This PR:
- Updates Vectara component by @JAtharva22
- Adds Ollama components by @yamonkjd
- Fixes bugs in the canvas by @Cristhianzl
- adds Docker image builds on release.
### Pull Request for Issue #1246
**Description**,
This pull request addresses issue #1246, which proposes the addition of
a self-query retriever according to the LangChain Vectara integration.
The self-query retriever aims to empower users with the ability to
perform queries directly within the Vectara component(vector store).
**Changes Made**
I have added one more file under
`src\backend\langflow\components\retrievers` which contains a new
VectaraSelfQueryRetriverComponent class
**Files Added:** VectaraSelfQueryRetriever.py
**langchain documentation for this component:**
https://python.langchain.com/docs/integrations/retrievers/self_query/vectara_self_query
This pull request adds a Dockerfile for building and pushing the application image. The Dockerfile includes the necessary steps to set up the environment, install dependencies, and run the application.
fix(dropdownComponent): add condition to check if options object is
empty before rendering dropdown component
fix(chatInput): add condition to check if chatValue is an empty object
before displaying message
fix(chatMessage): remove useMemo hook and fix condition to check if chat
message is empty before displaying message
fix(formModal): add conditions to check if thought and files exist
before updating chat object
fix(genericModal): add condition to check if inputVariables exist before
displaying notice or success message
fix(chatInput): add condition to check if chatValue is an empty object before displaying message
fix(chatMessage): remove useMemo hook and fix condition to check if chat message is empty before displaying message
fix(formModal): add conditions to check if thought and files exist before updating chat object
fix(genericModal): add condition to check if inputVariables exist before displaying notice or success message
### Pull Request for Issue #1217
[feature
request](https://github.com/logspace-ai/langflow/labels/feature%20request)
[python](https://github.com/logspace-ai/langflow/labels/python)
**Description**
This pull request addresses issue #1217 , which concerns the ability to
add files directly to the Vectara vector store using the indexing API's
file upload feature.
**Changes Made**
I have implemented the ability to add files directly to the Vectara
vector store by providing URLs of documents online. The add_files()
method (as well as from_files()) has been added to facilitate this
functionality.
**Files Modified/Added**
Modified: vectara.py
