| Name | pebblo JSON |
| Version |
0.1.15
JSON |
| download |
| home_page | None |
| Summary | Pebblo Gen-AI Data Analyzer |
| upload_time | 2024-05-07 02:02:17 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.9 |
| license | None |
| keywords |
langchain
ai
rag
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<p align="center">
<img src="https://github.com/daxa-ai/pebblo/blob/main/docs/gh_pages/static/img/pebblo-logo-name.jpg?raw=true" />
</p>
---
[](https://github.com/daxa-ai/pebblo)
[](http://opensource.org/licenses/MIT)
[](https://daxa-ai.github.io/pebblo/)
[](https://pypi.org/project/pebblo/)
[](https://discord.gg/wyAfaYXwwv)
[](https://twitter.com/daxa_ai)
---
**Pebblo** enables developers to safely load data and promote their Gen AI app to deployment without worrying about the organization’s compliance and security requirements. The project identifies semantic topics and entities found in the loaded data and summarizes them on the UI or a PDF report.
Pebblo has two components.
1. Pebblo Server - a REST api application with topic-classifier, entity-classifier and reporting features
1. Pebblo Safe DataLoader - a thin wrapper to Gen-AI framework's data loaders
## Pebblo Server
### Installation
#### Using `pip`
```bash
pip install pebblo --extra-index-url https://packages.daxa.ai/simple/
```
#### Download python package
Alternatively, download and install the latest Pebblo python `.whl` package from URL https://packages.daxa.ai/pebblo/0.1.13/pebblo-0.1.13-py3-none-any.whl
Example:
```bash
curl -LO "https://packages.daxa.ai/pebblo/0.1.13/pebblo-0.1.13-py3-none-any.whl"
pip install pebblo-0.1.13-py3-none-any.whl
```
### Run Pebblo Server
```bash
pebblo
```
Pebblo Server now listens to `localhost:8000` to accept Gen-AI application data snippets for inspection and reporting.
##### Pebblo Optional Flags
- `--config <file>`: specify a configuration file in yaml format.
See [configuration](docs/gh_pages/docs/config.md) guide for knobs to control Pebblo Server behavior like enabling snippet anonymization, selecting specific report renderer, etc.
### Using Docker
```bash
docker run -p 8000:8000 docker.daxa.ai/daxaai/pebblo
```
Local UI can be accessed by pointing the browser to `https://localhost:8000`.
See [installation](docs/gh_pages/docs/installation.md) guide for details on how to pass custom config.yaml and accessing PDF reports in the host machine.
### Troubleshooting
Refer to [troubleshooting](docs/gh_pages/docs/troubleshooting.md) guide.
## Pebblo Safe DataLoader
### Langchain
`Pebblo Safe DataLoader` is natively supported in Langchain framework. It is available in Langchain versions `>=0.1.7`
#### Enable Pebblo in Langchain Application
Add `PebbloSafeLoader` wrapper to the existing Langchain document loader(s) used in the RAG application. `PebbloSafeLoader` is interface compatible with Langchain `BaseLoader`. The application can continue to use `load()` and `lazy_load()` methods as it would on an Langchain document loader.
Here is the snippet of Lanchain RAG application using `CSVLoader` before enabling `PebbloSafeLoader`.
```python
from langchain.document_loaders.csv_loader import CSVLoader
loader = CSVLoader(file_path)
documents = loader.load()
vectordb = Chroma.from_documents(documents, OpenAIEmbeddings())
```
The Pebblo SafeLoader can be enabled with few lines of code change to the above snippet.
```python
from langchain.document_loaders.csv_loader import CSVLoader
from langchain_community.document_loaders.pebblo import PebbloSafeLoader
loader = PebbloSafeLoader(
CSVLoader(file_path),
name="acme-corp-rag-1", # App name (Mandatory)
owner="Joe Smith", # Owner (Optional)
description="Support productivity RAG application", # Description (Optional)
)
documents = loader.load()
vectordb = Chroma.from_documents(documents, OpenAIEmbeddings())
```
See [here](https://github.com/srics/pebblo/tree/main/pebblo_safeloader) for samples with Pebblo enabled RAG applications and [this](https://daxa-ai.github.io/pebblo/rag) document for more details.
# Contribution
Pebblo is a open-source community project. If you want to contribute see [Contributor Guidelines](https://github.com/daxa-ai/pebblo/blob/main/CONTRIBUTING.md) for more details.
