seektalent 0.7.6

Local CLI Agent for deterministic multi-round resume matching with Pydantic AI

SeekTalent

SeekTalent is a local-first recruiter workbench with a stable CLI and a local browser UI. It turns a required job title, a job description, and optional sourcing notes into a deterministic multi-round shortlist using requirement extraction, local Liepin retrieval through OpenCLI, per-resume scoring, reflection, and finalization.

The current product shape is local-first:

• the CLI remains the stable terminal entrypoint;
• the local recruiter workbench is the primary browser UI for business workflows;
• business data, workflow control state, workbench projections, bounded diagnostics, provider state, and backups stay local by default;
• account entitlement may use a minimal remote control plane, but SeekTalent is not a hosted recruiting SaaS.

Highlights

• Installable CLI with stable subcommands: run, workbench, init, doctor, version, update, inspect
• Stable Python entrypoints: run_match(...) and run_match_async(...)
• DB-first local control plane for conversation turns, workflow runs, public progress, checkpoints, candidate truth, and recruiter Workbench projections
• Bounded artifact modes: production keeps product state in SQLite; development can emit compact diagnostics; debug_full_local is explicit and short-lived
• Explicit text-LLM configuration using SEEKTALENT_TEXT_LLM_* plus bare *_MODEL_ID values
• Real Liepin integration through the local OpenCLI browser bridge

Quick Start

Prerequisites

• Python 3.12+
• one supported LLM provider credential
• OpenCLI Chrome extension installed and connected
• Liepin already logged in in the local browser profile

Install as a CLI

Recommended for end users:

pipx install seektalent==0.7.1

If you prefer a plain Python environment:

pip install seektalent==0.7.1

The current starter env defaults to the canonical text-LLM surface, with SEEKTALENT_TEXT_LLM_PROTOCOL_FAMILY=openai_chat_completions_compatible, the matching SEEKTALENT_TEXT_LLM_ENDPOINT_* values, and bare stage *_MODEL_ID settings. Dual-protocol support still exists through the same SEEKTALENT_TEXT_LLM_* surface.

Create a starter env file

seektalent init

For installed PyPI users, seektalent init writes a minimal .env with one required value:

SEEKTALENT_TEXT_LLM_API_KEY=

All other runtime, output, cleanup, source, OpenCLI, Liepin, and model settings use product defaults.

Fill the required value in .env

At minimum:

SEEKTALENT_TEXT_LLM_API_KEY=your-text-llm-key

Users can also set the same key directly in the current terminal and start immediately:

export SEEKTALENT_TEXT_LLM_API_KEY=your-text-llm-key
seektalent workbench

Active model configuration uses the SEEKTALENT_TEXT_LLM_* tuple plus bare *_MODEL_ID values. SEEKTALENT_TEXT_LLM_API_KEY is the canonical runtime credential.

Validate the local setup

seektalent doctor

Installed PyPI users start the local Workbench with the packaged frontend:

seektalent workbench

The command starts the backend and serves the built React Workbench from the same loopback origin. It defaults the Workbench to Liepin through OpenCLI in the user's local browser. No extra SeekTalent env configuration is required beyond the LLM API key. SeekTalent downloads and pins its managed Node/OpenCLI runtime under ~/.seektalent/opencli-runtime on first use when needed. The user still installs and connects the OpenCLI Chrome plugin in their own Chrome profile, and Liepin must already be logged in. If OpenCLI bootstrap, daemon, extension, or Liepin login checks fail, startup exits before launching the server and prints a reason_code=... diagnostic. The packaged frontend does not require pnpm, Vite, Node, OpenCLI CLI, or a repository checkout on the user's machine.

For source checkout development, use the repo-local OpenCLI/React launcher:

scripts/start-dev-workbench.sh

The development launcher installs React dependencies with pnpm when needed, points SEEKTALENT_LIEPIN_OPENCLI_COMMAND at apps/web-react/node_modules/.bin/opencli, exports SEEKTALENT_LIEPIN_WORKER_MODE=opencli plus SEEKTALENT_LIEPIN_BROWSER_ACTION_BACKEND=opencli, then starts the backend on 127.0.0.1:8012 and the React Workbench on 127.0.0.1:5178. The user still installs and connects the OpenCLI Chrome extension in their own Chrome profile. When OpenCLI is selected and ready, Liepin behavior is real local browser behavior, not fixture data.

doctor, inspect --json, cleanup, and Workbench startup do not upload local databases, provider cookies, browser sessions, raw resumes, or configured secrets. Runtime network calls are limited to the configured LLM provider and the local browser's Liepin session unless an optional provider is explicitly configured. Remote eval logging through W&B/Weave is off by default and requires explicit configuration.

