Merge remote-tracking branch 'origin/main' into fix/398-select-width

The concept's phone cap (120px) cut Existing tags ("Replace after review").
#tag-existing now never shrinks for its row text and keeps its natural width
at phone width, beside the text. The comparison expects selectsFit for every
select, and a new test walks every option of both selects at 390 and 320 px
in both themes. TESTING.md D132 records the decision.

TESTING.md

@@ -3200,12 +3200,16 @@ the per-section hand-off panel, was retired by S12 (#329): every section is nati
   again"; an Unload that found nothing loaded only reads the status again. At phone width
   the concept's 120px select cap cuts every engine label, so `#tag-model` alone keeps its
   natural width there and its row wraps the select under the text (`workspace.css`
-  `/* D132 */`); Existing tags stays as the concept draws it, cut at 390 as there. The
-  comparison maps `selectsFit` only for the engine select and measures each row's
-  `flexWrap` and whether its control sits under the text. Pinned by `auto-tagging matches
-  the concept` (both themes and sizes), `auto-tagging at 390 wraps only the engine row`,
-  `auto-tagging engine select fits at 320 wide` and the mutation check (it includes a
-  wrapped row) (system-tagging-concept.spec), and the model, Download, Unload and Preview
+  `/* D132 */`). The concept's cap cuts Existing tags too ("Replace after review"); by the
+  maintainer's decision (#398) that parity is not kept: `#tag-existing` never shrinks for
+  its row text and at phone width keeps its natural width beside the text (its row does
+  not wrap; the text column narrows). 1600 is as the concept draws it. The comparison
+  expects `selectsFit` true for every select and measures each row's `flexWrap` and
+  whether its control sits under the text. Pinned by `auto-tagging matches the concept`
+  (both themes and sizes), `auto-tagging at 390 wraps only the engine row`, `auto-tagging
+  selects fit every option at 390/320 wide` (every option of both selects, both themes, no
+  page scroll) and the mutation check (a wrapped row, a squeezed engine and Existing tags
+  select) (system-tagging-concept.spec), and the model, Download, Unload and Preview
   tests of workspace-system-tagging.spec.
 - **D133** (Auto-tagging, S11): a "Suggestions per image" row (`#tag-suggestions`,
   number 1–100, host key `autotag_suggestion_limit`) follows the two confidence rows:

py/api/__init__.py

@@ -1107,196 +1107,3 @@ class PromptManagerAPI(
                         result["parameters"][field] = metadata[field]
 
