Deploy hf-hub-query with current fast-agent and Monty

Dockerfile

@@ -13,9 +13,9 @@ WORKDIR /app
 
 COPY wheels /tmp/wheels
 RUN uv pip install --system --no-cache \
-    "fast-agent-mcp>=0.6.1" \
+    "fast-agent-mcp==0.6.24" \
     huggingface_hub \
-    "pydantic-monty==0.0.10"
+    "pydantic-monty==0.0.17"
 
 COPY --link ./ /app
 RUN chown -R 1000:1000 /app

_monty_codegen_shared.md

@@ -50,11 +50,8 @@ result
 - For human-facing follower/member/liker lists without an explicit requested count, prefer `limit=100` and return coverage when more may exist.
 - For follower/following/member/liker queries that require local filtering on actor fields such as `username` or `fullname`, prefer a bounded scan like `limit=100` / `scan_limit=100` by default, or at most about `200` when a slightly broader sample is justified. Do **not** jump to `1000` unless the user explicitly asked for exhaustive coverage or a very large sample.
 - Unknown `fields` / `where` keys now fail fast. Use only canonical field names.
-- Ownership phrasing like "what collections does Qwen have", "collections by Qwen", or "collections owned by Qwen" means an owner lookup, so use `hf_collections_search(owner="Qwen")`, not a keyword-only `query="Qwen"` search.
-- `hf_collections_search(owner=...)` filters owners case-insensitively, so preserve the user-provided owner spelling but use the owner argument directly.
+- Ownership phrasing like "what collections does Qwen have", "collections by Qwen", or "collections owned by Qwen" means an owner lookup, so use `hf_collections_search(owner="Qwen")`, not a keyword-only `query="Qwen"` search; it filters owners case-insensitively.
 - Ownership phrasing like "what spaces does X have", "what models does X have", or "what datasets does X have" means an author/owner inventory lookup, so use `hf_spaces_search(author="X")`, `hf_models_search(author="X")`, or `hf_datasets_search(author="X")` rather than a global keyword-only search.
-- For paper discovery, use `hf_papers_search(...)` for search, `hf_daily_papers(...)` for the curated daily feed, `hf_paper_info(...)` for exact metadata, and `hf_read_paper(...)` for markdown content.
-- The main Hub-native join points on paper rows are `organization`, `submitted_by`, and `author_usernames`. Papers do not expose first-class model/dataset/space repo IDs.
 - For profile/detail/social questions about a user or org — bio, description, display name, website, GitHub, Twitter/X, LinkedIn, Bluesky, organizations, or pro status — use `hf_profile_summary(...)` first.
 - For join-style questions that need profile details for followers, following, members, likers, or other actor lists, first fetch a **bounded** actor list, filter locally on actor fields like `username` / `fullname`, then hydrate only the bounded matches with `hf_profile_summary(...)`.
 - Do **not** set the initial actor-list limit equal to the whole remaining call budget when each match needs a follow-up profile lookup; reserve budget for the profile-detail calls and return coverage if the hydration step is partial.
@@ -63,45 +60,13 @@ result
 - Think like `huggingface_hub`: `search`, `filter`, `author`, repo-type-specific upstream params, then `fields`.
 - Push constraints upstream whenever a first-class helper argument exists.
 - `post_filter` is only for normalized row filters that cannot be pushed upstream.
+- `num_params` is a first-class upstream model-search arg; use `num_params="min:6B,max:128B"` instead of `post_filter` when possible.
 - For created/updated date constraints, pair local `post_filter` with the matching sort (`created_at` or `last_modified`). Do **not** rely on date-only `post_filter` over an unsorted repo search window.
 - Keep `post_filter` simple:
   - exact match or `in` for returned fields like `runtime_stage`
-  - `gte` / `lte` for normalized numeric fields like `num_params`, `downloads`, and `likes`
+  - `gte` / `lte` for normalized numeric fields like `downloads` and `likes`
   - `gte` / `lte` also work for normalized ISO timestamp fields like `created_at` and `last_modified`
-- `num_params` is one of the main valid reasons to use `post_filter` on model search today.
-- Do **not** use `post_filter` for things that already have first-class upstream params like `author`, `pipeline_tag`, `dataset_name`, `language`, `models`, or `datasets`.
-
-## Common repo fields
-
-- `repo_id`
-- `repo_type`
-- `author`
-- `likes`
-- `downloads`
-- `created_at`
-- `last_modified`
-- `num_params`
-- `repo_url`
-- model: `library_name`, `pipeline_tag`
-- dataset: `description`, `paperswithcode_id`
-- space: `sdk`, `models`, `datasets`, `subdomain`
-
-## Common collection fields
-
-- `collection_id`
-- `title`
-- `owner`
-- `description`
-- `last_updated`
-- `item_count`
-- use `hf_collections_search(owner="<org-or-user>", ...)` for owner lookups
-
-## Common paper join points
-
-- `organization`
-- `submitted_by`
-- `author_usernames`
-- `discussion_id`
+- Do **not** use `post_filter` for things that already have first-class upstream params like `author`, `pipeline_tag`, `num_params` on model search, `dataset_name`, `language`, `models`, or `datasets`.
