### Fix Focus Areas
- app/core/main.py[262-265]
- app/core/main.py[292-294]
### Suggested fix
Change `models = llm_creation()` to `models = llm_creation(api_key=args.api_key)` (or equivalent provider-aware wiring) so the CLI-provided key is honored during model creation.

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

4. Evaluation flag ignored 🐞 Bug ≡ Correctness

Description

The CLI defines --evaluation but always calls create_workflow(evaluation=False), so evaluation mode
cannot be enabled from the CLI.

Code

app/core/main.py[R308-315]

  try:
-        # Create and process workflow
      workflow = create_workflow(
          models=models,
+            session_id=session_id,
          endpoint_url=endpoint_url,
          evaluation=False,
-            api_key=args.api_key
+            api_key=args.api_key,
      )
-

Evidence

Argument parsing defines args.evaluation, but the workflow is constructed with a hard-coded
evaluation=False, making the flag ineffective.

app/core/main.py[258-261]
app/core/main.py[308-316]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
`--evaluation` is exposed on the CLI but never applied; `create_workflow(..., evaluation=False, ...)` forces non-evaluation behavior.
### Issue Context
Users invoking `python -m app.core.main --evaluation ...` will not get evaluation-mode execution.
### Fix Focus Areas
- app/core/main.py[258-261]
- app/core/main.py[308-316]
### Suggested fix
Pass `evaluation=args.evaluation` into `create_workflow(...)` so the CLI flag works as intended.

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

5. ~~Session logger not reconfigured~~ ☑ 🐞 Bug ◔ Observability

Description

main.py sets its module logger before initialize_session_context(), so logging stays configured for
the non-session log path even after a new session_id is created and set.

Code

app/core/main.py[R295-298]

+    # Create a user session (mirrors the Streamlit session lifecycle)
+    session_id = create_user_session()
+    initialize_session_context(session_id)
+

Evidence

setup_logger() chooses a session-specific log file only when session_id_context is already set.
main.py creates a session and sets the session context later, but never reinitializes its logger
afterward, so logs from the CLI run won’t be session-scoped.

app/core/main.py[18-21]
app/core/main.py[295-298]
app/core/session.py[72-101]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
The logger in `app.core.main` is constructed before the session context is set. Since `setup_logger()` routes logs based on `session_id_context`, the CLI run continues logging to the non-session file.
### Issue Context
This reduces the usefulness of the new session lifecycle for debugging local runs.
### Fix Focus Areas
- app/core/main.py[18-21]
- app/core/main.py[295-298]
- app/core/session.py[72-101]
### Suggested fix
After `initialize_session_context(session_id)`, re-run `setup_logger(__name__)` (or reconfigure the existing logger) so subsequent logs are written to the session-specific log file.

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

github-actions · 2026-04-24T16:26:32Z

PR Reviewer Guide 🔍

(Review updated until commit `1515fec`)

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 3 🔵🔵🔵⚪⚪

🔒 No security concerns identified

⚡ Recommended focus areas for review

Docstring Format

The docstring for the _prepare_session_files function does not follow the Google style guidelines. Please revise it to include type annotations (e.g., session_id (str), file_paths (List[str])), a one-line summary, and clearly defined sections for Args, Returns, and Raises.

def _prepare_session_files(session_id: str, file_paths: List[str]) -> Path:
    """
    Copy user-supplied local files into the session's input directory so that
    the FILE_ANALYZER tool can discover them at runtime.

    Args:
        session_id: Active session identifier.
        file_paths: List of local file paths provided via the CLI.

    Returns:
        Path to the session input directory.

