<img width="1410" alt="image"
src="https://github.com/user-attachments/assets/bce407a2-96a1-42e9-9772-b49b8f20886c"
/>
### Changes 🏗️
Add the missing `send execution update` command on completed/update
status change for the node execution.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Screenshot attached
### Changes 🏗️
This simply adds "fal-ai/veo3" to the ``FalModel`` in the
``ai_video_generator.py`` file
Oh i also set it so veo3 also always generates videos with audio so
``generate_audio=True`` is set to true if veo3 is selected
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Test the veo3 model via Fal.ai and it should work.
### Changes 🏗️
Today openAI dropped the prices of the o3 model so this simply drops the
price from 7 to 4
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Run the platform with the new price, check the O3 model in the ai
text generator block and see its cheaper to use
Allowing depth-first execution will unlock faster processing latency and
a better sense of progress.
<img width="950" alt="image"
src="https://github.com/user-attachments/assets/e2a0e11a-8bc5-4a65-a10d-b5b6c6383354"
/>
### Changes 🏗️
* Prioritize adding a new execution over processing execution output
* Make sure to enqueue each node once when processing output instead of
draining a single node and move on.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Run company follower count finder agent.
---------
Co-authored-by: Swifty <craigswift13@gmail.com>
## Changes
- log helpful hints when metrics fail to record
- clarify API key errors in v1 router
- improve Postmark unsubscribe and webhook logs
- surface actionable feedback across integrations and store APIs
- handle Otto proxy failures with guidance
## Checklist
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan
There are a few UI bugs on the builder that this PR addresses.
<img width="554" alt="image"
src="https://github.com/user-attachments/assets/1be70197-de7e-40fe-ab11-405c145e763d"
/>
### Changes 🏗️
Fix these UI issues:
* (screenshot attached above) Key-value input width was unintentionally
maxed out due to a stale CSS rule.
* When multiple executions within the same node are running, we pick the
latest status, making one running and one completed execution displayed
as completed.
* No balance errors were executed, only displayed while at least one
node execution was triggered, while this can be done directly when the
execution request is triggered.
* Run & Stop button glitch: it's still showing as stopped when the graph
is still running, this is due to way the UI code tracks execution in the
node-level, instead of graph level.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Manual tests on the described behaviours.
This pull request introduces a comprehensive backend testing guide and
adds new tests for analytics logging and various API endpoints, focusing
on snapshot testing. It also includes corresponding snapshot files for
these tests. Below are the most significant changes:
### Documentation Updates:
* Added a detailed `TESTING.md` file to the backend, providing a guide
for running tests, snapshot testing, writing API route tests, and best
practices. It includes examples for mocking, fixtures, and CI/CD
integration.
### Analytics Logging Tests:
* Implemented tests for logging raw metrics and analytics in
`analytics_test.py`, covering success scenarios, various input values,
invalid requests, and complex nested data. These tests utilize snapshot
testing for response validation.
* Added snapshot files for analytics logging tests, including responses
for success cases, various metric values, and complex analytics data.
[[1]](diffhunk://#diff-654bc5aa1951008ec5c110a702279ef58709ee455ba049b9fa825fa60f7e3869R1-R3)
[[2]](diffhunk://#diff-e0a434b107abc71aeffb7d7989dbfd8f466b5e53f8dea25a87937ec1b885b122R1-R3)
[[3]](diffhunk://#diff-dd0bc0b72264de1a0c0d3bd0c54ad656061317f425e4de461018ca51a19171a0R1-R3)
[[4]](diffhunk://#diff-63af007073db553d04988544af46930458a768544cabd08412265e0818320d11R1-R30)
### Snapshot Files for API Endpoints:
* Added snapshot files for various API endpoint tests, such as:
- Graph-related operations (`graphs_get_single_response`,
`graphs_get_all_response`, `blocks_get_all_response`).
