search results - search box reduce height to 60px

### Background

Currently, AutoGPT only supports ollama servers running locally. Often,
this is not the case as the ollama server could be running on a more
suited instance, such as a Jetson board. This PR adds "ollama host" to
the input of all LLM blocks, allowing users to select the ollama host
for the LLM blocks.

### Changes 🏗️

- Changes contained within blocks/llm.py:
    - Adding ollama host input to all LLM blocks
- Fixed incorrect parsing of prompt when passing to ollama in the
StructuredResponse block
    - Used ollama.Client instances to accomplish this.


### Testing 🔍

Tested all LLM blocks with Ollama remote hosts as well as with the
default localhost value.


### Related issues
https://github.com/Significant-Gravitas/AutoGPT/issues/8225

---------

Co-authored-by: Fried-Squid <Fried-Squid>
Co-authored-by: Toran Bruce Richards <toran.richards@gmail.com>
Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
Co-authored-by: Aarushi <50577581+aarushik93@users.noreply.github.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
Co-authored-by: Nicholas Tindle <nicktindle@outlook.com>

.github/dependabot.yml

@@ -7,6 +7,9 @@ updates:
       interval: "weekly"
     open-pull-requests-limit: 10
     target-branch: "dev"
+    commit-message:
+      prefix: "chore(libs/deps)"
+      prefix-development: "chore(libs/deps-dev)"
     groups:
       production-dependencies:
         dependency-type: "production"
@@ -26,6 +29,9 @@ updates:
       interval: "weekly"
     open-pull-requests-limit: 10
     target-branch: "dev"
+    commit-message:
+      prefix: "chore(backend/deps)"
+      prefix-development: "chore(backend/deps-dev)"
     groups:
       production-dependencies:
         dependency-type: "production"
@@ -38,7 +44,6 @@ updates:
         - "minor"
         - "patch"
 
-
   # frontend (Next.js project)
   - package-ecosystem: "npm"
     directory: "autogpt_platform/frontend"
@@ -46,6 +51,9 @@ updates:
       interval: "weekly"
     open-pull-requests-limit: 10
     target-branch: "dev"
+    commit-message:
+      prefix: "chore(frontend/deps)"
+      prefix-development: "chore(frontend/deps-dev)"
     groups:
       production-dependencies:
         dependency-type: "production"
@@ -58,7 +66,6 @@ updates:
         - "minor"
         - "patch"
 
-
   # infra (Terraform)
   - package-ecosystem: "terraform"
     directory: "autogpt_platform/infra"
@@ -66,6 +73,10 @@ updates:
       interval: "weekly"
     open-pull-requests-limit: 5
     target-branch: "dev"
+    commit-message:
+      prefix: "chore(infra/deps)"
+      prefix-development: "chore(infra/deps-dev)"
+
     groups:
       production-dependencies:
         dependency-type: "production"
@@ -78,7 +89,6 @@ updates:
         - "minor"
         - "patch"
 
-
   # market (Poetry project)
   - package-ecosystem: "pip"
     directory: "autogpt_platform/market"
@@ -86,6 +96,9 @@ updates:
       interval: "weekly"
     open-pull-requests-limit: 10
     target-branch: "dev"
+    commit-message:
+      prefix: "chore(market/deps)"
+      prefix-development: "chore(market/deps-dev)"
     groups:
       production-dependencies:
         dependency-type: "production"
@@ -146,6 +159,9 @@ updates:
       interval: "weekly"
     open-pull-requests-limit: 1
     target-branch: "dev"
+    commit-message:
+      prefix: "chore(platform/deps)"
+      prefix-development: "chore(platform/deps-dev)"
     groups:
       production-dependencies:
         dependency-type: "production"
@@ -166,6 +182,8 @@ updates:
       interval: "weekly"
     open-pull-requests-limit: 1
     target-branch: "dev"
+    commit-message:
+      prefix: "chore(docs/deps)"
     groups:
       production-dependencies:
         dependency-type: "production"

.github/workflows/platform-backend-ci.yml

@@ -6,11 +6,13 @@ on:
     paths:
       - ".github/workflows/platform-backend-ci.yml"
       - "autogpt_platform/backend/**"
+      - "autogpt_platform/autogpt_libs/**"
   pull_request:
     branches: [master, dev, release-*]
     paths:
       - ".github/workflows/platform-backend-ci.yml"
       - "autogpt_platform/backend/**"
+      - "autogpt_platform/autogpt_libs/**"
   merge_group:
 
 concurrency:
@@ -77,6 +79,17 @@ jobs:
             echo "$HOME/.local/bin" >> $GITHUB_PATH
           fi
 
+      - name: Check poetry.lock
+        run: |
+          poetry lock --no-update
+
+          if ! git diff --quiet poetry.lock; then
+            echo "Error: poetry.lock not up to date."
+            echo
+            git diff poetry.lock
+            exit 1
+          fi
+
       - name: Install Python dependencies
         run: poetry install
 

.github/workflows/platform-frontend-ci.yml

@@ -23,6 +23,7 @@ jobs:
 
     steps:
       - uses: actions/checkout@v4
+
       - name: Set up Node.js
         uses: actions/setup-node@v4
         with:
@@ -38,24 +39,12 @@ jobs:
 
   test:
     runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        browser: [chromium, firefox, webkit]
 
     steps:
-      - name: Free Disk Space (Ubuntu)
-        uses: jlumbroso/free-disk-space@main
-        with:
-          # this might remove tools that are actually needed,
-          # if set to "true" but frees about 6 GB
-          tool-cache: false
-
-          # all of these default to true, but feel free to set to
-          # "false" if necessary for your workflow
-          android: false
-          dotnet: false
-          haskell: false
-          large-packages: true
-          docker-images: true
-          swap-storage: true
-
       - name: Checkout repository
         uses: actions/checkout@v4
         with:
@@ -66,6 +55,12 @@ jobs:
         with:
           node-version: "21"
 
+      - name: Free Disk Space (Ubuntu)
+        uses: jlumbroso/free-disk-space@main
+        with:
+          large-packages: false  # slow
+          docker-images: false  # limited benefit
+
       - name: Copy default supabase .env
         run: |
           cp ../supabase/docker/.env.example ../.env
@@ -86,16 +81,16 @@ jobs:
         run: |
           cp .env.example .env
 
-      - name: Install Playwright Browsers
-        run: yarn playwright install --with-deps
+      - name: Install Browser '${{ matrix.browser }}'
+        run: yarn playwright install --with-deps ${{ matrix.browser }}
 
       - name: Run tests
         run: |
-          yarn test
+          yarn test --project=${{ matrix.browser }}
 
       - uses: actions/upload-artifact@v4
         if: ${{ !cancelled() }}
         with:
-          name: playwright-report
+          name: playwright-report-${{ matrix.browser }}
           path: playwright-report/
           retention-days: 30

.gitignore

@@ -173,3 +173,6 @@ LICENSE.rtf
 autogpt_platform/backend/settings.py
 /.auth
 /autogpt_platform/frontend/.auth
+
+*.ign.*
+.test-contents

.pre-commit-config.yaml

@@ -98,6 +98,11 @@ repos:
         files: ^autogpt_platform/autogpt_libs/
         args: [--fix]
 
+      - id: ruff-format
+        name: Format (Ruff) - AutoGPT Platform - Libs
+        alias: ruff-lint-platform-libs
+        files: ^autogpt_platform/autogpt_libs/
+
   - repo: local
     # isort needs the context of which packages are installed to function, so we
     # can't use a vendored isort pre-commit hook (which runs in its own isolated venv).
@@ -140,7 +145,7 @@ repos:
     # everything in .gitignore, so it works fine without any config or arguments.
     hooks:
       - id: black
-        name: Lint (Black)
+        name: Format (Black)
 
   - repo: https://github.com/PyCQA/flake8
     rev: 7.0.0

SECURITY.md

@@ -8,7 +8,7 @@ We take the security of our project seriously. If you believe you have found a s
 
 Instead, please report them via:
 - [GitHub Security Advisory](https://github.com/Significant-Gravitas/AutoGPT/security/advisories/new)
-- [Huntr.dev](https://huntr.com/repos/significant-gravitas/autogpt) - where you may be eligible for a bounty
+<!--- [Huntr.dev](https://huntr.com/repos/significant-gravitas/autogpt) - where you may be eligible for a bounty-->
 
 ### Reporting Process
 1. **Submit Report**: Use one of the above channels to submit your report

autogpt_platform/autogpt_libs/autogpt_libs/auth/depends.py

@@ -35,3 +35,12 @@ def verify_user(payload: dict | None, admin_only: bool) -> User:
         raise fastapi.HTTPException(status_code=403, detail="Admin access required")
 
     return User.from_payload(payload)
+
+
+def get_user_id(payload: dict = fastapi.Depends(auth_middleware)) -> str:
+    user_id = payload.get("sub")
+    if not user_id:
+        raise fastapi.HTTPException(
+            status_code=401, detail="User ID not found in token"
+        )
+    return user_id

autogpt_platform/autogpt_libs/autogpt_libs/feature_flag/client.py

@@ -72,7 +72,7 @@ def feature_flag(
     """
 
     def decorator(
-        func: Callable[P, Union[T, Awaitable[T]]]
+        func: Callable[P, Union[T, Awaitable[T]]],
     ) -> Callable[P, Union[T, Awaitable[T]]]:
         @wraps(func)
         async def async_wrapper(*args: P.args, **kwargs: P.kwargs) -> T:

autogpt_platform/autogpt_libs/autogpt_libs/feature_flag/client_test.py

@@ -1,7 +1,8 @@
 import pytest
-from autogpt_libs.feature_flag.client import feature_flag, mock_flag_variation
 from ldclient import LDClient
 
+from autogpt_libs.feature_flag.client import feature_flag, mock_flag_variation
+
 
 @pytest.fixture
 def ld_client(mocker):

autogpt_platform/autogpt_libs/autogpt_libs/feature_flag/config.py

@@ -6,7 +6,7 @@ class Settings(BaseSettings):
     launch_darkly_sdk_key: str = Field(
         default="",
         description="The Launch Darkly SDK key",
-        validation_alias="LAUNCH_DARKLY_SDK_KEY"
+        validation_alias="LAUNCH_DARKLY_SDK_KEY",
     )
 
     model_config = SettingsConfigDict(case_sensitive=True, extra="ignore")

autogpt_platform/autogpt_libs/autogpt_libs/logging/config.py

@@ -23,7 +23,6 @@ DEBUG_LOG_FORMAT = (
 
 
 class LoggingConfig(BaseSettings):
-
     level: str = Field(
         default="INFO",
         description="Logging level",

autogpt_platform/autogpt_libs/autogpt_libs/logging/test_utils.py

@@ -24,10 +24,10 @@ from .utils import remove_color_codes
         ),
         ("", ""),
         ("hello", "hello"),
-        ("hello\x1B[31m world", "hello world"),
-        ("\x1B[36mHello,\x1B[32m World!", "Hello, World!"),
+        ("hello\x1b[31m world", "hello world"),
+        ("\x1b[36mHello,\x1b[32m World!", "Hello, World!"),
         (
-            "\x1B[1m\x1B[31mError:\x1B[0m\x1B[31m file not found",
+            "\x1b[1m\x1b[31mError:\x1b[0m\x1b[31m file not found",
             "Error: file not found",
         ),
     ],

autogpt_platform/autogpt_libs/autogpt_libs/rate_limit/config.py

@@ -0,0 +1,31 @@
+from pydantic import Field
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+
+class RateLimitSettings(BaseSettings):
+    redis_host: str = Field(
+        default="redis://localhost:6379",
+        description="Redis host",
+        validation_alias="REDIS_HOST",
+    )
+
+    redis_port: str = Field(
+        default="6379", description="Redis port", validation_alias="REDIS_PORT"
+    )
+
+    redis_password: str = Field(
+        default="password",
+        description="Redis password",
+        validation_alias="REDIS_PASSWORD",
+    )
+
+    requests_per_minute: int = Field(
+        default=60,
+        description="Maximum number of requests allowed per minute per API key",
+        validation_alias="RATE_LIMIT_REQUESTS_PER_MINUTE",
+    )
+
+    model_config = SettingsConfigDict(case_sensitive=True, extra="ignore")
+
+
+RATE_LIMIT_SETTINGS = RateLimitSettings()

autogpt_platform/autogpt_libs/autogpt_libs/rate_limit/limiter.py

@@ -0,0 +1,51 @@
+import time
+from typing import Tuple
+
+from redis import Redis
+
+from .config import RATE_LIMIT_SETTINGS
+
+
+class RateLimiter:
+    def __init__(
+        self,
+        redis_host: str = RATE_LIMIT_SETTINGS.redis_host,
+        redis_port: str = RATE_LIMIT_SETTINGS.redis_port,
+        redis_password: str = RATE_LIMIT_SETTINGS.redis_password,
+        requests_per_minute: int = RATE_LIMIT_SETTINGS.requests_per_minute,
+    ):
+        self.redis = Redis(
+            host=redis_host,
+            port=int(redis_port),
+            password=redis_password,
+            decode_responses=True,
+        )
+        self.window = 60
+        self.max_requests = requests_per_minute
+
+    async def check_rate_limit(self, api_key_id: str) -> Tuple[bool, int, int]:
+        """
+        Check if request is within rate limits.
+
+        Args:
+            api_key_id: The API key identifier to check
+
+        Returns:
+            Tuple of (is_allowed, remaining_requests, reset_time)
+        """
+        now = time.time()
+        window_start = now - self.window
+        key = f"ratelimit:{api_key_id}:1min"
+
+        pipe = self.redis.pipeline()
+        pipe.zremrangebyscore(key, 0, window_start)
+        pipe.zadd(key, {str(now): now})
+        pipe.zcount(key, window_start, now)
+        pipe.expire(key, self.window)
+
+        _, _, request_count, _ = pipe.execute()
+
+        remaining = max(0, self.max_requests - request_count)
+        reset_time = int(now + self.window)
+
+        return request_count <= self.max_requests, remaining, reset_time

autogpt_platform/autogpt_libs/autogpt_libs/rate_limit/middleware.py

@@ -0,0 +1,32 @@
+from fastapi import HTTPException, Request
+from starlette.middleware.base import RequestResponseEndpoint
+
+from .limiter import RateLimiter
+
+
+async def rate_limit_middleware(request: Request, call_next: RequestResponseEndpoint):
+    """FastAPI middleware for rate limiting API requests."""
+    limiter = RateLimiter()
+
+    if not request.url.path.startswith("/api"):
+        return await call_next(request)
+
+    api_key = request.headers.get("Authorization")
+    if not api_key:
+        return await call_next(request)
+
+    api_key = api_key.replace("Bearer ", "")
+
+    is_allowed, remaining, reset_time = await limiter.check_rate_limit(api_key)
+
+    if not is_allowed:
+        raise HTTPException(
+            status_code=429, detail="Rate limit exceeded. Please try again later."
+        )
+
+    response = await call_next(request)
+    response.headers["X-RateLimit-Limit"] = str(limiter.max_requests)
+    response.headers["X-RateLimit-Remaining"] = str(remaining)
+    response.headers["X-RateLimit-Reset"] = str(reset_time)
+
+    return response

autogpt_platform/autogpt_libs/poetry.lock

@@ -1091,19 +1091,22 @@ pyasn1 = ">=0.4.6,<0.7.0"
 
 [[package]]
 name = "pydantic"
-version = "2.10.2"
+version = "2.9.2"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic-2.10.2-py3-none-any.whl", hash = "sha256:cfb96e45951117c3024e6b67b25cdc33a3cb7b2fa62e239f7af1378358a1d99e"},
-    {file = "pydantic-2.10.2.tar.gz", hash = "sha256:2bc2d7f17232e0841cbba4641e65ba1eb6fafb3a08de3a091ff3ce14a197c4fa"},
+    {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"},
+    {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"},
 ]
 
 [package.dependencies]
 annotated-types = ">=0.6.0"
-pydantic-core = "2.27.1"
-typing-extensions = ">=4.12.2"
+pydantic-core = "2.23.4"
+typing-extensions = [
+    {version = ">=4.12.2", markers = "python_version >= \"3.13\""},
+    {version = ">=4.6.1", markers = "python_version < \"3.13\""},
+]
 
 [package.extras]
 email = ["email-validator (>=2.0.0)"]
@@ -1111,111 +1114,100 @@ timezone = ["tzdata"]
 
 [[package]]
 name = "pydantic-core"
-version = "2.27.1"
+version = "2.23.4"
 description = "Core functionality for Pydantic validation and serialization"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pydantic_core-2.27.1-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:71a5e35c75c021aaf400ac048dacc855f000bdfed91614b4a726f7432f1f3d6a"},
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-    {file = "ruff-0.8.0-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:87a8e86bae0dbd749c815211ca11e3a7bd559b9710746c559ed63106d382bd9c"},
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-    {file = "ruff-0.8.0-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:780d5d8523c04202184405e60c98d7595bdb498c3c6abba3b6d4cdf2ca2af426"},
-    {file = "ruff-0.8.0-py3-none-win32.whl", hash = "sha256:5fdb6efecc3eb60bba5819679466471fd7d13c53487df7248d6e27146e985468"},
-    {file = "ruff-0.8.0-py3-none-win_amd64.whl", hash = "sha256:582891c57b96228d146725975fbb942e1f30a0c4ba19722e692ca3eb25cc9b4f"},
-    {file = "ruff-0.8.0-py3-none-win_arm64.whl", hash = "sha256:ba93e6294e9a737cd726b74b09a6972e36bb511f9a102f1d9a7e1ce94dd206a6"},
-    {file = "ruff-0.8.0.tar.gz", hash = "sha256:a7ccfe6331bf8c8dad715753e157457faf7351c2b69f62f32c165c2dbcbacd44"},
+    {file = "ruff-0.8.2-py3-none-linux_armv6l.whl", hash = "sha256:c49ab4da37e7c457105aadfd2725e24305ff9bc908487a9bf8d548c6dad8bb3d"},
+    {file = "ruff-0.8.2-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:ec016beb69ac16be416c435828be702ee694c0d722505f9c1f35e1b9c0cc1bf5"},
+    {file = "ruff-0.8.2-py3-none-macosx_11_0_arm64.whl", hash = "sha256:f05cdf8d050b30e2ba55c9b09330b51f9f97d36d4673213679b965d25a785f3c"},
+    {file = "ruff-0.8.2-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:60f578c11feb1d3d257b2fb043ddb47501ab4816e7e221fbb0077f0d5d4e7b6f"},
+    {file = "ruff-0.8.2-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:cbd5cf9b0ae8f30eebc7b360171bd50f59ab29d39f06a670b3e4501a36ba5897"},
+    {file = "ruff-0.8.2-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b402ddee3d777683de60ff76da801fa7e5e8a71038f57ee53e903afbcefdaa58"},
+    {file = "ruff-0.8.2-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:705832cd7d85605cb7858d8a13d75993c8f3ef1397b0831289109e953d833d29"},
+    {file = "ruff-0.8.2-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:32096b41aaf7a5cc095fa45b4167b890e4c8d3fd217603f3634c92a541de7248"},
+    {file = "ruff-0.8.2-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e769083da9439508833cfc7c23e351e1809e67f47c50248250ce1ac52c21fb93"},
+    {file = "ruff-0.8.2-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5fe716592ae8a376c2673fdfc1f5c0c193a6d0411f90a496863c99cd9e2ae25d"},
+    {file = "ruff-0.8.2-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:81c148825277e737493242b44c5388a300584d73d5774defa9245aaef55448b0"},
+    {file = "ruff-0.8.2-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:d261d7850c8367704874847d95febc698a950bf061c9475d4a8b7689adc4f7fa"},
+    {file = "ruff-0.8.2-py3-none-musllinux_1_2_i686.whl", hash = "sha256:1ca4e3a87496dc07d2427b7dd7ffa88a1e597c28dad65ae6433ecb9f2e4f022f"},
+    {file = "ruff-0.8.2-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:729850feed82ef2440aa27946ab39c18cb4a8889c1128a6d589ffa028ddcfc22"},
+    {file = "ruff-0.8.2-py3-none-win32.whl", hash = "sha256:ac42caaa0411d6a7d9594363294416e0e48fc1279e1b0e948391695db2b3d5b1"},
+    {file = "ruff-0.8.2-py3-none-win_amd64.whl", hash = "sha256:2aae99ec70abf43372612a838d97bfe77d45146254568d94926e8ed5bbb409ea"},
+    {file = "ruff-0.8.2-py3-none-win_arm64.whl", hash = "sha256:fb88e2a506b70cfbc2de6fae6681c4f944f7dd5f2fe87233a7233d888bad73e8"},
+    {file = "ruff-0.8.2.tar.gz", hash = "sha256:b84f4f414dda8ac7f75075c1fa0b905ac0ff25361f42e6d5da681a465e0f78e5"},
 ]
 
 [[package]]
@@ -1852,4 +1844,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<4.0"
-content-hash = "54bf6e076ec4d09be2307f07240018459dd6594efdc55a2dc2dc1d673184587e"
+content-hash = "2d92dded4ebeff76a3d1dd0bb6b348e8177f053918141b4c4828442da318a907"

autogpt_platform/autogpt_libs/pyproject.toml

@@ -10,7 +10,7 @@ packages = [{ include = "autogpt_libs" }]
 colorama = "^0.4.6"
 expiringdict = "^1.2.2"
 google-cloud-logging = "^3.11.3"
-pydantic = "^2.10.2"
+pydantic = "^2.9.2"
 pydantic-settings = "^2.6.1"
 pyjwt = "^2.10.0"
 pytest-asyncio = "^0.24.0"
@@ -20,8 +20,8 @@ python-dotenv = "^1.0.1"
 supabase = "^2.10.0"
 
 [tool.poetry.group.dev.dependencies]
-redis = "^5.2.0"
-ruff = "^0.8.0"
+redis = "^5.2.1"
+ruff = "^0.8.2"
 
 [build-system]
 requires = ["poetry-core"]

autogpt_platform/backend/Dockerfile

@@ -6,18 +6,23 @@ ENV PYTHONUNBUFFERED 1
 
 WORKDIR /app
 
+RUN echo 'Acquire::http::Pipeline-Depth 0;\nAcquire::http::No-Cache true;\nAcquire::BrokenProxy true;\n' > /etc/apt/apt.conf.d/99fixbadproxy
+
+RUN apt-get update --allow-releaseinfo-change --fix-missing
+
 # Install build dependencies
-RUN apt-get update \
-    && apt-get install -y build-essential curl ffmpeg wget libcurl4-gnutls-dev libexpat1-dev libpq5 gettext libz-dev libssl-dev postgresql-client git \
-    && apt-get clean \
-    && rm -rf /var/lib/apt/lists/*
-
-ENV POETRY_VERSION=1.8.3 \
-    POETRY_HOME="/opt/poetry" \
-    POETRY_NO_INTERACTION=1 \
-    POETRY_VIRTUALENVS_CREATE=false \
-    PATH="$POETRY_HOME/bin:$PATH"
+RUN apt-get install -y build-essential 
+RUN apt-get install -y libpq5
+RUN apt-get install -y libz-dev
+RUN apt-get install -y libssl-dev
+RUN apt-get install -y postgresql-client
 
+ENV POETRY_VERSION=1.8.3
+ENV POETRY_HOME=/opt/poetry
+ENV POETRY_NO_INTERACTION=1
+ENV POETRY_VIRTUALENVS_CREATE=false
+ENV PATH=/opt/poetry/bin:$PATH
+    
 # Upgrade pip and setuptools to fix security vulnerabilities
 RUN pip3 install --upgrade pip setuptools
 
@@ -39,11 +44,11 @@ FROM python:3.11.10-slim-bookworm AS server_dependencies
 
 WORKDIR /app
 
-ENV POETRY_VERSION=1.8.3 \
-    POETRY_HOME="/opt/poetry" \
-    POETRY_NO_INTERACTION=1 \
-    POETRY_VIRTUALENVS_CREATE=false \
-    PATH="$POETRY_HOME/bin:$PATH"
+ENV POETRY_VERSION=1.8.3
+ENV POETRY_HOME=/opt/poetry
+ENV POETRY_NO_INTERACTION=1
+ENV POETRY_VIRTUALENVS_CREATE=false
+ENV PATH=/opt/poetry/bin:$PATH
 
 
 # Upgrade pip and setuptools to fix security vulnerabilities

autogpt_platform/backend/README.md

@@ -200,4 +200,4 @@ To add a new agent block, you need to create a new class that inherits from `Blo
 * `run` method: the main logic of the block.
 * `test_input` & `test_output`: the sample input and output data for the block, which will be used to auto-test the block.
 * You can mock the functions declared in the block using the `test_mock` field for your unit tests.
-* Once you finish creating the block, you can test it by running `pytest -s test/block/test_block.py`.
+* Once you finish creating the block, you can test it by running `poetry run pytest -s test/block/test_block.py`.

autogpt_platform/backend/backend/blocks/__init__.py

@@ -15,10 +15,10 @@ modules = [
     if f.is_file() and f.name != "__init__.py"
 ]
 for module in modules:
-    if not re.match("^[a-z_.]+$", module):
+    if not re.match("^[a-z0-9_.]+$", module):
         raise ValueError(
             f"Block module {module} error: module name must be lowercase, "
-            "separated by underscores, and contain only alphabet characters"
+            "and contain only alphanumeric characters and underscores."
         )
 
     importlib.import_module(f".{module}", package=__name__)

autogpt_platform/backend/backend/blocks/ai_image_generator_block.py

@@ -12,6 +12,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 
 
 class ImageSize(str, Enum):
@@ -101,12 +102,10 @@ class ImageGenModel(str, Enum):
 
 class AIImageGeneratorBlock(Block):
     class Input(BlockSchema):
-        credentials: CredentialsMetaInput[Literal["replicate"], Literal["api_key"]] = (
-            CredentialsField(
-                provider="replicate",
-                supported_credential_types={"api_key"},
-                description="Enter your Replicate API key to access the image generation API. You can obtain an API key from https://replicate.com/account/api-tokens.",
-            )
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.REPLICATE], Literal["api_key"]
+        ] = CredentialsField(
+            description="Enter your Replicate API key to access the image generation API. You can obtain an API key from https://replicate.com/account/api-tokens.",
         )
         prompt: str = SchemaField(
             description="Text prompt for image generation",

autogpt_platform/backend/backend/blocks/ai_music_generator.py

@@ -13,6 +13,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 
 logger = logging.getLogger(__name__)
 
@@ -54,13 +55,11 @@ class NormalizationStrategy(str, Enum):
 
 class AIMusicGeneratorBlock(Block):
     class Input(BlockSchema):
-        credentials: CredentialsMetaInput[Literal["replicate"], Literal["api_key"]] = (
-            CredentialsField(
-                provider="replicate",
-                supported_credential_types={"api_key"},
-                description="The Replicate integration can be used with "
-                "any API key with sufficient permissions for the blocks it is used on.",
-            )
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.REPLICATE], Literal["api_key"]
+        ] = CredentialsField(
+            description="The Replicate integration can be used with "
+            "any API key with sufficient permissions for the blocks it is used on.",
         )
         prompt: str = SchemaField(
             description="A description of the music you want to generate",

autogpt_platform/backend/backend/blocks/ai_shortform_video_block.py

@@ -12,6 +12,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 from backend.util.request import requests
 
 TEST_CREDENTIALS = APIKeyCredentials(
@@ -140,13 +141,11 @@ logger = logging.getLogger(__name__)
 
 class AIShortformVideoCreatorBlock(Block):
     class Input(BlockSchema):
-        credentials: CredentialsMetaInput[Literal["revid"], Literal["api_key"]] = (
-            CredentialsField(
-                provider="revid",
-                supported_credential_types={"api_key"},
-                description="The revid.ai integration can be used with "
-                "any API key with sufficient permissions for the blocks it is used on.",
-            )
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.REVID], Literal["api_key"]
+        ] = CredentialsField(
+            description="The revid.ai integration can be used with "
+            "any API key with sufficient permissions for the blocks it is used on.",
         )
         script: str = SchemaField(
             description="""1. Use short and punctuated sentences\n\n2. Use linebreaks to create a new clip\n\n3. Text outside of brackets is spoken by the AI, and [text between brackets] will be used to guide the visual generation. For example, [close-up of a cat] will show a close-up of a cat.""",

autogpt_platform/backend/backend/blocks/basic.py

@@ -1,13 +1,11 @@
-import re
 from typing import Any, List
 
-from jinja2 import BaseLoader, Environment
-
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema, BlockType
 from backend.data.model import SchemaField
 from backend.util.mock import MockObject
+from backend.util.text import TextFormatter
 
