feat: expose test command via api

.gitignore

@@ -18,3 +18,6 @@ devenv.local.nix
 
 # pre-commit
 .pre-commit-config.yaml
+
+# test
+unit-text.json

README.md

@@ -79,6 +79,34 @@ unit-text ideate
 unit-text test <path-to-the-draft.md>
 ```
 
+### API
+
+The package also provides a FastAPI server for programmatic access:
+
+```bash
+# Start the development server
+uv run fastapi dev ./src/unit_text/api
+
+# Start the production server
+uv run fastapi run ./src/unit_text/api
+
+# or for convenience
+uv run unit-text-api
+```
+
+The server exposes a `/test` endpoint that accepts POST requests with two files:
+
+- `file`: Your draft text file
+- `config`: Your idea configuration JSON file
+
+Example using curl:
+
+```bash
+curl -X POST http://localhost:8000/test \
+  -F "file=@draft.md" \
+  -F "config=@unit-text.json"
+```
+
 ## 📝 Process
 
 The ideation phase is where you define your blog idea. It looks something like this:

pyproject.toml

@@ -5,7 +5,17 @@ description = "Unit tests for plain text"
 readme = "README.md"
 license = "AGPL-3.0-or-later"
 license-files = ["LICENSE"]
-keywords = ["cli", "ollama", "llm", "language", "unit", "test", "blog", "editor", "ai"]
+keywords = [
+    "cli",
+    "ollama",
+    "llm",
+    "language",
+    "unit",
+    "test",
+    "blog",
+    "editor",
+    "ai",
+]
 classifiers = [
     "Development Status :: 4 - Beta",
     "Environment :: Console",
@@ -29,30 +39,33 @@ authors = [
 ]
 requires-python = ">=3.11"
 dependencies = [
-    "dicttoxml>=1.7.16",
     "ollama>=0.4.7",
     "pydantic>=2.10.6",
+    "dicttoxml>=1.7.16",
+
+    # CLI
     "typer>=0.15.1",
+    "rich",
+
+    # TODO should be optional?
+    # API
+    "fastapi[standard]>=0.115.11",
 ]
 
-# https://packaging.python.org/en/latest/specifications/well-known-project-urls/#well-known-labels
 [project.urls]
 source = "https://github.com/sealambda/unit-text"
 issues = "https://github.com/sealambda/unit-text/issues"
 
 [project.scripts]
 unit-text = "unit_text:app"
+unit-text-api = "unit_text.api:run"
 
 [build-system]
 requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [dependency-groups]
-dev = [
-    "commitizen>=4.1.1",
-    "pre-commit>=4.1.0",
-    "ruff>=0.9.4",
-]
+dev = ["commitizen>=4.1.1", "pre-commit>=4.1.0", "ruff>=0.9.4"]
 
 [tool.commitizen]
 name = "cz_conventional_commits"
@@ -65,16 +78,10 @@ major_version_zero = true
 
 [tool.ruff.lint]
 select = [
-    # pycodestyle
-    "E",
-    # Pyflakes
-    "F",
-    # pyupgrade
-    "UP",
-    # flake8-bugbear
-    "B",
-    # flake8-simplify
-    "SIM",
-    # isort
-    "I",
+    "E",   # pycodestyle
+    "F",   # Pyflakes
+    "UP",  # pyupgrade
+    "B",   # flake8-bugbear
+    "SIM", # flake8-simplify
+    "I",   # isort
 ]

src/unit_text/__init__.py

@@ -1 +1,11 @@
-from .cli import app as app
+"""Unit tests for plain text."""
+
+from unit_text.cli import app
+from unit_text.core import Evaluation, IdeaModel, run_tests
+
+__all__ = [
+    "Evaluation",
+    "IdeaModel",
+    "app",
+    "run_tests",
+]

src/unit_text/__main__.py

@@ -1,3 +1,6 @@
-from .cli import app
+"""Main entry point for unit-text."""
 
-app(prog_name="unit-text")
+from unit_text.cli.app import app
+
+if __name__ == "__main__":
+    app(prog_name="unit-text")

src/unit_text/api/__init__.py

@@ -0,0 +1,4 @@
+from .app import app
+from .server import run
+
+__all__ = ["app", "run"]

src/unit_text/api/__main__.py

@@ -0,0 +1,6 @@
+"""Main entry point for unit-text."""
+
+from .app import app
+
+if __name__ == "__main__":
+    app(prog_name="unit-text-api")

src/unit_text/api/app.py

@@ -0,0 +1,32 @@
+"""FastAPI application for the unit-text API."""
+