         return result
-
-    def _extract_readable_prompt(self, parsed_data):
-        """Extract human-readable prompt text from ComfyUI/A1111 data."""
-
-        def safe_to_string(value):
-            if isinstance(value, str):
-                return value
-            elif isinstance(value, list):
-                return " ".join(str(item) for item in value if item)
-            elif value is not None:
-                return str(value)
-            return None
-
-        # First check if we already extracted a positive prompt (A1111 format)
-        if parsed_data.get("positive_prompt"):
-            return parsed_data["positive_prompt"]
-
-        # Check if prompt is already a string
-        if isinstance(parsed_data.get("prompt"), str):
-            return parsed_data["prompt"]
-
-        # Check if prompt is a simple value that can be converted
-        if parsed_data.get("prompt") and not isinstance(
-            parsed_data.get("prompt"), dict
-        ):
-            return safe_to_string(parsed_data["prompt"])
-
-        prompt_data = parsed_data.get("prompt")
-        if isinstance(prompt_data, dict):
-            # Use the enhanced logic from parse-metadata.py
-            positive_prompt = self._extract_positive_prompt_from_comfyui_data(
-                prompt_data
-            )
-            if positive_prompt:
-                return positive_prompt
-
-        # Check workflow data if available
-        workflow_data = parsed_data.get("workflow")
-        if isinstance(workflow_data, dict):
-            positive_prompt = self._extract_positive_prompt_from_comfyui_data(
-                workflow_data
-            )
-            if positive_prompt:
-                return positive_prompt
-
-        # Check parameters for positive prompt
-        if parsed_data.get("parameters", {}).get("positive"):
-            return safe_to_string(parsed_data["parameters"]["positive"])
-
-        return None
-
-    def _get_node_inputs(self, node):
-        """Safely get inputs from a node, handling both dict and list formats.
-
-        Old format: inputs is a dict with direct key-value pairs
-            inputs = {"text": "my prompt", "seed": 123}
-
-        New format: inputs is a list of connection objects
-            inputs = [
-                {"name": "text", "type": "STRING", "link": null,
-                 "widget": {"name": "text"}},
-                {"name": "clip", "type": "CLIP", "link": 11}
-            ]
-        """
-        if not isinstance(node, dict):
-            return {}
-
-        inputs = node.get("inputs", {})
-
-        # If inputs is already a dict, return it
-        if isinstance(inputs, dict):
-            return inputs
-
-        # If inputs is a list, convert to dict format
-        if isinstance(inputs, list):
-            inputs_dict = {}
-            for input_item in inputs:
-                if isinstance(input_item, dict) and "name" in input_item:
-                    name = input_item["name"]
-                    inputs_dict[name] = input_item
-            return inputs_dict
-
-        return {}
-
-    def _find_text_in_node(self, node):
-        """Try to find text content in a node using various strategies.
-
-        Handles both old and new workflow formats.
-        """
-        if not isinstance(node, dict):
-            return None
-
-        # Strategy 1: Check normalized inputs for 'text' field
-        inputs = self._get_node_inputs(node)
-        if "text" in inputs and isinstance(inputs["text"], str):
-            return inputs["text"]
-
-        # Strategy 2: For text encoder nodes, check widgets_values
-        class_type = node.get("class_type", node.get("type", ""))
-        text_encoder_types = [
-            "CLIPTextEncode",
-            "CLIPTextEncodeSDXL",
-            "CLIPTextEncodeSDXLRefiner",
-            "CLIPTextEncodeFlux",
-            "PromptManager",
-            "PromptManagerText",
-            "BNK_CLIPTextEncoder",
-            "Text Encoder",
-            "CLIP Text Encode",
-        ]
-
-        if any(
-            encoder_type.lower() in class_type.lower()
-            for encoder_type in text_encoder_types
-        ):
-            widgets_values = node.get("widgets_values", [])
-            if widgets_values and len(widgets_values) > 0:
-                if isinstance(widgets_values[0], str) and widgets_values[0].strip():
-                    return widgets_values[0]
-
-        return None
-
-    def _extract_positive_prompt_from_comfyui_data(self, data):
-        """Extract positive prompt from ComfyUI data.
-
-        Handles both old and new formats.
-        """
-        if not isinstance(data, dict):
-            return None
-
-        # Build nodes dictionary
-        nodes_by_id = {}
-        if "nodes" in data:
-            # Handle nodes array format
-            for node in data["nodes"]:
-                if isinstance(node, dict):
-                    nid = node.get("id")
-                    if nid is not None:
-                        nodes_by_id[nid] = node
-        else:
-            # Handle flat dictionary format (node_id -> node_data)
-            for nid_str, node in data.items():
-                try:
-                    nid = int(nid_str)
-                except (ValueError, TypeError):
-                    nid = nid_str
-                if isinstance(node, dict):
-                    if "id" in node:
-                        nid = node["id"]
-                    nodes_by_id[nid] = node
-
-        if not nodes_by_id:
-            return None
-
-        # First, try to find positive/negative connection pattern
-        pos_id = None
-        for node in nodes_by_id.values():
-            if isinstance(node, dict):
-                inputs = self._get_node_inputs(node)
-                if "positive" in inputs and "negative" in inputs:
-                    try:
-                        pos_input = inputs["positive"]
-                        if isinstance(pos_input, list) and len(pos_input) > 0:
-                            pos_id = int(pos_input[0])
-                            break
-                    except (ValueError, TypeError, IndexError):
-                        continue
-
-        # Get text from the positive node
-        if pos_id is not None and pos_id in nodes_by_id:
-            text_val = self._find_text_in_node(nodes_by_id[pos_id])
-            if text_val:
-                return text_val
-
-        # Fallback: find any text encoder node with text content
-        text_nodes = []
-        for node in nodes_by_id.values():
-            if isinstance(node, dict):
-                text_val = self._find_text_in_node(node)
-                if text_val:
-                    # Try to determine if this is positive or negative
-                    node_title = node.get("title", "").lower()
-                    if "neg" not in node_title and "negative" not in node_title:
-                        # Prioritize non-negative prompts
-                        text_nodes.insert(0, text_val)
-                    else:
-                        text_nodes.append(text_val)
-
-        # Return the first positive-looking prompt
-        if text_nodes:
-            return text_nodes[0]
-
-        return None

py/api/admin.py

@@ -47,7 +47,7 @@ try:
         extract_generation_params,
         parse_page_json,
     )
-    from ...utils.prompt_pair_resolver import resolve_prompt_pair
+    from ...utils.prompt_pair_resolver import resolve_prompt_pair, sampler_less_prompt
     from ...utils.review_capture import reviewable
 except ImportError:
     from database.pair_ingestion import blank_positive, ingest_resolved_pair
@@ -62,7 +62,7 @@ except ImportError:
         extract_generation_params,
         parse_page_json,
     )
-    from utils.prompt_pair_resolver import resolve_prompt_pair
+    from utils.prompt_pair_resolver import resolve_prompt_pair, sampler_less_prompt
     from utils.review_capture import reviewable
 
 
@@ -1754,13 +1754,24 @@ class AdminRoutesMixin:
             canonical.get("parameters"), str
         ):
             return resolution["state"]
+        elif canonical.get("prompt"):
+            # No node takes a positive or negative input (a guider or wrapper
+            # graph): the one wired text, never a guess (#252).
+            found = sampler_less_prompt(canonical["prompt"])
+            prompt_text = found["text"]
+            if prompt_text is None and isinstance(canonical.get("parameters"), str):
+                # A metadata saver also wrote A1111 text: its positive prompt.
+                parsed = self._parse_comfyui_prompt(metadata)["positive_prompt"]
+                prompt_text = parsed.strip() if parsed and parsed.strip() else None
+            if prompt_text is None:
+                linked = self._link_recorded_run(
+                    media_file, canonical, detailed, history
+                )
+                if linked is not None:
+                    return linked
+                return "unresolved" if found["state"] == "ambiguous" else "found"
         else:
-            parsed = self._parse_comfyui_prompt(metadata)
-            if not (parsed.get("prompt") or parsed.get("parameters")):
-                return None
-            prompt_text = self._extract_readable_prompt(parsed)
-            if prompt_text is not None and not isinstance(prompt_text, str):
-                prompt_text = str(prompt_text)
+            prompt_text = self._parse_comfyui_prompt(metadata)["positive_prompt"]
             if not (prompt_text and prompt_text.strip()):
                 return "found"
             prompt_text = prompt_text.strip()