-jinja = Environment(loader=BaseLoader())
+formatter = TextFormatter()
 
 
 class StoreValueBlock(Block):
@@ -304,9 +302,9 @@ class AgentOutputBlock(Block):
         """
         if input_data.format:
             try:
-                fmt = re.sub(r"(?<!{){[ a-zA-Z0-9_]+}", r"{\g<0>}", input_data.format)
-                template = jinja.from_string(fmt)
-                yield "output", template.render({input_data.name: input_data.value})
+                yield "output", formatter.format_string(
+                    input_data.format, {input_data.name: input_data.value}
+                )
             except Exception as e:
                 yield "output", f"Error: {e}, {input_data.value}"
         else:
@@ -494,3 +492,101 @@ class NoteBlock(Block):
 
     def run(self, input_data: Input, **kwargs) -> BlockOutput:
         yield "output", input_data.text
+
+
+class CreateDictionaryBlock(Block):
+    class Input(BlockSchema):
+        values: dict[str, Any] = SchemaField(
+            description="Key-value pairs to create the dictionary with",
+            placeholder="e.g., {'name': 'Alice', 'age': 25}",
+        )
+
+    class Output(BlockSchema):
+        dictionary: dict[str, Any] = SchemaField(
+            description="The created dictionary containing the specified key-value pairs"
+        )
+        error: str = SchemaField(
+            description="Error message if dictionary creation failed"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="b924ddf4-de4f-4b56-9a85-358930dcbc91",
+            description="Creates a dictionary with the specified key-value pairs. Use this when you know all the values you want to add upfront.",
+            categories={BlockCategory.DATA},
+            input_schema=CreateDictionaryBlock.Input,
+            output_schema=CreateDictionaryBlock.Output,
+            test_input=[
+                {
+                    "values": {"name": "Alice", "age": 25, "city": "New York"},
+                },
+                {
+                    "values": {"numbers": [1, 2, 3], "active": True, "score": 95.5},
+                },
+            ],
+            test_output=[
+                (
+                    "dictionary",
+                    {"name": "Alice", "age": 25, "city": "New York"},
+                ),
+                (
+                    "dictionary",
+                    {"numbers": [1, 2, 3], "active": True, "score": 95.5},
+                ),
+            ],
+        )
+
+    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        try:
+            # The values are already validated by Pydantic schema
+            yield "dictionary", input_data.values
+        except Exception as e:
+            yield "error", f"Failed to create dictionary: {str(e)}"
+
+
+class CreateListBlock(Block):
+    class Input(BlockSchema):
+        values: List[Any] = SchemaField(
+            description="A list of values to be combined into a new list.",
+            placeholder="e.g., ['Alice', 25, True]",
+        )
+
+    class Output(BlockSchema):
+        list: List[Any] = SchemaField(
+            description="The created list containing the specified values."
+        )
+        error: str = SchemaField(description="Error message if list creation failed.")
+
+    def __init__(self):
+        super().__init__(
+            id="a912d5c7-6e00-4542-b2a9-8034136930e4",
+            description="Creates a list with the specified values. Use this when you know all the values you want to add upfront.",
+            categories={BlockCategory.DATA},
+            input_schema=CreateListBlock.Input,
+            output_schema=CreateListBlock.Output,
+            test_input=[
+                {
+                    "values": ["Alice", 25, True],
+                },
+                {
+                    "values": [1, 2, 3, "four", {"key": "value"}],
+                },
+            ],
+            test_output=[
+                (
+                    "list",
+                    ["Alice", 25, True],
+                ),
+                (
+                    "list",
+                    [1, 2, 3, "four", {"key": "value"}],
+                ),
+            ],
+        )
+
+    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        try:
+            # The values are already validated by Pydantic schema
+            yield "list", input_data.values
+        except Exception as e:
+            yield "error", f"Failed to create list: {str(e)}"

autogpt_platform/backend/backend/blocks/code_executor.py

@@ -0,0 +1,190 @@
+from enum import Enum
+from typing import Literal
+
+from e2b_code_interpreter import Sandbox
+from pydantic import SecretStr
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import (
+    APIKeyCredentials,
+    CredentialsField,
+    CredentialsMetaInput,
+    SchemaField,
+)
+from backend.integrations.providers import ProviderName
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="e2b",
+    api_key=SecretStr("mock-e2b-api-key"),
+    title="Mock E2B API key",
+    expires_at=None,
+)
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.type,
+}
+
+
+class ProgrammingLanguage(Enum):
+    PYTHON = "python"
+    JAVASCRIPT = "js"
+    BASH = "bash"
+    R = "r"
+    JAVA = "java"
+
+
+class CodeExecutionBlock(Block):
+    # TODO : Add support to upload and download files
+    # Currently, You can customized the CPU and Memory, only by creating a pre customized sandbox template
+    class Input(BlockSchema):
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.E2B], Literal["api_key"]
+        ] = CredentialsField(
+            description="Enter your api key for the E2B Sandbox. You can get it in here - https://e2b.dev/docs",
+        )
+
+        # Todo : Option to run commond in background
+        setup_commands: list[str] = SchemaField(
+            description=(
+                "Shell commands to set up the sandbox before running the code. "
+                "You can use `curl` or `git` to install your desired Debian based "
+                "package manager. `pip` and `npm` are pre-installed.\n\n"
+                "These commands are executed with `sh`, in the foreground."
+            ),
+            placeholder="pip install cowsay",
+            default=[],
+            advanced=False,
+        )
+
+        code: str = SchemaField(
+            description="Code to execute in the sandbox",
+            placeholder="print('Hello, World!')",
+            default="",
+            advanced=False,
+        )
+
+        language: ProgrammingLanguage = SchemaField(
+            description="Programming language to execute",
+            default=ProgrammingLanguage.PYTHON,
+            advanced=False,
+        )
+
+        timeout: int = SchemaField(
+            description="Execution timeout in seconds", default=300
+        )
+
+        template_id: str = SchemaField(
+            description=(
+                "You can use an E2B sandbox template by entering its ID here. "
+                "Check out the E2B docs for more details: "
+                "[E2B - Sandbox template](https://e2b.dev/docs/sandbox-template)"
+            ),
+            default="",
+            advanced=True,
+        )
+
+    class Output(BlockSchema):
+        response: str = SchemaField(description="Response from code execution")
+        stdout_logs: str = SchemaField(
+            description="Standard output logs from execution"
+        )
+        stderr_logs: str = SchemaField(description="Standard error logs from execution")
+        error: str = SchemaField(description="Error message if execution failed")
+
+    def __init__(self):
+        super().__init__(
+            id="0b02b072-abe7-11ef-8372-fb5d162dd712",
+            description="Executes code in an isolated sandbox environment with internet access.",
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=CodeExecutionBlock.Input,
+            output_schema=CodeExecutionBlock.Output,
+            test_credentials=TEST_CREDENTIALS,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "code": "print('Hello World')",
+                "language": ProgrammingLanguage.PYTHON.value,
+                "setup_commands": [],
+                "timeout": 300,
+                "template_id": "",
+            },
+            test_output=[
+                ("response", "Hello World"),
+                ("stdout_logs", "Hello World\n"),
+            ],
+            test_mock={
+                "execute_code": lambda code, language, setup_commands, timeout, api_key, template_id: (
+                    "Hello World",
+                    "Hello World\n",
+                    "",
+                ),
+            },
+        )
+
+    def execute_code(
+        self,
+        code: str,
+        language: ProgrammingLanguage,
+        setup_commands: list[str],
+        timeout: int,
+        api_key: str,
+        template_id: str,
+    ):
+        try:
+            sandbox = None
+            if template_id:
+                sandbox = Sandbox(
+                    template=template_id, api_key=api_key, timeout=timeout
+                )
+            else:
+                sandbox = Sandbox(api_key=api_key, timeout=timeout)
+
+            if not sandbox:
+                raise Exception("Sandbox not created")
+
+            # Running setup commands
+            for cmd in setup_commands:
+                sandbox.commands.run(cmd)
+
+            # Executing the code
+            execution = sandbox.run_code(
+                code,
+                language=language.value,
+                on_error=lambda e: sandbox.kill(),  # Kill the sandbox if there is an error
+            )
+
+            if execution.error:
+                raise Exception(execution.error)
+
+            response = execution.text
+            stdout_logs = "".join(execution.logs.stdout)
+            stderr_logs = "".join(execution.logs.stderr)
+
+            return response, stdout_logs, stderr_logs
+
+        except Exception as e:
+            raise e
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            response, stdout_logs, stderr_logs = self.execute_code(
+                input_data.code,
+                input_data.language,
+                input_data.setup_commands,
+                input_data.timeout,
+                credentials.api_key.get_secret_value(),
+                input_data.template_id,
+            )
+
+            if response:
+                yield "response", response
+            if stdout_logs:
+                yield "stdout_logs", stdout_logs
+            if stderr_logs:
+                yield "stderr_logs", stderr_logs
+        except Exception as e:
+            yield "error", str(e)

autogpt_platform/backend/backend/blocks/code_extraction_block.py

@@ -0,0 +1,110 @@
+import re
+
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+
+
+class CodeExtractionBlock(Block):
+    class Input(BlockSchema):
+        text: str = SchemaField(
+            description="Text containing code blocks to extract (e.g., AI response)",
+            placeholder="Enter text containing code blocks",
+        )
+
+    class Output(BlockSchema):
+        html: str = SchemaField(description="Extracted HTML code")
+        css: str = SchemaField(description="Extracted CSS code")
+        javascript: str = SchemaField(description="Extracted JavaScript code")
+        python: str = SchemaField(description="Extracted Python code")
+        sql: str = SchemaField(description="Extracted SQL code")
+        java: str = SchemaField(description="Extracted Java code")
+        cpp: str = SchemaField(description="Extracted C++ code")
+        csharp: str = SchemaField(description="Extracted C# code")
+        json_code: str = SchemaField(description="Extracted JSON code")
+        bash: str = SchemaField(description="Extracted Bash code")
+        php: str = SchemaField(description="Extracted PHP code")
+        ruby: str = SchemaField(description="Extracted Ruby code")
+        yaml: str = SchemaField(description="Extracted YAML code")
+        markdown: str = SchemaField(description="Extracted Markdown code")
+        typescript: str = SchemaField(description="Extracted TypeScript code")
+        xml: str = SchemaField(description="Extracted XML code")
+        remaining_text: str = SchemaField(
+            description="Remaining text after code extraction"
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="d3a7d896-3b78-4f44-8b4b-48fbf4f0bcd8",
+            description="Extracts code blocks from text and identifies their programming languages",
+            categories={BlockCategory.TEXT},
+            input_schema=CodeExtractionBlock.Input,
+            output_schema=CodeExtractionBlock.Output,
+            test_input={
+                "text": "Here's a Python example:\n```python\nprint('Hello World')\n```\nAnd some HTML:\n```html\n<h1>Title</h1>\n```"
+            },
+            test_output=[
+                ("html", "<h1>Title</h1>"),
+                ("python", "print('Hello World')"),
+                ("remaining_text", "Here's a Python example:\nAnd some HTML:"),
+            ],
+        )
+
+    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        # List of supported programming languages with mapped aliases
+        language_aliases = {
+            "html": ["html", "htm"],
+            "css": ["css"],
+            "javascript": ["javascript", "js"],
+            "python": ["python", "py"],
+            "sql": ["sql"],
+            "java": ["java"],
+            "cpp": ["cpp", "c++"],
+            "csharp": ["csharp", "c#", "cs"],
+            "json_code": ["json"],
+            "bash": ["bash", "shell", "sh"],
+            "php": ["php"],
+            "ruby": ["ruby", "rb"],
+            "yaml": ["yaml", "yml"],
+            "markdown": ["markdown", "md"],
+            "typescript": ["typescript", "ts"],
+            "xml": ["xml"],
+        }
+
+        # Extract code for each language
+        for canonical_name, aliases in language_aliases.items():
+            code = ""
+            # Try each alias for the language
+            for alias in aliases:
+                code_for_alias = self.extract_code(input_data.text, alias)
+                if code_for_alias:
+                    code = code + "\n\n" + code_for_alias if code else code_for_alias
+
+            if code:  # Only yield if there's actual code content
+                yield canonical_name, code
+
+        # Remove all code blocks from the text to get remaining text
+        pattern = (
+            r"```(?:"
+            + "|".join(
+                re.escape(alias)
+                for aliases in language_aliases.values()
+                for alias in aliases
+            )
+            + r")\s+[\s\S]*?```"
+        )
+
+        remaining_text = re.sub(pattern, "", input_data.text).strip()
+        remaining_text = re.sub(r"\n\s*\n", "\n", remaining_text)
+
+        if remaining_text:  # Only yield if there's remaining text
+            yield "remaining_text", remaining_text
+
+    def extract_code(self, text: str, language: str) -> str:
+        # Escape special regex characters in the language string
+        language = re.escape(language)
+        # Extract all code blocks enclosed in ```language``` blocks
+        pattern = re.compile(rf"```{language}\s+(.*?)```", re.DOTALL | re.IGNORECASE)
+        matches = pattern.finditer(text)
+        # Combine all code blocks for this language with newlines between them
+        code_blocks = [match.group(1).strip() for match in matches]
+        return "\n\n".join(code_blocks) if code_blocks else ""

autogpt_platform/backend/backend/blocks/discord.py

@@ -12,16 +12,15 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 
-DiscordCredentials = CredentialsMetaInput[Literal["discord"], Literal["api_key"]]
+DiscordCredentials = CredentialsMetaInput[
+    Literal[ProviderName.DISCORD], Literal["api_key"]
+]
 
 
 def DiscordCredentialsField() -> DiscordCredentials:
-    return CredentialsField(
-        description="Discord bot token",
-        provider="discord",
-        supported_credential_types={"api_key"},
-    )
+    return CredentialsField(description="Discord bot token")
 
 
 TEST_CREDENTIALS = APIKeyCredentials(

autogpt_platform/backend/backend/blocks/exa/_auth.py

@@ -0,0 +1,32 @@
+from typing import Literal
+
+from pydantic import SecretStr
+
+from backend.data.model import APIKeyCredentials, CredentialsField, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
+
+ExaCredentials = APIKeyCredentials
+ExaCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.EXA],
+    Literal["api_key"],
+]
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="exa",
+    api_key=SecretStr("mock-exa-api-key"),
+    title="Mock Exa API key",
+    expires_at=None,
+)
+
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+
+def ExaCredentialsField() -> ExaCredentialsInput:
+    """Creates an Exa credentials input on a block."""
+    return CredentialsField(description="The Exa integration requires an API Key.")

autogpt_platform/backend/backend/blocks/exa/search.py

@@ -0,0 +1,157 @@
+from datetime import datetime
+from typing import List
+
+from pydantic import BaseModel
+
+from backend.blocks.exa._auth import (
+    ExaCredentials,
+    ExaCredentialsField,
+    ExaCredentialsInput,
+)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+from backend.util.request import requests
+
+
+class ContentSettings(BaseModel):
+    text: dict = SchemaField(
+        description="Text content settings",
+        default={"maxCharacters": 1000, "includeHtmlTags": False},
+    )
+    highlights: dict = SchemaField(
+        description="Highlight settings",
+        default={"numSentences": 3, "highlightsPerUrl": 3},
+    )
+    summary: dict = SchemaField(
+        description="Summary settings",
+        default={"query": ""},
+    )
+
+
+class ExaSearchBlock(Block):
+    class Input(BlockSchema):
+        credentials: ExaCredentialsInput = ExaCredentialsField()
+        query: str = SchemaField(description="The search query")
+        useAutoprompt: bool = SchemaField(
+            description="Whether to use autoprompt",
+            default=True,
+        )
+        type: str = SchemaField(
+            description="Type of search",
+            default="",
+        )
+        category: str = SchemaField(
+            description="Category to search within",
+            default="",
+        )
+        numResults: int = SchemaField(
+            description="Number of results to return",
+            default=10,
+        )
+        includeDomains: List[str] = SchemaField(
+            description="Domains to include in search",
+            default=[],
+        )
+        excludeDomains: List[str] = SchemaField(
+            description="Domains to exclude from search",
+            default=[],
+        )
+        startCrawlDate: datetime = SchemaField(
+            description="Start date for crawled content",
+        )
+        endCrawlDate: datetime = SchemaField(
+            description="End date for crawled content",
+        )
+        startPublishedDate: datetime = SchemaField(
+            description="Start date for published content",
+        )
+        endPublishedDate: datetime = SchemaField(
+            description="End date for published content",
+        )
+        includeText: List[str] = SchemaField(
+            description="Text patterns to include",
+            default=[],
+        )
+        excludeText: List[str] = SchemaField(
+            description="Text patterns to exclude",
+            default=[],
+        )
+        contents: ContentSettings = SchemaField(
+            description="Content retrieval settings",
+            default=ContentSettings(),
+        )
+
+    class Output(BlockSchema):
+        results: list = SchemaField(
+            description="List of search results",
+            default=[],
+        )
+
+    def __init__(self):
+        super().__init__(
+            id="996cec64-ac40-4dde-982f-b0dc60a5824d",
+            description="Searches the web using Exa's advanced search API",
+            categories={BlockCategory.SEARCH},
+            input_schema=ExaSearchBlock.Input,
+            output_schema=ExaSearchBlock.Output,
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: ExaCredentials, **kwargs
+    ) -> BlockOutput:
+        url = "https://api.exa.ai/search"
+        headers = {
+            "Content-Type": "application/json",
+            "x-api-key": credentials.api_key.get_secret_value(),
+        }
+
+        payload = {
+            "query": input_data.query,
+            "useAutoprompt": input_data.useAutoprompt,
+            "numResults": input_data.numResults,
+            "contents": {
+                "text": {"maxCharacters": 1000, "includeHtmlTags": False},
+                "highlights": {
+                    "numSentences": 3,
+                    "highlightsPerUrl": 3,
+                },
+                "summary": {"query": ""},
+            },
+        }
+
+        # Add dates if they exist
+        date_fields = [
+            "startCrawlDate",
+            "endCrawlDate",
+            "startPublishedDate",
+            "endPublishedDate",
+        ]
+        for field in date_fields:
+            value = getattr(input_data, field, None)
+            if value:
+                payload[field] = value.strftime("%Y-%m-%dT%H:%M:%S.000Z")
+
+        # Add other fields
+        optional_fields = [
+            "type",
+            "category",
+            "includeDomains",
+            "excludeDomains",
+            "includeText",
+            "excludeText",
+        ]
+
+        for field in optional_fields:
+            value = getattr(input_data, field)
+            if value:  # Only add non-empty values
+                payload[field] = value
+
+        try:
+            response = requests.post(url, headers=headers, json=payload)
+            response.raise_for_status()
+            data = response.json()
+            # Extract just the results array from the response
+            yield "results", data.get("results", [])
+        except Exception as e:
+            yield "error", str(e)
+            yield "results", []

autogpt_platform/backend/backend/blocks/fal/_auth.py

@@ -3,10 +3,11 @@ from typing import Literal
 from pydantic import SecretStr
 
 from backend.data.model import APIKeyCredentials, CredentialsField, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
 
 FalCredentials = APIKeyCredentials
 FalCredentialsInput = CredentialsMetaInput[
-    Literal["fal"],
+    Literal[ProviderName.FAL],
     Literal["api_key"],
 ]
 
@@ -30,7 +31,5 @@ def FalCredentialsField() -> FalCredentialsInput:
     Creates a FAL credentials input on a block.
     """
     return CredentialsField(
-        provider="fal",
-        supported_credential_types={"api_key"},
         description="The FAL integration can be used with an API Key.",
     )

autogpt_platform/backend/backend/blocks/fal/ai_video_generator.py

@@ -1,7 +1,7 @@
 import logging
 import time
 from enum import Enum
-from typing import Any, Dict
+from typing import Any
 
 import httpx
 
@@ -64,7 +64,7 @@ class AIVideoGeneratorBlock(Block):
             },
         )
 
-    def _get_headers(self, api_key: str) -> Dict[str, str]:
+    def _get_headers(self, api_key: str) -> dict[str, str]:
         """Get headers for FAL API requests."""
         return {
             "Authorization": f"Key {api_key}",
@@ -72,8 +72,8 @@ class AIVideoGeneratorBlock(Block):
         }
 
     def _submit_request(
-        self, url: str, headers: Dict[str, str], data: Dict[str, Any]
-    ) -> Dict[str, Any]:
+        self, url: str, headers: dict[str, str], data: dict[str, Any]
+    ) -> dict[str, Any]:
         """Submit a request to the FAL API."""
         try:
             response = httpx.post(url, headers=headers, json=data)
@@ -83,7 +83,7 @@ class AIVideoGeneratorBlock(Block):
             logger.error(f"FAL API request failed: {str(e)}")
             raise RuntimeError(f"Failed to submit request: {str(e)}")
 
-    def _poll_status(self, status_url: str, headers: Dict[str, str]) -> Dict[str, Any]:
+    def _poll_status(self, status_url: str, headers: dict[str, str]) -> dict[str, Any]:
         """Poll the status endpoint until completion or failure."""
         try:
             response = httpx.get(status_url, headers=headers)

autogpt_platform/backend/backend/blocks/github/_auth.py

@@ -8,6 +8,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     OAuth2Credentials,
 )
+from backend.integrations.providers import ProviderName
 from backend.util.settings import Secrets
 
 secrets = Secrets()
@@ -17,7 +18,7 @@ GITHUB_OAUTH_IS_CONFIGURED = bool(
 
 GithubCredentials = APIKeyCredentials | OAuth2Credentials
 GithubCredentialsInput = CredentialsMetaInput[
-    Literal["github"],
+    Literal[ProviderName.GITHUB],
     Literal["api_key", "oauth2"] if GITHUB_OAUTH_IS_CONFIGURED else Literal["api_key"],
 ]
 
@@ -30,10 +31,6 @@ def GithubCredentialsField(scope: str) -> GithubCredentialsInput:
         scope: The authorization scope needed for the block to work. ([list of available scopes](https://docs.github.com/en/apps/oauth-apps/building-oauth-apps/scopes-for-oauth-apps#available-scopes))
     """  # noqa
     return CredentialsField(
-        provider="github",
-        supported_credential_types=(
-            {"api_key", "oauth2"} if GITHUB_OAUTH_IS_CONFIGURED else {"api_key"}
-        ),
         required_scopes={scope},
         description="The GitHub integration can be used with OAuth, "
         "or any API key with sufficient permissions for the blocks it is used on.",

autogpt_platform/backend/backend/blocks/github/pull_requests.py

@@ -1,3 +1,5 @@
+import re
+
 from typing_extensions import TypedDict
 
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
@@ -253,7 +255,7 @@ class GithubReadPullRequestBlock(Block):
     @staticmethod
     def read_pr_changes(credentials: GithubCredentials, pr_url: str) -> str:
         api = get_api(credentials)
-        files_url = pr_url + "/files"
+        files_url = prepare_pr_api_url(pr_url=pr_url, path="files")
         response = api.get(files_url)
         files = response.json()
         changes = []
@@ -331,7 +333,7 @@ class GithubAssignPRReviewerBlock(Block):
         credentials: GithubCredentials, pr_url: str, reviewer: str
     ) -> str:
         api = get_api(credentials)
-        reviewers_url = pr_url + "/requested_reviewers"
+        reviewers_url = prepare_pr_api_url(pr_url=pr_url, path="requested_reviewers")
         data = {"reviewers": [reviewer]}
         api.post(reviewers_url, json=data)
         return "Reviewer assigned successfully"
@@ -398,7 +400,7 @@ class GithubUnassignPRReviewerBlock(Block):
         credentials: GithubCredentials, pr_url: str, reviewer: str
     ) -> str:
         api = get_api(credentials)
-        reviewers_url = pr_url + "/requested_reviewers"
+        reviewers_url = prepare_pr_api_url(pr_url=pr_url, path="requested_reviewers")
         data = {"reviewers": [reviewer]}
         api.delete(reviewers_url, json=data)
         return "Reviewer unassigned successfully"
@@ -478,7 +480,7 @@ class GithubListPRReviewersBlock(Block):
         credentials: GithubCredentials, pr_url: str
     ) -> list[Output.ReviewerItem]:
         api = get_api(credentials)
-        reviewers_url = pr_url + "/requested_reviewers"
+        reviewers_url = prepare_pr_api_url(pr_url=pr_url, path="requested_reviewers")
         response = api.get(reviewers_url)
         data = response.json()
         reviewers: list[GithubListPRReviewersBlock.Output.ReviewerItem] = [
@@ -499,3 +501,14 @@ class GithubListPRReviewersBlock(Block):
             input_data.pr_url,
         )
         yield from (("reviewer", reviewer) for reviewer in reviewers)
+
+
+def prepare_pr_api_url(pr_url: str, path: str) -> str:
+    # Pattern to capture the base repository URL and the pull request number
+    pattern = r"^(?:https?://)?([^/]+/[^/]+/[^/]+)/pull/(\d+)"
+    match = re.match(pattern, pr_url)
+    if not match:
+        return pr_url
+
+    base_url, pr_number = match.groups()
+    return f"{base_url}/pulls/{pr_number}/{path}"

autogpt_platform/backend/backend/blocks/github/triggers.py

@@ -111,7 +111,9 @@ class GithubPullRequestTriggerBlock(GitHubTriggerBase, Block):
     def __init__(self):
         from backend.integrations.webhooks.github import GithubWebhookType
 
-        example_payload = json.loads(self.EXAMPLE_PAYLOAD_FILE.read_text())
+        example_payload = json.loads(
+            self.EXAMPLE_PAYLOAD_FILE.read_text(encoding="utf-8")
+        )
 
         super().__init__(
             id="6c60ec01-8128-419e-988f-96a063ee2fea",

autogpt_platform/backend/backend/blocks/google/_auth.py

@@ -3,6 +3,7 @@ from typing import Literal
 from pydantic import SecretStr
 
 from backend.data.model import CredentialsField, CredentialsMetaInput, OAuth2Credentials
+from backend.integrations.providers import ProviderName
 from backend.util.settings import Secrets
 
 # --8<-- [start:GoogleOAuthIsConfigured]
@@ -12,7 +13,9 @@ GOOGLE_OAUTH_IS_CONFIGURED = bool(
 )
 # --8<-- [end:GoogleOAuthIsConfigured]
 GoogleCredentials = OAuth2Credentials
-GoogleCredentialsInput = CredentialsMetaInput[Literal["google"], Literal["oauth2"]]
+GoogleCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.GOOGLE], Literal["oauth2"]
+]
 
 
 def GoogleCredentialsField(scopes: list[str]) -> GoogleCredentialsInput:
@@ -23,8 +26,6 @@ def GoogleCredentialsField(scopes: list[str]) -> GoogleCredentialsInput:
         scopes: The authorization scopes needed for the block to work.
     """
     return CredentialsField(
-        provider="google",
-        supported_credential_types={"oauth2"},
         required_scopes=set(scopes),
         description="The Google integration requires OAuth2 authentication.",
     )

autogpt_platform/backend/backend/blocks/google_maps.py

@@ -10,6 +10,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 
 TEST_CREDENTIALS = APIKeyCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -38,12 +39,8 @@ class Place(BaseModel):
 class GoogleMapsSearchBlock(Block):
     class Input(BlockSchema):
         credentials: CredentialsMetaInput[
-            Literal["google_maps"], Literal["api_key"]
-        ] = CredentialsField(
-            provider="google_maps",
-            supported_credential_types={"api_key"},
-            description="Google Maps API Key",
-        )
+            Literal[ProviderName.GOOGLE_MAPS], Literal["api_key"]
+        ] = CredentialsField(description="Google Maps API Key")
         query: str = SchemaField(
             description="Search query for local businesses",
             placeholder="e.g., 'restaurants in New York'",

autogpt_platform/backend/backend/blocks/hubspot/_auth.py

@@ -3,10 +3,11 @@ from typing import Literal
 from pydantic import SecretStr
 
 from backend.data.model import APIKeyCredentials, CredentialsField, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
 
 HubSpotCredentials = APIKeyCredentials
 HubSpotCredentialsInput = CredentialsMetaInput[
-    Literal["hubspot"],
+    Literal[ProviderName.HUBSPOT],
     Literal["api_key"],
 ]
 
@@ -14,8 +15,6 @@ HubSpotCredentialsInput = CredentialsMetaInput[
 def HubSpotCredentialsField() -> HubSpotCredentialsInput:
     """Creates a HubSpot credentials input on a block."""
     return CredentialsField(
-        provider="hubspot",
-        supported_credential_types={"api_key"},
         description="The HubSpot integration requires an API Key.",
     )
 

autogpt_platform/backend/backend/blocks/ideogram.py

@@ -11,6 +11,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 from backend.util.request import requests
 
 TEST_CREDENTIALS = APIKeyCredentials(
@@ -83,13 +84,10 @@ class UpscaleOption(str, Enum):
 
 class IdeogramModelBlock(Block):
     class Input(BlockSchema):
-
-        credentials: CredentialsMetaInput[Literal["ideogram"], Literal["api_key"]] = (
-            CredentialsField(
-                provider="ideogram",
-                supported_credential_types={"api_key"},
-                description="The Ideogram integration can be used with any API key with sufficient permissions for the blocks it is used on.",
-            )
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.IDEOGRAM], Literal["api_key"]
+        ] = CredentialsField(
+            description="The Ideogram integration can be used with any API key with sufficient permissions for the blocks it is used on.",
         )
         prompt: str = SchemaField(
             description="Text prompt for image generation",

autogpt_platform/backend/backend/blocks/jina/_auth.py

@@ -3,27 +3,14 @@ from typing import Literal
 from pydantic import SecretStr
 
 from backend.data.model import APIKeyCredentials, CredentialsField, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
 
 JinaCredentials = APIKeyCredentials
 JinaCredentialsInput = CredentialsMetaInput[
-    Literal["jina"],
+    Literal[ProviderName.JINA],
     Literal["api_key"],
 ]
 
-TEST_CREDENTIALS = APIKeyCredentials(
-    id="01234567-89ab-cdef-0123-456789abcdef",
-    provider="jina",
-    api_key=SecretStr("mock-jina-api-key"),
-    title="Mock Jina API key",
-    expires_at=None,
-)
-TEST_CREDENTIALS_INPUT = {
-    "provider": TEST_CREDENTIALS.provider,
-    "id": TEST_CREDENTIALS.id,
-    "type": TEST_CREDENTIALS.type,
-    "title": TEST_CREDENTIALS.type,
-}
-
 
 def JinaCredentialsField() -> JinaCredentialsInput:
     """
@@ -31,8 +18,6 @@ def JinaCredentialsField() -> JinaCredentialsInput:
 
     """
     return CredentialsField(
-        provider="jina",
-        supported_credential_types={"api_key"},
         description="The Jina integration can be used with an API Key.",
     )
 

autogpt_platform/backend/backend/blocks/jina/fact_checker.py

@@ -0,0 +1,59 @@
+from urllib.parse import quote
+
+import requests
+
+from backend.blocks.jina._auth import (
+    JinaCredentials,
+    JinaCredentialsField,
+    JinaCredentialsInput,
+)
+from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
+from backend.data.model import SchemaField
+
+
+class FactCheckerBlock(Block):
+    class Input(BlockSchema):
+        statement: str = SchemaField(
+            description="The statement to check for factuality"
+        )
+        credentials: JinaCredentialsInput = JinaCredentialsField()
+
+    class Output(BlockSchema):
+        factuality: float = SchemaField(
+            description="The factuality score of the statement"
+        )
+        result: bool = SchemaField(description="The result of the factuality check")
+        reason: str = SchemaField(description="The reason for the factuality result")
+        error: str = SchemaField(description="Error message if the check fails")
+
+    def __init__(self):
+        super().__init__(
+            id="d38b6c5e-9968-4271-8423-6cfe60d6e7e6",
+            description="This block checks the factuality of a given statement using Jina AI's Grounding API.",
+            categories={BlockCategory.SEARCH},
+            input_schema=FactCheckerBlock.Input,
+            output_schema=FactCheckerBlock.Output,
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: JinaCredentials, **kwargs
+    ) -> BlockOutput:
+        encoded_statement = quote(input_data.statement)
+        url = f"https://g.jina.ai/{encoded_statement}"
+
+        headers = {
+            "Accept": "application/json",
+            "Authorization": f"Bearer {credentials.api_key.get_secret_value()}",
+        }
+
+        response = requests.get(url, headers=headers)
+        response.raise_for_status()
+        data = response.json()
+
+        if "data" in data:
+            data = data["data"]
+            yield "factuality", data["factuality"]
+            yield "result", data["result"]
+            yield "reason", data["reason"]
+        else:
+            raise RuntimeError(f"Expected 'data' key not found in response: {data}")

autogpt_platform/backend/backend/blocks/llm.py

@@ -7,6 +7,8 @@ from typing import TYPE_CHECKING, Any, List, Literal, NamedTuple
 
 from pydantic import SecretStr
 
+from backend.integrations.providers import ProviderName
+
 if TYPE_CHECKING:
     from enum import _EnumMemberT
 
@@ -27,7 +29,13 @@ from backend.util.settings import BehaveAs, Settings
 
 logger = logging.getLogger(__name__)
 
-LLMProviderName = Literal["anthropic", "groq", "openai", "ollama", "open_router"]
+LLMProviderName = Literal[
+    ProviderName.ANTHROPIC,
+    ProviderName.GROQ,
+    ProviderName.OLLAMA,
+    ProviderName.OPENAI,
+    ProviderName.OPEN_ROUTER,
+]
 AICredentials = CredentialsMetaInput[LLMProviderName, Literal["api_key"]]
 
 TEST_CREDENTIALS = APIKeyCredentials(
@@ -48,8 +56,6 @@ TEST_CREDENTIALS_INPUT = {
 def AICredentialsField() -> AICredentials:
     return CredentialsField(
         description="API key for the LLM provider.",
-        provider=["anthropic", "groq", "openai", "ollama", "open_router"],
-        supported_credential_types={"api_key"},
         discriminator="model",
         discriminator_mapping={
             model.value: model.metadata.provider for model in LlmModel
@@ -105,9 +111,9 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     # Ollama models
     OLLAMA_LLAMA3_8B = "llama3"
     OLLAMA_LLAMA3_405B = "llama3.1:405b"
+    OLLAMA_DOLPHIN = "dolphin-mistral:latest"
     # OpenRouter models
     GEMINI_FLASH_1_5_8B = "google/gemini-flash-1.5"
-    GEMINI_FLASH_1_5_EXP = "google/gemini-flash-1.5-exp"
     GROK_BETA = "x-ai/grok-beta"
     MISTRAL_NEMO = "mistralai/mistral-nemo"
     COHERE_COMMAND_R_08_2024 = "cohere/command-r-08-2024"
@@ -117,6 +123,14 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     PERPLEXITY_LLAMA_3_1_SONAR_LARGE_128K_ONLINE = (
         "perplexity/llama-3.1-sonar-large-128k-online"
     )
+    QWEN_QWQ_32B_PREVIEW = "qwen/qwq-32b-preview"
+    NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B = "nousresearch/hermes-3-llama-3.1-405b"
+    NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B = "nousresearch/hermes-3-llama-3.1-70b"
+    AMAZON_NOVA_LITE_V1 = "amazon/nova-lite-v1"
+    AMAZON_NOVA_MICRO_V1 = "amazon/nova-micro-v1"
+    AMAZON_NOVA_PRO_V1 = "amazon/nova-pro-v1"
+    MICROSOFT_WIZARDLM_2_8X22B = "microsoft/wizardlm-2-8x22b"
+    GRYPHE_MYTHOMAX_L2_13B = "gryphe/mythomax-l2-13b"
 