Recommended black-box workflow

seektalent --help
seektalent doctor
seektalent run --job-title-file ./job_title.md --jd-file ./jd.md
seektalent inspect --json
seektalent update

Run one workflow

seektalent run \
  --job-title "Python agent engineer" \
  --jd "Python agent engineer with retrieval and ranking experience"

Add notes when you want to inject sourcing preferences or exclusions:

seektalent run \
  --job-title "Python agent engineer" \
  --jd "Python agent engineer with retrieval and ranking experience" \
  --notes "Shanghai preferred, avoid pure frontend profiles"

Canonical output is human-readable. For wrappers and scripts, use machine output:

seektalent run \
  --job-title "Python agent engineer" \
  --jd "Python agent engineer" \
  --notes "Shanghai preferred" \
  --json

Print upgrade instructions

seektalent update

Inspect the published CLI contract

seektalent inspect --json

Install Paths

Terminal users

Recommended:

pipx install seektalent==0.7.1

This gives you the seektalent command directly.

Python integrators

pip install seektalent==0.7.1

Then:

from seektalent import run_match

result = run_match(
    job_title="Python agent engineer",
    jd="Python agent engineer",
)

print(result.final_markdown)
print(result.run_dir)

CLI

The canonical entrypoint is:

seektalent run --help

Available commands:

• seektalent run
• seektalent init
• seektalent doctor
• seektalent version
• seektalent update
• seektalent inspect

Recommended black-box sequence:

• seektalent --help
• seektalent doctor
• seektalent run
• seektalent inspect --json
• seektalent update

Key options on run:

• --job-title or --job-title-file for the required job title
• --jd or --jd-file for the required job description
• --notes or --notes-file for optional sourcing preferences
• --env-file
• --output-dir
• --json

The default output root is ./runs relative to the current working directory. Override it per run with:

seektalent run \
  --job-title "Python agent engineer" \
  --jd "Python agent engineer" \
  --notes "Shanghai preferred" \
  --output-dir ./outputs

Full CLI reference:

• docs/cli.md

Wrapping SeekTalent

Two supported wrapper patterns are intentionally stable:

Wrap the CLI

Run:

seektalent run --job-title "..." --jd "..." --json

Then read the single JSON object from stdout.

Wrap the library

from seektalent import run_match

result = run_match(job_title="...", jd="...", notes="...")
payload = result.final_result.model_dump(mode="json")

Pass notes="..." when you want to add sourcing preferences; omit it when JD alone is enough.

Use this path when you want to build your own API server, desktop shell, or workflow wrapper around the runtime.

Configuration

Environment variables are read from .env by default. You will usually configure:

• the canonical text-LLM runtime credential SEEKTALENT_TEXT_LLM_API_KEY
• text-LLM protocol and endpoint settings under SEEKTALENT_TEXT_LLM_*, plus bare stage *_MODEL_ID values
• optional CTS settings only when SEEKTALENT_PROVIDER_NAME=cts is set explicitly
• runtime settings such as round limits, concurrency, and output directory

Full configuration reference:

• docs/configuration.md

Important rules:

• active model variables use bare *_MODEL_ID values, not provider-prefixed strings
• the canonical runtime credential is SEEKTALENT_TEXT_LLM_API_KEY
• protocol selection and endpoint routing are configured through SEEKTALENT_TEXT_LLM_*

Local Workbench

Installed users start the packaged local Workbench with:

seektalent workbench

Source-checkout development uses the repo-local React/OpenCLI launcher:

scripts/start-dev-workbench.sh

See docs/development.md for lower-level backend/frontend commands and Workbench verification. React Workbench visual acceptance is pinned to the assets under docs/superpowers/artifacts/react-agent-workbench-design/.

Local State And Outputs

Workbench product state is SQLite-first:

• runtime_control.sqlite3 is the workflow source of truth for runs, commands, public events, checkpoints, stage outputs, candidate truth, and projection state.
• workbench.sqlite3 is the recruiter-facing projection/read model.
• conversation_agent.sqlite3 stores thread/turn state and active or historical runtime links.
• agent_memory.sqlite3 stores advisory memory, usage, jobs, and retention state.

Artifacts are side-channel diagnostics or exports under artifacts/, not the production reconciliation path. prod avoids full traces by default, dev keeps compact bounded diagnostics, and debug_full_local must be enabled deliberately.

Output reference:

• docs/outputs.md

Limits

Current boundaries are intentional:

• SeekTalent is local-first, not a hosted multi-tenant recruiting SaaS
• the Workbench is the primary browser UI for local recruiter workflows
• source adapters are scoped to the fields and semantics implemented in this repository
• the runtime is built for auditable deterministic control flow, not open-ended autonomous tool use

Docs

Start with docs/README.md. Active docs are intentionally small; historical plans, old designs, and superseded drafts are not product truth.

License

This project is licensed under the GNU Affero General Public License v3.0.

See LICENSE.