tests/browser/system-tagging-concept.spec.mjs

@@ -127,9 +127,9 @@ function mapTaggingConcept(reference, { template, phone }) {
         actions: { ...reference.actions, buttons: [preview, ['Download again', ''], ['Unload', '']] },
         // D134: the prompt-tag batch, reviewed first.
         operations: [{ tree: ['div', 'div.row-actions'], title: 'Tag output images', description: BATCH, actions: [['Review', '']] }],
-        // D132: the engine select shows its whole chosen option at every width (at 390 the concept's 120px cap cuts it;
-        // `#tag-model` alone may grow there). Existing tags keeps the concept's own fit, cut or not.
-        selectsFit: reference.selectsFit.map((fit, index) => (index === 0 ? true : fit)),
+        // D132 (#398): every select shows its whole chosen option at every width (at 390 the concept's 120px cap cuts
+        // them; production lets each grow past it).
+        selectsFit: reference.selectsFit.map(() => true),
     };
 }
 
@@ -168,16 +168,28 @@ for (const theme of THEMES) for (const [width, height] of SIZES) {
     });
 }
 
-// D132 below the concept's smallest size: on a 320px phone the engine select still shows its whole option.
-for (const theme of THEMES) test(`auto-tagging engine select fits at 320 wide ${theme}`, async ({ page }) => {
-    await page.setViewportSize({ width: 320, height: 700 });
-    const production = await productionTagging(page, theme);
-    for (const model of ['hf', 'gguf', 'wd14-swinv2']) {
-        await page.locator('#workspace-main #tag-model').selectOption(model);
-        expect((await page.evaluate(measureTagging, '#workspace-main')).selectsFit[0], model).toBe(true);
-    }
-    expect(production.pageScroll).toBe(false);
-});
+// D132 (#398) at phone width and below the concept's smallest size: every option of every select, once chosen, shows
+// whole, with no page scroll.
+for (const theme of THEMES) for (const width of [390, 320]) {
+    test(`auto-tagging selects fit every option at ${width} wide ${theme}`, async ({ page }, testInfo) => {
+        await page.setViewportSize({ width, height: 844 });
+        await productionTagging(page, theme);
+        await page.locator('#workspace-main #tag-existing').selectOption('replace_after_review');
+        await page.locator('#workspace-main section.surface').screenshot({ path: testInfo.outputPath(`production-tagging-selects-${theme}-${width}.png`) });
+        const selects = page.locator('#workspace-main section.surface > .setting-row > select');
+        await expect(selects).toHaveCount(2);
+        for (let index = 0; index < 2; index += 1) {
+            const select = selects.nth(index);
+            const values = await select.evaluate(node => [...node.options].map(option => option.value));
+            for (const value of values) {
+                await select.selectOption(value);
+                const measured = await page.evaluate(measureTagging, '#workspace-main');
+                expect(measured.selectsFit, `${await select.getAttribute('id')}=${value}`).toEqual([true, true]);
+                expect(measured.pageScroll, value).toBe(false);
+            }
+        }
+    });
+}
 
 test('auto-tagging comparison detects mutations', async ({ page, request }) => {
     await page.setViewportSize({ width: 1600, height: 1100 });
@@ -222,6 +234,9 @@ test('auto-tagging comparison detects mutations', async ({ page, request }) => {
     const undoSqueeze = await mutate(page, { css: '#workspace-main #tag-model { max-width: 60px !important; min-width: 0 !important; }' });
     expect(await paths()).toEqual(expect.arrayContaining(['selectsFit.0']));
     await undoSqueeze();
+    const undoSqueezeExisting = await mutate(page, { css: '#workspace-main #tag-existing { max-width: 60px !important; min-width: 0 !important; }' });
+    expect(await paths()).toEqual(expect.arrayContaining(['selectsFit.1']));
+    await undoSqueezeExisting();
     // A row that wraps where the concept's does not.
     const undoWrap = await mutate(page, { css: '#workspace-main .setting-row:has(> #tag-existing) { flex-wrap: wrap; }' });
     expect(await paths()).toEqual(['rows.1.flexWrap']);
@@ -233,14 +248,14 @@ test('auto-tagging comparison detects mutations', async ({ page, request }) => {
     expect(diffInventory(expected, await measure())).toEqual([]);
 });
 
-// D132 at phone width, unmapped: only the engine row wraps; Existing tags keeps the concept's cut select.
+// D132 at phone width: only the engine row wraps; Existing tags grows beside its text instead (#398).
 test('auto-tagging at 390 wraps only the engine row', async ({ page, request }) => {
     await page.setViewportSize({ width: 390, height: 844 });
     const concept = await conceptTagging(page, 'dark');
     const production = await productionTagging(page, 'dark');
     expect(diffInventory(mapTaggingConcept(concept, await savedTemplate(request, page)), production)).toEqual([]);
     expect(production.rows.map(row => row.flexWrap)).toEqual(['wrap', 'nowrap', 'nowrap', 'nowrap', 'nowrap']);
-    expect(production.selectsFit[1]).toBe(concept.selectsFit[1]);
+    expect(production.selectsFit).toEqual([true, true]);
 });
 
 /** Runs in the page: the open review dialog: its title, body and the concept's tokens. */

tests/test_api_admin.py

@@ -846,6 +846,14 @@ class TestSettingsReadMonitorThroughModule(AdminAPITestCase):
         self.assertEqual(data["settings"]["gallery_root_paths"], ["output"])
 
