feat(models): add provider model scanning (#2106)

* feat(models): add provider model scanning * fix: double close button * feat: update plugin module * fix(monitoring): WeChat Work feedback recording bugs (#2108) * fix(monitoring): fix WeChat Work feedback recording bugs - Fix feedback events silently dropped when stream session expires: dispatch feedback handlers regardless of session availability - Fix IntegrityError on repeated feedback (like→dislike) for same message: implement UPSERT logic in record_feedback() - Fix cancel feedback (type=3) not removing records: add delete logic - Fix inaccurate_reasons validation error: convert int reason codes to strings before creating FeedbackEvent (Pydantic expects List[str]) - Fix feedback timestamps 8 hours off in frontend: use parseUTCTimestamp instead of new Date() for UTC timestamp parsing - Fix StreamSessionManager.cleanup missing _feedback_index cleanup Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix(monitoring): apply ruff format to wecom feedback files Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> --------- Co-authored-by: 6mvp6 <13727783693@163.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> * feat: add feat for receive files in wecombot * fix: ruff error * fix: always show sidebar plus buttons on touch/mobile devices (#2115) Agent-Logs-Url: https://github.com/langbot-app/LangBot/sessions/e27a4886-fbad-4a7a-8558-67a387852753 Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * fix: SPA fallback for all frontend routes, not just /home/* After migrating from Next.js to Vite SPA, routes like /auth/space/callback returned 404 because the static file server only had SPA fallback for /home/*. Now all non-API routes fall back to index.html for React Router to handle. * style: ruff format main.py * feat: add marketplace link when no parser available for file upload Links to /home/market?category=Parser, same pattern as knowledge engine selector. * fix: lint error * fix(user): allow password login and password change for Space accounts with local password set Previously, Space accounts were unconditionally blocked from password login and password change based on account_type. Now the check verifies whether the user actually has a local password set, allowing Space users who have set a local password to authenticate and change it normally. * feat: add edition field to telemetry payload Sends constants.edition (community/saas) with each telemetry event so Space can distinguish between community and SaaS instances. * style: ruff format telemetry.py * fix(dingtalk): use voice recognition text instead of raw audio binary When DingTalk sends a voice message to the bot, the callback JSON contains a 'recognition' field with the speech-to-text result (powered by Qwen). Previously, LangBot only extracted the 'downloadCode' to download the raw audio binary and passed it as 'file_base64' to LLM APIs, which caused 400 errors since most models don't support this content type. This patch: - Extracts the 'recognition' field from DingTalk audio message content - Uses it as plain text input to the LLM instead of raw audio - Falls back to audio binary only when no recognition text is available - Fixes duplicate text issue for audio messages with recognition Fixes voice messages returning 'Request failed' on all LLM models. * feat: integrate Alembic for database migrations Replace manual if-sqlite/if-postgres branching with Alembic: - Add alembic dependency - Create programmatic alembic env (no CLI/alembic.ini needed) - Support async engines via run_sync passthrough - render_as_batch=True for SQLite ALTER TABLE compatibility - Auto-stamp baseline on first run (existing DB at version 25) - Run alembic upgrade head after legacy migrations - Include sample migration showing schema + data migration patterns - Add alembic dir to package-data for distribution * ci: add migration test workflow for SQLite and PostgreSQL Tests alembic upgrade on both databases: - Stamp baseline on existing schema - Upgrade to head - Idempotent re-upgrade - Fresh DB upgrade from scratch * feat: add autogenerate support and CLI entrypoint for alembic - autogenerate: compare ORM models vs DB schema to generate migrations - CLI: python -m langbot.pkg.persistence.alembic_runner <command> - autogenerate, upgrade, stamp, current - Reads data/config.yaml for DB connection * fix: add filereader for dingtalk,lark (#2122) * fix: add filereader for dingtalk * feat: add lark * feat: update uv.lock * chore: update version to 4.9.6 in pyproject.toml, __init__.py, and uv.lock * fix: update langbot-plugin version to 0.3.8 * fix: update langbot-plugin version to 0.3.8 * docs: update database migration instructions in AGENTS.md * fix(dashscopeapi): fix null value check in reasoning content processing logic (#2128) * fix(n8n-runner): fix output_key not applied when n8n returns plain JSON (#2119) * fix: bump dependencies to resolve Dependabot security alerts (#2130) * fix: bump dependencies to resolve Dependabot security alerts Python: - aiohttp: >=3.11.18 → >=3.13.4 (duplicate Host headers, header injection, redirect leak, multipart DoS) - cryptography: >=44.0.3 → >=46.0.7 (buffer overflow with non-contiguous buffers) - pillow: >=11.2.1 → >=12.2.0 (FITS GZIP decompression bomb, HIGH) - langchain-text-splitters: >=0.0.1 → >=1.1.2 (SSRF redirect bypass) - langchain-core: add >=1.2.28 (incomplete f-string validation) - langsmith: add >=0.7.31 (streaming token redaction bypass) - python-multipart: add >=0.0.26 (multipart DoS) - Mako: add >=1.3.11 (path traversal) - pytest: >=8.4.1 → >=9.0.3 (tmpdir handling) - uv: >=0.7.11 → >=0.11.6 (arbitrary file deletion) JavaScript (web/): - vite: ^8.0.3 → ^8.0.5 (fs.deny bypass, WebSocket file read, path traversal, HIGH) - axios: ^1.13.5 → ^1.15.0 (cloud metadata exfiltration) - lodash: ^4.17.23 → ^4.18.0 (code injection via _.template, prototype pollution, HIGH) * fix: update pnpm-lock.yaml for bumped dependencies * feat(ci): add i18n key consistency check for frontend locales (#2133) * feat(ci): add i18n key consistency check workflow Agent-Logs-Url: https://github.com/langbot-app/LangBot/sessions/c7bf50da-189b-49a5-9671-dbe8e70ff9d0 Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * feat(ci): replace eval with line-by-line parser, add permissions block Agent-Logs-Url: https://github.com/langbot-app/LangBot/sessions/c7bf50da-189b-49a5-9671-dbe8e70ff9d0 Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> --------- Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com> Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> * feat(models): add provider model scanning * feat(models): add 'select all' functionality and enrich model abilities * fix:ruff * fix:ruff --------- Co-authored-by: WangCham <651122857@qq.com> Co-authored-by: 6mvp6 <119733319+6mvp6@users.noreply.github.com> Co-authored-by: 6mvp6 <13727783693@163.com> Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com> Co-authored-by: Guanchao Wang <wangcham233@gmail.com> Co-authored-by: Copilot <198982749+Copilot@users.noreply.github.com> Co-authored-by: RockChinQ <45992437+RockChinQ@users.noreply.github.com> Co-authored-by: RockChinQ <rockchinq@gmail.com> Co-authored-by: haiyangbg <zhouhaiyangaa@gmail.com> Co-authored-by: Rock Chin <1010553892@qq.com> Co-authored-by: Amadeus <115918672+AmadeusKurisu1@users.noreply.github.com> Co-authored-by: hzhhong <hung.z.h916@gmail.com> Co-authored-by: fdc310 <2213070223@qq.com>
2026-06-02 03:55:55 +00:00 · 2026-04-19 17:47:07 +08:00
parent 05c684d757
commit 4e5a6ee79a
23 changed files with 1213 additions and 115 deletions
--- a/src/langbot/pkg/api/http/controller/groups/provider/providers.py
+++ b/src/langbot/pkg/api/http/controller/groups/provider/providers.py
@@ -43,3 +43,12 @@ class ModelProvidersRouterGroup(group.RouterGroup):
                    return self.success()
                except ValueError as e:
                    return self.http_status(400, -1, str(e))
+
+        @self.route('/<provider_uuid>/scan-models', methods=['GET'], auth_type=group.AuthType.USER_TOKEN_OR_API_KEY)
+        async def _(provider_uuid: str) -> str:
+            try:
+                model_type = quart.request.args.get('type')
+                result = await self.ap.provider_service.scan_provider_models(provider_uuid, model_type)
+                return self.success(data=result)
+            except ValueError as e:
+                return self.http_status(400, -1, str(e))
--- a/src/langbot/pkg/api/http/service/provider.py
+++ b/src/langbot/pkg/api/http/service/provider.py
@@ -1,6 +1,7 @@
 from __future__ import annotations

