feat: show document artifact after generating report #658
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🦋 Changeset detectedLatest commit: b1e59f6 The changes in this PR will be included in the next version bump. This PR includes changesets to release 4 packages
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""" WalkthroughThis change updates both Python and TypeScript deep research workflows to emit a document artifact event immediately after generating a report, ensuring the artifact is displayed without delay. It also updates related dependencies, imports additional styles, and modifies ESLint configuration for the server package. Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Workflow (Python/TS)
participant Artifact Event Stream
User->>Workflow (Python/TS): Request report generation
Workflow (Python/TS)->>Workflow (Python/TS): Generate report (streaming or non-streaming)
Workflow (Python/TS)->>User: Stream report content (incremental events)
Workflow (Python/TS)->>Artifact Event Stream: Emit document artifact event (full report)
Artifact Event Stream->>User: Display document artifact immediately
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packages/server/next/app/components/ui/chat/chat-message-content.tsx
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packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py
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Actionable comments posted: 1
🧹 Nitpick comments (2)
packages/server/project-config/eslint.config.mjs (1)
21-21: Question: Is the empty-object-type rule disablement needed globally?Turning off
@typescript-eslint/no-empty-object-typefor the entire project may hide unintended uses of empty object types. Consider scoping this override to only the files or patterns that actually require it, or using inline// eslint-disable-next-linecomments where necessary to minimize global impact.packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py (1)
381-382: Move the import to the top of the file for consistency.The
AsyncGeneratorimport should be moved to the top-level imports section for better code organization and consistency with Python conventions.+from collections.abc import AsyncGenerator import logging import os import uuid from typing import List, Literal, Optional ... - from collections.abc import AsyncGenerator
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.changeset/tame-wolves-obey.md(1 hunks)packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py(2 hunks)packages/create-llama/templates/components/use-cases/typescript/deep_research/src/app/workflow.ts(2 hunks)packages/server/next/app/layout.tsx(1 hunks)packages/server/package.json(1 hunks)packages/server/project-config/eslint.config.mjs(1 hunks)packages/server/project-config/package.json(1 hunks)
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packages/create-llama/templates/components/use-cases/typescript/deep_research/src/app/workflow.ts (1)
packages/server/src/utils/events.ts (1)
artifactEvent(121-124)
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🔇 Additional comments (9)
packages/server/project-config/package.json (1)
44-44: LGTM: Dependency update supports new artifact features.The version bump from 0.5.2 to 0.5.5 for
@llamaindex/chat-uialigns with the feature addition and is consistent across packages.packages/server/package.json (1)
68-68: LGTM: Consistent dependency update.The version update maintains consistency with the project-config package and supports the new artifact event functionality.
packages/server/next/app/layout.tsx (1)
4-4: LGTM: Added necessary styles for artifact rendering.The editor.css import is appropriately placed and necessary to support the document artifact display functionality.
.changeset/tame-wolves-obey.md (1)
1-7: LGTM: Well-documented changeset.The changeset properly documents the feature addition with appropriate patch-level versioning and clear description.
packages/create-llama/templates/components/use-cases/typescript/deep_research/src/app/workflow.ts (2)
1-1: LGTM: Proper import addition for artifact functionality.The
artifactEventimport is correctly added to support the new document artifact feature.
342-357: LGTM: Well-implemented artifact event emission.The implementation correctly:
- Sends the artifact event after streaming completion but before the final stop event
- Captures the complete response content
- Uses proper data structure with appropriate metadata (title, content, type)
- Provides immediate visibility of the generated document as intended
The timing and data structure align perfectly with the PR objective to show document artifacts after report generation.
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py (3)
26-36: LGTM! Import additions support the new artifact functionality.The new imports are correctly added to support the artifact emission feature. The imports include all necessary classes for creating and emitting document artifacts after report generation.
400-412: LGTM! Artifact emission correctly implements the PR objective.The artifact creation and emission logic correctly implements the feature to show document artifacts after generating reports. The structure includes all necessary metadata and the content is properly set to the generated report text.
415-415:✅ Verification successful
Verify the impact of returning empty string instead of the report content.
The change from returning the response object to returning an empty string could be a breaking change if downstream code expects the actual report content in the StopEvent result.
🏁 Script executed:
#!/bin/bash # Description: Search for usage of StopEvent result from DeepResearchWorkflow to verify impact # Expected: Find code that depends on the StopEvent result containing the report content # Search for workflow usage and StopEvent handling rg -A 10 -B 5 "DeepResearchWorkflow.*run\|StopEvent.*result" --type py # Search for any code that processes the workflow result rg -A 5 "\.run\(" --type py | rg -A 5 -B 5 "result"Length of output: 2466
No downstream dependencies on DeepResearchWorkflow’s StopEvent result detected
I searched the entire codebase and found no references to
DeepResearchWorkflowor handling of itsStopEvent.result. Since this is a template file (used only when scaffolding new projects) and nothing in our repo consumes that return value, returning an empty string here won’t break any existing code.
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py
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🧹 Nitpick comments (1)
python/llama-index-server/llama_index/server/models/artifacts.py (1)
3-3: Remove unused importDict.