 
+def _wired_prompt(text):
+    """A sampler-less graph whose one encoder feeds a guider (#252)."""
+    return {
+        "1": {"class_type": "CLIPTextEncode", "inputs": {"text": text}},
+        "2": {"class_type": "BasicGuider", "inputs": {"conditioning": ["1", 0]}},
+    }
+
+
 def _raise(*args, **kwargs):
     raise RuntimeError("boom")
 
@@ -2186,11 +2194,7 @@ class TestOutputScanInternals(AdminAPITestCase):
 
     def test_ingest_outcomes(self):
         f = Path("gen.png")
-        meta = {
-            "prompt": json.dumps(
-                {"1": {"class_type": "CLIPTextEncode", "inputs": {"text": "a cat"}}}
-            )
-        }
+        meta = {"prompt": json.dumps(_wired_prompt("a cat"))}
         self.assertIsNone(self.api._ingest_scanned_file(f, {}))
         self.assertIsNone(self.api._ingest_scanned_file(f, {"prompt": "{}"}))
         self.assertEqual(
@@ -2202,31 +2206,19 @@ class TestOutputScanInternals(AdminAPITestCase):
 
     def test_ingest_link_failures_are_tolerated(self):
         f = Path("gen.png")
-        meta = {
-            "prompt": json.dumps(
-                {"1": {"class_type": "CLIPTextEncode", "inputs": {"text": "a dog"}}}
-            )
-        }
+        meta = {"prompt": json.dumps(_wired_prompt("a dog"))}
         self.api.db.link_image_to_prompt = _raise
         self.assertEqual(self.api._ingest_scanned_file(f, meta), "added")
         self.assertEqual(self.api._ingest_scanned_file(f, meta), "found")
 
     def test_ingest_save_failure_counts_as_found(self):
         f = Path("gen.png")
-        meta = {
-            "prompt": json.dumps(
-                {"1": {"class_type": "CLIPTextEncode", "inputs": {"text": "a bird"}}}
-            )
-        }
+        meta = {"prompt": json.dumps(_wired_prompt("a bird"))}
         self.api.db.save_prompt = lambda *a, **k: None
         self.assertEqual(self.api._ingest_scanned_file(f, meta), "found")
 
     def test_batch_counts_and_per_file_errors(self):
-        meta = {
-            "prompt": json.dumps(
-                {"1": {"class_type": "CLIPTextEncode", "inputs": {"text": "a fish"}}}
-            )
-        }
+        meta = {"prompt": json.dumps(_wired_prompt("a fish"))}
         self.api.db.get_prompt_by_hash = _raise
         counts = self.api._ingest_scan_batch_sync(
             [(Path("a.png"), meta), (Path("b.png"), {})]
@@ -2915,7 +2907,7 @@ class TestScanReadsVideos(AdminAPITestCase):
         shutil.which("ffmpeg") and shutil.which("ffprobe"), "ffmpeg not installed"
     )
     async def test_scan_adds_prompts_found_in_videos(self):
-        graph = {"1": {"class_type": "CLIPTextEncode", "inputs": {"text": "a cat"}}}
+        graph = _wired_prompt("a cat")
         _write_mp4(
             self.output_dir / "clip.mp4", json.dumps({"prompt": json.dumps(graph)})
         )

tests/test_api_core.py

@@ -835,7 +835,6 @@ class TestMetadataParsing(unittest.TestCase):
         self.assertEqual(parsed["positive_prompt"], "a cat")
         self.assertEqual(parsed["negative_prompt"], "dog")
         self.assertEqual(parsed["parameters"]["parameters"], meta["parameters"])
-        self.assertEqual(self.api._extract_readable_prompt(parsed), "a cat")
 
     def test_parse_comfyui_fields(self):
         meta = {
@@ -856,97 +855,6 @@ class TestMetadataParsing(unittest.TestCase):
         self.assertEqual(parsed["prompt"], "plain text")
         self.assertEqual(parsed["workflow"], {"nodes": []})
 