    Raises:
        SessionFilePreparationError: If any supplied path cannot be staged safely.
    """
    input_dir = create_user_session(session_id, input_dir=True)
    staged_destinations: dict[Path, Path] = {}

    for raw_path in file_paths:
        src = Path(raw_path).expanduser().resolve(strict=False)
        if not src.exists():
            raise SessionFilePreparationError(src, f"File not found: {src}")
        if not src.is_file():
            raise SessionFilePreparationError(src, f"Input path is not a file: {src}")

        dest = input_dir / src.name
        previous_src = staged_destinations.get(dest)
        if previous_src is not None:
            if previous_src == src:
                raise SessionFilePreparationError(
                    src,
                    f"Input file was provided more than once: {src}",
                )
            raise SessionFilePreparationError(
                src,
                (
                    f"Cannot stage '{src}' because it would overwrite '{previous_src}' in "
                    f"the session input directory. Rename one of the files or choose a different path."
                ),
            )

        if src == dest.resolve(strict=False):
            raise SessionFilePreparationError(
                src,
                f"Input file is already staged in the session directory: {src}",
            )

        if dest.exists():
            raise SessionFilePreparationError(
                src,
                f"Cannot stage '{src}' because destination '{dest}' already exists.",
            )

        try:
            shutil.copy2(str(src), str(dest))
        except (shutil.SameFileError, OSError) as exc:
            raise SessionFilePreparationError(
                src,
                f"Failed to stage '{src}' into '{dest}': {exc}",
            ) from exc

        staged_destinations[dest] = src
        logger.info(f"Copied '{src}' -> '{dest}'")

    return input_dir

Docstring Format

The main function’s docstring should be updated to adhere to Google style format. Consider structuring the usage examples and including a short summary along with detailed type information for any parameters or return values.

def main():
    """
    CLI entry-point for running the MetaboT workflow.

    Usage examples:
        python -m app.core.main -q 1
        python -m app.core.main -c "Describe my dataset" -f data.csv
        python -m app.core.main -c "Compare files" -f file1.csv file2.tsv
    """

github-actions · 2026-04-24T16:27:00Z

PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Impact
Possible issue	Ensure destination directory exists Ensure that the destination directory exists before attempting to copy files. This prevents errors if the directory structure is not already in place. app/core/main.py [226-227] +dest.parent.mkdir(parents=True, exist_ok=True) shutil.copy2(str(src), str(dest)) Suggestion importance[1-10]: 8 __ Why: The suggestion to ensure the destination directory exists before copying files is important for preventing runtime errors. It enhances the robustness of the `_prepare_session_files` function by ensuring that the directory structure is in place, which is crucial for file operations. The improved code accurately reflects the suggested change.	Medium

qodo-code-review · 2026-04-24T16:29:02Z

+    # Initialize language models
    models = llm_creation()



3. Api key cli not applied 🐞 Bug ☼ Reliability

The CLI accepts --api-key but does not pass it to llm_creation(), so model initialization may still rely on environment variables and fail even when the user supplies a key.

Agent Prompt

### Issue description `--api-key` is parsed but not used when creating the LLM instances via `llm_creation()`. This can break local CLI usage when the environment variables are not set. ### Issue Context `llm_creation(api_key=None, ...)` is designed to accept an explicit key. The CLI already exposes `--api-key`. ### Fix Focus Areas - app/core/main.py[262-265] - app/core/main.py[292-294] ### Suggested fix Change `models = llm_creation()` to `models = llm_creation(api_key=args.api_key)` (or equivalent provider-aware wiring) so the CLI-provided key is honored during model creation.

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

- Introduced SessionFilePreparationError for better error management during file staging. - Enhanced _prepare_session_files function to handle various file-related errors. - Added unit tests for session file preparation, covering valid file copying and error scenarios. - Documented changes in the agentic engineering log.

qodo-code-review · 2026-04-24T22:37:30Z

Code Review by Qodo

🐞 Bugs (4) 📘 Rule violations (0) 📎 Requirement gaps (0)

1. Wrong API key reused 🐞 Bug ≡ Correctness ⭐ New

Description

main() now forwards --api-key into llm_creation(), but llm_creation keeps a single api_key value and
applies it to every configured provider section. In a multi-provider params.ini (OpenAI + deepseek +
ovh), deepseek/ovh models will incorrectly receive the OpenAI key (or the first resolved key),
causing authentication failures.