 import uuid
+import traceback

 import sqlalchemy

@@ -164,3 +165,66 @@ class ModelProviderService:
            .values(api_keys=[api_key])
        )
        await self.ap.model_mgr.reload_provider('00000000-0000-0000-0000-000000000000')
+
+    async def scan_provider_models(self, provider_uuid: str, model_type: str | None = None) -> dict:
+        provider = await self.get_provider(provider_uuid)
+        if provider is None:
+            raise ValueError('provider not found')
+
+        runtime_provider = await self.ap.model_mgr.load_provider(provider)
+
+        try:
+            scan_result = await runtime_provider.requester.scan_models(
+                runtime_provider.token_mgr.get_token() if runtime_provider.token_mgr.tokens else None
+            )
+        except NotImplementedError:
+            raise ValueError('current provider does not support model scanning')
+        except Exception as exc:
+            self.ap.logger.warning(
+                f'Failed to scan models for provider {provider_uuid}: {exc}\n{traceback.format_exc()}'
+            )
+            raise ValueError(str(exc)) from exc
+
+        if isinstance(scan_result, dict):
+            scanned_models = scan_result.get('models', [])
+            debug_info = scan_result.get('debug')
+        else:
+            scanned_models = scan_result
+            debug_info = None
+
+        llm_models = await self.ap.llm_model_service.get_llm_models_by_provider(provider_uuid)
+        embedding_models = await self.ap.embedding_models_service.get_embedding_models_by_provider(provider_uuid)
+        existing_llm_names = {model['name'] for model in llm_models}
+        existing_embedding_names = {model['name'] for model in embedding_models}
+
+        filtered_models = []
+        for model in scanned_models:
+            scanned_type = model.get('type', 'llm')
+            if model_type and scanned_type != model_type:
+                continue
+
+            model_name = model.get('name') or model.get('id')
+            if not model_name:
+                continue
+
+            filtered_models.append(
+                {
+                    'id': model.get('id', model_name),
+                    'name': model_name,
+                    'type': scanned_type,
+                    'abilities': model.get('abilities', []),
+                    'display_name': model.get('display_name'),
+                    'description': model.get('description'),
+                    'context_length': model.get('context_length'),
+                    'owned_by': model.get('owned_by'),
+                    'input_modalities': model.get('input_modalities', []),
+                    'output_modalities': model.get('output_modalities', []),
+                    'already_added': (
+                        model_name in existing_embedding_names
+                        if scanned_type == 'embedding'
+                        else model_name in existing_llm_names
+                    ),
+                }
+            )
+
+        return {'models': filtered_models, 'debug': debug_info}
--- a/src/langbot/pkg/provider/modelmgr/modelmgr.py
+++ b/src/langbot/pkg/provider/modelmgr/modelmgr.py
@@ -227,7 +227,8 @@ class ModelManager:
            raise provider_errors.RequesterNotFoundError(provider_entity.requester)

        requester_inst = self.requester_dict[provider_entity.requester](
-            ap=self.ap, config={'base_url': provider_entity.base_url}
+            ap=self.ap,
+            config={'base_url': provider_entity.base_url},
        )
        await requester_inst.initialize()

--- a/src/langbot/pkg/provider/modelmgr/requester.py
+++ b/src/langbot/pkg/provider/modelmgr/requester.py
@@ -303,6 +303,14 @@ class ProviderAPIRequester(metaclass=abc.ABCMeta):
    async def initialize(self):
        pass

+    async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any] | list[dict[str, typing.Any]]:
+        """Scan models supported by the provider.
+
+        The default implementation does not support scanning. Requesters that
+        can enumerate remote models should override this method.
+        """
+        raise NotImplementedError('This provider does not support model scanning')
+
    @abc.abstractmethod
    async def invoke_llm(
        self,
--- a/src/langbot/pkg/provider/modelmgr/requesters/chatcmpl.py
+++ b/src/langbot/pkg/provider/modelmgr/requesters/chatcmpl.py
@@ -31,6 +31,192 @@ class OpenAIChatCompletions(requester.ProviderAPIRequester):
            http_client=httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']),
        )

+    def _mask_api_key(self, api_key: str | None) -> str:
+        if not api_key:
+            return ''
+        if len(api_key) <= 8:
+            return '****'
+        return f'{api_key[:4]}...{api_key[-4:]}'
+
+    def _infer_model_type(self, model_id: str) -> str:
+        normalized_model_id = (model_id or '').lower()
+        embedding_keywords = (
+            'embedding',
+            'embed',
+            'bge-',
+            'e5-',
+            'm3e',
+            'gte-',
+            'multilingual-e5',
+            'text-embedding',
+        )
+        return 'embedding' if any(keyword in normalized_model_id for keyword in embedding_keywords) else 'llm'
+
+    def _infer_model_abilities(self, item: dict[str, typing.Any], model_id: str) -> list[str]:
+        normalized_model_id = (model_id or '').lower()
+        abilities: set[str] = set()
+
+        def _flatten(value: typing.Any) -> list[str]:
+            if value is None:
+                return []
+            if isinstance(value, str):
+                return [value.lower()]
+            if isinstance(value, dict):
+                flattened: list[str] = []
+                for nested_value in value.values():
+                    flattened.extend(_flatten(nested_value))
+                return flattened
+            if isinstance(value, (list, tuple, set)):
+                flattened: list[str] = []
+                for nested_value in value:
+                    flattened.extend(_flatten(nested_value))
+                return flattened
+            return [str(value).lower()]
+
+        capability_tokens = _flatten(item.get('capabilities'))
+        capability_tokens.extend(_flatten(item.get('modalities')))
+        capability_tokens.extend(_flatten(item.get('input_modalities')))
+        capability_tokens.extend(_flatten(item.get('output_modalities')))
+        capability_tokens.extend(_flatten(item.get('supported_generation_methods')))
+        capability_tokens.extend(_flatten(item.get('supported_parameters')))
+        capability_tokens.extend(_flatten(item.get('architecture')))
+
+        combined_tokens = capability_tokens + [normalized_model_id]
+
+        vision_keywords = (
+            'vision',
+            'image',
+            'file',
+            'video',
+            'multimodal',
+            'vl',
+            'ocr',
+            'omni',
+        )
+        function_call_keywords = (
+            'function',
+            'tool',
+            'tools',
+            'tool_choice',
+            'tool_call',
+            'tool-use',
+            'tool_use',
+        )
+
+        if any(any(keyword in token for keyword in vision_keywords) for token in combined_tokens):
+            abilities.add('vision')
+
+        if any(any(keyword in token for keyword in function_call_keywords) for token in combined_tokens):
+            abilities.add('func_call')
+
+        return sorted(abilities)
+
+    def _normalize_modalities(self, value: typing.Any) -> list[str]:
+        normalized: list[str] = []
+
+        def _collect(item: typing.Any):
+            if item is None:
+                return
+            if isinstance(item, str):
+                for part in item.replace('->', ',').replace('+', ',').split(','):
+                    token = part.strip().lower()
+                    if token and token not in normalized:
+                        normalized.append(token)
+                return
+            if isinstance(item, dict):
+                for nested in item.values():
+                    _collect(nested)
+                return
+            if isinstance(item, (list, tuple, set)):
+                for nested in item:
+                    _collect(nested)
+                return
+
+        _collect(value)
+        return normalized
+
+    def _extract_scan_metadata(self, item: dict[str, typing.Any], model_id: str) -> dict[str, typing.Any]:
+        display_name = item.get('name')
+        if not isinstance(display_name, str) or not display_name.strip() or display_name == model_id:
+            display_name = ''
+
+        description = item.get('description')
+        if not isinstance(description, str) or not description.strip():
+            description = ''
+
+        context_length = item.get('context_length')
+        if context_length is None and isinstance(item.get('top_provider'), dict):
+            context_length = item['top_provider'].get('context_length')
+
+        if not isinstance(context_length, int):
+            try:
+                context_length = int(context_length) if context_length is not None else None
+            except (TypeError, ValueError):
+                context_length = None
+
+        input_modalities = self._normalize_modalities(item.get('input_modalities'))
+        output_modalities = self._normalize_modalities(item.get('output_modalities'))
+
+        if isinstance(item.get('architecture'), dict):
+            if not input_modalities:
+                input_modalities = self._normalize_modalities(item['architecture'].get('input_modalities'))
+            if not output_modalities:
+                output_modalities = self._normalize_modalities(item['architecture'].get('output_modalities'))
+
+        owned_by = item.get('owned_by')
+        if not isinstance(owned_by, str) or not owned_by.strip():
+            owned_by = ''
+
+        return {
+            'display_name': display_name or None,
+            'description': description or None,
+            'context_length': context_length,
+            'owned_by': owned_by or None,
+            'input_modalities': input_modalities,
+            'output_modalities': output_modalities,
+        }
+
+    async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any]:
+        headers = {}
+        if api_key:
+            headers['Authorization'] = f'Bearer {api_key}'
+
+        models_url = f'{self.requester_cfg["base_url"].rstrip("/")}/models'
+        async with httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']) as client:
+            response = await client.get(models_url, headers=headers)
+            response.raise_for_status()
+            payload = response.json()
+
+        models = []
+        for item in payload.get('data', []):
+            model_id = item.get('id')
+            if not model_id:
+                continue
+            models.append(
+                {
+                    'id': model_id,
+                    'name': model_id,
+                    'type': self._infer_model_type(model_id),
+                    'abilities': self._infer_model_abilities(item, model_id),
+                    **self._extract_scan_metadata(item, model_id),
+                }
+            )
+
+        models.sort(key=lambda item: (item['type'] != 'llm', item['name'].lower()))
+        return {
+            'models': models,
+            'debug': {
+                'request': {
+                    'method': 'GET',
+                    'url': models_url,
+                    'headers': {
+                        'Authorization': f'Bearer {self._mask_api_key(api_key)}' if api_key else '',
+                    },
+                },
+                'response': payload,
+            },
+        }
+
    async def _req(
        self,
        args: dict,
--- a/src/langbot/pkg/provider/modelmgr/requesters/geminichatcmpl.py
+++ b/src/langbot/pkg/provider/modelmgr/requesters/geminichatcmpl.py
@@ -1,6 +1,7 @@
 from __future__ import annotations