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+
+from unit_text.core import IdeaModel, TestResult, run_tests
+
+app = FastAPI()
+
+
+class TestRequest(BaseModel):
+    """Request model for the test endpoint."""
+
+    draft: str
+    idea: IdeaModel
+
+
+@app.get("/")
+async def root():
+    """Root endpoint returning a welcome message."""
+    return {"message": "Welcome to the unit-text API!"}
+
+
+@app.post("/test")
+async def test(request: TestRequest) -> TestResult:
+    """Run tests on the input draft against the idea configuration."""
+    print("Running tests...")
+
+    try:
+        return run_tests(request.draft, request.idea)
+    except Exception as e:
+        raise HTTPException(status_code=400, detail=str(e)) from e

src/unit_text/api/server.py

@@ -0,0 +1,8 @@
+import uvicorn
+
+from .app import app
+
+
+# This is just a convenience function to run the server from the command line
+def run():
+    uvicorn.run(app, host="0.0.0.0", port=8000)

src/unit_text/cli/__init__.py

@@ -0,0 +1,3 @@
+from .app import app
+
+__all__ = ["app"]

src/unit_text/cli.py → src/unit_text/cli/app.py

@@ -1,16 +1,14 @@
 from pathlib import Path
 from typing import Annotated
 
-import ollama
 import typer
-from dicttoxml import dicttoxml
 from rich import print
 from rich.console import Group
 from rich.markdown import Markdown
 from rich.panel import Panel
 from rich.prompt import Prompt
 
-from .models import Evaluation, IdeaModel, TestResult
+from unit_text.core import Evaluation, IdeaModel, run_tests
 
 app = typer.Typer(
     short_help="Unit tests for prose",
@@ -94,77 +92,11 @@ def ideate(config: OptConfig = default_config):
 
 @app.command()
 def test(file: Path, config: OptConfig = default_config):
-    """Test the input file."""
+    """Run tests on the input file against the config."""
     print("Running tests...")
 
     idea = IdeaModel.model_validate_json(config.read_text())
-
-    xml_idea = dicttoxml(idea.model_dump(), attr_type=False, custom_root="idea")
-
-    body = {"draft": file.read_text()}
-    xml_body = dicttoxml(body, attr_type=False, root=False)
-
-    prompt = f"""
-    {xml_idea}
-
-    {xml_body}
-    """
-
-    response = ollama.chat(
-        model="deepseek-r1:7b",
-        messages=[
-            {
-                "role": "system",
-                "content": """
-You are an experienced technical writer and editor
-with expertise in developer-focused content.
-Your role is to provide detailed, actionable feedback on blog posts,
-focusing on both technical accuracy and engaging writing style.
-
-When reviewing a blog post, analyze it against the following criteria:
-
-1. Clarity:
-   - Is the main message clear and well-articulated?
-   - Are technical concepts explained appropriately for the target audience?
-   - Is the writing style engaging and accessible?
-   - Are there any confusing or ambiguous sections?
-
-2. Alignment with Objectives:
-   - Does the content match the stated goals and target audience?
-   - Is the technical depth appropriate for the intended readers?
-   - Are the examples and analogies relevant and helpful?
-   - Does the post deliver on its promises?
-
-3. Completeness:
-   - Are all key points fully developed?
-   - Is there a clear introduction and conclusion?
-   - Are code examples (if any) complete and well-explained?
-   - Are there any missing or unnecessary sections?
-
-4. Overall Suggestions:
-   - Specific improvements for structure and flow
-   - Recommendations for enhancing engagement
-   - Suggestions for technical accuracy or depth
-   - Ideas for better examples or analogies
-
-For each evaluation, return a `test_passed` boolean
