daxa-ai / pebblo Goto Github PK

Create a Dockerfile for pebblo to quickly run pebblo in a containerized environment.

Tasks:

• Add Pebblo Dockerfile
• CI: Add docker image push on release/tag

1. Separate findings for entities list.
2. Separate findings for topics list.
3. Timezone for reports.

As of pebblo 0.1.7, we have good information about current state of the app loading. It would be useful to capture history of last 5 loads of the app.
This will give below information about each load:

• Location of the report and report file name
• How many findings were there in that report
• How many files were there with findings
• When the report was generated.

1. Display Pebblo version and Pebblo client versions on JSON Schema and Reports

Description: By using context words, it increases result score by matching the text coming from a specific column or a specific user input.
PR: #204

Feature: Document snippet anonymizer

Anonymize document snippets in Pebblo report. As Pebblo is considered for environments beyond dev, anonymization will help distribute the report to more app stakeholders.

Description

Pebblo currently supports LangChain RAG apps. Extend the client to support another popular RAG development framework: LlamaIndex.

https://www.llamaindex.ai/

Components

• Pebblo SafeLoader for LlamaIndex

• Pebblo server is failing on conda environment due to Pango(WeasyPrint) dependency issue
• Once Pebblo installation is completed and user tries to run Pebblo
• Below runtime error occurs -
  WeasyPrint could not import some external libraries. Please carefully follow the installation steps before reporting an issue: https://doc.courtbouillon.org/weasyprint/stable/first_steps.html#installation https://doc.courtbouillon.org/weasyprint/stable/first_steps.html#troubleshooting
• Please refer below screenshot for complete error message:

Pebblo (as of 0.1.12 version) supports single data source. Having support multiple data sources within single RAG application would be a good feature.

Description:
When I have multiple data sources to be used in my app, I should be able to see all those data sources and their details in the pebblo report.

As part of this feature, following changes would need to be done in the report:

1. Report Summary: Aggregate details about all data data sources.
2. Top Files With Most Findings: Add new column to show to which data source the file belongs.
3. Data Source: It would show snippets about all data sources.

Description

When execute RAG app, we are getting error "unable to reach pebblo server." but it is generating report as expected on Pebblo Server.

Error message
$ python3 fin_corp_rag_app.py
Loading RAG documents ...
Unable to reach pebblo server.
Loaded 93 documents ...

Hydrating Vector DB ...
Finished hydrating Vector DB ...

Expected behavior
It should call Pebblo APIs and pdf report should get generated without any error.

Additional context
Pebblo server was healthy when this error occured.

System:

• OS: Mac
• GPU/CPU:
• Pebblo version (commit or version number): 0.1.11
• Langchain version: 0.1.9
• DocumentStore:
• Reader:
• Retriever:

As of pebblo 0.1.9, we have only pebblo_report.pdf as output of the pebblo package.
It would be useful if we can have simple UI running locally on pebblo server which will show all apps discovered, giving details about each app(equivalent to pebblo_report.pdf).

Runtime:loacal is not adding any value in final report.
Instead we can have OS:os_name or OS:os_name:os_version

Description:

• Once Pebblo installation is completed and user tries to run Pebblo
• Below runtime error occurs - OSError: [E050] can't find model en_core_web_lg
• Using Ubuntu VM with Ubuntu 22.04
• Please refer below screenshot for complete error message: