victor-research
Research vertical for Victor AI - Web research, information gathering, and knowledge synthesis
Features
🔍 Web Research Deep web searches with multiple sources Academic paper discovery
Fact checking and verification 📚 Knowledge Synthesis Literature review automation
Competitive analysis Trend identification 📊 Information Management
Source citation and attribution Research note organization Bibliography generation
Installation
# Install with Victor core
pip install victor-ai
# Install research vertical
pip install victor-research
Quick Start
from victor.framework import Agent
# Create agent with research vertical
agent = await Agent.create(
provider="anthropic",
model="claude-3-opus-20240229",
vertical="research"
)
Available Tools
Once installed, the research vertical provides these tools:
- web_search - Search the web
- web_fetch - Fetch and extract content
- deep_research - Multi-step research
- fact_check - Verify claims
License
Apache License 2.0 - see LICENSE for details.
Links
- Victor AI: https://github.com/vijay-singh/codingagent
- Documentation: https://docs.victor.dev/verticals/research
- Victor Registry: https://github.com/anvai-labs/victor-registry
1 maintainer
Metadata
1 maintainer
Release files for victor-research 0.7.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| victor_research-0.7.2.tar.gz | 58.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| victor_research-0.7.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 120.8 kB
Release files / victor_research-0.7.2.tar.gz
| Download URL | victor_research-0.7.2.tar.gz |
|---|---|
| Size | 58.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Yes |
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twine/6.1.0 CPython/3.13.12
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Transparency logRelease files / victor_research-0.7.2-py3-none-any.whl
| Download URL | victor_research-0.7.2-py3-none-any.whl |
|---|---|
| Size | 62.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.12
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jul 17, 2026.
Transparency log