-    def test_extract_readable_prompt_variants(self):
-        extract = self.api._extract_readable_prompt
-        self.assertEqual(extract({"prompt": "plain"}), "plain")
-        self.assertEqual(extract({"prompt": ["a", "", "b"]}), "a b")
-        self.assertEqual(extract({"prompt": 42}), "42")
-        self.assertEqual(
-            extract({"prompt": None, "parameters": {"positive": ["x", "y"]}}), "x y"
-        )
-        self.assertIsNone(extract({"prompt": {}, "parameters": {}}))
-
-        graph = {
-            "1": {"class_type": "CLIPTextEncode", "inputs": {"text": "pos"}},
-            "2": {"class_type": "CLIPTextEncode", "inputs": {"text": "neg"}},
-            "3": {
-                "class_type": "KSampler",
-                "inputs": {"positive": ["1", 0], "negative": ["2", 0]},
-            },
-        }
-        self.assertEqual(extract({"prompt": graph}), "pos")
-        self.assertEqual(extract({"prompt": {"x": 1}, "workflow": graph}), "pos")
-
-    def test_node_inputs_and_text_lookup(self):
-        self.assertEqual(self.api._get_node_inputs("nope"), {})
-        self.assertEqual(self.api._get_node_inputs({"inputs": 5}), {})
-        self.assertEqual(self.api._get_node_inputs({"inputs": {"a": 1}}), {"a": 1})
-        listed = self.api._get_node_inputs(
-            {"inputs": [{"name": "text", "link": None}, {"nope": 1}, "junk"]}
-        )
-        self.assertEqual(list(listed), ["text"])
-
-        self.assertIsNone(self.api._find_text_in_node(None))
-        self.assertEqual(self.api._find_text_in_node({"inputs": {"text": "hi"}}), "hi")
-        self.assertEqual(
-            self.api._find_text_in_node(
-                {"type": "CLIPTextEncode", "widgets_values": ["w"]}
-            ),
-            "w",
-        )
-        self.assertIsNone(
-            self.api._find_text_in_node(
-                {"type": "CLIPTextEncode", "widgets_values": [" "]}
-            )
-        )
-        self.assertIsNone(self.api._find_text_in_node({"type": "KSampler"}))
-
-    def test_positive_prompt_from_nodes_array_and_fallbacks(self):
-        extract = self.api._extract_positive_prompt_from_comfyui_data
-        self.assertIsNone(extract("x"))
-        self.assertIsNone(extract({}))
-        self.assertIsNone(extract({"nodes": []}))
-
-        workflow = {
-            "nodes": [
-                {"id": 1, "type": "CLIPTextEncode", "widgets_values": ["pos"]},
-                {
-                    "id": 2,
-                    "type": "CLIPTextEncode",
-                    "widgets_values": ["neg"],
-                    "title": "Negative",
-                },
-                {"id": 3, "type": "KSampler", "inputs": [{"name": "seed", "link": 4}]},
-                "junk",
-            ]
-        }
-        self.assertEqual(extract(workflow), "pos")
-
-        only_negative = {
-            "nodes": [
-                {
-                    "id": 2,
-                    "type": "CLIPTextEncode",
-                    "widgets_values": ["neg"],
-                    "title": "neg",
-                },
-            ]
-        }
-        self.assertEqual(extract(only_negative), "neg")
-
-        bad_link = {
-            "1": {"class_type": "CLIPTextEncode", "inputs": {"text": "pos"}},
-            "3": {
-                "class_type": "KSampler",
-                "inputs": {"positive": "oops", "negative": []},
-            },
-            "4": {
-                "class_type": "KSampler",
-                "inputs": {"positive": ["zz", 0], "negative": []},
-            },
-        }
-        self.assertEqual(extract(bad_link), "pos")
-
 
 if __name__ == "__main__":
     unittest.main()

tests/test_pair_scan.py

@@ -115,7 +115,12 @@ class TestPairScan(AdminAPITestCase):
         self.assertEqual(second["pairs_added"], 0)
 