[[1]](diffhunk://#diff-b25dba271606530cfa428c00073d7e016184a7bb22166148ab1726b3e113dda8R1-R29)
[[2]](diffhunk://#diff-1054e58ec3094715660f55bfba1676d65b6833a81a91a08e90ad57922444d056R1-R31)
[[3]](diffhunk://#diff-cfd403ab6f3efc89188acaf993d85e6f792108d1740c7e7149eb05efb73d918dR1-R14)
- User-related operations (`auth_get_or_create_user_response`,
`auth_update_email_response`).
[[1]](diffhunk://#diff-49e65ab1eb6af4d0163a6c54ed10be621ce7336b2ab5d47d47679bfaefdb7059R1-R5)
[[2]](diffhunk://#diff-ac1216f96878bd4356454c317473654d5d5c7c180125663b80b0b45aa5ab52cbR1-R3)
- Credit-related operations (`credits_get_balance_response`,
`credits_get_auto_top_up_response`, `credits_top_up_request_response`).
[[1]](diffhunk://#diff-189488f8da5be74d80ac3fb7f84f1039a408573184293e9ba2e321d535c57cddR1-R3)
[[2]](diffhunk://#diff-ba3c4a6853793cbed24030cdccedf966d71913451ef8eb4b2c4f426ef18ed87aR1-R4)
[[3]](diffhunk://#diff-43d7daa0c82070a9b6aee88a774add8e87533e630bbccbac5a838b7a7ae56a75R1-R3)
- Graph execution and deletion (`blocks_execute_response`,
`graphs_delete_response`).
[[1]](diffhunk://#diff-a2ade7d646ad85a2801e7ff39799a925a612548a1cdd0ed99b44dd870d1465b5R1-R12)
[[2]](diffhunk://#diff-c0d1cd0a8499ee175ce3007c3a87ba5f3235ce02d38ce837560b36a44fdc4a22R1-R3)##
Summary
- add pytest-snapshot to backend dev requirements
- snapshot server route response JSONs
- mention how to update stored snapshots
## Testing
- `poetry run format`
- `poetry run test`
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] run poetry run test
---------
Co-authored-by: Claude <noreply@anthropic.com>
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
- Part of #9307
- ❗ Blocks #9541
### Changes 🏗️
Backend:
- Fix+improve `GET /library/presets` (`list_presets`) endpoint
- Fix pagination
- Add `graph_id` filter parameter
- Allow partial preset updates: `PUT /presets/{preset_id}` -> `PATCH
/presets/{preset_id}`
- Allow creating preset from graph execution through `POST /presets`
- Clean up models & DB functions
- Split `upsert_preset` into `create_preset` + `update_preset`
- Add `LibraryAgentPresetUpdatable`
- Replace `CreateLibraryAgentPresetRequest` with
`LibraryAgentPresetCreatable`
- Use `LibraryAgentPresetCreatable` as base class for
`LibraryAgentPreset`
- Remove redundant `set_is_deleted_for_library_agent(..)`
- Improve log statements
- Improve DB statements (e.g. by using unique keys where possible)
Frontend:
- Add timestamp parsing logic to library agent preset endpoints
- Brand `LibraryAgentPreset.id` + references
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] CI green
- Since these changes don't affect existing front-end functionality, no
additional testing is needed.
**Goal**: Allow parallel runs within a single node. Currently, we
prevent this to avoid unexpected ordering of the execution.
### Changes 🏗️
#### Executor changes
We decoupled the node execution output processing, which is responsible
for deciding the next executions from the node executor code.
Currently, `execute_node` does two big things:
* Runs the block’s execute(...) (which yields outputs).
* immediately enqueues the next nodes based on those outputs.
This PR makes:
* execute_node(node_exec) -> stream of (output_name, data). That purely
runs the block and yields each output as soon as it’s available.
* Move _enqueue_next_nodes into the graph executor. So the next
execution is handled serially by the graph executor to avoid concurrency
issues.
#### UI changes
The change on the executor also fixes the behavior of the execution
update to the UI We will report the execution output to the UI as soon
as it is available, not when the node execution is fully completed.
