Apache
/
nifi
mirror of https://github.com/apache/nifi.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

NIFI-12646 Set Python Processor versions to 2.0.0-SNAPSHOT

This commit is contained in:
exceptionfactory 2024-01-29 08:12:42 -06:00
parent da9aa33bf1
commit dff7ea3535
No known key found for this signature in database
GPG Key ID: 29B6A52D2AAE8DBA
7 changed files with 7 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
nifi-python-extensions/nifi-openai-module/src/main/python/PromptChatGPT.py
View File

@ -30,7 +30,7 @@ class PromptChatGPT(FlowFileTransform):
implements = ['org.apache.nifi.python.processor.FlowFileTransform']
class ProcessorDetails:
version = '2.0.0-M2'
version = '2.0.0-SNAPSHOT'
description = "Submits a prompt to ChatGPT, writing the results either to a FlowFile attribute or to the contents of the FlowFile"
tags = ["text", "chatgpt", "gpt", "machine learning", "ML", "artificial intelligence", "ai", "document", "langchain"]
dependencies = ['langchain==0.0.331', 'openai==0.28.1', 'jsonpath-ng']

2
nifi-python-extensions/nifi-text-embeddings-module/src/main/python/ChunkDocument.py
View File

@ -104,7 +104,7 @@ class ChunkDocument(FlowFileTransform):
class Java:
implements = ['org.apache.nifi.python.processor.FlowFileTransform']
class ProcessorDetails:
version = '2.0.0-M2'
version = '2.0.0-SNAPSHOT'
description = """Chunks incoming documents that are formatted as JSON Lines into chunks that are appropriately sized for creating Text Embeddings.
The input is expected to be in "json-lines" format, with each line having a 'text' and a 'metadata' element.
Each line will then be split into one or more lines in the output."""

2
nifi-python-extensions/nifi-text-embeddings-module/src/main/python/ParseDocument.py
View File

@ -45,7 +45,7 @@ class ParseDocument(FlowFileTransform):
implements = ["org.apache.nifi.python.processor.FlowFileTransform"]
class ProcessorDetails:
version = "2.0.0-M2"
version = "2.0.0-SNAPSHOT"
description = """Parses incoming unstructured text documents and performs optical character recognition (OCR) in order to extract text from PDF and image files.
The output is formatted as "json-lines" with two keys: 'text' and 'metadata'.
Note that use of this Processor may require significant storage space and RAM utilization due to third-party dependencies necessary for processing PDF and image files.

2
nifi-python-extensions/nifi-text-embeddings-module/src/main/python/vectorstores/PutChroma.py
View File

@ -26,7 +26,7 @@ class PutChroma(FlowFileTransform):
implements = ['org.apache.nifi.python.processor.FlowFileTransform']
class ProcessorDetails:
version = '2.0.0-M2'
version = '2.0.0-SNAPSHOT'
description = """Publishes JSON data to a Chroma VectorDB. The Incoming data must be in single JSON per Line format, each with two keys: 'text' and 'metadata'.
The text must be a string, while metadata must be a map with strings for values. Any additional fields will be ignored. If the collection name specified
does not exist, the Processor will automatically create the collection."""

2
nifi-python-extensions/nifi-text-embeddings-module/src/main/python/vectorstores/PutPinecone.py
View File

@ -52,7 +52,7 @@ class PutPinecone(FlowFileTransform):
implements = ['org.apache.nifi.python.processor.FlowFileTransform']
class ProcessorDetails:
version = '2.0.0-M2'
version = '2.0.0-SNAPSHOT'
description = """Publishes JSON data to Pinecone. The Incoming data must be in single JSON per Line format, each with two keys: 'text' and 'metadata'.
The text must be a string, while metadata must be a map with strings for values. Any additional fields will be ignored."""
tags = ["pinecone", "vector", "vectordb", "vectorstore", "embeddings", "ai", "artificial intelligence", "ml", "machine learning", "text", "LLM"]

2
nifi-python-extensions/nifi-text-embeddings-module/src/main/python/vectorstores/QueryChroma.py
View File

@ -27,7 +27,7 @@ class QueryChroma(FlowFileTransform):
implements = ['org.apache.nifi.python.processor.FlowFileTransform']
class ProcessorDetails:
version = '2.0.0-M2'
version = '2.0.0-SNAPSHOT'
description = "Queries a Chroma Vector Database in order to gather a specified number of documents that are most closely related to the given query."
tags = ["chroma", "vector", "vectordb", "embeddings", "enrich", "enrichment", "ai", "artificial intelligence", "ml", "machine learning", "text", "LLM"]

2
nifi-python-extensions/nifi-text-embeddings-module/src/main/python/vectorstores/QueryPinecone.py
View File

@ -27,7 +27,7 @@ class QueryPinecone(FlowFileTransform):
implements = ['org.apache.nifi.python.processor.FlowFileTransform']
class ProcessorDetails:
version = '2.0.0-M2'
version = '2.0.0-SNAPSHOT'
description = "Queries Pinecone in order to gather a specified number of documents that are most closely related to the given query."
tags = ["pinecone", "vector", "vectordb", "vectorstore", "embeddings", "ai", "artificial intelligence", "ml", "machine learning", "text", "LLM"]