 import typing
+import httpx

 from . import chatcmpl

@@ -20,6 +21,68 @@ class GeminiChatCompletions(chatcmpl.OpenAIChatCompletions):
        'timeout': 120,
    }

+    async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any]:
+        models_url = 'https://generativelanguage.googleapis.com/v1beta/models'
+        params = {'key': api_key} if api_key else {}
+
+        all_models: list[dict[str, typing.Any]] = []
+        next_page_token = ''
+        last_payload: dict[str, typing.Any] = {}
+
+        async with httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']) as client:
+            while True:
+                request_params = dict(params)
+                if next_page_token:
+                    request_params['pageToken'] = next_page_token
+
+                response = await client.get(models_url, params=request_params)
+                response.raise_for_status()
+                payload = response.json()
+                last_payload = payload
+
+                for item in payload.get('models', []):
+                    model_name = item.get('name', '')
+                    model_id = model_name.replace('models/', '', 1)
+                    if not model_id:
+                        continue
+
+                    supported_methods = item.get('supportedGenerationMethods', []) or []
+                    if 'embedContent' in supported_methods and 'generateContent' not in supported_methods:
+                        model_type = 'embedding'
+                    else:
+                        model_type = 'llm'
+
+                    all_models.append(
+                        {
+                            'id': model_id,
+                            'name': model_id,
+                            'type': model_type,
+                            'abilities': self._infer_model_abilities(item, model_id),
+                            'display_name': item.get('displayName') or None,
+                            'description': item.get('description') or None,
+                            'context_length': item.get('inputTokenLimit'),
+                            'input_modalities': self._normalize_modalities(item.get('inputModalities')),
+                            'output_modalities': self._normalize_modalities(item.get('outputModalities')),
+                        }
+                    )
+
+                next_page_token = payload.get('nextPageToken', '')
+                if not next_page_token:
+                    break
+
+        all_models.sort(key=lambda item: (item['type'] != 'llm', item['name'].lower()))
+        return {
+            'models': all_models,
+            'debug': {
+                'request': {
+                    'method': 'GET',
+                    'url': models_url,
+                    'query': {'key': self._mask_api_key(api_key)} if api_key else {},
+                },
+                'response': last_payload,
+            },
+        }
+
    async def _closure_stream(
        self,
        query: pipeline_query.Query,
--- a/src/langbot/pkg/provider/modelmgr/requesters/modelscopechatcmpl.py
+++ b/src/langbot/pkg/provider/modelmgr/requesters/modelscopechatcmpl.py
@@ -31,6 +31,175 @@ class ModelScopeChatCompletions(requester.ProviderAPIRequester):
            http_client=httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']),
        )