     @property
     def metadata(self) -> ModelMetadata:
@@ -151,8 +165,8 @@ MODEL_METADATA = {
     LlmModel.LLAMA3_1_8B: ModelMetadata("groq", 131072),
     LlmModel.OLLAMA_LLAMA3_8B: ModelMetadata("ollama", 8192),
     LlmModel.OLLAMA_LLAMA3_405B: ModelMetadata("ollama", 8192),
+    LlmModel.OLLAMA_DOLPHIN: ModelMetadata("ollama", 32768),
     LlmModel.GEMINI_FLASH_1_5_8B: ModelMetadata("open_router", 8192),
-    LlmModel.GEMINI_FLASH_1_5_EXP: ModelMetadata("open_router", 8192),
     LlmModel.GROK_BETA: ModelMetadata("open_router", 8192),
     LlmModel.MISTRAL_NEMO: ModelMetadata("open_router", 4000),
     LlmModel.COHERE_COMMAND_R_08_2024: ModelMetadata("open_router", 4000),
@@ -162,6 +176,14 @@ MODEL_METADATA = {
     LlmModel.PERPLEXITY_LLAMA_3_1_SONAR_LARGE_128K_ONLINE: ModelMetadata(
         "open_router", 8192
     ),
+    LlmModel.QWEN_QWQ_32B_PREVIEW: ModelMetadata("open_router", 4000),
+    LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B: ModelMetadata("open_router", 4000),
+    LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B: ModelMetadata("open_router", 4000),
+    LlmModel.AMAZON_NOVA_LITE_V1: ModelMetadata("open_router", 4000),
+    LlmModel.AMAZON_NOVA_MICRO_V1: ModelMetadata("open_router", 4000),
+    LlmModel.AMAZON_NOVA_PRO_V1: ModelMetadata("open_router", 4000),
+    LlmModel.MICROSOFT_WIZARDLM_2_8X22B: ModelMetadata("open_router", 4000),
+    LlmModel.GRYPHE_MYTHOMAX_L2_13B: ModelMetadata("open_router", 4000),
 }
 
 for model in LlmModel:
@@ -220,6 +242,12 @@ class AIStructuredResponseGeneratorBlock(Block):
             description="The maximum number of tokens to generate in the chat completion.",
         )
 
+        ollama_host: str = SchemaField(
+            advanced=True,
+            default="localhost:11434",
+            description="Ollama host for local  models",
+        )
+
     class Output(BlockSchema):
         response: dict[str, Any] = SchemaField(
             description="The response object generated by the language model."
@@ -265,6 +293,7 @@ class AIStructuredResponseGeneratorBlock(Block):
         prompt: list[dict],
         json_format: bool,
         max_tokens: int | None = None,
+        ollama_host: str = "localhost:11434",
     ) -> tuple[str, int, int]:
         """
         Args:
@@ -273,6 +302,7 @@ class AIStructuredResponseGeneratorBlock(Block):
             prompt: The prompt to send to the LLM.
             json_format: Whether the response should be in JSON format.
             max_tokens: The maximum number of tokens to generate in the chat completion.
+            ollama_host: The host for ollama to use
 
         Returns:
             The response from the LLM.
@@ -362,9 +392,10 @@ class AIStructuredResponseGeneratorBlock(Block):
                 response.usage.completion_tokens if response.usage else 0,
             )
         elif provider == "ollama":
+            client = ollama.Client(host=ollama_host)
             sys_messages = [p["content"] for p in prompt if p["role"] == "system"]
             usr_messages = [p["content"] for p in prompt if p["role"] != "system"]
-            response = ollama.generate(
+            response = client.generate(
                 model=llm_model.value,
                 prompt=f"{sys_messages}\n\n{usr_messages}",
                 stream=False,
@@ -464,6 +495,7 @@ class AIStructuredResponseGeneratorBlock(Block):
                     llm_model=llm_model,
                     prompt=prompt,
                     json_format=bool(input_data.expected_format),
+                    ollama_host=input_data.ollama_host,
                     max_tokens=input_data.max_tokens,
                 )
                 self.merge_stats(
@@ -546,6 +578,11 @@ class AITextGeneratorBlock(Block):
         prompt_values: dict[str, str] = SchemaField(
             advanced=False, default={}, description="Values used to fill in the prompt."
         )
+        ollama_host: str = SchemaField(
+            advanced=True,
+            default="localhost:11434",
+            description="Ollama host for local  models",
+        )
         max_tokens: int | None = SchemaField(
             advanced=True,
             default=None,
@@ -636,6 +673,11 @@ class AITextSummarizerBlock(Block):
             description="The number of overlapping tokens between chunks to maintain context.",
             ge=0,
         )
+        ollama_host: str = SchemaField(
+            advanced=True,
+            default="localhost:11434",
+            description="Ollama host for local  models",
+        )
 
     class Output(BlockSchema):
         summary: str = SchemaField(description="The final summary of the text.")
@@ -774,6 +816,11 @@ class AIConversationBlock(Block):
             default=None,
             description="The maximum number of tokens to generate in the chat completion.",
         )
+        ollama_host: str = SchemaField(
+            advanced=True,
+            default="localhost:11434",
+            description="Ollama host for local  models",
+        )
 
     class Output(BlockSchema):
         response: str = SchemaField(
@@ -871,6 +918,11 @@ class AIListGeneratorBlock(Block):
             default=None,
             description="The maximum number of tokens to generate in the chat completion.",
         )
+        ollama_host: str = SchemaField(
+            advanced=True,
+            default="localhost:11434",
+            description="Ollama host for local  models",
+        )
 
     class Output(BlockSchema):
         generated_list: List[str] = SchemaField(description="The generated list.")
@@ -1022,6 +1074,7 @@ class AIListGeneratorBlock(Block):
                         credentials=input_data.credentials,
                         model=input_data.model,
                         expected_format={},  # Do not use structured response
+                        ollama_host=input_data.ollama_host,
                     ),
                     credentials=credentials,
                 )

autogpt_platform/backend/backend/blocks/medium.py

@@ -12,6 +12,7 @@ from backend.data.model import (
     SchemaField,
     SecretField,
 )
+from backend.integrations.providers import ProviderName
 from backend.util.request import requests
 
 TEST_CREDENTIALS = APIKeyCredentials(
@@ -77,12 +78,10 @@ class PublishToMediumBlock(Block):
             description="Whether to notify followers that the user has published",
             placeholder="False",
         )
-        credentials: CredentialsMetaInput[Literal["medium"], Literal["api_key"]] = (
-            CredentialsField(
-                provider="medium",
-                supported_credential_types={"api_key"},
-                description="The Medium integration can be used with any API key with sufficient permissions for the blocks it is used on.",
-            )
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.MEDIUM], Literal["api_key"]
+        ] = CredentialsField(
+            description="The Medium integration can be used with any API key with sufficient permissions for the blocks it is used on.",
         )
 
     class Output(BlockSchema):

autogpt_platform/backend/backend/blocks/pinecone.py

@@ -10,22 +10,18 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 
 PineconeCredentials = APIKeyCredentials
 PineconeCredentialsInput = CredentialsMetaInput[
-    Literal["pinecone"],
+    Literal[ProviderName.PINECONE],
     Literal["api_key"],
 ]
 
 
 def PineconeCredentialsField() -> PineconeCredentialsInput:
-    """
-    Creates a Pinecone credentials input on a block.
-
-    """
+    """Creates a Pinecone credentials input on a block."""
     return CredentialsField(
-        provider="pinecone",
-        supported_credential_types={"api_key"},
         description="The Pinecone integration can be used with an API Key.",
     )
 
@@ -147,7 +143,7 @@ class PineconeQueryBlock(Block):
                 top_k=input_data.top_k,
                 include_values=input_data.include_values,
                 include_metadata=input_data.include_metadata,
-            ).to_dict()
+            ).to_dict()  # type: ignore
             combined_text = ""
             if results["matches"]:
                 texts = [

autogpt_platform/backend/backend/blocks/replicate_flux_advanced.py

@@ -13,6 +13,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 
 TEST_CREDENTIALS = APIKeyCredentials(
     id="01234567-89ab-cdef-0123-456789abcdef",
@@ -54,13 +55,11 @@ class ImageType(str, Enum):
 
 class ReplicateFluxAdvancedModelBlock(Block):
     class Input(BlockSchema):
-        credentials: CredentialsMetaInput[Literal["replicate"], Literal["api_key"]] = (
-            CredentialsField(
-                provider="replicate",
-                supported_credential_types={"api_key"},
-                description="The Replicate integration can be used with "
-                "any API key with sufficient permissions for the blocks it is used on.",
-            )
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.REPLICATE], Literal["api_key"]
+        ] = CredentialsField(
+            description="The Replicate integration can be used with "
+            "any API key with sufficient permissions for the blocks it is used on.",
         )
         prompt: str = SchemaField(
             description="Text prompt for image generation",

autogpt_platform/backend/backend/blocks/search.py

@@ -11,6 +11,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 
 
 class GetWikipediaSummaryBlock(Block, GetRequest):
@@ -65,10 +66,8 @@ class GetWeatherInformationBlock(Block, GetRequest):
             description="Location to get weather information for"
         )
         credentials: CredentialsMetaInput[
-            Literal["openweathermap"], Literal["api_key"]
+            Literal[ProviderName.OPENWEATHERMAP], Literal["api_key"]
         ] = CredentialsField(
-            provider="openweathermap",
-            supported_credential_types={"api_key"},
             description="The OpenWeatherMap integration can be used with "
             "any API key with sufficient permissions for the blocks it is used on.",
         )

autogpt_platform/backend/backend/blocks/slant3d/_api.py

@@ -0,0 +1,70 @@
+from enum import Enum
+from typing import Literal
+
+from pydantic import BaseModel, SecretStr
+
+from backend.data.model import APIKeyCredentials, CredentialsField, CredentialsMetaInput
+from backend.integrations.providers import ProviderName
+
+Slant3DCredentialsInput = CredentialsMetaInput[
+    Literal[ProviderName.SLANT3D], Literal["api_key"]
+]
+
+
+def Slant3DCredentialsField() -> Slant3DCredentialsInput:
+    return CredentialsField(description="Slant3D API key for authentication")
+
+
+TEST_CREDENTIALS = APIKeyCredentials(
+    id="01234567-89ab-cdef-0123-456789abcdef",
+    provider="slant3d",
+    api_key=SecretStr("mock-slant3d-api-key"),
+    title="Mock Slant3D API key",
+    expires_at=None,
+)
+
+TEST_CREDENTIALS_INPUT = {
+    "provider": TEST_CREDENTIALS.provider,
+    "id": TEST_CREDENTIALS.id,
+    "type": TEST_CREDENTIALS.type,
+    "title": TEST_CREDENTIALS.title,
+}
+
+
+class CustomerDetails(BaseModel):
+    name: str
+    email: str
+    phone: str
+    address: str
+    city: str
+    state: str
+    zip: str
+    country_iso: str = "US"
+    is_residential: bool = True
+
+
+class Color(Enum):
+    WHITE = "white"
+    BLACK = "black"
+
+
+class Profile(Enum):
+    PLA = "PLA"
+    PETG = "PETG"
+
+
+class OrderItem(BaseModel):
+    # filename: str
+    file_url: str
+    quantity: str  # String as per API spec
+    color: Color = Color.WHITE
+    profile: Profile = Profile.PLA
+    # image_url: str = ""
+    # sku: str = ""
+
+
+class Filament(BaseModel):
+    filament: str
+    hexColor: str
+    colorTag: str
+    profile: str

autogpt_platform/backend/backend/blocks/slant3d/base.py

@@ -0,0 +1,94 @@
+from typing import Any, Dict
+
+from backend.data.block import Block
+from backend.util.request import requests
+
+from ._api import Color, CustomerDetails, OrderItem, Profile
+
+
+class Slant3DBlockBase(Block):
+    """Base block class for Slant3D API interactions"""
+
+    BASE_URL = "https://www.slant3dapi.com/api"
+
+    def _get_headers(self, api_key: str) -> Dict[str, str]:
+        return {"api-key": api_key, "Content-Type": "application/json"}
+
+    def _make_request(self, method: str, endpoint: str, api_key: str, **kwargs) -> Dict:
+        url = f"{self.BASE_URL}/{endpoint}"
+        response = requests.request(
+            method=method, url=url, headers=self._get_headers(api_key), **kwargs
+        )
+
+        if not response.ok:
+            error_msg = response.json().get("error", "Unknown error")
+            raise RuntimeError(f"API request failed: {error_msg}")
+
+        return response.json()
+
+    def _check_valid_color(self, profile: Profile, color: Color, api_key: str) -> str:
+        response = self._make_request(
+            "GET",
+            "filament",
+            api_key,
+            params={"profile": profile.value, "color": color.value},
+        )
+        if profile == Profile.PLA:
+            color_tag = color.value
+        else:
+            color_tag = f"{profile.value.lower()}{color.value.capitalize()}"
+        valid_tags = [filament["colorTag"] for filament in response["filaments"]]
+
+        if color_tag not in valid_tags:
+            raise ValueError(
+                f"""Invalid color profile combination {color_tag}.
+Valid colors for {profile.value} are:
+{','.join([filament['colorTag'].replace(profile.value.lower(), '') for filament in response['filaments'] if filament['profile'] == profile.value])}
+"""
+            )
+        return color_tag
+
+    def _convert_to_color(self, profile: Profile, color: Color, api_key: str) -> str:
+        return self._check_valid_color(profile, color, api_key)
+
+    def _format_order_data(
+        self,
+        customer: CustomerDetails,
+        order_number: str,
+        items: list[OrderItem],
+        api_key: str,
+    ) -> list[dict[str, Any]]:
+        """Helper function to format order data for API requests"""
+        orders = []
+        for item in items:
+            order_data = {
+                "email": customer.email,
+                "phone": customer.phone,
+                "name": customer.name,
+                "orderNumber": order_number,
+                "filename": item.file_url,
+                "fileURL": item.file_url,
+                "bill_to_street_1": customer.address,
+                "bill_to_city": customer.city,
+                "bill_to_state": customer.state,
+                "bill_to_zip": customer.zip,
+                "bill_to_country_as_iso": customer.country_iso,
+                "bill_to_is_US_residential": str(customer.is_residential).lower(),
+                "ship_to_name": customer.name,
+                "ship_to_street_1": customer.address,
+                "ship_to_city": customer.city,
+                "ship_to_state": customer.state,
+                "ship_to_zip": customer.zip,
+                "ship_to_country_as_iso": customer.country_iso,
+                "ship_to_is_US_residential": str(customer.is_residential).lower(),
+                "order_item_name": item.file_url,
+                "order_quantity": item.quantity,
+                "order_image_url": "",
+                "order_sku": "NOT_USED",
+                "order_item_color": self._convert_to_color(
+                    item.profile, item.color, api_key
+                ),
+                "profile": item.profile.value,
+            }
+            orders.append(order_data)
+        return orders

autogpt_platform/backend/backend/blocks/slant3d/filament.py

@@ -0,0 +1,85 @@
+from typing import List
+
+from backend.data.block import BlockOutput, BlockSchema
+from backend.data.model import APIKeyCredentials, SchemaField
+
+from ._api import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    Filament,
+    Slant3DCredentialsField,
+    Slant3DCredentialsInput,
+)
+from .base import Slant3DBlockBase
+
+
+class Slant3DFilamentBlock(Slant3DBlockBase):
+    """Block for retrieving available filaments"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+
+    class Output(BlockSchema):
+        filaments: List[Filament] = SchemaField(
+            description="List of available filaments"
+        )
+        error: str = SchemaField(description="Error message if request failed")
+
+    def __init__(self):
+        super().__init__(
+            id="7cc416f4-f305-4606-9b3b-452b8a81031c",
+            description="Get list of available filaments",
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={"credentials": TEST_CREDENTIALS_INPUT},
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                (
+                    "filaments",
+                    [
+                        {
+                            "filament": "PLA BLACK",
+                            "hexColor": "000000",
+                            "colorTag": "black",
+                            "profile": "PLA",
+                        },
+                        {
+                            "filament": "PLA WHITE",
+                            "hexColor": "ffffff",
+                            "colorTag": "white",
+                            "profile": "PLA",
+                        },
+                    ],
+                )
+            ],
+            test_mock={
+                "_make_request": lambda *args, **kwargs: {
+                    "filaments": [
+                        {
+                            "filament": "PLA BLACK",
+                            "hexColor": "000000",
+                            "colorTag": "black",
+                            "profile": "PLA",
+                        },
+                        {
+                            "filament": "PLA WHITE",
+                            "hexColor": "ffffff",
+                            "colorTag": "white",
+                            "profile": "PLA",
+                        },
+                    ]
+                }
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            result = self._make_request(
+                "GET", "filament", credentials.api_key.get_secret_value()
+            )
+            yield "filaments", result["filaments"]
+        except Exception as e:
+            yield "error", str(e)
+            raise

autogpt_platform/backend/backend/blocks/slant3d/order.py

@@ -0,0 +1,418 @@
+import uuid
+from typing import List
+
+import requests as baserequests
+
+from backend.data.block import BlockOutput, BlockSchema
+from backend.data.model import APIKeyCredentials, SchemaField
+from backend.util import settings
+from backend.util.settings import BehaveAs
+
+from ._api import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    CustomerDetails,
+    OrderItem,
+    Slant3DCredentialsField,
+    Slant3DCredentialsInput,
+)
+from .base import Slant3DBlockBase
+
+
+class Slant3DCreateOrderBlock(Slant3DBlockBase):
+    """Block for creating new orders"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+        order_number: str = SchemaField(
+            description="Your custom order number (or leave blank for a random one)",
+            default_factory=lambda: str(uuid.uuid4()),
+        )
+        customer: CustomerDetails = SchemaField(
+            description="Customer details for where to ship the item",
+            advanced=False,
+        )
+        items: List[OrderItem] = SchemaField(
+            description="List of items to print",
+            advanced=False,
+        )
+
+    class Output(BlockSchema):
+        order_id: str = SchemaField(description="Slant3D order ID")
+        error: str = SchemaField(description="Error message if order failed")
+
+    def __init__(self):
+        super().__init__(
+            id="f73007d6-f48f-4aaf-9e6b-6883998a09b4",
+            description="Create a new print order",
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "order_number": "TEST-001",
+                "customer": {
+                    "name": "John Doe",
+                    "email": "john@example.com",
+                    "phone": "123-456-7890",
+                    "address": "123 Test St",
+                    "city": "Test City",
+                    "state": "TS",
+                    "zip": "12345",
+                },
+                "items": [
+                    {
+                        "file_url": "https://example.com/model.stl",
+                        "quantity": "1",
+                        "color": "black",
+                        "profile": "PLA",
+                    }
+                ],
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("order_id", "314144241")],
+            test_mock={
+                "_make_request": lambda *args, **kwargs: {"orderId": "314144241"},
+                "_convert_to_color": lambda *args, **kwargs: "black",
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            order_data = self._format_order_data(
+                input_data.customer,
+                input_data.order_number,
+                input_data.items,
+                credentials.api_key.get_secret_value(),
+            )
+            result = self._make_request(
+                "POST", "order", credentials.api_key.get_secret_value(), json=order_data
+            )
+            yield "order_id", result["orderId"]
+        except Exception as e:
+            yield "error", str(e)
+            raise
+
+
+class Slant3DEstimateOrderBlock(Slant3DBlockBase):
+    """Block for getting order cost estimates"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+        order_number: str = SchemaField(
+            description="Your custom order number (or leave blank for a random one)",
+            default_factory=lambda: str(uuid.uuid4()),
+        )
+        customer: CustomerDetails = SchemaField(
+            description="Customer details for where to ship the item",
+            advanced=False,
+        )
+        items: List[OrderItem] = SchemaField(
+            description="List of items to print",
+            advanced=False,
+        )
+
+    class Output(BlockSchema):
+        total_price: float = SchemaField(description="Total price in USD")
+        shipping_cost: float = SchemaField(description="Shipping cost")
+        printing_cost: float = SchemaField(description="Printing cost")
+        error: str = SchemaField(description="Error message if estimation failed")
+
+    def __init__(self):
+        super().__init__(
+            id="bf8823d6-b42a-48c7-b558-d7c117f2ae85",
+            description="Get order cost estimate",
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "order_number": "TEST-001",
+                "customer": {
+                    "name": "John Doe",
+                    "email": "john@example.com",
+                    "phone": "123-456-7890",
+                    "address": "123 Test St",
+                    "city": "Test City",
+                    "state": "TS",
+                    "zip": "12345",
+                },
+                "items": [
+                    {
+                        "file_url": "https://example.com/model.stl",
+                        "quantity": "1",
+                        "color": "black",
+                        "profile": "PLA",
+                    }
+                ],
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                ("total_price", 9.31),
+                ("shipping_cost", 5.56),
+                ("printing_cost", 3.75),
+            ],
+            test_mock={
+                "_make_request": lambda *args, **kwargs: {
+                    "totalPrice": 9.31,
+                    "shippingCost": 5.56,
+                    "printingCost": 3.75,
+                },
+                "_convert_to_color": lambda *args, **kwargs: "black",
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        order_data = self._format_order_data(
+            input_data.customer,
+            input_data.order_number,
+            input_data.items,
+            credentials.api_key.get_secret_value(),
+        )
+        try:
+            result = self._make_request(
+                "POST",
+                "order/estimate",
+                credentials.api_key.get_secret_value(),
+                json=order_data,
+            )
+            yield "total_price", result["totalPrice"]
+            yield "shipping_cost", result["shippingCost"]
+            yield "printing_cost", result["printingCost"]
+        except baserequests.HTTPError as e:
+            yield "error", str(f"Error estimating order: {e} {e.response.text}")
+            raise
+
+
+class Slant3DEstimateShippingBlock(Slant3DBlockBase):
+    """Block for getting shipping cost estimates"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+        order_number: str = SchemaField(
+            description="Your custom order number (or leave blank for a random one)",
+            default_factory=lambda: str(uuid.uuid4()),
+        )
+        customer: CustomerDetails = SchemaField(
+            description="Customer details for where to ship the item"
+        )
+        items: List[OrderItem] = SchemaField(
+            description="List of items to print",
+            advanced=False,
+        )
+
+    class Output(BlockSchema):
+        shipping_cost: float = SchemaField(description="Estimated shipping cost")
+        currency_code: str = SchemaField(description="Currency code (e.g., 'usd')")
+        error: str = SchemaField(description="Error message if estimation failed")
+
+    def __init__(self):
+        super().__init__(
+            id="00aae2a1-caf6-4a74-8175-39a0615d44e1",
+            description="Get shipping cost estimate",
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "order_number": "TEST-001",
+                "customer": {
+                    "name": "John Doe",
+                    "email": "john@example.com",
+                    "phone": "123-456-7890",
+                    "address": "123 Test St",
+                    "city": "Test City",
+                    "state": "TS",
+                    "zip": "12345",
+                },
+                "items": [
+                    {
+                        "file_url": "https://example.com/model.stl",
+                        "quantity": "1",
+                        "color": "black",
+                        "profile": "PLA",
+                    }
+                ],
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("shipping_cost", 4.81), ("currency_code", "usd")],
+            test_mock={
+                "_make_request": lambda *args, **kwargs: {
+                    "shippingCost": 4.81,
+                    "currencyCode": "usd",
+                },
+                "_convert_to_color": lambda *args, **kwargs: "black",
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            order_data = self._format_order_data(
+                input_data.customer,
+                input_data.order_number,
+                input_data.items,
+                credentials.api_key.get_secret_value(),
+            )
+            result = self._make_request(
+                "POST",
+                "order/estimateShipping",
+                credentials.api_key.get_secret_value(),
+                json=order_data,
+            )
+            yield "shipping_cost", result["shippingCost"]
+            yield "currency_code", result["currencyCode"]
+        except Exception as e:
+            yield "error", str(e)
+            raise
+
+
+class Slant3DGetOrdersBlock(Slant3DBlockBase):
+    """Block for retrieving all orders"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+
+    class Output(BlockSchema):
+        orders: List[str] = SchemaField(description="List of orders with their details")
+        error: str = SchemaField(description="Error message if request failed")
+
+    def __init__(self):
+        super().__init__(
+            id="42283bf5-8a32-4fb4-92a2-60a9ea48e105",
+            description="Get all orders for the account",
+            input_schema=self.Input,
+            output_schema=self.Output,
+            # This block is disabled for cloud hosted because it allows access to all orders for the account
+            disabled=settings.Settings().config.behave_as == BehaveAs.CLOUD,
+            test_input={"credentials": TEST_CREDENTIALS_INPUT},
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                (
+                    "orders",
+                    [
+                        "1234567890",
+                    ],
+                )
+            ],
+            test_mock={
+                "_make_request": lambda *args, **kwargs: {
+                    "ordersData": [
+                        {
+                            "orderId": 1234567890,
+                            "orderTimestamp": {
+                                "_seconds": 1719510986,
+                                "_nanoseconds": 710000000,
+                            },
+                        }
+                    ]
+                }
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            result = self._make_request(
+                "GET", "order", credentials.api_key.get_secret_value()
+            )
+            yield "orders", [str(order["orderId"]) for order in result["ordersData"]]
+        except Exception as e:
+            yield "error", str(e)
+            raise
+
+
+class Slant3DTrackingBlock(Slant3DBlockBase):
+    """Block for tracking order status and shipping"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+        order_id: str = SchemaField(description="Slant3D order ID to track")
+
+    class Output(BlockSchema):
+        status: str = SchemaField(description="Order status")
+        tracking_numbers: List[str] = SchemaField(
+            description="List of tracking numbers"
+        )
+        error: str = SchemaField(description="Error message if tracking failed")
+
+    def __init__(self):
+        super().__init__(
+            id="dd7c0293-c5af-4551-ba3e-fc162fb1fb89",
+            description="Track order status and shipping",
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "order_id": "314144241",
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("status", "awaiting_shipment"), ("tracking_numbers", [])],
+            test_mock={
+                "_make_request": lambda *args, **kwargs: {
+                    "status": "awaiting_shipment",
+                    "trackingNumbers": [],
+                }
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            result = self._make_request(
+                "GET",
+                f"order/{input_data.order_id}/get-tracking",
+                credentials.api_key.get_secret_value(),
+            )
+            yield "status", result["status"]
+            yield "tracking_numbers", result["trackingNumbers"]
+        except Exception as e:
+            yield "error", str(e)
+            raise
+
+
+class Slant3DCancelOrderBlock(Slant3DBlockBase):
+    """Block for canceling orders"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+        order_id: str = SchemaField(description="Slant3D order ID to cancel")
+
+    class Output(BlockSchema):
+        status: str = SchemaField(description="Cancellation status message")
+        error: str = SchemaField(description="Error message if cancellation failed")
+
+    def __init__(self):
+        super().__init__(
+            id="54de35e1-407f-450b-b5fa-3b5e2eba8185",
+            description="Cancel an existing order",
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "order_id": "314144241",
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("status", "Order cancelled")],
+            test_mock={
+                "_make_request": lambda *args, **kwargs: {"status": "Order cancelled"}
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            result = self._make_request(
+                "DELETE",
+                f"order/{input_data.order_id}",
+                credentials.api_key.get_secret_value(),
+            )
+            yield "status", result["status"]
+        except Exception as e:
+            yield "error", str(e)
+            raise

autogpt_platform/backend/backend/blocks/slant3d/slicing.py

@@ -0,0 +1,61 @@
+from backend.data.block import BlockOutput, BlockSchema
+from backend.data.model import APIKeyCredentials, SchemaField
+
+from ._api import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    Slant3DCredentialsField,
+    Slant3DCredentialsInput,
+)
+from .base import Slant3DBlockBase
+
+
+class Slant3DSlicerBlock(Slant3DBlockBase):
+    """Block for slicing 3D model files"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+        file_url: str = SchemaField(
+            description="URL of the 3D model file to slice (STL)"
+        )
+
+    class Output(BlockSchema):
+        message: str = SchemaField(description="Response message")
+        price: float = SchemaField(description="Calculated price for printing")
+        error: str = SchemaField(description="Error message if slicing failed")
+
+    def __init__(self):
+        super().__init__(
+            id="f8a12c8d-3e4b-4d5f-b6a7-8c9d0e1f2g3h",
+            description="Slice a 3D model file and get pricing information",
+            input_schema=self.Input,
+            output_schema=self.Output,
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "file_url": "https://example.com/model.stl",
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[("message", "Slicing successful"), ("price", 8.23)],
+            test_mock={
+                "_make_request": lambda *args, **kwargs: {
+                    "message": "Slicing successful",
+                    "data": {"price": 8.23},
+                }
+            },
+        )
+
+    def run(
+        self, input_data: Input, *, credentials: APIKeyCredentials, **kwargs
+    ) -> BlockOutput:
+        try:
+            result = self._make_request(
+                "POST",
+                "slicer",
+                credentials.api_key.get_secret_value(),
+                json={"fileURL": input_data.file_url},
+            )
+            yield "message", result["message"]
+            yield "price", result["data"]["price"]
+        except Exception as e:
+            yield "error", str(e)
+            raise

autogpt_platform/backend/backend/blocks/slant3d/webhook.py

@@ -0,0 +1,125 @@
+from pydantic import BaseModel
+
+from backend.data.block import (
+    Block,
+    BlockCategory,
+    BlockOutput,
+    BlockSchema,
+    BlockWebhookConfig,
+)
+from backend.data.model import SchemaField
+from backend.util import settings
+from backend.util.settings import AppEnvironment, BehaveAs
+
+from ._api import (
+    TEST_CREDENTIALS,
+    TEST_CREDENTIALS_INPUT,
+    Slant3DCredentialsField,
+    Slant3DCredentialsInput,
+)
+
+
+class Slant3DTriggerBase:
+    """Base class for Slant3D webhook triggers"""
+
+    class Input(BlockSchema):
+        credentials: Slant3DCredentialsInput = Slant3DCredentialsField()
+        # Webhook URL is handled by the webhook system
+        payload: dict = SchemaField(hidden=True, default={})
+
+    class Output(BlockSchema):
+        payload: dict = SchemaField(
+            description="The complete webhook payload received from Slant3D"
+        )
+        order_id: str = SchemaField(description="The ID of the affected order")
+        error: str = SchemaField(
+            description="Error message if payload processing failed"
+        )
+
+    def run(self, input_data: Input, **kwargs) -> BlockOutput:
+        yield "payload", input_data.payload
+        yield "order_id", input_data.payload["orderId"]
+
+
+class Slant3DOrderWebhookBlock(Slant3DTriggerBase, Block):
+    """Block for handling Slant3D order webhooks"""
+
+    class Input(Slant3DTriggerBase.Input):
+        class EventsFilter(BaseModel):
+            """
+            Currently Slant3D only supports 'SHIPPED' status updates
+            Could be expanded in the future with more status types
+            """
+
+            shipped: bool = True
+
+        events: EventsFilter = SchemaField(
+            title="Events",
+            description="Order status events to subscribe to",
+            default=EventsFilter(shipped=True),
+        )
+
+    class Output(Slant3DTriggerBase.Output):
+        status: str = SchemaField(description="The new status of the order")
+        tracking_number: str = SchemaField(
+            description="The tracking number for the shipment"
+        )
+        carrier_code: str = SchemaField(description="The carrier code (e.g., 'usps')")
+
+    def __init__(self):
+        super().__init__(
+            id="8a74c2ad-0104-4640-962f-26c6b69e58cd",
+            description=(
+                "This block triggers on Slant3D order status updates and outputs "
+                "the event details, including tracking information when orders are shipped."
+            ),
+            # All webhooks are currently subscribed to for all orders. This works for self hosted, but not for cloud hosted prod
+            disabled=(
+                settings.Settings().config.behave_as == BehaveAs.CLOUD
+                and settings.Settings().config.app_env != AppEnvironment.LOCAL
+            ),
+            categories={BlockCategory.DEVELOPER_TOOLS},
+            input_schema=self.Input,
+            output_schema=self.Output,
+            webhook_config=BlockWebhookConfig(
+                provider="slant3d",
+                webhook_type="orders",  # Only one type for now
+                resource_format="",  # No resource format needed
+                event_filter_input="events",
+                event_format="order.{event}",
+            ),
+            test_input={
+                "credentials": TEST_CREDENTIALS_INPUT,
+                "events": {"shipped": True},
+                "payload": {
+                    "orderId": "1234567890",
+                    "status": "SHIPPED",
+                    "trackingNumber": "ABCDEF123456",
+                    "carrierCode": "usps",
+                },
+            },
+            test_credentials=TEST_CREDENTIALS,
+            test_output=[
+                (
+                    "payload",
+                    {
+                        "orderId": "1234567890",
+                        "status": "SHIPPED",
+                        "trackingNumber": "ABCDEF123456",
+                        "carrierCode": "usps",
+                    },
+                ),
+                ("order_id", "1234567890"),
+                ("status", "SHIPPED"),
+                ("tracking_number", "ABCDEF123456"),
+                ("carrier_code", "usps"),
+            ],
+        )
+
+    def run(self, input_data: Input, **kwargs) -> BlockOutput:  # type: ignore
+        yield from super().run(input_data, **kwargs)
+
+        # Extract and normalize values from the payload
+        yield "status", input_data.payload["status"]
+        yield "tracking_number", input_data.payload["trackingNumber"]
+        yield "carrier_code", input_data.payload["carrierCode"]

autogpt_platform/backend/backend/blocks/talking_head.py

@@ -10,6 +10,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 from backend.util.request import requests
 