 
 Examples:
 
@@ -113,9 +78,9 @@ result
 ```py
 result = await hf_models_search(
     pipeline_tag="text-generation",
+    num_params="min:20B,max:80B",
     sort="trending_score",
     limit=50,
-    post_filter={"num_params": {"gte": 20_000_000_000, "lte": 80_000_000_000}},
 )
 result
 ```
@@ -170,7 +135,7 @@ else:
 result
 ```
 
-Bounded join pattern:
+Follower-profile join pattern:
 
 ```py
 followers_resp = await hf_user_graph(
@@ -217,10 +182,81 @@ result = {
 result
 ```
 
-Use the same pattern for other bounded joins:
-- actor list → filter locally → hydrate exact matches
-- actor list → per-actor likes/details → aggregate under `results`
-- preserve upstream helper `meta` under top-level `coverage` whenever partiality matters
+Follower-likes aggregation pattern:
+
+```py
+followers_resp = await hf_user_graph(relation="followers", limit=100, fields=["username"])
+followers = followers_resp.get("items") or []
+results = []
+for follower in followers:
+    username = follower.get("username")
+    if not username:
+        continue
+    likes_resp = await hf_user_likes(
+        username=username,
+        repo_types=["model"],
+        limit=20,
+        fields=["repo_id", "liked_at"],
+    )
+    results.append(
+        {
+            "follower": username,
+            "liked_models": likes_resp.get("items") or [],
+        }
+    )
+coverage = {
+    "followers": followers_resp.get("meta") or {},
+}
+result = {"results": results, "coverage": coverage}
+result
+```
+
+Current-user pro-follower model-likes pattern:
+
+```py
+followers_resp = await hf_user_graph(
+    relation="followers",
+    pro_only=True,
+    limit=100,
+    fields=["username"],
+)
+followers = followers_resp.get("items") or []
+remaining_calls = max(0, max_calls - 1)
+results = {}
+partial = (
+    (followers_resp.get("meta") or {}).get("limit_boundary_hit")
+    or (followers_resp.get("meta") or {}).get("more_available") not in {False, None}
+)
+processed_followers = 0
+for follower in followers:
+    if remaining_calls <= 0:
+        partial = True
+        break
+    username = follower.get("username")
+    if not username:
+        continue
+    likes_resp = await hf_user_likes(
+        username=username,
+        repo_types=["model"],
+        limit=2,
+        fields=["repo_id", "repo_author", "liked_at"],
+    )
+    remaining_calls -= 1
+    likes_meta = likes_resp.get("meta") or {}
+    if likes_meta.get("limit_boundary_hit") or likes_meta.get("more_available") not in {False, None}:
+        partial = True
+    items = likes_resp.get("items") or []
+    if items:
+        results[username] = items
+    processed_followers += 1
+coverage = {
+    "followers": followers_resp.get("meta") or {},
+    "processed_followers": processed_followers,
+    "partial": partial,
+}
+result = {"results": results, "coverage": coverage}
+result
+```
 
 ## Navigation graph
 
@@ -232,10 +268,7 @@ Use the helper that matches the question type.
 - space search/list/discovery → `hf_spaces_search(...)`
 - cross-type repo search → `hf_repo_search(...)`
 - trending repos → `hf_trending(...)`
-- Daily papers → `hf_daily_papers(...)`
-- paper search → `hf_papers_search(...)`
-- paper detail → `hf_paper_info(...)`
-- paper markdown → `hf_read_paper(...)`
+- daily papers → `hf_daily_papers(...)`
 - repo discussions → `hf_repo_discussions(...)`
 - specific discussion details → `hf_repo_discussion_details(...)`
 - users who liked one repo → `hf_repo_likers(...)`
@@ -290,22 +323,16 @@ await hf_collection_items(collection_id: 'str', repo_types: 'list[str] | None' =
 
 await hf_collections_search(query: 'str | None' = None, owner: 'str | None' = None, limit: 'int' = 20, count_only: 'bool' = False, where: 'dict[str, Any] | None' = None, fields: 'list[str] | None' = None) -> 'dict[str, Any]'
 
-await hf_daily_papers(date: 'str | None' = None, week: 'str | None' = None, month: 'str | None' = None, submitter: 'str | None' = None, sort: 'str | None' = None, p: 'int | None' = None, limit: 'int' = 20, where: 'dict[str, Any] | None' = None, fields: 'list[str] | None' = None) -> 'dict[str, Any]'
+await hf_daily_papers(limit: 'int' = 20, where: 'dict[str, Any] | None' = None, fields: 'list[str] | None' = None) -> 'dict[str, Any]'
 
-await hf_datasets_search(search: 'str | None' = None, filter: 'str | list[str] | None' = None, author: 'str | None' = None, benchmark: 'str | bool | None' = None, dataset_name: 'str | None' = None, gated: 'bool | None' = None, language_creators: 'str | list[str] | None' = None, language: 'str | list[str] | None' = None, multilinguality: 'str | list[str] | None' = None, size_categories: 'str | list[str] | None' = None, task_categories: 'str | list[str] | None' = None, task_ids: 'str | list[str] | None' = None, sort: 'str | None' = None, limit: 'int' = 20, expand: 'list[str] | None' = None, full: 'bool | None' = None, fields: 'list[str] | None' = None, post_filter: 'dict[str, Any] | None' = None) -> 'dict[str, Any]'
+await hf_datasets_search(search: 'str | None' = None, filter: 'str | list[str] | None' = None, author: 'str | None' = None, benchmark: 'str | bool | None' = None, dataset_name: 'str | None' = None, gated: 'bool | None' = None, language_creators: 'str | list[str] | None' = None, language: 'str | list[str] | None' = None, multilinguality: 'str | list[str] | None' = None, size_categories: 'str | list[str] | None' = None, task_categories: 'str | list[str] | None' = None, task_ids: 'str | list[str] | None' = None, sort: 'str | None' = None, limit: 'int' = 100, expand: 'list[str] | None' = None, full: 'bool | None' = None, fields: 'list[str] | None' = None, post_filter: 'dict[str, Any] | None' = None) -> 'dict[str, Any]'
 