+    def _mask_api_key(self, api_key: str | None) -> str:
+        if not api_key:
+            return ''
+        if len(api_key) <= 8:
+            return '****'
+        return f'{api_key[:4]}...{api_key[-4:]}'
+
+    def _infer_model_type(self, model_id: str) -> str:
+        normalized_model_id = (model_id or '').lower()
+        embedding_keywords = (
+            'embedding',
+            'embed',
+            'bge-',
+            'e5-',
+            'm3e',
+            'gte-',
+            'multilingual-e5',
+            'text-embedding',
+        )
+        return 'embedding' if any(keyword in normalized_model_id for keyword in embedding_keywords) else 'llm'
+
+    def _infer_model_abilities(self, item: dict[str, typing.Any], model_id: str) -> list[str]:
+        normalized_model_id = (model_id or '').lower()
+        abilities: set[str] = set()
+
+        def _flatten(value: typing.Any) -> list[str]:
+            if value is None:
+                return []
+            if isinstance(value, str):
+                return [value.lower()]
+            if isinstance(value, dict):
+                flattened: list[str] = []
+                for nested_value in value.values():
+                    flattened.extend(_flatten(nested_value))
+                return flattened
+            if isinstance(value, (list, tuple, set)):
+                flattened: list[str] = []
+                for nested_value in value:
+                    flattened.extend(_flatten(nested_value))
+                return flattened
+            return [str(value).lower()]
+
+        capability_tokens = _flatten(item.get('capabilities'))
+        capability_tokens.extend(_flatten(item.get('modalities')))
+        capability_tokens.extend(_flatten(item.get('input_modalities')))
+        capability_tokens.extend(_flatten(item.get('output_modalities')))
+        capability_tokens.extend(_flatten(item.get('supported_generation_methods')))
+        capability_tokens.extend(_flatten(item.get('supported_parameters')))
+        capability_tokens.extend(_flatten(item.get('architecture')))
+
+        combined_tokens = capability_tokens + [normalized_model_id]
+
+        vision_keywords = ('vision', 'image', 'file', 'video', 'multimodal', 'vl', 'ocr', 'omni')
+        function_call_keywords = ('function', 'tool', 'tools', 'tool_choice', 'tool_call', 'tool-use', 'tool_use')
+
+        if any(any(keyword in token for keyword in vision_keywords) for token in combined_tokens):
+            abilities.add('vision')
+
+        if any(any(keyword in token for keyword in function_call_keywords) for token in combined_tokens):
+            abilities.add('func_call')
+
+        return sorted(abilities)
+
+    def _normalize_modalities(self, value: typing.Any) -> list[str]:
+        normalized: list[str] = []
+
+        def _collect(item: typing.Any):
+            if item is None:
+                return
+            if isinstance(item, str):
+                for part in item.replace('->', ',').replace('+', ',').split(','):
+                    token = part.strip().lower()
+                    if token and token not in normalized:
+                        normalized.append(token)
+                return
+            if isinstance(item, dict):
+                for nested in item.values():
+                    _collect(nested)
+                return
+            if isinstance(item, (list, tuple, set)):
+                for nested in item:
+                    _collect(nested)
+                return
+
+        _collect(value)
+        return normalized
+
+    def _extract_scan_metadata(self, item: dict[str, typing.Any], model_id: str) -> dict[str, typing.Any]:
+        display_name = item.get('name')
+        if not isinstance(display_name, str) or not display_name.strip() or display_name == model_id:
+            display_name = ''
+
+        description = item.get('description')
+        if not isinstance(description, str) or not description.strip():
+            description = ''
+
+        context_length = item.get('context_length')
+        if context_length is None and isinstance(item.get('top_provider'), dict):
+            context_length = item['top_provider'].get('context_length')
+
+        if not isinstance(context_length, int):
+            try:
+                context_length = int(context_length) if context_length is not None else None
+            except (TypeError, ValueError):
+                context_length = None
+
+        input_modalities = self._normalize_modalities(item.get('input_modalities'))
+        output_modalities = self._normalize_modalities(item.get('output_modalities'))
+
+        if isinstance(item.get('architecture'), dict):
+            if not input_modalities:
+                input_modalities = self._normalize_modalities(item['architecture'].get('input_modalities'))
+            if not output_modalities:
+                output_modalities = self._normalize_modalities(item['architecture'].get('output_modalities'))
+
+        owned_by = item.get('owned_by')
+        if not isinstance(owned_by, str) or not owned_by.strip():
+            owned_by = ''
+
+        return {
+            'display_name': display_name or None,
+            'description': description or None,
+            'context_length': context_length,
+            'owned_by': owned_by or None,
+            'input_modalities': input_modalities,
+            'output_modalities': output_modalities,
+        }
+
+    async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any]:
+        headers = {}
+        if api_key:
+            headers['Authorization'] = f'Bearer {api_key}'
+
+        models_url = f'{self.requester_cfg["base_url"].rstrip("/")}/models'
+        async with httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']) as client:
+            response = await client.get(models_url, headers=headers)
+            response.raise_for_status()
+            payload = response.json()
+
+        models = []
+        for item in payload.get('data', []):
+            model_id = item.get('id')
+            if not model_id:
+                continue
+            models.append(
+                {
+                    'id': model_id,
+                    'name': model_id,
+                    'type': self._infer_model_type(model_id),
+                    'abilities': self._infer_model_abilities(item, model_id),
+                    **self._extract_scan_metadata(item, model_id),
+                }
+            )
+
+        models.sort(key=lambda item: (item['type'] != 'llm', item['name'].lower()))
+        return {
+            'models': models,
+            'debug': {
+                'request': {
+                    'method': 'GET',
+                    'url': models_url,
+                    'headers': {
+                        'Authorization': f'Bearer {self._mask_api_key(api_key)}' if api_key else '',
+                    },
+                },
+                'response': payload,
+            },
+        }
+
    async def _req(
        self,
        query: pipeline_query.Query,
--- a/src/langbot/pkg/provider/modelmgr/requesters/ollamachat.py
+++ b/src/langbot/pkg/provider/modelmgr/requesters/ollamachat.py
@@ -8,6 +8,7 @@ import uuid
 import json

 import ollama
+import httpx

 from .. import errors, requester
 import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
@@ -31,6 +32,60 @@ class OllamaChatCompletions(requester.ProviderAPIRequester):
        os.environ['OLLAMA_HOST'] = self.requester_cfg['base_url']
        self.client = ollama.AsyncClient(timeout=self.requester_cfg['timeout'])

+    def _infer_model_type(self, model_id: str) -> str:
+        normalized_model_id = (model_id or '').lower()
+        embedding_keywords = ('embedding', 'embed', 'bge-', 'e5-', 'm3e', 'gte-', 'text-embedding')
+        return 'embedding' if any(keyword in normalized_model_id for keyword in embedding_keywords) else 'llm'
+
+    def _infer_model_abilities(self, item: dict[str, typing.Any], model_id: str) -> list[str]:
+        normalized_model_id = (model_id or '').lower()
+        abilities: set[str] = set()
+        details = item.get('details', {}) or {}
+        families = details.get('families', []) or []
+        tokens = [normalized_model_id, str(details.get('family', '')).lower()]
+        tokens.extend(str(family).lower() for family in families)
+
+        if any(keyword in token for token in tokens for keyword in ('vision', 'vl', 'omni', 'llava', 'ocr')):
+            abilities.add('vision')
+        if any(keyword in token for token in tokens for keyword in ('tool', 'function')):
+            abilities.add('func_call')
+        return sorted(abilities)
+
+    async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any]:
+        del api_key
+        models_url = f'{self.requester_cfg["base_url"].rstrip("/")}/api/tags'
+
+        async with httpx.AsyncClient(trust_env=True, timeout=self.requester_cfg['timeout']) as client:
+            response = await client.get(models_url)
+            response.raise_for_status()
+            payload = response.json()
+
+        models: list[dict[str, typing.Any]] = []
+        for item in payload.get('models', []):
+            model_id = item.get('model') or item.get('name')
+            if not model_id:
+                continue
+            models.append(
+                {
+                    'id': model_id,
+                    'name': item.get('name', model_id),
+                    'type': self._infer_model_type(model_id),
+                    'abilities': self._infer_model_abilities(item, model_id),
+                }
+            )
+
+        models.sort(key=lambda item: (item['type'] != 'llm', item['name'].lower()))
+        return {
+            'models': models,
+            'debug': {
+                'request': {
+                    'method': 'GET',
+                    'url': models_url,
+                },
+                'response': payload,
+            },
+        }
+
    async def _req(
        self,
        args: dict,
--- a/src/langbot/pkg/provider/modelmgr/requesters/openrouterchatcmpl.py
+++ b/src/langbot/pkg/provider/modelmgr/requesters/openrouterchatcmpl.py
@@ -15,3 +15,11 @@ class OpenRouterChatCompletions(modelscopechatcmpl.ModelScopeChatCompletions):
        'base_url': 'https://openrouter.ai/api/v1',
        'timeout': 120,
    }
+
+    async def scan_models(self, api_key: str | None = None) -> dict[str, typing.Any]:
+        original_base_url = self.requester_cfg.get('base_url', '')
+        self.requester_cfg['base_url'] = 'https://openrouter.ai/api/v1'
+        try:
+            return await super().scan_models(api_key)
+        finally:
+            self.requester_cfg['base_url'] = original_base_url
--- a/web/src/app/home/components/models-dialog/ModelsDialog.tsx
+++ b/web/src/app/home/components/models-dialog/ModelsDialog.tsx
@@ -16,6 +16,8 @@ import { ProviderCard } from './components';
 import {
  ExtraArg,
  ModelType,
+  ScanModelsResult,
+  SelectedScannedModel,
  TestResult,
  ProviderModels,
  LANGBOT_MODELS_PROVIDER_REQUESTER,
@@ -262,6 +264,60 @@ export default function ModelsDialog({
    }
  }