 TEST_CREDENTIALS = APIKeyCredentials(
@@ -29,13 +30,11 @@ TEST_CREDENTIALS_INPUT = {
 
 class CreateTalkingAvatarVideoBlock(Block):
     class Input(BlockSchema):
-        credentials: CredentialsMetaInput[Literal["d_id"], Literal["api_key"]] = (
-            CredentialsField(
-                provider="d_id",
-                supported_credential_types={"api_key"},
-                description="The D-ID integration can be used with "
-                "any API key with sufficient permissions for the blocks it is used on.",
-            )
+        credentials: CredentialsMetaInput[
+            Literal[ProviderName.D_ID], Literal["api_key"]
+        ] = CredentialsField(
+            description="The D-ID integration can be used with "
+            "any API key with sufficient permissions for the blocks it is used on.",
         )
         script_input: str = SchemaField(
             description="The text input for the script",

autogpt_platform/backend/backend/blocks/text.py

@@ -1,13 +1,11 @@
 import re
 from typing import Any
 
-from jinja2 import BaseLoader, Environment
-
 from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema
 from backend.data.model import SchemaField
-from backend.util import json
+from backend.util import json, text
 
-jinja = Environment(loader=BaseLoader())
+formatter = text.TextFormatter()
 
 
 class MatchTextPatternBlock(Block):
@@ -73,6 +71,7 @@ class ExtractTextInformationBlock(Block):
             description="Case sensitive match", default=True
         )
         dot_all: bool = SchemaField(description="Dot matches all", default=True)
+        find_all: bool = SchemaField(description="Find all matches", default=False)
 
     class Output(BlockSchema):
         positive: str = SchemaField(description="Extracted text")
@@ -90,12 +89,27 @@ class ExtractTextInformationBlock(Block):
                 {"text": "Hello, World!", "pattern": "Hello, (.+)", "group": 0},
                 {"text": "Hello, World!", "pattern": "Hello, (.+)", "group": 2},
                 {"text": "Hello, World!", "pattern": "hello,", "case_sensitive": False},
+                {
+                    "text": "Hello, World!! Hello, Earth!!",
+                    "pattern": "Hello, (\\S+)",
+                    "group": 1,
+                    "find_all": False,
+                },
+                {
+                    "text": "Hello, World!! Hello, Earth!!",
+                    "pattern": "Hello, (\\S+)",
+                    "group": 1,
+                    "find_all": True,
+                },
             ],
             test_output=[
                 ("positive", "World!"),
                 ("positive", "Hello, World!"),
                 ("negative", "Hello, World!"),
                 ("positive", "Hello,"),
+                ("positive", "World!!"),
+                ("positive", "World!!"),
+                ("positive", "Earth!!"),
             ],
         )
 
@@ -107,15 +121,21 @@ class ExtractTextInformationBlock(Block):
             flags = flags | re.DOTALL
 
         if isinstance(input_data.text, str):
-            text = input_data.text
+            txt = input_data.text
         else:
-            text = json.dumps(input_data.text)
+            txt = json.dumps(input_data.text)
 
-        match = re.search(input_data.pattern, text, flags)
-        if match and input_data.group <= len(match.groups()):
-            yield "positive", match.group(input_data.group)
-        else:
-            yield "negative", text
+        matches = [
+            match.group(input_data.group)
+            for match in re.finditer(input_data.pattern, txt, flags)
+            if input_data.group <= len(match.groups())
+        ]
+        for match in matches:
+            yield "positive", match
+            if not input_data.find_all:
+                return
+        if not matches:
+            yield "negative", input_data.text
 
 
 class FillTextTemplateBlock(Block):
@@ -146,19 +166,20 @@ class FillTextTemplateBlock(Block):
                     "values": {"list": ["Hello", " World!"]},
                     "format": "{% for item in list %}{{ item }}{% endfor %}",
                 },
+                {
+                    "values": {},
+                    "format": "{% set name = 'Alice' %}Hello, World! {{ name }}",
+                },
             ],
             test_output=[
                 ("output", "Hello, World! Alice"),
                 ("output", "Hello World!"),
+                ("output", "Hello, World! Alice"),
             ],
         )
 
     def run(self, input_data: Input, **kwargs) -> BlockOutput:
-        # For python.format compatibility: replace all {...} with {{..}}.
-        # But avoid replacing {{...}} to {{{...}}}.
-        fmt = re.sub(r"(?<!{){[ a-zA-Z0-9_]+}", r"{\g<0>}", input_data.format)
-        template = jinja.from_string(fmt)
-        yield "output", template.render(**input_data.values)
+        yield "output", formatter.format_string(input_data.format, input_data.values)
 
 
 class CombineTextsBlock(Block):

autogpt_platform/backend/backend/blocks/text_to_speech_block.py

@@ -9,6 +9,7 @@ from backend.data.model import (
     CredentialsMetaInput,
     SchemaField,
 )
+from backend.integrations.providers import ProviderName
 from backend.util.request import requests
 
 TEST_CREDENTIALS = APIKeyCredentials(
@@ -38,10 +39,8 @@ class UnrealTextToSpeechBlock(Block):
             default="Scarlett",
         )
         credentials: CredentialsMetaInput[
-            Literal["unreal_speech"], Literal["api_key"]
+            Literal[ProviderName.UNREAL_SPEECH], Literal["api_key"]
         ] = CredentialsField(
-            provider="unreal_speech",
-            supported_credential_types={"api_key"},
             description="The Unreal Speech integration can be used with "
             "any API key with sufficient permissions for the blocks it is used on.",
         )

autogpt_platform/backend/backend/data/block.py

@@ -65,7 +65,7 @@ class BlockCategory(Enum):
 
 
 class BlockSchema(BaseModel):
-    cached_jsonschema: ClassVar[dict[str, Any]] = {}
+    cached_jsonschema: ClassVar[dict[str, Any]]
 
     @classmethod
     def jsonschema(cls) -> dict[str, Any]:
@@ -145,6 +145,10 @@ class BlockSchema(BaseModel):
         - A field that is called `credentials` MUST be a `CredentialsMetaInput`.
         """
         super().__pydantic_init_subclass__(**kwargs)
+
+        # Reset cached JSON schema to prevent inheriting it from parent class
+        cls.cached_jsonschema = {}
+
         credentials_fields = [
             field_name
             for field_name, info in cls.model_fields.items()
@@ -176,6 +180,11 @@ class BlockSchema(BaseModel):
                 f"Field 'credentials' on {cls.__qualname__} "
                 f"must be of type {CredentialsMetaInput.__name__}"
             )
+        if credentials_field := cls.model_fields.get(CREDENTIALS_FIELD_NAME):
+            credentials_input_type = cast(
+                CredentialsMetaInput, credentials_field.annotation
+            )
+            credentials_input_type.validate_credentials_field_schema(cls)
 
 
 BlockSchemaInputType = TypeVar("BlockSchemaInputType", bound=BlockSchema)

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -53,8 +53,8 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.LLAMA3_1_8B: 1,
     LlmModel.OLLAMA_LLAMA3_8B: 1,
     LlmModel.OLLAMA_LLAMA3_405B: 1,
+    LlmModel.OLLAMA_DOLPHIN: 1,
     LlmModel.GEMINI_FLASH_1_5_8B: 1,
-    LlmModel.GEMINI_FLASH_1_5_EXP: 1,
     LlmModel.GROK_BETA: 5,
     LlmModel.MISTRAL_NEMO: 1,
     LlmModel.COHERE_COMMAND_R_08_2024: 1,
@@ -62,6 +62,14 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.EVA_QWEN_2_5_32B: 1,
     LlmModel.DEEPSEEK_CHAT: 2,
     LlmModel.PERPLEXITY_LLAMA_3_1_SONAR_LARGE_128K_ONLINE: 1,
+    LlmModel.QWEN_QWQ_32B_PREVIEW: 2,
+    LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_405B: 1,
+    LlmModel.NOUSRESEARCH_HERMES_3_LLAMA_3_1_70B: 1,
+    LlmModel.AMAZON_NOVA_LITE_V1: 1,
+    LlmModel.AMAZON_NOVA_MICRO_V1: 1,
+    LlmModel.AMAZON_NOVA_PRO_V1: 1,
+    LlmModel.MICROSOFT_WIZARDLM_2_8X22B: 1,
+    LlmModel.GRYPHE_MYTHOMAX_L2_13B: 1,
 }
 
 for model in LlmModel:

autogpt_platform/backend/backend/data/cost.py

@@ -10,6 +10,7 @@ class BlockCostType(str, Enum):
     RUN = "run"  # cost X credits per run
     BYTE = "byte"  # cost X credits per byte
     SECOND = "second"  # cost X credits per second
+    DOLLAR = "dollar"  # cost X dollars per run
 
 
 class BlockCost(BaseModel):

autogpt_platform/backend/backend/data/credit.py

@@ -2,9 +2,9 @@ from abc import ABC, abstractmethod
 from datetime import datetime, timezone
 
 from prisma import Json
-from prisma.enums import UserBlockCreditType
+from prisma.enums import CreditTransactionType
 from prisma.errors import UniqueViolationError
-from prisma.models import UserBlockCredit
+from prisma.models import CreditTransaction
 
 from backend.data.block import Block, BlockInput, get_block
 from backend.data.block_cost_config import BLOCK_COSTS
@@ -76,7 +76,7 @@ class UserCredit(UserCreditBase):
             else cur_month.replace(year=cur_month.year + 1, month=1)
         )
 
-        user_credit = await UserBlockCredit.prisma().group_by(
+        user_credit = await CreditTransaction.prisma().group_by(
             by=["userId"],
             sum={"amount": True},
             where={
@@ -93,10 +93,10 @@ class UserCredit(UserCreditBase):
         key = f"MONTHLY-CREDIT-TOP-UP-{cur_month}"
 
         try:
-            await UserBlockCredit.prisma().create(
+            await CreditTransaction.prisma().create(
                 data={
                     "amount": self.num_user_credits_refill,
-                    "type": UserBlockCreditType.TOP_UP,
+                    "type": CreditTransactionType.TOP_UP,
                     "userId": user_id,
                     "transactionKey": key,
                     "createdAt": self.time_now(),
@@ -184,11 +184,11 @@ class UserCredit(UserCreditBase):
         if validate_balance and user_credit < cost:
             raise ValueError(f"Insufficient credit: {user_credit} < {cost}")
 
-        await UserBlockCredit.prisma().create(
+        await CreditTransaction.prisma().create(
             data={
                 "userId": user_id,
                 "amount": -cost,
-                "type": UserBlockCreditType.USAGE,
+                "type": CreditTransactionType.USAGE,
                 "blockId": block.id,
                 "metadata": Json(
                     {
@@ -202,11 +202,11 @@ class UserCredit(UserCreditBase):
         return cost
 
     async def top_up_credits(self, user_id: str, amount: int):
-        await UserBlockCredit.prisma().create(
+        await CreditTransaction.prisma().create(
             data={
                 "userId": user_id,
                 "amount": amount,
-                "type": UserBlockCreditType.TOP_UP,
+                "type": CreditTransactionType.TOP_UP,
                 "createdAt": self.time_now(),
             }
         )

autogpt_platform/backend/backend/data/db.py

@@ -29,6 +29,13 @@ async def connect():
     if not prisma.is_connected():
         raise ConnectionError("Failed to connect to Prisma.")
 
+    # Connection acquired from a pool like Supabase somehow still possibly allows
+    # the db client obtains a connection but still reject query connection afterward.
+    try:
+        await prisma.execute_raw("SELECT 1")
+    except Exception as e:
+        raise ConnectionError("Failed to connect to Prisma.") from e
+
 
 @conn_retry("Prisma", "Releasing connection")
 async def disconnect():

autogpt_platform/backend/backend/data/execution.py

@@ -9,7 +9,6 @@ from prisma.models import (
     AgentNodeExecution,
     AgentNodeExecutionInputOutput,
 )
-from prisma.types import AgentGraphExecutionWhereInput
 from pydantic import BaseModel
 
 from backend.data.block import BlockData, BlockInput, CompletedBlockOutput
@@ -19,14 +18,14 @@ from backend.util import json, mock
 from backend.util.settings import Config
 
 
-class GraphExecution(BaseModel):
+class GraphExecutionEntry(BaseModel):
     user_id: str
     graph_exec_id: str
     graph_id: str
-    start_node_execs: list["NodeExecution"]
+    start_node_execs: list["NodeExecutionEntry"]
 
 
-class NodeExecution(BaseModel):
+class NodeExecutionEntry(BaseModel):
     user_id: str
     graph_exec_id: str
     graph_id: str
@@ -325,34 +324,6 @@ async def update_execution_status(
     return ExecutionResult.from_db(res)
 
 
-async def get_graph_execution(
-    graph_exec_id: str, user_id: str
-) -> AgentGraphExecution | None:
-    """
-    Retrieve a specific graph execution by its ID.
-
-    Args:
-        graph_exec_id (str): The ID of the graph execution to retrieve.
-        user_id (str): The ID of the user to whom the graph (execution) belongs.
-
-    Returns:
-        AgentGraphExecution | None: The graph execution if found, None otherwise.
-    """
-    execution = await AgentGraphExecution.prisma().find_first(
-        where={"id": graph_exec_id, "userId": user_id},
-        include=GRAPH_EXECUTION_INCLUDE,
-    )
-    return execution
-
-
-async def list_executions(graph_id: str, graph_version: int | None = None) -> list[str]:
-    where: AgentGraphExecutionWhereInput = {"agentGraphId": graph_id}
-    if graph_version is not None:
-        where["agentGraphVersion"] = graph_version
-    executions = await AgentGraphExecution.prisma().find_many(where=where)
-    return [execution.id for execution in executions]
-
-
 async def get_execution_results(graph_exec_id: str) -> list[ExecutionResult]:
     executions = await AgentNodeExecution.prisma().find_many(
         where={"agentGraphExecutionId": graph_exec_id},

autogpt_platform/backend/backend/data/graph.py

@@ -105,6 +105,8 @@ class GraphExecution(BaseDbModel):
     duration: float
     total_run_time: float
     status: ExecutionStatus
+    graph_id: str
+    graph_version: int
 
     @staticmethod
     def from_db(execution: AgentGraphExecution):
@@ -130,6 +132,8 @@ class GraphExecution(BaseDbModel):
             duration=duration,
             total_run_time=total_run_time,
             status=ExecutionStatus(execution.executionStatus),
+            graph_id=execution.agentGraphId,
+            graph_version=execution.agentGraphVersion,
         )
 
 
@@ -139,7 +143,6 @@ class Graph(BaseDbModel):
     is_template: bool = False
     name: str
     description: str
-    executions: list[GraphExecution] = []
     nodes: list[Node] = []
     links: list[Link] = []
 
@@ -254,7 +257,7 @@ class GraphModel(Graph):
         for link in self.links:
             input_links[link.sink_id].append(link)
 
-        # Nodes: required fields are filled or connected and dependencies are satisfied
+        # Nodes: required fields are filled or connected
         for node in self.nodes:
             block = get_block(node.block_id)
             if block is None:
@@ -275,38 +278,6 @@ class GraphModel(Graph):
                         f"Node {block.name} #{node.id} required input missing: `{name}`"
                     )
 
-            # Get input schema properties and check dependencies
-            input_schema = block.input_schema.model_fields
-            required_fields = block.input_schema.get_required_fields()
-
-            def has_value(name):
-                return (
-                    node is not None
-                    and name in node.input_default
-                    and node.input_default[name] is not None
-                    and str(node.input_default[name]).strip() != ""
-                ) or (name in input_schema and input_schema[name].default is not None)
-
-            # Validate dependencies between fields
-            for field_name, field_info in input_schema.items():
-
-                # Apply input dependency validation only on run & field with depends_on
-                json_schema_extra = field_info.json_schema_extra or {}
-                dependencies = json_schema_extra.get("depends_on", [])
-                if not for_run or not dependencies:
-                    continue
-
-                # Check if dependent field has value in input_default
-                field_has_value = has_value(field_name)
-                field_is_required = field_name in required_fields
-
-                # Check for missing dependencies when dependent field is present
-                missing_deps = [dep for dep in dependencies if not has_value(dep)]
-                if missing_deps and (field_has_value or field_is_required):
-                    raise ValueError(
-                        f"Node {block.name} #{node.id}: Field `{field_name}` requires [{', '.join(missing_deps)}] to be set"
-                    )
-
         node_map = {v.id: v for v in self.nodes}
 
         def is_static_output_block(nid: str) -> bool:
@@ -357,11 +328,6 @@ class GraphModel(Graph):
 
     @staticmethod
     def from_db(graph: AgentGraph, hide_credentials: bool = False):
-        executions = [
-            GraphExecution.from_db(execution)
-            for execution in graph.AgentGraphExecution or []
-        ]
-
         return GraphModel(
             id=graph.id,
             user_id=graph.userId,
@@ -370,7 +336,6 @@ class GraphModel(Graph):
             is_template=graph.isTemplate,
             name=graph.name or "",
             description=graph.description or "",
-            executions=executions,
             nodes=[
                 GraphModel._process_node(node, hide_credentials)
                 for node in graph.AgentNodes or []
@@ -440,7 +405,6 @@ async def set_node_webhook(node_id: str, webhook_id: str | None) -> NodeModel:
 
 async def get_graphs(
     user_id: str,
-    include_executions: bool = False,
     filter_by: Literal["active", "template"] | None = "active",
 ) -> list[GraphModel]:
     """
@@ -448,35 +412,44 @@ async def get_graphs(
     Default behaviour is to get all currently active graphs.
 
     Args:
-        include_executions: Whether to include executions in the graph metadata.
         filter_by: An optional filter to either select templates or active graphs.
         user_id: The ID of the user that owns the graph.
 
     Returns:
         list[GraphModel]: A list of objects representing the retrieved graphs.
     """
-    where_clause: AgentGraphWhereInput = {}
+    where_clause: AgentGraphWhereInput = {"userId": user_id}
 
     if filter_by == "active":
         where_clause["isActive"] = True
     elif filter_by == "template":
         where_clause["isTemplate"] = True
 
-    where_clause["userId"] = user_id
-
-    graph_include = AGENT_GRAPH_INCLUDE
-    graph_include["AgentGraphExecution"] = include_executions
-
     graphs = await AgentGraph.prisma().find_many(
         where=where_clause,
         distinct=["id"],
         order={"version": "desc"},
-        include=graph_include,
+        include=AGENT_GRAPH_INCLUDE,
     )
 
     return [GraphModel.from_db(graph) for graph in graphs]
 
 
+async def get_executions(user_id: str) -> list[GraphExecution]:
+    executions = await AgentGraphExecution.prisma().find_many(
+        where={"userId": user_id},
+        order={"createdAt": "desc"},
+    )
+    return [GraphExecution.from_db(execution) for execution in executions]
+
+
+async def get_execution(user_id: str, execution_id: str) -> GraphExecution | None:
+    execution = await AgentGraphExecution.prisma().find_first(
+        where={"id": execution_id, "userId": user_id}
+    )
+    return GraphExecution.from_db(execution) if execution else None
+
+
 async def get_graph(
     graph_id: str,
     version: int | None = None,

autogpt_platform/backend/backend/data/integrations.py

@@ -7,6 +7,7 @@ from pydantic import Field
 
 from backend.data.includes import INTEGRATION_WEBHOOK_INCLUDE
 from backend.data.queue import AsyncRedisEventBus
+from backend.integrations.providers import ProviderName
 
 from .db import BaseDbModel
 
@@ -18,7 +19,7 @@ logger = logging.getLogger(__name__)
 
 class Webhook(BaseDbModel):
     user_id: str
-    provider: str
+    provider: ProviderName
     credentials_id: str
     webhook_type: str
     resource: str
@@ -37,7 +38,7 @@ class Webhook(BaseDbModel):
         return Webhook(
             id=webhook.id,
             user_id=webhook.userId,
-            provider=webhook.provider,
+            provider=ProviderName(webhook.provider),
             credentials_id=webhook.credentialsId,
             webhook_type=webhook.webhookType,
             resource=webhook.resource,
@@ -61,7 +62,7 @@ async def create_webhook(webhook: Webhook) -> Webhook:
         data={
             "id": webhook.id,
             "userId": webhook.user_id,
-            "provider": webhook.provider,
+            "provider": webhook.provider.value,
             "credentialsId": webhook.credentials_id,
             "webhookType": webhook.webhook_type,
             "resource": webhook.resource,
@@ -144,25 +145,28 @@ class WebhookEventBus(AsyncRedisEventBus[WebhookEvent]):
     def event_bus_name(self) -> str:
         return "webhooks"
 
-    async def publish(self, event: WebhookEvent):
-        await self.publish_event(event, f"{event.webhook_id}/{event.event_type}")
 
-    async def listen(
-        self, webhook_id: str, event_type: Optional[str] = None
-    ) -> AsyncGenerator[WebhookEvent, None]:
-        async for event in self.listen_events(f"{webhook_id}/{event_type or '*'}"):
-            yield event
-
-
-event_bus = WebhookEventBus()
+_webhook_event_bus = WebhookEventBus()
 
 
 async def publish_webhook_event(event: WebhookEvent):
-    await event_bus.publish(event)
+    await _webhook_event_bus.publish_event(
+        event, f"{event.webhook_id}/{event.event_type}"
+    )
 
 
-async def listen_for_webhook_event(
+async def listen_for_webhook_events(
     webhook_id: str, event_type: Optional[str] = None
+) -> AsyncGenerator[WebhookEvent, None]:
+    async for event in _webhook_event_bus.listen_events(
+        f"{webhook_id}/{event_type or '*'}"
+    ):
+        yield event
+
+
+async def wait_for_webhook_event(
+    webhook_id: str, event_type: Optional[str] = None, timeout: Optional[float] = None
 ) -> WebhookEvent | None:
-    async for event in event_bus.listen(webhook_id, event_type):
-        return event  # Only one event is expected
+    return await _webhook_event_bus.wait_for_event(
+        f"{webhook_id}/{event_type or '*'}", timeout
+    )

autogpt_platform/backend/backend/data/model.py

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 import logging
 from typing import (
+    TYPE_CHECKING,
     Annotated,
     Any,
     Callable,
@@ -11,19 +12,32 @@ from typing import (
     Optional,
     TypedDict,
     TypeVar,
+    get_args,
 )
 from uuid import uuid4
 
-from pydantic import BaseModel, Field, GetCoreSchemaHandler, SecretStr, field_serializer
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    GetCoreSchemaHandler,
+    SecretStr,
+    field_serializer,
+)
 from pydantic_core import (
     CoreSchema,
     PydanticUndefined,
     PydanticUndefinedType,
+    ValidationError,
     core_schema,
 )
 
+from backend.integrations.providers import ProviderName
 from backend.util.settings import Secrets
 
+if TYPE_CHECKING:
+    from backend.data.block import BlockSchema
+
 T = TypeVar("T")
 logger = logging.getLogger(__name__)
 
@@ -120,11 +134,10 @@ def SchemaField(
     title: Optional[str] = None,
     description: Optional[str] = None,
     placeholder: Optional[str] = None,
-    advanced: Optional[bool] = None,
+    advanced: Optional[bool] = False,
     secret: bool = False,
     exclude: bool = False,
     hidden: Optional[bool] = None,
-    depends_on: list[str] | None = None,
     **kwargs,
 ) -> T:
     json_extra = {
@@ -134,7 +147,6 @@ def SchemaField(
             "secret": secret,
             "advanced": advanced,
             "hidden": hidden,
-            "depends_on": depends_on,
         }.items()
         if v is not None
     }
@@ -148,7 +160,7 @@ def SchemaField(
         exclude=exclude,
         json_schema_extra=json_extra,
         **kwargs,
-    )
+    )  # type: ignore
 
 
 class _BaseCredentials(BaseModel):
@@ -222,7 +234,7 @@ class UserIntegrations(BaseModel):
     oauth_states: list[OAuthState] = Field(default_factory=list)
 
 
-CP = TypeVar("CP", bound=str)
+CP = TypeVar("CP", bound=ProviderName)
 CT = TypeVar("CT", bound=CredentialsType)
 
 
@@ -235,19 +247,51 @@ class CredentialsMetaInput(BaseModel, Generic[CP, CT]):
     provider: CP
     type: CT
 
+    @staticmethod
+    def _add_json_schema_extra(schema, cls: CredentialsMetaInput):
+        schema["credentials_provider"] = get_args(
+            cls.model_fields["provider"].annotation
+        )
+        schema["credentials_types"] = get_args(cls.model_fields["type"].annotation)
 
-class CredentialsFieldSchemaExtra(BaseModel, Generic[CP, CT]):
+    model_config = ConfigDict(
+        json_schema_extra=_add_json_schema_extra,  # type: ignore
+    )
+
+    @classmethod
+    def validate_credentials_field_schema(cls, model: type["BlockSchema"]):
+        """Validates the schema of a `credentials` field"""
+        field_schema = model.jsonschema()["properties"][CREDENTIALS_FIELD_NAME]
+        try:
+            schema_extra = _CredentialsFieldSchemaExtra[CP, CT].model_validate(
+                field_schema
+            )
+        except ValidationError as e:
+            if "Field required [type=missing" not in str(e):
+                raise
+
+            raise TypeError(
+                "Field 'credentials' JSON schema lacks required extra items: "
+                f"{field_schema}"
+            ) from e
+
+        if (
+            len(schema_extra.credentials_provider) > 1
+            and not schema_extra.discriminator
+        ):
+            raise TypeError("Multi-provider CredentialsField requires discriminator!")
+
+
+class _CredentialsFieldSchemaExtra(BaseModel, Generic[CP, CT]):
     # TODO: move discrimination mechanism out of CredentialsField (frontend + backend)
     credentials_provider: list[CP]
-    credentials_scopes: Optional[list[str]]
+    credentials_scopes: Optional[list[str]] = None
     credentials_types: list[CT]
     discriminator: Optional[str] = None
     discriminator_mapping: Optional[dict[str, CP]] = None
 
 
 def CredentialsField(
-    provider: CP | list[CP],
-    supported_credential_types: set[CT],
     required_scopes: set[str] = set(),
     *,
     discriminator: Optional[str] = None,
@@ -255,26 +299,26 @@ def CredentialsField(
     title: Optional[str] = None,
     description: Optional[str] = None,
     **kwargs,
-) -> CredentialsMetaInput[CP, CT]:
+) -> CredentialsMetaInput:
     """
     `CredentialsField` must and can only be used on fields named `credentials`.
     This is enforced by the `BlockSchema` base class.
     """
-    if not isinstance(provider, str) and len(provider) > 1 and not discriminator:
-        raise TypeError("Multi-provider CredentialsField requires discriminator!")
 
