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<p align="center">
  <img src="assets/logo.svg" alt="Proofpress logo" width="88" height="88">
</p>

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# Proofpress

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[![Python 3.11+](https://img.shields.io/badge/python-3.11%2B-3776AB?logo=python&logoColor=white)](pyproject.toml)
[![MCP](https://img.shields.io/badge/MCP-supported-0E6675)](docs/REMOTE_MCP.md)
[![CI](https://github.com/chenmingtang830/proofpress/actions/workflows/ci.yml/badge.svg)](https://github.com/chenmingtang830/proofpress/actions/workflows/ci.yml)
[![License: Apache-2.0](https://img.shields.io/badge/license-Apache--2.0-blue.svg)](LICENSE)

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**Typed knowledge infrastructure for continuous learning.**

Build on every discovery. Proofpress turns agent-produced findings into typed,
evidence-bound knowledge that teams and agents can inspect, review, and reuse.
Each finding carries its evidence, dependencies, and conditions for reuse.

**Verifiable. Traceable. Auditable.**

Spend less time reconstructing past work. Carry forward what the team learned,
recognize what needs rechecking, and give the next experiment a better starting
point.

[Website](https://proofpress.dev) · [Quick start](#quick-start) ·
[Localhost guide](docs/LOCALHOST_QUICKSTART.md) ·
[Product thesis](docs/THESIS.md) · [Remote MCP](docs/REMOTE_MCP.md)

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[//]: # (ob:quickstart)

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## Quick start

**New here? Choose a path, then complete one finding → human review → reuse loop.**

| What you want | Start here |
|---|---|
| Try the product with synthetic data | [Local demo](#try-the-local-demo) — no account or credential. |
| Use your own files with Claude Code on localhost | [Your own local workspace](#use-your-own-files-on-localhost) — an empty database, full review UI, file-to-finding instructions and agent setup. |
| Join an existing team workspace | [Connect to Hosted](#connect-an-agent-to-a-hosted-workspace) — use your team's assigned URL and Agent credential. |
| Deploy on your own server | [Self-hosting](docs/SELF_HOSTING.md) — persistent storage, credentials and backups. |
| Develop Proofpress | [Contributing](CONTRIBUTING.md). |

### Try the local demo

You need [Python 3.11+](https://www.python.org/downloads/),
[Git](https://git-scm.com/downloads), and
[uv](https://docs.astral.sh/uv/getting-started/installation/).
Use a macOS/Linux terminal, or Windows WSL2:

```sh
uv tool install --with "mcp>=2,<3" "git+https://github.com/chenmingtang830/proofpress.git"
uv tool update-shell
```

Open a new terminal if `proofpress` is not found, then run:

```sh
proofpress quickstart --ui
```

This creates `./proofpress-demo` with **synthetic** evidence and candidates,
starts the local review UI and opens your browser. Inspect a candidate and make
a human review decision. Stop with `Ctrl-C`; the workspace remains on disk.
Choose another empty destination with `--workspace PATH`; use `--no-browser`
for a headless demo. The generated `proofpress-mcp.json` targets this demo's
Git-backed ledger, not the SQLite workspace below.

<p align="center">
  <img src="assets/quickstart/local-ui-review-queue.png" alt="Synthetic local demo review queue; separate from a real research workspace" width="100%">
</p>

### Use your own files on localhost

For real work, start an **empty** workspace. After installing above, run the
bootstrap command yourself in a private terminal:

```sh
umask 077
mkdir -p "$HOME/.local/share/proofpress"
proofpress hosted --database "$HOME/.local/share/proofpress/workspace.db" \
  bootstrap --workspace-id workspace:research --owner-principal human:owner
```

Save the returned Owner `token` and `recovery_secret` in your password manager;
keep them out of agents, chat and Git. Bootstrap runs once. Then start the server:

```sh
proofpress hosted --database "$HOME/.local/share/proofpress/workspace.db" \
  serve --host 127.0.0.1 --port 7334
```

Open **[http://127.0.0.1:7334](http://127.0.0.1:7334)** and sign in with the
Owner token. Despite the command name `hosted`, this server stays on your
machine. Keep the terminal running; restart with the same database to keep your
history. You do not need Docker or a frontend build.

Continue in **[Localhost: files → Claude Code → review → reuse](docs/LOCALHOST_QUICKSTART.md)**:

1. Save review criteria in **Admin → Verification settings**. Human review
   works without a model key.
2. Issue a separate Agent key and connect Claude Code to this workspace's
   `http://127.0.0.1:7334/mcp` endpoint with the maintained plugin/skill.
3. Let Claude read selected local files and submit bounded evidence plus
   candidate findings. There is no generic bulk-upload or folder-crawling UI.
4. Review a finding yourself, then retrieve it in a fresh Claude conversation.

For capture format errors, update the plugin/skill and follow the
[capture input guide](.agents/skills/proofpress-governed-context/references/capture-input.md):
read `proofpress_get_capture_schema` before writing and use the bundled helper
to prepare exact excerpts and real hashes for selected files or slides.

Proofpress stores submitted excerpts and governance records locally. Claude
Code still processes the material it reads under your Claude configuration;
localhost does not make the model offline. Optional Proofpress AI checks have
a separate provider/processing opt-in.

#### Use your own AI-assisted review (BYOK)

Provider API keys are encrypted before being stored in SQLite. To enable the
API key input, configure the server's `PROOFPRESS_SECRET_ENCRYPTION_KEY` first.
This encryption key is separate from your provider API key and Owner/Agent
credentials. The localhost UI offers **Copy setup commands** using the current
database and port, then **Check storage again** after restarting. Existing saved
credentials get original-key recovery instructions. Manual commands follow.

For an instance that has **never saved a provider key**, stop the server with
`Ctrl-C`, then initialize a persistent encryption key in your private Terminal:

```sh
umask 077
mkdir -p "$HOME/.local/share/proofpress"
python3 - <<'PYTHON'
import base64
import os
from pathlib import Path

key_file = Path.home() / ".local/share/proofpress/provider-key-encryption.key"
try:
    with key_file.open("x", encoding="ascii") as output:
        output.write(base64.urlsafe_b64encode(os.urandom(32)).decode("ascii") + "\n")
except FileExistsError:
    pass
PYTHON
```

The file is created with owner-only permissions and is not overwritten on
repeat runs. If you have already stored provider credentials, reuse the
**original encryption key**; generating another key cannot decrypt them.

Load the key and restart your existing database. Run this entire block in the
same Terminal tab **every time you start the server**; change the database
path if your workspace uses a different one:

```sh
export PROOFPRESS_SECRET_ENCRYPTION_KEY="$(cat "$HOME/.local/share/proofpress/provider-key-encryption.key")"
proofpress hosted --database "$HOME/.local/share/proofpress/workspace.db" \
  serve --host 127.0.0.1 --port 7334
```

Reload **Admin → Verification settings**, turn on **AI-assisted checks**, choose
your provider and model, enter its API key privately, review the processing
notice, and save. Keep automatic approval off unless you separately choose it.
Saving AI settings can process pending findings and incur provider charges.

The key field should now be enabled; after saving, only the provider key's last
four characters are shown. A saved key does not prove a successful provider
call: verify a review receipt. Keep the encryption file outside Git, retain a
protected backup, and reuse it across restarts. Never paste either key into
chat. See the [complete BYOK guide and troubleshooting](docs/LOCALHOST_QUICKSTART.md#optional-use-your-own-ai-review-provider).

### Connect an agent to a Hosted workspace

From the repository whose agent work you want Proofpress to govern:

1. Install the [`proofpress` Agent Plugin](plugins/proofpress/README.md) for
   Codex, Claude Code, or Cursor. It bundles the governed-context skill and
   policy assets; a separate skill download is unnecessary on the normal path.
2. Add the `/mcp` URL assigned to your team. The generic plugin intentionally
   contains no customer endpoint, so it cannot silently connect to another
   workspace.
3. Complete OAuth with the separate agent credential issued for that client.
   Never use an owner or recovery credential in an agent client.
4. Start a fresh agent session. If you want repository-specific proposal
   selection, ask: **“Initialize a Proofpress policy for this repository.”**
   Review and commit the generated `.proofpress/context-policy.yaml`.
5. Give the agent a real task. It will retrieve eligible context when available,
   submit bounded proposals when warranted, and stop for Human Approval.

For example, Codex users can install from this repository and connect an
assigned Hosted workspace as follows:

```sh
codex plugin marketplace add chenmingtang830/proofpress --ref main
codex plugin add proofpress@proofpress-plugins
codex mcp add proofpress --url https://YOUR-PROOFPRESS-HOST/mcp
codex mcp login proofpress
```

Installing the plugin does not create a Hosted workspace, MCP connection, or
ledger. Each team needs a separately provisioned Hosted workspace or a
self-hosted deployment. See [Remote MCP](docs/REMOTE_MCP.md) for Claude Code,
Cursor, manual fallback, and the full authorization boundary.

Want a managed Hosted Proofpress session and to work with us as a design
partner? [Tell us about your workflow](https://ancient-ball-940.notion.site/eacf21eef9b54c3287f72892cd024a1c?pvs=105).

Building Proofpress itself? Use the [contribution guide](CONTRIBUTING.md).


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[//]: # (ob:thesis-summary)

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## Agents generate outputs faster than teams can trust them

The result is saved. The reasoning is scattered. Experiments, evaluations,
analyses, and failed attempts leave findings across files, chats, traces, and
repositories. The next person or agent has to reconstruct what supports a
conclusion, where it applies, and whether it is still current.

Memory helps preserve and retrieve context. Files, embeddings, and knowledge
graphs are useful representations. Some memory systems also extract facts,
update relationships, and track time. The remaining question is concrete:
**which finding may the next workflow rely on, under which conditions?**

Compression alone won't close the trust gap. Scattered evidence, silent drift,
memory laundering, and repeated reconstruction can survive a shorter context.

<p align="center">
  <img src="assets/architecture/agent-knowledge-inflection.svg" alt="Conceptual trust gap between agent-produced findings and verified organizational knowledge" width="100%">
</p>

<sub>Illustrative model, not measured data. The curve describes the trust gap;
it is not a universal mathematical growth law.</sub>

## A typed knowledge system

A finding is more than a text record with extra fields. Its type and lifecycle
make its role, supporting evidence, dependencies, and reuse conditions explicit.
Proofpress applies checks and review decisions to those objects before they
enter downstream context.

- **Verifiable:** inspect the submitted evidence and recorded checks behind a finding.
- **Traceable:** follow its sources, dependencies, versions, and declared downstream use.
- **Auditable:** retain review decisions, revisions, withdrawals, and outcome observations.

These properties make reliance inspectable; they do not guarantee that every
finding is true or that every relevant event was captured.

### Knowledge should be managed like software

Software reuse depends on more than storing and finding source code. The
analogy for knowledge is an explicit lifecycle around a usable object:

| Software concept | Knowledge counterpart |
|---|---|
| Compiler | Turn submitted findings into structured, evidence-bound objects. |
| Type checker | Check evidence, scope, and the rules for reuse. |
| Dependency manager | Track what a conclusion depends on and what needs reassessment. |
| Runtime | Return eligible knowledge and record its use in a workflow. |

This is an architectural analogy, not a claim of formal proof or a literal
compiler implementation.

### Capture → Verify → Reuse → Learn → Review

1. **Capture findings and evidence.** Preserve the source version and intended scope through MCP, CLI, Python, or HTTP.
2. **Verify and review.** Apply deterministic checks and optional model advice. Human review is the default admission path; agents cannot approve their own claims.
3. **Reuse within conditions.** Retrieve current, admitted, in-scope knowledge for the requesting actor. Record the exact versions supplied and relied on.
4. **Connect outcomes.** Attach outputs, tests, and later observations to the work that used a finding.
5. **Maintain the lifecycle.** Reassess, revise, supersede, or withdraw findings as evidence and dependencies change. Retain prior decisions and history.

The learning loop serves **continuous organizational learning**. Outcome-based
retrieval weighting is a product direction, not a shipped or validated automatic
learning engine. Reuse utility is separate from evidence confidence and never
grants authority.

## Across agents and tools

<p align="center">
  <img src="assets/architecture/product-architecture.svg" alt="Proofpress connects agents through MCP, CLI, Python, and HTTP to evidence checks, review, and scoped reuse" width="100%">
</p>

Existing memory, observability, skills, and workflow tools can supply inputs or
consume eligible findings. Proofpress maintains the knowledge lifecycle across
them. The Owner workspace lets reviewers inspect support and lineage before
admitting, rejecting, or requesting revision.

<p align="center">
  <img src="assets/product/research-ledger-record.svg" alt="Illustrative typed finding with evidence, scope, review history, and conditions for reuse" width="100%">
</p>

[Task run tracking](docs/TASK_RUNS.md) documents the Run, ContextReceipt,
Reliance, Output, and Observation contracts.

## Evaluation evidence

- **89.3% → 93.4% rubric completion** in the [seven-model Harvey LAB-derived controlled evaluation](studies/long-horizon-eval/relaybench/PUBLIC_RESULTS.md), across 126 paired runs.
- The [website evidence section](https://proofpress.dev/#evidence) reports the separate **5.5× fewer numeric errors** result (11 → 2 incorrect final values, 20 paired chains, 1,600 numeric slots per arm).
- **38.3% fewer executor tokens** in the separate [Muse Spark 1.1 two-task APEX pilot](studies/apex-agent-eval/ara/evidence/tables/table3_cross_task_summary.md). This excludes upstream treatment preparation.

These are bounded controlled studies with different protocols and denominators.
They do not establish customer ROI, universal error prevention, or the complete
autonomous learning loop. See the [study catalog](studies/README.md).

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### Use the Python client

Run the same lifecycle in-process or over HTTP:

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```python
from proofpress import ProofpressClient, ProofpressError

client = ProofpressClient.in_process(".")
evidence = client.import_evidence("run.otlp.json", idempotency_key="run-001")
candidate = client.propose_claim(
    "The bounded result is ready for review.",
    evidence["evidence"],
    scope="experiment:demo",
    proposer="agent:runner",
    idempotency_key="proposal-001",
)