Code

app/core/main.py[R346-347]

+    # Initialize language models
+    models = llm_creation(api_key=args.api_key)

Evidence

llm_creation mutates the function parameter api_key once and then reuses it for subsequent
sections, instead of resolving a per-section/per-provider key; main() now passes the CLI OpenAI key
into llm_creation, guaranteeing it will be reused for deepseek/ovh sections. The default params.ini
includes deepseek and ovh sections, so this misconfiguration is reachable in the repo’s standard
setup.

app/core/main.py[109-166]
app/core/main.py[346-348]
app/config/params.ini[1-49]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

### Issue description
`llm_creation()` reuses a single `api_key` value across all config sections. After this PR, `main()` passes `--api-key` into `llm_creation()`, so deepseek/ovh models can receive the OpenAI key and fail auth.

### Issue Context
`app/config/params.ini` contains OpenAI sections plus `deepseek_*` and `ovh_*` sections. Each provider needs its own key (from provider-specific env vars), while the CLI `--api-key` is described as an OpenAI key.

### Fix Focus Areas
- app/core/main.py[109-166]
- app/core/main.py[346-348]

### Suggested fix approach
- In `llm_creation()`, do **not** mutate/reuse the incoming `api_key` parameter across sections.
- Introduce a per-section variable, e.g. `section_api_key`:
 - If `provider == "openai"` and a CLI `api_key` is provided, use it.
 - Otherwise, resolve via `get_api_key(provider)` for that section.
- Use `section_api_key` when setting `model_params[...]`.
- (Optional) If you want CLI support for deepseek/ovh keys too, add explicit CLI flags rather than overloading `--api-key`.

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

2. ~~Directory copy crashes~~ ☑ 🐞 Bug ☼ Reliability

Description

_prepare_session_files() accepts any existing path and passes it to shutil.copy2(); if the user
supplies a directory (or other non-regular file), this will raise an OSError (e.g.,
IsADirectoryError) that is not caught, aborting the CLI run.

Code

app/core/main.py[R222-228]

+    for raw_path in file_paths:
+        src = Path(raw_path).resolve()
+        if not src.exists():
+            raise FileNotFoundError(f"File not found: {src}")
+        dest = input_dir / src.name
+        shutil.copy2(str(src), str(dest))
+        logger.info(f"Copied '{src}' -> '{dest}'")

Evidence

The new file-staging loop only checks src.exists() before calling shutil.copy2(), which will fail
for directories/special files. main() only catches FileNotFoundError around
_prepare_session_files(), so other copy-related exceptions will propagate and crash the program.

app/core/main.py[205-230]
app/core/main.py[299-307]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
`_prepare_session_files()` checks only `Path.exists()` and then calls `shutil.copy2()`. Passing a directory, unreadable file, or same-file destination can raise exceptions that are not handled by the CLI, causing the run to abort.
### Issue Context
The CLI accepts `-f/--file` to stage files for `FILE_ANALYZER`. This path should fail fast with a clear message for invalid inputs and should not crash the whole workflow.
### Fix Focus Areas
- app/core/main.py[205-230]
- app/core/main.py[299-307]
### Suggested fix
- Validate each path with `src.is_file()` (and optionally reject symlinks with `src.is_symlink()` if desired).
- Wrap `shutil.copy2(...)` in a `try/except` for `OSError` (including `IsADirectoryError`, `PermissionError`, `shutil.SameFileError`) and re-raise as a user-friendly exception that `main()` handles.
- Expand the `except` in `main()` to catch these failures and print a helpful error per bad path.

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

3. ~~Filename collisions overwrite~~ ☑ 🐞 Bug ≡ Correctness

Description

_prepare_session_files() stages files as input_dir/src.name, so two different source paths with the
same basename will silently overwrite each other, causing FILE_ANALYZER to analyze the wrong
content.

