PROD -> release 20/08

flake.nix

@@ -1,6 +1,6 @@
 {
   description = "A basic flake with a shell";
-  inputs.nixpkgs.url = "github:NixOS/nixpkgs/nixpkgs-unstable";
+  inputs.nixpkgs.url = "nixpkgs";
   inputs.systems.url = "github:nix-systems/default";
   inputs.flake-utils = {
     url = "github:numtide/flake-utils";

pyproject.toml

@@ -24,7 +24,7 @@ dependencies = [
   "sphinx-notfound-page>=1.1.0,<1.2.0",
   "sphinx-design>=0.6.1,<0.7",
   # autodoc
-  "openprotein-python>=0.14.2,<0.15.0",
+  "openprotein-python>=0.16.0,<0.17.0",
   "ipython>=9.8.0,<10",
   # nbsphinx needs ipywidgets to render notebooks containing widget output
   "ipywidgets>=8.1.0,<9",
@@ -39,7 +39,9 @@ channels = ["conda-forge"]
 platforms = ["linux-64", "osx-arm64"]
 
 [tool.pixi.tasks]
-build = "sphinx-build source build"
+# -W promotes warnings to errors so doc/client-API drift fails the build;
+# --keep-going still reports every warning in one pass.
+build = "sphinx-build -W --keep-going source build"
 
 [tool.pixi.feature.dev.tasks]
 # install dev version of the client

source/_static/js/foldSpec.js

@@ -240,7 +240,7 @@ const foldSpec = {
         tags: ["fold requests", "esmfold2"],
         summary: "ESMFold2",
         description:
-          "Create structure prediction using ESMFold2, an all-atom structure prediction\nmodel. Folds protein/DNA/RNA/ligand complexes, optionally conditioned on an MSA.\n\nArgs:\n  - `sequences`: List of chain/molecule entities in the input. Each entry describes a protein, nucleic acid, or ligand, including its sequence, identifier(s), and optional attributes such as msa_id, SMILES string, CCD code.\n    - `msa_id` should refer to the id of an msa job which included this protein as a query, or `null` for single sequence mode.\n    - `smiles` and `ccd` are mutually exclusive for ligands.\n  - `diffusion_samples`: Number of diffusion samples to use. Controls how many independent structure samples are generated per input. Default is 1.\n  - `num_steps`: Number of sampling steps to use. Sets the number of steps in the diffusion process for each sample. Default is 200.\n  - `num_recycles`: Number of recycling steps to use. Determines how many times the model refines its prediction iteratively. Default is 3.\n  - `seed`: Random seed for reproducible sampling. `null` lets the system decide.",
+          "Create structure prediction using ESMFold2, an all-atom structure prediction\nmodel. Folds protein/DNA/RNA/ligand complexes, optionally conditioned on an MSA.\n\nArgs:\n  - `sequences`: List of chain/molecule entities in the input. Each entry describes a protein, nucleic acid, or ligand, including its sequence, identifier(s), and optional attributes such as msa_id, SMILES string, CCD code.\n    - `msa_id` should refer to the id of an msa job which included this protein as a query, or `null` for single sequence mode.\n    - `smiles` and `ccd` are mutually exclusive for ligands.\n  - `diffusion_samples`: Number of diffusion samples to use. Controls how many independent structure samples are generated per input. Default is 1.\n  - `num_steps`: Number of sampling steps to use. Sets the number of steps in the diffusion process for each sample. Default is 100.\n  - `num_recycles`: Number of recycling steps to use. Determines how many times the model refines its prediction iteratively. Default is 3.\n  - `seed`: Random seed for reproducible sampling. `null` lets the system decide.",
         requestBody: {
           description: "Request for structure prediction.",
           content: {
@@ -328,7 +328,7 @@ const foldSpec = {
         tags: ["fold requests", "esmfold2"],
         summary: "ESMFold2-Fast",
         description:
-          "Create structure prediction using ESMFold2-Fast, an inference-optimized\nsingle-sequence variant of ESMFold2 whose folding trunk has half the depth\n(24 vs 48 layers). Folds protein/DNA/RNA/ligand complexes.\n\nUnlike ESMFold2, ESMFold2-Fast is single-sequence only and does not accept\nan MSA (`msa_id`).\n\nArgs:\n  - `sequences`: List of chain/molecule entities in the input. Each entry describes a protein, nucleic acid, or ligand, including its sequence, identifier(s), and optional attributes such as SMILES string, CCD code.\n    - `smiles` and `ccd` are mutually exclusive for ligands.\n  - `diffusion_samples`: Number of diffusion samples to use. Controls how many independent structure samples are generated per input. Default is 1.\n  - `num_steps`: Number of sampling steps to use. Sets the number of steps in the diffusion process for each sample. Default is 200.\n  - `num_recycles`: Number of recycling steps to use. Determines how many times the model refines its prediction iteratively. Default is 3.\n  - `seed`: Random seed for reproducible sampling. `null` lets the system decide.",
+          "Create structure prediction using ESMFold2-Fast, an inference-optimized\nsingle-sequence variant of ESMFold2 whose folding trunk has half the depth\n(24 vs 48 layers). Folds protein/DNA/RNA/ligand complexes.\n\nUnlike ESMFold2, ESMFold2-Fast is single-sequence only and does not accept\nan MSA (`msa_id`).\n\nArgs:\n  - `sequences`: List of chain/molecule entities in the input. Each entry describes a protein, nucleic acid, or ligand, including its sequence, identifier(s), and optional attributes such as SMILES string, CCD code.\n    - `smiles` and `ccd` are mutually exclusive for ligands.\n  - `diffusion_samples`: Number of diffusion samples to use. Controls how many independent structure samples are generated per input. Default is 1.\n  - `num_steps`: Number of sampling steps to use. Sets the number of steps in the diffusion process for each sample. Default is 100.\n  - `num_recycles`: Number of recycling steps to use. Determines how many times the model refines its prediction iteratively. Default is 3.\n  - `seed`: Random seed for reproducible sampling. `null` lets the system decide.",
         requestBody: {
           description: "Request for structure prediction.",
           content: {
@@ -2006,7 +2006,7 @@ const foldSpec = {
             type: "integer",
             description: "Number of sampling steps to use.",
             minimum: 1,
-            default: 200,
+            default: 100,
           },
           num_recycles: {
             type: "integer",
@@ -2047,7 +2047,7 @@ const foldSpec = {
             ],
           ],
           diffusion_samples: 1,
-          num_steps: 200,
+          num_steps: 100,
           num_recycles: 3,
         },
       },
@@ -2091,7 +2091,7 @@ const foldSpec = {
             type: "integer",
             description: "Number of sampling steps to use.",
             minimum: 1,
-            default: 200,
+            default: 100,
           },
           num_recycles: {
             type: "integer",
@@ -2131,7 +2131,7 @@ const foldSpec = {
             ],
           ],
           diffusion_samples: 1,
-          num_steps: 200,
+          num_steps: 100,
           num_recycles: 3,
         },
       },