-await hf_models_search(search: 'str | None' = None, filter: 'str | list[str] | None' = None, author: 'str | None' = None, apps: 'str | list[str] | None' = None, gated: 'bool | None' = None, inference: 'str | None' = None, inference_provider: 'str | list[str] | None' = None, model_name: 'str | None' = None, trained_dataset: 'str | list[str] | None' = None, pipeline_tag: 'str | None' = None, emissions_thresholds: 'tuple[float, float] | None' = None, sort: 'str | None' = None, limit: 'int' = 20, expand: 'list[str] | None' = None, full: 'bool | None' = None, card_data: 'bool' = False, fetch_config: 'bool' = False, fields: 'list[str] | None' = None, post_filter: 'dict[str, Any] | None' = None) -> 'dict[str, Any]'
+await hf_models_search(search: 'str | None' = None, filter: 'str | list[str] | None' = None, author: 'str | None' = None, apps: 'str | list[str] | None' = None, gated: 'bool | None' = None, inference: 'str | None' = None, inference_provider: 'str | list[str] | None' = None, model_name: 'str | None' = None, trained_dataset: 'str | list[str] | None' = None, pipeline_tag: 'str | None' = None, num_params: 'str | None' = None, emissions_thresholds: 'tuple[float, float] | None' = None, sort: 'str | None' = None, limit: 'int' = 100, expand: 'list[str] | None' = None, full: 'bool | None' = None, card_data: 'bool' = False, fetch_config: 'bool' = False, fields: 'list[str] | None' = None, post_filter: 'dict[str, Any] | None' = None) -> 'dict[str, Any]'
 
 await hf_org_members(organization: 'str', limit: 'int | None' = None, scan_limit: 'int | None' = None, count_only: 'bool' = False, where: 'dict[str, Any] | None' = None, fields: 'list[str] | None' = None) -> 'dict[str, Any]'
 
-await hf_paper_info(paper_id: 'str', fields: 'list[str] | None' = None) -> 'dict[str, Any]'
-
-await hf_papers_search(query: 'str', limit: 'int' = 20, where: 'dict[str, Any] | None' = None, fields: 'list[str] | None' = None) -> 'dict[str, Any]'
-
 await hf_profile_summary(handle: 'str | None' = None, include: 'list[str] | None' = None, likes_limit: 'int' = 10, activity_limit: 'int' = 10) -> 'dict[str, Any]'
 
-await hf_read_paper(paper_id: 'str') -> 'dict[str, Any]'
-
 await hf_recent_activity(feed_type: 'str | None' = None, entity: 'str | None' = None, activity_types: 'list[str] | None' = None, repo_types: 'list[str] | None' = None, limit: 'int | None' = None, max_pages: 'int | None' = None, start_cursor: 'str | None' = None, count_only: 'bool' = False, where: 'dict[str, Any] | None' = None, fields: 'list[str] | None' = None) -> 'dict[str, Any]'
 
 await hf_repo_details(repo_id: 'str | None' = None, repo_ids: 'list[str] | None' = None, repo_type: 'str' = 'auto', fields: 'list[str] | None' = None) -> 'dict[str, Any]'
@@ -316,11 +343,11 @@ await hf_repo_discussions(repo_type: 'str', repo_id: 'str', limit: 'int' = 20, f
 
 await hf_repo_likers(repo_id: 'str', repo_type: 'str', limit: 'int | None' = None, count_only: 'bool' = False, pro_only: 'bool | None' = None, where: 'dict[str, Any] | None' = None, fields: 'list[str] | None' = None) -> 'dict[str, Any]'
 
-await hf_repo_search(search: 'str | None' = None, repo_type: 'str | None' = None, repo_types: 'list[str] | None' = None, filter: 'str | list[str] | None' = None, author: 'str | None' = None, sort: 'str | None' = None, limit: 'int' = 20, fields: 'list[str] | None' = None, post_filter: 'dict[str, Any] | None' = None) -> 'dict[str, Any]'
+await hf_repo_search(search: 'str | None' = None, repo_type: 'str | None' = None, repo_types: 'list[str] | None' = None, filter: 'str | list[str] | None' = None, author: 'str | None' = None, sort: 'str | None' = None, limit: 'int' = 100, fields: 'list[str] | None' = None, post_filter: 'dict[str, Any] | None' = None) -> 'dict[str, Any]'
 
 await hf_runtime_capabilities(section: 'str | None' = None) -> 'dict[str, Any]'
 
-await hf_spaces_search(search: 'str | None' = None, filter: 'str | list[str] | None' = None, author: 'str | None' = None, datasets: 'str | list[str] | None' = None, models: 'str | list[str] | None' = None, linked: 'bool' = False, sort: 'str | None' = None, limit: 'int' = 20, expand: 'list[str] | None' = None, full: 'bool | None' = None, fields: 'list[str] | None' = None, post_filter: 'dict[str, Any] | None' = None) -> 'dict[str, Any]'
+await hf_spaces_search(search: 'str | None' = None, filter: 'str | list[str] | None' = None, author: 'str | None' = None, datasets: 'str | list[str] | None' = None, models: 'str | list[str] | None' = None, linked: 'bool' = False, sort: 'str | None' = None, limit: 'int' = 100, expand: 'list[str] | None' = None, full: 'bool | None' = None, fields: 'list[str] | None' = None, post_filter: 'dict[str, Any] | None' = None) -> 'dict[str, Any]'
 
 await hf_trending(repo_type: 'str' = 'model', limit: 'int' = 20, where: 'dict[str, Any] | None' = None, fields: 'list[str] | None' = None) -> 'dict[str, Any]'
 
@@ -387,27 +414,24 @@ All helpers return the same envelope: `{ok, item, items, meta, error}`.
