Feature: Simplify app code using LlamaIndexServer #529
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- Removed FastAPI specific environment variables from `getFrameworkEnvs`. - Updated logging to use `picocolors` for better visibility. - Enhanced condition checks for vector database settings. - Updated dependencies in `pyproject.toml` and improved settings initialization in FastAPI app. - Added observability parameter to the Python template installation function. - Cleaned up unused console logs in question handling.
🦋 Changeset detectedLatest commit: aa66e09 The changes in this PR will be included in the next version bump. This PR includes changesets to release 1 package
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WalkthroughThis pull request implements extensive changes across workflow configurations, application setup, testing scripts, helper modules, and new feature implementations. It adds specific environment variables for GitHub Actions, refines conditional logic in app creation and testing, enhances installation functions and type definitions in helper files, and introduces new workflows for agentic RAG, deep research, and financial reports in both Python and TypeScript. Additionally, new FastAPI and Next.js applications, along with vectordb integration files, are introduced, and several configuration files and documentation templates are added. Changes
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templates/components/vectordbs/llamaindexserver/llamacloud/python/generate.py
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templates/types/llamaindexserver/fastapi/app/index.py (1)
16-29:⚠️ Potential issueAdd create_if_missing parameter and improve error handling
The function lacks the
create_if_missingparameter that's used in the generate.py file, and there's no error handling for potential issues when loading the index.-def get_index(config: IndexConfig = None): +def get_index(config: IndexConfig = None, create_if_missing: bool = False): + """ + Get an index from storage or create a new one if specified. + + Args: + config: Index configuration (defaults to IndexConfig()) + create_if_missing: Whether to create a new index if it doesn't exist + + Returns: + The loaded index, a new index if create_if_missing is True, or None + + Raises: + Exception: If there's an error loading the index + """ if config is None: config = IndexConfig() storage_dir = config.storage_dir # check if storage already exists if not os.path.exists(storage_dir): + if create_if_missing: + logger.info(f"Creating new index in {storage_dir}...") + from llama_index.core.indices import VectorStoreIndex + index = VectorStoreIndex([]) # Empty index + index.storage_context.persist(storage_dir) + logger.info(f"Created empty index in {storage_dir}") + return index return None # load the existing index logger.info(f"Loading index from {storage_dir}...") - storage_context = get_storage_context(storage_dir) - index = load_index_from_storage(storage_context) - logger.info(f"Finished loading index from {storage_dir}") - return index + try: + storage_context = get_storage_context(storage_dir) + index = load_index_from_storage(storage_context) + logger.info(f"Finished loading index from {storage_dir}") + return index + except Exception as e: + logger.error(f"Error loading index from {storage_dir}: {e}") + raise
🧹 Nitpick comments (28)
templates/components/workflows/python/agentic_rag/workflow.py (2)
9-19: Function implementation is good but could use environment variable for model name.The implementation follows the pattern used in other workflow components with proper error handling. However, the OpenAI model is hardcoded as "gpt-4o-mini" while other components use environment variables for model configuration.
Consider using an environment variable for the model name to maintain consistency with the settings in
settings.py:- return AgentWorkflow.from_tools_or_functions( - tools_or_functions=[query_tool], - llm=OpenAI(model="gpt-4o-mini"), - system_prompt=os.getenv("SYSTEM_PROMPT", "You are a helpful assistant."), - ) + return AgentWorkflow.from_tools_or_functions( + tools_or_functions=[query_tool], + llm=OpenAI(model=os.getenv("MODEL", "gpt-4o-mini")), + system_prompt=os.getenv("SYSTEM_PROMPT", "You are a helpful assistant."), + )
11-14: Consider using ValueError for consistency.Other workflow components (
deep_researchandfinancial_report) useValueErrorfor similar error cases, while this implementation usesRuntimeError.- if query_tool is None: - raise RuntimeError( - "Index not found! Please run `poetry run generate` to index the data first." - ) + if query_tool is None: + raise ValueError( + "Index not found! Please run `poetry run generate` to index the data first." + )templates/types/llamaindexserver/fastapi/app/settings.py (1)
8-17: Consider handling missing OpenAI API key.The OpenAI client will fail if the OPENAI_API_KEY environment variable is not set. Consider adding a check for this.
def init_settings(): + if not os.getenv("OPENAI_API_KEY"): + raise ValueError( + "OPENAI_API_KEY environment variable is required but not set." + ) + Settings.llm = OpenAI( model=os.getenv("MODEL", "gpt-4o-mini"), temperature=os.getenv("LLM_TEMPERATURE", 0.5), max_tokens=os.getenv("LLM_MAX_TOKENS", 1000), ) Settings.embed_model = OpenAIEmbedding( model=os.getenv("EMBEDDING_MODEL", "text-embedding-3-small"), dimensions=os.getenv("EMBEDDING_DIMENSIONS", 1024), )templates/types/llamaindexserver/fastapi/main.py (2)
29-31: Consider moving global initialization inside a function.Loading environment variables and initializing settings at the module level can make testing difficult. Consider moving this initialization inside a function that can be called when needed.
-load_dotenv() -init_settings() -app = create_app() +def initialize_app(): + load_dotenv() + init_settings() + return create_app() + + +app = initialize_app()
39-42: Using subprocess.run to execute shell commands.The code uses
subprocess.runto execute shell commands. While this is generally safe with fixed commands like "fastapi", consider using Python's built-in libraries for running the FastAPI server for better error handling and control.- if env == "dev": - subprocess.run(["fastapi", "dev", "--host", app_host, "--port", app_port]) - else: - subprocess.run(["fastapi", "run", "--host", app_host, "--port", app_port]) + import uvicorn + + if env == "dev": + # For development, you might want to use reload=True + uvicorn.run("main:app", host=app_host, port=int(app_port), reload=True) + else: + uvicorn.run("main:app", host=app_host, port=int(app_port))Note: This approach assumes the
main.pyfile is in the Python path. You may need to adjust the import path accordingly.templates/components/vectordbs/llamaindexserver/llamacloud/python/generate.py (3)
1-14: Consider improving import organization with docstring documentationThe import organization is functional with the flake8 noqa directive, but consider adding a module docstring to explain the purpose of this script and its relationship to the LlamaCloud service.
# flake8: noqa: E402 +""" +This module generates a data source for LlamaCloud by initializing settings +and creating an index if it doesn't exist, then loading it to LlamaCloud. +""" from dotenv import load_dotenv load_dotenv() import logging from app.index import get_index from app.settings import init_settings from llama_index.server.services.llamacloud.generate import ( load_to_llamacloud, )
19-28: Add docstring togenerate_datasource()functionThe function would benefit from a docstring explaining its purpose, behavior, and potential exceptions.
def generate_datasource(): + """ + Generate and load a data source to LlamaCloud. + + Initializes application settings, retrieves or creates an index, + and loads it to LlamaCloud. + + Raises: + ValueError: If the index cannot be found or created. + """ init_settings() logger.info("Generate index for the provided data") index = get_index(create_if_missing=True) if index is None: raise ValueError("Index not found and could not be created") load_to_llamacloud(index, logger=logger)
27-27: Consider error handling for load_to_llamacloud operationThe function loads the index to LlamaCloud but doesn't handle potential exceptions that might occur during this operation.
- load_to_llamacloud(index, logger=logger) + try: + load_to_llamacloud(index, logger=logger) + logger.info("Successfully loaded index to LlamaCloud") + except Exception as e: + logger.error(f"Failed to load index to LlamaCloud: {e}") + raisetemplates/types/llamaindexserver/fastapi/generate.py (1)
1-35: Add main block to make the script executableConsider adding a main block to make the script runnable as a standalone program.
def generate_datasource(): # ... existing function implementation ... logger.info(f"Finished creating new index. Stored in {storage_dir}") + + +if __name__ == "__main__": + generate_datasource()templates/types/llamaindexserver/fastapi/Dockerfile (2)
1-26: Enhance Dockerfile with security and operational best practicesThe Dockerfile would benefit from security enhancements (using a non-root user), healthcheck, volume for persistent data, and clearer environment variable handling.
FROM python:3.11 AS build WORKDIR /app ENV PYTHONPATH=/app # Install Poetry RUN curl -sSL https://install.python-poetry.org | POETRY_HOME=/opt/poetry python && \ cd /usr/local/bin && \ ln -s /opt/poetry/bin/poetry && \ poetry config virtualenvs.create false # Install dependencies COPY ./pyproject.toml ./poetry.lock* /app/ RUN poetry install --no-root --no-cache --only main # ==================================== # Release # ==================================== FROM build AS release COPY . . +# Create a non-root user and switch to it +RUN useradd -m appuser && \ + chown -R appuser:appuser /app +USER appuser + +# Create and configure volumes for persistent data +ENV STORAGE_DIR=/app/storage +ENV DATA_DIR=/app/data +VOLUME ["/app/storage", "/app/data"] + EXPOSE 8000 + +# Add healthcheck +HEALTHCHECK --interval=30s --timeout=30s --start-period=5s --retries=3 \ + CMD curl -f http://localhost:8000/health || exit 1 CMD ["poetry", "run", "prod"]
15-15: Consider specifying exact dependency versionsThe current Poetry installation doesn't specify the exact versions of dependencies required for production. Consider using a more specific installation command.
-RUN poetry install --no-root --no-cache --only main +RUN poetry install --no-root --no-cache --only main --no-interactiontemplates/types/llamaindexserver/fastapi/DEPLOY.md (5)
3-3: Fix trailing punctuation in heading.The heading "Using Fly.io:" has a trailing colon that should be removed according to Markdown best practices.
-### Using [Fly.io](https://fly.io/): +### Using [Fly.io](https://fly.io/)🧰 Tools
🪛 markdownlint-cli2 (0.17.2)
3-3: Trailing punctuation in heading
Punctuation: ':'(MD026, no-trailing-punctuation)
11-11: Fix punctuation consistency.There are two punctuation marks at the end of this sentence.
-Then, run this command and follow the prompts to deploy the app.: +Then, run this command and follow the prompts to deploy the app:🧰 Tools
🪛 LanguageTool
[formatting] ~11-~11: These punctuation marks differ from each other. Use only one if you are ending a sentence.
Context: ...and follow the prompts to deploy the app.:shell fly launchAnd to open t...(DOUBLE_PUNCTUATION_PREMIUM)
27-27: Correct verb tense in document description.The phrase "If you're having documents" should be changed to "If you have documents" or "If there are documents" for better grammatical clarity.