# A human authorizer reviews through the owner surface. A successor agent reads:
context = client.context(scope="experiment:demo", actor="agent:successor")
```

### Other MCP clients and advanced local use

Use [Remote MCP](docs/REMOTE_MCP.md) for client-specific plugin/skill installation
and OAuth. For a real localhost workspace, follow the
[local guide](docs/LOCALHOST_QUICKSTART.md); for the synthetic Git-backed demo,
use its generated `proofpress-mcp.json`. These are separate storage backends.

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## Choose a deployment

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- **One local repository:** use the in-process client or localhost HTTP for a
  Git-backed ledger, local review, and governed-context reads.
- **One private workspace across people, devices, and agents:** use `proofpress hosted`
  for durable storage, distinct human Reviewer credentials, scoped agent credentials,
  review, and HTTP/MCP access.
- **Workflow-specific evidence:** use a profile or integration for typed
  validation without changing the authority model.
- **Owner UI preview:** run `npm run preview:local` from `web/owner`; it reuses
  one ignored, mode-`0600` local credential and synthetic workspace.
- **Hosted boundary:** the reference deployment is private and single-instance,
  not a multi-tenant Proofpress cloud. See [Self-hosting](docs/SELF_HOSTING.md).

### Self-host in three steps

1. Deploy this repository with [`render.yaml`](render.yaml), or use the
   provider-neutral examples in [`deploy/self-hosted/`](deploy/self-hosted/).
2. In a private server shell, bootstrap one owner workspace:

   ```sh
   proofpress hosted --database /var/data/proofpress.db \
     bootstrap --workspace-id workspace:personal \
     --owner-principal human:owner
   ```

3. Store the one-time owner credential and recovery secret outside Git, then
   issue a distinct credential for each human Reviewer and agent or device. Configure backups
   before relying on the instance.

- The Blueprint contains no Proofpress credentials or customer data.
- A fork uses the operator's own account, storage, domain, and billing.

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- Submitting evidence or proposing a claim never admits it.
- Agent credentials identify and constrain callers; they do not carry owner authority.
- Governed-context reads return only admitted, current, in-scope, actor-eligible claims.

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## Integrations and deployment

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- `proofpress.profiles.experiment` validates bounded metric, table-cell, and derivation evidence.
- `proofpress.integrations.repository` binds one repository change to Git and check receipts for self-dogfood.
- `proofpress.integrations.matter_catalog` and `proofpress.integrations.document_extraction` are optional evidence-entry integrations. Their output remains candidate evidence.
- `proofpress hosted` runs the private hosted control plane and web review surface. See [Self-hosting](docs/SELF_HOSTING.md).