Code

app/core/main.py[R226-228]

+        dest = input_dir / src.name
+        shutil.copy2(str(src), str(dest))
+        logger.info(f"Copied '{src}' -> '{dest}'")

Evidence

Destination paths are derived only from src.name (basename), so collisions overwrite previous
copies without warning. FILE_ANALYZER lists and analyzes whatever ends up in the input folder, so a
later collision changes the analyzed file set silently.

app/core/main.py[220-229]
app/core/agents/entry/tool_filesparser.py[41-54]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
Staging uses `dest = input_dir / src.name`, which is not unique across different directories. If users pass two files named the same, the second overwrites the first and the analysis becomes incorrect.
### Issue Context
The CLI supports multiple inputs (`nargs='+'`). Collisions are plausible (e.g., `results.csv` from two folders).
### Fix Focus Areas
- app/core/main.py[205-230]
### Suggested fix
Implement one of:
- **Fail on collision**: if `dest.exists()` then raise a clear error instructing the user to rename/choose a different file.
- **Collision-resistant naming**: append a short hash of the full resolved path (or file content) to the filename (e.g., `results__a1b2c3.csv`).
- **Preserve directory structure**: copy into subfolders derived from the source parent (sanitized) so basenames can repeat safely.

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

View more (1)

4. API key CLI not applied 🐞 Bug ☼ Reliability

Description

The CLI accepts --api-key but does not pass it to llm_creation(), so model initialization may still
rely on environment variables and fail even when the user supplies a key.

Code

app/core/main.py[R292-294]

+    # Initialize language models
 models = llm_creation()

Evidence

llm_creation() explicitly supports an api_key parameter, but main() calls it with no arguments.
Meanwhile, the CLI defines --api-key, meaning the supplied key may not be used to build the LLM
clients created in llm_creation().

app/core/main.py[262-265]
app/core/main.py[292-294]
app/core/main.py[101-160]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
`--api-key` is parsed but not used when creating the LLM instances via `llm_creation()`. This can break local CLI usage when the environment variables are not set.
### Issue Context
`llm_creation(api_key=None, ...)` is designed to accept an explicit key. The CLI already exposes `--api-key`.
### Fix Focus Areas
- app/core/main.py[262-265]
- app/core/main.py[292-294]
### Suggested fix
Change `models = llm_creation()` to `models = llm_creation(api_key=args.api_key)` (or equivalent provider-aware wiring) so the CLI-provided key is honored during model creation.

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

5. Session ID leaks to stdout 🐞 Bug ☼ Reliability ⭐ New

Description

main() now calls initialize_session_context(session_id), whose implementation prints the session id
unconditionally. This introduces unsolicited stdout output for every CLI run and can break scripts
that expect clean output.

Code

app/core/main.py[R331-334]

+    session_id = create_user_session()
+    initialize_session_context(session_id)
+    global logger
+    logger = setup_logger(__name__)

Evidence
initialize_session_context() contains an unconditional print statement, and main() invokes it on the
CLI path.
app/core/main.py[331-334]
app/core/session.py[15-18]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

### Issue description
The CLI now emits `Session ID set to: ...` on stdout because `initialize_session_context()` uses `print()`. This is noisy and can interfere with piping/automation.

### Issue Context
The session context is valuable, but it should be logged (or gated behind a verbose flag), not printed unconditionally.

### Fix Focus Areas
- app/core/session.py[15-18]
- app/core/main.py[331-334]

### Suggested fix approach
- Remove the `print()` from `initialize_session_context()` (preferred), or gate it behind an explicit verbosity flag.
- If you still want visibility, emit via the configured logger after it’s set up for the session.

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

6. Evaluation flag ignored 🐞 Bug ≡ Correctness

Description

The CLI defines --evaluation but always calls create_workflow(evaluation=False), so evaluation mode
cannot be enabled from the CLI.

Code

app/core/main.py[R308-315]

 try:
-        # Create and process workflow
     workflow = create_workflow(
         models=models,
+            session_id=session_id,
         endpoint_url=endpoint_url,
         evaluation=False,
-            api_key=args.api_key
+            api_key=args.api_key,
     )
-

Evidence

Argument parsing defines args.evaluation, but the workflow is constructed with a hard-coded
evaluation=False, making the flag ineffective.

app/core/main.py[258-261]
app/core/main.py[308-316]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
`--evaluation` is exposed on the CLI but never applied; `create_workflow(..., evaluation=False, ...)` forces non-evaluation behavior.
### Issue Context
Users invoking `python -m app.core.main --evaluation ...` will not get evaluation-mode execution.
### Fix Focus Areas
- app/core/main.py[258-261]
- app/core/main.py[308-316]
### Suggested fix
Pass `evaluation=args.evaluation` into `create_workflow(...)` so the CLI flag works as intended.