-If you're having documents in the `./data` folder, run the following command to generate vector embeddings of the documents: +If you have documents in the `./data` folder, run the following command to generate vector embeddings of the documents:This change should be applied to both instances (lines 27 and 60).
Also applies to: 60-60
🧰 Tools
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[uncategorized] ~27-~27: This verb may not be in the correct tense. Consider changing the tense to fit the context better.
Context: ...ation/) instead. #### Documents If you're having documents in the./datafolder, run t...(AI_EN_LECTOR_REPLACEMENT_VERB_TENSE)
29-31: Add language specifiers to code blocks.Code blocks should have a language specified for proper syntax highlighting.
For fly console command (line 29-31), add
shell:-``` +```shell fly console --machine <machine_id> --command "poetry run generate"For docker build command (line 41-43), add `shell`: ```diff -``` +```shell docker build -t <your_image_name> .For docker run command (lines 47-54), add `shell`: ```diff -``` +```shell docker run \ -v $(pwd)/.env:/app/.env \ # Use ENV variables and configuration from your file-system -v $(pwd)/config:/app/config \ -v $(pwd)/storage:/app/storage \ # Use your file system to store vector embeddings -p 8000:8000 \ <your_image_name>For document processing command (lines 62-71), add `shell`: ```diff -``` +```shell docker run \ --rm \ -v $(pwd)/.env:/app/.env \ # Use ENV variables and configuration from your file-system -v $(pwd)/config:/app/config \ -v $(pwd)/data:/app/data \ # Use your local folder to read the data -v $(pwd)/storage:/app/storage \ # Use your file system to store the vector database <your_image_name> \ poetry run generateAlso applies to: 41-43, 47-54, 62-71 <details> <summary>🧰 Tools</summary> <details> <summary>🪛 markdownlint-cli2 (0.17.2)</summary> 29-29: Fenced code blocks should have a language specified null (MD040, fenced-code-language) </details> </details> --- `35-35`: **Improve "also" placement for better readability.** Move "also" before the verb for more natural phrasing. ```diff -> **Note**: Using documents will make the app stateful. As Fly.io is a stateless app, you should use [LlamaCloud](https://docs.cloud.llamaindex.ai/llamacloud/getting_started) or a vector database to store the embeddings of the documents. This applies also for document uploads by the user. +> **Note**: Using documents will make the app stateful. As Fly.io is a stateless app, you should use [LlamaCloud](https://docs.cloud.llamaindex.ai/llamacloud/getting_started) or a vector database to store the embeddings of the documents. This also applies for document uploads by the user.🧰 Tools
🪛 LanguageTool
[style] ~35-~35: To make your writing flow more naturally, try moving ‘also’ before the verb.
Context: ...e the embeddings of the documents. This applies also for document uploads by the user. ### ...(ALSO_PLACEMENT)
questions/simple.ts (2)
53-53: Reconfirm the default.
SettinguseLlamaCloud = falseby default is fine. However, ensure any CLI flags or environment variables override it where needed.
168-169: Always settingfrontend = true.
This enforces front-end generation even for Python-based apps. If the intended behavior is to skip front-end creation for certain workflows, consider exposing a flag to override this. Otherwise, it’s acceptable if all flows must include a front-end.e2e/shared/llamaindexserver_template.spec.ts (3)
19-19:const appType: AppType = "--frontend"check.
This forces the CLI to always pass--frontend. If this is a placeholder or a forced choice, clarify in code comments to avoid confusion.
75-76: Skipping chat tests forfinancial_reportanddeep_research.
Reflects that these app types are not meant to handle streaming chat in the test environment. If you plan to add interactive or streaming chat features, consider adjusting.
89-94: Response logging in tests.
Printing the response status and body is helpful for debugging. Be mindful not to inadvertently log sensitive information in production test logs.helpers/python.ts (1)
399-418: NewinstallLegacyPythonTemplatefunction.
It organizes the copying of vector DB files, loaders, settings, and services. This large block gains clarity by separating out older templates from the new “llamaindexserver.”templates/components/workflows/python/deep_research/workflow.py (6)
33-45: Verify or refinecreate_workflowindex handling.The function gracefully raises an error if the index is missing. This is good defensive coding. However, you might want to provide a more user-friendly message or a fallback mechanism (e.g., generating a default index or prompting the user to create one).
47-66: Consider including docstrings or inline comments explaining the event classes.Classes like
PlanResearchEvent,ResearchEvent,CollectAnswersEvent, andReportEventare well-named but lack descriptive docstrings or even single-line comments to clarify their responsibilities. Adding those can improve maintainability and onboarding for new contributors.
277-312: Clarify error handling inanswer()step.If an exception occurs during research, you return an error message within the answer itself (line 300). This is helpful, but consider logging the error separately or storing it in a structured form (e.g., an error event). That would let the workflow differentiate between normal answers and error states without mixing them in the user-facing text.
382-448: Sanitize user input withinplan_research.Here, user input is included in a large prompt (lines 388–446). If usage of the results might be displayed or logged, consider sanitizing or escaping user-provided strings to prevent potential injection issues in logs or UI.
450-483: Use caution with unbounded LLM calls inresearch().There's potential for large context or complicated question inputs. Consider adding logic to restrict context size or handle extremely long queries to avoid excessive LLM token usage.
485-526: Enable throttling at report generation.
write_report()can produce a large response, especially with multiple answers combined. Think about implementing pagination or chunked streaming to handle extremely large outputs gracefully.
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.github/workflows/e2e.yml(1 hunks)create-app.ts(1 hunks)e2e/shared/llamaindexserver_template.spec.ts(4 hunks)e2e/utils.ts(1 hunks)helpers/index.ts(5 hunks)helpers/python.ts(5 hunks)helpers/tools.ts(2 hunks)helpers/types.ts(2 hunks)helpers/typescript.ts(1 hunks)questions/index.ts(1 hunks)questions/simple.ts(5 hunks)templates/components/vectordbs/llamaindexserver/llamacloud/python/generate.py(1 hunks)templates/components/vectordbs/llamaindexserver/llamacloud/python/index.py(1 hunks)templates/components/workflows/python/agentic_rag/workflow.py(1 hunks)templates/components/workflows/python/deep_research/workflow.py(1 hunks)templates/components/workflows/python/financial_report/workflow.py(1 hunks)templates/types/llamaindexserver/fastapi/DEPLOY.md(1 hunks)templates/types/llamaindexserver/fastapi/Dockerfile(1 hunks)templates/types/llamaindexserver/fastapi/README-template.md(1 hunks)templates/types/llamaindexserver/fastapi/app/index.py(1 hunks)templates/types/llamaindexserver/fastapi/app/settings.py(1 hunks)templates/types/llamaindexserver/fastapi/generate.py(1 hunks)templates/types/llamaindexserver/fastapi/gitignore(1 hunks)templates/types/llamaindexserver/fastapi/main.py(1 hunks)templates/types/llamaindexserver/fastapi/pyproject.toml(1 hunks)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
templates/types/llamaindexserver/fastapi/gitignoretemplates/types/llamaindexserver/fastapi/README-template.mdtemplates/components/workflows/python/agentic_rag/workflow.pytemplates/types/llamaindexserver/fastapi/generate.pytemplates/types/llamaindexserver/fastapi/main.pytemplates/components/vectordbs/llamaindexserver/llamacloud/python/generate.pytemplates/types/llamaindexserver/fastapi/app/settings.pytemplates/types/llamaindexserver/fastapi/app/index.pytemplates/types/llamaindexserver/fastapi/Dockerfiletemplates/types/llamaindexserver/fastapi/DEPLOY.mdtemplates/components/vectordbs/llamaindexserver/llamacloud/python/index.pytemplates/components/workflows/python/financial_report/workflow.pytemplates/types/llamaindexserver/fastapi/pyproject.tomltemplates/components/workflows/python/deep_research/workflow.py
🧬 Code Definitions (6)
questions/index.ts (1)
questions/simple.ts (1)
askSimpleQuestions(18-112)
templates/types/llamaindexserver/fastapi/generate.py (1)
templates/types/llamaindexserver/fastapi/app/settings.py (1)
init_settings(8-17)
templates/types/llamaindexserver/fastapi/main.py (4)
templates/types/llamaindexserver/fastapi/app/settings.py (1)
init_settings(8-17)templates/components/workflows/python/agentic_rag/workflow.py (1)
create_workflow(9-19)templates/components/workflows/python/deep_research/workflow.py (1)
create_workflow(33-44)templates/components/workflows/python/financial_report/workflow.py (1)
create_workflow(28-48)
templates/components/workflows/python/financial_report/workflow.py (3)
templates/types/llamaindexserver/fastapi/app/index.py (1)
get_index(16-28)templates/components/workflows/python/agentic_rag/workflow.py (1)
create_workflow(9-19)templates/components/workflows/python/deep_research/workflow.py (6)
create_workflow(33-44)ResearchEvent(52-55)ReportEvent(64-65)research(450-482)analyze(172-275)report(351-362)
questions/simple.ts (1)
helpers/datasources.ts (2)
EXAMPLE_FILE(7-12)EXAMPLE_10K_SEC_FILES(14-33)
templates/components/workflows/python/deep_research/workflow.py (2)
templates/types/llamaindexserver/fastapi/app/index.py (2)
IndexConfig(12-13)get_index(16-28)templates/components/workflows/python/financial_report/workflow.py (5)
create_workflow(28-48)ResearchEvent(56-57)ReportEvent(64-65)research(190-225)report(298-327)
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templates/types/llamaindexserver/fastapi/DEPLOY.md
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[uncategorized] ~60-~60: This verb may not be in the correct tense. Consider changing the tense to fit the context better.
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🔇 Additional comments (50)
helpers/tools.ts (1)
127-127:Details
✅ Verification successful
Updated dependency version for code interpreter tools.