 ### hf_daily_papers
 
 - category: `curated_feed`
-- backed_by: `HfApi.list_daily_papers`
 - returns:
   - envelope: `{ok, item, items, meta, error}`
-  - row_type: `paper`
-  - default_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-  - guaranteed_fields: `paper_id`, `title`, `published_at`
-  - optional_fields: `summary`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-- supported_params: `date`, `week`, `month`, `submitter`, `sort`, `p`, `limit`, `where`, `fields`
-- param_values:
-  - sort: `published_at`, `trending`
+  - row_type: `daily_paper`
+  - default_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_on_daily_at`, `authors`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `github_repo_url`, `github_stars`, `project_page_url`, `num_comments`, `is_author_participating`, `repo_id`, `rank`
+  - guaranteed_fields: `paper_id`, `title`, `published_at`, `rank`
+  - optional_fields: `summary`, `submitted_on_daily_at`, `authors`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `github_repo_url`, `github_stars`, `project_page_url`, `num_comments`, `is_author_participating`, `repo_id`
+- supported_params: `limit`, `where`, `fields`
 - fields_contract:
-  - allowed_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
+  - allowed_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_on_daily_at`, `authors`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `github_repo_url`, `github_stars`, `project_page_url`, `num_comments`, `is_author_participating`, `repo_id`, `rank`
   - canonical_only: `true`
 - where_contract:
-  - allowed_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
+  - allowed_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_on_daily_at`, `authors`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `github_repo_url`, `github_stars`, `project_page_url`, `num_comments`, `is_author_participating`, `repo_id`, `rank`
   - supported_ops: `eq`, `in`, `contains`, `icontains`, `gte`, `lte`
   - normalized_only: `true`
 - limit_contract:
   - default_limit: `20`
   - max_limit: `500`
-- notes: Curated daily papers feed backed by HfApi.list_daily_papers. Useful join points: organization, submitted_by, author_usernames, discussion_id.
+- notes: Returns daily paper summary rows. repo_id is omitted unless the upstream payload provides it.
 
 ### hf_datasets_search
 
@@ -430,7 +454,7 @@ All helpers return the same envelope: `{ok, item, items, meta, error}`.
   - supported_ops: `eq`, `in`, `contains`, `icontains`, `gte`, `lte`
   - normalized_only: `true`
 - limit_contract:
-  - default_limit: `20`
+  - default_limit: `100`
   - max_limit: `5000`
 - notes: Thin dataset-search wrapper around the Hub list_datasets path. Prefer this over hf_repo_search for dataset-only queries. This is a one-shot selective search; if meta.limit_boundary_hit is true, more rows may exist and counts are not exact.
 
@@ -444,7 +468,7 @@ All helpers return the same envelope: `{ok, item, items, meta, error}`.
   - default_fields: `repo_id`, `repo_type`, `author`, `likes`, `downloads`, `trending_score`, `created_at`, `last_modified`, `pipeline_tag`, `num_params`, `repo_url`, `tags`, `library_name`, `description`, `paperswithcode_id`, `sdk`, `models`, `datasets`, `subdomain`, `runtime_stage`, `runtime`
   - guaranteed_fields: `repo_id`, `repo_type`, `author`, `repo_url`
   - optional_fields: `likes`, `downloads`, `trending_score`, `created_at`, `last_modified`, `pipeline_tag`, `num_params`, `tags`, `library_name`, `description`, `paperswithcode_id`, `sdk`, `models`, `datasets`, `subdomain`, `runtime_stage`, `runtime`
-- supported_params: `search`, `filter`, `author`, `apps`, `gated`, `inference`, `inference_provider`, `model_name`, `trained_dataset`, `pipeline_tag`, `emissions_thresholds`, `sort`, `limit`, `expand`, `full`, `card_data`, `fetch_config`, `fields`, `post_filter`
+- supported_params: `search`, `filter`, `author`, `apps`, `gated`, `inference`, `inference_provider`, `model_name`, `trained_dataset`, `pipeline_tag`, `num_params`, `emissions_thresholds`, `sort`, `limit`, `expand`, `full`, `card_data`, `fetch_config`, `fields`, `post_filter`
 - sort_values: `created_at`, `downloads`, `last_modified`, `likes`, `trending_score`
 - expand_values: `author`, `base_models`, `card_data`, `config`, `created_at`, `disabled`, `downloads`, `downloads_all_time`, `eval_results`, `gated`, `gguf`, `inference`, `inference_provider_mapping`, `last_modified`, `library_name`, `likes`, `mask_token`, `model_index`, `pipeline_tag`, `private`, `resource_group`, `safetensors`, `sha`, `siblings`, `spaces`, `tags`, `transformers_info`, `trending_score`, `widget_data`, `xet_enabled`, `gitaly_uid`
 - fields_contract:
@@ -455,7 +479,7 @@ All helpers return the same envelope: `{ok, item, items, meta, error}`.
