Feature/chat level up

.gitattributes

@@ -0,0 +1,79 @@
+# Pin line endings on text files so cross-platform contributors don't
+# see phantom "modified" diffs from autocrlf-driven CRLF<->LF flips.
+#
+# Background: Windows users with `core.autocrlf=true` (the Git for
+# Windows default) see Cargo.toml / tauri.conf.json / etc. as modified
+# the moment they `git checkout` because the working-tree copy gets
+# rewritten with CRLF while origin's blobs are LF. Without this file,
+# every status check on Windows lights those up as dirty even though
+# no real change was made. With this file, git normalizes them on the
+# way in and out and the status stays clean.
+
+# Default: treat as text, normalize to LF in the index. The working
+# tree gets the platform's native line ending on checkout (LF on
+# macOS/Linux, LF on Windows-with-`core.eol=lf`, CRLF on
+# Windows-with-default-config).
+* text=auto
+
+# Repo-shape files MUST stay LF in the working tree everywhere -- the
+# Tauri / Cargo / npm toolchains all read them with LF assumptions
+# even on Windows, and a CRLF-shaped tauri.conf.json caused real
+# parse failures earlier in the project history (see the patch-
+# tauri-conf.mjs script's "self-heal an empty/corrupt JSON" branch).
+*.toml          text eol=lf
+*.json          text eol=lf
+*.yml           text eol=lf
+*.yaml          text eol=lf
+*.md            text eol=lf
+
+# Source files: LF everywhere. Vite + tsc handle either, but pinning
+# avoids whitespace-only diffs in PRs.
+*.ts            text eol=lf
+*.tsx           text eol=lf
+*.js            text eol=lf
+*.jsx           text eol=lf
+*.mjs           text eol=lf
+*.cjs           text eol=lf
+*.py            text eol=lf
+*.rs            text eol=lf
+*.css           text eol=lf
+*.html          text eol=lf
+
+# Shell scripts: LF (would otherwise silently break on macOS / Linux
+# with "bad interpreter" errors when bash sees \r in the shebang).
+*.sh            text eol=lf
+
+# PowerShell: CRLF. The PS 5.1 parser handles either but PowerShell
+# scripts authored on Windows traditionally ship CRLF, and Windows
+# editors would otherwise rewrite them on save and produce noise.
+*.ps1           text eol=crlf
+*.psm1          text eol=crlf
+*.psd1          text eol=crlf
+
+# Binary blobs that Git would otherwise try to diff/normalize. Mark
+# them explicitly so a `text=auto` heuristic mistake can't corrupt
+# them on a cross-platform clone.
+*.png           binary
+*.jpg           binary
+*.jpeg          binary
+*.gif           binary
+*.webp          binary
+*.ico           binary
+*.icns          binary
+*.woff          binary
+*.woff2         binary
+*.ttf           binary
+*.otf           binary
+*.zip           binary
+*.gz            binary
+*.tar           binary
+*.7z            binary
+*.exe           binary
+*.dll           binary
+*.so            binary
+*.dylib         binary
+*.pyd           binary
+*.safetensors   binary
+*.gguf          binary
+*.bin           binary
+*.onnx          binary

.github/workflows/release.yml

@@ -265,7 +265,7 @@ jobs:
           tagName: ${{ inputs.release_tag || github.ref_name }}
           tauriScript: npx tauri
           args: --bundles ${{ matrix.bundle_targets }} --ci
-          includeUpdaterJson: false
+          includeUpdaterJson: true
           updaterJsonPreferNsis: false
 
   publish-manifest:

.gitignore

@@ -14,4 +14,5 @@ assets/
 src-tauri/gen/
 .env
 .env.local
-.claude
+.claude
+AGENTS.md

backend_service/agent.py

@@ -32,6 +32,13 @@ class ToolCallResult:
     arguments: dict[str, Any]
     result: str
     elapsed_seconds: float
+    # Phase 2.8: optional structured output the frontend can render
+    # natively (table / code / markdown / image / chart). When None,
+    # the legacy collapsible-JSON renderer fires. The `result` text
+    # field is always populated so the language model sees something
+    # readable on the next turn regardless of UI rendering.
+    render_as: str | None = None
+    data: dict[str, Any] | None = None
 
