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deep-searcher

Route DeepSearcher workflows for provider setup, data ingestion, RAG querying, CLI and service operation, and evaluation.

The English summary is being prepared. Showing the original description.

Works withOpenAI
See how to install

Files included (35)

  • SKILL.md4.6 KB
  • references/installation-and-compatibility.md2.1 KB
  • references/repo-provenance.md1.4 KB
  • references/repo-routing-metadata.json499 B
  • references/troubleshooting.md2.8 KB
  • scripts/check_deepsearcher_environment.py6.1 KB
  • sub-skills/cli-and-service/references/cli-reference.md1.7 KB
  • sub-skills/cli-and-service/references/service-reference.md2.7 KB
  • sub-skills/cli-and-service/references/troubleshooting.md2.3 KB
  • sub-skills/cli-and-service/scripts/check_cli_help.py8.5 KB
  • sub-skills/cli-and-service/scripts/check_service_routes.py2.7 KB
  • sub-skills/cli-and-service/scripts/serve_deepsearcher_api.py7.6 KB
  • sub-skills/cli-and-service/SKILL.md3.0 KB
  • sub-skills/data-ingestion/references/data-formats-and-chunking.md7.2 KB
  • sub-skills/data-ingestion/references/local-loading.md6.8 KB
  • sub-skills/data-ingestion/references/troubleshooting.md7.9 KB
  • sub-skills/data-ingestion/references/web-loading.md6.3 KB
  • sub-skills/data-ingestion/scripts/validate_ingestion_inputs.py13.3 KB
  • sub-skills/data-ingestion/SKILL.md3.7 KB
  • sub-skills/evaluation/references/data-formats.md6.2 KB
  • sub-skills/evaluation/references/evaluation-workflow.md7.6 KB
  • sub-skills/evaluation/references/troubleshooting.md7.7 KB
  • sub-skills/evaluation/scripts/check_evaluation_inputs.py14.7 KB
  • sub-skills/evaluation/SKILL.md5.7 KB
  • sub-skills/provider-configuration/references/configuration-workflows.md3.8 KB
  • sub-skills/provider-configuration/references/provider-matrix.md5.6 KB
  • sub-skills/provider-configuration/references/troubleshooting.md2.3 KB
  • sub-skills/provider-configuration/scripts/validate_provider_config.py13.3 KB
  • sub-skills/provider-configuration/SKILL.md3.5 KB
  • sub-skills/rag-query/references/agent-behavior.md8.0 KB
  • sub-skills/rag-query/references/api-reference.md7.3 KB
  • sub-skills/rag-query/references/troubleshooting.md8.8 KB
  • sub-skills/rag-query/references/workflows.md7.8 KB
  • sub-skills/rag-query/scripts/mock_rag_smoke.py9.3 KB
  • sub-skills/rag-query/SKILL.md3.1 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

DeepSearcher

Use this repo skill when a task mentions the DeepSearcher package, its deepsearcher console command, document loading, website crawling, retrieval-augmented querying, the HTTP service, or the evaluation workflow. The skill is split into focused sub-skills so future agents can jump straight to the right workflow without reopening the original checkout.

Start here

User intentRead
Pick LLM, embedding, loader, crawler, or vector DB providers; diagnose missing SDKs or credentialssub-skills/provider-configuration/SKILL.md
Load local files/directories or websites into a collectionsub-skills/data-ingestion/SKILL.md
Ask questions over loaded data, choose DeepSearch vs ChainOfRAG vs NaiveRAG, or inspect retrieved referencessub-skills/rag-query/SKILL.md
Use the deepsearcher CLI or the bundled FastAPI service helpersub-skills/cli-and-service/SKILL.md
Validate or run the 2WikiMultiHopQA retrieval evaluation workflowsub-skills/evaluation/SKILL.md

Package facts to keep in mind

  • Distribution: deepsearcher.
  • Version inspected for this skill: 0.0.2.
  • Import module: deepsearcher.
  • Console script: deepsearcher = deepsearcher.cli:main.
  • Python requirement from package metadata: >=3.10.
  • The default configuration constructs providers during init_config(config), so provider and vector DB readiness matter even before query/load workflows run.
  • The inspected default config uses OpenAI, OpenAIEmbedding, PDFLoader, FireCrawlCrawler, and Milvus with a local ./milvus.db URI.

Install and sanity check

  1. Install the package in an environment with Python 3.10+:

    pip install deepsearcher
    
  2. For this checkout's inspected default local stack, also ensure a Milvus Lite-compatible set and a FireCrawl version that exports ScrapeOptions:

    pip install "pymilvus==2.5.8" "milvus-lite==2.5.1" "setuptools<81" "firecrawl-py==2.16.5"
    

    These pins were needed in the inspected environment to keep the default Milvus/FireCrawl paths usable.

  3. Run the bundled environment check before deeper work:

    python scripts/check_deepsearcher_environment.py
    

    Add --check-cli-help if you want a temp-cwd CLI probe with a dummy OpenAI key.

  4. If you only need to verify the installed package identity, the helper's version/import output is enough. If the installed package is missing optional provider SDKs, route to the provider sub-skill before assuming the repo skill is incomplete.

How to route requests

  • Configuration, provider names, credentials, and optional extras: provider-configuration.
  • Loading files, crawling websites, chunking, and collection creation: data-ingestion.
  • Querying loaded data and interpreting references: rag-query.
  • CLI help, deepsearcher load/query, FastAPI endpoints, and deployment checks: cli-and-service.
  • 2WikiMultiHopQA recall evaluation and report outputs: evaluation.

Cross-cutting cautions

  • init_config(config) creates every configured provider, not just the one you care about. A bad default provider can fail before the workflow begins.
  • The default local Milvus URI is relative to the current working directory, so repeated runs in the same directory can lock ./milvus.db.
  • CLI help and service startup can expose provider initialization problems early; use the dedicated CLI/service sub-skill for those failure modes.
  • Do not point future agents back to the original repository checkout. Read the bundled references and scripts in this skill tree instead.

Skill metadata for future refreshes

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