   - supported_ops: `eq`, `in`, `contains`, `icontains`, `gte`, `lte`
   - normalized_only: `true`
 - limit_contract:
-  - default_limit: `20`
+  - default_limit: `100`
   - max_limit: `5000`
 - notes: Thin model-search wrapper around the Hub list_models path. Prefer this over hf_repo_search for model-only queries. This is a one-shot selective search; if meta.limit_boundary_hit is true, more rows may exist and counts are not exact.
 
@@ -482,45 +506,6 @@ All helpers return the same envelope: `{ok, item, items, meta, error}`.
   - scan_max: `10000`
 - notes: Returns organization member summary rows.
 
-### hf_paper_info
-
-- category: `paper_detail`
-- backed_by: `HfApi.paper_info`
-- returns:
-  - envelope: `{ok, item, items, meta, error}`
-  - row_type: `paper`
-  - default_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-  - guaranteed_fields: `paper_id`, `title`, `published_at`
-  - optional_fields: `summary`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-- supported_params: `paper_id`, `fields`
-- fields_contract:
-  - allowed_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-  - canonical_only: `true`
-- notes: Exact paper metadata helper backed by HfApi.paper_info.
-
-### hf_papers_search
-
-- category: `paper_search`
-- backed_by: `HfApi.list_papers`
-- returns:
-  - envelope: `{ok, item, items, meta, error}`
-  - row_type: `paper`
-  - default_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-  - guaranteed_fields: `paper_id`, `title`, `published_at`
-  - optional_fields: `summary`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-- supported_params: `query`, `limit`, `where`, `fields`
-- fields_contract:
-  - allowed_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-  - canonical_only: `true`
-- where_contract:
-  - allowed_fields: `paper_id`, `title`, `summary`, `published_at`, `submitted_at`, `authors`, `author_usernames`, `organization`, `submitted_by`, `discussion_id`, `upvotes`, `source`, `comments`, `project_page`, `github_repo`, `github_stars`, `rank`
-  - supported_ops: `eq`, `in`, `contains`, `icontains`, `gte`, `lte`
-  - normalized_only: `true`
-- limit_contract:
-  - default_limit: `20`
-  - max_limit: `500`
-- notes: Paper search helper backed by HfApi.list_papers. Use organization, submitted_by, and author_usernames as the main Hub-native join points.
-
 ### hf_profile_summary
 
 - category: `profile_summary`
@@ -535,22 +520,6 @@ All helpers return the same envelope: `{ok, item, items, meta, error}`.
   - include: `likes`, `activity`
 - notes: Profile summary helper. Aggregate counts like followers_count/following_count are in the base item. include=['likes', 'activity'] adds composed samples and extra upstream work; no other include values are supported. Overview-owned repo counts may differ slightly from visible public search/list results.
 
-### hf_read_paper
-
-- category: `paper_markdown`
-- backed_by: `HfApi.read_paper`
-- returns:
-  - envelope: `{ok, item, items, meta, error}`
-  - row_type: `paper_content`
-  - default_fields: `paper_id`, `content`
-  - guaranteed_fields: `paper_id`, `content`
-  - optional_fields: []
-- supported_params: `paper_id`
-- fields_contract:
-  - allowed_fields: `paper_id`, `content`
-  - canonical_only: `true`
-- notes: Returns paper markdown content backed by HfApi.read_paper.
-
 ### hf_recent_activity
 
 - category: `activity_feed`
@@ -681,7 +650,7 @@ All helpers return the same envelope: `{ok, item, items, meta, error}`.
   - supported_ops: `eq`, `in`, `contains`, `icontains`, `gte`, `lte`
   - normalized_only: `true`
 - limit_contract:
-  - default_limit: `20`
+  - default_limit: `100`
   - max_limit: `5000`
 - notes: Small generic repo-search helper. Prefer hf_models_search, hf_datasets_search, or hf_spaces_search for single-type queries; use hf_repo_search for intentionally cross-type search. This is a one-shot selective search; if meta.limit_boundary_hit is true, more rows may exist and counts are not exact.
 
@@ -720,7 +689,7 @@ All helpers return the same envelope: `{ok, item, items, meta, error}`.
   - supported_ops: `eq`, `in`, `contains`, `icontains`, `gte`, `lte`
   - normalized_only: `true`
 - limit_contract:
-  - default_limit: `20`
+  - default_limit: `100`
   - max_limit: `5000`
 - notes: Thin space-search wrapper around the Hub list_spaces path. Prefer this over hf_repo_search for space-only queries. This is a one-shot selective search; if meta.limit_boundary_hit is true, more rows may exist and counts are not exact.