Dictis imported but not used anywhere in this module.Apply this diff:
-from typing import Dict, List, Literal, Optional, Union +from typing import List, Literal, Optional, Union🧰 Tools
🪛 Ruff (0.11.9)
3-3:
typing.Dictimported but unusedRemove unused import:
typing.Dict(F401)
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python/llama-index-server/llama_index/server/models/artifacts.py (1)
packages/server/src/utils/events.ts (1)
DocumentArtifactData(107-112)
🪛 Ruff (0.11.9)
python/llama-index-server/llama_index/server/models/artifacts.py
3-3: typing.Dict imported but unused
Remove unused import: typing.Dict
(F401)
🪛 Pylint (3.3.7)
python/llama-index-server/llama_index/server/models/artifacts.py
[refactor] 24-24: Too few public methods (0/2)
(R0903)
[refactor] 29-29: Too few public methods (0/2)
(R0903)
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🔇 Additional comments (1)
python/llama-index-server/llama_index/server/models/artifacts.py (1)
33-33: Ensure new model is exported.
Verify thatDocumentArtifactSourceis added topython/llama-index-server/llama_index/server/models/__init__.pyso it’s publicly accessible.
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♻️ Duplicate comments (1)
python/llama-index-server/llama_index/server/utils/stream.py (1)
28-40: Use more specific type checking for better type safety.The
isinstance(res, AsyncGenerator)check was flagged in past reviews as not robust enough. It should check against the specific LlamaIndex type for better type safety.- if isinstance(res, AsyncGenerator): + if isinstance(res, CompletionResponseAsyncGen):This ensures we're specifically handling LlamaIndex's streaming response type rather than any generic async generator.
🧹 Nitpick comments (1)
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py (1)
4-4: Remove unused import.The
AsyncGeneratorimport is not used in this file since the streaming logic has been moved to the utility function.-from typing import List, Literal, Optional, AsyncGenerator +from typing import List, Literal, Optional🧰 Tools
🪛 Ruff (0.11.9)
4-4:
typing.AsyncGeneratorimported but unusedRemove unused import:
typing.AsyncGenerator(F401)
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packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py (4)
python/llama-index-server/llama_index/server/models/artifacts.py (5)
ArtifactEvent(58-66)ArtifactType(13-15)Artifact(36-55)DocumentArtifactData(29-33)DocumentArtifactSource(24-26)python/llama-index-server/llama_index/server/models/chat.py (1)
ChatRequest(29-44)python/llama-index-server/llama_index/server/models/source_nodes.py (1)
SourceNodesEvent(10-22)python/llama-index-server/llama_index/server/utils/stream.py (1)
handle_llm_response_stream(10-45)
🪛 Ruff (0.11.9)
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py
4-4: typing.AsyncGenerator imported but unused
Remove unused import: typing.AsyncGenerator
(F401)
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🔇 Additional comments (5)
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py (4)
26-37: Well-organized imports for artifact functionality.The new imports are properly structured and include all necessary classes for creating and emitting document artifacts.
380-380: Good use of the utility function for unified response handling.Using
handle_llm_response_streamprovides a clean abstraction for handling both streaming and non-streaming responses, improving code maintainability.
382-400: Perfect implementation of artifact event creation.This implementation exactly matches the pattern suggested by Marcus in the past review comments, creating a document artifact with proper metadata and source references.
403-403: Appropriate return value change.Returning an empty string is consistent with the new approach where the actual content is delivered via the artifact event rather than the workflow result.
python/llama-index-server/llama_index/server/utils/stream.py (1)
10-45: Well-designed utility function with proper documentation.The function provides a clean abstraction for handling both streaming and non-streaming responses, with good documentation and error handling through the
chunk.delta or ""pattern.
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Actionable comments posted: 0
🧹 Nitpick comments (1)
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py (1)
4-4: Remove unused import.The
AsyncGeneratorimport is not directly used in this file since the type checking is handled internally by thewrite_response_to_streamutility function.-from typing import List, Literal, Optional, AsyncGenerator +from typing import List, Literal, Optional🧰 Tools
🪛 Ruff (0.11.9)
4-4:
typing.AsyncGeneratorimported but unusedRemove unused import:
typing.AsyncGenerator(F401)
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packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py(3 hunks)python/llama-index-server/llama_index/server/utils/stream.py(1 hunks)
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🧬 Code Graph Analysis (1)
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py (3)
python/llama-index-server/llama_index/server/models/artifacts.py (5)
ArtifactEvent(58-66)ArtifactType(13-15)Artifact(36-55)DocumentArtifactData(29-33)DocumentArtifactSource(24-26)python/llama-index-server/llama_index/server/models/source_nodes.py (1)
SourceNodesEvent(10-22)python/llama-index-server/llama_index/server/utils/stream.py (1)
write_response_to_stream(10-45)
🪛 Ruff (0.11.9)
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py
4-4: typing.AsyncGenerator imported but unused
Remove unused import: typing.AsyncGenerator
(F401)
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🔇 Additional comments (3)
packages/create-llama/templates/components/use-cases/python/deep_research/workflow.py (3)
26-37: Well-structured imports for artifact functionality.The imports are correctly organized and include all the necessary components for creating and emitting document artifacts. The addition of the
write_response_to_streamutility function import aligns with the pattern of abstracting streaming complexity.
380-401: Excellent implementation of artifact event emission.This implementation perfectly follows the pattern suggested in previous reviews by @marcusschiesser. The code correctly:
- Uses the
write_response_to_streamutility to handle both streaming and non-streaming responses- Creates an
ArtifactEventwith proper document artifact structure- Includes all required metadata (timestamp, title, content, type, sources)
- Maps context nodes to document sources appropriately
The abstraction of response handling complexity allows the workflow to focus on the business logic of creating and emitting the artifact.
403-403: Appropriate return value change.Returning an empty string makes sense since the actual response content is now handled through the stream and artifact event, maintaining clean separation of concerns.
Summary by CodeRabbit
New Features
Style
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