+  async function handleScanModels(
+    providerUuid: string,
+    modelType: ModelType,
+  ): Promise<ScanModelsResult> {
+    try {
+      const resp = await httpClient.scanProviderModels(providerUuid, modelType);
+      return {
+        models: resp.models,
+        debug: resp.debug,
+      };
+    } catch (err) {
+      toast.error(t('models.getModelListError') + (err as CustomApiError).msg);
+      return { models: [] };
+    }
+  }
+
+  async function handleAddScannedModels(
+    providerUuid: string,
+    modelType: ModelType,
+    models: SelectedScannedModel[],
+  ) {
+    if (models.length === 0) return;
+
+    setIsSubmitting(true);
+    try {
+      for (const item of models) {
+        if (modelType === 'llm') {
+          await httpClient.createProviderLLMModel({
+            name: item.model.name,
+            provider_uuid: providerUuid,
+            abilities: item.abilities,
+            extra_args: {},
+          } as never);
+        } else {
+          await httpClient.createProviderEmbeddingModel({
+            name: item.model.name,
+            provider_uuid: providerUuid,
+            extra_args: {},
+          } as never);
+        }
+      }
+      setAddModelPopoverOpen(null);
+      loadProviderModels(providerUuid, true);
+      loadProviders();
+      toast.success(
+        t('models.addSelectedModelsSuccess', { count: models.length }),
+      );
+    } catch (err) {
+      toast.error(t('models.createError') + (err as CustomApiError).msg);
+    } finally {
+      setIsSubmitting(false);
+    }
+  }
+
  async function handleUpdateModel(
    providerUuid: string,
    modelId: string,
@@ -404,6 +460,10 @@ export default function ModelsDialog({
        onAddModel={(modelType, name, abilities, extraArgs) =>
          handleAddModel(provider.uuid, modelType, name, abilities, extraArgs)
        }
+        onScanModels={(modelType) => handleScanModels(provider.uuid, modelType)}
+        onAddScannedModels={(modelType, models) =>
+          handleAddScannedModels(provider.uuid, modelType, models)
+        }
        onOpenEditModel={(modelId) => setEditModelPopoverOpen(modelId)}
        onCloseEditModel={() => setEditModelPopoverOpen(null)}
        onUpdateModel={(modelId, modelType, name, abilities, extraArgs) =>
--- a/web/src/app/home/components/models-dialog/component/provider-form/ProviderForm.tsx
+++ b/web/src/app/home/components/models-dialog/component/provider-form/ProviderForm.tsx
@@ -169,8 +169,6 @@ export default function ProviderForm({
                  onValueChange={(v) => {
                    field.onChange(v);
                    const req = requesterList.find((r) => r.value === v);
-                    // Auto-fill default URL when creating new provider
-                    // or when base_url is empty in edit mode
                    if (req && (!providerId || !form.getValues('base_url'))) {
                      form.setValue('base_url', req.defaultUrl);
                    }
--- a/web/src/app/home/components/models-dialog/components/AddModelPopover.tsx
+++ b/web/src/app/home/components/models-dialog/components/AddModelPopover.tsx
@@ -1,5 +1,14 @@
-import { useState, useEffect } from 'react';
-import { Plus, MessageSquareText, Cpu, Eye, Wrench, Check } from 'lucide-react';
+import { useState, useEffect, useRef } from 'react';
+import {
+  Plus,
+  MessageSquareText,
+  Cpu,
+  Eye,
+  Wrench,
+  Check,
+  RefreshCw,
+  Search,
+} from 'lucide-react';
 import { Button } from '@/components/ui/button';
 import { Input } from '@/components/ui/input';
 import { Label } from '@/components/ui/label';
@@ -11,7 +20,14 @@ import {
 } from '@/components/ui/popover';
 import { Tabs, TabsContent, TabsList, TabsTrigger } from '@/components/ui/tabs';
 import { useTranslation } from 'react-i18next';
-import { ExtraArg, ModelType, TestResult } from '../types';
+import { ScannedProviderModel } from '@/app/infra/entities/api';
+import {
+  ExtraArg,
+  ModelType,
+  ScanModelsResult,
+  SelectedScannedModel,
+  TestResult,
+} from '../types';
 import ExtraArgsEditor from './ExtraArgsEditor';

 interface AddModelPopoverProps {
@@ -24,6 +40,11 @@ interface AddModelPopoverProps {
    abilities: string[],
    extraArgs: ExtraArg[],
  ) => Promise<void>;
+  onScanModels: (modelType: ModelType) => Promise<ScanModelsResult>;
+  onAddScannedModels: (
+    modelType: ModelType,
+    models: SelectedScannedModel[],
+  ) => Promise<void>;
  onTestModel: (
    name: string,
    modelType: ModelType,
@@ -41,6 +62,8 @@ export default function AddModelPopover({
  onOpen,
  onClose,
  onAddModel,
+  onScanModels,
+  onAddScannedModels,
  onTestModel,
  isSubmitting,
  isTesting,
@@ -48,22 +71,44 @@ export default function AddModelPopover({
  onResetTestResult,
 }: AddModelPopoverProps) {
  const { t } = useTranslation();
+  const prevIsOpenRef = useRef(false);

  const [tab, setTab] = useState<ModelType>('llm');
+  const [mode, setMode] = useState<'manual' | 'scan'>('manual');
  const [name, setName] = useState('');
  const [abilities, setAbilities] = useState<string[]>([]);
  const [extraArgs, setExtraArgs] = useState<ExtraArg[]>([]);
+  const [scanLoading, setScanLoading] = useState(false);
+  const [scannedModels, setScannedModels] = useState<ScannedProviderModel[]>(
+    [],
+  );
+  const [selectedScannedModels, setSelectedScannedModels] = useState<
+    Record<string, SelectedScannedModel>
+  >({});
+  const [scanQuery, setScanQuery] = useState('');

-  // Reset form when popover opens
  useEffect(() => {
-    if (isOpen) {
+    const wasOpen = prevIsOpenRef.current;
+    if (isOpen && !wasOpen) {
      setTab('llm');
+      setMode('manual');
      setName('');
      setAbilities([]);
      setExtraArgs([]);
+      setScanLoading(false);
+      setScannedModels([]);
+      setSelectedScannedModels({});
+      setScanQuery('');
      onResetTestResult();
    }
-  }, [isOpen]);
+    prevIsOpenRef.current = isOpen;
+  }, [isOpen, onResetTestResult]);
+
+  useEffect(() => {
+    setScannedModels([]);
+    setSelectedScannedModels({});
+    setScanQuery('');
+  }, [tab, mode]);

  const handleAdd = async () => {
    await onAddModel(tab, name, abilities, extraArgs);
@@ -73,6 +118,50 @@ export default function AddModelPopover({
    await onTestModel(name, tab, tab === 'llm' ? abilities : [], extraArgs);
  };

+  const handleScan = async () => {
+    setScanLoading(true);
+    try {
+      const result = await onScanModels(tab);
+
+      // Enrich abilities from debug.response.data (e.g. features.tools.function_calling)
+      const debugData = (
+        result.debug?.response as { data?: Record<string, unknown>[] }
+      )?.data;
+      if (Array.isArray(debugData)) {
+        const debugMap = new Map<string, Record<string, unknown>>();
+        for (const item of debugData) {
+          if (typeof item?.id === 'string') {
+            debugMap.set(item.id, item);
+          }
+        }
+        for (const model of result.models) {
+          const debugItem = debugMap.get(model.id);
+          if (!debugItem) continue;
+          const features = debugItem.features as
+            | Record<string, unknown>
+            | undefined;
+          const tools = features?.tools as Record<string, unknown> | undefined;
+          if (tools?.function_calling === true) {
+            const abilities = new Set(model.abilities || []);
+            abilities.add('func_call');
+            model.abilities = [...abilities];
+          }
+        }
+      }
+
+      setScannedModels(result.models);
+      setSelectedScannedModels({});
+    } finally {
+      setScanLoading(false);
+    }
+  };
+
+  const handleAddScanned = async () => {
+    const selectedModels = Object.values(selectedScannedModels);
+    if (selectedModels.length === 0) return;
+    await onAddScannedModels(tab, selectedModels);
+  };
+
  const toggleAbility = (ability: string, checked: boolean) => {
    if (checked) {
      setAbilities([...abilities, ability]);
@@ -81,6 +170,76 @@ export default function AddModelPopover({
    }
  };

+  const toggleScannedModel = (
+    model: ScannedProviderModel,
+    checked: boolean,
+  ) => {
+    setSelectedScannedModels((prev) => {
+      const next = { ...prev };
+      if (checked) {
+        next[model.id] = {
+          model,
+          abilities:
+            model.type === 'llm'
+              ? prev[model.id]?.abilities || model.abilities || []
+              : [],
+        };
+      } else {
+        delete next[model.id];
+      }
+      return next;
+    });
+  };
+
+  const toggleScannedModelAbility = (
+    modelId: string,
+    ability: string,
+    checked: boolean,
+  ) => {
+    setSelectedScannedModels((prev) => {
+      const current = prev[modelId];
+      if (!current) return prev;
+
+      const nextAbilities = checked
+        ? [...current.abilities, ability]
+        : current.abilities.filter((item) => item !== ability);
+
+      return {
+        ...prev,
+        [modelId]: {
+          ...current,
+          abilities: nextAbilities,
+        },
+      };
+    });
+  };
+
+  const filteredScannedModels = scannedModels.filter((model) =>
+    model.name.toLowerCase().includes(scanQuery.trim().toLowerCase()),
+  );
+
+  const selectableModels = filteredScannedModels.filter(
+    (m) => !m.already_added,
+  );
+  const allSelected =
+    selectableModels.length > 0 &&
+    selectableModels.every((m) => Boolean(selectedScannedModels[m.id]));
+
+  const toggleSelectAll = () => {
+    if (allSelected) {
+      setSelectedScannedModels({});
+    } else {
+      const next: Record<string, SelectedScannedModel> = {};
+      for (const model of selectableModels) {
+        next[model.id] = {
+          model,
+          abilities: model.type === 'llm' ? model.abilities || [] : [],
+        };
+      }
+      setSelectedScannedModels(next);
+    }
+  };
+
  return (
    <Popover
      open={isOpen}
@@ -98,8 +257,11 @@ export default function AddModelPopover({
        </Button>
      </PopoverTrigger>
      <PopoverContent
-        className="w-80"
+        className="w-[min(24rem,calc(100vw-2rem))] max-h-[calc(100vh-8rem)] overflow-y-auto"
        align="end"
+        side="left"
+        sideOffset={8}
+        collisionPadding={16}
        onClick={(e) => e.stopPropagation()}
      >
        <Tabs value={tab} onValueChange={(v) => setTab(v as ModelType)}>
@@ -114,7 +276,17 @@ export default function AddModelPopover({
            </TabsTrigger>
          </TabsList>

-          <TabsContent value="llm" className="space-y-3 mt-3">
+          <Tabs
+            value={mode}
+            onValueChange={(v) => setMode(v as 'manual' | 'scan')}
+          >
+            <TabsList className="grid w-full grid-cols-2 mt-3">
+              <TabsTrigger value="manual">{t('models.manualAdd')}</TabsTrigger>
+              <TabsTrigger value="scan">{t('models.scanAdd')}</TabsTrigger>
+            </TabsList>
+
+            <TabsContent value="manual" className="mt-3">
+              <div className="space-y-3">
                <div className="space-y-2">
                  <Label>{t('models.modelName')}</Label>
                  <Input
@@ -123,6 +295,8 @@ export default function AddModelPopover({
                    onChange={(e) => setName(e.target.value)}
                  />
                </div>
+
+                {tab === 'llm' && (
                  <div className="space-y-2">
                    <Label>{t('models.abilities')}</Label>
                    <div className="flex gap-4">
@@ -154,6 +328,8 @@ export default function AddModelPopover({
                      </div>
                    </div>
                  </div>
+                )}
+
                <ExtraArgsEditor args={extraArgs} onChange={setExtraArgs} />
                <div className="flex gap-2">
                  <Button
@@ -183,48 +359,178 @@ export default function AddModelPopover({
                    )}
                  </Button>
                </div>
+              </div>
            </TabsContent>

-          <TabsContent value="embedding" className="space-y-3 mt-3">
-            <div className="space-y-2">
-              <Label>{t('models.modelName')}</Label>
-              <Input
-                placeholder={t('models.modelName')}
-                value={name}
-                onChange={(e) => setName(e.target.value)}
-              />
+            <TabsContent value="scan" className="space-y-3 mt-3">
+              <div className="text-xs text-muted-foreground">
+                {t('models.scanModelsHint')}
              </div>
-            <ExtraArgsEditor args={extraArgs} onChange={setExtraArgs} />
+
              <div className="flex gap-2">
                <Button
                  className="flex-1"
                  size="sm"
-                onClick={handleAdd}
-                disabled={isSubmitting || isTesting}
+                  variant="outline"
+                  onClick={handleScan}
+                  disabled={scanLoading || isSubmitting}
                >
-                {isSubmitting ? t('common.saving') : t('common.add')}
+                  {scanLoading ? (
+                    <RefreshCw className="h-4 w-4 mr-1 animate-spin" />
+                  ) : (
+                    <Search className="h-4 w-4 mr-1" />
+                  )}
+                  {t('models.scanModels')}
                </Button>
                <Button
                  className="flex-1"
                  size="sm"
-                variant="outline"
-                onClick={handleTest}
-                disabled={isSubmitting || isTesting}
+                  onClick={handleAddScanned}
+                  disabled={
+                    isSubmitting ||
+                    scanLoading ||
+                    Object.keys(selectedScannedModels).length === 0
+                  }
                >
-                {isTesting ? (
-                  t('common.loading')
-                ) : testResult?.success ? (
-                  <>
-                    <Check className="h-4 w-4 mr-1 text-green-500" />
-                    {(testResult.duration / 1000).toFixed(1)}s
-                  </>
-                ) : (
-                  t('common.test')
-                )}
+                  {isSubmitting
+                    ? t('common.saving')
+                    : t('models.addSelectedModels')}
                </Button>
              </div>
+
+              <div className="space-y-2">
+                <Label>{t('models.scannedModels')}</Label>
+                <Input
+                  placeholder={t('models.searchScannedModels')}
+                  value={scanQuery}
+                  onChange={(e) => setScanQuery(e.target.value)}
+                  disabled={scannedModels.length === 0}
+                />
+                {selectableModels.length > 0 && (
+                  <div className="flex items-center gap-2 pt-1">
+                    <Checkbox
+                      id="scan-select-all"
+                      checked={allSelected}
+                      onCheckedChange={toggleSelectAll}
+                    />
+                    <Label
+                      htmlFor="scan-select-all"
+                      className="text-sm font-medium"
+                    >
+                      {t('models.selectAll')}
+                      <span className="text-muted-foreground ml-1">
+                        ({Object.keys(selectedScannedModels).length}/
+                        {selectableModels.length})
+                      </span>
+                    </Label>
+                  </div>
+                )}
+              </div>
+
+              <div
+                className="h-64 overflow-y-auto overscroll-contain rounded-md border"
+                onWheel={(e) => e.stopPropagation()}
+              >
+                <div className="p-3 space-y-2">
+                  {filteredScannedModels.length === 0 ? (
+                    <p className="text-sm text-muted-foreground">
+                      {scannedModels.length === 0
+                        ? t('models.noScannedModels')
+                        : t('models.noScannedModelsMatch')}
+                    </p>
+                  ) : (
+                    filteredScannedModels.map((model) => {
+                      const isSelected = Boolean(
+                        selectedScannedModels[model.id],
+                      );
+                      const selectedAbilities =
+                        selectedScannedModels[model.id]?.abilities || [];
+                      return (
+                        <div
+                          key={model.id}
+                          className="rounded-md border p-3 space-y-2"
+                        >
+                          <div className="flex items-start gap-3">
+                            <Checkbox
+                              checked={isSelected || model.already_added}
+                              disabled={model.already_added}
+                              onCheckedChange={(checked) =>
+                                toggleScannedModel(model, checked as boolean)
+                              }
+                            />
+                            <div className="min-w-0 flex-1">
+                              <div className="text-sm font-medium break-all">
+                                {model.name}
+                              </div>
+                              <div className="text-xs text-muted-foreground">
+                                {model.already_added
+                                  ? t('models.alreadyAdded')
+                                  : model.type === 'llm'
+                                    ? t('models.chat')
+                                    : t('models.embedding')}
+                              </div>
+                            </div>
+                          </div>
+
+                          {tab === 'llm' &&
+                            isSelected &&
+                            !model.already_added && (
+                              <div className="flex gap-4 pl-7">
+                                <div className="flex items-center gap-2">
+                                  <Checkbox
+                                    id={`scan-vision-${model.id}`}
+                                    checked={selectedAbilities.includes(
+                                      'vision',
+                                    )}
+                                    onCheckedChange={(checked) =>
+                                      toggleScannedModelAbility(
+                                        model.id,
+                                        'vision',
+                                        checked as boolean,
+                                      )
+                                    }
+                                  />
+                                  <Label
+                                    htmlFor={`scan-vision-${model.id}`}
+                                    className="text-sm"
+                                  >
+                                    <Eye className="h-3 w-3 inline mr-1" />
+                                    {t('models.visionAbility')}
+                                  </Label>
+                                </div>
+                                <div className="flex items-center gap-2">
+                                  <Checkbox
+                                    id={`scan-func-${model.id}`}
+                                    checked={selectedAbilities.includes(
+                                      'func_call',
+                                    )}
+                                    onCheckedChange={(checked) =>
+                                      toggleScannedModelAbility(
+                                        model.id,
+                                        'func_call',
+                                        checked as boolean,
+                                      )
+                                    }
+                                  />
+                                  <Label
+                                    htmlFor={`scan-func-${model.id}`}
+                                    className="text-sm"
+                                  >
+                                    <Wrench className="h-3 w-3 inline mr-1" />
+                                    {t('models.functionCallAbility')}
+                                  </Label>
+                                </div>
+                              </div>
+                            )}
+                        </div>
+                      );
+                    })
+                  )}
+                </div>
+              </div>
            </TabsContent>
          </Tabs>
+        </Tabs>
      </PopoverContent>
    </Popover>
  );
--- a/web/src/app/home/components/models-dialog/components/ProviderCard.tsx
+++ b/web/src/app/home/components/models-dialog/components/ProviderCard.tsx
@@ -24,7 +24,14 @@ import { Card, CardContent, CardHeader, CardTitle } from '@/components/ui/card';
 import { Badge } from '@/components/ui/badge';
 import { useTranslation } from 'react-i18next';
 import langbotIcon from '@/app/assets/langbot-logo.webp';
-import { ExtraArg, ModelType, TestResult, ProviderModels } from '../types';
+import {
+  ExtraArg,
+  ModelType,
+  ScanModelsResult,
+  SelectedScannedModel,
+  TestResult,
+  ProviderModels,
+} from '../types';
 import ModelItem from './ModelItem';
 import AddModelPopover from './AddModelPopover';

