feat: Adds Qdrant Vector Search

[Anush008]

Description

This PR adds support for using Qdrant as a vector search provider in Honcho.

Qdrant is an open-source vector search engine built for high-performance and massive-scale.

Testing

I've unit tested this integration against a local Qdrant instance.

Setup

You can run Qdrant with

docker run -p 6333:6333 qdrant/qdrant

Then set,

VECTOR_STORE_TYPE=qdrant
VECTOR_STORE_QDRANT_URL=http://localhost:6333

The dashboard is accessible at http://localhost:6333/dashboard

Summary by CodeRabbit

• New Features
  • Qdrant is now supported as a vector store backend with configurable settings for connection URL, API key, protocol preferences (gRPC/HTTPS), port, and request timeout.

[coderabbitai]

No actionable comments were generated in the recent review. 🎉

ℹ️ Recent review info

⚙️ Run configuration

Configuration used: Organization UI

Review profile: CHILL

Plan: Pro

Run ID: 8123276b-acec-4181-812a-39dc61786d8c

📥 Commits

Reviewing files that changed from the base of the PR and between 256ed8c and d369e77.

⛔ Files ignored due to path filters (1)

• uv.lock is excluded by !**/*.lock

📒 Files selected for processing (7)

• .env.template
• README.md
• config.toml.example
• docs/v3/contributing/configuration.mdx
• pyproject.toml
• src/config.py
• src/vector_store/__init__.py

✅ Files skipped from review due to trivial changes (3)

• docs/v3/contributing/configuration.mdx
• .env.template
• config.toml.example

🚧 Files skipped from review as they are similar to previous changes (4)

• README.md
• src/vector_store/init.py
• pyproject.toml
• src/config.py

---

Walkthrough

This PR adds Qdrant as a supported vector store backend. Configuration settings are defined in the model, documented in templates and examples, the vector store implementation handles upsert/query/delete operations, the factory instantiates it conditionally, and documentation and changelog entries reflect the new capability.

Changes

Qdrant Vector Store Integration

Layer / File(s)	Summary
Configuration model and dependency src/config.py, pyproject.toml	VectorStoreSettings.TYPE adds "qdrant" as a Literal option; new fields define Qdrant-specific settings (URL, API key, PREFER_GRPC, GRPC_PORT, HTTPS, PREFIX, TIMEOUT). qdrant-client>=1.18.0 is added as a project dependency.
Configuration templates and examples .env.template, config.toml.example	Both files update type comments to include qdrant and provide commented configuration blocks for Qdrant connection parameters, matching the model definition.
QdrantVectorStore implementation src/vector_store/qdrant.py	New async class implements VectorStore interface: deterministic UUIDv5 point IDs, collection provisioning, upsert_many storing original _id in payload, query with filter support and distance conversion, delete_many, delete_namespace, and close.
Factory integration src/vector_store/__init__.py	_create_store_by_type recognizes store_type == "qdrant" and returns a QdrantVectorStore instance.
Documentation and release notes README.md, CHANGELOG.md, docs/changelog/introduction.mdx, docs/v3/contributing/configuration.mdx	User documentation and changelog entries are updated to list qdrant as a supported vector store; configuration documentation includes Qdrant-specific environment variables.

Estimated code review effort

🎯 3 (Moderate) | ⏱️ ~20 minutes

Poem

🐇 I nibble on configs, neat and spry,

Qdrant seeds the vectors high,
UUIDs hop in ordered rows,
Nearest neighbors strike a pose,
Hooray — the search field brightly grows!

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 10.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title 'feat: Adds Qdrant Vector Search' clearly and concisely summarizes the main change: adding Qdrant as a new vector search provider to the project.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

_{✏️ Tip: You can configure your own custom pre-merge checks in the settings.}

✨ Finishing Touches

🧪 Generate unit tests (beta)

• Create PR with unit tests

---

Thanks for using CodeRabbit! It's free for OSS, and your support helps us grow. If you like it, consider giving us a shout-out.

❤️ Share

• X
• Mastodon
• Reddit
• LinkedIn

_{Comment @coderabbitai help to get the list of available commands and usage tips.}

[coderabbitai]

Actionable comments posted: 1

🧹 Nitpick comments (1)

src/vector_store/qdrant.py (1)

20-21: 💤 Low value

Consider documenting the UUID namespace choice.

The function uses uuid.NAMESPACE_DNS to generate deterministic UUIDs. While this works correctly, a brief comment explaining why NAMESPACE_DNS was chosen (or noting that any fixed namespace would work) would help future maintainers understand this is an arbitrary but consistent choice.

🤖 Prompt for AI Agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@src/vector_store/qdrant.py` around lines 20 - 21, The helper _point_id uses
uuid.uuid5 with uuid.NAMESPACE_DNS to produce deterministic IDs but lacks
explanation; add a short comment above the _point_id function (or inline)
stating that NAMESPACE_DNS is chosen only as a fixed, arbitrary namespace for
deterministic UUIDv5 generation and that any constant namespace would work, so
maintainers understand the choice (reference: function _point_id).

🤖 Prompt for all review comments with AI agents

Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@src/vector_store/qdrant.py`:
- Around line 66-138: Add Google-style docstrings to each public method
upsert_many, query, delete_many, delete_namespace, and close in the Qdrant
vector store class: for each method document Args (types and description for
namespace, vectors, embedding, top_k, filters, max_distance, ids), Returns
(e.g., list[VectorQueryResult] or None), and Raises (e.g., VectorStoreError on
failures or any exceptions propagated), and include brief summary line and any
notes about side effects (creates collection in upsert_many, filters applied in
query). Ensure docstrings follow Google style (one-line summary, blank line,
Args/Returns/Raises sections) and reference types used in the file such as
VectorRecord and VectorQueryResult.

---

Nitpick comments:
In `@src/vector_store/qdrant.py`:
- Around line 20-21: The helper _point_id uses uuid.uuid5 with
uuid.NAMESPACE_DNS to produce deterministic IDs but lacks explanation; add a
short comment above the _point_id function (or inline) stating that
NAMESPACE_DNS is chosen only as a fixed, arbitrary namespace for deterministic
UUIDv5 generation and that any constant namespace would work, so maintainers
understand the choice (reference: function _point_id).

🪄 Autofix (Beta)

Fix all unresolved CodeRabbit comments on this PR:

• Push a commit to this branch (recommended)
• Create a new PR with the fixes

---

ℹ️ Review info

⚙️ Run configuration

Configuration used: Organization UI

Review profile: CHILL

Plan: Pro

Run ID: 6f79ae20-91f2-4cab-a8c9-74563de256f5

📥 Commits

Reviewing files that changed from the base of the PR and between a420264 and 256ed8c.

⛔ Files ignored due to path filters (1)

• uv.lock is excluded by !**/*.lock

📒 Files selected for processing (10)

• .env.template
• CHANGELOG.md
• README.md
• config.toml.example
• docs/changelog/introduction.mdx
• docs/v3/contributing/configuration.mdx
• pyproject.toml
• src/config.py
• src/vector_store/__init__.py
• src/vector_store/qdrant.py

[Anush008]

Hi @VVoruganti

Just bumping this PR. Please take a look when possible.