This, however, broke the bread calculation logic that assumes each
execution update will never overlap. So the change in this PR makes the
bead calculation take the overlap / duplicated execution update into
account, and simplify the overall calculation logic.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Execute this agent and observe its concurrency ordering
<img width="1424" alt="image"
src="https://github.com/user-attachments/assets/0fe8259f-9091-4ecc-b824-ce8e8819c2d2"
/>
Currently, the get_graph function, with no graph version specifier will
try to fetch the latest version, and when the graph is not owned and the
latest version is not available for listing, it will return `None`
instead of picking the latest graph version available on the store.
### Changes 🏗️
Instead of using the latest graph.version to fetch the store listing,
don't provide any version filter at all and pick up whatever available
version in the store.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] CI, existing tests
Suppose we have pint with list[list[int]] type, and we want directly
insert the a new value inside the first index of the first list e.g:
list[0][0] = X through a dynamic pin, this will be translated into
list_$_0_$_0, and the system does not currently support this.
### Changes 🏗️
Add support for nested dynamic pins for list, object, and dict.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] lots of unit tests
- [x] Tried inserting the value directly on the `value` nested field on
Google Sheets Write block.
<img width="371" alt="image"
src="https://github.com/user-attachments/assets/0a5e7213-b0e0-4fce-9e89-b39f7a583582"
/>
Now, SendWebRequestBlock can upload files. To make this work, we also
need to improve the UI rendering on the key-value pair input so that it
can also render media/file upload.
### Changes 🏗️
* Add file multipart upload support for SendWebRequestBlock
* Improve key-value input UI rendering to allow rendering any types as a
normal input block (it was only string & number).
<img width="381" alt="image"
src="https://github.com/user-attachments/assets/b41d778d-8f9d-4aec-95b6-0b32bef50e89"
/>
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Test running http request block, othe key-value pair input block
<!-- Clearly explain the need for these changes: -->
This PR adds a new internal block, **AI Image Editor**, which enables
**text-based image editing** via BlackForest Labs’ Flux Kontext models
on Replicate. This block allows users to input a prompt and optionally a
reference image, and returns a transformed image URL. It supports two
model variants (Pro and Max), with different cost tiers. This
functionality will enhance multimedia capabilities across internal agent
workflows and support richer AI-powered image manipulation.
---
### Changes 🏗️
* Added `FluxKontextBlock` in `backend/blocks/flux_kontext.py`
* Uses `ReplicateClient` to call Flux Kontext Pro or Max models
* Supports inputs for `prompt`, `input_image`, `aspect_ratio`, `seed`,
and `model`
* Outputs transformed image URL or error
* Added credit pricing logic for Flux Kontext models to
`block_cost_config.py`:
* Pro: 10 credits
* Max: 20 credits
* Added documentation for the new block at
`docs/content/platform/blocks/flux_kontext.md`
* Updated block index at `docs/content/platform/blocks/blocks.md` to
include Flux Kontext
---
### Checklist 📋
#### For code changes:
* [x] I have clearly listed my changes in the PR description
* [x] I have made a test plan
* [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
* [x] Prompt-only input generates an image
* [x] Prompt with image applies edit correctly
* [x] Image respects specified aspect ratio
* [x] Invalid image URL returns helpful error
* [x] Using the same seed gives consistent output
* [x] Output chaining works: result URI can be used in downstream blocks
* [x] Output from Max model shows higher fidelity than Pro
<details>
<summary>Example test plan</summary>
* [x] Create from scratch and execute an agent using Flux Kontext with
at least 3 blocks
* [x] Import agent with Flux Kontext from file upload, and confirm
execution
* [x] Upload agent (with Flux Kontext block) to marketplace (internal
test)
* [x] Import agent from marketplace and confirm correct execution
* [x] Edit agent with Flux Kontext block from monitor and confirm output
</details>
#### For configuration changes:
* [x] `.env.example` is updated or already compatible with my changes
* [x] `docker-compose.yml` is updated or already compatible with my
changes
* [x] I have included a list of my configuration changes in the PR
description (under **Changes**)
* No new environment variables or services introduced
<details>
<summary>Examples of configuration changes</summary>
* N/A
</details>
---------
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
### Changes 🏗️
This PR adds `Run 10 agents` step to wallet tasks that can be done by
running any agents 10 times either from Library or Builder (onboarding
agent run also counts).