@@ -53,6 +60,11 @@ interface ProviderCardProps {
    abilities: string[],
    extraArgs: ExtraArg[],
  ) => Promise<void>;
+  onScanModels: (modelType: ModelType) => Promise<ScanModelsResult>;
+  onAddScannedModels: (
+    modelType: ModelType,
+    models: SelectedScannedModel[],
+  ) => Promise<void>;
  onOpenEditModel: (modelId: string) => void;
  onCloseEditModel: () => void;
  onUpdateModel: (
@@ -101,6 +113,8 @@ export default function ProviderCard({
  onOpenAddModel,
  onCloseAddModel,
  onAddModel,
+  onScanModels,
+  onAddScannedModels,
  onOpenEditModel,
  onCloseEditModel,
  onUpdateModel,
@@ -298,6 +312,8 @@ export default function ProviderCard({
                onOpen={onOpenAddModel}
                onClose={onCloseAddModel}
                onAddModel={onAddModel}
+                onScanModels={onScanModels}
+                onAddScannedModels={onAddScannedModels}
                onTestModel={onTestModel}
                isSubmitting={isSubmitting}
                isTesting={isTesting}
--- a/web/src/app/home/components/models-dialog/types.ts
+++ b/web/src/app/home/components/models-dialog/types.ts
@@ -2,6 +2,8 @@ import {
  LLMModel,
  EmbeddingModel,
  ModelProvider,
+  ProviderScanDebugInfo,
+  ScannedProviderModel,
 } from '@/app/infra/entities/api';

 export type ExtraArg = {
@@ -22,6 +24,16 @@ export interface TestResult {
  duration: number;
 }

+export type SelectedScannedModel = {
+  model: ScannedProviderModel;
+  abilities: string[];
+};
+
+export type ScanModelsResult = {
+  models: ScannedProviderModel[];
+  debug?: ProviderScanDebugInfo;
+};
+
 export interface ModelItemProps {
  model: LLMModel | EmbeddingModel;
  modelType: ModelType;
@@ -75,6 +87,11 @@ export interface ProviderCardProps {
    abilities: string[],
    extraArgs: ExtraArg[],
  ) => Promise<void>;
+  onScanModels: (modelType: ModelType) => Promise<ScanModelsResult>;
+  onAddScannedModels: (
+    modelType: ModelType,
+    models: SelectedScannedModel[],
+  ) => Promise<void>;
  onOpenEditModel: (modelId: string) => void;
  onCloseEditModel: () => void;
  onUpdateModel: (
--- a/web/src/app/infra/entities/api/index.ts
+++ b/web/src/app/infra/entities/api/index.ts
@@ -61,6 +61,34 @@ export interface ApiRespModelProvider {
  provider: ModelProvider;
 }

+export interface ScannedProviderModel {
+  id: string;
+  name: string;
+  type: 'llm' | 'embedding';
+  abilities?: string[];
+  display_name?: string;
+  description?: string;
+  context_length?: number | null;
+  owned_by?: string;
+  input_modalities?: string[];
+  output_modalities?: string[];
+  already_added: boolean;
+}
+
+export interface ProviderScanDebugInfo {
+  request?: {
+    method?: string;
+    url?: string;
+    headers?: Record<string, string>;
+  };
+  response?: unknown;
+}
+
+export interface ApiRespScannedProviderModels {
+  models: ScannedProviderModel[];
+  debug?: ProviderScanDebugInfo;
+}
+
 export interface LLMModel {
  uuid: string;
  name: string;
--- a/web/src/app/infra/http/BackendClient.ts
+++ b/web/src/app/infra/http/BackendClient.ts
@@ -37,6 +37,7 @@ import {
  MCPServer,
  ApiRespModelProviders,
  ApiRespModelProvider,
+  ApiRespScannedProviderModels,
  ModelProvider,
  ApiRespKnowledgeEngines,
  ApiRespParsers,
@@ -106,6 +107,14 @@ export class BackendClient extends BaseHttpClient {
    return this.delete(`/api/v1/provider/providers/${uuid}`);
  }