-    field_schema_extra = CredentialsFieldSchemaExtra[CP, CT](
-        credentials_provider=[provider] if isinstance(provider, str) else provider,
-        credentials_scopes=list(required_scopes) or None,  # omit if empty
-        credentials_types=list(supported_credential_types),
-        discriminator=discriminator,
-        discriminator_mapping=discriminator_mapping,
-    )
+    field_schema_extra = {
+        k: v
+        for k, v in {
+            "credentials_scopes": list(required_scopes) or None,
+            "discriminator": discriminator,
+            "discriminator_mapping": discriminator_mapping,
+        }.items()
+        if v is not None
+    }
 
     return Field(
         title=title,
         description=description,
-        json_schema_extra=field_schema_extra.model_dump(exclude_none=True),
+        json_schema_extra=field_schema_extra,  # validated on BlockSchema init
         **kwargs,
     )
 

autogpt_platform/backend/backend/data/queue.py

@@ -1,8 +1,9 @@
+import asyncio
 import json
 import logging
 from abc import ABC, abstractmethod
 from datetime import datetime
-from typing import Any, AsyncGenerator, Generator, Generic, TypeVar
+from typing import Any, AsyncGenerator, Generator, Generic, Optional, TypeVar
 
 from pydantic import BaseModel
 from redis.asyncio.client import PubSub as AsyncPubSub
@@ -48,12 +49,12 @@ class BaseRedisEventBus(Generic[M], ABC):
         except Exception as e:
             logger.error(f"Failed to parse event result from Redis {msg} {e}")
 
-    def _subscribe(
+    def _get_pubsub_channel(
         self, connection: redis.Redis | redis.AsyncRedis, channel_key: str
     ) -> tuple[PubSub | AsyncPubSub, str]:
-        channel_name = f"{self.event_bus_name}/{channel_key}"
+        full_channel_name = f"{self.event_bus_name}/{channel_key}"
         pubsub = connection.pubsub()
-        return pubsub, channel_name
+        return pubsub, full_channel_name
 
 
 class RedisEventBus(BaseRedisEventBus[M], ABC):
@@ -64,17 +65,19 @@ class RedisEventBus(BaseRedisEventBus[M], ABC):
         return redis.get_redis()
 
     def publish_event(self, event: M, channel_key: str):
-        message, channel_name = self._serialize_message(event, channel_key)
-        self.connection.publish(channel_name, message)
+        message, full_channel_name = self._serialize_message(event, channel_key)
+        self.connection.publish(full_channel_name, message)
 
     def listen_events(self, channel_key: str) -> Generator[M, None, None]:
-        pubsub, channel_name = self._subscribe(self.connection, channel_key)
+        pubsub, full_channel_name = self._get_pubsub_channel(
+            self.connection, channel_key
+        )
         assert isinstance(pubsub, PubSub)
 
         if "*" in channel_key:
-            pubsub.psubscribe(channel_name)
+            pubsub.psubscribe(full_channel_name)
         else:
-            pubsub.subscribe(channel_name)
+            pubsub.subscribe(full_channel_name)
 
         for message in pubsub.listen():
             if event := self._deserialize_message(message, channel_key):
@@ -89,19 +92,31 @@ class AsyncRedisEventBus(BaseRedisEventBus[M], ABC):
         return await redis.get_redis_async()
 
     async def publish_event(self, event: M, channel_key: str):
-        message, channel_name = self._serialize_message(event, channel_key)
+        message, full_channel_name = self._serialize_message(event, channel_key)
         connection = await self.connection
-        await connection.publish(channel_name, message)
+        await connection.publish(full_channel_name, message)
 
     async def listen_events(self, channel_key: str) -> AsyncGenerator[M, None]:
-        pubsub, channel_name = self._subscribe(await self.connection, channel_key)
+        pubsub, full_channel_name = self._get_pubsub_channel(
+            await self.connection, channel_key
+        )
         assert isinstance(pubsub, AsyncPubSub)
 
         if "*" in channel_key:
-            await pubsub.psubscribe(channel_name)
+            await pubsub.psubscribe(full_channel_name)
         else:
-            await pubsub.subscribe(channel_name)
+            await pubsub.subscribe(full_channel_name)
 
         async for message in pubsub.listen():
             if event := self._deserialize_message(message, channel_key):
                 yield event
+
+    async def wait_for_event(
+        self, channel_key: str, timeout: Optional[float] = None
+    ) -> M | None:
+        try:
+            return await asyncio.wait_for(
+                anext(aiter(self.listen_events(channel_key))), timeout
+            )
+        except TimeoutError:
+            return None

autogpt_platform/backend/backend/executor/manager.py

@@ -25,8 +25,8 @@ from backend.data.execution import (
     ExecutionQueue,
     ExecutionResult,
     ExecutionStatus,
-    GraphExecution,
-    NodeExecution,
+    GraphExecutionEntry,
+    NodeExecutionEntry,
     merge_execution_input,
     parse_execution_output,
 )
@@ -96,13 +96,13 @@ class LogMetadata:
 
 
 T = TypeVar("T")
-ExecutionStream = Generator[NodeExecution, None, None]
+ExecutionStream = Generator[NodeExecutionEntry, None, None]
 
 
 def execute_node(
     db_client: "DatabaseManager",
     creds_manager: IntegrationCredentialsManager,
-    data: NodeExecution,
+    data: NodeExecutionEntry,
     execution_stats: dict[str, Any] | None = None,
 ) -> ExecutionStream:
     """
@@ -252,15 +252,15 @@ def _enqueue_next_nodes(
     graph_exec_id: str,
     graph_id: str,
     log_metadata: LogMetadata,
-) -> list[NodeExecution]:
+) -> list[NodeExecutionEntry]:
     def add_enqueued_execution(
         node_exec_id: str, node_id: str, data: BlockInput
-    ) -> NodeExecution:
+    ) -> NodeExecutionEntry:
         exec_update = db_client.update_execution_status(
             node_exec_id, ExecutionStatus.QUEUED, data
         )
         db_client.send_execution_update(exec_update)
-        return NodeExecution(
+        return NodeExecutionEntry(
             user_id=user_id,
             graph_exec_id=graph_exec_id,
             graph_id=graph_id,
@@ -269,7 +269,7 @@ def _enqueue_next_nodes(
             data=data,
         )
 
-    def register_next_executions(node_link: Link) -> list[NodeExecution]:
+    def register_next_executions(node_link: Link) -> list[NodeExecutionEntry]:
         enqueued_executions = []
         next_output_name = node_link.source_name
         next_input_name = node_link.sink_name
@@ -501,8 +501,8 @@ class Executor:
     @error_logged
     def on_node_execution(
         cls,
-        q: ExecutionQueue[NodeExecution],
-        node_exec: NodeExecution,
+        q: ExecutionQueue[NodeExecutionEntry],
+        node_exec: NodeExecutionEntry,
     ) -> dict[str, Any]:
         log_metadata = LogMetadata(
             user_id=node_exec.user_id,
@@ -529,8 +529,8 @@ class Executor:
     @time_measured
     def _on_node_execution(
         cls,
-        q: ExecutionQueue[NodeExecution],
-        node_exec: NodeExecution,
+        q: ExecutionQueue[NodeExecutionEntry],
+        node_exec: NodeExecutionEntry,
         log_metadata: LogMetadata,
         stats: dict[str, Any] | None = None,
     ):
@@ -580,7 +580,9 @@ class Executor:
 
     @classmethod
     @error_logged
-    def on_graph_execution(cls, graph_exec: GraphExecution, cancel: threading.Event):
+    def on_graph_execution(
+        cls, graph_exec: GraphExecutionEntry, cancel: threading.Event
+    ):
         log_metadata = LogMetadata(
             user_id=graph_exec.user_id,
             graph_eid=graph_exec.graph_exec_id,
@@ -605,7 +607,7 @@ class Executor:
     @time_measured
     def _on_graph_execution(
         cls,
-        graph_exec: GraphExecution,
+        graph_exec: GraphExecutionEntry,
         cancel: threading.Event,
         log_metadata: LogMetadata,
     ) -> tuple[dict[str, Any], Exception | None]:
@@ -636,13 +638,13 @@ class Executor:
         cancel_thread.start()
 
         try:
-            queue = ExecutionQueue[NodeExecution]()
+            queue = ExecutionQueue[NodeExecutionEntry]()
             for node_exec in graph_exec.start_node_execs:
                 queue.add(node_exec)
 
             running_executions: dict[str, AsyncResult] = {}
 
-            def make_exec_callback(exec_data: NodeExecution):
+            def make_exec_callback(exec_data: NodeExecutionEntry):
                 node_id = exec_data.node_id
 
                 def callback(result: object):
@@ -717,7 +719,7 @@ class ExecutionManager(AppService):
         self.use_redis = True
         self.use_supabase = True
         self.pool_size = settings.config.num_graph_workers
-        self.queue = ExecutionQueue[GraphExecution]()
+        self.queue = ExecutionQueue[GraphExecutionEntry]()
         self.active_graph_runs: dict[str, tuple[Future, threading.Event]] = {}
 
     @classmethod
@@ -768,7 +770,7 @@ class ExecutionManager(AppService):
         data: BlockInput,
         user_id: str,
         graph_version: int | None = None,
-    ) -> GraphExecution:
+    ) -> GraphExecutionEntry:
         graph: GraphModel | None = self.db_client.get_graph(
             graph_id=graph_id, user_id=user_id, version=graph_version
         )
@@ -818,7 +820,7 @@ class ExecutionManager(AppService):
         starting_node_execs = []
         for node_exec in node_execs:
             starting_node_execs.append(
-                NodeExecution(
+                NodeExecutionEntry(
                     user_id=user_id,
                     graph_exec_id=node_exec.graph_exec_id,
                     graph_id=node_exec.graph_id,
@@ -832,7 +834,7 @@ class ExecutionManager(AppService):
             )
             self.db_client.send_execution_update(exec_update)
 
-        graph_exec = GraphExecution(
+        graph_exec = GraphExecutionEntry(
             user_id=user_id,
             graph_id=graph_id,
             graph_exec_id=graph_exec_id,

autogpt_platform/backend/backend/integrations/creds_manager.py

@@ -1,6 +1,7 @@
 import logging
 from contextlib import contextmanager
 from datetime import datetime
+from typing import TYPE_CHECKING
 
 from autogpt_libs.utils.synchronize import RedisKeyedMutex
 from redis.lock import Lock as RedisLock
@@ -8,10 +9,13 @@ from redis.lock import Lock as RedisLock
 from backend.data import redis
 from backend.data.model import Credentials
 from backend.integrations.credentials_store import IntegrationCredentialsStore
-from backend.integrations.oauth import HANDLERS_BY_NAME, BaseOAuthHandler
+from backend.integrations.oauth import HANDLERS_BY_NAME
 from backend.util.exceptions import MissingConfigError
 from backend.util.settings import Settings
 
+if TYPE_CHECKING:
+    from backend.integrations.oauth import BaseOAuthHandler
+
 logger = logging.getLogger(__name__)
 settings = Settings()
 
@@ -148,7 +152,7 @@ class IntegrationCredentialsManager:
         self.store.locks.release_all_locks()
 
 
-def _get_provider_oauth_handler(provider_name: str) -> BaseOAuthHandler:
+def _get_provider_oauth_handler(provider_name: str) -> "BaseOAuthHandler":
     if provider_name not in HANDLERS_BY_NAME:
         raise KeyError(f"Unknown provider '{provider_name}'")
 

autogpt_platform/backend/backend/integrations/oauth/__init__.py

@@ -1,10 +1,15 @@
-from .base import BaseOAuthHandler
+from typing import TYPE_CHECKING
+
 from .github import GitHubOAuthHandler
 from .google import GoogleOAuthHandler
 from .notion import NotionOAuthHandler
 
+if TYPE_CHECKING:
+    from ..providers import ProviderName
+    from .base import BaseOAuthHandler
+
 # --8<-- [start:HANDLERS_BY_NAMEExample]
-HANDLERS_BY_NAME: dict[str, type[BaseOAuthHandler]] = {
+HANDLERS_BY_NAME: dict["ProviderName", type["BaseOAuthHandler"]] = {
     handler.PROVIDER_NAME: handler
     for handler in [
         GitHubOAuthHandler,

autogpt_platform/backend/backend/integrations/oauth/base.py

@@ -4,13 +4,14 @@ from abc import ABC, abstractmethod
 from typing import ClassVar
 
 from backend.data.model import OAuth2Credentials
+from backend.integrations.providers import ProviderName
 
 logger = logging.getLogger(__name__)
 
 
 class BaseOAuthHandler(ABC):
     # --8<-- [start:BaseOAuthHandler1]
-    PROVIDER_NAME: ClassVar[str]
+    PROVIDER_NAME: ClassVar[ProviderName]
     DEFAULT_SCOPES: ClassVar[list[str]] = []
     # --8<-- [end:BaseOAuthHandler1]
 
@@ -76,6 +77,8 @@ class BaseOAuthHandler(ABC):
         """Handles the default scopes for the provider"""
         # If scopes are empty, use the default scopes for the provider
         if not scopes:
-            logger.debug(f"Using default scopes for provider {self.PROVIDER_NAME}")
+            logger.debug(
+                f"Using default scopes for provider {self.PROVIDER_NAME.value}"
+            )
             scopes = self.DEFAULT_SCOPES
         return scopes

autogpt_platform/backend/backend/integrations/oauth/github.py

@@ -3,6 +3,7 @@ from typing import Optional
 from urllib.parse import urlencode
 
 from backend.data.model import OAuth2Credentials
+from backend.integrations.providers import ProviderName
 from backend.util.request import requests
 
 from .base import BaseOAuthHandler
@@ -23,7 +24,7 @@ class GitHubOAuthHandler(BaseOAuthHandler):
       access token *with no refresh token*.
     """  # noqa
 
-    PROVIDER_NAME = "github"
+    PROVIDER_NAME = ProviderName.GITHUB
 
     def __init__(self, client_id: str, client_secret: str, redirect_uri: str):
         self.client_id = client_id

autogpt_platform/backend/backend/integrations/oauth/google.py

@@ -9,6 +9,7 @@ from google_auth_oauthlib.flow import Flow
 from pydantic import SecretStr
 
 from backend.data.model import OAuth2Credentials
+from backend.integrations.providers import ProviderName
 
 from .base import BaseOAuthHandler
 
@@ -21,7 +22,7 @@ class GoogleOAuthHandler(BaseOAuthHandler):
     Based on the documentation at https://developers.google.com/identity/protocols/oauth2/web-server
     """  # noqa
 
-    PROVIDER_NAME = "google"
+    PROVIDER_NAME = ProviderName.GOOGLE
     EMAIL_ENDPOINT = "https://www.googleapis.com/oauth2/v2/userinfo"
     DEFAULT_SCOPES = [
         "https://www.googleapis.com/auth/userinfo.email",

autogpt_platform/backend/backend/integrations/oauth/notion.py

@@ -2,6 +2,7 @@ from base64 import b64encode
 from urllib.parse import urlencode
 
 from backend.data.model import OAuth2Credentials
+from backend.integrations.providers import ProviderName
 from backend.util.request import requests
 
 from .base import BaseOAuthHandler
@@ -16,7 +17,7 @@ class NotionOAuthHandler(BaseOAuthHandler):
     - Notion doesn't use scopes
     """
 
-    PROVIDER_NAME = "notion"
+    PROVIDER_NAME = ProviderName.NOTION
 
     def __init__(self, client_id: str, client_secret: str, redirect_uri: str):
         self.client_id = client_id

autogpt_platform/backend/backend/integrations/providers.py

@@ -1,7 +1,30 @@
 from enum import Enum
 
 
+# --8<-- [start:ProviderName]
 class ProviderName(str, Enum):
+    ANTHROPIC = "anthropic"
+    DISCORD = "discord"
+    D_ID = "d_id"
+    E2B = "e2b"
+    EXA = "exa"
+    FAL = "fal"
     GITHUB = "github"
     GOOGLE = "google"
+    GOOGLE_MAPS = "google_maps"
+    GROQ = "groq"
+    HUBSPOT = "hubspot"
+    IDEOGRAM = "ideogram"
+    JINA = "jina"
+    MEDIUM = "medium"
     NOTION = "notion"
+    OLLAMA = "ollama"
+    OPENAI = "openai"
+    OPENWEATHERMAP = "openweathermap"
+    OPEN_ROUTER = "open_router"
+    PINECONE = "pinecone"
+    REPLICATE = "replicate"
+    REVID = "revid"
+    SLANT3D = "slant3d"
+    UNREAL_SPEECH = "unreal_speech"
+    # --8<-- [end:ProviderName]

autogpt_platform/backend/backend/integrations/webhooks/__init__.py

@@ -1,15 +1,18 @@
 from typing import TYPE_CHECKING
 
 from .github import GithubWebhooksManager
+from .slant3d import Slant3DWebhooksManager
 
 if TYPE_CHECKING:
+    from ..providers import ProviderName
     from .base import BaseWebhooksManager
 
 # --8<-- [start:WEBHOOK_MANAGERS_BY_NAME]
-WEBHOOK_MANAGERS_BY_NAME: dict[str, type["BaseWebhooksManager"]] = {
+WEBHOOK_MANAGERS_BY_NAME: dict["ProviderName", type["BaseWebhooksManager"]] = {
     handler.PROVIDER_NAME: handler
     for handler in [
         GithubWebhooksManager,
+        Slant3DWebhooksManager,
     ]
 }
 # --8<-- [end:WEBHOOK_MANAGERS_BY_NAME]

autogpt_platform/backend/backend/integrations/webhooks/base.py

@@ -9,6 +9,7 @@ from strenum import StrEnum
 
 from backend.data import integrations
 from backend.data.model import Credentials
+from backend.integrations.providers import ProviderName
 from backend.util.exceptions import MissingConfigError
 from backend.util.settings import Config
 
@@ -20,7 +21,7 @@ WT = TypeVar("WT", bound=StrEnum)
 
 class BaseWebhooksManager(ABC, Generic[WT]):
     # --8<-- [start:BaseWebhooksManager1]
-    PROVIDER_NAME: ClassVar[str]
+    PROVIDER_NAME: ClassVar[ProviderName]
     # --8<-- [end:BaseWebhooksManager1]
 
     WebhookType: WT
@@ -81,7 +82,9 @@ class BaseWebhooksManager(ABC, Generic[WT]):
     # --8<-- [end:BaseWebhooksManager3]
 
     # --8<-- [start:BaseWebhooksManager5]
-    async def trigger_ping(self, webhook: integrations.Webhook) -> None:
+    async def trigger_ping(
+        self, webhook: integrations.Webhook, credentials: Credentials | None
+    ) -> None:
         """
         Triggers a ping to the given webhook.
 
@@ -141,7 +144,7 @@ class BaseWebhooksManager(ABC, Generic[WT]):
         secret = secrets.token_hex(32)
         provider_name = self.PROVIDER_NAME
         ingress_url = (
-            f"{app_config.platform_base_url}/api/integrations/{provider_name}"
+            f"{app_config.platform_base_url}/api/integrations/{provider_name.value}"
             f"/webhooks/{id}/ingress"
         )
         provider_webhook_id, config = await self._register_webhook(

autogpt_platform/backend/backend/integrations/webhooks/github.py

@@ -8,6 +8,7 @@ from strenum import StrEnum
 
 from backend.data import integrations
 from backend.data.model import Credentials
+from backend.integrations.providers import ProviderName
 
 from .base import BaseWebhooksManager
 
@@ -20,7 +21,7 @@ class GithubWebhookType(StrEnum):
 
 
 class GithubWebhooksManager(BaseWebhooksManager):
-    PROVIDER_NAME = "github"
+    PROVIDER_NAME = ProviderName.GITHUB
 
     WebhookType = GithubWebhookType
 
@@ -58,10 +59,15 @@ class GithubWebhooksManager(BaseWebhooksManager):
 
         return payload, event_type
 
-    async def trigger_ping(self, webhook: integrations.Webhook) -> None:
+    async def trigger_ping(
+        self, webhook: integrations.Webhook, credentials: Credentials | None
+    ) -> None:
+        if not credentials:
+            raise ValueError("Credentials are required but were not passed")
+
         headers = {
             **self.GITHUB_API_DEFAULT_HEADERS,
-            "Authorization": f"Bearer {webhook.config.get('access_token')}",
+            "Authorization": credentials.bearer(),
         }
 
         repo, github_hook_id = webhook.resource, webhook.provider_webhook_id

autogpt_platform/backend/backend/integrations/webhooks/graph_lifecycle_hooks.py

@@ -95,11 +95,18 @@ async def on_node_activate(
     if not block.webhook_config:
         return node
 
+    provider = block.webhook_config.provider
+    if provider not in WEBHOOK_MANAGERS_BY_NAME:
+        raise ValueError(
+            f"Block #{block.id} has webhook_config for provider {provider} "
+            "which does not support webhooks"
+        )
+
     logger.debug(
         f"Activating webhook node #{node.id} with config {block.webhook_config}"
     )
 
-    webhooks_manager = WEBHOOK_MANAGERS_BY_NAME[block.webhook_config.provider]()
+    webhooks_manager = WEBHOOK_MANAGERS_BY_NAME[provider]()
 
     try:
         resource = block.webhook_config.resource_format.format(**node.input_default)
@@ -167,7 +174,14 @@ async def on_node_deactivate(
     if not block.webhook_config:
         return node
 
-    webhooks_manager = WEBHOOK_MANAGERS_BY_NAME[block.webhook_config.provider]()
+    provider = block.webhook_config.provider
+    if provider not in WEBHOOK_MANAGERS_BY_NAME:
+        raise ValueError(
+            f"Block #{block.id} has webhook_config for provider {provider} "
+            "which does not support webhooks"
+        )
+
+    webhooks_manager = WEBHOOK_MANAGERS_BY_NAME[provider]()
 
     if node.webhook_id:
         logger.debug(f"Node #{node.id} has webhook_id {node.webhook_id}")
@@ -189,7 +203,7 @@ async def on_node_deactivate(
             logger.warning(
                 f"Cannot deregister webhook #{webhook.id}: credentials "
                 f"#{webhook.credentials_id} not available "
-                f"({webhook.provider} webhook ID: {webhook.provider_webhook_id})"
+                f"({webhook.provider.value} webhook ID: {webhook.provider_webhook_id})"
             )
         return updated_node
 

autogpt_platform/backend/backend/integrations/webhooks/slant3d.py

@@ -0,0 +1,99 @@
+import logging
+
+import requests
+from fastapi import Request
+
+from backend.data import integrations
+from backend.data.model import APIKeyCredentials, Credentials
+from backend.integrations.providers import ProviderName
+from backend.integrations.webhooks.base import BaseWebhooksManager
+
+logger = logging.getLogger(__name__)
+
+
+class Slant3DWebhooksManager(BaseWebhooksManager):
+    """Manager for Slant3D webhooks"""
+
+    PROVIDER_NAME = ProviderName.SLANT3D
+    BASE_URL = "https://www.slant3dapi.com/api"
+
+    async def _register_webhook(
+        self,
+        credentials: Credentials,
+        webhook_type: str,
+        resource: str,
+        events: list[str],
+        ingress_url: str,
+        secret: str,
+    ) -> tuple[str, dict]:
+        """Register a new webhook with Slant3D"""
+
+        if not isinstance(credentials, APIKeyCredentials):
+            raise ValueError("API key is required to register a webhook")
+
+        headers = {
+            "api-key": credentials.api_key.get_secret_value(),
+            "Content-Type": "application/json",
+        }
+
+        # Slant3D's API doesn't use events list, just register for all order updates
+        payload = {"endPoint": ingress_url}
+
+        response = requests.post(
+            f"{self.BASE_URL}/customer/webhookSubscribe", headers=headers, json=payload
+        )
+
+        if not response.ok:
+            error = response.json().get("error", "Unknown error")
+            raise RuntimeError(f"Failed to register webhook: {error}")
+
+        webhook_config = {
+            "endpoint": ingress_url,
+            "provider": self.PROVIDER_NAME,
+            "events": ["order.shipped"],  # Currently the only supported event
+            "type": webhook_type,
+        }
+
+        return "", webhook_config
+
+    @classmethod
+    async def validate_payload(
+        cls, webhook: integrations.Webhook, request: Request
+    ) -> tuple[dict, str]:
+        """Validate incoming webhook payload from Slant3D"""
+
+        payload = await request.json()
+
+        # Validate required fields from Slant3D API spec
+        required_fields = ["orderId", "status", "trackingNumber", "carrierCode"]
+        missing_fields = [field for field in required_fields if field not in payload]
+
+        if missing_fields:
+            raise ValueError(f"Missing required fields: {', '.join(missing_fields)}")
+
+        # Normalize payload structure
+        normalized_payload = {
+            "orderId": payload["orderId"],
+            "status": payload["status"],
+            "trackingNumber": payload["trackingNumber"],
+            "carrierCode": payload["carrierCode"],
+        }
+
+        # Currently Slant3D only sends shipping notifications
+        # Convert status to lowercase for event format compatibility
+        event_type = f"order.{payload['status'].lower()}"
+
+        return normalized_payload, event_type
+
+    async def _deregister_webhook(
+        self, webhook: integrations.Webhook, credentials: Credentials
+    ) -> None:
+        """
+        Note: Slant3D API currently doesn't provide a deregistration endpoint.
+        This would need to be handled through support.
+        """
+        # Log warning since we can't properly deregister
+        logger.warning(
+            f"Warning: Manual deregistration required for webhook {webhook.id}"
+        )
+        pass

autogpt_platform/backend/backend/server/integrations/router.py

@@ -1,5 +1,5 @@
 import logging
-from typing import Annotated, Literal
+from typing import TYPE_CHECKING, Annotated, Literal
 
 from fastapi import APIRouter, Body, Depends, HTTPException, Path, Query, Request
 from pydantic import BaseModel, Field, SecretStr
@@ -9,8 +9,8 @@ from backend.data.integrations import (
     WebhookEvent,
     get_all_webhooks,
     get_webhook,
-    listen_for_webhook_event,
     publish_webhook_event,
+    wait_for_webhook_event,
 )
 from backend.data.model import (
     APIKeyCredentials,
@@ -20,12 +20,16 @@ from backend.data.model import (
 )
 from backend.executor.manager import ExecutionManager
 from backend.integrations.creds_manager import IntegrationCredentialsManager
-from backend.integrations.oauth import HANDLERS_BY_NAME, BaseOAuthHandler
+from backend.integrations.oauth import HANDLERS_BY_NAME
+from backend.integrations.providers import ProviderName
 from backend.integrations.webhooks import WEBHOOK_MANAGERS_BY_NAME
 from backend.util.exceptions import NeedConfirmation
 from backend.util.service import get_service_client
 from backend.util.settings import Settings
 
+if TYPE_CHECKING:
+    from backend.integrations.oauth import BaseOAuthHandler
+
 from ..utils import get_user_id
 
 logger = logging.getLogger(__name__)
@@ -42,7 +46,9 @@ class LoginResponse(BaseModel):
 
 @router.get("/{provider}/login")
 def login(
-    provider: Annotated[str, Path(title="The provider to initiate an OAuth flow for")],
+    provider: Annotated[
+        ProviderName, Path(title="The provider to initiate an OAuth flow for")
+    ],
     user_id: Annotated[str, Depends(get_user_id)],
     request: Request,
     scopes: Annotated[
@@ -74,7 +80,9 @@ class CredentialsMetaResponse(BaseModel):
 
 @router.post("/{provider}/callback")
 def callback(
-    provider: Annotated[str, Path(title="The target provider for this OAuth exchange")],
+    provider: Annotated[
+        ProviderName, Path(title="The target provider for this OAuth exchange")
+    ],
     code: Annotated[str, Body(title="Authorization code acquired by user login")],
     state_token: Annotated[str, Body(title="Anti-CSRF nonce")],
     user_id: Annotated[str, Depends(get_user_id)],
@@ -103,11 +111,12 @@ def callback(
         if not set(scopes).issubset(set(credentials.scopes)):
             # For now, we'll just log the warning and continue
             logger.warning(
-                f"Granted scopes {credentials.scopes} for {provider}do not include all requested scopes {scopes}"
+                f"Granted scopes {credentials.scopes} for provider {provider.value} "
+                f"do not include all requested scopes {scopes}"
             )
 
     except Exception as e:
-        logger.error(f"Code->Token exchange failed for provider {provider}: {e}")
+        logger.error(f"Code->Token exchange failed for provider {provider.value}: {e}")
         raise HTTPException(
             status_code=400, detail=f"Failed to exchange code for tokens: {str(e)}"
         )
@@ -116,7 +125,8 @@ def callback(
     creds_manager.create(user_id, credentials)
 
     logger.debug(
-        f"Successfully processed OAuth callback for user {user_id} and provider {provider}"
+        f"Successfully processed OAuth callback for user {user_id} "
+        f"and provider {provider.value}"
     )
     return CredentialsMetaResponse(
         id=credentials.id,
@@ -148,7 +158,9 @@ def list_credentials(
 
 @router.get("/{provider}/credentials")
 def list_credentials_by_provider(
-    provider: Annotated[str, Path(title="The provider to list credentials for")],
+    provider: Annotated[
+        ProviderName, Path(title="The provider to list credentials for")
+    ],
     user_id: Annotated[str, Depends(get_user_id)],
 ) -> list[CredentialsMetaResponse]:
     credentials = creds_manager.store.get_creds_by_provider(user_id, provider)
@@ -167,7 +179,9 @@ def list_credentials_by_provider(
 
 @router.get("/{provider}/credentials/{cred_id}")
 def get_credential(
-    provider: Annotated[str, Path(title="The provider to retrieve credentials for")],
+    provider: Annotated[
+        ProviderName, Path(title="The provider to retrieve credentials for")
+    ],
     cred_id: Annotated[str, Path(title="The ID of the credentials to retrieve")],
     user_id: Annotated[str, Depends(get_user_id)],
 ) -> Credentials:
@@ -184,7 +198,9 @@ def get_credential(
 @router.post("/{provider}/credentials", status_code=201)
 def create_api_key_credentials(
     user_id: Annotated[str, Depends(get_user_id)],
-    provider: Annotated[str, Path(title="The provider to create credentials for")],
+    provider: Annotated[
+        ProviderName, Path(title="The provider to create credentials for")
+    ],
     api_key: Annotated[str, Body(title="The API key to store")],
     title: Annotated[str, Body(title="Optional title for the credentials")],
     expires_at: Annotated[
@@ -225,7 +241,9 @@ class CredentialsDeletionNeedsConfirmationResponse(BaseModel):
 @router.delete("/{provider}/credentials/{cred_id}")
 async def delete_credentials(
     request: Request,
-    provider: Annotated[str, Path(title="The provider to delete credentials for")],
+    provider: Annotated[
+        ProviderName, Path(title="The provider to delete credentials for")
+    ],
     cred_id: Annotated[str, Path(title="The ID of the credentials to delete")],
     user_id: Annotated[str, Depends(get_user_id)],
     force: Annotated[
@@ -264,15 +282,20 @@ async def delete_credentials(
 @router.post("/{provider}/webhooks/{webhook_id}/ingress")
 async def webhook_ingress_generic(
     request: Request,
-    provider: Annotated[str, Path(title="Provider where the webhook was registered")],
+    provider: Annotated[
+        ProviderName, Path(title="Provider where the webhook was registered")
+    ],
     webhook_id: Annotated[str, Path(title="Our ID for the webhook")],
 ):
-    logger.debug(f"Received {provider} webhook ingress for ID {webhook_id}")
+    logger.debug(f"Received {provider.value} webhook ingress for ID {webhook_id}")
     webhook_manager = WEBHOOK_MANAGERS_BY_NAME[provider]()
     webhook = await get_webhook(webhook_id)
     logger.debug(f"Webhook #{webhook_id}: {webhook}")
     payload, event_type = await webhook_manager.validate_payload(webhook, request)
-    logger.debug(f"Validated {provider} {event_type} event with payload {payload}")
+    logger.debug(
+        f"Validated {provider.value} {webhook.webhook_type} {event_type} event "
+        f"with payload {payload}"
+    )
 
     webhook_event = WebhookEvent(
         provider=provider,
@@ -300,18 +323,28 @@ async def webhook_ingress_generic(
         )
 
 
-@router.post("/{provider}/webhooks/{webhook_id}/ping")
+@router.post("/webhooks/{webhook_id}/ping")
 async def webhook_ping(
-    provider: Annotated[str, Path(title="Provider where the webhook was registered")],
     webhook_id: Annotated[str, Path(title="Our ID for the webhook")],
     user_id: Annotated[str, Depends(get_user_id)],  # require auth
 ):
-    webhook_manager = WEBHOOK_MANAGERS_BY_NAME[provider]()
     webhook = await get_webhook(webhook_id)
+    webhook_manager = WEBHOOK_MANAGERS_BY_NAME[webhook.provider]()
 
-    await webhook_manager.trigger_ping(webhook)
-    if not await listen_for_webhook_event(webhook_id, event_type="ping"):
-        raise HTTPException(status_code=500, detail="Webhook ping event not received")
+    credentials = (
+        creds_manager.get(user_id, webhook.credentials_id)
+        if webhook.credentials_id
+        else None
+    )
+    try:
+        await webhook_manager.trigger_ping(webhook, credentials)
+    except NotImplementedError:
+        return False
+
+    if not await wait_for_webhook_event(webhook_id, event_type="ping", timeout=10):
+        raise HTTPException(status_code=504, detail="Webhook ping timed out")
+
+    return True
 