- Merge `Finish onboarding` and `See results` steps into one in the
wallet
- User is redirected directly to onboarding agent runs in Library after
congrats screen
- Add `RUN_AGENTS` step and `agentRuns` integer to schema and related
migration
- Running agent from Library and Builder increments `agentRuns`
- Open NPS survey popup when 10 agents are run
- Fix resuming onboarding on login when unfinished
- Remove no longer needed `get-results.mp4` tutorial video
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Onboarding can be completed and proper reward is awarded
- [x] `Run 10 agents` can be completed and reward is awarded
- [x] When unning different agents and the same agent
- [x] Running from library and builder counts
- [x] Onboarding is resumed to last finished step on login
This makes button on the marketplace listing page show `See runs` if
user has an agent in the library.
### Changes 🏗️
- Remove `/` from the related endpoint
- Use `active_version_id` instead of `store_listing_version_id` to check
for the library agent
- Fix `get_store_agent_details`
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- Log in and pick an agent that has never been in user library
- [x] Button says `Add to library`
- Add the agent and return to the listing page
- [x] Button says `See runs`
- Remove agent from library
- [x] Button says `Add to library`
- Add agent again
- [x] Button says `See runs`
---------
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
- Resolves#9752
- Follow-up fix to #9940
### Changes 🏗️
- `GRAPH_EXECUTION_INCLUDE` ->
`graph_execution_include(include_block_ids)`
- Add `get_io_block_ids()` and `get_webhook_block_ids()` to
`backend.data.blocks`
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [ ] I have tested my changes according to the test plan:
- [ ] Payload for webhook-triggered runs is shown on
`/library/agents/[id]`
# Query Optimization for AgentNodeExecution Tables
## Overview
This PR describes the database index optimizations applied to improve
the performance of slow queries in the AutoGPT platform backend.
## Problem Analysis
The following queries were identified as consuming significant database
resources:
### 1. Complex Filtering Query (19.3% of total time)
```sql
SELECT ... FROM "AgentNodeExecution"
WHERE "agentNodeId" = $1
AND "agentGraphExecutionId" = $2
AND "executionStatus" = $3
AND "id" NOT IN (
SELECT "referencedByInputExecId"
FROM "AgentNodeExecutionInputOutput"
WHERE "name" = $4 AND "referencedByInputExecId" IS NOT NULL
)
ORDER BY "addedTime" ASC
```
### 2. Multi-table JOIN Query (8.9% of total time)
```sql
SELECT ... FROM "AgentNodeExecution"
LEFT JOIN "AgentNode" ON ...
LEFT JOIN "AgentBlock" ON ...
WHERE "AgentBlock"."id" IN (...)
AND "executionStatus" != $11
AND "agentGraphExecutionId" IN (...)
ORDER BY "queuedTime" DESC, "addedTime" DESC
```
### 3. Bulk Graph Execution Queries (multiple variations, ~10% combined)
Multiple queries filtering by `agentGraphExecutionId` with various
ordering requirements.
## Optimization Strategy
### 1. Composite Indexes for AgentNodeExecution
Set the following composite indexes to the `AgentNodeExecution` model:
```prisma
@@index([agentGraphExecutionId, agentNodeId, executionStatus])
@@index([addedTime, queuedTime])
```
#### Benefits:
- **Index 1**: Covers the exact WHERE clause of the complex filtering
query, allowing index-only scans
- **Index 2**: Optimizes queries filtering by graph execution and status
- **Index 3**: Supports efficient sorting when filtering by graph
execution
- **Index 4**: Optimizes ORDER BY operations on time fields
### 2. Composite Index for AgentNodeExecutionInputOutput
Added the following composite index:
```prisma
// Input and Output pin names are unique for each AgentNodeExecution.
@@unique([referencedByInputExecId, referencedByOutputExecId, name])
@@index([referencedByOutputExecId])
// Composite index for `upsert_execution_input`.