     def test_legacy_single_prompt_second_pass_not_reported_as_new_link(self):
-        meta = {"prompt": json.dumps({"1": graph()["1"]})}
+        # A sampler-less graph: one encoder wired into a guider (#252).
+        single = {
+            "1": graph()["1"],
+            "2": {"class_type": "BasicGuider", "inputs": {"conditioning": ["1", 0]}},
+        }
+        meta = {"prompt": json.dumps(single)}
         path = self.output_dir / "old.png"
         self.assertEqual(self.api._ingest_scanned_file(path, meta), "added")
         self.assertEqual(self.api._ingest_scanned_file(path, meta), "unchanged")
@@ -292,3 +297,155 @@ class TestPairScan(AdminAPITestCase):
             self.api.db.get_image_prompt_info(str(path))["workflow_data"], workflow
         )
         self.assertEqual(self.api._ingest_scanned_file(path, metadata), "unchanged")
+
+
+def flux_graph(text="a red fox", encoder="CLIPTextEncode"):
+    """A sampler-less Flux graph: the prompt reaches a guider's conditioning (#252)."""
+    return {
+        "1": {"class_type": "UNETLoader", "inputs": {"unet_name": "flux.safetensors"}},
+        "2": {"class_type": "DualCLIPLoader", "inputs": {"clip_name1": "t5"}},
+        "6": {"class_type": encoder, "inputs": {"text": text, "clip": ["2", 0]}},
+        "22": {
+            "class_type": "BasicGuider",
+            "inputs": {"model": ["1", 0], "conditioning": ["6", 0]},
+        },
+        "13": {
+            "class_type": "SamplerCustomAdvanced",
+            "inputs": {"guider": ["22", 0], "sigmas": ["17", 0]},
+        },
+        "17": {"class_type": "BasicScheduler", "inputs": {"steps": 20}},
+        "9": {"class_type": "SaveImage", "inputs": {"images": ["13", 0]}},
+    }
+
+
+class TestSamplerLessScan(AdminAPITestCase):
+    """Graphs where no node takes a positive or negative input (#252)."""
+
+    def _scanned(self, name, prompt_graph, workflow=None):
+        meta = {"prompt": json.dumps(prompt_graph)}
+        if workflow is not None:
+            meta["workflow"] = json.dumps(workflow)
+        return self.api._ingest_scanned_file(self.output_dir / name, meta)
+
+    def _texts(self):
+        return [p["text"] for p in self.api.db.get_recent_prompts()["prompts"]]
+
+    def test_the_one_wired_prompt_is_linked(self):
+        self.assertEqual(self._scanned("flux.png", flux_graph()), "added")
+        self.assertEqual(self._texts(), ["a red fox"])
+
+    def test_a_text_node_feeding_the_encoder_is_one_prompt(self):
+        g = flux_graph(text=["30", 0])
+        g["30"] = {"class_type": "TextInput", "inputs": {"text": "a red fox"}}
+        self.assertEqual(self._scanned("textinput.png", g), "added")
+        self.assertEqual(self._texts(), ["a red fox"])
+
+    def test_a_display_node_that_feeds_nothing_is_never_the_prompt(self):
+        # A real scan stored a "=== GIT CLONE REPORT ===" display text this way.
+        g = flux_graph()
+        g["40"] = {
+            "class_type": "easy showAnything",
+            "inputs": {"text": "=== GIT CLONE REPORT ===\nTotal repositories: 1"},
+        }
+        self.assertEqual(self._scanned("report.png", g), "added")
+        self.assertEqual(self._texts(), ["a red fox"])
+
+    def test_only_unconsumed_texts_store_nothing(self):
+        g = {
+            "40": {"class_type": "easy showAnything", "inputs": {"text": "report"}},
+            "41": {"class_type": "Textbox", "inputs": {"text": "install note"}},
+        }
+        self.assertEqual(self._scanned("notes.png", g), "found")
+        self.assertEqual(self._texts(), [])
+
+    def test_two_wired_texts_are_ambiguous_and_stay_unlinked(self):
+        # A LoRA loader's text input is wired too: the scan stored "<lora:...>".
+        g = flux_graph()
+        g["50"] = {
+            "class_type": "Lora Loader (LoraManager)",
+            "inputs": {
+                "model": ["1", 0],
+                "clip": ["2", 0],
+                "text": "<lora:style:1.00>",
+            },
+        }
+        g["22"]["inputs"]["model"] = ["50", 0]
+        g["6"]["inputs"]["clip"] = ["50", 1]
+        self.assertEqual(self._scanned("lora.png", g), "unresolved")
+        self.assertEqual(self._texts(), [])
+
+    def test_an_untraceable_wired_text_makes_the_graph_ambiguous(self):
+        # The encoder's text comes from a node no rule reads: never guess the other.
+        g = flux_graph(text=["60", 0])
+        g["60"] = {"class_type": "SomeLLMNode", "inputs": {"seed": 1}}
+        g["50"] = {
+            "class_type": "Lora Loader (LoraManager)",
+            "inputs": {"model": ["1", 0], "text": "<lora:style:1.00>"},
+        }
+        g["22"]["inputs"]["model"] = ["50", 0]
+        self.assertEqual(self._scanned("llm.png", g), "unresolved")
+        self.assertEqual(self._texts(), [])
+
+    def test_this_repositorys_prompt_node_is_authoritative(self):
+        g = flux_graph(text="a red fox", encoder="PromptManager")
+        g["50"] = {
+            "class_type": "Lora Loader (LoraManager)",
+            "inputs": {"model": ["1", 0], "text": "<lora:style:1.00>"},
+        }
+        g["22"]["inputs"]["model"] = ["50", 0]
+        self.assertEqual(self._scanned("own.png", g), "added")
+        self.assertEqual(self._texts(), ["a red fox"])
+
+    def test_a_numeric_text_is_never_stored_as_a_prompt(self):
+        self.assertEqual(self._scanned("number.png", flux_graph(text="2048")), "found")
+        self.assertEqual(self._texts(), [])
+
+    def test_workflow_widget_values_are_never_read(self):
+        # The API text is linked from a node no rule reads; the UI workflow
+        # still holds a stale widget value, which the old scan stored.
+        g = flux_graph(text=["70", 0])
+        g["70"] = {"class_type": "PromptBuilder", "inputs": {"prompt": "x", "n": 2}}
+        workflow = {
+            "nodes": [
+                {"id": 6, "type": "CLIPTextEncode", "widgets_values": ["stale text"]}
+            ]
+        }
+        self.assertEqual(self._scanned("stale.png", g, workflow), "unresolved")
+        self.assertEqual(self._texts(), [])
+
+    def test_a_lora_loaders_trigger_word_output_is_not_its_text(self):
+        # The encoder reads the loader's trigger-word output (slot 2), not its
+        # text input: the prompt is unknown, never the "<lora:...>" syntax.
+        g = flux_graph(text=["50", 2])
+        g["50"] = {
+            "class_type": "Lora Loader (LoraManager)",
+            "inputs": {"model": ["1", 0], "text": "<lora:style:1.00>"},
+        }
+        g["22"]["inputs"]["model"] = ["50", 0]
+        self.assertEqual(self._scanned("trigger.png", g), "unresolved")
+        self.assertEqual(self._texts(), [])
+
+    def test_a_seeded_text_node_holds_a_template_not_the_prompt(self):
+        g = flux_graph(text=["80", 0])
+        g["80"] = {
+            "class_type": "RandomPrompt",
+            "inputs": {"text": "a {red|blue} fox", "seed": 5},
+        }
+        self.assertEqual(self._scanned("random.png", g), "unresolved")
+        self.assertEqual(self._texts(), [])
+
+    def test_a1111_parameters_beside_an_undecided_graph_are_read(self):
+        # Metadata savers write both; the old scan read the A1111 positive.
+        g = flux_graph()
+        g["50"] = {
+            "class_type": "Lora Loader (LoraManager)",
+            "inputs": {"model": ["1", 0], "text": "<lora:style:1.00>"},
+        }
+        g["22"]["inputs"]["model"] = ["50", 0]
+        meta = {
+            "prompt": json.dumps(g),
+            "parameters": "a red fox\nNegative prompt: blur\nSteps: 20",
+        }
+        path = self.output_dir / "saver.png"
+        self.assertEqual(self.api._ingest_scanned_file(path, meta), "added")
+        self.assertEqual(self._texts(), ["a red fox"])