 
 # --------------------------- UTILITIES ---------------------------- #
@@ -331,6 +364,14 @@ async def remove_all_webhooks_for_credentials(
         NeedConfirmation: If any of the webhooks are still in use and `force` is `False`
     """
     webhooks = await get_all_webhooks(credentials.id)
+    if credentials.provider not in WEBHOOK_MANAGERS_BY_NAME:
+        if webhooks:
+            logger.error(
+                f"Credentials #{credentials.id} for provider {credentials.provider} "
+                f"are attached to {len(webhooks)} webhooks, "
+                f"but there is no available WebhooksHandler for {credentials.provider}"
+            )
+        return
     if any(w.attached_nodes for w in webhooks) and not force:
         raise NeedConfirmation(
             "Some webhooks linked to these credentials are still in use by an agent"
@@ -349,18 +390,23 @@ async def remove_all_webhooks_for_credentials(
             logger.warning(f"Webhook #{webhook.id} failed to prune")
 
 
-def _get_provider_oauth_handler(req: Request, provider_name: str) -> BaseOAuthHandler:
+def _get_provider_oauth_handler(
+    req: Request, provider_name: ProviderName
+) -> "BaseOAuthHandler":
     if provider_name not in HANDLERS_BY_NAME:
         raise HTTPException(
-            status_code=404, detail=f"Unknown provider '{provider_name}'"
+            status_code=404,
+            detail=f"Provider '{provider_name.value}' does not support OAuth",
         )
 
-    client_id = getattr(settings.secrets, f"{provider_name}_client_id")
-    client_secret = getattr(settings.secrets, f"{provider_name}_client_secret")
+    client_id = getattr(settings.secrets, f"{provider_name.value}_client_id")
+    client_secret = getattr(settings.secrets, f"{provider_name.value}_client_secret")
     if not (client_id and client_secret):
         raise HTTPException(
             status_code=501,
-            detail=f"Integration with provider '{provider_name}' is not configured",
+            detail=(
+                f"Integration with provider '{provider_name.value}' is not configured"
+            ),
         )
 
     handler_class = HANDLERS_BY_NAME[provider_name]

autogpt_platform/backend/backend/server/rest_api.py

@@ -16,6 +16,7 @@ import backend.data.db
 import backend.data.graph
 import backend.data.user
 import backend.server.routers.v1
+import backend.server.v2.store.routes
 import backend.util.service
 import backend.util.settings
 
@@ -25,15 +26,26 @@ logger = logging.getLogger(__name__)
 logging.getLogger("autogpt_libs").setLevel(logging.INFO)
 
 
+@contextlib.contextmanager
+def launch_darkly_context():
+    if settings.config.app_env != backend.util.settings.AppEnvironment.LOCAL:
+        initialize_launchdarkly()
+        try:
+            yield
+        finally:
+            shutdown_launchdarkly()
+    else:
+        yield
+
+
 @contextlib.asynccontextmanager
 async def lifespan_context(app: fastapi.FastAPI):
     await backend.data.db.connect()
     await backend.data.block.initialize_blocks()
     await backend.data.user.migrate_and_encrypt_user_integrations()
     await backend.data.graph.fix_llm_provider_credentials()
-    initialize_launchdarkly()
-    yield
-    shutdown_launchdarkly()
+    with launch_darkly_context():
+        yield
     await backend.data.db.disconnect()
 
 
@@ -73,7 +85,10 @@ def handle_internal_http_error(status_code: int = 500, log_error: bool = True):
 
 app.add_exception_handler(ValueError, handle_internal_http_error(400))
 app.add_exception_handler(Exception, handle_internal_http_error(500))
-app.include_router(backend.server.routers.v1.v1_router, tags=["v1"])
+app.include_router(backend.server.routers.v1.v1_router, tags=["v1"], prefix="/api")
+app.include_router(
+    backend.server.v2.store.routes.router, tags=["v2"], prefix="/api/store"
+)
 
 
 @app.get(path="/health", tags=["health"], dependencies=[])
@@ -106,17 +121,17 @@ class AgentServer(backend.util.service.AppProcess):
     async def test_create_graph(
         create_graph: backend.server.routers.v1.CreateGraph,
         user_id: str,
-        is_template=False,
     ):
         return await backend.server.routers.v1.create_new_graph(create_graph, user_id)
 
     @staticmethod
-    async def test_get_graph_run_status(
-        graph_id: str, graph_exec_id: str, user_id: str
-    ):
-        return await backend.server.routers.v1.get_graph_run_status(
-            graph_id, graph_exec_id, user_id
+    async def test_get_graph_run_status(graph_exec_id: str, user_id: str):
+        execution = await backend.data.graph.get_execution(
+            user_id=user_id, execution_id=graph_exec_id
         )
+        if not execution:
+            raise ValueError(f"Execution {graph_exec_id} not found")
+        return execution.status
 
     @staticmethod
     async def test_get_graph_run_node_execution_results(

autogpt_platform/backend/backend/server/routers/v1.py

@@ -69,8 +69,7 @@ integration_creds_manager = IntegrationCredentialsManager()
 _user_credit_model = get_user_credit_model()
 
 # Define the API routes
-v1_router = APIRouter(prefix="/api")
-
+v1_router = APIRouter()
 
 v1_router.include_router(
     backend.server.integrations.router.router,
@@ -132,7 +131,7 @@ def execute_graph_block(block_id: str, data: BlockInput) -> CompletedBlockOutput
 
 @v1_router.get(path="/credits", dependencies=[Depends(auth_middleware)])
 async def get_user_credits(
-    user_id: Annotated[str, Depends(get_user_id)]
+    user_id: Annotated[str, Depends(get_user_id)],
 ) -> dict[str, int]:
     # Credits can go negative, so ensure it's at least 0 for user to see.
     return {"credits": max(await _user_credit_model.get_or_refill_credit(user_id), 0)}
@@ -149,12 +148,9 @@ class DeleteGraphResponse(TypedDict):
 
 @v1_router.get(path="/graphs", tags=["graphs"], dependencies=[Depends(auth_middleware)])
 async def get_graphs(
-    user_id: Annotated[str, Depends(get_user_id)],
-    with_runs: bool = False,
+    user_id: Annotated[str, Depends(get_user_id)]
 ) -> Sequence[graph_db.Graph]:
-    return await graph_db.get_graphs(
-        include_executions=with_runs, filter_by="active", user_id=user_id
-    )
+    return await graph_db.get_graphs(filter_by="active", user_id=user_id)
 
 
 @v1_router.get(
@@ -252,6 +248,13 @@ async def do_create_graph(
 async def delete_graph(
     graph_id: str, user_id: Annotated[str, Depends(get_user_id)]
 ) -> DeleteGraphResponse:
+    if active_version := await graph_db.get_graph(graph_id, user_id=user_id):
+
+        def get_credentials(credentials_id: str) -> "Credentials | None":
+            return integration_creds_manager.get(user_id, credentials_id)
+
+        await on_graph_deactivate(active_version, get_credentials)
+
     return {"version_counts": await graph_db.delete_graph(graph_id, user_id=user_id)}
 
 
@@ -386,7 +389,7 @@ def execute_graph(
 async def stop_graph_run(
     graph_exec_id: str, user_id: Annotated[str, Depends(get_user_id)]
 ) -> Sequence[execution_db.ExecutionResult]:
-    if not await execution_db.get_graph_execution(graph_exec_id, user_id):
+    if not await graph_db.get_execution(user_id=user_id, execution_id=graph_exec_id):
         raise HTTPException(404, detail=f"Agent execution #{graph_exec_id} not found")
 
     await asyncio.to_thread(
@@ -398,23 +401,14 @@ async def stop_graph_run(
 
 
 @v1_router.get(
-    path="/graphs/{graph_id}/executions",
+    path="/executions",
     tags=["graphs"],
     dependencies=[Depends(auth_middleware)],
 )
-async def list_graph_runs(
-    graph_id: str,
+async def get_executions(
     user_id: Annotated[str, Depends(get_user_id)],
-    graph_version: int | None = None,
-) -> Sequence[str]:
-    graph = await graph_db.get_graph(graph_id, graph_version, user_id=user_id)
-    if not graph:
-        rev = "" if graph_version is None else f" v{graph_version}"
-        raise HTTPException(
-            status_code=404, detail=f"Agent #{graph_id}{rev} not found."
-        )
-
-    return await execution_db.list_executions(graph_id, graph_version)
+) -> list[graph_db.GraphExecution]:
+    return await graph_db.get_executions(user_id=user_id)
 
 
 @v1_router.get(
@@ -434,25 +428,6 @@ async def get_graph_run_node_execution_results(
     return await execution_db.get_execution_results(graph_exec_id)
 
 
-# NOTE: This is used for testing
-async def get_graph_run_status(
-    graph_id: str,
-    graph_exec_id: str,
-    user_id: Annotated[str, Depends(get_user_id)],
-) -> execution_db.ExecutionStatus:
-    graph = await graph_db.get_graph(graph_id, user_id=user_id)
-    if not graph:
-        raise HTTPException(status_code=404, detail=f"Graph #{graph_id} not found.")
-
-    execution = await execution_db.get_graph_execution(graph_exec_id, user_id)
-    if not execution:
-        raise HTTPException(
-            status_code=404, detail=f"Execution #{graph_exec_id} not found."
-        )
-
-    return execution.executionStatus
-
-
 ########################################################
 ##################### Templates ########################
 ########################################################

autogpt_platform/backend/backend/server/v2/store/db.py

@@ -0,0 +1,709 @@
+import logging
+from datetime import datetime
+import random
+import prisma.enums
+import prisma.errors
+import prisma.models
+import prisma.types
+
+import backend.server.v2.store.exceptions
+import backend.server.v2.store.model
+
+logger = logging.getLogger(__name__)
+
+
+async def get_store_agents(
+    featured: bool = False,
+    creator: str | None = None,
+    sorted_by: str | None = None,
+    search_query: str | None = None,
+    category: str | None = None,
+    page: int = 1,
+    page_size: int = 20,
+) -> backend.server.v2.store.model.StoreAgentsResponse:
+    logger.debug(
+        f"Getting store agents. featured={featured}, creator={creator}, sorted_by={sorted_by}, search={search_query}, category={category}, page={page}"
+    )
+
+    where_clause = {}
+    if featured:
+        where_clause["featured"] = featured
+    if creator:
+        where_clause["creator_username"] = creator
+    if category:
+        where_clause["categories"] = {"has": category}
+    if search_query:
+        where_clause["OR"] = [
+            {"agent_name": {"contains": search_query, "mode": "insensitive"}},
+            {"description": {"contains": search_query, "mode": "insensitive"}},
+        ]
+
+    order_by = []
+    if sorted_by == "rating":
+        order_by.append({"rating": "desc"})
+    elif sorted_by == "runs":
+        order_by.append({"runs": "desc"})
+    elif sorted_by == "name":
+        order_by.append({"agent_name": "asc"})
+
+    try:
+        agents = await prisma.models.StoreAgent.prisma().find_many(
+            where=prisma.types.StoreAgentWhereInput(**where_clause),
+            order=order_by,
+            skip=(page - 1) * page_size,
+            take=page_size,
+        )
+
+        total = await prisma.models.StoreAgent.prisma().count(
+            where=prisma.types.StoreAgentWhereInput(**where_clause)
+        )
+        total_pages = (total + page_size - 1) // page_size
+
+        store_agents = [
+            backend.server.v2.store.model.StoreAgent(
+                slug=agent.slug,
+                agent_name=agent.agent_name,
+                agent_image=agent.agent_image[0] if agent.agent_image else "",
+                creator=agent.creator_username,
+                creator_avatar=agent.creator_avatar,
+                sub_heading=agent.sub_heading,
+                description=agent.description,
+                runs=agent.runs,
+                rating=agent.rating,
+            )
+            for agent in agents
+        ]
+
+        logger.debug(f"Found {len(store_agents)} agents")
+        return backend.server.v2.store.model.StoreAgentsResponse(
+            agents=store_agents,
+            pagination=backend.server.v2.store.model.Pagination(
+                current_page=page,
+                total_items=total,
+                total_pages=total_pages,
+                page_size=page_size,
+            ),
+        )
+    except Exception as e:
+        logger.error(f"Error getting store agents: {str(e)}")
+        raise backend.server.v2.store.exceptions.DatabaseError(
+            "Failed to fetch store agents"
+        ) from e
+
+
+async def get_store_agent_details(
+    username: str, agent_name: str
+) -> backend.server.v2.store.model.StoreAgentDetails:
+    logger.debug(f"Getting store agent details for {username}/{agent_name}")
+
+    try:
+        agent = await prisma.models.StoreAgent.prisma().find_first(
+            where={"creator_username": username, "slug": agent_name}
+        )
+
+        if not agent:
+            logger.warning(f"Agent not found: {username}/{agent_name}")
+            raise backend.server.v2.store.exceptions.AgentNotFoundError(
+                f"Agent {username}/{agent_name} not found"
+            )
+
+        logger.debug(f"Found agent details for {username}/{agent_name}")
+        return backend.server.v2.store.model.StoreAgentDetails(
+            store_listing_version_id=agent.storeListingVersionId,
+            slug=agent.slug,
+            agent_name=agent.agent_name,
+            agent_video=agent.agent_video or "",
+            agent_image=agent.agent_image,
+            creator=agent.creator_username,
+            creator_avatar=agent.creator_avatar,
+            sub_heading=agent.sub_heading,
+            description=agent.description,
+            categories=agent.categories,
+            runs=agent.runs,
+            rating=agent.rating,
+            versions=agent.versions,
+            last_updated=agent.updated_at,
+        )
+    except backend.server.v2.store.exceptions.AgentNotFoundError:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting store agent details: {str(e)}")
+        raise backend.server.v2.store.exceptions.DatabaseError(
+            "Failed to fetch agent details"
+        ) from e
+
+
+async def get_store_creators(
+    featured: bool = False,
+    search_query: str | None = None,
+    sorted_by: str | None = None,
+    page: int = 1,
+    page_size: int = 20,
+) -> backend.server.v2.store.model.CreatorsResponse:
+    logger.debug(
+        f"Getting store creators. featured={featured}, search={search_query}, sorted_by={sorted_by}, page={page}"
+    )
+
+    # Build where clause
+    where = {}
+
+    # Add search filter if provided
+    if search_query:
+        where["OR"] = [
+            {"username": {"contains": search_query, "mode": "insensitive"}},
+            {"name": {"contains": search_query, "mode": "insensitive"}},
+            {"description": {"contains": search_query, "mode": "insensitive"}},
+        ]
+
+    try:
+        # Get total count for pagination
+        total = await prisma.models.Creator.prisma().count(
+            where=prisma.types.CreatorWhereInput(**where)
+        )
+        total_pages = (total + page_size - 1) // page_size
+
+        # Add pagination
+        skip = (page - 1) * page_size
+        take = page_size
+
+        # Add sorting
+        order = []
+        if sorted_by == "agent_rating":
+            order.append({"agent_rating": "desc"})
+        elif sorted_by == "agent_runs":
+            order.append({"agent_runs": "desc"})
+        elif sorted_by == "num_agents":
+            order.append({"num_agents": "desc"})
+        else:
+            order.append({"username": "asc"})
+
+        # Execute query
+        creators = await prisma.models.Creator.prisma().find_many(
+            where=prisma.types.CreatorWhereInput(**where),
+            skip=skip,
+            take=take,
+            order=order,
+        )
+
+        # Convert to response model
+        creator_models = [
+            backend.server.v2.store.model.Creator(
+                username=creator.username,
+                name=creator.name,
+                description=creator.description,
+                avatar_url=creator.avatar_url,
+                num_agents=creator.num_agents,
+                agent_rating=creator.agent_rating,
+                agent_runs=creator.agent_runs,
+            )
+            for creator in creators
+        ]
+
+        logger.debug(f"Found {len(creator_models)} creators")
+        return backend.server.v2.store.model.CreatorsResponse(
+            creators=creator_models,
+            pagination=backend.server.v2.store.model.Pagination(
+                current_page=page,
+                total_items=total,
+                total_pages=total_pages,
+                page_size=page_size,
+            ),
+        )
+    except Exception as e:
+        logger.error(f"Error getting store creators: {str(e)}")
+        raise backend.server.v2.store.exceptions.DatabaseError(
+            "Failed to fetch store creators"
+        ) from e
+
+
+async def get_store_creator_details(
+    username: str,
+) -> backend.server.v2.store.model.CreatorDetails:
+    logger.debug(f"Getting store creator details for {username}")
+
+    try:
+        # Query creator details from database
+        creator = await prisma.models.Creator.prisma().find_unique(
+            where={"username": username}
+        )
+
+        if not creator:
+            logger.warning(f"Creator not found: {username}")
+            raise backend.server.v2.store.exceptions.CreatorNotFoundError(
+                f"Creator {username} not found"
+            )
+
+        logger.debug(f"Found creator details for {username}")
+        return backend.server.v2.store.model.CreatorDetails(
+            name=creator.name,
+            username=creator.username,
+            description=creator.description,
+            links=creator.links,
+            avatar_url=creator.avatar_url,
+            agent_rating=creator.agent_rating,
+            agent_runs=creator.agent_runs,
+            top_categories=creator.top_categories,
+        )
+    except backend.server.v2.store.exceptions.CreatorNotFoundError:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting store creator details: {str(e)}")
+        raise backend.server.v2.store.exceptions.DatabaseError(
+            "Failed to fetch creator details"
+        ) from e
+
+
+async def get_store_submissions(
+    user_id: str, page: int = 1, page_size: int = 20
+) -> backend.server.v2.store.model.StoreSubmissionsResponse:
+    logger.debug(f"Getting store submissions for user {user_id}, page={page}")
+
+    try:
+        # Calculate pagination values
+        skip = (page - 1) * page_size
+
+        where = prisma.types.StoreSubmissionWhereInput(user_id=user_id)
+        # Query submissions from database
+        submissions = await prisma.models.StoreSubmission.prisma().find_many(
+            where=where, skip=skip, take=page_size, order=[{"date_submitted": "desc"}]
+        )
+
+        # Get total count for pagination
+        total = await prisma.models.StoreSubmission.prisma().count(where=where)
+
+        total_pages = (total + page_size - 1) // page_size
+
+        # Convert to response models
+        submission_models = [
+            backend.server.v2.store.model.StoreSubmission(
+                agent_id=sub.agent_id,
+                agent_version=sub.agent_version,
+                name=sub.name,
+                sub_heading=sub.sub_heading,
+                slug=sub.slug,
+                description=sub.description,
+                image_urls=sub.image_urls or [],
+                date_submitted=sub.date_submitted or datetime.now(),
+                status=sub.status,
+                runs=sub.runs or 0,
+                rating=sub.rating or 0.0,
+            )
+            for sub in submissions
+        ]
+
+        logger.debug(f"Found {len(submission_models)} submissions")
+        return backend.server.v2.store.model.StoreSubmissionsResponse(
+            submissions=submission_models,
+            pagination=backend.server.v2.store.model.Pagination(
+                current_page=page,
+                total_items=total,
+                total_pages=total_pages,
+                page_size=page_size,
+            ),
+        )
+
+    except Exception as e:
+        logger.error(f"Error fetching store submissions: {str(e)}")
+        # Return empty response rather than exposing internal errors
+        return backend.server.v2.store.model.StoreSubmissionsResponse(
+            submissions=[],
+            pagination=backend.server.v2.store.model.Pagination(
+                current_page=page,
+                total_items=0,
+                total_pages=0,
+                page_size=page_size,
+            ),
+        )
+
+
+async def delete_store_submission(
+    user_id: str,
+    submission_id: str,
+) -> bool:
+    """
+    Delete a store listing submission.
+
+    Args:
+        user_id: ID of the authenticated user
+        submission_id: ID of the submission to be deleted
+
+    Returns:
+        bool: True if the submission was successfully deleted, False otherwise
+    """
+    logger.debug(f"Deleting store submission {submission_id} for user {user_id}")
+
+    try:
+        # Verify the submission belongs to this user
+        submission = await prisma.models.StoreListing.prisma().find_first(
+            where={"agentId": submission_id, "owningUserId": user_id}
+        )
+
+        if not submission:
+            logger.warning(f"Submission not found for user {user_id}: {submission_id}")
+            raise backend.server.v2.store.exceptions.SubmissionNotFoundError(
+                f"Submission not found for this user. User ID: {user_id}, Submission ID: {submission_id}"
+            )
+
+        # Delete the submission
+        await prisma.models.StoreListing.prisma().delete(
+            where=prisma.types.StoreListingWhereUniqueInput(id=submission.id)
+        )
+
+        logger.debug(
+            f"Successfully deleted submission {submission_id} for user {user_id}"
+        )
+        return True
+
+    except Exception as e:
+        logger.error(f"Error deleting store submission: {str(e)}")
+        return False
+
+
+async def create_store_submission(
+    user_id: str,
+    agent_id: str,
+    agent_version: int,
+    slug: str,
+    name: str,
+    video_url: str | None = None,
+    image_urls: list[str] = [],
+    description: str = "",
+    sub_heading: str = "",
+    categories: list[str] = [],
+) -> backend.server.v2.store.model.StoreSubmission:
+    """
+    Create a new store listing submission.
+
+    Args:
+        user_id: ID of the authenticated user submitting the listing
+        agent_id: ID of the agent being submitted
+        agent_version: Version of the agent being submitted
+        slug: URL slug for the listing
+        name: Name of the agent
+        video_url: Optional URL to video demo
+        image_urls: List of image URLs for the listing
+        description: Description of the agent
+        categories: List of categories for the agent
+
+    Returns:
+        StoreSubmission: The created store submission
+    """
+    logger.debug(
+        f"Creating store submission for user {user_id}, agent {agent_id} v{agent_version}"
+    )
+
+    try:
+        # First verify the agent belongs to this user
+        agent = await prisma.models.AgentGraph.prisma().find_first(
+            where=prisma.types.AgentGraphWhereInput(
+                id=agent_id, version=agent_version, userId=user_id
+            )
+        )
+
+        if not agent:
+            logger.warning(
+                f"Agent not found for user {user_id}: {agent_id} v{agent_version}"
+            )
+            raise backend.server.v2.store.exceptions.AgentNotFoundError(
+                f"Agent not found for this user. User ID: {user_id}, Agent ID: {agent_id}, Version: {agent_version}"
+            )
+
+        listing = await prisma.models.StoreListing.prisma().find_first(
+            where=prisma.types.StoreListingWhereInput(
+                agentId=agent_id, owningUserId=user_id
+            )
+        )
+        if listing is not None:
+            logger.warning(f"Listing already exists for agent {agent_id}")
+            raise backend.server.v2.store.exceptions.ListingExistsError(
+                "Listing already exists for this agent"
+            )
+
+        # Create the store listing
+        listing = await prisma.models.StoreListing.prisma().create(
+            data={
+                "agentId": agent_id,
+                "agentVersion": agent_version,
+                "owningUserId": user_id,
+                "createdAt": datetime.now(),
+                "StoreListingVersions": {
+                    "create": {
+                        "agentId": agent_id,
+                        "agentVersion": agent_version,
+                        "slug": slug,
+                        "name": name,
+                        "videoUrl": video_url,
+                        "imageUrls": image_urls,
+                        "description": description,
+                        "categories": categories,
+                        "subHeading": sub_heading,
+                    }
+                },
+            }
+        )
+
+        logger.debug(f"Created store listing for agent {agent_id}")
+        # Return submission details
+        return backend.server.v2.store.model.StoreSubmission(
+            agent_id=agent_id,
+            agent_version=agent_version,
+            name=name,
+            slug=slug,
+            sub_heading=sub_heading,
+            description=description,
+            image_urls=image_urls,
+            date_submitted=listing.createdAt,
+            status=prisma.enums.SubmissionStatus.PENDING,
+            runs=0,
+            rating=0.0,
+        )
+
+    except (
+        backend.server.v2.store.exceptions.AgentNotFoundError,
+        backend.server.v2.store.exceptions.ListingExistsError,
+    ):
+        raise
+    except prisma.errors.PrismaError as e:
+        logger.error(f"Database error creating store submission: {str(e)}")
+        raise backend.server.v2.store.exceptions.DatabaseError(
+            "Failed to create store submission"
+        ) from e
+
+
+async def create_store_review(
+    user_id: str,
+    store_listing_version_id: str,
+    score: int,
+    comments: str | None = None,
+) -> backend.server.v2.store.model.StoreReview:
+    try:
+        review = await prisma.models.StoreListingReview.prisma().upsert(
+            where={
+                "storeListingVersionId_reviewByUserId": {
+                    "storeListingVersionId": store_listing_version_id,
+                    "reviewByUserId": user_id,
+                }
+            },
+            data={
+                "create": {
+                    "reviewByUserId": user_id,
+                    "storeListingVersionId": store_listing_version_id,
+                    "score": score,
+                    "comments": comments,
+                },
+                "update": {
+                    "score": score,
+                    "comments": comments,
+                },
+            },
+        )
+
+        return backend.server.v2.store.model.StoreReview(
+            score=review.score,
+            comments=review.comments,
+        )
+
+    except prisma.errors.PrismaError as e:
+        logger.error(f"Database error creating store review: {str(e)}")
+        raise backend.server.v2.store.exceptions.DatabaseError(
+            "Failed to create store review"
+        ) from e
+
+
+async def get_user_profile(
+    user_id: str,
+) -> backend.server.v2.store.model.ProfileDetails:
+    logger.debug(f"Getting user profile for {user_id}")
+
+    try:
+        profile = await prisma.models.Profile.prisma().find_first(
+            where={"userId": user_id}  # type: ignore
+        )
+
+        if not profile:
+            logger.warning(f"Profile not found for user {user_id}")
+            await prisma.models.Profile.prisma().create(
+                data=prisma.types.ProfileCreateInput(
+                    userId=user_id,
+                    name="No Profile Data",
+                    username=f"{random.choice(['happy', 'clever', 'swift', 'bright', 'wise'])}-{random.choice(['fox', 'wolf', 'bear', 'eagle', 'owl'])}_{random.randint(1000,9999)}",
+                    description="No Profile Data",
+                    links=[],
+                    avatarUrl="",
+                )
+            )
+            return backend.server.v2.store.model.ProfileDetails(
+                name="No Profile Data",
+                username="No Profile Data",
+                description="No Profile Data",
+                links=[],
+                avatar_url="",
+            )
+
+        return backend.server.v2.store.model.ProfileDetails(
+            name=profile.name,
+            username=profile.username,
+            description=profile.description,
+            links=profile.links,
+            avatar_url=profile.avatarUrl,
+        )
+    except Exception as e:
+        logger.error(f"Error getting user profile: {str(e)}")
+        return backend.server.v2.store.model.ProfileDetails(
+            name="No Profile Data",
+            username="No Profile Data",
+            description="No Profile Data",
+            links=[],
+            avatar_url="",
+        )
+
+
+async def update_or_create_profile(
+    user_id: str, profile: backend.server.v2.store.model.Profile
+) -> backend.server.v2.store.model.CreatorDetails:
+    """
+    Update the store profile for a user. Creates a new profile if one doesn't exist.
+    Only allows updating if the user_id matches the owning user.
+
+    Args:
+        user_id: ID of the authenticated user
+        profile: Updated profile details
+
+    Returns:
+        CreatorDetails: The updated profile
+
+    Raises:
+        HTTPException: If user is not authorized to update this profile
+    """
+    logger.debug(f"Updating profile for user {user_id}")
+
+    try:
+        # Check if profile exists for user
+        existing_profile = await prisma.models.Profile.prisma().find_first(
+            where={"userId": user_id}
+        )
+
+        # If no profile exists, create a new one
+        if not existing_profile:
+            logger.debug(f"Creating new profile for user {user_id}")
+            # Create new profile since one doesn't exist
+            new_profile = await prisma.models.Profile.prisma().create(
+                data={
+                    "userId": user_id,
+                    "name": profile.name,
+                    "username": profile.username,
+                    "description": profile.description,
+                    "links": profile.links,
+                    "avatarUrl": profile.avatar_url,
+                }
+            )
+
+            return backend.server.v2.store.model.CreatorDetails(
+                name=new_profile.name,
+                username=new_profile.username,
+                description=new_profile.description,
+                links=new_profile.links,
+                avatar_url=new_profile.avatarUrl or "",
+                agent_rating=0.0,
+                agent_runs=0,
+                top_categories=[],
+            )
+        else:
+            logger.debug(f"Updating existing profile for user {user_id}")
+            # Update the existing profile
+            updated_profile = await prisma.models.Profile.prisma().update(
+                where={"id": existing_profile.id},
+                data=prisma.types.ProfileUpdateInput(
+                    name=profile.name,
+                    username=profile.username,
+                    description=profile.description,
+                    links=profile.links,
+                    avatarUrl=profile.avatar_url,
+                ),
+            )
+            if updated_profile is None:
+                logger.error(f"Failed to update profile for user {user_id}")
+                raise backend.server.v2.store.exceptions.DatabaseError(
+                    "Failed to update profile"
+                )
+
+            return backend.server.v2.store.model.CreatorDetails(
+                name=updated_profile.name,
+                username=updated_profile.username,
+                description=updated_profile.description,
+                links=updated_profile.links,
+                avatar_url=updated_profile.avatarUrl or "",
+                agent_rating=0.0,
+                agent_runs=0,
+                top_categories=[],
+            )
+
+    except prisma.errors.PrismaError as e:
+        logger.error(f"Database error updating profile: {str(e)}")
+        raise backend.server.v2.store.exceptions.DatabaseError(
+            "Failed to update profile"
+        ) from e
+
+
+async def get_my_agents(
+    user_id: str,
+    page: int = 1,
+    page_size: int = 20,
+) -> backend.server.v2.store.model.MyAgentsResponse:
+    logger.debug(f"Getting my agents for user {user_id}, page={page}")
+
+    try:
+        agents_with_max_version = await prisma.models.AgentGraph.prisma().find_many(
+            where=prisma.types.AgentGraphWhereInput(
+                userId=user_id, StoreListing={"none": {"isDeleted": False}}
+            ),
+            order=[{"version": "desc"}],
+            distinct=["id"],
+            skip=(page - 1) * page_size,
+            take=page_size,
+        )
+
+        # store_listings = await prisma.models.StoreListing.prisma().find_many(
+        #     where=prisma.types.StoreListingWhereInput(
+        #         isDeleted=False,
+        #     ),
+        # )
+
+        total = len(
+            await prisma.models.AgentGraph.prisma().find_many(
+                where=prisma.types.AgentGraphWhereInput(
+                    userId=user_id, StoreListing={"none": {"isDeleted": False}}
+                ),
+                order=[{"version": "desc"}],
+                distinct=["id"],
+            )
+        )
+
+        total_pages = (total + page_size - 1) // page_size
+
+        agents = agents_with_max_version
+
+        my_agents = [
+            backend.server.v2.store.model.MyAgent(
+                agent_id=agent.id,
+                agent_version=agent.version,
+                agent_name=agent.name or "",
+                last_edited=agent.updatedAt or agent.createdAt,
+            )
+            for agent in agents
+        ]
+
+        return backend.server.v2.store.model.MyAgentsResponse(
+            agents=my_agents,
+            pagination=backend.server.v2.store.model.Pagination(
+                current_page=page,
+                total_items=total,
+                total_pages=total_pages,
+                page_size=page_size,
+            ),
+        )
+    except Exception as e:
+        logger.error(f"Error getting my agents: {str(e)}")
+        raise backend.server.v2.store.exceptions.DatabaseError(
+            "Failed to fetch my agents"
+        ) from e