@@index([name, time])
```
#### Benefits:
- Dramatically improves the NOT IN subquery performance in Query 1
- Allows the database to use an index scan instead of a full table scan
- Reduces the subquery execution time from O(n) to O(log n)
## Expected Performance Improvements
1. **Query 1 (19.3% of total time)**:
- Expected improvement: 80-90% reduction in execution time
- The composite index on `[agentNodeId, agentGraphExecutionId,
executionStatus]` will allow index-only scans
- The subquery will benefit from the new index on
`AgentNodeExecutionInputOutput`
2. **Query 2 (8.9% of total time)**:
- Expected improvement: 50-70% reduction in execution time
- The `[agentGraphExecutionId, executionStatus]` index will reduce the
initial filtering cost
3. **Bulk Queries (10% combined)**:
- Expected improvement: 60-80% reduction in execution time
- Composite indexes including time fields will optimize sorting
operations
## Migration Considerations
1. **Index Creation Time**: Creating these indexes on existing large
tables may take time
2. **Storage Impact**: Each index requires additional storage space
3. **Write Performance**: Slight decrease in INSERT/UPDATE performance
due to index maintenance
## Additional Optimizations
### NotificationEvent Table Index
Added index for notification batch queries:
```prisma
@@index([userNotificationBatchId])
```
This optimizes the query:
```sql
SELECT ... FROM "NotificationEvent"
WHERE "userNotificationBatchId" IN (...)
```
#### Benefits:
- Eliminates full table scans when filtering by batch ID
- Improves query performance from O(n) to O(log n)
- Particularly beneficial for users with many notification events
## Future Optimizations
Consider these additional optimizations if needed:
1. Partitioning `AgentNodeExecution` table by `createdAt` or
`agentGraphExecutionId`
2. Implementing materialized views for frequently accessed aggregate
data
3. Adding covering indexes for specific query patterns
4. Implementing query result caching at the application level
---------
Co-authored-by: Zamil Majdy <zamil.majdy@agpt.co>
- Resolves#10024
Caching the repeated DB calls by the graph lifecycle hooks significantly
speeds up graph update/create calls with many authenticated blocks
(~300ms saved per authenticated block)
### Changes 🏗️
- Add and use `IntegrationCredentialsManager.cached_getter(user_id)` in
lifecycle hooks
- Split `refresh_if_needed(..)` method out of
`IntegrationCredentialsManager.get(..)`
- Simplify interface of lifecycle hooks: change `get_credentials`
parameter to `user_id`
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Save a graph with nodes with credentials
This pull request refines the handling of `input_data.content` and
improves error message formatting in the `run` method of `mem0.py`. The
changes enhance robustness and clarity in the code.
### Handling `input_data.content`:
* Updated the `run` method to handle `Content` objects explicitly,
ensuring proper formatting of messages when `input_data.content` is of
type `Content`. Additionally, non-standard types are now converted to
strings for consistent handling.
(`[autogpt_platform/backend/backend/blocks/mem0.pyR127-R130](diffhunk://#diff-d7abf8c3299388129480b6a9be78438fe7e0fbe239da630ebb486ad99c80dd24R127-R130)`)
### Error message formatting:
* Simplified the error message formatting by removing the unnecessary
`object=` keyword in the `str()` conversion of exceptions.
(`[autogpt_platform/backend/backend/blocks/mem0.pyL155-R157](diffhunk://#diff-d7abf8c3299388129480b6a9be78438fe7e0fbe239da630ebb486ad99c80dd24L155-R157)`)
## Summary
- fix AddMemoryBlock so `Content` input uses the underlying string
- improve error handling in Mem0 AddMemoryBlock
## Testing
- `ruff check autogpt_platform/backend/backend/blocks/mem0.py`
- `pre-commit run --files
autogpt_platform/backend/backend/blocks/mem0.py` *(fails: unable to
fetch remote hooks)*
- `poetry run pytest -k AddMemoryBlock -q` *(fails: Error 111 connecting
to localhost:6379)*
Checklist 📋
For code changes:
I have clearly listed my changes in the PR description
I have made a test plan
I have tested my changes according to the test plan:
Payload for webhook-triggered runs is shown on /library/agents/[id]
### Changes 🏗️
Keep the original URL when an HTTP error occurs in
`SendWebRequestBlock`.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Test sending POST request on a web that doesn't support POST
request using `SendWebRequestBlock`.
The executor can sometimes become dangling due to the executor stopping
executing messages but the process is not fully killed. This PR avoids
such a scenario by simply keeping retrying it.
### Changes 🏗️
Introduced continuous_retry decorator and use it to executor message
consumption/
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Run executor service and execute some agents.
Makes all optional fields on `Credentials` models actually optional, and
sets `exclude_none=True` on the corresponding `model_dump`.
This is a hotfix: after running the `aryshare-revid` branch on the dev
deployment, there is some data in the DB that isn't valid for the
`UserIntegrations` model on the `dev` branch (see
[here](https://github.com/Significant-Gravitas/AutoGPT/pull/9946#discussion_r2098428575)).
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] This fix worked on the `aryshare-revid` branch:
52b6d9696b
- Resolves#9987
### Changes 🏗️
- Split `pin_url(..)` out of `validate_url(..)` and call
`extra_url_validator` in between
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] GitHub Read Pull Request Block works with "Include PR Changes"
enabled
Resolves#9947
### Changes 🏗️
Backend:
- Send a graph execution update after terminating a run
- Don't wipe the graph execution stats when not passed in to `update_graph_execution_stats`
Frontend:
- Don't hide the output of stopped runs
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- Go to `/library/agents/[id]`
- Run an agent that takes a while (long enough to click stop and see the effect)
- Hit stop after it has executed a few nodes
- [x] -> run status should change to "Stopped"
- [x] -> run stats (steps, duration, cost) should stay the same or increase only one last time
- [x] -> output so far should be visible
- [x] -> shown information should stay the same after refreshing the page
---
Co-authored-by: Krzysztof Czerwinski <34861343+kcze@users.noreply.github.com>
I am disabling all the Twitter and Todoist blocks whose OAuth is not
configured.
> I have already checked it locally. When OAuth is not set, the blocks
do not appear in the block menu
Github Blocks use an URL transformer passed to `Requests` to convert web
URLs to the API URLs. This doesn't always work with the anti-SSRF URL
pinning mechanism that was implemented in #8531.
### Changes 🏗️
In `Requests.request(..)`:
- Apply `validate_url` *after* `extra_url_validator`, to prevent
mismatch between `pinned_url` and `original_hostname`
- Simplify logic & add clarifying comments
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Tested the github blocks that had the issue
---------
Co-authored-by: Reinier van der Leer <pwuts@agpt.co>
The changes in this PR are to add Llama API support.
### Changes 🏗️
We add both backend and frontend support.
**Backend**:
- Add llama_api provider
- Include models supported by Llama API along with configs
- llm_call
- credential store and llama_api_key field in Settings
**Frontend**:
- Llama API as a type
- Credentials input and provider for Llama API
### Checklist 📋
#### For code changes:
- [X] I have clearly listed my changes in the PR description
- [X] I have tested my changes according to the test plan:
**Test Plan**:
<details>
<summary>AI Text Generator</summary>
- [X] Start-up backend and frontend:
- Start backend with Docker services: `docker compose up -d --build`
- Start frontend: `npm install && npm run dev`
- By visiting http://localhost:3000/, test inference and structured
outputs
- [X] Create from scratch
- [X] Request for Llama API Credentials
<img width="2015" alt="image"
src="https://github.com/user-attachments/assets/3dede402-3718-4441-9327-ecab25c63ebf"
/>
- [X] Execute an agent with at least 3 blocks
<img width="2026" alt="image"
src="https://github.com/user-attachments/assets/59d6d56b-2ccc-4af5-b511-4af312c3f7f8"
/>
- [X] Confirm it executes correctly
</details>
<details>
<summary>Structured Response Generator</summary>
- [X] Start-up backend and frontend:
- Start backend with Docker services: `docker compose up -d --build`
- Start frontend: `npm install && npm run dev`
- By visiting http://localhost:3000/, test inference and structured
outputs
- [X] Create from scratch
- [X] Execute an agent
<img width="2023" alt="image"
src="https://github.com/user-attachments/assets/d1107638-bf1b-45b1-a296-1e0fac29525b"
/>
- [X] Confirm it executes correctly
</details>
---------
Co-authored-by: Nicholas Tindle <nicholas.tindle@agpt.co>
> Log entry with size 865.8K exceeds maximum size of 256.0K
Some logs are just too large.