+  public scanProviderModels(
+    uuid: string,
+    modelType?: 'llm' | 'embedding',
+  ): Promise<ApiRespScannedProviderModels> {
+    const params = modelType ? { type: modelType } : {};
+    return this.get(`/api/v1/provider/providers/${uuid}/scan-models`, params);
+  }
+
  // ============ Provider Model LLM ============
  public getProviderLLMModels(
    providerUuid?: string,
--- a/web/src/i18n/locales/en-US.ts
+++ b/web/src/i18n/locales/en-US.ts
@@ -181,6 +181,10 @@ const enUS = {
    mustBeValidNumber: 'Must be a valid number',
    mustBeTrueOrFalse: 'Must be true or false',
    requestURL: 'Request URL',
+    scanURL: 'Scan Models URL',
+    scanURLPlaceholder: 'Leave empty to use Request URL + /models',
+    scanURLDescription:
+      'Fill in the actual model-list endpoint when model scanning does not use the same address as model invocation.',
    apiKey: 'API Key',
    abilities: 'Abilities',
    selectModelAbilities: 'Select model abilities',
@@ -218,6 +222,20 @@ const enUS = {
    providerCount: '{{count}} providers',
    // New keys for provider-based structure
    addModel: 'Add Model',
+    manualAdd: 'Manual',
+    scanAdd: 'Scan',
+    scanModels: 'Scan Models',
+    scanModelsHint:
+      'Read available models from the current provider, then select which ones to add.',
+    scannedModels: 'Scanned Models',
+    scanDebug: 'Debug Info',
+    searchScannedModels: 'Search scanned models',
+    noScannedModels: 'No scan results yet. Click the button above to scan.',
+    noScannedModelsMatch: 'No matching models',
+    addSelectedModels: 'Add Selected',
+    addSelectedModelsSuccess: '{{count}} model(s) added',
+    selectAll: 'Select All',
+    alreadyAdded: 'Already added',
    addLLMModel: 'Add LLM Model',
    addEmbeddingModel: 'Add Embedding Model',
    provider: 'Provider',
--- a/web/src/i18n/locales/es-ES.ts
+++ b/web/src/i18n/locales/es-ES.ts
@@ -227,6 +227,20 @@ const esES = {
    providerCount: '{{count}} proveedores',
    // New keys for provider-based structure
    addModel: 'Añadir modelo',
+    manualAdd: 'Manual',
+    scanAdd: 'Escanear',
+    scanModels: 'Escanear modelos',
+    scanModelsHint:
+      'Lee los modelos disponibles del proveedor actual y luego elige cuáles agregar.',
+    scannedModels: 'Modelos detectados',
+    searchScannedModels: 'Buscar modelos detectados',
+    noScannedModels:
+      'Todavía no hay resultados. Pulsa el botón superior para escanear.',
+    noScannedModelsMatch: 'No hay modelos coincidentes',
+    addSelectedModels: 'Agregar seleccionados',
+    addSelectedModelsSuccess: 'Se agregaron {{count}} modelo(s)',
+    selectAll: 'Seleccionar todo',
+    alreadyAdded: 'Ya agregado',
    addLLMModel: 'Añadir modelo LLM',
    addEmbeddingModel: 'Añadir modelo Embedding',
    provider: 'Proveedor',
--- a/web/src/i18n/locales/ja-JP.ts
+++ b/web/src/i18n/locales/ja-JP.ts
@@ -221,6 +221,20 @@
      'ローカルモデルがありません。作成ボタンをクリックしてモデルを追加してください。',
    providerCount: '{{count}} 件のプロバイダー',
    addModel: 'モデルを追加',
+    manualAdd: '手動追加',
+    scanAdd: 'スキャン追加',
+    scanModels: 'モデルをスキャン',
+    scanModelsHint:
+      '現在のプロバイダーから利用可能なモデルを取得し、追加するモデルを選択します。',
+    scannedModels: 'スキャン結果',
+    searchScannedModels: 'スキャン結果を検索',
+    noScannedModels:
+      'まだスキャン結果がありません。上のボタンからスキャンしてください。',
+    noScannedModelsMatch: '一致するモデルがありません',
+    addSelectedModels: '選択したモデルを追加',
+    addSelectedModelsSuccess: '{{count}} 件のモデルを追加しました',
+    selectAll: 'すべて選択',
+    alreadyAdded: '追加済み',
    addLLMModel: 'LLMモデルを追加',
    addEmbeddingModel: '埋め込みモデルを追加',
    provider: 'プロバイダー',
--- a/web/src/i18n/locales/th-TH.ts
+++ b/web/src/i18n/locales/th-TH.ts
@@ -215,6 +215,19 @@ const thTH = {
    noLocalModels: 'ไม่มีโมเดลท้องถิ่น คลิกสร้างเพื่อเพิ่มโมเดล',
    providerCount: '{{count}} ผู้ให้บริการ',
    addModel: 'เพิ่มโมเดล',
+    manualAdd: 'เพิ่มเอง',
+    scanAdd: 'สแกน',
+    scanModels: 'สแกนโมเดล',
+    scanModelsHint:
+      'ดึงรายการโมเดลที่ใช้ได้จากผู้ให้บริการปัจจุบัน แล้วเลือกโมเดลที่ต้องการเพิ่ม',
+    scannedModels: 'ผลการสแกน',
+    searchScannedModels: 'ค้นหาผลการสแกน',
+    noScannedModels: 'ยังไม่มีผลการสแกน กดปุ่มด้านบนเพื่อเริ่มสแกน',
+    noScannedModelsMatch: 'ไม่พบโมเดลที่ตรงกัน',
+    addSelectedModels: 'เพิ่มที่เลือก',
+    addSelectedModelsSuccess: 'เพิ่มแล้ว {{count}} โมเดล',
+    selectAll: 'เลือกทั้งหมด',
+    alreadyAdded: 'เพิ่มแล้ว',
    addLLMModel: 'เพิ่มโมเดล LLM',
    addEmbeddingModel: 'เพิ่มโมเดล Embedding',
    provider: 'ผู้ให้บริการ',
--- a/web/src/i18n/locales/vi-VN.ts
+++ b/web/src/i18n/locales/vi-VN.ts
@@ -222,6 +222,19 @@ const viVN = {
    noLocalModels: 'Không có mô hình cục bộ. Nhấn Tạo để thêm mô hình.',
    providerCount: '{{count}} nhà cung cấp',
    addModel: 'Thêm mô hình',
+    manualAdd: 'Thủ công',
+    scanAdd: 'Quét',
+    scanModels: 'Quét mô hình',
+    scanModelsHint:
+      'Đọc danh sách mô hình khả dụng từ nhà cung cấp hiện tại rồi chọn mô hình cần thêm.',
+    scannedModels: 'Kết quả quét',
+    searchScannedModels: 'Tìm trong kết quả quét',
+    noScannedModels: 'Chưa có kết quả quét. Nhấn nút phía trên để bắt đầu.',
+    noScannedModelsMatch: 'Không có mô hình phù hợp',
+    addSelectedModels: 'Thêm mục đã chọn',
+    addSelectedModelsSuccess: 'Đã thêm {{count}} mô hình',
+    selectAll: 'Chọn tất cả',
+    alreadyAdded: 'Đã thêm',
    addLLMModel: 'Thêm mô hình LLM',
    addEmbeddingModel: 'Thêm mô hình Embedding',
    provider: 'Nhà cung cấp',
--- a/web/src/i18n/locales/zh-Hans.ts
+++ b/web/src/i18n/locales/zh-Hans.ts
@@ -173,6 +173,10 @@ const zhHans = {
    mustBeValidNumber: '必须是有效的数字',
    mustBeTrueOrFalse: '必须是 true 或 false',
    requestURL: '请求URL',
+    scanURL: '扫描模型地址',
+    scanURLPlaceholder: '留空则默认使用请求URL + /models',
+    scanURLDescription:
+      '当模型扫描接口与模型调用接口不是同一个地址时，在这里填写实际的模型列表接口。',
    apiKey: 'API Key',
    abilities: '能力',
    selectModelAbilities: '选择模型能力',
@@ -209,6 +213,19 @@ const zhHans = {
    providerCount: '共 {{count}} 个自定义供应商',
    // 供应商结构新增键
    addModel: '添加模型',
+    manualAdd: '手动添加',
+    scanAdd: '扫描添加',
+    scanModels: '扫描模型',
+    scanModelsHint: '从当前供应商接口读取可用模型，然后勾选要添加的模型。',
+    scannedModels: '扫描结果',
+    scanDebug: '调试信息',
+    searchScannedModels: '搜索扫描结果',
+    noScannedModels: '还没有扫描结果，点击上方按钮开始扫描。',
+    noScannedModelsMatch: '没有匹配的模型',
+    addSelectedModels: '添加所选模型',
+    addSelectedModelsSuccess: '已添加 {{count}} 个模型',
+    selectAll: '全选模型',
+    alreadyAdded: '已添加',
    addLLMModel: '添加对话模型',
    addEmbeddingModel: '添加嵌入模型',
    provider: '供应商',
--- a/web/src/i18n/locales/zh-Hant.ts
+++ b/web/src/i18n/locales/zh-Hant.ts
@@ -208,6 +208,18 @@ const zhHant = {
    noLocalModels: '暫無本地模型。點擊建立按鈕新增模型。',
    providerCount: '共 {{count}} 個供應商',
    addModel: '新增模型',
+    manualAdd: '手動添加',
+    scanAdd: '掃描添加',
+    scanModels: '掃描模型',
+    scanModelsHint: '從目前供應商介面讀取可用模型，然後勾選要添加的模型。',
+    scannedModels: '掃描結果',
+    searchScannedModels: '搜尋掃描結果',
+    noScannedModels: '尚無掃描結果，點擊上方按鈕開始掃描。',
+    noScannedModelsMatch: '沒有符合的模型',
+    addSelectedModels: '添加所選模型',
+    addSelectedModelsSuccess: '已添加 {{count}} 個模型',
+    selectAll: '全選模型',
+    alreadyAdded: '已添加',
    addLLMModel: '新增對話模型',
    addEmbeddingModel: '新增嵌入模型',
    provider: '供應商',