autogpt_platform/backend/backend/server/v2/store/db_test.py

@@ -0,0 +1,260 @@
+from datetime import datetime
+
+import prisma.errors
+import prisma.models
+import pytest
+from prisma import Prisma
+
+import backend.server.v2.store.db as db
+from backend.server.v2.store.model import Profile
+
+
+@pytest.fixture(autouse=True)
+async def setup_prisma():
+    # Don't register client if already registered
+    try:
+        Prisma()
+    except prisma.errors.ClientAlreadyRegisteredError:
+        pass
+    yield
+
+
+@pytest.mark.asyncio
+async def test_get_store_agents(mocker):
+    # Mock data
+    mock_agents = [
+        prisma.models.StoreAgent(
+            listing_id="test-id",
+            storeListingVersionId="version123",
+            slug="test-agent",
+            agent_name="Test Agent",
+            agent_video=None,
+            agent_image=["image.jpg"],
+            featured=False,
+            creator_username="creator",
+            creator_avatar="avatar.jpg",
+            sub_heading="Test heading",
+            description="Test description",
+            categories=[],
+            runs=10,
+            rating=4.5,
+            versions=["1.0"],
+            updated_at=datetime.now(),
+        )
+    ]
+
+    # Mock prisma calls
+    mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
+    mock_store_agent.return_value.find_many = mocker.AsyncMock(return_value=mock_agents)
+    mock_store_agent.return_value.count = mocker.AsyncMock(return_value=1)
+
+    # Call function
+    result = await db.get_store_agents()
+
+    # Verify results
+    assert len(result.agents) == 1
+    assert result.agents[0].slug == "test-agent"
+    assert result.pagination.total_items == 1
+
+    # Verify mocks called correctly
+    mock_store_agent.return_value.find_many.assert_called_once()
+    mock_store_agent.return_value.count.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_get_store_agent_details(mocker):
+    # Mock data
+    mock_agent = prisma.models.StoreAgent(
+        listing_id="test-id",
+        storeListingVersionId="version123",
+        slug="test-agent",
+        agent_name="Test Agent",
+        agent_video="video.mp4",
+        agent_image=["image.jpg"],
+        featured=False,
+        creator_username="creator",
+        creator_avatar="avatar.jpg",
+        sub_heading="Test heading",
+        description="Test description",
+        categories=["test"],
+        runs=10,
+        rating=4.5,
+        versions=["1.0"],
+        updated_at=datetime.now(),
+    )
+
+    # Mock prisma call
+    mock_store_agent = mocker.patch("prisma.models.StoreAgent.prisma")
+    mock_store_agent.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
+
+    # Call function
+    result = await db.get_store_agent_details("creator", "test-agent")
+
+    # Verify results
+    assert result.slug == "test-agent"
+    assert result.agent_name == "Test Agent"
+
+    # Verify mock called correctly
+    mock_store_agent.return_value.find_first.assert_called_once_with(
+        where={"creator_username": "creator", "slug": "test-agent"}
+    )
+
+
+@pytest.mark.asyncio
+async def test_get_store_creator_details(mocker):
+    # Mock data
+    mock_creator_data = prisma.models.Creator(
+        name="Test Creator",
+        username="creator",
+        description="Test description",
+        links=["link1"],
+        avatar_url="avatar.jpg",
+        num_agents=1,
+        agent_rating=4.5,
+        agent_runs=10,
+        top_categories=["test"],
+    )
+
+    # Mock prisma call
+    mock_creator = mocker.patch("prisma.models.Creator.prisma")
+    mock_creator.return_value.find_unique = mocker.AsyncMock()
+    # Configure the mock to return values that will pass validation
+    mock_creator.return_value.find_unique.return_value = mock_creator_data
+
+    # Call function
+    result = await db.get_store_creator_details("creator")
+
+    # Verify results
+    assert result.username == "creator"
+    assert result.name == "Test Creator"
+    assert result.description == "Test description"
+    assert result.avatar_url == "avatar.jpg"
+
+    # Verify mock called correctly
+    mock_creator.return_value.find_unique.assert_called_once_with(
+        where={"username": "creator"}
+    )
+
+
+@pytest.mark.asyncio
+async def test_create_store_submission(mocker):
+    # Mock data
+    mock_agent = prisma.models.AgentGraph(
+        id="agent-id",
+        version=1,
+        userId="user-id",
+        createdAt=datetime.now(),
+        isActive=True,
+        isTemplate=False,
+    )
+
+    mock_listing = prisma.models.StoreListing(
+        id="listing-id",
+        createdAt=datetime.now(),
+        updatedAt=datetime.now(),
+        isDeleted=False,
+        isApproved=False,
+        agentId="agent-id",
+        agentVersion=1,
+        owningUserId="user-id",
+    )
+
+    # Mock prisma calls
+    mock_agent_graph = mocker.patch("prisma.models.AgentGraph.prisma")
+    mock_agent_graph.return_value.find_first = mocker.AsyncMock(return_value=mock_agent)
+
+    mock_store_listing = mocker.patch("prisma.models.StoreListing.prisma")
+    mock_store_listing.return_value.find_first = mocker.AsyncMock(return_value=None)
+    mock_store_listing.return_value.create = mocker.AsyncMock(return_value=mock_listing)
+
+    # Call function
+    result = await db.create_store_submission(
+        user_id="user-id",
+        agent_id="agent-id",
+        agent_version=1,
+        slug="test-agent",
+        name="Test Agent",
+        description="Test description",
+    )
+
+    # Verify results
+    assert result.name == "Test Agent"
+    assert result.description == "Test description"
+
+    # Verify mocks called correctly
+    mock_agent_graph.return_value.find_first.assert_called_once()
+    mock_store_listing.return_value.find_first.assert_called_once()
+    mock_store_listing.return_value.create.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_update_profile(mocker):
+    # Mock data
+    mock_profile = prisma.models.Profile(
+        id="profile-id",
+        name="Test Creator",
+        username="creator",
+        description="Test description",
+        links=["link1"],
+        avatarUrl="avatar.jpg",
+        createdAt=datetime.now(),
+        updatedAt=datetime.now(),
+    )
+
+    # Mock prisma calls
+    mock_profile_db = mocker.patch("prisma.models.Profile.prisma")
+    mock_profile_db.return_value.find_first = mocker.AsyncMock(
+        return_value=mock_profile
+    )
+    mock_profile_db.return_value.update = mocker.AsyncMock(return_value=mock_profile)
+
+    # Test data
+    profile = Profile(
+        name="Test Creator",
+        username="creator",
+        description="Test description",
+        links=["link1"],
+        avatar_url="avatar.jpg",
+    )
+
+    # Call function
+    result = await db.update_or_create_profile("user-id", profile)
+
+    # Verify results
+    assert result.username == "creator"
+    assert result.name == "Test Creator"
+
+    # Verify mocks called correctly
+    mock_profile_db.return_value.find_first.assert_called_once()
+    mock_profile_db.return_value.update.assert_called_once()
+
+
+@pytest.mark.asyncio
+async def test_get_user_profile(mocker):
+    # Mock data
+    mock_profile = prisma.models.Profile(
+        id="profile-id",
+        name="No Profile Data",
+        username="testuser",
+        description="Test description",
+        links=["link1", "link2"],
+        avatarUrl="avatar.jpg",
+        createdAt=datetime.now(),
+        updatedAt=datetime.now(),
+    )
+
+    # Mock prisma calls
+    mock_profile_db = mocker.patch("prisma.models.Profile.prisma")
+    mock_profile_db.return_value.find_unique = mocker.AsyncMock(
+        return_value=mock_profile
+    )
+
+    # Call function
+    result = await db.get_user_profile("user-id")
+
+    # Verify results
+    assert result.name == "No Profile Data"
+    assert result.username == "No Profile Data"
+    assert result.description == "No Profile Data"
+    assert result.links == []
+    assert result.avatar_url == ""

autogpt_platform/backend/backend/server/v2/store/exceptions.py

@@ -0,0 +1,76 @@
+class MediaUploadError(Exception):
+    """Base exception for media upload errors"""
+
+    pass
+
+
+class InvalidFileTypeError(MediaUploadError):
+    """Raised when file type is not supported"""
+
+    pass
+
+
+class FileSizeTooLargeError(MediaUploadError):
+    """Raised when file size exceeds maximum limit"""
+
+    pass
+
+
+class FileReadError(MediaUploadError):
+    """Raised when there's an error reading the file"""
+
+    pass
+
+
+class StorageConfigError(MediaUploadError):
+    """Raised when storage configuration is invalid"""
+
+    pass
+
+
+class StorageUploadError(MediaUploadError):
+    """Raised when upload to storage fails"""
+
+    pass
+
+
+class StoreError(Exception):
+    """Base exception for store-related errors"""
+
+    pass
+
+
+class AgentNotFoundError(StoreError):
+    """Raised when an agent is not found"""
+
+    pass
+
+
+class CreatorNotFoundError(StoreError):
+    """Raised when a creator is not found"""
+
+    pass
+
+
+class ListingExistsError(StoreError):
+    """Raised when trying to create a listing that already exists"""
+
+    pass
+
+
+class DatabaseError(StoreError):
+    """Raised when there is an error interacting with the database"""
+
+    pass
+
+
+class ProfileNotFoundError(StoreError):
+    """Raised when a profile is not found"""
+
+    pass
+
+
+class SubmissionNotFoundError(StoreError):
+    """Raised when a submission is not found"""
+
+    pass

autogpt_platform/backend/backend/server/v2/store/media.py

@@ -0,0 +1,101 @@
+import logging
+import os
+import uuid
+
+import fastapi
+from google.cloud import storage
+
+import backend.server.v2.store.exceptions
+from backend.util.settings import Settings
+
+logger = logging.getLogger(__name__)
+
+ALLOWED_IMAGE_TYPES = {"image/jpeg", "image/png", "image/gif", "image/webp"}
+ALLOWED_VIDEO_TYPES = {"video/mp4", "video/webm"}
+MAX_FILE_SIZE = 50 * 1024 * 1024  # 50MB
+
+
+async def upload_media(user_id: str, file: fastapi.UploadFile) -> str:
+    settings = Settings()
+
+    # Check required settings first before doing any file processing
+    if (
+        not settings.config.media_gcs_bucket_name
+        or not settings.config.google_application_credentials
+    ):
+        logger.error("Missing required GCS settings")
+        raise backend.server.v2.store.exceptions.StorageConfigError(
+            "Missing storage configuration"
+        )
+
+    try:
+        # Validate file type
+        content_type = file.content_type
+        if (
+            content_type not in ALLOWED_IMAGE_TYPES
+            and content_type not in ALLOWED_VIDEO_TYPES
+        ):
+            logger.warning(f"Invalid file type attempted: {content_type}")
+            raise backend.server.v2.store.exceptions.InvalidFileTypeError(
+                f"File type not supported. Must be jpeg, png, gif, webp, mp4 or webm. Content type: {content_type}"
+            )
+
+        # Validate file size
+        file_size = 0
+        chunk_size = 8192  # 8KB chunks
+
+        try:
+            while chunk := await file.read(chunk_size):
+                file_size += len(chunk)
+                if file_size > MAX_FILE_SIZE:
+                    logger.warning(f"File size too large: {file_size} bytes")
+                    raise backend.server.v2.store.exceptions.FileSizeTooLargeError(
+                        "File too large. Maximum size is 50MB"
+                    )
+        except backend.server.v2.store.exceptions.FileSizeTooLargeError:
+            raise
+        except Exception as e:
+            logger.error(f"Error reading file chunks: {str(e)}")
+            raise backend.server.v2.store.exceptions.FileReadError(
+                "Failed to read uploaded file"
+            ) from e
+
+        # Reset file pointer
+        await file.seek(0)
+
+        # Generate unique filename
+        filename = file.filename or ""
+        file_ext = os.path.splitext(filename)[1].lower()
+        unique_filename = f"{uuid.uuid4()}{file_ext}"
+
+        # Construct storage path
+        media_type = "images" if content_type in ALLOWED_IMAGE_TYPES else "videos"
+        storage_path = f"users/{user_id}/{media_type}/{unique_filename}"
+
+        try:
+            storage_client = storage.Client()
+            bucket = storage_client.bucket(settings.config.media_gcs_bucket_name)
+            blob = bucket.blob(storage_path)
+            blob.content_type = content_type
+
+            file_bytes = await file.read()
+            blob.upload_from_string(file_bytes, content_type=content_type)
+
+            public_url = blob.public_url
+
+            logger.info(f"Successfully uploaded file to: {storage_path}")
+            return public_url
+
+        except Exception as e:
+            logger.error(f"GCS storage error: {str(e)}")
+            raise backend.server.v2.store.exceptions.StorageUploadError(
+                "Failed to upload file to storage"
+            ) from e
+
+    except backend.server.v2.store.exceptions.MediaUploadError:
+        raise
+    except Exception as e:
+        logger.exception("Unexpected error in upload_media")
+        raise backend.server.v2.store.exceptions.MediaUploadError(
+            "Unexpected error during media upload"
+        ) from e

autogpt_platform/backend/backend/server/v2/store/media_test.py

@@ -0,0 +1,107 @@
+import io
+import unittest.mock
+
+import fastapi
+import pytest
+import starlette.datastructures
+
+import backend.server.v2.store.exceptions
+import backend.server.v2.store.media
+from backend.util.settings import Settings
+
+
+@pytest.fixture
+def mock_settings(monkeypatch):
+    settings = Settings()
+    settings.config.media_gcs_bucket_name = "test-bucket"
+    settings.config.google_application_credentials = "test-credentials"
+    monkeypatch.setattr("backend.server.v2.store.media.Settings", lambda: settings)
+    return settings
+
+
+@pytest.fixture
+def mock_storage_client(mocker):
+    mock_client = unittest.mock.MagicMock()
+    mock_bucket = unittest.mock.MagicMock()
+    mock_blob = unittest.mock.MagicMock()
+
+    mock_client.bucket.return_value = mock_bucket
+    mock_bucket.blob.return_value = mock_blob
+    mock_blob.public_url = "http://test-url/media/test.jpg"
+
+    mocker.patch("google.cloud.storage.Client", return_value=mock_client)
+
+    return mock_client
+
+
+async def test_upload_media_success(mock_settings, mock_storage_client):
+    test_file = fastapi.UploadFile(
+        filename="test.jpeg",
+        file=io.BytesIO(b"test data"),
+        headers=starlette.datastructures.Headers({"content-type": "image/jpeg"}),
+    )
+
+    result = await backend.server.v2.store.media.upload_media("test-user", test_file)
+
+    assert result == "http://test-url/media/test.jpg"
+    mock_bucket = mock_storage_client.bucket.return_value
+    mock_blob = mock_bucket.blob.return_value
+    mock_blob.upload_from_string.assert_called_once()
+
+
+async def test_upload_media_invalid_type(mock_settings, mock_storage_client):
+    test_file = fastapi.UploadFile(
+        filename="test.txt",
+        file=io.BytesIO(b"test data"),
+        headers=starlette.datastructures.Headers({"content-type": "text/plain"}),
+    )
+
+    with pytest.raises(backend.server.v2.store.exceptions.InvalidFileTypeError):
+        await backend.server.v2.store.media.upload_media("test-user", test_file)
+
+    mock_bucket = mock_storage_client.bucket.return_value
+    mock_blob = mock_bucket.blob.return_value
+    mock_blob.upload_from_string.assert_not_called()
+
+
+async def test_upload_media_missing_credentials(monkeypatch):
+    settings = Settings()
+    settings.config.media_gcs_bucket_name = ""
+    settings.config.google_application_credentials = ""
+    monkeypatch.setattr("backend.server.v2.store.media.Settings", lambda: settings)
+
+    test_file = fastapi.UploadFile(
+        filename="test.jpeg",
+        file=io.BytesIO(b"test data"),
+        headers=starlette.datastructures.Headers({"content-type": "image/jpeg"}),
+    )
+
+    with pytest.raises(backend.server.v2.store.exceptions.StorageConfigError):
+        await backend.server.v2.store.media.upload_media("test-user", test_file)
+
+
+async def test_upload_media_video_type(mock_settings, mock_storage_client):
+    test_file = fastapi.UploadFile(
+        filename="test.mp4",
+        file=io.BytesIO(b"test video data"),
+        headers=starlette.datastructures.Headers({"content-type": "video/mp4"}),
+    )
+
+    result = await backend.server.v2.store.media.upload_media("test-user", test_file)
+
+    assert result == "http://test-url/media/test.jpg"
+    mock_bucket = mock_storage_client.bucket.return_value
+    mock_blob = mock_bucket.blob.return_value
+    mock_blob.upload_from_string.assert_called_once()
+
+
+async def test_upload_media_file_too_large(mock_settings, mock_storage_client):
+    large_data = b"x" * (50 * 1024 * 1024 + 1)  # 50MB + 1 byte
+    test_file = fastapi.UploadFile(
+        filename="test.jpeg",
+        file=io.BytesIO(large_data),
+        headers=starlette.datastructures.Headers({"content-type": "image/jpeg"}),
+    )
+
+    with pytest.raises(backend.server.v2.store.exceptions.FileSizeTooLargeError):
+        await backend.server.v2.store.media.upload_media("test-user", test_file)

autogpt_platform/backend/backend/server/v2/store/model.py

@@ -0,0 +1,150 @@
+import datetime
+from typing import List
+
+import prisma.enums
+import pydantic
+
+
+class Pagination(pydantic.BaseModel):
+    total_items: int = pydantic.Field(
+        description="Total number of items.", examples=[42]
+    )
+    total_pages: int = pydantic.Field(
+        description="Total number of pages.", examples=[97]
+    )
+    current_page: int = pydantic.Field(
+        description="Current_page page number.", examples=[1]
+    )
+    page_size: int = pydantic.Field(
+        description="Number of items per page.", examples=[25]
+    )
+
+
+class MyAgent(pydantic.BaseModel):
+    agent_id: str
+    agent_version: int
+    agent_name: str
+    last_edited: datetime.datetime
+
+
+class MyAgentsResponse(pydantic.BaseModel):
+    agents: list[MyAgent]
+    pagination: Pagination
+
+
+class StoreAgent(pydantic.BaseModel):
+    slug: str
+    agent_name: str
+    agent_image: str
+    creator: str
+    creator_avatar: str
+    sub_heading: str
+    description: str
+    runs: int
+    rating: float
+
+
+class StoreAgentsResponse(pydantic.BaseModel):
+    agents: list[StoreAgent]
+    pagination: Pagination
+
+
+class StoreAgentDetails(pydantic.BaseModel):
+    store_listing_version_id: str
+    slug: str
+    agent_name: str
+    agent_video: str
+    agent_image: list[str]
+    creator: str
+    creator_avatar: str
+    sub_heading: str
+    description: str
+    categories: list[str]
+    runs: int
+    rating: float
+    versions: list[str]
+    last_updated: datetime.datetime
+
+
+class Creator(pydantic.BaseModel):
+    name: str
+    username: str
+    description: str
+    avatar_url: str
+    num_agents: int
+    agent_rating: float
+    agent_runs: int
+
+
+class CreatorsResponse(pydantic.BaseModel):
+    creators: List[Creator]
+    pagination: Pagination
+
+
+class CreatorDetails(pydantic.BaseModel):
+    name: str
+    username: str
+    description: str
+    links: list[str]
+    avatar_url: str
+    agent_rating: float
+    agent_runs: int
+    top_categories: list[str]
+
+
+class Profile(pydantic.BaseModel):
+    name: str
+    username: str
+    description: str
+    links: list[str]
+    avatar_url: str
+
+
+class StoreSubmission(pydantic.BaseModel):
+    agent_id: str
+    agent_version: int
+    name: str
+    sub_heading: str
+    slug: str
+    description: str
+    image_urls: list[str]
+    date_submitted: datetime.datetime
+    status: prisma.enums.SubmissionStatus
+    runs: int
+    rating: float
+
+
+class StoreSubmissionsResponse(pydantic.BaseModel):
+    submissions: list[StoreSubmission]
+    pagination: Pagination
+
+
+class StoreSubmissionRequest(pydantic.BaseModel):
+    agent_id: str
+    agent_version: int
+    slug: str
+    name: str
+    sub_heading: str
+    video_url: str | None = None
+    image_urls: list[str] = []
+    description: str = ""
+    categories: list[str] = []
+
+
+class ProfileDetails(pydantic.BaseModel):
+    name: str
+    username: str
+    description: str
+    links: list[str]
+    avatar_url: str | None = None
+
+
+class StoreReview(pydantic.BaseModel):
+    score: int
+    comments: str | None = None
+
+
+class StoreReviewCreate(pydantic.BaseModel):
+    store_listing_version_id: str
+    score: int
+    comments: str | None = None

autogpt_platform/backend/backend/server/v2/store/model_test.py

@@ -0,0 +1,193 @@
+import datetime
+
+import prisma.enums
+
+import backend.server.v2.store.model
+
+
+def test_pagination():
+    pagination = backend.server.v2.store.model.Pagination(
+        total_items=100, total_pages=5, current_page=2, page_size=20
+    )
+    assert pagination.total_items == 100
+    assert pagination.total_pages == 5
+    assert pagination.current_page == 2
+    assert pagination.page_size == 20
+
+
+def test_store_agent():
+    agent = backend.server.v2.store.model.StoreAgent(
+        slug="test-agent",
+        agent_name="Test Agent",
+        agent_image="test.jpg",
+        creator="creator1",
+        creator_avatar="avatar.jpg",
+        sub_heading="Test subheading",
+        description="Test description",
+        runs=50,
+        rating=4.5,
+    )
+    assert agent.slug == "test-agent"
+    assert agent.agent_name == "Test Agent"
+    assert agent.runs == 50
+    assert agent.rating == 4.5
+
+
+def test_store_agents_response():
+    response = backend.server.v2.store.model.StoreAgentsResponse(
+        agents=[
+            backend.server.v2.store.model.StoreAgent(
+                slug="test-agent",
+                agent_name="Test Agent",
+                agent_image="test.jpg",
+                creator="creator1",
+                creator_avatar="avatar.jpg",
+                sub_heading="Test subheading",
+                description="Test description",
+                runs=50,
+                rating=4.5,
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            total_items=1, total_pages=1, current_page=1, page_size=20
+        ),
+    )
+    assert len(response.agents) == 1
+    assert response.pagination.total_items == 1
+
+
+def test_store_agent_details():
+    details = backend.server.v2.store.model.StoreAgentDetails(
+        store_listing_version_id="version123",
+        slug="test-agent",
+        agent_name="Test Agent",
+        agent_video="video.mp4",
+        agent_image=["image1.jpg", "image2.jpg"],
+        creator="creator1",
+        creator_avatar="avatar.jpg",
+        sub_heading="Test subheading",
+        description="Test description",
+        categories=["cat1", "cat2"],
+        runs=50,
+        rating=4.5,
+        versions=["1.0", "2.0"],
+        last_updated=datetime.datetime.now(),
+    )
+    assert details.slug == "test-agent"
+    assert len(details.agent_image) == 2
+    assert len(details.categories) == 2
+    assert len(details.versions) == 2
+
+
+def test_creator():
+    creator = backend.server.v2.store.model.Creator(
+        agent_rating=4.8,
+        agent_runs=1000,
+        name="Test Creator",
+        username="creator1",
+        description="Test description",
+        avatar_url="avatar.jpg",
+        num_agents=5,
+    )
+    assert creator.name == "Test Creator"
+    assert creator.num_agents == 5
+
+
+def test_creators_response():
+    response = backend.server.v2.store.model.CreatorsResponse(
+        creators=[
+            backend.server.v2.store.model.Creator(
+                agent_rating=4.8,
+                agent_runs=1000,
+                name="Test Creator",
+                username="creator1",
+                description="Test description",
+                avatar_url="avatar.jpg",
+                num_agents=5,
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            total_items=1, total_pages=1, current_page=1, page_size=20
+        ),
+    )
+    assert len(response.creators) == 1
+    assert response.pagination.total_items == 1
+
+
+def test_creator_details():
+    details = backend.server.v2.store.model.CreatorDetails(
+        name="Test Creator",
+        username="creator1",
+        description="Test description",
+        links=["link1.com", "link2.com"],
+        avatar_url="avatar.jpg",
+        agent_rating=4.8,
+        agent_runs=1000,
+        top_categories=["cat1", "cat2"],
+    )
+    assert details.name == "Test Creator"
+    assert len(details.links) == 2
+    assert details.agent_rating == 4.8
+    assert len(details.top_categories) == 2
+
+
+def test_store_submission():
+    submission = backend.server.v2.store.model.StoreSubmission(
+        agent_id="agent123",
+        agent_version=1,
+        sub_heading="Test subheading",
+        name="Test Agent",
+        slug="test-agent",
+        description="Test description",
+        image_urls=["image1.jpg", "image2.jpg"],
+        date_submitted=datetime.datetime(2023, 1, 1),
+        status=prisma.enums.SubmissionStatus.PENDING,
+        runs=50,
+        rating=4.5,
+    )
+    assert submission.name == "Test Agent"
+    assert len(submission.image_urls) == 2
+    assert submission.status == prisma.enums.SubmissionStatus.PENDING
+
+
+def test_store_submissions_response():
+    response = backend.server.v2.store.model.StoreSubmissionsResponse(
+        submissions=[
+            backend.server.v2.store.model.StoreSubmission(
+                agent_id="agent123",
+                agent_version=1,
+                sub_heading="Test subheading",
+                name="Test Agent",
+                slug="test-agent",
+                description="Test description",
+                image_urls=["image1.jpg"],
+                date_submitted=datetime.datetime(2023, 1, 1),
+                status=prisma.enums.SubmissionStatus.PENDING,
+                runs=50,
+                rating=4.5,
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            total_items=1, total_pages=1, current_page=1, page_size=20
+        ),
+    )
+    assert len(response.submissions) == 1
+    assert response.pagination.total_items == 1
+
+
+def test_store_submission_request():
+    request = backend.server.v2.store.model.StoreSubmissionRequest(
+        agent_id="agent123",
+        agent_version=1,
+        slug="test-agent",
+        name="Test Agent",
+        sub_heading="Test subheading",
+        video_url="video.mp4",
+        image_urls=["image1.jpg", "image2.jpg"],
+        description="Test description",
+        categories=["cat1", "cat2"],
+    )
+    assert request.agent_id == "agent123"
+    assert request.agent_version == 1
+    assert len(request.image_urls) == 2
+    assert len(request.categories) == 2