The version of
e2b_code_interpreterhas been updated from1.0.3to1.1.1for both the Code Interpreter and Artifact Code Generator tools. This is a good practice to keep dependencies up-to-date.Let's verify if there are any notable changes in this version update:
Also applies to: 158-158
🌐 Web query:
What are the changes between e2b_code_interpreter versions 1.0.3 and 1.1.1?💡 Result:
The available search results don't explicitly list a changelog between versions 1.0.3 and 1.1.1 of the E2B Code Interpreter SDK. However, based on the documentation and release patterns, here are the key changes we can infer:
Core Improvements
- Stateful Execution Context: Enhanced context preservation between code executions using Jupyter Kernel messaging protocol[13][16]
- Data Handling: Better extraction of DataFrame contents and structured data outputs from executed code[7][16]
- Error Handling: Added timeout parameters (
requestTimeoutMsandtimeoutMs) for code execution control[11]New Features
# New timeout parameters in 1.1.1 execution = sandbox.run_code("x+=1; x", timeoutMs=60000, # Execution timeout requestTimeoutMs=30000 # Network timeout )Security & Reliability
- Fixed memory issues causing sporadic 504/503 errors[7]
- Improved sandbox isolation through Firecracker virtualization[2][5]
- Enhanced Linux kernel parameter configuration for production use[7]
API Changes
- Added
onResultcallback for final execution output handling[11]- Introduced
onStderr/onStdoutstreaming handlers[13][16]- Environment variable configuration support (
envsparameter)[11]The most significant undocumented change appears to be the transition from basic code execution to full Jupyter kernel integration, enabling:
- Interactive chart rendering
- DataFrame visualization
- Shared execution state between cells[13][16]
For precise version comparisons, the E2B team recommends checking their GitHub release notes[14] or contacting support directly[2]. The Python Package Index (PyPI) shows updated file hashes and build configurations between versions but no explicit changelog[16].
Citations:
- 1: https://e2b.dev/docs/legacy/code-interpreter/installation
- 2: https://e2b.dev/blog/launching-the-code-interpreter-sdk
- 3: https://pypi.org/project/e2b/
- 4: https://github.com/e2b-dev/code-interpreter/blob/main/pnpm-lock.yaml
- 5: https://github.com/e2b-dev/code-interpreter
- 6: https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/langgraph-python/langgraph_code_interpreter.ipynb
- 7: https://e2b.dev/changelog
- 8: https://e2b.dev/docs
- 9: https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/codestral-code-interpreter-python/codestral_code_interpreter.ipynb
- 10: https://e2b-blog.framer.website/blog/how-to-add-code-interpreter-to-llama3
- 11: https://changelog.e2b.dev/docs/sdk-reference/code-interpreter-js-sdk/v1.0.4/sandbox
- 12: https://public.dhe.ibm.com/ps/products/db2/info/vr105/pdf/en_US/DB2InstallingServers-db2ise1050.pdf
- 13: https://www.npmjs.com/package/@e2b/code-interpreter/v/1.0.1
- 14: https://github.com/e2b-dev/llm-code-interpreter/releases
- 15: https://apps.dtic.mil/sti/tr/pdf/ADB053656.pdf
- 16: https://pypi.org/project/e2b-code-interpreter/
- 17: https://www.nrc.gov/docs/ML0727/ML072740014.pdf
- 18: https://huggingface.co/learn/cookbook/zh-CN/agents
- 19: https://github.com/e2b-dev/e2b-cookbook/blob/main/examples/upload-dataset-code-interpreter/llama_3_code_interpreter_upload_dataset.ipynb
- 20: https://sourceforge.net/projects/e2b-code-interpreter.mirror/files/@e2b_code-interpreter-python@1.0.3/
Dependency Version Update Verified
The update from version
"1.0.3"to"1.1.1"for thee2b_code_interpreterdependency inhelpers/tools.ts(lines 127 and 158) is confirmed. The new version includes important enhancements—such as stateful execution context, improved data and error handling (with new timeout parameters), enhanced sandbox isolation, and additional API callbacks—without introducing breaking changes. Keeping dependencies up-to-date with these improvements is indeed a good practice.helpers/types.ts (2)
27-28: Added new LlamaIndexServer template type.The addition of
"llamaindexserver"to theTemplateTypealigns with the PR objective to simplify app code using LlamaIndexServer.
59-60: Added agentic_rag use case to supported template use cases.The addition of
"agentic_rag"toTemplateUseCaseenables new functionality for the application and aligns with the LlamaIndexServer integration.templates/types/llamaindexserver/fastapi/gitignore (1)
1-5: Appropriate .gitignore patterns for Python FastAPI project.The .gitignore file correctly includes common patterns that should be excluded from version control:
__pycache__: Python bytecode filesstorage: Data storage directory.env: Environment variables file (important for security)output: Output files/directories.ui/: UI-related filesThis helps maintain a clean repository without sensitive or unnecessary files.
.github/workflows/e2e.yml (1)
70-71: Added Python encoding environment variables for cross-platform compatibility.The addition of
PYTHONIOENCODINGandPYTHONLEGACYWINDOWSSTDIOenvironment variables ensures consistent UTF-8 text encoding across all platforms (especially important for Windows), which is essential for running E2E tests reliably with international text or special characters.templates/types/llamaindexserver/fastapi/README-template.md (1)
1-14: Well-structured README templateThis README provides clear and concise information about the LlamaIndex multi-agents project, including deployment instructions and learning resources. The structure follows documentation best practices with distinct sections for different types of information.
questions/index.ts (1)
19-20: Clean code refactoringThis simple refactoring improves readability by storing the result in a named variable before returning it. While it doesn't change functionality, it makes the code more maintainable and easier to debug.
create-app.ts (1)
93-93: Correct conditional logic for LlamaIndexServer templateThe added condition correctly prevents frontend installation when using the "llamaindexserver" template with FastAPI. This aligns with the PR objective to simplify app code using LlamaIndexServer.
templates/components/vectordbs/llamaindexserver/llamacloud/python/index.py (1)
1-7: Well-structured module exportsThis module follows good Python practices by clearly defining imports and using
__all__to explicitly declare the public API. The code provides a clean interface to LlamaCloud functionality.e2e/utils.ts (1)
116-121: Support for "llamaindexserver" template type added correctly.This change appropriately extends the condition to include "llamaindexserver" as a valid template type that can use the
--use-caseargument, maintaining consistency with the existing behavior for "multiagent" and "reflex" templates.templates/types/llamaindexserver/fastapi/app/settings.py (1)
8-17: Add a docstring with link to documentation.The function should include documentation that explains how to configure these settings through environment variables.
def init_settings(): + """Initialize LlamaIndex settings with OpenAI models. + + Environment variables: + - MODEL: OpenAI model name (default: "gpt-4o-mini") + - LLM_TEMPERATURE: Temperature for the LLM (default: 0.5) + - LLM_MAX_TOKENS: Max tokens for the LLM (default: 1000) + - EMBEDDING_MODEL: OpenAI embedding model (default: "text-embedding-3-small") + - EMBEDDING_DIMENSIONS: Dimensions for embeddings (default: 1024) + + For more information on configuring LlamaIndex settings, see: + https://docs.llamaindex.ai/en/stable/module_guides/settings/settings.html + """ Settings.llm = OpenAI( model=os.getenv("MODEL", "gpt-4o-mini"), temperature=os.getenv("LLM_TEMPERATURE", 0.5), max_tokens=os.getenv("LLM_MAX_TOKENS", 1000), ) Settings.embed_model = OpenAIEmbedding( model=os.getenv("EMBEDDING_MODEL", "text-embedding-3-small"), dimensions=os.getenv("EMBEDDING_DIMENSIONS", 1024), )templates/types/llamaindexserver/fastapi/main.py (2)
13-27: Well-structured FastAPI application setup.The
create_appfunction is well-designed, allowing for extension and customization of the FastAPI application. The use of a factory pattern promotes testability and flexibility.
34-42:Details
❓ Verification inconclusive
Potential conflict between
runfunction and global app initialization.The
runfunction sets theAPP_ENVenvironment variable, but the app is already created at the module level with the current environment. This could lead to inconsistencies ifrunis called with a different environment than was available during app initialization.Consider one of these approaches:
- Move app initialization into the
runfunction- Pass the environment to
create_appdirectly rather than relying on environment variables- Add a warning if the environment differs from what was used during initialization
🏁 Script executed:
#!/bin/bash # Check if APP_ENV is already set in the environment if [ -n "$APP_ENV" ]; then echo "APP_ENV is currently set to: $APP_ENV" echo "The run function will override this value, which might cause inconsistency with the globally initialized app" fiLength of output: 15
Below is the revised review comment after additional investigation:
Attention: Ensure Consistency in Environment Setup Across Initialization
Although our shell check shows that no external
APP_ENVis set when running the script, the concern remains: if the global app instance in this module is initialized (likely at module load) with a default or previously set environment, then callingrun(env)later will updateAPP_ENVwithout affecting the already configured app. This mismatch can lead to inconsistent behavior.Please verify one of the following approaches:
- Move Global App Initialization: Delay initializing the app until inside the
runfunction (or use a factory method) so that the environment passed torun(env)is used from the start.- Parameterize App Creation: Pass the environment as a parameter to the app creation function (e.g.,
create_app(env)) rather than solely relying on environment variables.- Add a Consistency Check: Introduce a runtime warning if the environment specified in
run(env)doesn’t match the one used during global app initialization.Ensure that the global initialization logic is reviewed to confirm that no conflicting values are present.
templates/components/vectordbs/llamaindexserver/llamacloud/python/generate.py (1)
1-32: Consider refactoring to reduce code duplicationThis code appears to be reused from server code, as mentioned in previous comments. Consider implementing a shared utility module that both this file and the server code can import.
templates/types/llamaindexserver/fastapi/Dockerfile (1)
26-26:Details
✅ Verification successful
Ensure
prodcommand is defined in pyproject.tomlMake sure the
prodcommand referenced in the CMD instruction is defined in your pyproject.toml file's[tool.poetry.scripts]section.
🏁 Script executed:
#!/bin/bash # Verify that the 'prod' command is defined in pyproject.toml if [ -f templates/types/llamaindexserver/fastapi/pyproject.toml ]; then echo "Checking for 'prod' command in pyproject.toml..." grep -A 10 "\[tool.poetry.scripts\]" templates/types/llamaindexserver/fastapi/pyproject.toml else echo "pyproject.toml file not found in expected location" fiLength of output: 537
Verified: The 'prod' command is correctly defined in pyproject.toml.
The CMD instruction in the Dockerfile correctly invokes
poetry run prod, and our verification confirms that theprodscript is present in the[tool.poetry.scripts]section ofpyproject.toml. No further changes are required.helpers/typescript.ts (1)
265-265: LGTM! Dependencies updated to latest versions.You've updated all LlamaIndex dependencies to their latest versions, which is excellent for ensuring compatibility with the newest features and bug fixes.
Also applies to: 268-268, 271-271, 274-274, 277-277, 280-281, 284-285
helpers/index.ts (6)
4-4: LGTM! Improved module import.The import was improved to include direct named import for
cyanwhile still importing the full module.