# License
Pebblo is released under the MIT License
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"description": "<p align=\"center\">\n <img src=\"https://github.com/daxa-ai/pebblo/blob/main/docs/gh_pages/static/img/pebblo-logo-name.jpg?raw=true\" />\n</p>\n\n---\n[](https://github.com/daxa-ai/pebblo)\n[](http://opensource.org/licenses/MIT)\n[](https://daxa-ai.github.io/pebblo/)\n\n[](https://pypi.org/project/pebblo/)\n\n\n\n[](https://discord.gg/wyAfaYXwwv)\n[](https://twitter.com/daxa_ai)\n---\n\n\n**Pebblo** enables developers to safely load data and promote their Gen AI app to deployment without worrying about the organization\u2019s compliance and security requirements. The project identifies semantic topics and entities found in the loaded data and summarizes them on the UI or a PDF report.\n\nPebblo has two components.\n\n1. Pebblo Server - a REST api application with topic-classifier, entity-classifier and reporting features\n1. Pebblo Safe DataLoader - a thin wrapper to Gen-AI framework's data loaders\n\n## Pebblo Server\n\n### Installation\n \n#### Using `pip`\n\n```bash\npip install pebblo --extra-index-url https://packages.daxa.ai/simple/\n```\n\n#### Download python package\nAlternatively, download and install the latest Pebblo python `.whl` package from URL https://packages.daxa.ai/pebblo/0.1.13/pebblo-0.1.13-py3-none-any.whl\n\nExample:\n```bash\ncurl -LO \"https://packages.daxa.ai/pebblo/0.1.13/pebblo-0.1.13-py3-none-any.whl\" \npip install pebblo-0.1.13-py3-none-any.whl\n```\n### Run Pebblo Server\n\n```bash\npebblo\n```\n\nPebblo Server now listens to `localhost:8000` to accept Gen-AI application data snippets for inspection and reporting.\n\n##### Pebblo Optional Flags\n\n- `--config <file>`: specify a configuration file in yaml format.\n\n\nSee [configuration](docs/gh_pages/docs/config.md) guide for knobs to control Pebblo Server behavior like enabling snippet anonymization, selecting specific report renderer, etc.\n\n### Using Docker\n\n```bash\ndocker run -p 8000:8000 docker.daxa.ai/daxaai/pebblo\n```\n\nLocal UI can be accessed by pointing the browser to `https://localhost:8000`.\n\nSee [installation](docs/gh_pages/docs/installation.md) guide for details on how to pass custom config.yaml and accessing PDF reports in the host machine.\n\n### Troubleshooting\n\nRefer to [troubleshooting](docs/gh_pages/docs/troubleshooting.md) guide.\n\n## Pebblo Safe DataLoader\n\n### Langchain\n\n`Pebblo Safe DataLoader` is natively supported in Langchain framework. It is available in Langchain versions `>=0.1.7`\n\n#### Enable Pebblo in Langchain Application\n\nAdd `PebbloSafeLoader` wrapper to the existing Langchain document loader(s) used in the RAG application. `PebbloSafeLoader` is interface compatible with Langchain `BaseLoader`. The application can continue to use `load()` and `lazy_load()` methods as it would on an Langchain document loader.\n\nHere is the snippet of Lanchain RAG application using `CSVLoader` before enabling `PebbloSafeLoader`.\n\n```python\n from langchain.document_loaders.csv_loader import CSVLoader\n\n loader = CSVLoader(file_path)\n documents = loader.load()\n vectordb = Chroma.from_documents(documents, OpenAIEmbeddings())\n```\n\nThe Pebblo SafeLoader can be enabled with few lines of code change to the above snippet.\n\n```python\n from langchain.document_loaders.csv_loader import CSVLoader\n from langchain_community.document_loaders.pebblo import PebbloSafeLoader\n\n loader = PebbloSafeLoader(\n CSVLoader(file_path),\n name=\"acme-corp-rag-1\", # App name (Mandatory)\n owner=\"Joe Smith\", # Owner (Optional)\n description=\"Support productivity RAG application\", # Description (Optional)\n )\n documents = loader.load()\n vectordb = Chroma.from_documents(documents, OpenAIEmbeddings())\n```\n\nSee [here](https://github.com/srics/pebblo/tree/main/pebblo_safeloader) for samples with Pebblo enabled RAG applications and [this](https://daxa-ai.github.io/pebblo/rag) document for more details.\n\n# Contribution\n\nPebblo is a open-source community project. If you want to contribute see [Contributor Guidelines](https://github.com/daxa-ai/pebblo/blob/main/CONTRIBUTING.md) for more details.\n\n# License\n\nPebblo is released under the MIT License\n",
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