Merge pull request #76 from Kiln-AI/main

Docs update

.coveragerc

@@ -2,3 +2,4 @@
 omit =
     **/test_*.py
     libs/core/kiln_ai/adapters/ml_model_list.py
+    conftest.py

.github/workflows/build_and_test.yml

@@ -12,7 +12,6 @@ jobs:
           - "3.10"
           - "3.11"
           - "3.12"
-          - "3.13"
 
     steps:
       - uses: actions/checkout@v4

.github/workflows/build_desktop.yml

@@ -36,9 +36,22 @@ jobs:
       - name: Install the project
         run: uv sync
 
-      # Compress MacOS app param ignored on Windows
-      - run: uv run bash ./app/desktop/build_desktop_app.sh --compress-mac-app
-      - uses: actions/upload-artifact@v4
+      # Compress MacOS app param ignored on other platforms
+      - name: Build Desktop App
+        run: uv run bash ./app/desktop/build_desktop_app.sh --compress-mac-app
+
+      - name: Build Windows Installer
+        if: matrix.os == 'windows-latest'
+        uses: Minionguyjpro/[email protected]
+        with:
+          path: ./app/desktop/WinInnoSetup.iss
+
+      - name: Copy Windows Installer
+        if: matrix.os == 'windows-latest'
+        run: cp ./app/desktop/Output/kilnsetup.exe ./app/desktop/build/dist/Kiln.Windows.Installer.exe
+
+      - name: Upload Build
+        uses: actions/upload-artifact@v4
         with:
           name: kiln-desktop-${{ runner.os }}-${{ runner.arch }}
           path: ./app/desktop/build/dist/*

.github/workflows/test_count.yml

@@ -18,7 +18,7 @@ jobs:
           enable-cache: true
 
       - name: Set up Python
-        run: uv python install
+        run: uv python install 3.12
 
       - name: Install the project
         run: uv sync --all-extras --dev

app/desktop/WinInnoSetup.iss

@@ -1,7 +1,7 @@
 ; Script generated by the Inno Setup Script Wizard.
 ; SEE THE DOCUMENTATION FOR DETAILS ON CREATING INNO SETUP SCRIPT FILES!
 
-#define MyAppPath "APP_PATH_TEMPLATE"
+#define MyAppPath "build\dist\Kiln"
 #define MyAppName "Kiln"
 #define MyAppVersion "0.5.6"
 #define MyAppPublisher "Chesterfield Laboratories Inc"

app/desktop/desktop_server.py

@@ -1,9 +1,13 @@
 import contextlib
 import threading
 import time
+from contextlib import asynccontextmanager
 
 import kiln_server.server as kiln_server
 import uvicorn
+from fastapi import FastAPI
+from kiln_ai.datamodel import set_strict_mode as set_strict_mode_datamodel
+from kiln_ai.datamodel import strict_mode as strict_mode_datamodel
 
 from app.desktop.studio_server.data_gen_api import connect_data_gen_api
 from app.desktop.studio_server.finetune_api import connect_fine_tune_api
@@ -14,8 +18,18 @@
 from app.desktop.studio_server.webhost import connect_webhost
 
 
+@asynccontextmanager
+async def lifespan(app: FastAPI):
+    # Set strict mode on startup
+    original_strict_mode = strict_mode_datamodel()
+    set_strict_mode_datamodel(True)
+    yield
+    # Reset strict mode on shutdown
+    set_strict_mode_datamodel(original_strict_mode)
+
+
 def make_app():
-    app = kiln_server.make_app()
+    app = kiln_server.make_app(lifespan=lifespan)
     connect_provider_api(app)
     connect_prompt_api(app)
     connect_repair_api(app)

app/desktop/studio_server/finetune_api.py

@@ -138,10 +138,7 @@ async def finetune(
         project_id: str, task_id: str, finetune_id: str
     ) -> FinetuneWithStatus:
         task = task_from_id(project_id, task_id)
-        finetune = next(
-            (finetune for finetune in task.finetunes() if finetune.id == finetune_id),
-            None,
-        )
+        finetune = Finetune.from_id_and_parent_path(finetune_id, task.path)
         if finetune is None:
             raise HTTPException(
                 status_code=404,
@@ -227,14 +224,7 @@ async def create_finetune(
             )
         finetune_adapter_class = finetune_registry[request.provider]
 