44-48: Improved null checking for vectorDb.This change enhances the robustness of the validation by explicitly checking for
undefined, ensuring the condition only runs when vectorDb is properly defined and not "none" or "llamacloud".
99-99: LGTM! Consistent styling.Changed the styling from string concatenation to template literals, which improves readability.
171-175: Improved code structure for template installation.The condition has been restructured to call
installTSTemplateonly when the framework is not "fastapi", which clarifies the flow of the function.
177-183: Improved configuration management.The configuration writing logic has been moved to operate unconditionally if the template is not "llamaindexserver", which streamlines the code and makes it more maintainable.
199-199: Enhanced condition for backend environment file creation.Modified the condition to exclude both "community" and "llamapack" templates when creating the backend environment file, which provides better consistency across different template types.
templates/types/llamaindexserver/fastapi/pyproject.toml (1)
1-48: LGTM! Well-structured Poetry configuration file.This new configuration file for the FastAPI application includes all necessary components:
- Appropriate project metadata
- Useful scripts for generating datasources and running the application
- Comprehensive dependencies for both production and development
- Well-configured mypy settings for type checking
The Python version constraints, dependency specifications, and build system settings are correctly defined for the application's requirements.
questions/simple.ts (5)
2-2: Good import addition.
It makes sense to import the financial and file datasources in this context, as they align with the new app types.
9-9: ConsolidatedAppTypelooks clean.
Refactoring the supported app types to"agentic_rag","financial_report", and"deep_research"streamlines the flow and avoids unnecessary branching.
25-45: Updated prompt and choices match new use cases.
The changes to both the prompt ("What use case do you want to build?") and the choice array accurately reflect the newly consolidated set of app types. This improves clarity for users selecting a predefined use case.
130-150: Configuration object for each app type is consistent.
"agentic_rag"references a single example file, which is good for basic usage."financial_report"references 10K SEC files and includes relevant tools like the interpreter and document generator."deep_research"reuses those same example SEC files with no additional tools.
All entries correctly refer to"llamaindexserver"as the template. Looks good.
155-155:useCase: answers.appTypeis logical.
Aligns with the newly consolidated app type system, ensuring the returned object remains consistent.e2e/shared/llamaindexserver_template.spec.ts (4)
21-21:templateUseCasesarray now references updated app types.
Reflects the new set of recognized use cases:"financial_report","agentic_rag", and"deep_research". This harmonizes the test coverage with the simplifiedAppType.
24-24: Test description updated.
Changing to “Test use case …” is clearer and consistent with the new approach inquestions/simple.ts.
26-27: Revised skip logic.
Skipping tests based solely onDATASOURCE === "--no-files"is consistent with the file-based design ofllamaindexserver.
41-41: Use oftemplateType: "llamaindexserver".
Aligns with the code changes inquestions/simple.ts.helpers/python.ts (5)
15-15: AddedTemplateObservabilityimport.
Positive step for hooking in advanced observability options.
33-33: Optionalobservabilityparameter.
Concept is well-structured. Clearly indicates where additional dependencies might be injected based on different observability tools.
273-287: Observability dependencies seem correct but confirm versions.
Addingtraceloop-sdkandllama-index-callbacks-arize-phoenixis logical. Consider verifying that the pinned versions match your Python version constraints or any projected updates.
520-564: NewinstallLlamaIndexServerTemplatefunction.
Segregating “llamaindexserver” logic is beneficial. The explicit references touseCaseanduseLlamaParsemake the template more customizable and maintainable.
566-640:installPythonTemplaterestructured for clarity.
Having a single entry point that dispatches to eitherinstallLlamaIndexServerTemplateorinstallLegacyPythonTemplateis more maintainable. The approach to add-on dependencies at the end is logical.templates/components/workflows/python/financial_report/workflow.py (11)
1-3: Imports are aligned with usage.
They set the stage for a specialized “financial report” workflow.
4-26: Additional dependencies are well-structured.
References toget_index,llama_indexmodules, and specialized tools (code interpreter, document generator) are suitable for a robust financial workflow.
28-49:create_workflowfor financial reports.
- Validates that the index exists and raises an error if not found.
- Properly instantiates specialized tools.
- Uses a
FinancialReportWorkflowto unify them.
Looks good.
51-66: Event classes are well-defined.
InputEvent,ResearchEvent,AnalyzeEvent, andReportEventall provide a clear structure for each step’s payload.
68-88: Class docstring thoroughly explains the workflow.
This is helpful documentation. The multi-step approach for financial analysis, code interpretation, and report generation addresses typical finance use cases.
89-124: Constructor enforces required tools.
- Assertions for
query_engine_tool,code_interpreter_tool, anddocument_generator_tool.- The fallback to
Settings.llmis neat for a sensible default.
125-144:prepare_chat_historystep.
- Conditionally sets streaming behavior.
- Merges any existing chat history with the new user message.
- Applies a system prompt if available.
This builds a robust LLM context.
146-188:handle_llm_inputhandles multi-tool calls well.
- Returns a
StopEventif no tool calls.- Rejects simultaneous tool calls.
- Routes calls to specific events (ResearchEvent, AnalyzeEvent, or ReportEvent).
All are correct for a multi-step approach.
190-226:researchstep logs progress and updates memory.
- Uses
call_toolswithquery_engine_tool.- Writes the result into tool messages for subsequent analysis.
228-296:analyzestep handles different triggers nicely.
- If triggered by the model requesting the code interpreter, we proceed with analysis.
- The approach for merging custom prompts to the memory is well-implemented.
- Fallback logic ensures results flow back into the workflow.
298-327:reportstep finalizes generation.
- Provides a “Reporter” context.
- Uses the
DocumentGeneratortool to create the synthetic output.- Falls back to an
InputEventwith the latest chat history.
This is consistent with earlier steps and fosters a seamless chain.templates/components/workflows/python/deep_research/workflow.py (2)
77-79: Evaluate the appropriate location forDataEvent.Previously, it was suggested that if this event is strictly tied to “llamaindexserver,” it might be more coherent to define or relocate it alongside the server-specific events. The same feedback still applies.
105-116:Details
❓ Verification inconclusive
Potential concurrency considerations with shared
SimpleComposableMemory.You store
SimpleComposableMemoryas a shared state in the workflow. Since you use asynchronous steps (and potentially multiple workers for theanswerstep), ensure that any writes to the memory are thread- or task-safe to avoid race conditions.
🏁 Script executed:
#!/bin/bash # Search for concurrency keywords in memory usage to verify no race conditions exist rg "async|await|thread|concurrent|lock|SimpleComposableMemory|ChatMemoryBuffer" -A 5Length of output: 105069
Action Required: Verify Concurrency Safety for Shared Memory
The shared instance of
SimpleComposableMemoryis initialized without any explicit locking or synchronization mechanisms. Given that asynchronous steps (and possibly multiple workers in theanswerstep) might perform concurrent writes, please verify that the implementation ofSimpleComposableMemory—and its underlyingChatMemoryBuffer—handles concurrent access safely. If these components aren't inherently thread- or task-safe, consider adding proper concurrency controls (e.g., locks) to prevent potential race conditions.
templates/components/workflows/python/deep_research/workflow.py
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🧹 Nitpick comments (17)
templates/types/llamaindexserver/nextjs/src/app/data.ts (4)
7-10: Consider adding proper typing for the params parameter.The function parameter
paramsis typed asany, which bypasses TypeScript's type checking benefits. If you know the expected structure of the parameters, consider creating a proper interface or type for it.- export async function getIndex(params?: any) { + interface IndexParams { + // Define expected properties here + } + export async function getIndex(params?: IndexParams) {
12-18: Improve error handling for document store operations.The code correctly checks for empty document stores, but consider adding error handling for potential failures when accessing the document store. Additionally, the TODO comment indicates this is a temporary implementation until
storageContext.numDocsis supported.// TODO: support storageContext.numDocs later - const numberOfDocs = Object.keys( - (storageContext.docStore as SimpleDocumentStore).toDict(), - ).length; - if (numberOfDocs === 0) { - return null; - } + try { + const numberOfDocs = Object.keys( + (storageContext.docStore as SimpleDocumentStore).toDict(), + ).length; + if (numberOfDocs === 0) { + return null; + } + } catch (error) { + console.error("Failed to access document store:", error); + return null; + }
20-21: Add error handling for VectorStoreIndex initialization.The function does not handle potential errors during index initialization. Consider adding a try-catch block to handle exceptions properly.
- return await VectorStoreIndex.init({ storageContext }); + try { + return await VectorStoreIndex.init({ storageContext }); + } catch (error) { + console.error("Failed to initialize vector store index:", error); + return null; + }
7-21: Consider documenting the unused params parameter or removing it if not needed.The
paramsparameter is declared but never used within the function. If it's intended for future use, this should be documented with a comment. Otherwise, consider removing it to avoid confusion.- export async function getIndex(params?: any) { + /** + * Get the vector store index if documents exist + * @param params Reserved for future use to customize index retrieval + * @returns The vector store index or null if no documents exist + */ + export async function getIndex(params?: any) {Alternatively, if it's not needed:
- export async function getIndex(params?: any) { + export async function getIndex() {templates/types/llamaindexserver/nextjs/README-template.md (5)
7-9: Add Language Identifier to Fenced Code BlockStatic analysis suggests specifying a language for fenced code blocks to enable proper syntax highlighting. Consider adding
bashfor the terminal command block shown here.-``` +```bash🧰 Tools
🪛 markdownlint-cli2 (0.17.2)
7-7: Fenced code blocks should have a language specified
null(MD040, fenced-code-language)
16-18: Specify Language for Fenced Code BlockFor better readability and consistency, please add a language identifier (e.g.
bash) to this fenced code block.-``` +```bash🧰 Tools
🪛 markdownlint-cli2 (0.17.2)
16-16: Fenced code blocks should have a language specified
null(MD040, fenced-code-language)
22-24: Add Language Specifier for Code BlockAdding a language identifier to this fenced code block helps with syntax highlighting. For terminal commands, using
bashis recommended.-``` +```bash🧰 Tools
🪛 markdownlint-cli2 (0.17.2)
22-22: Fenced code blocks should have a language specified
null(MD040, fenced-code-language)
33-37: Specify Language for Curl Command BlockTo improve clarity, specify a language (e.g.
bash) for this fenced code block that contains the curl command.-``` +```bash🧰 Tools
🪛 markdownlint-cli2 (0.17.2)
33-33: Fenced code blocks should have a language specified
null(MD040, fenced-code-language)
30-30: Language Correction: Use "a" Instead of "an"The phrase “an request” should be revised to “a request” because "request" starts with a consonant sound.