 
 @dataclass
@@ -108,8 +115,19 @@ def _execute_tool_call(
         )
 
     start = time.perf_counter()
+    render_as: str | None = None
+    structured_data: dict[str, Any] | None = None
     try:
-        result_text = tool.execute(**arguments)
+        # Phase 2.8: try the structured entry first. Tools that
+        # haven't migrated return None and we fall back to the
+        # plain-text path below.
+        structured = tool.execute_structured(**arguments)
+        if structured is not None:
+            result_text = structured.text
+            render_as = structured.render_as
+            structured_data = structured.data
+        else:
+            result_text = tool.execute(**arguments)
     except Exception as exc:
         result_text = f"Error executing {tool_name}: {exc}"
     elapsed = round(time.perf_counter() - start, 3)
@@ -122,6 +140,8 @@ def _execute_tool_call(
         arguments=arguments,
         result=result_text,
         elapsed_seconds=elapsed,
+        render_as=render_as,
+        data=structured_data,
     )
 
 
@@ -384,6 +404,11 @@ def run_agent_loop_streaming(
                     "name": tc_result.tool_name,
                     "result": tc_result.result[:2000],  # Cap for streaming
                     "elapsed": tc_result.elapsed_seconds,
+                    # Phase 2.8: stream the structured shape so the
+                    # frontend can render it as the tool finishes
+                    # rather than waiting for the final done payload.
+                    "renderAs": tc_result.render_as,
+                    "data": tc_result.data,
                 },
             }
 

backend_service/app.py

@@ -84,6 +84,8 @@
 CHAT_SESSIONS_PATH = DATA_LOCATION.chat_sessions_path
 LIBRARY_CACHE_PATH = DATA_LOCATION.data_dir / "library_cache.json"
 DOCUMENTS_DIR = DATA_LOCATION.documents_dir
+WORKSPACES_PATH = DATA_LOCATION.workspaces_path
+WORKSPACES_DIR = DATA_LOCATION.workspaces_dir
 IMAGE_OUTPUTS_DIR = DATA_LOCATION.image_outputs_dir
 VIDEO_OUTPUTS_DIR = DATA_LOCATION.video_outputs_dir
 MAX_DOC_SIZE_BYTES = 50 * 1024 * 1024  # 50 MB per file
@@ -351,6 +353,20 @@ def _generate_image_artifacts(
     logger.info("Generating image: model=%s repo=%s size=%dx%d steps=%d draft=%s",
                 variant.get("name"), variant.get("repo"), effective_width, effective_height, request.steps, request.draftMode)
     runtime_manager = runtime_manager or ImageRuntimeManager()
+    # FU-019: variant-declared defaults override schema defaults only
+    # when the user hasn't moved the slider. Schema defaults (24 steps,
+    # CFG 5.5) come from ImageGenerationRequest in models/__init__.py.
+    SCHEMA_DEFAULT_STEPS = 24
+    SCHEMA_DEFAULT_GUIDANCE = 5.5
+    effective_steps = request.steps
+    effective_guidance = request.guidance
+    variant_default_steps = variant.get("defaultSteps")
+    variant_cfg_override = variant.get("cfgOverride")
+    if variant_default_steps is not None and request.steps == SCHEMA_DEFAULT_STEPS:
+        effective_steps = int(variant_default_steps)
+    if variant_cfg_override is not None and abs(request.guidance - SCHEMA_DEFAULT_GUIDANCE) < 1e-3:
+        effective_guidance = float(variant_cfg_override)
+
     rendered_images, runtime_status = runtime_manager.generate(
         ImageGenerationConfig(
             modelId=request.modelId,
@@ -360,15 +376,39 @@ def _generate_image_artifacts(
             negativePrompt=request.negativePrompt or "",
             width=effective_width,
             height=effective_height,
-            steps=request.steps,
-            guidance=request.guidance,
+            steps=effective_steps,
+            guidance=effective_guidance,
             batchSize=request.batchSize,
             seed=request.seed,
             qualityPreset=request.qualityPreset,
             sampler=request.sampler,
             ggufRepo=(variant.get("ggufRepo") or None),
             ggufFile=(variant.get("ggufFile") or None),
             runtime=(variant.get("engine") or None),
+            cacheStrategy=request.cacheStrategy,
+            cacheRelL1Thresh=request.cacheRelL1Thresh,
+            cfgDecay=request.cfgDecay,
+            previewVae=request.previewVae,
+            # FU-019: variant-declared LoRA + step / guidance overrides.
+            # When the catalog variant pins a Hyper-SD / FLUX-Turbo /
+            # lightx2v LoRA, the engine fuses it into the pipeline at
+            # load time. ``defaultSteps`` / ``cfgOverride`` substitute
+            # only when the user kept the schema defaults — explicit
+            # slider tweaks survive untouched.
+            loraRepo=(variant.get("loraRepo") or None),
+            loraFile=(variant.get("loraFile") or None),
+            loraScale=(variant.get("loraScale") if variant.get("loraScale") is not None else None),
+            defaultSteps=(variant.get("defaultSteps") if variant.get("defaultSteps") is not None else None),
+            cfgOverride=(variant.get("cfgOverride") if variant.get("cfgOverride") is not None else None),
+            # FU-023: variant-pinned Nunchaku SVDQuant snapshot. Threads
+            # through to ``_ensure_pipeline`` which prefers it over
+            # NF4 / int8wo on CUDA when nunchaku is installed.
+            nunchakuRepo=(variant.get("nunchakuRepo") or None),
+            nunchakuFile=(variant.get("nunchakuFile") or None),
+            # FU-024: opt-in FP8 layerwise casting. Threaded from the
+            # request rather than the catalog so users can experiment
+            # without the catalog committing to fp8 readiness per repo.
+            fp8LayerwiseCasting=request.fp8LayerwiseCasting,
         )
     )
     created_at = datetime.utcnow().replace(microsecond=0).isoformat() + "Z"
@@ -425,6 +465,21 @@ def _generate_video_artifact(
         request.steps,
     )
 
