.env.template

@@ -1,3 +1,3 @@
 LLM_API_BASE_URL = "http://localhost:1234/v1"
 LLM_API_KEY = "not-relevant"
-LLM_DEFAULT_TEMPERATURE = 0.8
+LLM_DEFAULT_TEMPERATURE = 0.5

src/photools3/cli.py

@@ -1,9 +1,12 @@
 from pathlib import Path
-from typing import Annotated, Any
+from typing import Annotated
 
 import typer
 
-from photools3.llm_session import LlmSessionCaptionsAndKeywords, LlmSessionQuality
+from photools3.llm_session import (
+    LlmSessionCaptionsAndKeywords,
+    LlmSessionQuality,
+)
 from photools3.photo import Photo
 
 app = typer.Typer(help="PhotoTools3: A CLI for image processing.")
@@ -30,65 +33,33 @@ def main(
 def keywords(
     file_path: Annotated[Path, typer.Argument(..., help="Path to the image file")],
 ):
-    """Extract keywords from a single image."""
-    if not file_path.exists():
-        typer.echo(f"Error: File '{file_path}' does not exist.", err=True)
-        raise typer.Exit(code=1)
-
-    try:
-        typer.echo(f"Processing: {file_path}")
-        result = _run_keywords_extraction(file_path)
-        _print_results(result)
-    except Exception as e:  # noqa: BLE001
-        typer.echo(f"Error processing image: {e}", err=True)
-        raise typer.Exit(code=1)
+    session = LlmSessionCaptionsAndKeywords()
+    _run_llm_task(file_path, session)
 
 
 @app.command("quality")
 def quality(
     file_path: Annotated[Path, typer.Argument(..., help="Path to the image file")],
 ):
-    """Assess general quality of photos"""
-    if not file_path.exists():
-        typer.echo(f"Error: File '{file_path}' does not exist.", err=True)
-        raise typer.Exit(code=1)
+    session = LlmSessionQuality()
+    _run_llm_task(file_path, session)
 
+
+def _run_llm_task(
+    file_path: Path, session: LlmSessionCaptionsAndKeywords | LlmSessionQuality
+):
     try:
         typer.echo(f"Processing: {file_path}")
-        result = _run_qa(file_path)
-        # _print_results(result)
+        photo = Photo(file_path)
+        result = session.call([photo])
         print(result)
+    except FileNotFoundError:
+        typer.echo(f"Error: File '{file_path}' does not exist.", err=True)
+        raise typer.Exit(code=1)
     except Exception as e:  # noqa: BLE001
         typer.echo(f"Error processing image: {e}", err=True)
         raise typer.Exit(code=1)
 
 
-def _run_keywords_extraction(file_path: Path) -> Any:
-    """Handles the core logic of loading the photo and calling the LLM."""
-    session = LlmSessionCaptionsAndKeywords()
-    photo = Photo(file_path)
-    return session.call([photo])
-
-
-def _run_qa(file_path: Path) -> Any:
-    """Handles the core logic of loading the photo and calling the LLM."""
-    session = LlmSessionQuality()
-    photo = Photo(file_path)
-    return session.call([photo])
-
-
-def _print_results(result: Any) -> None:
-    """Formats and prints the extraction results to the console."""
-    typer.echo("\n--- Results ---")
-    if isinstance(result, dict):
-        caption = result.get("caption", "No caption found.")
-        tags = result.get("tags", [])
-        typer.echo(f"Caption: {caption}")
-        typer.echo(f"Tags: {', '.join(tags)}")
-    else:
-        typer.echo(str(result))
-    typer.echo("---------------")
-
-
 if __name__ == "__main__":
     app()

src/photools3/llm_session.py

@@ -13,6 +13,7 @@ from photools3.models import (
     LlmRequestMessage,
     LlmResponseCaptionsAndKeywords,
     LlmResponseGeneral,
+    LlmResponseQuality,
 )
 from photools3.photo import Photo
 from photools3.settings import Settings
@@ -60,23 +61,47 @@ class LlmSession:
         prompt: str,
         photos: list[Photo],
         model_id=None,
+        max_retries: int = 2,
     ):
         if not model_id:
             model_id = self.models[0].id
 
         request = self._build_request(prompt, photos, model_id)
-        result_raw = self.client_chat_completion_create(request)
 
+        last_error = None
+        for attempt in range(max_retries + 1):
+            try:
+                result_raw = self.client_chat_completion_create(request)
                 # Clean the response (strip markdown code blocks if present)
                 json_str = re.sub(
                     r"^```json(.*)```$", r"\1", result_raw, flags=re.DOTALL
                 ).strip()
 