 

hf-hub-query.md

@@ -1,12 +1,14 @@
 ---
 type: agent
 name: hf_hub_query
-model: gpt-oss
+model: hf.openai/gpt-oss-120b:sambanova
 use_history: false
 default: true
 description: "Read-only Hugging Face Hub navigator for discovery, lookup, filtering, ranking, counts, field-constrained extraction, and relationship questions across users, orgs, models, datasets, spaces, collections, discussions, daily papers, recent activity, followers/following, likes, and likers. Good for structured raw outputs and compact results. Generated helper calls can explicitly bound limit, scan_limit, max_pages, and ranking_window for brevity or broader coverage, and the tool can also be asked about its supported helpers, canonical fields, defaults, and coverage behavior."
 shell: false
 skills: []
+#tool_hooks:
+#  after_llm_call: monty_api/llm_time_hook.py:display_llm_time
 function_tools:
   - entrypoint: tool_entrypoints.py:hf_hub_query_raw
     variant: code

monty_api/constants.py

@@ -183,24 +183,22 @@ COLLECTION_CANONICAL_FIELDS: tuple[str, ...] = (
     "item_count",
 )
 
-PAPER_CANONICAL_FIELDS: tuple[str, ...] = (
+DAILY_PAPER_CANONICAL_FIELDS: tuple[str, ...] = (
     "paper_id",
     "title",
     "summary",
     "published_at",
-    "submitted_at",
+    "submitted_on_daily_at",
     "authors",
-    "author_usernames",
     "organization",
     "submitted_by",
     "discussion_id",
     "upvotes",
-    "source",
-    "comments",
-    "project_page",
-    "github_repo",
+    "github_repo_url",
     "github_stars",
+    "project_page_url",
+    "num_comments",
+    "is_author_participating",
+    "repo_id",
     "rank",
 )
-
-PAPER_CONTENT_FIELDS: tuple[str, ...] = ("paper_id", "content")

monty_api/helper_contracts.py

@@ -16,10 +16,9 @@ from .constants import (
     ACTIVITY_CANONICAL_FIELDS,
     ACTOR_CANONICAL_FIELDS,
     COLLECTION_CANONICAL_FIELDS,
+    DAILY_PAPER_CANONICAL_FIELDS,
     DISCUSSION_CANONICAL_FIELDS,
     DISCUSSION_DETAIL_CANONICAL_FIELDS,
-    PAPER_CANONICAL_FIELDS,
-    PAPER_CONTENT_FIELDS,
     PROFILE_CANONICAL_FIELDS,
     REPO_CANONICAL_FIELDS,
     USER_CANONICAL_FIELDS,
@@ -77,10 +76,9 @@ FIELD_GROUPS: dict[str, list[str]] = {
     "activity": list(ACTIVITY_CANONICAL_FIELDS),
     "actor": list(ACTOR_CANONICAL_FIELDS),
     "collection": list(COLLECTION_CANONICAL_FIELDS),
+    "daily_paper": list(DAILY_PAPER_CANONICAL_FIELDS),
     "discussion": list(DISCUSSION_CANONICAL_FIELDS),
     "discussion_detail": list(DISCUSSION_DETAIL_CANONICAL_FIELDS),
-    "paper": list(PAPER_CANONICAL_FIELDS),
-    "paper_content": list(PAPER_CONTENT_FIELDS),
     "profile": list(PROFILE_CANONICAL_FIELDS),
     "repo": list(REPO_CANONICAL_FIELDS),
     "trending_repo": list(TRENDING_CANONICAL_FIELDS),
@@ -111,12 +109,10 @@ HELPER_CONTRACT_SPECS: dict[str, dict[str, Any]] = {
     },
     "hf_daily_papers": {
         "category": "curated_feed",
-        "row_type": "paper",
-        "fields_group": "paper",
+        "row_type": "daily_paper",
+        "fields_group": "daily_paper",
         "filter_param": "where",
-        "filter_group": "paper",
-        "param_values": {"sort": ["published_at", "trending"]},
-        "backed_by": "HfApi.list_daily_papers",
+        "filter_group": "daily_paper",
     },
     "hf_datasets_search": {
         "category": "wrapped_hf_repo_search",
@@ -146,20 +142,6 @@ HELPER_CONTRACT_SPECS: dict[str, dict[str, Any]] = {
         "row_type": "profile",
         "param_values": {"include": ["likes", "activity"]},
     },
-    "hf_paper_info": {
-        "category": "paper_detail",
-        "row_type": "paper",
-        "fields_group": "paper",
-        "backed_by": "HfApi.paper_info",
-    },
-    "hf_papers_search": {
-        "category": "paper_search",
-        "row_type": "paper",
-        "fields_group": "paper",
-        "filter_param": "where",
-        "filter_group": "paper",
-        "backed_by": "HfApi.list_papers",
-    },
     "hf_recent_activity": {
         "category": "activity_feed",
         "row_type": "activity",
@@ -207,12 +189,6 @@ HELPER_CONTRACT_SPECS: dict[str, dict[str, Any]] = {
         "row_type": "runtime_capability",
         "param_values": {"section": list(RUNTIME_CAPABILITY_SECTION_VALUES)},
     },
-    "hf_read_paper": {
-        "category": "paper_markdown",
-        "row_type": "paper_content",
-        "fields_group": "paper_content",
-        "backed_by": "HfApi.read_paper",
-    },
     "hf_spaces_search": {
         "category": "wrapped_hf_repo_search",
         "row_type": "repo",
@@ -420,9 +396,6 @@ def build_helper_contracts(
         param_values = _param_values_for_helper(helper_name)
         if param_values is not None:
             contract["param_values"] = param_values
-        backed_by = spec.get("backed_by")
-        if isinstance(backed_by, str):
-            contract["backed_by"] = backed_by
 
         upstream_repo_type = spec.get("upstream_repo_type")
         if isinstance(upstream_repo_type, str):

monty_api/helpers/__init__.py

@@ -1,7 +1,6 @@
 from .activity import register_activity_helpers
 from .collections import register_collection_helpers
 from .introspection import register_introspection_helpers
-from .papers import register_paper_helpers
 from .profiles import register_profile_helpers
 from .repos import register_repo_helpers
 
@@ -9,7 +8,6 @@ __all__ = [
     "register_activity_helpers",
     "register_collection_helpers",
     "register_introspection_helpers",
-    "register_paper_helpers",
     "register_profile_helpers",
     "register_repo_helpers",
 ]

monty_api/helpers/introspection.py

@@ -10,6 +10,7 @@ from ..constants import (
     ACTIVITY_CANONICAL_FIELDS,
     ACTOR_CANONICAL_FIELDS,
     COLLECTION_CANONICAL_FIELDS,
+    DAILY_PAPER_CANONICAL_FIELDS,
     DISCUSSION_CANONICAL_FIELDS,
     DISCUSSION_DETAIL_CANONICAL_FIELDS,
     DEFAULT_MAX_CALLS,
@@ -18,8 +19,6 @@ from ..constants import (
     LIKES_SCAN_LIMIT_CAP,
     MAX_CALLS_LIMIT,
     OUTPUT_ITEMS_TRUNCATION_LIMIT,
-    PAPER_CANONICAL_FIELDS,
-    PAPER_CONTENT_FIELDS,
     PROFILE_CANONICAL_FIELDS,
     RECENT_ACTIVITY_SCAN_MAX_PAGES,
     REPO_CANONICAL_FIELDS,
@@ -141,8 +140,7 @@ async def hf_runtime_capabilities(
             "user_likes": list(USER_LIKES_CANONICAL_FIELDS),
             "activity": list(ACTIVITY_CANONICAL_FIELDS),
             "collection": list(COLLECTION_CANONICAL_FIELDS),
-            "paper": list(PAPER_CANONICAL_FIELDS),
-            "paper_content": list(PAPER_CONTENT_FIELDS),
+            "daily_paper": list(DAILY_PAPER_CANONICAL_FIELDS),
             "discussion": list(DISCUSSION_CANONICAL_FIELDS),
             "discussion_detail": list(DISCUSSION_DETAIL_CANONICAL_FIELDS),
         },

monty_api/helpers/profiles.py

@@ -338,8 +338,8 @@ async def hf_org_members(
     )
     sample_complete = (
         exact_count
-        and total_matched <= applied_limit
-        and (not count_only or total_matched == 0)
+        and len(normalized) <= applied_limit
+        and (not count_only or len(normalized) == 0)
     )
     more_available = ctx._derive_more_available(
         sample_complete=sample_complete,
@@ -372,18 +372,13 @@ async def hf_org_members(
             "organization": org,
         },
         limit_plan=limit_plan,
-        matched_count=total_matched,
+        matched_count=len(normalized),
         returned_count=len(items),
         exact_count=exact_count,
         count_only=count_only,
         sample_complete=sample_complete,
         more_available=more_available,
-        scan_limit_hit=scan_limit_hit
-        or (
-            overview_total is not None
-            and overview_total > observed_total
-            and observed_total >= scan_lim
-        ),
+        scan_limit_hit=scan_limit_hit,
     )
     return ctx._helper_success(
         start_calls=start_calls, source=endpoint, items=items, meta=meta
@@ -578,8 +573,8 @@ async def _user_graph_helper(
     )
     sample_complete = (
         exact_count
-        and total_matched <= applied_limit
-        and (not count_only or total_matched == 0)
+        and len(normalized) <= applied_limit
+        and (not count_only or len(normalized) == 0)
     )
     more_available = ctx._derive_more_available(
         sample_complete=sample_complete,
@@ -622,18 +617,13 @@ async def _user_graph_helper(
             "organization": u if entity_type == "organization" else None,
         },
         limit_plan=limit_plan,
-        matched_count=total_matched,
+        matched_count=len(normalized),
         returned_count=len(items),
         exact_count=exact_count,
         count_only=count_only,
         sample_complete=sample_complete,
         more_available=more_available,
-        scan_limit_hit=scan_limit_hit
-        or (
-            overview_total is not None
-            and overview_total > observed_total
-            and observed_total >= scan_lim
-        ),
+        scan_limit_hit=scan_limit_hit,
     )
     return ctx._helper_success(
         start_calls=start_calls, source=endpoint, items=items, meta=meta

monty_api/helpers/repos.py

@@ -7,6 +7,7 @@ from ..context_types import HelperRuntimeContext
 from ..helper_contracts import repo_expand_alias_map
 from ..constants import (
     ACTOR_CANONICAL_FIELDS,
+    DAILY_PAPER_CANONICAL_FIELDS,
     EXHAUSTIVE_HELPER_RETURN_HARD_CAP,
     LIKES_ENRICHMENT_MAX_REPOS,
     LIKES_RANKING_WINDOW_DEFAULT,
@@ -122,6 +123,9 @@ def _build_repo_search_extra_args(
             if value:
                 normalized["cardData"] = True
             continue
+        if key in {"num_params", "num_parameters"}:
+            normalized["num_parameters"] = value
+            continue