tests/test_sampler_less_prompt.py

@@ -0,0 +1,112 @@
+"""``sampler_less_prompt``: the one wired text of a graph with no sampler (#252)."""
+
+import time
+import unittest
+
+from utils.prompt_pair_resolver import sampler_less_prompt
+
+
+def _guided(**nodes):
+    """``nodes`` plus a guider consuming node ``"1"``."""
+    graph = {"9": {"class_type": "BasicGuider", "inputs": {"conditioning": ["1", 0]}}}
+    graph.update(nodes)
+    return graph
+
+
+class TestSamplerLessPrompt(unittest.TestCase):
+    def test_not_a_graph_or_too_large_is_absent(self):
+        for graph in (None, [], {}, "text"):
+            self.assertEqual(sampler_less_prompt(graph)["state"], "absent")
+        big = {str(i): {"class_type": "X", "inputs": {}} for i in range(3)}
+        self.assertEqual(sampler_less_prompt(big, max_visits=2)["state"], "absent")
+
+    def test_one_literal_text(self):
+        graph = _guided(**{"1": {"class_type": "Enc", "inputs": {"text": " a fox "}}})
+        self.assertEqual(
+            sampler_less_prompt(graph),
+            {"state": "resolved", "text": "a fox", "texts": ["a fox"]},
+        )
+
+    def test_a_number_literal_is_never_a_prompt(self):
+        for value in (2048, "2048", "1.5", " 7 "):
+            graph = _guided(**{"1": {"class_type": "Enc", "inputs": {"text": value}}})
+            self.assertEqual(sampler_less_prompt(graph)["state"], "absent", value)
+
+    def test_a_long_digit_run_with_a_letter_is_text_and_fast(self):
+        text = "9" * 50_000 + "x"
+        graph = _guided(**{"1": {"class_type": "Enc", "inputs": {"text": text}}})
+        started = time.monotonic()
+        self.assertEqual(sampler_less_prompt(graph)["text"], text)
+        self.assertLess(time.monotonic() - started, 1.0)
+
+    def test_number_like_words_are_prompts(self):
+        for value in ("nan", "inf", "Infinity", "1_000"):
+            graph = _guided(**{"1": {"class_type": "Enc", "inputs": {"text": value}}})
+            self.assertEqual(sampler_less_prompt(graph)["text"], value)
+
+    def test_an_own_node_with_unreadable_text_beside_another_text_is_ambiguous(self):
+        graph = _guided(
+            **{
+                "1": {"class_type": "PromptManager", "inputs": {"text": ["5", 0]}},
+                "5": {"class_type": "LLM", "inputs": {"seed": 3}},
+                "2": {"class_type": "Enc", "inputs": {"text": "<lora:x:1>"}},
+                "3": {"class_type": "Sink", "inputs": {"c": ["2", 0]}},
+            }
+        )
+        self.assertEqual(sampler_less_prompt(graph)["state"], "ambiguous")
+
+    def test_unhashable_class_type_is_an_unknown_node_not_a_crash(self):
+        graph = _guided(**{"1": {"class_type": ["x"], "inputs": {"text": "a fox"}}})
+        self.assertEqual(sampler_less_prompt(graph)["text"], "a fox")
+
+    def test_own_negative_node_is_not_authoritative(self):
+        graph = _guided(
+            **{
+                "1": {"class_type": "Enc", "inputs": {"text": "a fox"}},
+                "2": {
+                    "class_type": "PromptManagerNegative",
+                    "inputs": {"text": "blur"},
+                },
+                "3": {"class_type": "Sink", "inputs": {"c": ["2", 0]}},
+            }
+        )
+        found = sampler_less_prompt(graph)
+        self.assertEqual(found["state"], "ambiguous")
+        self.assertEqual(found["texts"], ["a fox", "blur"])
+
+    def test_own_node_text_wins_over_an_untraceable_text(self):
+        graph = _guided(
+            **{
+                "1": {"class_type": "PromptManagerText", "inputs": {"text": "a fox"}},
+                "2": {"class_type": "Enc", "inputs": {"text": ["5", 0]}},
+                "5": {"class_type": "LLM", "inputs": {"seed": 3}},
+                "6": {"class_type": "Sink", "inputs": {"c": ["2", 0]}},
+            }
+        )
+        self.assertEqual(sampler_less_prompt(graph)["text"], "a fox")
+
+    def test_two_own_texts_are_ambiguous(self):
+        graph = _guided(
+            **{
+                "1": {"class_type": "PromptManager", "inputs": {"text": "a fox"}},
+                "2": {"class_type": "PromptManager", "inputs": {"text": "a cat"}},
+                "3": {"class_type": "Sink", "inputs": {"c": ["2", 0]}},
+            }
+        )
+        self.assertEqual(sampler_less_prompt(graph)["state"], "ambiguous")
+
+    def test_only_an_untraceable_text_is_ambiguous_with_nothing_to_show(self):
+        graph = _guided(
+            **{
+                "1": {"class_type": "Enc", "inputs": {"text": ["5", 0]}},
+                "5": {"class_type": "LLM", "inputs": {"seed": 3}},
+            }
+        )
+        self.assertEqual(
+            sampler_less_prompt(graph),
+            {"state": "ambiguous", "text": None, "texts": []},
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()