-You can start by sending an request on the chat UI to create a report comparing the finances of Apple and Tesla. +You can start by sending a request on the chat UI to create a report comparing the finances of Apple and Tesla.🧰 Tools
🪛 LanguageTool
[misspelling] ~30-~30: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ... CSV Template You can start by sending an request on the chat UI to create a repo...(EN_A_VS_AN)
templates/components/workflows/typescript/agentic_rag/workflow.ts (2)
5-16: Consider handling tool failures gracefully.
IfdocumentGeneratorfails or throws an exception, the code may not capture this event. You could catch or surface any tool-related errors to ensure robust error handling.
27-31: Add minimal documentation comments if possible.
Consider adding a short doc comment forworkflowFactoryto highlight usage or parameters, even though it currently takes no parameters, to maintain consistency with other factories in the codebase.templates/components/workflows/typescript/deep_research/workflow.ts (3)
101-101: Avoid using '{}' as a type.
Using'{}'as a type can make the code ambiguous and prone to future errors. Prefer usingvoidor a more descriptive interface if data properties are expected in the future.-class PlanResearchEvent extends WorkflowEvent<{}> {} +class PlanResearchEvent extends WorkflowEvent<void> {}🧰 Tools
🪛 Biome (1.9.4)
[error] 101-101: Don't use '{}' as a type.
Prefer explicitly define the object shape. '{}' means "any non-nullable value".
(lint/complexity/noBannedTypes)
103-103: Avoid using '{}' as a type.
As withPlanResearchEvent,'{}'should be replaced withvoidor a more specific type.-class ReportEvent extends WorkflowEvent<{}> {} +class ReportEvent extends WorkflowEvent<void> {}🧰 Tools
🪛 Biome (1.9.4)
[error] 103-103: Don't use '{}' as a type.
Prefer explicitly define the object shape. '{}' means "any non-nullable value".
(lint/complexity/noBannedTypes)
409-410: Add error handling for LLM JSON parsing.
When callingJSON.parse(result.text), consider a try/catch block to handle malformed JSON gracefully. This prevents workflow failure if the LLM output is invalid.templates/types/llamaindexserver/nextjs/src/app/settings.ts (1)
4-11: Consider making model configuration more flexible with environment variablesThe function correctly initializes LlamaIndex settings, but the model names are hardcoded. For a template that others will use, it would be better to read these values from environment variables with sensible defaults.
export function initSettings() { Settings.llm = new OpenAI({ - model: "gpt-4o-mini", + model: process.env.LLM_MODEL || "gpt-4o-mini", }); Settings.embedModel = new OpenAIEmbedding({ - model: "text-embedding-ada-002", + model: process.env.EMBEDDING_MODEL || "text-embedding-ada-002", }); }Also consider adding basic error handling and JSDoc comments to improve code maintainability.
templates/types/llamaindexserver/nextjs/src/generate.ts (1)
22-25: Make the script execution conditionalThe script automatically executes when imported. Consider making this execution conditional or providing a way to import the function without running it.
-(async () => { - initSettings(); - await generateDatasource(); -})(); +// Only run if this file is executed directly +if (require.main === module) { + (async () => { + try { + initSettings(); + await generateDatasource(); + console.log("Data generation completed successfully"); + } catch (error) { + console.error("Failed to generate data:", error); + process.exit(1); + } + })(); +}helpers/typescript.ts (1)
37-55: Validate function parameters for resilience.The function signature is extended with
backend(boolean) andrelativeEngineDestPath(string). Consider validating or defaulting these arguments if they are potentially undefined in some use cases. This ensures the function remains robust even if future callers omit or provide invalid values for these parameters.
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📒 Files selected for processing (13)
helpers/typescript.ts(3 hunks)templates/components/workflows/typescript/agentic_rag/workflow.ts(1 hunks)templates/components/workflows/typescript/deep_research/workflow.ts(1 hunks)templates/components/workflows/typescript/financial_report/workflow.ts(1 hunks)templates/types/llamaindexserver/nextjs/README-template.md(1 hunks)templates/types/llamaindexserver/nextjs/gitignore(1 hunks)templates/types/llamaindexserver/nextjs/package.json(1 hunks)templates/types/llamaindexserver/nextjs/src/.prettierrc.json(1 hunks)templates/types/llamaindexserver/nextjs/src/app/data.ts(1 hunks)templates/types/llamaindexserver/nextjs/src/app/settings.ts(1 hunks)templates/types/llamaindexserver/nextjs/src/generate.ts(1 hunks)templates/types/llamaindexserver/nextjs/src/index.ts(1 hunks)templates/types/llamaindexserver/nextjs/tsconfig.json(1 hunks)
✅ Files skipped from review due to trivial changes (4)
- templates/types/llamaindexserver/nextjs/src/.prettierrc.json
- templates/types/llamaindexserver/nextjs/gitignore
- templates/types/llamaindexserver/nextjs/tsconfig.json
- templates/types/llamaindexserver/nextjs/package.json
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📓 Path-based instructions (1)
`templates/**`: For files under the `templates` folder, do not report 'Missing Dependencies Detected' errors.
templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
templates/types/llamaindexserver/nextjs/src/app/settings.tstemplates/types/llamaindexserver/nextjs/src/app/data.tstemplates/types/llamaindexserver/nextjs/src/generate.tstemplates/types/llamaindexserver/nextjs/src/index.tstemplates/components/workflows/typescript/agentic_rag/workflow.tstemplates/components/workflows/typescript/deep_research/workflow.tstemplates/components/workflows/typescript/financial_report/workflow.tstemplates/types/llamaindexserver/nextjs/README-template.md
🧬 Code Definitions (4)
templates/types/llamaindexserver/nextjs/src/generate.ts (1)
templates/types/llamaindexserver/nextjs/src/app/settings.ts (1)
initSettings(4-11)
templates/types/llamaindexserver/nextjs/src/index.ts (4)
templates/types/llamaindexserver/nextjs/src/app/settings.ts (1)
initSettings(4-11)templates/components/workflows/typescript/agentic_rag/workflow.ts (1)
workflowFactory(27-31)templates/components/workflows/typescript/financial_report/workflow.ts (1)
workflowFactory(33-70)templates/components/workflows/typescript/deep_research/workflow.ts (1)
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templates/components/workflows/typescript/agentic_rag/workflow.ts (2)
templates/components/workflows/typescript/financial_report/workflow.ts (1)
workflowFactory(33-70)templates/components/workflows/typescript/deep_research/workflow.ts (1)
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templates/components/workflows/typescript/deep_research/workflow.ts (2)
templates/components/workflows/typescript/financial_report/workflow.ts (1)
workflowFactory(33-70)templates/types/llamaindexserver/nextjs/src/app/data.ts (1)
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templates/components/workflows/typescript/deep_research/workflow.ts
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🔇 Additional comments (9)
templates/types/llamaindexserver/nextjs/src/app/data.ts (1)
1-5: Dependencies look good for LlamaIndex integration.The imports correctly include the necessary components from the LlamaIndex library to work with document storage and vector indexing.
templates/components/workflows/typescript/agentic_rag/workflow.ts (2)
1-4: Imports look consistent and match the intended usage.
No issues found with these import statements.
18-25: Research agent declaration is straightforward and well-structured.
The approach to limit handoff recipients to[reportAgent]is clear and maintains a clean separation of concerns.templates/components/workflows/typescript/deep_research/workflow.ts (1)
121-440: Workflow steps and steps chaining logic appear consistent.
The event-driven design is coherent, and each step is properly tied into subsequent steps. Great job structuring a multi-phase research workflow.templates/components/workflows/typescript/financial_report/workflow.ts (3)
28-29: Confirm that 360,000 ms aligns with the rest of your code’s timeout logic.
Some parts of this workflow passtimeoutin seconds; verify whether 360 * 1000 (ms) consistently matches your workflow or if you need to standardize time units.
33-70: Factory setup is comprehensive and includes proper checks.
The index availability check and environment variable check forE2B_API_KEYprevent runtime issues. The tool creation pattern is clear and maintainable.
72-411: Workflow steps are well-defined and event-driven.
The scheduling of InputEvent, ResearchEvent, AnalyzeEvent, and ReportGenerationEvent logically flow, with robust memory handling and tooling. This structured approach is solid for complex workflows.helpers/typescript.ts (2)
317-317: Confirm the emptyrelativeEngineDestPathassignment.You’re passing an empty
relativeEngineDestPathtoupdatePackageJson. This suppresses creation of the “generate” script (or other references) in the package.json. If this is intended—e.g., for frameworks that do not need the engine—no problem. Otherwise, consider preserving the previously computed path.
334-360:Details
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Ensure new provider dependency versions are correct and safe.
The updated dependency versions (e.g.,
@llamaindex/openai,@llamaindex/groq,@llamaindex/anthropic) could introduce breaking changes or security patches. Verify that these versions are compatible with your existing usage and that no new vulnerabilities were introduced.
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The automated checks (using npm-check-updates and the GitHub security API) encountered permission issues and argument conflicts, so we couldn’t conclusively verify the safety and compatibility of the new dependency versions. Please perform a manual security and compatibility review of the following provider dependency versions in
helpers/typescript.ts(lines 334–360):
- openai / azure-openai:
"@llamaindex/openai": "^0.2.0"- gemini:
"@llamaindex/google": "^0.2.0"- ollama:
"@llamaindex/ollama": "^0.1.0"- mistral:
"@llamaindex/mistral": "^0.2.0"- groq:
"@llamaindex/groq": "^0.0.61""@llamaindex/huggingface": "^0.1.0"(used as groq’s default embedding model)- anthropic:
"@llamaindex/anthropic": "^0.3.0""@llamaindex/huggingface": "^0.1.0"(used as anthropic’s default embedding model)Please verify that these versions:
- Are compatible with their current usage in the codebase.
- Do not introduce breaking changes.
- Remain free from known vulnerabilities (e.g., by checking changelogs/security advisories manually or via alternative tooling with the appropriate permissions).
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🧹 Nitpick comments (3)
templates/components/workflows/typescript/financial_report/workflow.ts (3)
44-46: Improve missing API key error handling.