source/_static/js/getSwaggerJson.js

@@ -199,75 +199,97 @@ const prodFetchUrls = {
 export default async function getSwaggerJson(swaggerType) {
   let apiPathToShow = [];
   let apiSchemasToShow = [];
-  let swagerSpecs = {};
+  let swaggerSpecs = {};
 
   const environment = getEnvironment();
   const fetchUrls = environment === "dev" ? devFetchUrls : prodFetchUrls;
 
   if (swaggerType === "project") {
     // get the full swagger specs
-    swagerSpecs = await (await fetch(fetchUrls.projectUrl)).json();
+    swaggerSpecs = await (await fetch(fetchUrls.projectUrl)).json();
     // update variables according to the swagger type
     apiPathToShow = apiPathProject;
     apiSchemasToShow = apiSchemasProject;
-    swagerSpecs.tags = apiTagsProject;
+    swaggerSpecs.tags = apiTagsProject;
   }
   if (swaggerType === "align") {
     // get the full swagger specs
-    swagerSpecs = await (await fetch(fetchUrls.projectUrl)).json();
+    swaggerSpecs = await (await fetch(fetchUrls.projectUrl)).json();
 
     // update variables according to the swagger type
     apiPathToShow = apiPathAlign;
     apiSchemasToShow = apiSchemasAlign;
-    swagerSpecs.tags = apiTagsAlign;
+    swaggerSpecs.tags = apiTagsAlign;
   } else if (swaggerType === "poet") {
     // get the full swagger specs
-    swagerSpecs = await (await fetch(fetchUrls.poetUrl)).json();
+    swaggerSpecs = await (await fetch(fetchUrls.poetUrl)).json();
     // update variables according to the swagger type
     apiPathToShow = apiPathPoet;
     apiSchemasToShow = apiSchemasPoet;
-    swagerSpecs.tags = apiTagsPoet;
+    swaggerSpecs.tags = apiTagsPoet;
   } else if (swaggerType === "auth") {
     // get the full swagger specs
-    swagerSpecs = await (await fetch(fetchUrls.authUrl)).json();
+    swaggerSpecs = await (await fetch(fetchUrls.authUrl)).json();
     // update variables according to the swagger type
     apiPathToShow = apiPathAuth;
     apiSchemasToShow = apiSchemasAuth;
-    swagerSpecs.tags = apiTagsAuth;
+    swaggerSpecs.tags = apiTagsAuth;
   } else if (swaggerType === "embeddings") {
     // get the full swagger specs
-    swagerSpecs = await (await fetch(fetchUrls.embeddingsUrl)).json();
-    return swagerSpecs;
+    swaggerSpecs = await (await fetch(fetchUrls.embeddingsUrl)).json();
+    return swaggerSpecs;
   } else if (swaggerType === "prompt") {
     // The prompt service exports its own (prompt-only) spec, so there is
     // nothing to filter — fetch and return it as-is. Includes the dynamic
     // per-system-prompt routes whenever the backend DB is seeded.
-    swagerSpecs = await (await fetch(fetchUrls.promptUrl)).json();
-    return swagerSpecs;
+    swaggerSpecs = await (await fetch(fetchUrls.promptUrl)).json();
+    return swaggerSpecs;
+  } else if (swaggerType === "models") {
+    // Served from the main service. Rather than curating explicit path/schema
+    // allowlists, just keep the models module's routes (everything under
+    // /api/v1/models).
+    swaggerSpecs = await (await fetch(fetchUrls.projectUrl)).json();
+    const modelsPaths = {};
+    const usedTags = new Set();
+    for (const pathKey in swaggerSpecs.paths) {
+      if (!pathKey.startsWith("/api/v1/models")) continue;
+      const pathItem = swaggerSpecs.paths[pathKey];
+      modelsPaths[pathKey] = pathItem;
+      for (const method in pathItem) {
+        (pathItem[method].tags || []).forEach((t) => usedTags.add(t));
+      }
+    }
+    swaggerSpecs.paths = modelsPaths;
+    // Keep only the tags used by the models routes so the other main-service
+    // tag sections don't render.
+    if (Array.isArray(swaggerSpecs.tags)) {
+      swaggerSpecs.tags = swaggerSpecs.tags.filter((t) => usedTags.has(t.name));
+    }
+    return swaggerSpecs;
   }
 
   const filteredPathsToShow = {};
-  for (const pathKey in swagerSpecs.paths) {
+  for (const pathKey in swaggerSpecs.paths) {
     apiPathToShow.forEach((pathToShow) => {
       if (pathToShow === pathKey) {
-        filteredPathsToShow[pathToShow] = swagerSpecs.paths[pathToShow];
+        filteredPathsToShow[pathToShow] = swaggerSpecs.paths[pathToShow];
       }
     });
   }
 
-  swagerSpecs.paths = filteredPathsToShow;
+  swaggerSpecs.paths = filteredPathsToShow;
 
   const filteredSchemasToShow = {};
-  for (const schemaKey in swagerSpecs.components.schemas) {
+  for (const schemaKey in swaggerSpecs.components.schemas) {
     apiSchemasToShow.forEach((schemaKeyToShow) => {
       if (schemaKeyToShow === schemaKey) {
         filteredSchemasToShow[schemaKeyToShow] =
-          swagerSpecs.components.schemas[schemaKeyToShow];
+          swaggerSpecs.components.schemas[schemaKeyToShow];
       }
     });
   }
 
-  swagerSpecs.components.schemas = filteredSchemasToShow;
+  swaggerSpecs.components.schemas = filteredSchemasToShow;
 
-  return swagerSpecs;
+  return swaggerSpecs;
 }

source/_static/js/predictorSpec.js

@@ -1450,7 +1450,15 @@ const predictorSpec = {
           type: {
             type: "string",
             description: "Type of kernel to use with GP.",
-            enum: ["linear", "rbf", "matern21", "matern32"],
+            enum: [
+              "linear",
+              "rbf",
+              "matern12",
+              "matern32",
+              "matern52",
+              "periodic",
+              "rational_quadratic",
+            ],
             example: "rbf",
           },
           multitask: {
@@ -1459,6 +1467,20 @@ const predictorSpec = {
             example: true,
             default: false,
           },
+          period: {
+            type: "number",
+            format: "double",
+            description:
+              "Period length for the periodic kernel. Only valid when type is periodic.",
+            example: 1,
+          },
+          alpha: {
+            type: "number",
+            format: "double",
+            description:
+              "Scale-mixture parameter for the rational_quadratic kernel; must be > 0. Only valid when type is rational_quadratic.",
+            example: 1,
+          },
         },
       },
       TrainRequestGP: {