**Description:** This is like the rag-conversation template in many
ways. What's different is:
- support for a timescale vector store.
- support for time-based filters.
- support for metadata filters.
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
# Astra DB Vector store integration
- **Description:** This PR adds a `VectorStore` implementation for
DataStax Astra DB using its HTTP API
- **Issue:** (no related issue)
- **Dependencies:** A new required dependency is `astrapy` (`>=0.5.3`)
which was added to pyptoject.toml, optional, as per guidelines
- **Tag maintainer:** I recently mentioned to @baskaryan this
integration was coming
- **Twitter handle:** `@rsprrs` if you want to mention me
This PR introduces the `AstraDB` vector store class, extensive
integration test coverage, a reworking of the documentation which
conflates Cassandra and Astra DB on a single "provider" page and a new,
completely reworked vector-store example notebook (common to the
Cassandra store, since parts of the flow is shared by the two APIs). I
also took care in ensuring docs (and redirects therein) are behaving
correctly.
All style, linting, typechecks and tests pass as far as the `AstraDB`
integration is concerned.
I could build the documentation and check it all right (but ran into
trouble with the `api_docs_build` makefile target which I could not
verify: `Error: Unable to import module
'plan_and_execute.agent_executor' with error: No module named
'langchain_experimental'` was the first of many similar errors)
Thank you for a review!
Stefano
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
- **Description:** Correct naming for package in README
- **Issue:** README wasn't aligned with pyproject.toml, resulting in not
being able to install the rag-supabase package.
- **Tag maintainer:** @gregnr
This PR adds a self-querying template using Qdrant as a vector store.
The template uses an artificial dataset and was implemented in a way
that simplifies passing different components and choosing LLM and
embedding providers.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
# Description
Add a RAG template showcasing Momento Vector Index as a vector store.
Includes a project directory and README.
# **Twitter handle**
Tag the company @momentohq for a mention and @mlonml for the
contribution.
This change adds a new template for simple RAG using the SingleStoreDB
vectorstore.
Twitter: @alexjpeng
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
**Description:** This template creates an agent that transforms a single
LLM into a cognitive synergist by engaging in multi-turn
self-collaboration with multiple personas.
**Tag maintainer:** @hwchase17
---------
Co-authored-by: Sayandip Sarkar <sayandip.sarkar@skypointcloud.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
- a few instructions in the readme (load_documents -> ingest.py)
- added docker run command for local elastic
- adds input type definition to render playground properly
<!-- Thank you for contributing to LangChain!
Replace this entire comment with:
- **Description:** a description of the change,
- **Issue:** the issue # it fixes (if applicable),
- **Dependencies:** any dependencies required for this change,
- **Tag maintainer:** for a quicker response, tag the relevant
maintainer (see below),
- **Twitter handle:** we announce bigger features on Twitter. If your PR
gets announced, and you'd like a mention, we'll gladly shout you out!
Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally.
See contribution guidelines for more information on how to write/run
tests, lint, etc:
https://github.com/langchain-ai/langchain/blob/master/.github/CONTRIBUTING.md
If you're adding a new integration, please include:
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in `docs/extras`
directory.
If no one reviews your PR within a few days, please @-mention one of
@baskaryan, @eyurtsev, @hwchase17.
-->
---------
Co-authored-by: Matvey Arye <mat@timescale.com>
This PR addresses what seems like a unnecessary Python version
restriction in the pyroject.toml specs within both Cassandra (/Astra DB)
templates. With "^3.11" I got some version incompatibilities with the
latest "langchain add [...]" commands, so these are now relaxed in line
with the other templates I could inspect.
Incidentally, in the "entomology" template, the need for an explicit
"setup" step for the user to carry on has been removed, replaced by a
check-and-execute-if-necessary instruction on app startup.
Thank you for your attention!
Ran the following bash script for all templates
```bash
#!/bin/bash
set -e
current_dir="$(pwd)"
for directory in */; do
if [ -d "$directory" ]; then
(cd "$directory" && poetry lock --no-update)
fi
done
cd "$current_dir"
```
Co-authored-by: Bagatur <baskaryan@gmail.com>
Add Redis langserve template! Eventually will add semantic caching to
this too. But I was struggling to get that to work for some reason with
the LCEL implementation here.
- **Description:** Introduces the Redis LangServe template. A simple RAG
based app built on top of Redis that allows you to chat with company's
public financial data (Edgar 10k filings)
- **Issue:** None
- **Dependencies:** The template contains the poetry project
requirements to run this template
- **Tag maintainer:** @baskaryan @Spartee
- **Twitter handle:** @tchutch94
**Note**: this requires the commit here that deletes the
`_aget_relevant_documents()` method from the Redis retriever class that
wasn't implemented. That was breaking the langserve app.
---------
Co-authored-by: Sam Partee <sam.partee@redis.com>
Updates the bedrock rag template.
- Removes pinecone and replaces with FAISS as the vector store
- Fixes the environment variables, setting defaults
- Adds a `main.py` test file quick sanity testing
- Updates README.md with correct instructions
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