Throwing an error immediately is one valid approach, but consider more user-friendly alternatives such as providing instructions for settingE2B_API_KEYor falling back to a feature-limited mode if feasible.
250-282: Parallel tool calls for research are well structured.
The step-based approach with progress updates is clear. Consider verifying each result for correctness or fallback behavior if a single tool call fails.
301-343: Add user guidance on data privacy for financial data.
When analyzing sensitive financial info, you might remind users that the data can appear in tool outputs (including logs). Consider a disclaimer or a masking strategy before persisting.
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templates/components/workflows/typescript/deep_research/workflow.tstemplates/components/workflows/typescript/financial_report/workflow.tstemplates/components/workflows/typescript/agentic_rag/workflow.ts
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templates/components/workflows/typescript/deep_research/workflow.ts (2)
templates/components/workflows/typescript/agentic_rag/workflow.ts (1)
workflowFactory(27-31)templates/types/llamaindexserver/nextjs/src/app/data.ts (1)
getIndex(7-21)
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templates/components/workflows/typescript/deep_research/workflow.ts
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🔇 Additional comments (5)
templates/components/workflows/typescript/deep_research/workflow.ts (1)
435-445: Streaming approach validated.
The generator-based streaming logic is clear, efficient, and properly awaits chunks. No immediate concurrency or performance concerns are evident in this implementation.templates/components/workflows/typescript/financial_report/workflow.ts (1)
113-116: LLM type check is correct.
Verifyingthis.llmfor tool call support is commendable. This guard prevents improper usage of a non-ToolCallLLM instance.templates/components/workflows/typescript/agentic_rag/workflow.ts (3)
5-16: Clear responsibility for ReportAgent.
Using a dedicated agent for blog post creation and persisting results with thedocumentGeneratortool is a clean design approach. No immediate issues found.
18-25: Handoff strategy from researchAgent.
TheresearchAgentis configured to gather information and potentially hand off toreportAgent. Verify that the system ensures only safe or relevant data is relayed to prevent mixing unvetted content.
27-31: Multi-agent workflow design.
ThemultiAgentconstruction fosters modular responsibilities. The root agent is clearly defined, with a straightforward agent chain. Overall, well-structured and maintainable.
templates/components/workflows/typescript/deep_research/workflow.ts
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templates/components/workflows/python/agentic_rag/workflow.py (1)
12-23: Function implementation looks good but consider adding docstring.The
create_workflowfunction follows a consistent pattern with other workflow templates, providing proper error handling when the index isn't found. The use of environment variables for the system prompt allows for flexibility in configuration. The function correctly initializes anAgentWorkflowwith appropriate tools and defaults.Consider adding a docstring to describe:
- The function's purpose
- Parameters and return type descriptions
- The error conditions
def create_workflow(chat_request: Optional[ChatRequest] = None) -> AgentWorkflow: + """ + Create an AgentWorkflow instance using a query engine tool based on the provided index. + + Args: + chat_request: Optional ChatRequest to pass to the index retrieval function + + Returns: + AgentWorkflow: Configured workflow ready for handling user queries + + Raises: + RuntimeError: If the index is not found, suggesting to run the generation script + """ query_tool = get_query_engine_tool(index=get_index(chat_request=chat_request)) if query_tool is None: raise RuntimeError(llama-index-server/pyproject.toml (1)
39-39: Enforce Fixed Dependency Version.
The version specification forllama-index-indices-managed-llama-cloudhas been changed to the strict"0.6.3"(instead of using the caret notation). This enforces usage of exactly version 0.6.3 rather than allowing compatible patch updates. Please confirm that this decision aligns with our dependency management strategy.🧰 Tools
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[error] pyproject.toml changed significantly since poetry.lock was last generated. Run
poetry lock [--no-update]to fix the lock file.llama-index-server/llama_index/server/api/routers/chat.py (1)
110-111: Simplified condition for yielding chunk deltas.Similar to the previous change, this modification removes the check for non-empty deltas when streaming chunks from a
StopEventresult. The code now yields all deltas regardless of their content, creating more consistent streaming behavior.This change maintains consistency with the modification on line 102. When streaming text responses, it's often better to pass through all tokens (even empty ones) and let the client decide how to handle them, rather than filtering at the server level. This approach provides more flexibility and prevents potential issues with certain LLM streaming implementations that might rely on receiving every token.
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templates/components/workflows/python/agentic_rag/workflow.py
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templates/components/workflows/python/agentic_rag/workflow.py (3)
templates/types/llamaindexserver/fastapi/app/index.py (1)
get_index(21-32)templates/components/workflows/python/financial_report/workflow.py (1)
create_workflow(29-51)templates/components/workflows/python/deep_research/workflow.py (1)
create_workflow(34-44)
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🔇 Additional comments (3)
templates/components/workflows/python/agentic_rag/workflow.py (1)
1-10: Import organization and dependency choices look good.The imports are well-organized, with standard library imports first, followed by application-specific and third-party imports. The code properly imports required components from LlamaIndex's core and server modules needed for the agentic RAG workflow implementation.
llama-index-server/pyproject.toml (1)
29-65:Details
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102-102:Details
❓ Verification inconclusive
Simplified streaming logic by removing empty string check.
The code now unconditionally yields
event.deltawithout first checking if it contains non-whitespace characters. This change allows empty deltas to flow through the stream, which might be necessary for certain clients that expect consistent token-by-token streaming.To ensure this doesn't cause issues, verify that downstream consumers of this stream can properly handle empty delta strings:
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The simplified streaming logic now directly yields
event.delta, including empty strings, which could be acceptable for clients expecting consistent token streaming. However, our initial scan for references to client-side functions (likehandleStreamChunk,processStreamData, oronStreamMessage) in JavaScript/TypeScript files yielded no results. This absence means we cannot fully confirm from the codebase that downstream consumers handle empty strings properly.
- File:
llama-index-server/llama_index/server/api/routers/chat.py- Line: 102 (
yield event.delta)Action Required:
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…sage, and conditionally include Llama Cloud API key in env file.
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🧹 Nitpick comments (19)
templates/components/workflows/typescript/deep_research/workflow.ts (2)
405-407: Add error handling for JSON parsing.When parsing
result.textas JSON, consider wrapping the parse in a try/catch or validating the output to avoid runtime errors if the LLM response contains invalid or unexpected JSON.try { - const plan = JSON.parse(result.text) as z.infer<typeof responseFormat>; + const parsed = JSON.parse(result.text ?? "{}"); + const plan = responseFormat.parse(parsed); } catch (e) { throw new Error(`Failed to parse LLM response: ${e instanceof Error ? e.message : e}`); }
1-426: Add test coverage to ensure workflow correctness.This file lacks tests verifying workflow behavior, error handling, or edge cases. Consider adding unit tests and integration tests for core methods (e.g.,
handlePlanResearch,handleResearch,handleReport) to ensure reliability over time.🧰 Tools
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[error] 121-121: Don't use '{}' as a type.
Prefer explicitly define the object shape. '{}' means "any non-nullable value".
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[error] 123-123: Don't use '{}' as a type.
Prefer explicitly define the object shape. '{}' means "any non-nullable value".
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templates/components/workflows/python/deep_research/README-template.md (2)
30-34: Production Deployment Command.
The instructions for running the production server are clear. For improved consistency, it’s recommended to add a language specifier (e.g.,shell) to the fenced code block.-``` +```shell
40-44: Use Case Description and Language Correction.
The use case section is informative. Note that the phrase "sending an request" should use "a request" (since “request” starts with a consonant sound).-You can start by sending an request on the [chat UI]... +You can start by sending a request on the [chat UI]...🧰 Tools
🪛 LanguageTool
[misspelling] ~44-~44: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ...a) directory. You can start by sending an request on the [chat UI](http://localho...(EN_A_VS_AN)
templates/components/workflows/python/agentic_rag/README-template.md (2)
30-34: Production Command with Consistency Note.
The production command is provided clearly. As a suggestion, add a language specifier (e.g.,shell) to the fenced code block to improve consistency with other code snippets.-``` +```shell
40-44: Use Case and Language Refinement.
The section describing the use case for the agentic RAG workflow is informative. Like the previous file, consider changing "an request" to "a request" for grammatical correctness.-You can start by sending an request on the [chat UI]... +You can start by sending a request on the [chat UI]...🧰 Tools
🪛 LanguageTool
[misspelling] ~44-~44: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ...a) directory. You can start by sending an request on the [chat UI](http://localho...(EN_A_VS_AN)
templates/components/workflows/typescript/financial_report/README-template.md (4)
1-9: Project Introduction and Setup Instructions.
The introduction clearly states that this project leverages LlamaIndex with Next.js and thecreate-llamabootstrap. However, the fenced code block fornpm installis missing a language specifier; adding one (e.g.,shell) would enhance clarity.-``` +```shell🧰 Tools
🪛 markdownlint-cli2 (0.17.2)
7-7: Fenced code blocks should have a language specified
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14-16: Embeddings Generation Command.
The command to generate embeddings is provided clearly; consider specifying the fenced block language to maintain consistency.-``` +```shell🧰 Tools
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20-24: Development Server Execution.
The instructions for running the development server are unambiguous. Adding a language specifier to the code block (e.g.,shell) is recommended for uniformity.-``` +```shell🧰 Tools
🪛 markdownlint-cli2 (0.17.2)
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36-42: Testing the API Endpoint.
The curl command example to test the/api/chatendpoint is well-detailed. As with earlier blocks, adding a language identifier (e.g.,shell) to this fenced code block would be ideal.-``` +```shell🧰 Tools
🪛 LanguageTool
[misspelling] ~36-~36: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ...ata](./data). You can start by sending an request on the [chat UI](http://localho...(EN_A_VS_AN)
templates/components/workflows/typescript/deep_research/README-template.md (5)
5-9: Dependency Installation Instructions.
The instructions for installing dependencies usingnpm installare clear; however, the fenced code block could benefit from a language specifier (shell).-``` +```shell
14-16: Generating Embeddings.
The command to generate the embeddings for the documents is easy to follow; adding a language specifier to the code block is recommended.-``` +```shell
20-24: Launching the Development Server.
Instructions for starting the development server (npm run dev) are clear; please add a language specifier for the code block to ensure consistency.-``` +```shell
32-35: Deep Research Use Case.
The use case description is clear and well-articulated. For consistency, review the phrasing (e.g., “sending a request” rather than “sending an request”) if applicable.-You can start by sending an request on the [chat UI]... +You can start by sending a request on the [chat UI]...
36-42: Curl Command for API Testing.
