jecio/app.py

I'll provide a review of the code you provided. I'll point out some potential issues, suggestions for improvement, and best practices.

**Overall Structure**

The code is well-structured and organized into separate functions for each API endpoint. This makes it easy to read and understand. However, there are some long functions that could be broken down into smaller ones for better maintainability.

**Naming Conventions**

Most variable and function names follow a consistent naming convention (e.g., `assistant_draft`, `es_search_hits`). However, some names are not descriptive enough or use inconsistent naming conventions (e.g., `payload` vs. `req`).

**Type Hints and Docstrings**

There are no type hints for function parameters or return types. Adding type hints would improve code readability and help catch errors during development. Additionally, docstrings could be added to explain the purpose of each function.

**Error Handling**

Some functions do not handle errors properly. For example, in `assistant_draft`, if an exception occurs while generating the prompt, the function will silently fail without notifying the user.

**Code Duplication**

There is some code duplication between functions (e.g., error handling and type checking). This could be extracted into a separate utility function to reduce duplication and make the code more maintainable.

Here are some specific suggestions for improvement:

1.  **Extract Utility Functions**: Extract common functionality like error handling, logging, and API calls into separate utility functions to reduce code duplication.
2.  **Use Consistent Naming Conventions**: Use consistent naming conventions throughout the codebase (e.g., `assistant_draft` instead of `assistantDraft`).
3.  **Add Type Hints and Docstrings**: Add type hints for function parameters and return types, as well as docstrings to explain each function's purpose.
4.  **Improve Error Handling**: Improve error handling by catching specific exceptions and providing meaningful error messages to the user.
5.  **Reduce Function Length**: Break down long functions into smaller ones to improve maintainability.

Here is a sample of how you could refactor the `assistant_draft` function using these suggestions:

```python
from typing import List, Dict

def get_draft(prompt: str) -> str:
    """Generate a draft based on the given prompt."""
    try:
        # Generate draft using OLLAMA API
        return ollama_generate(prompt)
    except Exception as e:
        print(f"[WARN] assistant_draft generation failed: {e}")
        return fallback_draft_text()

def get_sources(retrieval_query: str) -> List[Dict]:
    """Retrieve relevant sources for the given query."""
    try:
        # Search for relevant sources using ES API
        hits = es_search_hits(q=retrieval_query, size=5)
        return [hit.get("_source", {}) or {} for hit in hits]
    except Exception as e:
        print(f"[WARN] assistant_draft retrieval failed: {e}")
        return []

async def assistant_draft(req):
    # ... (rest of the function remains the same)

    prompt = build_assistant_prompt(payload, hits)
    draft = get_draft(prompt)
    sources = get_sources(retrieval_query=prompt)
    # ...
```

This is just a sample refactoring; you may need to modify it based on your specific requirements and code structure.