utils/prompt_pair_resolver.py

@@ -2578,3 +2578,115 @@ def resolve_text_input(
         return resolver.text(inputs.get(input_name), "string")[0]
     except _Unresolved:
         return None
+
+
+_NUMBER = re.compile(r"[+-]?(?:\d+(?:\.\d*)?|\.\d+)(?:[eE][+-]?\d+)?")
+
+
+def _numeric(text: str) -> bool:
+    """Whether ``text`` is a plain number (a widget value such as ``2048``)."""
+    return _NUMBER.fullmatch(text) is not None
+
+
+def sampler_less_prompt(graph: Any, *, max_visits: int = 500) -> Dict[str, Any]:
+    """The positive prompt of an API graph with no sampler pair, if one (#252).
+
+    For graphs ``_no_sampler`` finds ``absent`` (no node takes a ``positive``
+    or ``negative`` input, such as a Flux guider or a video wrapper). Only the
+    executed API graph is read, never the UI workflow. A candidate is a node
+    with a ``text`` input whose output another node consumes: a text that
+    feeds nothing did not make the image. Its text is traced as a STRING
+    (``resolve_text_input``); a linked text no rule reads is unknown unless
+    it is built from a candidate's text (``_covered``). Blank and
+    numeric texts are never prompts, and a node with a seed input holds a
+    template, not the prompt (unknown). This repository's own positive-text
+    nodes are authoritative: when they give a text, only they count.
+
+    Returns ``{"state", "text", "texts"}``: ``resolved`` with the one distinct
+    text; ``ambiguous`` when several texts or an unknown one could be the
+    prompt (``texts`` lists the readable ones); ``absent`` when none.
+    """
+    absent = {"state": "absent", "text": None, "texts": []}
+    if not isinstance(graph, dict) or not graph or len(graph) > max_visits:
+        return absent
+    nodes = {str(key): value for key, value in graph.items()}
+    consumed = {
+        str(value[0])
+        for node in nodes.values()
+        if isinstance(node, dict) and isinstance(node.get("inputs"), dict)
+        for value in node["inputs"].values()
+        if _link(value)
+    }
+    own: list = []
+    other: list = []
+    unknown = False
+    for node_id, node in nodes.items():
+        inputs = node.get("inputs") if isinstance(node, dict) else None
+        if node_id not in consumed or not _has_text_input(node):
+            continue
+        if _seeded(inputs):
+            # Generated at run time (a wildcard or a language model): its
+            # text input is a template, not the prompt that ran.
+            unknown = True
+            continue
+        value = inputs["text"]
+        text = resolve_text_input(nodes, node_id, "text", max_visits=max_visits)
+        if text is None:
+            # A literal that is not a string (a number) is never a prompt.
+            if _link(value) and not _covered(nodes, value):
+                unknown = True
+            continue
+        text = text.strip()
+        if not text or _numeric(text):
+            continue
+        kind = node.get("class_type")
+        if isinstance(kind, str) and kind in _OWN_CLASSES and "Negative" not in kind:
+            own.append(text)
+        else:
+            other.append(text)
+    texts = list(dict.fromkeys(own or other))
+    if len(texts) == 1 and (own or not unknown):
+        return {"state": "resolved", "text": texts[0], "texts": texts}
+    if texts or unknown:
+        return {"state": "ambiguous", "text": None, "texts": texts}
+    return absent
+
+
+def _has_text_input(node: Any) -> bool:
+    inputs = node.get("inputs") if isinstance(node, dict) else None
+    return isinstance(inputs, dict) and "text" in inputs
+
+
+def _seeded(inputs: dict) -> bool:
+    """A seed input: the node's string output is a run-time value (the
+    resolver's ``runtime-value`` rule)."""
+    return any(isinstance(name, str) and name.endswith("seed") for name in inputs)
+
+
+def _covered(nodes: dict, link: list) -> bool:
+    """Whether an unreadable text link is built from a candidate's text.
+
+    True when a node upstream of ``link`` is read through its first output
+    (slot 0, the legacy encoder rule's text) and has an unseeded ``text``
+    input: that candidate is read on its own, and whatever else is joined to
+    it at run time (a caption, a language model) is no stored prompt to
+    choose. Another output of such a node (a loader's trigger words) is not
+    its text. False when the text comes only from inputs no candidate holds
+    (a builder's ``prompt`` field): the prompt is unknown then.
+    """
+    seen, stack = set(), [(str(link[0]), link[1])]
+    while stack:
+        node_id, slot = stack.pop()
+        if (node_id, slot) in seen:
+            continue
+        seen.add((node_id, slot))
+        node = nodes.get(node_id)
+        inputs = node.get("inputs") if isinstance(node, dict) else None
+        if not isinstance(inputs, dict):
+            continue
+        if "text" in inputs and slot == 0 and not _seeded(inputs):
+            return True
+        stack.extend(
+            (str(value[0]), value[1]) for value in inputs.values() if _link(value)
+        )
+    return False

web/js/workspace/workspace.css

@@ -433,10 +433,13 @@ pre.prompt-text { font: inherit; font-size: 12px; line-height: 1.75; margin-bloc
 }
 /* D132: at phone width the concept's 120px cap cuts every engine label ("WD14 SwinV2 · ~400 MB"); the Tagging model
    select alone keeps its natural width there (its widest engine label) and, with no room beside the row text, wraps
-   under it. */
+   under it. Existing tags (#398) never shrinks for its row text and, past the cap, keeps its natural width beside the
+   text ("Replace after review"), bounded by its row like the engine select. */
+.setting-row #tag-existing { flex-shrink: 0; /* D132 */ }
 @media (max-width: 700px) {
   #workspace-main .setting-row:has(> #tag-model) { flex-wrap: wrap; /* D132 */ }
   #workspace-main .setting-row #tag-model { flex-shrink: 0; max-width: 100% !important; /* D132 */ }
+  #workspace-main .setting-row #tag-existing { max-width: 100% !important; /* D132 */ }
 }
 
 /* D109: System › Diagnostics & logs' added Lines field sits in the concept's toolbar like its Level select, and a value