The curl command example is detailed and useful. Consider adding a language specifier (e.g.,shell) to the fenced code block for consistency.-``` +```shell🧰 Tools
🪛 LanguageTool
[misspelling] ~36-~36: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ...a) directory. You can start by sending an request on the [chat UI](http://localho...(EN_A_VS_AN)
templates/components/workflows/python/financial_report/README-template.md (2)
30-34: Production Deployment Command.
The production command is provided clearly. As seen in other sections, adding a language specifier (e.g.,shell) to the fenced code block is recommended for consistency.-``` +```shell
40-44: Financial Report Use Case.
The use case section clearly explains how to request a financial report. Please update "sending an request" to "sending a request" for grammatical consistency.-You can start by sending an request on the [chat UI]... +You can start by sending a request on the [chat UI]...🧰 Tools
🪛 LanguageTool
[misspelling] ~44-~44: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ...a) directory. You can start by sending an request on the [chat UI](http://localho...(EN_A_VS_AN)
templates/components/workflows/typescript/agentic_rag/README-template.md (2)
7-9: Specify language in fenced code blocks for enhanced readability.
Fenced code blocks on lines 7–9, 16–18, and 22–24 are missing a language identifier. Specifying a language (e.g.,bashorshell) ensures proper syntax highlighting and consistency with best markdown practices.Example diff for the first fenced block:
-``` +```bash npm install -``` +```Please apply analogous changes to the fenced blocks on lines 16 and 22.
Also applies to: 16-18, 22-24
🧰 Tools
🪛 markdownlint-cli2 (0.17.2)
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null(MD040, fenced-code-language)
36-36: Correct the article usage before "request".
The sentence on line 36 currently uses “an request” (if present) whereas “request” starts with a consonant sound and should be preceded by “a”.Proposed change:
-You can start by sending an request on the [chat UI](http://localhost:3000) or you can test the `/api/chat` endpoint with the following curl request: +You can start by sending a request on the [chat UI](http://localhost:3000) or you can test the `/api/chat` endpoint with the following curl request:🧰 Tools
🪛 LanguageTool
[misspelling] ~36-~36: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ...a) directory. You can start by sending an request on the [chat UI](http://localho...(EN_A_VS_AN)
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📒 Files selected for processing (11)
.github/workflows/e2e.yml(2 hunks)e2e/shared/llamaindexserver_template.spec.ts(4 hunks)helpers/env-variables.ts(5 hunks)llama-index-server/tests/api/test_event_stream.py(0 hunks)templates/components/workflows/python/agentic_rag/README-template.md(1 hunks)templates/components/workflows/python/deep_research/README-template.md(1 hunks)templates/components/workflows/python/financial_report/README-template.md(1 hunks)templates/components/workflows/typescript/agentic_rag/README-template.md(1 hunks)templates/components/workflows/typescript/deep_research/README-template.md(1 hunks)templates/components/workflows/typescript/deep_research/workflow.ts(1 hunks)templates/components/workflows/typescript/financial_report/README-template.md(1 hunks)
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- llama-index-server/tests/api/test_event_stream.py
🚧 Files skipped from review as they are similar to previous changes (3)
- .github/workflows/e2e.yml
- e2e/shared/llamaindexserver_template.spec.ts
- helpers/env-variables.ts
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📓 Path-based instructions (1)
`templates/**`: For files under the `templates` folder, do not report 'Missing Dependencies Detected' errors.
templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
templates/components/workflows/typescript/deep_research/README-template.mdtemplates/components/workflows/typescript/deep_research/workflow.tstemplates/components/workflows/python/agentic_rag/README-template.mdtemplates/components/workflows/python/deep_research/README-template.mdtemplates/components/workflows/python/financial_report/README-template.mdtemplates/components/workflows/typescript/agentic_rag/README-template.mdtemplates/components/workflows/typescript/financial_report/README-template.md
🪛 LanguageTool
templates/components/workflows/typescript/deep_research/README-template.md
[misspelling] ~36-~36: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
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(EN_A_VS_AN)
templates/components/workflows/python/agentic_rag/README-template.md
[misspelling] ~44-~44: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ...a) directory. You can start by sending an request on the [chat UI](http://localho...
(EN_A_VS_AN)
templates/components/workflows/python/deep_research/README-template.md
[misspelling] ~44-~44: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
Context: ...a) directory. You can start by sending an request on the [chat UI](http://localho...
(EN_A_VS_AN)
templates/components/workflows/python/financial_report/README-template.md
[misspelling] ~44-~44: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
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templates/components/workflows/typescript/agentic_rag/README-template.md
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templates/components/workflows/typescript/financial_report/README-template.md
[misspelling] ~36-~36: Use “a” instead of ‘an’ if the following word doesn’t start with a vowel sound, e.g. ‘a sentence’, ‘a university’.
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🪛 Biome (1.9.4)
templates/components/workflows/typescript/deep_research/workflow.ts
[error] 121-121: Don't use '{}' as a type.
Prefer explicitly define the object shape. '{}' means "any non-nullable value".
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[error] 123-123: Don't use '{}' as a type.
Prefer explicitly define the object shape. '{}' means "any non-nullable value".
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🪛 markdownlint-cli2 (0.17.2)
templates/components/workflows/typescript/agentic_rag/README-template.md
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🔇 Additional comments (37)
templates/components/workflows/typescript/deep_research/workflow.ts (2)
121-123: Refactor to avoid using{}as a type.This usage was previously flagged.
{}means any non-nullable value, obscuring future type checks. Use a more explicit shape (e.g.,Record<string, never>) for empty payloads or define a dedicated interface with meaningful fields if needed.🧰 Tools
🪛 Biome (1.9.4)
[error] 121-121: Don't use '{}' as a type.
Prefer explicitly define the object shape. '{}' means "any non-nullable value".
(lint/complexity/noBannedTypes)
[error] 123-123: Don't use '{}' as a type.
Prefer explicitly define the object shape. '{}' means "any non-nullable value".
(lint/complexity/noBannedTypes)
183-185: Sanitize or validate user input before storing in memory.This was mentioned before. If user input can be sensitive or untrusted, consider sanitizing or validating it before calling
this.memory.put({ role: "user", content: userInput }).templates/components/workflows/python/deep_research/README-template.md (8)
1-8: Clear Introduction and Context.
The opening lines effectively explain that this is a multi-agents project using LlamaIndex and Workflows, and they include useful links for further context.
9-11: Installation Instructions.
The installation command using Poetry is clearly presented within a shell code block. Verify that the command aligns with your project setup.
13-15: Environment Configuration Reminder.
The instructions to review the pre-configured parameters in the.envfile (particularly setting theOPENAI_API_KEY) are clear and prominent.
16-20: Embeddings Generation Command.
The command to generate document embeddings is straightforward and easy to follow.
22-26: Development Server Setup.
The steps to launch the development server are clearly outlined and follow the expected pattern.
36-38: LLM and Embedding Model Configuration.
Providing a link to the settings file for configuring the LLM and embedding model is very helpful for users.
45-50: Curl Command Example.
The example curl command for testing the/api/chatendpoint is well-formatted and clear.
52-60: Additional Resources.
The "Learn More" section effectively provides further reading and contributions links. The layout is clear and comprehensive.templates/components/workflows/python/agentic_rag/README-template.md (8)
1-8: Clear Introduction and Setup Instructions.
The introductory block clearly describes the agentic RAG project and includes a direct reference to the relevant Agent Workflows documentation.
9-11: Installation Command is Clear.
The code block for installing dependencies using Poetry is straightforward and easy to follow.
13-15: Environment Variables Setup.
The instructions emphasize checking the.envfile and setting theOPENAI_API_KEYwhich is crucial for the LLM integration.
16-20: Embeddings Generation.
The command to generate document embeddings is clearly given; this helps ensure that the documentation is actionable.
22-26: Development Server Instructions.
The steps to start the development server are presented consistently with the previous file, ensuring uniformity across templates.
36-38: LLM Configuration Section.
The pointers to configure the LLM and embedding model are clear and directly linked to the relevant settings file, making it easy to follow.
45-50: Example Curl Command.
The curl command example is clearly formatted and helps users test the/api/chatendpoint.
52-60: Resources for Further Learning.
The "Learn More" section is concise and provides useful links for additional reading and community feedback.templates/components/workflows/typescript/financial_report/README-template.md (5)
11-13: Environment Variable Configuration.
The instructions about the.envfile and setting up both theOPENAI_API_KEYandE2B_API_KEYare clear and complete.
26-26: Browser Access Instruction.
The instruction to open http://localhost:3000 is clear and direct.
28-30: LLM and Embedding Model Configuration.
Clear and useful instructions specific to LlamaIndexTS configurations are provided with relevant links.
32-34: Use Case Description.
The description of the financial report generation use case is clear.
44-53: Additional Resources and Feedback.
The "Learn More" section is well-organized and provides valuable links for further information and community participation.templates/components/workflows/typescript/deep_research/README-template.md (5)
1-3: Project Overview.
The introduction clearly identifies that the project is bootstrapped withcreate-llamaand provides a useful link to the tool.
11-13: Environment Setup and API Keys.
The guidance to check the.envfile and set theOPENAI_API_KEYis clear and direct.
26-26: Accessing the Chat UI.
The instruction to open http://localhost:3000 in a browser is concise and clear.
28-30: LLM and Embedding Model Settings.
The configuration instruction provides useful links and is easy to follow.
44-53: Further Learning and Resources.
The final section includes detailed and relevant links, inviting users to learn more and contribute.templates/components/workflows/python/financial_report/README-template.md (9)
1-8: Project Introduction.
The opening lines successfully position this as a multi-agents project using LlamaIndex along with Workflows, setting the right context.
9-11: Environment Setup with Poetry.
The installation step using Poetry is clearly shown in a shell code block and is easy to follow.
13-15: API Keys Configuration.
The instructions to check the.envfile and set bothOPENAI_API_KEYandE2B_API_KEY(with a link to obtain the key) are very helpful.
16-20: Generating Embeddings.
The command to generate document embeddings is clearly presented and easy to follow.
22-26: Launching the Development Server.
The process to run the development server is straightforward and clearly documented.
28-30: Accessing the Chat UI.
The instruction to launch the chat UI in a web browser is clear and direct.
36-38: LLM and Embedding Model Configuration.
The configuration section is complete with a reference to the settings file, which is very helpful.
45-51: Testing the Financial Report Endpoint.
The curl command example for testing the/api/chatendpoint is well-formatted and clear.