-to indicate if the content was good enough for that specific aspect.
-
-Keep your feedback constructive but honest.
-Focus on specific, actionable improvements rather than general observations.
-Reference specific parts of the text when making suggestions.
-""",
-            },
-            {"role": "user", "content": prompt},
-        ],
-        format=TestResult.model_json_schema(),
-        options=ollama.Options(
-            temperature=0,  # to ensure consistent results
-            num_ctx=8192,  # to ensure the entire text is processed
-        ),
-    )
-
-    out = TestResult.model_validate_json(response.message.content)
+    out = run_tests(file.read_text(), idea)
 
     def evaluation_panel(evaluation: Evaluation, title: str) -> Panel:
         return Panel(

src/unit_text/core/__init__.py

@@ -0,0 +1,9 @@
+from .lib import run_tests
+from .models import Evaluation, IdeaModel, TestResult
+
+__all__ = [
+    "Evaluation",
+    "TestResult",
+    "run_tests",
+    "IdeaModel",
+]

src/unit_text/core/lib.py

@@ -0,0 +1,74 @@
+import ollama
+from dicttoxml import dicttoxml
+
+from .models import IdeaModel, TestResult
+
+
+def run_tests(draft: str, idea: IdeaModel) -> TestResult:
+    """Run tests on the draft content against the idea."""
+    xml_idea = dicttoxml(idea.model_dump(), attr_type=False, custom_root="idea")
+
+    body = {"draft": draft}
+    xml_body = dicttoxml(body, attr_type=False, root=False)
+
+    prompt = f"""
+    {xml_idea}
+
+    {xml_body}
+    """
+
+    response = ollama.chat(
+        model="deepseek-r1:7b",
+        messages=[
+            {
+                "role": "system",
+                "content": """
+You are an experienced technical writer and editor
+with expertise in developer-focused content.
+Your role is to provide detailed, actionable feedback on blog posts,
+focusing on both technical accuracy and engaging writing style.
+
+When reviewing a blog post, analyze it against the following criteria:
+
+1. Clarity:
+   - Is the main message clear and well-articulated?
+   - Are technical concepts explained appropriately for the target audience?
+   - Is the writing style engaging and accessible?
+   - Are there any confusing or ambiguous sections?
+
+2. Alignment with Objectives:
+   - Does the content match the stated goals and target audience?
+   - Is the technical depth appropriate for the intended readers?
+   - Are the examples and analogies relevant and helpful?
+   - Does the post deliver on its promises?
+
+3. Completeness:
+   - Are all key points fully developed?
+   - Is there a clear introduction and conclusion?
+   - Are code examples (if any) complete and well-explained?
+   - Are there any missing or unnecessary sections?
+
+4. Overall Suggestions:
+   - Specific improvements for structure and flow
+   - Recommendations for enhancing engagement
+   - Suggestions for technical accuracy or depth
+   - Ideas for better examples or analogies
+
+For each evaluation, return a `test_passed` boolean
+to indicate if the content was good enough for that specific aspect.
+
+Keep your feedback constructive but honest.
+Focus on specific, actionable improvements rather than general observations.
+Reference specific parts of the text when making suggestions.
+""",
+            },
+            {"role": "user", "content": prompt},
+        ],
+        format=TestResult.model_json_schema(),
+        options=ollama.Options(
+            temperature=0,  # to ensure consistent results
+            num_ctx=8192,  # to ensure the entire text is processed
+        ),
+    )
+
+    return TestResult.model_validate_json(response.message.content)