- [AFF](https://github.com/only-then-labs/aff) is the separate Apache-2.0 format and CLI for portable agent Findings. Its [collaborator trial](https://github.com/only-then-labs/aff/blob/main/docs/SHARE.md) works with a Git collection; Proofpress is an optional open-source governance runtime for authenticated review and reuse.
- Proofpress's OAFF v0.1 integration can [export bounded claims](docs/OAFF_EXPORT.md) and [receive foreign candidate packages](docs/OAFF_IMPORT.md) without granting receiver-local authority.

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## Read this next

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- **Work on the repository:** [repository structure and ownership](docs/REPOSITORY_STRUCTURE.md).
- **Understand the product:** [Thesis](docs/THESIS.md) → [claims and governed context](docs/VERIFIED_KNOWLEDGE_LEDGER.md) → [FAQ](docs/FAQ.md).
- **Connect an agent:** [trace integration](docs/TRACE_ADAPTER.md) → [content-addressed receipt adapter](docs/CONTENT_ADDRESSED_ADAPTER.md) → [external experiment evidence](docs/EXTERNAL_EXPERIMENT_INGESTION.md) → [Baseten training evidence](docs/BASETEN_TRAINING_ADAPTER.md) → [spreadsheet cell evidence](docs/SPREADSHEET_ADAPTER.md) → [MCP and WebMCP](docs/WEBMCP.md) → [repository dogfood](docs/REPOSITORY_DOGFOOD.md).
- **Run it privately:** [self-hosting guide](docs/SELF_HOSTING.md) → [`render.yaml`](render.yaml) → [deployment examples](deploy/self-hosted/).
- **Explore prior experiments:** [study catalog](studies/README.md). Research evidence is separately scoped; it is not a blanket product-efficacy claim.

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- Python-first and one private workspace per deployment today.
- Human Reviewers may inspect and decide claims. Credential and policy administration stays with the bootstrap Owner; invitations and customer VPC packaging are not available.
- No Notion or multi-repository knowledge ingestion.
- Not a universal OCR, RAG, memory, or search platform.

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## Compatibility

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Python is the supported SDK and CLI installation path. Older Python imports,
console aliases, and portable top-level commands remain deprecated forwarding
shims; new integrations should use `ProofpressClient`, `proofpress`, and
`proofpress legacy ...` for the portable artifact ledger. Browser tooling builds the Owner workspace. The public website is maintained
separately in [continuara-lab/proofpress-website](https://github.com/continuara-lab/proofpress-website);
this product repository does not deploy proofpress.dev.

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See the [documentation index](docs/README.md), [study catalog](studies/README.md), and [GitHub Releases](https://github.com/chenmingtang830/proofpress/releases).

[//]: # (proofpress:meta:eyJhcnRpZmFjdF9pZCI6InBwXzU1NmIxMTVkZTcxMWIwY2QzM2VlZDI2MCIsInBvbGljeSI6InBvcnRhYmxlIiwicG9ydGFibGVfaGVhZCI6ImRjYjQ3ZDQzIiwicG9ydGFibGVfaGVhZF9ldmVudCI6InBwZV9hY2ZkMjY2ZjIwZmU1N2MzY2RiZDc0YmEiLCJwb3J0YWJsZV9saW5lYWdlX2lkIjoicHBsXzMxNTQxYmZkZjRkNzQzYTNjZTYwMmUzZCIsInByb29mcHJlc3MiOjF9)
[//]: # (proofpress:discovery:Verifiable revision history by Proofpress | https://github.com/chenmingtang830/proofpress)