52-60: Additional Learning Resources.
The "Learn More" section effectively provides useful links and encourages feedback and contributions.
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Actionable comments posted: 1
🧹 Nitpick comments (1)
helpers/env-variables.ts (1)
239-384: Consider updating getModelEnvs to include template parameterWhile you've added conditional logic to skip calling
getModelEnvswhen the template is "llamaindexserver", it would be more consistent to update the function signature to include the template parameter, similar to what you did forgetVectorDBEnvsandgetFrameworkEnvs. This would allow for more granular conditional logic within the function if needed in the future.-const getModelEnvs = (modelConfig: ModelConfig): EnvVar[] => { +const getModelEnvs = (modelConfig: ModelConfig, template?: TemplateType): EnvVar[] => { // You could add conditional logic here if needed return [ ... ];
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🧬 Code Definitions (1)
helpers/env-variables.ts (1)
helpers/types.ts (1)
TemplateType(22-28)
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🔇 Additional comments (9)
helpers/env-variables.ts (9)
47-47: Good addition of the template parameterAdding the optional template parameter to
getVectorDBEnvsallows for more flexible environment variable configuration based on the template type, which aligns with the PR objective of simplifying app code for LlamaIndexServer.
172-182: Conditional NEXT_PUBLIC_USE_LLAMACLOUD inclusion looks goodThe conditional logic to exclude the NEXT_PUBLIC_USE_LLAMACLOUD environment variable when using the "llamaindexserver" template is appropriate. This aligns with the existing review comment about skipping certain configurations with LlamaIndexServer.
227-235: Framework-dependent storage cache configuration is appropriateThe conditional inclusion of STORAGE_CACHE_DIR based on the framework being used (excluding "fastapi") is a sensible approach, as FastAPI would handle storage differently.
392-406: Conditional FILESERVER_URL_PREFIX inclusion is goodConditionally including the FILESERVER_URL_PREFIX environment variable only when the template is not "llamaindexserver" helps simplify the configuration when using LlamaIndexServer, which is in line with the PR objective.
412-413: Improved environment variable descriptionsThe enhanced descriptions for APP_HOST and APP_PORT provide better clarity about their purpose.
Also applies to: 417-418
423-429: Conditional NEXT_PUBLIC_CHAT_API inclusion is appropriateThe additional check for template type before including the NEXT_PUBLIC_CHAT_API environment variable is consistent with the pattern of simplifying the configuration for LlamaIndexServer.
585-593: Good addition of LlamaCloud API key for LlamaParseAdding the LLAMA_CLOUD_API_KEY environment variable when useLlamaParse is true is a useful addition that provides the necessary configuration for the LlamaParse feature.
595-597: Appropriate skipping of model and engine envs for LlamaIndexServerExcluding the model and engine environment variables when using the "llamaindexserver" template makes sense as LlamaIndexServer would handle these configurations differently. This aligns with the previous review comment about skipping getModelEnvs for the new template.
598-599: Updated function calls to pass template parameterThe updates to include the template parameter in the function calls to getVectorDBEnvs and getFrameworkEnvs are necessary to support the new parameter additions.
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Actionable comments posted: 1
🧹 Nitpick comments (1)
templates/components/workflows/python/agentic_rag/workflow.py (1)
12-22: The workflow creation looks good but consider environment variable configuration.The implementation of
create_workflowfollows best practices with proper error handling and configuration. However, the AI summary mentions that the system prompt should be configurable through an environment variable, but the current implementation uses a hardcoded value.Consider updating the system prompt to be configurable via environment variables:
- return AgentWorkflow.from_tools_or_functions( - tools_or_functions=[query_tool], - llm=Settings.llm or OpenAI(model="gpt-4o-mini"), - system_prompt="You are a helpful assistant.", - ) + system_prompt = os.environ.get( + "AGENTIC_RAG_SYSTEM_PROMPT", "You are a helpful assistant." + ) + return AgentWorkflow.from_tools_or_functions( + tools_or_functions=[query_tool], + llm=Settings.llm or OpenAI(model="gpt-4o-mini"), + system_prompt=system_prompt, + )Note: If you implement this change, you'll need to keep the
osimport.
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`templates/**`: For files under the `templates` folder, do not report 'Missing Dependencies Detected' errors.
templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
templates/components/workflows/python/agentic_rag/workflow.py
🪛 Ruff (0.8.2)
templates/components/workflows/python/agentic_rag/workflow.py
1-1: os imported but unused
Remove unused import: os
(F401)
🪛 GitHub Actions: Lint on push or pull request
templates/components/workflows/python/agentic_rag/workflow.py
[error] 1-1: Unused import: 'os'. Remove unused import: os.
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templates/components/workflows/python/agentic_rag/workflow.py (1)
20-20: Good fallback mechanism for LLM configuration.The code properly checks for a configured LLM in settings before defaulting to the OpenAI model, which provides flexibility in how the application is configured.
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templates/components/workflows/python/agentic_rag/workflow.py (1)
11-21: Function implementation is clean and effective.The
create_workflowfunction is well-structured with proper type annotations, error handling, and a clear implementation. It creates an agent workflow with RAG capabilities using a query tool and OpenAI model.A minor enhancement suggestion would be to load the system prompt from an environment variable for easier customization without code changes.
+import os + def create_workflow(chat_request: Optional[ChatRequest] = None) -> AgentWorkflow: query_tool = get_query_engine_tool(index=get_index(chat_request=chat_request)) if query_tool is None: raise RuntimeError( "Index not found! Please run `poetry run generate` to index the data first." ) return AgentWorkflow.from_tools_or_functions( tools_or_functions=[query_tool], llm=Settings.llm or OpenAI(model="gpt-4o-mini"), - system_prompt="You are a helpful assistant.", + system_prompt=os.environ.get("AGENT_SYSTEM_PROMPT", "You are a helpful assistant."), )
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templates/components/workflows/python/agentic_rag/workflow.py (1)
1-9: Imports look well-organized and clear.The necessary imports are properly organized with appropriate spacing. I notice the
osimport from the previous version has been removed, addressing the linting error from the past review.
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templates/components/vectordbs/llamaindexserver/llamacloud/typescript/generate.ts (4)
1-2: Remove redundant dotenv configuration.
Currently, the code importsdotenvas a module, imports"dotenv/config", and also callsdotenv.config()again. This triple usage is unnecessary duplication. Consider using only one of these approaches to keep the code concise.-import * as dotenv from "dotenv"; -import "dotenv/config"; +import "dotenv/config"; // If you prefer explicit initialization, remove the above line and keep: -import "dotenv/config"; +import * as dotenv from "dotenv"; +dotenv.config();
34-47: Consider handling non-existent or inaccessible directories.
The current directory traversal code does not explicitly handle scenarios where "data" may be missing or inaccessible. Including a check for directory existence and handling potential errors gracefully would improve robustness.async function* walk(dir: string): AsyncGenerator<string> { + try { const directory = await fs.opendir(dir); for await (const dirent of directory) { const entryPath = path.join(dir, dirent.name); if (dirent.isDirectory()) { yield* walk(entryPath); } else if (dirent.isFile()) { yield entryPath; } } + } catch (error) { + console.warn(`Skipping inaccessible directory: ${dir}`); + } }
65-66: Consider verifying that “data” directory exists before traversal.
In some deployment setups, thedatadirectory may not exist or may be empty, leading to potential errors or wasted checks. Verifying its existence withfs.stator a try/catch could provide a clearer user experience.
91-101: Add test coverage for critical logic.
ThecheckRequiredEnvVars,walk, andloadAndIndexfunctions contain essential logic for validating environment setup and uploading documents. Consider adding unit or integration tests to prevent regressions and improve reliability.
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templates/components/vectordbs/llamaindexserver/llamacloud/typescript/generate.ts (2)
templates/components/vectordbs/llamaindexserver/llamacloud/typescript/index.ts (1)
getIndex(10-28)templates/types/llamaindexserver/nextjs/src/app/data.ts (1)
getIndex(7-22)
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templates/components/vectordbs/llamaindexserver/llamacloud/typescript/generate.ts (1)
6-7: Validate import paths for app modules.
These imports appear to reference files (./app/dataand./app/settings) that may not exist at this relative path, echoing a past review's concern. Ensure they actually resolve to the correct files or adjust the paths accordingly.
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templates/components/vectordbs/llamaindexserver/llamacloud/typescript/generate.ts (2)
2-2: Remove redundant dotenv.config()You are already invoking
dotenv.config()as a side effect in line 2 (import "dotenv/config";). Calling it again at line 9 is typically redundant. Removing one of these calls makes your code more consistent and avoids confusion.Here's a diff removing line 9:
import * as dotenv from "dotenv"; import "dotenv/config"; -dotenv.config();Also applies to: 9-9
66-86: Consider concurrent file uploads for large data directoriesUploading files one by one can be slow if you have many files. You could gather all file paths first, then upload them concurrently using
Promise.allor a controlled concurrency approach.Here's an example using
Promise.all:async function loadAndIndex() { const index = await getIndex(); ... - for await (const filePath of walk("data")) { - const buffer = await fs.readFile(filePath); - const filename = path.basename(filePath); - await LLamaCloudFileService.addFileToPipeline( - projectId, - pipelineId, - new File([buffer], filename), - ); - } + const filePaths = []; + for await (const filePath of walk("data")) { + filePaths.push(filePath); + } + + await Promise.all( + filePaths.map(async (fp) => { + const buffer = await fs.readFile(fp); + const filename = path.basename(fp); + await LLamaCloudFileService.addFileToPipeline( + projectId, + pipelineId, + new File([buffer], filename), + ); + }) + ); console.log(`Successfully uploaded documents to LlamaCloud!`); }
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templates/components/vectordbs/llamaindexserver/llamacloud/typescript/generate.ts (3)
templates/components/vectordbs/llamaindexserver/llamacloud/typescript/index.ts (1)
getIndex(10-28)templates/types/llamaindexserver/nextjs/src/app/data.ts (1)
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initSettings(4-11)
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🔇 Additional comments (1)
templates/components/vectordbs/llamaindexserver/llamacloud/typescript/generate.ts (1)
6-7: Import paths appear to be incorrectThe same concern from a previous review still applies here. The files
./app/dataand./app/settingsmight not exist relative to your current directory. Confirm that these paths are valid or update them to the correct locations.
templates/components/vectordbs/llamaindexserver/llamacloud/typescript/generate.ts
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New Features
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Bug Fixes