autogpt_platform/backend/backend/server/v2/store/routes.py

@@ -0,0 +1,439 @@
+import logging
+import typing
+
+import autogpt_libs.auth.depends
+import autogpt_libs.auth.middleware
+import fastapi
+import fastapi.responses
+
+import backend.server.v2.store.db
+import backend.server.v2.store.media
+import backend.server.v2.store.model
+
+logger = logging.getLogger(__name__)
+
+router = fastapi.APIRouter()
+
+
+##############################################
+############### Profile Endpoints ############
+##############################################
+
+
+@router.get("/profile", tags=["store", "private"])
+async def get_profile(
+    user_id: typing.Annotated[
+        str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
+    ]
+) -> backend.server.v2.store.model.ProfileDetails:
+    """
+    Get the profile details for the authenticated user.
+    """
+    try:
+        profile = await backend.server.v2.store.db.get_user_profile(user_id)
+        return profile
+    except Exception:
+        logger.exception("Exception occurred whilst getting user profile")
+        raise
+
+
+@router.post(
+    "/profile",
+    tags=["store", "private"],
+    dependencies=[fastapi.Depends(autogpt_libs.auth.middleware.auth_middleware)],
+)
+async def update_or_create_profile(
+    profile: backend.server.v2.store.model.Profile,
+    user_id: typing.Annotated[
+        str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
+    ],
+) -> backend.server.v2.store.model.CreatorDetails:
+    """
+    Update the store profile for the authenticated user.
+
+    Args:
+        profile (Profile): The updated profile details
+        user_id (str): ID of the authenticated user
+
+    Returns:
+        CreatorDetails: The updated profile
+
+    Raises:
+        HTTPException: If there is an error updating the profile
+    """
+    try:
+        updated_profile = await backend.server.v2.store.db.update_or_create_profile(
+            user_id=user_id, profile=profile
+        )
+        return updated_profile
+    except Exception:
+        logger.exception("Exception occurred whilst updating profile")
+        raise
+
+
+##############################################
+############### Agent Endpoints ##############
+##############################################
+
+
+@router.get("/agents", tags=["store", "public"])
+async def get_agents(
+    featured: bool = False,
+    creator: str | None = None,
+    sorted_by: str | None = None,
+    search_query: str | None = None,
+    category: str | None = None,
+    page: int = 1,
+    page_size: int = 20,
+) -> backend.server.v2.store.model.StoreAgentsResponse:
+    """
+    Get a paginated list of agents from the store with optional filtering and sorting.
+
+    Args:
+        featured (bool, optional): Filter to only show featured agents. Defaults to False.
+        creator (str | None, optional): Filter agents by creator username. Defaults to None.
+        sorted_by (str | None, optional): Sort agents by "runs" or "rating". Defaults to None.
+        search_query (str | None, optional): Search agents by name, subheading and description. Defaults to None.
+        category (str | None, optional): Filter agents by category. Defaults to None.
+        page (int, optional): Page number for pagination. Defaults to 1.
+        page_size (int, optional): Number of agents per page. Defaults to 20.
+
+    Returns:
+        StoreAgentsResponse: Paginated list of agents matching the filters
+
+    Raises:
+        HTTPException: If page or page_size are less than 1
+
+    Used for:
+    - Home Page Featured Agents
+    - Home Page Top Agents
+    - Search Results
+    - Agent Details - Other Agents By Creator
+    - Agent Details - Similar Agents
+    - Creator Details - Agents By Creator
+    """
+    if page < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page must be greater than 0"
+        )
+
+    if page_size < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page size must be greater than 0"
+        )
+
+    try:
+        agents = await backend.server.v2.store.db.get_store_agents(
+            featured=featured,
+            creator=creator,
+            sorted_by=sorted_by,
+            search_query=search_query,
+            category=category,
+            page=page,
+            page_size=page_size,
+        )
+        return agents
+    except Exception:
+        logger.exception("Exception occured whilst getting store agents")
+        raise
+
+
+@router.get("/agents/{username}/{agent_name}", tags=["store", "public"])
+async def get_agent(
+    username: str, agent_name: str
+) -> backend.server.v2.store.model.StoreAgentDetails:
+    """
+    This is only used on the AgentDetails Page
+
+    It returns the store listing agents details.
+    """
+    try:
+        agent = await backend.server.v2.store.db.get_store_agent_details(
+            username=username, agent_name=agent_name
+        )
+        return agent
+    except Exception:
+        logger.exception("Exception occurred whilst getting store agent details")
+        raise
+
+
+@router.post(
+    "/agents/{username}/{agent_name}/review",
+    tags=["store"],
+    dependencies=[fastapi.Depends(autogpt_libs.auth.middleware.auth_middleware)],
+)
+async def create_review(
+    username: str,
+    agent_name: str,
+    review: backend.server.v2.store.model.StoreReviewCreate,
+    user_id: typing.Annotated[
+        str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
+    ],
+) -> backend.server.v2.store.model.StoreReview:
+    """
+    Create a review for a store agent.
+
+    Args:
+        username: Creator's username
+        agent_name: Name/slug of the agent
+        review: Review details including score and optional comments
+        user_id: ID of authenticated user creating the review
+
+    Returns:
+        The created review
+    """
+    try:
+        # Create the review
+        created_review = await backend.server.v2.store.db.create_store_review(
+            user_id=user_id,
+            store_listing_version_id=review.store_listing_version_id,
+            score=review.score,
+            comments=review.comments,
+        )
+
+        return created_review
+    except Exception:
+        logger.exception("Exception occurred whilst creating store review")
+        raise
+
+
+##############################################
+############# Creator Endpoints #############
+##############################################
+
+
+@router.get("/creators", tags=["store", "public"])
+async def get_creators(
+    featured: bool = False,
+    search_query: str | None = None,
+    sorted_by: str | None = None,
+    page: int = 1,
+    page_size: int = 20,
+) -> backend.server.v2.store.model.CreatorsResponse:
+    """
+    This is needed for:
+    - Home Page Featured Creators
+    - Search Results Page
+
+    ---
+
+    To support this functionality we need:
+    - featured: bool - to limit the list to just featured agents
+    - search_query: str - vector search based on the creators profile description.
+    - sorted_by: [agent_rating, agent_runs] -
+    """
+    if page < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page must be greater than 0"
+        )
+
+    if page_size < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page size must be greater than 0"
+        )
+
+    try:
+        creators = await backend.server.v2.store.db.get_store_creators(
+            featured=featured,
+            search_query=search_query,
+            sorted_by=sorted_by,
+            page=page,
+            page_size=page_size,
+        )
+        return creators
+    except Exception:
+        logger.exception("Exception occurred whilst getting store creators")
+        raise
+
+
+@router.get("/creator/{username}", tags=["store", "public"])
+async def get_creator(username: str) -> backend.server.v2.store.model.CreatorDetails:
+    """
+    Get the details of a creator
+    - Creator Details Page
+    """
+    try:
+        creator = await backend.server.v2.store.db.get_store_creator_details(
+            username=username
+        )
+        return creator
+    except Exception:
+        logger.exception("Exception occurred whilst getting creator details")
+        raise
+
+
+############################################
+############# Store Submissions ###############
+############################################
+@router.get(
+    "/myagents",
+    tags=["store", "private"],
+    dependencies=[fastapi.Depends(autogpt_libs.auth.middleware.auth_middleware)],
+)
+async def get_my_agents(
+    user_id: typing.Annotated[
+        str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
+    ]
+) -> backend.server.v2.store.model.MyAgentsResponse:
+    try:
+        agents = await backend.server.v2.store.db.get_my_agents(user_id)
+        return agents
+    except Exception:
+        logger.exception("Exception occurred whilst getting my agents")
+        raise
+
+
+@router.delete(
+    "/submissions/{submission_id}",
+    tags=["store", "private"],
+    dependencies=[fastapi.Depends(autogpt_libs.auth.middleware.auth_middleware)],
+)
+async def delete_submission(
+    user_id: typing.Annotated[
+        str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
+    ],
+    submission_id: str,
+) -> bool:
+    """
+    Delete a store listing submission.
+
+    Args:
+        user_id (str): ID of the authenticated user
+        submission_id (str): ID of the submission to be deleted
+
+    Returns:
+        bool: True if the submission was successfully deleted, False otherwise
+    """
+    try:
+        result = await backend.server.v2.store.db.delete_store_submission(
+            user_id=user_id,
+            submission_id=submission_id,
+        )
+        return result
+    except Exception:
+        logger.exception("Exception occurred whilst deleting store submission")
+        raise
+
+
+@router.get(
+    "/submissions",
+    tags=["store", "private"],
+    dependencies=[fastapi.Depends(autogpt_libs.auth.middleware.auth_middleware)],
+)
+async def get_submissions(
+    user_id: typing.Annotated[
+        str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
+    ],
+    page: int = 1,
+    page_size: int = 20,
+) -> backend.server.v2.store.model.StoreSubmissionsResponse:
+    """
+    Get a paginated list of store submissions for the authenticated user.
+
+    Args:
+        user_id (str): ID of the authenticated user
+        page (int, optional): Page number for pagination. Defaults to 1.
+        page_size (int, optional): Number of submissions per page. Defaults to 20.
+
+    Returns:
+        StoreListingsResponse: Paginated list of store submissions
+
+    Raises:
+        HTTPException: If page or page_size are less than 1
+    """
+    if page < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page must be greater than 0"
+        )
+
+    if page_size < 1:
+        raise fastapi.HTTPException(
+            status_code=422, detail="Page size must be greater than 0"
+        )
+    try:
+        listings = await backend.server.v2.store.db.get_store_submissions(
+            user_id=user_id,
+            page=page,
+            page_size=page_size,
+        )
+        return listings
+    except Exception:
+        logger.exception("Exception occurred whilst getting store submissions")
+        raise
+
+
+@router.post(
+    "/submissions",
+    tags=["store", "private"],
+    dependencies=[fastapi.Depends(autogpt_libs.auth.middleware.auth_middleware)],
+)
+async def create_submission(
+    submission_request: backend.server.v2.store.model.StoreSubmissionRequest,
+    user_id: typing.Annotated[
+        str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
+    ],
+) -> backend.server.v2.store.model.StoreSubmission:
+    """
+    Create a new store listing submission.
+
+    Args:
+        submission_request (StoreSubmissionRequest): The submission details
+        user_id (str): ID of the authenticated user submitting the listing
+
+    Returns:
+        StoreSubmission: The created store submission
+
+    Raises:
+        HTTPException: If there is an error creating the submission
+    """
+    try:
+        submission = await backend.server.v2.store.db.create_store_submission(
+            user_id=user_id,
+            agent_id=submission_request.agent_id,
+            agent_version=submission_request.agent_version,
+            slug=submission_request.slug,
+            name=submission_request.name,
+            video_url=submission_request.video_url,
+            image_urls=submission_request.image_urls,
+            description=submission_request.description,
+            sub_heading=submission_request.sub_heading,
+            categories=submission_request.categories,
+        )
+        return submission
+    except Exception:
+        logger.exception("Exception occurred whilst creating store submission")
+        raise
+
+
+@router.post(
+    "/submissions/media",
+    tags=["store", "private"],
+    dependencies=[fastapi.Depends(autogpt_libs.auth.middleware.auth_middleware)],
+)
+async def upload_submission_media(
+    file: fastapi.UploadFile,
+    user_id: typing.Annotated[
+        str, fastapi.Depends(autogpt_libs.auth.depends.get_user_id)
+    ],
+) -> str:
+    """
+    Upload media (images/videos) for a store listing submission.
+
+    Args:
+        file (UploadFile): The media file to upload
+        user_id (str): ID of the authenticated user uploading the media
+
+    Returns:
+        str: URL of the uploaded media file
+
+    Raises:
+        HTTPException: If there is an error uploading the media
+    """
+    try:
+        media_url = await backend.server.v2.store.media.upload_media(
+            user_id=user_id, file=file
+        )
+        return media_url
+    except Exception:
+        logger.exception("Exception occurred whilst uploading submission media")
+        raise

autogpt_platform/backend/backend/server/v2/store/routes_test.py

@@ -0,0 +1,551 @@
+import datetime
+
+import autogpt_libs.auth.depends
+import autogpt_libs.auth.middleware
+import fastapi
+import fastapi.testclient
+import prisma.enums
+import pytest_mock
+
+import backend.server.v2.store.model
+import backend.server.v2.store.routes
+
+app = fastapi.FastAPI()
+app.include_router(backend.server.v2.store.routes.router)
+
+client = fastapi.testclient.TestClient(app)
+
+
+def override_auth_middleware():
+    """Override auth middleware for testing"""
+    return {"sub": "test-user-id"}
+
+
+def override_get_user_id():
+    """Override get_user_id for testing"""
+    return "test-user-id"
+
+
+app.dependency_overrides[autogpt_libs.auth.middleware.auth_middleware] = (
+    override_auth_middleware
+)
+app.dependency_overrides[autogpt_libs.auth.depends.get_user_id] = override_get_user_id
+
+
+def test_get_agents_defaults(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+        agents=[],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=0,
+            total_items=0,
+            total_pages=0,
+            page_size=10,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call.return_value = mocked_value
+    response = client.get("/agents")
+    assert response.status_code == 200
+
+    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
+        response.json()
+    )
+    assert data.pagination.total_pages == 0
+    assert data.agents == []
+    mock_db_call.assert_called_once_with(
+        featured=False,
+        creator=None,
+        sorted_by=None,
+        search_query=None,
+        category=None,
+        page=1,
+        page_size=20,
+    )
+
+
+def test_get_agents_featured(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+        agents=[
+            backend.server.v2.store.model.StoreAgent(
+                slug="featured-agent",
+                agent_name="Featured Agent",
+                agent_image="featured.jpg",
+                creator="creator1",
+                creator_avatar="avatar1.jpg",
+                sub_heading="Featured agent subheading",
+                description="Featured agent description",
+                runs=100,
+                rating=4.5,
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=1,
+            total_items=1,
+            total_pages=1,
+            page_size=20,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call.return_value = mocked_value
+    response = client.get("/agents?featured=true")
+    assert response.status_code == 200
+    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
+        response.json()
+    )
+    assert len(data.agents) == 1
+    assert data.agents[0].slug == "featured-agent"
+    mock_db_call.assert_called_once_with(
+        featured=True,
+        creator=None,
+        sorted_by=None,
+        search_query=None,
+        category=None,
+        page=1,
+        page_size=20,
+    )
+
+
+def test_get_agents_by_creator(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+        agents=[
+            backend.server.v2.store.model.StoreAgent(
+                slug="creator-agent",
+                agent_name="Creator Agent",
+                agent_image="agent.jpg",
+                creator="specific-creator",
+                creator_avatar="avatar.jpg",
+                sub_heading="Creator agent subheading",
+                description="Creator agent description",
+                runs=50,
+                rating=4.0,
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=1,
+            total_items=1,
+            total_pages=1,
+            page_size=20,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call.return_value = mocked_value
+    response = client.get("/agents?creator=specific-creator")
+    assert response.status_code == 200
+    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
+        response.json()
+    )
+    assert len(data.agents) == 1
+    assert data.agents[0].creator == "specific-creator"
+    mock_db_call.assert_called_once_with(
+        featured=False,
+        creator="specific-creator",
+        sorted_by=None,
+        search_query=None,
+        category=None,
+        page=1,
+        page_size=20,
+    )
+
+
+def test_get_agents_sorted(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+        agents=[
+            backend.server.v2.store.model.StoreAgent(
+                slug="top-agent",
+                agent_name="Top Agent",
+                agent_image="top.jpg",
+                creator="creator1",
+                creator_avatar="avatar1.jpg",
+                sub_heading="Top agent subheading",
+                description="Top agent description",
+                runs=1000,
+                rating=5.0,
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=1,
+            total_items=1,
+            total_pages=1,
+            page_size=20,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call.return_value = mocked_value
+    response = client.get("/agents?sorted_by=runs")
+    assert response.status_code == 200
+    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
+        response.json()
+    )
+    assert len(data.agents) == 1
+    assert data.agents[0].runs == 1000
+    mock_db_call.assert_called_once_with(
+        featured=False,
+        creator=None,
+        sorted_by="runs",
+        search_query=None,
+        category=None,
+        page=1,
+        page_size=20,
+    )
+
+
+def test_get_agents_search(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+        agents=[
+            backend.server.v2.store.model.StoreAgent(
+                slug="search-agent",
+                agent_name="Search Agent",
+                agent_image="search.jpg",
+                creator="creator1",
+                creator_avatar="avatar1.jpg",
+                sub_heading="Search agent subheading",
+                description="Specific search term description",
+                runs=75,
+                rating=4.2,
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=1,
+            total_items=1,
+            total_pages=1,
+            page_size=20,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call.return_value = mocked_value
+    response = client.get("/agents?search_query=specific")
+    assert response.status_code == 200
+    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
+        response.json()
+    )
+    assert len(data.agents) == 1
+    assert "specific" in data.agents[0].description.lower()
+    mock_db_call.assert_called_once_with(
+        featured=False,
+        creator=None,
+        sorted_by=None,
+        search_query="specific",
+        category=None,
+        page=1,
+        page_size=20,
+    )
+
+
+def test_get_agents_category(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+        agents=[
+            backend.server.v2.store.model.StoreAgent(
+                slug="category-agent",
+                agent_name="Category Agent",
+                agent_image="category.jpg",
+                creator="creator1",
+                creator_avatar="avatar1.jpg",
+                sub_heading="Category agent subheading",
+                description="Category agent description",
+                runs=60,
+                rating=4.1,
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=1,
+            total_items=1,
+            total_pages=1,
+            page_size=20,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call.return_value = mocked_value
+    response = client.get("/agents?category=test-category")
+    assert response.status_code == 200
+    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
+        response.json()
+    )
+    assert len(data.agents) == 1
+    mock_db_call.assert_called_once_with(
+        featured=False,
+        creator=None,
+        sorted_by=None,
+        search_query=None,
+        category="test-category",
+        page=1,
+        page_size=20,
+    )
+
+
+def test_get_agents_pagination(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreAgentsResponse(
+        agents=[
+            backend.server.v2.store.model.StoreAgent(
+                slug=f"agent-{i}",
+                agent_name=f"Agent {i}",
+                agent_image=f"agent{i}.jpg",
+                creator="creator1",
+                creator_avatar="avatar1.jpg",
+                sub_heading=f"Agent {i} subheading",
+                description=f"Agent {i} description",
+                runs=i * 10,
+                rating=4.0,
+            )
+            for i in range(5)
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=2,
+            total_items=15,
+            total_pages=3,
+            page_size=5,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call.return_value = mocked_value
+    response = client.get("/agents?page=2&page_size=5")
+    assert response.status_code == 200
+    data = backend.server.v2.store.model.StoreAgentsResponse.model_validate(
+        response.json()
+    )
+    assert len(data.agents) == 5
+    assert data.pagination.current_page == 2
+    assert data.pagination.page_size == 5
+    mock_db_call.assert_called_once_with(
+        featured=False,
+        creator=None,
+        sorted_by=None,
+        search_query=None,
+        category=None,
+        page=2,
+        page_size=5,
+    )
+
+
+def test_get_agents_malformed_request(mocker: pytest_mock.MockFixture):
+    # Test with invalid page number
+    response = client.get("/agents?page=-1")
+    assert response.status_code == 422
+
+    # Test with invalid page size
+    response = client.get("/agents?page_size=0")
+    assert response.status_code == 422
+
+    # Test with non-numeric values
+    response = client.get("/agents?page=abc&page_size=def")
+    assert response.status_code == 422
+
+    # Verify no DB calls were made
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agents")
+    mock_db_call.assert_not_called()
+
+
+def test_get_agent_details(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreAgentDetails(
+        store_listing_version_id="test-version-id",
+        slug="test-agent",
+        agent_name="Test Agent",
+        agent_video="video.mp4",
+        agent_image=["image1.jpg", "image2.jpg"],
+        creator="creator1",
+        creator_avatar="avatar1.jpg",
+        sub_heading="Test agent subheading",
+        description="Test agent description",
+        categories=["category1", "category2"],
+        runs=100,
+        rating=4.5,
+        versions=["1.0.0", "1.1.0"],
+        last_updated=datetime.datetime.now(),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_agent_details")
+    mock_db_call.return_value = mocked_value
+
+    response = client.get("/agents/creator1/test-agent")
+    assert response.status_code == 200
+
+    data = backend.server.v2.store.model.StoreAgentDetails.model_validate(
+        response.json()
+    )
+    assert data.agent_name == "Test Agent"
+    assert data.creator == "creator1"
+    mock_db_call.assert_called_once_with(username="creator1", agent_name="test-agent")
+
+
+def test_get_creators_defaults(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.CreatorsResponse(
+        creators=[],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=0,
+            total_items=0,
+            total_pages=0,
+            page_size=10,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_creators")
+    mock_db_call.return_value = mocked_value
+
+    response = client.get("/creators")
+    assert response.status_code == 200
+
+    data = backend.server.v2.store.model.CreatorsResponse.model_validate(
+        response.json()
+    )
+    assert data.pagination.total_pages == 0
+    assert data.creators == []
+    mock_db_call.assert_called_once_with(
+        featured=False, search_query=None, sorted_by=None, page=1, page_size=20
+    )
+
+
+def test_get_creators_pagination(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.CreatorsResponse(
+        creators=[
+            backend.server.v2.store.model.Creator(
+                name=f"Creator {i}",
+                username=f"creator{i}",
+                description=f"Creator {i} description",
+                avatar_url=f"avatar{i}.jpg",
+                num_agents=1,
+                agent_rating=4.5,
+                agent_runs=100,
+            )
+            for i in range(5)
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=2,
+            total_items=15,
+            total_pages=3,
+            page_size=5,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_creators")
+    mock_db_call.return_value = mocked_value
+
+    response = client.get("/creators?page=2&page_size=5")
+    assert response.status_code == 200
+
+    data = backend.server.v2.store.model.CreatorsResponse.model_validate(
+        response.json()
+    )
+    assert len(data.creators) == 5
+    assert data.pagination.current_page == 2
+    assert data.pagination.page_size == 5
+    mock_db_call.assert_called_once_with(
+        featured=False, search_query=None, sorted_by=None, page=2, page_size=5
+    )
+
+
+def test_get_creators_malformed_request(mocker: pytest_mock.MockFixture):
+    # Test with invalid page number
+    response = client.get("/creators?page=-1")
+    assert response.status_code == 422
+
+    # Test with invalid page size
+    response = client.get("/creators?page_size=0")
+    assert response.status_code == 422
+
+    # Test with non-numeric values
+    response = client.get("/creators?page=abc&page_size=def")
+    assert response.status_code == 422
+
+    # Verify no DB calls were made
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_creators")
+    mock_db_call.assert_not_called()
+
+
+def test_get_creator_details(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.CreatorDetails(
+        name="Test User",
+        username="creator1",
+        description="Test creator description",
+        links=["link1.com", "link2.com"],
+        avatar_url="avatar.jpg",
+        agent_rating=4.8,
+        agent_runs=1000,
+        top_categories=["category1", "category2"],
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_creator_details")
+    mock_db_call.return_value = mocked_value
+
+    response = client.get("/creator/creator1")
+    assert response.status_code == 200
+
+    data = backend.server.v2.store.model.CreatorDetails.model_validate(response.json())
+    assert data.username == "creator1"
+    assert data.name == "Test User"
+    mock_db_call.assert_called_once_with(username="creator1")
+
+
+def test_get_submissions_success(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreSubmissionsResponse(
+        submissions=[
+            backend.server.v2.store.model.StoreSubmission(
+                name="Test Agent",
+                description="Test agent description",
+                image_urls=["test.jpg"],
+                date_submitted=datetime.datetime.now(),
+                status=prisma.enums.SubmissionStatus.APPROVED,
+                runs=50,
+                rating=4.2,
+                agent_id="test-agent-id",
+                agent_version=1,
+                sub_heading="Test agent subheading",
+                slug="test-agent",
+            )
+        ],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=1,
+            total_items=1,
+            total_pages=1,
+            page_size=20,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_submissions")
+    mock_db_call.return_value = mocked_value
+
+    response = client.get("/submissions")
+    assert response.status_code == 200
+
+    data = backend.server.v2.store.model.StoreSubmissionsResponse.model_validate(
+        response.json()
+    )
+    assert len(data.submissions) == 1
+    assert data.submissions[0].name == "Test Agent"
+    assert data.pagination.current_page == 1
+    mock_db_call.assert_called_once_with(user_id="test-user-id", page=1, page_size=20)
+
+
+def test_get_submissions_pagination(mocker: pytest_mock.MockFixture):
+    mocked_value = backend.server.v2.store.model.StoreSubmissionsResponse(
+        submissions=[],
+        pagination=backend.server.v2.store.model.Pagination(
+            current_page=2,
+            total_items=10,
+            total_pages=2,
+            page_size=5,
+        ),
+    )
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_submissions")
+    mock_db_call.return_value = mocked_value
+
+    response = client.get("/submissions?page=2&page_size=5")
+    assert response.status_code == 200
+
+    data = backend.server.v2.store.model.StoreSubmissionsResponse.model_validate(
+        response.json()
+    )
+    assert data.pagination.current_page == 2
+    assert data.pagination.page_size == 5
+    mock_db_call.assert_called_once_with(user_id="test-user-id", page=2, page_size=5)
+
+
+def test_get_submissions_malformed_request(mocker: pytest_mock.MockFixture):
+    # Test with invalid page number
+    response = client.get("/submissions?page=-1")
+    assert response.status_code == 422
+
+    # Test with invalid page size
+    response = client.get("/submissions?page_size=0")
+    assert response.status_code == 422
+
+    # Test with non-numeric values
+    response = client.get("/submissions?page=abc&page_size=def")
+    assert response.status_code == 422
+
+    # Verify no DB calls were made
+    mock_db_call = mocker.patch("backend.server.v2.store.db.get_store_submissions")
+    mock_db_call.assert_not_called()

autogpt_platform/backend/backend/util/request.py

@@ -1,8 +1,10 @@
 import ipaddress
+import re
 import socket
 from typing import Callable
-from urllib.parse import urlparse
+from urllib.parse import urlparse, urlunparse
 
+import idna
 import requests as req
 
 from backend.util.settings import Config
@@ -21,8 +23,23 @@ BLOCKED_IP_NETWORKS = [
     # --8<-- [end:BLOCKED_IP_NETWORKS]
 ]
 
+ALLOWED_SCHEMES = ["http", "https"]
+HOSTNAME_REGEX = re.compile(r"^[A-Za-z0-9.-]+$")  # Basic DNS-safe hostname pattern
 
-def is_ip_blocked(ip: str) -> bool:
+
+def _canonicalize_url(url: str) -> str:
+    # Strip spaces and trailing slashes
+    url = url.strip().strip("/")
+    # Ensure the URL starts with http:// or https://
+    if not url.startswith(("http://", "https://")):
+        url = "http://" + url
+
+    # Replace backslashes with forward slashes to avoid parsing ambiguities
+    url = url.replace("\\", "/")
+    return url
+
+
+def _is_ip_blocked(ip: str) -> bool:
     """
     Checks if the IP address is in a blocked network.
     """
@@ -35,29 +52,51 @@ def validate_url(url: str, trusted_origins: list[str]) -> str:
     Validates the URL to prevent SSRF attacks by ensuring it does not point to a private
     or untrusted IP address, unless whitelisted.
     """
-    url = url.strip().strip("/")
-    if not url.startswith(("http://", "https://")):
-        url = "http://" + url
+    url = _canonicalize_url(url)
+    parsed = urlparse(url)
 
-    parsed_url = urlparse(url)
-    hostname = parsed_url.hostname
+    # Check scheme
+    if parsed.scheme not in ALLOWED_SCHEMES:
+        raise ValueError(
+            f"Scheme '{parsed.scheme}' is not allowed. Only HTTP/HTTPS are supported."
+        )
 
-    if not hostname:
-        raise ValueError(f"Invalid URL: Unable to determine hostname from {url}")
+    # Validate and IDNA encode the hostname
+    if not parsed.hostname:
+        raise ValueError("Invalid URL: No hostname found.")
 
-    if any(hostname == origin for origin in trusted_origins):
+    # IDNA encode to prevent Unicode domain attacks
+    try:
+        ascii_hostname = idna.encode(parsed.hostname).decode("ascii")
+    except idna.IDNAError:
+        raise ValueError("Invalid hostname with unsupported characters.")
+
+    # Check hostname characters
+    if not HOSTNAME_REGEX.match(ascii_hostname):
+        raise ValueError("Hostname contains invalid characters.")
+
+    # Rebuild the URL with the normalized, IDNA-encoded hostname
+    parsed = parsed._replace(netloc=ascii_hostname)
+    url = str(urlunparse(parsed))
+
+    # Check if hostname is a trusted origin (exact match)
+    if ascii_hostname in trusted_origins:
         return url
 
     # Resolve all IP addresses for the hostname
-    ip_addresses = {result[4][0] for result in socket.getaddrinfo(hostname, None)}
-    if not ip_addresses:
-        raise ValueError(f"Unable to resolve IP address for {hostname}")
+    try:
+        ip_addresses = {res[4][0] for res in socket.getaddrinfo(ascii_hostname, None)}
+    except socket.gaierror:
+        raise ValueError(f"Unable to resolve IP address for hostname {ascii_hostname}")
 
-    # Check if all IP addresses are global
+    if not ip_addresses:
+        raise ValueError(f"No IP addresses found for {ascii_hostname}")
+
+    # Check if any resolved IP address falls into blocked ranges
     for ip in ip_addresses:
-        if is_ip_blocked(ip):
+        if _is_ip_blocked(ip):
             raise ValueError(
-                f"Access to private IP address at {hostname}: {ip} is not allowed."
+                f"Access to private IP address {ip} for hostname {ascii_hostname} is not allowed."
             )
 
     return url

autogpt_platform/backend/backend/util/settings.py

@@ -148,6 +148,16 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         "This value is then used to generate redirect URLs for OAuth flows.",
     )
 
+    media_gcs_bucket_name: str = Field(
+        default="",
+        description="The name of the Google Cloud Storage bucket for media files",
+    )
+
+    google_application_credentials: str = Field(
+        default="",
+        description="The path to the Google Cloud credentials JSON file",
+    )
+
     @field_validator("platform_base_url", "frontend_base_url")
     @classmethod
     def validate_platform_base_url(cls, v: str, info: ValidationInfo) -> str:

autogpt_platform/backend/backend/util/test.py

@@ -60,9 +60,7 @@ async def wait_execution(
     timeout: int = 20,
 ) -> Sequence[ExecutionResult]:
     async def is_execution_completed():
-        status = await AgentServer().test_get_graph_run_status(
-            graph_id, graph_exec_id, user_id
-        )
+        status = await AgentServer().test_get_graph_run_status(graph_exec_id, user_id)
         log.info(f"Execution status: {status}")
         if status == ExecutionStatus.FAILED:
             log.info("Execution failed")

autogpt_platform/backend/backend/util/text.py

@@ -0,0 +1,22 @@
+import re
+
+from jinja2 import BaseLoader
+from jinja2.sandbox import SandboxedEnvironment
+
+
+class TextFormatter:
+    def __init__(self):
+        # Create a sandboxed environment
+        self.env = SandboxedEnvironment(loader=BaseLoader(), autoescape=True)
+
+        # Clear any registered filters, tests, and globals to minimize attack surface
+        self.env.filters.clear()
+        self.env.tests.clear()
+        self.env.globals.clear()
+
+    def format_string(self, template_str: str, values=None, **kwargs) -> str:
+        # For python.format compatibility: replace all {...} with {{..}}.
+        # But avoid replacing {{...}} to {{{...}}}.
+        template_str = re.sub(r"(?<!{){[ a-zA-Z0-9_]+}", r"{\g<0>}", template_str)
+        template = self.env.from_string(template_str)
+        return template.render(values or {}, **kwargs)

autogpt_platform/backend/docker-compose.test.yaml

@@ -1,20 +1,31 @@
-version: "3"
 services:
   postgres-test:
     image: ankane/pgvector:latest
     environment:
-      - POSTGRES_USER=agpt_user
-      - POSTGRES_PASSWORD=pass123
-      - POSTGRES_DB=agpt_local
+      - POSTGRES_USER=${DB_USER}
+      - POSTGRES_PASSWORD=${DB_PASS}
+      - POSTGRES_DB=${DB_NAME}
     healthcheck:
       test: pg_isready -U $$POSTGRES_USER -d $$POSTGRES_DB
       interval: 10s
       timeout: 5s
       retries: 5
     ports:
-      - "5433:5432"
+      - "${DB_PORT}:5432"
     networks:
       - app-network-test
+  redis-test:
+    image: redis:latest
+    command: redis-server --requirepass password
+    ports:
+      - "6379:6379"
+    networks:
+      - app-network-test
+    healthcheck:
+      test: ["CMD", "redis-cli", "ping"]
+      interval: 10s
+      timeout: 5s
+      retries: 5
 
 networks:
      app-network-test:

autogpt_platform/backend/linter.py

@@ -3,6 +3,10 @@ import subprocess
 
 directory = os.path.dirname(os.path.realpath(__file__))
 
+BACKEND_DIR = "."
+LIBS_DIR = "../autogpt_libs"
+TARGET_DIRS = [BACKEND_DIR, LIBS_DIR]
+
 
 def run(*command: str) -> None:
     print(f">>>>> Running poetry run {' '.join(command)}")
@@ -11,17 +15,19 @@ def run(*command: str) -> None:
 
 def lint():
     try:
-        run("ruff", "check", ".", "--exit-zero")
-        run("isort", "--diff", "--check", "--profile", "black", ".")
-        run("black", "--diff", "--check", ".")
-        run("pyright")
+        run("ruff", "check", *TARGET_DIRS, "--exit-zero")
+        run("ruff", "format", "--diff", "--check", LIBS_DIR)
+        run("isort", "--diff", "--check", "--profile", "black", BACKEND_DIR)
+        run("black", "--diff", "--check", BACKEND_DIR)
+        run("pyright", *TARGET_DIRS)
     except subprocess.CalledProcessError as e:
         print("Lint failed, try running `poetry run format` to fix the issues: ", e)
         raise e
 
 
 def format():
-    run("ruff", "check", "--fix", ".")
-    run("isort", "--profile", "black", ".")
-    run("black", ".")
-    run("pyright", ".")
+    run("ruff", "check", "--fix", *TARGET_DIRS)
+    run("ruff", "format", LIBS_DIR)
+    run("isort", "--profile", "black", BACKEND_DIR)
+    run("black", BACKEND_DIR)
+    run("pyright", *TARGET_DIRS)

autogpt_platform/backend/migrations/20241210013740_add_indexes/migration.sql

@@ -0,0 +1,41 @@
+-- CreateIndex
+CREATE INDEX "AgentGraph_userId_isActive_idx" ON "AgentGraph"("userId", "isActive");
+
+-- CreateIndex
+CREATE INDEX "AgentGraphExecution_agentGraphId_agentGraphVersion_idx" ON "AgentGraphExecution"("agentGraphId", "agentGraphVersion");
+
+-- CreateIndex
+CREATE INDEX "AgentGraphExecution_userId_idx" ON "AgentGraphExecution"("userId");
+
+-- CreateIndex
+CREATE INDEX "AgentNode_agentGraphId_agentGraphVersion_idx" ON "AgentNode"("agentGraphId", "agentGraphVersion");
+
+-- CreateIndex
+CREATE INDEX "AgentNode_agentBlockId_idx" ON "AgentNode"("agentBlockId");
+
+-- CreateIndex
+CREATE INDEX "AgentNode_webhookId_idx" ON "AgentNode"("webhookId");
+
+-- CreateIndex
+CREATE INDEX "AgentNodeExecution_agentGraphExecutionId_idx" ON "AgentNodeExecution"("agentGraphExecutionId");
+
+-- CreateIndex
+CREATE INDEX "AgentNodeExecution_agentNodeId_idx" ON "AgentNodeExecution"("agentNodeId");
+
+-- CreateIndex
+CREATE INDEX "AgentNodeExecutionInputOutput_referencedByOutputExecId_idx" ON "AgentNodeExecutionInputOutput"("referencedByOutputExecId");
+
+-- CreateIndex
+CREATE INDEX "AgentNodeLink_agentNodeSourceId_idx" ON "AgentNodeLink"("agentNodeSourceId");
+
+-- CreateIndex
+CREATE INDEX "AgentNodeLink_agentNodeSinkId_idx" ON "AgentNodeLink"("agentNodeSinkId");
+
+-- CreateIndex
+CREATE INDEX "AnalyticsMetrics_userId_idx" ON "AnalyticsMetrics"("userId");
+
+-- CreateIndex
+CREATE INDEX "IntegrationWebhook_userId_idx" ON "IntegrationWebhook"("userId");
+
+-- CreateIndex
+CREATE INDEX "UserBlockCredit_userId_createdAt_idx" ON "UserBlockCredit"("userId", "createdAt");

autogpt_platform/backend/migrations/20241211160646_rename_credit_model_and_add_stripe_customer/migration.sql

@@ -0,0 +1,8 @@
+-- AlterTable
+ALTER TABLE "User" ADD COLUMN "stripeCustomerId" TEXT;
+
+-- AlterEnum
+ALTER TYPE "UserBlockCreditType" RENAME TO "CreditTransactionType";
+
+-- AlterTable
+ALTER TABLE "UserBlockCredit" RENAME TO "CreditTransaction";