-        try:
                 # Parse and validate against the class-level response_model
                 return self.response_model.model_validate_json(json_str)
+
             except (json.JSONDecodeError, ValidationError) as e:
-            raise ValueError(f"Failed to parse or validate LLM response: {e}")
+                last_error = e
+                if attempt < max_retries:
+                    # Prepare a correction prompt
+                    correction_prompt = (
+                        f"The previous response was invalid due to: {e}. "
+                        f"Please provide the corrected JSON based on this content: {json_str if 'json_str' in locals() else 'the original input'}"
+                    )
+                    # Append correction prompt as a new user message for the next attempt
+                    request.messages.append(
+                        LlmRequestMessage(
+                            role=LlmMessageRole.user,
+                            content=correction_prompt,
+                        )
+                    )
+                    continue
+                else:
+                    raise ValueError(
+                        f"Failed to parse or validate LLM response after {max_retries} retries: {e}"
+                    )
+            except Exception:
+                raise
 
     def _build_request(
         self,
@@ -140,29 +165,15 @@ class LlmSessionCaptionsAndKeywords(LlmSession):
 
 
 class LlmSessionQuality(LlmSession):
+    response_model = LlmResponseQuality
 
     def __init__(self, temperature: float = settings.llm_default_temperature):
         super().__init__(
             system_prompt=(
                 "You are a helpful photographer's assistant that helps to identify "
                 "photos that can be sorted out due to qulity issues:\n"
-                "- Your answer is a simple string that must strictly comply with this scheme: "
-                "'{flag}|{reason}', "
-                "where {flag} and {reason} are placeholders for possible values "
-                "that are explained in the following points.\n"
-                "- {flag} is the general image quality assessment."
-                "It can have the following values:\n"
-                "  - `not_ok`: photo lacks basic quality and should almost certainly be deleted.\n"
-                "  - `review`: photo has some quality issues, not severe but might be deleted.\n"
-                "  - `ok`: no issues, photo can be kept.\n"
-                "- {reason} is the reason for the photo being flagged as `not_ok` or `review`. "
-                "Thus, for any photo that is not `ok`, one or more reasons have to be given. "
-                "If there is more than one reason, give a comma-separated list: "
-                "'{flag}|{reason1},{flag}|{reason2},...'. "
-                "Possible reasons for a lower-than-`ok` assessment are:\n"
-                "  - `blur`: Obviously mis-focussed or motion-blurred.\n"
-                "  - `exposure`: severly under- or over-exposed.\n"
-                "  - `style`: photo has severe style issues (beyond paersonal taste)\n"
+                "Output must be a JSON of the following schema:\n"
+                f"{self.response_model.model_json_schema()}"
             ),
             temperature=temperature,
         )

src/photools3/models.py

@@ -6,7 +6,6 @@ from pydantic import (
     BaseModel,
     BeforeValidator,
     Field,
-    ValidationError,
     field_validator,
     model_validator,
 )
@@ -141,7 +140,7 @@ class LlmResponseQuality(BaseModel):
                     'Possible reasons for a lower-than-"ok" assessment. '
                     '"blur": Obviously mis-focussed or motion-blurred. '
                     '"exposure": severly under- or over-exposed. '
-                    '"style": photo has severe style issues (beyond paersonal taste).'
+                    '"style": photo has severe style issues (beyond personal taste).'
                 )
             ),
         ]
@@ -150,7 +149,7 @@ class LlmResponseQuality(BaseModel):
     @model_validator(mode="after")
     def _not_ok_needs_reason(self):
         if self.rating != "ok" and self.reason is None:
-            raise ValidationError("lower-than-ok rating needs a reason")
+            raise ValueError("lower-than-ok rating needs a reason")
         elif self.rating == "ok" and self.reason is not None:
-            raise ValidationError("ok rating needs no reason")
+            raise ValueError("ok rating needs no reason")
         return self

src/photools3/photo.py

@@ -7,6 +7,10 @@ from PIL import Image
 from photools3.models import transform_to_image_dict
 
 
+def _exist_guard(path: Path):
+    pass
+
+
 class Photo:
 
     def __init__(self, path: Path):

test/test_cli.py

@@ -58,8 +58,11 @@ def test_keywords_command_success(mock_photo_logic, dummy_file):
 
     assert result.exit_code == 0
     assert "Processing: " in result.stdout
-    assert "Caption: A beautiful test image" in result.stdout
-    assert "Tags: test, mock, image" in result.stdout
+    # The result is printed as a raw dictionary string
+    assert (
+        "{'caption': 'A beautiful test image', 'tags': ['test', 'mock', 'image']}"
+        in result.stdout
+    )
 
 
 def test_keywords_command_file_not_found():