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

7. ~~Session logger not reconfigured~~ ☑ 🐞 Bug ◔ Observability

Description

main.py sets its module logger before initialize_session_context(), so logging stays configured for
the non-session log path even after a new session_id is created and set.

Code

app/core/main.py[R295-298]

+    # Create a user session (mirrors the Streamlit session lifecycle)
+    session_id = create_user_session()
+    initialize_session_context(session_id)
+

Evidence

setup_logger() chooses a session-specific log file only when session_id_context is already set.
main.py creates a session and sets the session context later, but never reinitializes its logger
afterward, so logs from the CLI run won’t be session-scoped.

app/core/main.py[18-21]
app/core/main.py[295-298]
app/core/session.py[72-101]

Agent prompt

The issue below was found during a code review. Follow the provided context and guidance below and implement a solution

## Issue description
The logger in `app.core.main` is constructed before the session context is set. Since `setup_logger()` routes logs based on `session_id_context`, the CLI run continues logging to the non-session file.
### Issue Context
This reduces the usefulness of the new session lifecycle for debugging local runs.
### Fix Focus Areas
- app/core/main.py[18-21]
- app/core/main.py[295-298]
- app/core/session.py[72-101]
### Suggested fix
After `initialize_session_context(session_id)`, re-run `setup_logger(__name__)` (or reconfigure the existing logger) so subsequent logs are written to the session-specific log file.

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

github-actions · 2026-04-24T22:38:11Z

Persistent review updated to latest commit 1515fec

github-actions · 2026-04-24T22:38:20Z

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qodo-code-review · 2026-04-24T22:40:55Z

+    # Initialize language models
+    models = llm_creation(api_key=args.api_key)


1. Wrong api key reused 🐞 Bug ≡ Correctness

main() now forwards --api-key into llm_creation(), but llm_creation keeps a single api_key value and applies it to every configured provider section. In a multi-provider params.ini (OpenAI + deepseek + ovh), deepseek/ovh models will incorrectly receive the OpenAI key (or the first resolved key), causing authentication failures.

Agent Prompt

### Issue description `llm_creation()` reuses a single `api_key` value across all config sections. After this PR, `main()` passes `--api-key` into `llm_creation()`, so deepseek/ovh models can receive the OpenAI key and fail auth. ### Issue Context `app/config/params.ini` contains OpenAI sections plus `deepseek_*` and `ovh_*` sections. Each provider needs its own key (from provider-specific env vars), while the CLI `--api-key` is described as an OpenAI key. ### Fix Focus Areas - app/core/main.py[109-166] - app/core/main.py[346-348] ### Suggested fix approach - In `llm_creation()`, do **not** mutate/reuse the incoming `api_key` parameter across sections. - Introduce a per-section variable, e.g. `section_api_key`: - If `provider == "openai"` and a CLI `api_key` is provided, use it. - Otherwise, resolve via `get_api_key(provider)` for that section. - Use `section_api_key` when setting `model_params[...]`. - (Optional) If you want CLI support for deepseek/ovh keys too, add explicit CLI flags rather than overloading `--api-key`.

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add CLI file input support for FILE_ANALYZER tool

b41b611

dosubot Bot added the size:L This PR changes 100-499 lines, ignoring generated files. label Apr 24, 2026

dosubot Bot added the enhancement New feature or request label Apr 24, 2026

github-actions Bot added the Review effort 3/5 label Apr 24, 2026

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lfnothias closed this Apr 24, 2026

lfnothias reopened this Apr 24, 2026

lfnothias merged commit 6a32a28 into dev Apr 24, 2026
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add CLI file input support for FILE_ANALYZER tool when running locally#172

add CLI file input support for FILE_ANALYZER tool when running locally#172
lfnothias merged 2 commits into
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		# Initialize language models
		models = llm_creation(api_key=args.api_key)

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