         if key in {"fetch_config", "linked"}:
             if value:
                 normalized[key] = True
@@ -179,7 +183,7 @@ async def _run_repo_search(
     extra_args_by_type: dict[str, dict[str, Any]] | None = None,
 ) -> dict[str, Any]:
     start_calls = ctx.call_count["n"]
-    default_limit = ctx._policy_int(helper_name, "default_limit", 20)
+    default_limit = ctx._policy_int(helper_name, "default_limit", 100)
     max_limit = ctx._policy_int(
         helper_name, "max_limit", SELECTIVE_ENDPOINT_RETURN_HARD_CAP
     )
@@ -339,9 +343,10 @@ async def hf_models_search(
     model_name: str | None = None,
     trained_dataset: str | list[str] | None = None,
     pipeline_tag: str | None = None,
+    num_params: str | None = None,
     emissions_thresholds: tuple[float, float] | None = None,
     sort: str | None = None,
-    limit: int = 20,
+    limit: int = 100,
     expand: list[str] | None = None,
     full: bool | None = None,
     card_data: bool = False,
@@ -369,6 +374,7 @@ async def hf_models_search(
                 "model_name": model_name,
                 "trained_dataset": trained_dataset,
                 "pipeline_tag": pipeline_tag,
+                "num_params": num_params,
                 "emissions_thresholds": emissions_thresholds,
                 "expand": expand,
                 "full": full,
@@ -394,7 +400,7 @@ async def hf_datasets_search(
     task_categories: str | list[str] | None = None,
     task_ids: str | list[str] | None = None,
     sort: str | None = None,
-    limit: int = 20,
+    limit: int = 100,
     expand: list[str] | None = None,
     full: bool | None = None,
     fields: list[str] | None = None,
@@ -438,7 +444,7 @@ async def hf_spaces_search(
     models: str | list[str] | None = None,
     linked: bool = False,
     sort: str | None = None,
-    limit: int = 20,
+    limit: int = 100,
     expand: list[str] | None = None,
     full: bool | None = None,
     fields: list[str] | None = None,
@@ -475,7 +481,7 @@ async def hf_repo_search(
     filter: str | list[str] | None = None,
     author: str | None = None,
     sort: str | None = None,
-    limit: int = 20,
+    limit: int = 100,
     fields: list[str] | None = None,
     post_filter: dict[str, Any] | None = None,
 ) -> dict[str, Any]:
@@ -1286,6 +1292,62 @@ async def hf_trending(
     )
 
 
+async def hf_daily_papers(
+    ctx: HelperRuntimeContext,
+    limit: int = 20,
+    where: dict[str, Any] | None = None,
+    fields: list[str] | None = None,
+) -> dict[str, Any]:
+    start_calls = ctx.call_count["n"]
+    default_limit = ctx._policy_int("hf_daily_papers", "default_limit", 20)
+    max_limit = ctx._policy_int(
+        "hf_daily_papers", "max_limit", OUTPUT_ITEMS_TRUNCATION_LIMIT
+    )
+    lim = ctx._clamp_int(limit, default=default_limit, minimum=1, maximum=max_limit)
+    resp = ctx._host_raw_call("/api/daily_papers", params={"limit": lim})
+    if not resp.get("ok"):
+        return ctx._helper_error(
+            start_calls=start_calls,
+            source="/api/daily_papers",
+            error=resp.get("error") or "daily papers fetch failed",
+        )
+    payload = resp.get("data") if isinstance(resp.get("data"), list) else []
+    items: list[dict[str, Any]] = []
+    for idx, row in enumerate(payload[:lim], start=1):
+        if not isinstance(row, dict):
+            continue
+        items.append(ctx._normalize_daily_paper_row(row, rank=idx))
+    try:
+        items = ctx._apply_where(
+            items, where, allowed_fields=DAILY_PAPER_CANONICAL_FIELDS
+        )
+    except ValueError as exc:
+        return ctx._helper_error(
+            start_calls=start_calls,
+            source="/api/daily_papers",
+            error=exc,
+        )
+    matched = len(items)
+    try:
+        items = ctx._project_daily_paper_items(items[:lim], fields)
+    except ValueError as exc:
+        return ctx._helper_error(
+            start_calls=start_calls,
+            source="/api/daily_papers",
+            error=exc,
+        )
+    return ctx._helper_success(
+        start_calls=start_calls,
+        source="/api/daily_papers",
+        items=items,
+        limit=lim,
+        scanned=len(payload),
+        matched=matched,
+        returned=len(items),
+        ordered_ranking=True,
+    )
+
+
 def register_repo_helpers(ctx: HelperRuntimeContext) -> dict[str, Callable[..., Any]]:
     return {
         "hf_models_search": partial(hf_models_search, ctx),
@@ -1298,4 +1360,5 @@ def register_repo_helpers(ctx: HelperRuntimeContext) -> dict[str, Callable[...,
         "hf_repo_discussion_details": partial(hf_repo_discussion_details, ctx),
         "hf_repo_details": partial(hf_repo_details, ctx),
         "hf_trending": partial(hf_trending, ctx),
+        "hf_daily_papers": partial(hf_daily_papers, ctx),
     }