-        dataset = next(
-            (
-                split
-                for split in task.dataset_splits()
-                if split.id == request.dataset_id
-            ),
-            None,
-        )
+        dataset = DatasetSplit.from_id_and_parent_path(request.dataset_id, task.path)
         if dataset is None:
             raise HTTPException(
                 status_code=404,
@@ -281,10 +271,7 @@ async def download_dataset_jsonl(
                 detail=f"Dataset format '{format_type}' not found",
             )
         task = task_from_id(project_id, task_id)
-        dataset = next(
-            (split for split in task.dataset_splits() if split.id == dataset_id),
-            None,
-        )
+        dataset = DatasetSplit.from_id_and_parent_path(dataset_id, task.path)
         if dataset is None:
             raise HTTPException(
                 status_code=404,

app/desktop/studio_server/provider_api.py

@@ -26,10 +26,21 @@
 from pydantic import BaseModel, Field
 
 
-async def connect_ollama() -> OllamaConnection:
+async def connect_ollama(custom_ollama_url: str | None = None) -> OllamaConnection:
     # Tags is a list of Ollama models. Proves Ollama is running, and models are available.
+    if (
+        custom_ollama_url
+        and not custom_ollama_url.startswith("http://")
+        and not custom_ollama_url.startswith("https://")
+    ):
+        raise HTTPException(
+            status_code=400,
+            detail="Invalid Ollama URL. It must start with http:// or https://",
+        )
+
     try:
-        tags = requests.get(ollama_base_url() + "/api/tags", timeout=5).json()
+        base_url = custom_ollama_url or ollama_base_url()
+        tags = requests.get(base_url + "/api/tags", timeout=5).json()
     except requests.exceptions.ConnectionError:
         raise HTTPException(
             status_code=417,
@@ -48,6 +59,10 @@ async def connect_ollama() -> OllamaConnection:
             detail="Failed to parse Ollama data - unsure which models are installed.",
         )
 
+    # Save the custom Ollama URL if used to connect
+    if custom_ollama_url and custom_ollama_url != Config.shared().ollama_base_url:
+        Config.shared().save_setting("ollama_base_url", custom_ollama_url)
+
     return ollama_connection
 
 
@@ -133,11 +148,18 @@ async def get_available_models() -> List[AvailableModels]:
         if fine_tuned_models:
             models.append(fine_tuned_models)
 
+        # Add any custom models
+        custom = custom_models()
+        if custom:
+            models.append(custom)
+
         return models
 
     @app.get("/api/provider/ollama/connect")
-    async def connect_ollama_api() -> OllamaConnection:
-        return await connect_ollama()
+    async def connect_ollama_api(
+        custom_ollama_url: str | None = None,
+    ) -> OllamaConnection:
+        return await connect_ollama(custom_ollama_url)
 
     @app.post("/api/provider/connect_api_key")
     async def connect_api_key(payload: dict):
@@ -436,6 +458,36 @@ def model_from_ollama_tag(
     return None, None
 
 
+def custom_models() -> AvailableModels | None:
+    custom_model_ids = Config.shared().custom_models
+    if not custom_model_ids or len(custom_model_ids) == 0:
+        return None
+
+    models: List[ModelDetails] = []
+    for model_id in custom_model_ids:
+        try:
+            provider_id = model_id.split("::", 1)[0]
+            model_name = model_id.split("::", 1)[1]
+            models.append(
+                ModelDetails(
+                    id=model_id,
+                    name=f"{provider_name_from_id(provider_id)}: {model_name}",
+                    supports_structured_output=False,
+                    supports_data_gen=False,
+                    untested_model=True,
+                )
+            )
+        except Exception as e:
+            # Continue on to the rest
+            print(f"Error processing custom model {model_id}: {e}")
+
+    return AvailableModels(
+        provider_name="Custom Models",
+        provider_id=ModelProviderName.kiln_custom_registry,
+        models=models,
+    )
+
+
 def all_fine_tuned_models() -> AvailableModels | None:
     # Add any fine tuned models
     models: List[ModelDetails] = []

app/desktop/studio_server/repair_api.py

@@ -41,8 +41,13 @@ async def run_repair(
             evaluator_feedback=input.evaluator_feedback,
         )
 
-        model_name = input.model_name or run.output.source.properties.get("model_name")
-        provider = input.provider or run.output.source.properties.get("model_provider")
+        source_properties = (
+            run.output.source.properties
+            if run.output.source and run.output.source.properties
+            else {}
+        )
+        model_name = input.model_name or source_properties.get("model_name")
+        provider = input.provider or source_properties.get("model_provider")
         if (
             not model_name
             or not provider

app/desktop/studio_server/settings_api.py

@@ -1,15 +1,19 @@
+from typing import Any
+
 from fastapi import FastAPI
 from kiln_ai.utils.config import Config
 
 
 def connect_settings(app: FastAPI):
     @app.post("/api/settings")
-    def update_settings(new_settings: dict[str, int | float | str | bool | None]):
+    def update_settings(
+        new_settings: dict[str, int | float | str | bool | list | None],
+    ):
         Config.shared().update_settings(new_settings)
         return Config.shared().settings(hide_sensitive=True)
 
     @app.get("/api/settings")
-    def read_settings():
+    def read_settings() -> dict[str, Any]:
         settings = Config.shared().settings(hide_sensitive=True)
         return settings