+    # FU-019: variant-declared step / CFG defaults override schema
+    # defaults only when the user kept the schema defaults — explicit
+    # slider movement on the frontend is preserved untouched. The
+    # video schema default is steps=50 (see VideoGenerationRequest).
+    SCHEMA_DEFAULT_STEPS = 50
+    SCHEMA_DEFAULT_GUIDANCE = 3.0
+    effective_steps = request.steps
+    effective_guidance = request.guidance
+    variant_default_steps = variant.get("defaultSteps")
+    variant_cfg_override = variant.get("cfgOverride")
+    if variant_default_steps is not None and request.steps == SCHEMA_DEFAULT_STEPS:
+        effective_steps = int(variant_default_steps)
+    if variant_cfg_override is not None and abs(request.guidance - SCHEMA_DEFAULT_GUIDANCE) < 1e-3:
+        effective_guidance = float(variant_cfg_override)
+
     video, runtime_status = runtime_manager.generate(
         VideoGenerationConfig(
             modelId=request.modelId,
@@ -436,8 +491,8 @@ def _generate_video_artifact(
             height=request.height,
             numFrames=request.numFrames,
             fps=request.fps,
-            steps=request.steps,
-            guidance=request.guidance,
+            steps=effective_steps,
+            guidance=effective_guidance,
             seed=request.seed,
             ggufRepo=(variant.get("ggufRepo") or None),
             ggufFile=(variant.get("ggufFile") or None),
@@ -447,6 +502,27 @@ def _generate_video_artifact(
             enableLtxRefiner=request.enableLtxRefiner,
             enhancePrompt=request.enhancePrompt,
             cfgDecay=request.cfgDecay,
+            stgScale=request.stgScale,
+            previewVae=request.previewVae,
+            # FU-019: variant-declared LoRA + override metadata.
+            loraRepo=(variant.get("loraRepo") or None),
+            loraFile=(variant.get("loraFile") or None),
+            loraScale=(variant.get("loraScale") if variant.get("loraScale") is not None else None),
+            defaultSteps=(variant.get("defaultSteps") if variant.get("defaultSteps") is not None else None),
+            cfgOverride=(variant.get("cfgOverride") if variant.get("cfgOverride") is not None else None),
+            # Phase 3 / Wan2.2-Distill 4-step: catalog-pinned distilled
+            # transformers replace both Wan A14B experts at pipeline load.
+            distillTransformerRepo=(variant.get("distillTransformerRepo") or None),
+            distillTransformerHighNoiseFile=(variant.get("distillTransformerHighNoiseFile") or None),
+            distillTransformerLowNoiseFile=(variant.get("distillTransformerLowNoiseFile") or None),
+            distillTransformerPrecision=(variant.get("distillTransformerPrecision") or None),
+            # FU-023 / FU-024: catalog-pinned Nunchaku snapshot + opt-in
+            # FP8 layerwise casting (CUDA-only). Same shape as the image
+            # side so a future video-Nunchaku release lands without app
+            # plumbing churn.
+            nunchakuRepo=(variant.get("nunchakuRepo") or None),
+            nunchakuFile=(variant.get("nunchakuFile") or None),
+            fp8LayerwiseCasting=request.fp8LayerwiseCasting,
         )
     )