### Changes 🏗️
Truncate logging on NotificationManager and LLMBlocks
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Existing CI
<!-- Clearly explain the need for these changes: -->
### Changes 🏗️
This pull request includes a small change to the `get_my_agents`
function in `autogpt_platform/backend/backend/server/v2/store/db.py`.
The change updates the sorting order for retrieving library agents to
use the `updatedAt` field instead of `agentGraphVersion`.
This aligns with the later sorting that is applied to the fetched page
in the frontend.
<!-- Concisely describe all of the changes made in this pull request:
-->
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [ ] ...
<details>
<summary>Example test plan</summary>
- [ ] Create from scratch and execute an agent with at least 3 blocks
- [ ] Import an agent from file upload, and confirm it executes
correctly
- [ ] Upload agent to marketplace
- [ ] Import an agent from marketplace and confirm it executes correctly
- [ ] Edit an agent from monitor, and confirm it executes correctly
</details>
#### For configuration changes:
- [x] `.env.example` is updated or already compatible with my changes
- [x] `docker-compose.yml` is updated or already compatible with my
changes
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)
<details>
<summary>Examples of configuration changes</summary>
- Changing ports
- Adding new services that need to communicate with each other
- Secrets or environment variable changes
- New or infrastructure changes such as databases
</details>
<!-- Clearly explain the need for these changes: -->
John thinks an hourly email is a bit much; I'm inclined to agree.
### Changes 🏗️
<!-- Concisely describe all of the changes made in this pull request:
-->
swaps the time for dealing the batch for the agent runs from one hour to
one day
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] No testing done
We want to add support for reading + writing events for google calendar
so agents can do cool stuff with that!
### Changes 🏗️
* Add support for google calendar blocks
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Run manual tests of each block
- [x] Build and run automatic tests
- Follow-up fix for #9862
### Changes 🏗️
- Rename the stored `data` input field to `inputs` on all Agent Executor
nodes in the DB
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Dry-run the query in Supabase to verify that the data operation
works
- [x] CI
```
2025-05-09 11:54:15,171 ERROR Error executing graph 954e6fc8-9c90-46fa-be5b-4063eb519ec7: Block ID AIMusicGeneratorBlock error: 44f6c8ad-d75c-4ae1-8209-aad1c0326928 is already in use
```
### Changes 🏗️
This PR avoids the use of global variables messing up with the way
`load_all_blocks` is cached.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] CI
Currently, there is no guarantee that an error will be reported right
away. And late execution is a serious issue that needs to be addressed
quickly
### Changes 🏗️
Provided a direct alert when late execution occurs.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
- [x] Manual run on the late executions job on artificially created late
executions.
This is a follow-up to
https://github.com/Significant-Gravitas/AutoGPT/pull/9903
The continued graph execution restarted all the execution stats from
zero, making the execution stats misleading.
### Changes 🏗️
Continue the execution stats when continuing the graph execution.
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Existing tests, manual graph run with the graph execution aborted
midway.
Some of the code paths in the notification & scheduler service were
synchronous HTTP calls that execute a long-running job that blocks. This
makes the service threads busy waiting.
### Changes 🏗️
* Remove queue_notification API
* Remove DTO
* Move heavy tasks intothe executor
<!-- Concisely describe all of the changes made in this pull request:
-->
### Checklist 📋
#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
<!-- Put your test plan here: -->
- [x] Manually executing notification service jobs through the scheduler
API
Zamil Majdy