[//]: # 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0fNPYEvuavC9fXdHC5HvRR7mCx47308iiCLgaQyuGHi0ORglDORJRAhjxFWoC-4Aw10g9ECT09XcFXimFxH30WxoByQVHUhAzleFUGkKQ2QRXCbSS51U-LazhZAQV7esx5J1CjsgCIlA5LT3lQmX4qG0yfnro7PjM9QUQu_h3Qs4aklXVsmgFnFM87FktUW1AvKjOUYloqhLWEMQVC4DkM28TfwZI6BykDskdscjHWIbUNu2KWVPmhkcP3xymv4ZI5eVfhcGGKN4iBalspbvtyik41v96ei1BYfD5NQynkTdKbmuLS_QgXi5wgK1P1xkKdp3jMMUq6WIewhHsqttkjmh41HvGXrkD0CGN24W7mcTO1XZNFju7ShqF4XEck3bsh-WI72jqXOeZQUfNX5eZyc_dsUFNxK-h2IEYG8zBiY3lvwO2e56rqtJmBGbedR_Og1fBNALASxoX7QzZJqGEUj4IpIv4APKlM06W2lfpumX0WhU_zdtSZJMAW8eQhcmu_GikEfRiGdDuWE5j3gu4iMxwtkkpig6mAXacNoaL6djI6nveSHnznO3COdyw0bgHsy7BIlYXDedGy9rUDYAVpfihW7puXVzVzew4QSU6_ojZxtpe3t_xGQaHKxUWimlEiZ7e9r78x026j__9d-19xfZTXd3R8lLA6du0KG6aQ8Yw6yhNIiawkvo2CA5EjZWVKkIQR1v2oGiOubBMW9YSXQshJ5SDB7vAkvbhz36BO4tOi-E_YWEEhQhzhCZIIplNES5k5tgabwL_Gyf5hWPwC-SC6hNioI0VdBRzMk_1XnNXThm-wxv4vRSjs84OGHoxak9wWGbDMDFKmY3qG-BkTt4f9Ma1swHtxIw_HgX1njssFv3tIUkto97Ns-u5cB1bKrMRsKrGMnDg9-bYDUWC4x3wYHtU8haLHATtRyMfh0gRvu5KkSIVngqreDtLpO-YwmliDWC4U0LARJAUwlPOswzQMgVDK3M-HiXOe5gfFvbg2sqGY7SgSGC8S7zesdObgzasYctY7l9xJ_IslBJKWVmVAwDQ7MiK4v2UXgm3cxomby7Do6aqLWGjaMJ6JJm2eV4l8G6izUb0QhlkDQ0SFtPT8sS3THwpsHYzu-WpekSiTiHTWvilI3dbTNFGHIRM2kvAtm-rWrxlONLA3nbHJBCYF4MIpW1ydqoYrye4y5fcr7E4WuFVoNSTKWnIqXGSR7OtQWcljyWwSpYlirm2OD4w8ocOdazsYAGrh3YjBoBc4lrUXdXmWNdknaPMsc-QNEHKPoARR-g6AMUfYCiD1D0AYo-QHHvAMX9m1FuvuvK8L5ubyH4RdombGoGkW7YlHjMswLTswzXcW3OPT-yTVOPSEQ9nUbcN13u26FneTQMdcO1PHwPlrFrQTebJkxjYhgT093SNOFQ7sPp8vqmib5pom-a6Jsmfh1NE8wmIAwBeOBW0zTRONBbikHu9ourc2phF5vlRnZTYt9ylZvKons5v1VBI6N2qOvEpG4tRy1_WA36FA9X-W_8Ew9FWQU4nNMUf4EtbdwNRkAKZSnS6cEPQ23BF1m-Vg0OaZmB1sTgZZZfkBS2TIobbiISJaqclS-gYbH2WDsXrsKWqHgxz67l0wDIlhx3VQZvQBhzknZsrWVywOSBYRt-3S7Q8tG3HLmHet0o6OB7ADqBXSqGU9AUJFkLpqCEqt-F96PM3YiS8BIFUyRC5JBEw38cI795YkGcpymFA1bgA7A76giL4r2qA3czCj1E9yWO8NSIervqeFfHWVDYjtWXUm1c8s1iY9GLImZcFVzMF8tSQaIBjTBFOE2bAj8Apsv5sCYfTrroP8EWmBKIF17gJc-VO6hdgyKbZzCwqAcE4Zmm9ygABHRBie0DViReU8hbRzY2keOjYhWaQpBglyQXORu1FolZDTXCn45Oj78_Pno1-_Htyc9vjl79cDQTf59uDJpR_MdJbnK84LC3oNe6CtR0QIDUDV2bunWBeStcskUn3ScAUjX-AEYkukkDs2miacVEGq10_wBHdd4oWFAjNKzArispWzGPpk3jCQEM-efL1ou3bZP6B2Ji7Am5_cDVND1Q_VZUlNXXz42-q0xa0T4WcFmZsX2NsKu4yEQ8GU3YtvHv8-fLYx-8euCDr4VOkX6osp7_eDRXnQfab-qS5t_UvQeVMQcVmPxj8_tml0ql0u_oKwkJh-d0Dv5Z7dS0onKVintCiE0J8lCjK6EUgY1YlouaHZFXwROBOavkokRiss8EhlJHYljDtaHKkYDOJQlAe87qTpzfonmGh4TRED2LaLCxMFMUgasuRZDFmy0ofXtr3976DO2tjFum54cW080ae7eiyIrfTwkGj7U3VUejAnXS1CvWnv3hTVzyCu6prlAVwJsTOA0sjkTQEPgBUAk4I08lHpj6p2nackDvgxz6rt6-q7fv6u27evuu3gd39Ua25bmeRXxm12qoldXb1mF2n_xchS8CrtsueF2E2LUGbVJ2jQZ9YOqtbo9zPM91gZ-kxkatbJwa_mlZtS8C-7S6RnG_MDoUYQZjX2qCKsoLYx43ukKdPniggSECe3yB3W8MqGomGyqtImVHgorawa1kQsiIVpPVdC2KzmlZxFYgtoCBGAwUimAUOpniBhnT_LK1JRSJWooWW7DJGwm8RscJvrFVLkJEtQEXcsnaTdnDirK6b1SuB1e_j_inwkliJQc1_0bFEpy0KA4bp1S-UE1RJ6vU6h44CU2-aOfrZdv_VT3F-BsSjG1-omBIOAdYM1XjbrE3t4MU2pdtudQKkFvMMiihXA9b_n6dXm2VEDw2TToSdherBVUMiqBRFDvTPh_1uEMVpJJ9qCU2I7btAzA7WzEpt6DlMVQMo4m4NWAzmik2Kng_1r5XkZxTLmLjv09WXGTdAKllWYkodClKO0EDbmw5SvNquS9hwhC7qMW_iDtEwDvc7FWs6v-GQqCn6QP7iG9FjvpXE_SvJuhfTdC_muD5Xk0A2l0PIptZnlkjl1aNyhb5v6vSRA1sRAYHuEUsL6zzsK3ik0b-71NPUvm_xLeowxw4Rbxut29KTGqRf0rViNIcTWpA6TQc_F4JAjHO9wd_UDfDJ7EFKAZ7e4cZgO-wSZUJimTipCVdFXGnB4dHs4NXB-_O22MjrkCifuYUPqp7fz76PXxpbmqdMXVy6tb1dydnx-cnp3-evTr54fuTk1ct8k7RCSwreJSsBXlFS8A2EiU3xUzO_DEX9nS8Jovk44cXrW_qhpZpV14p7oa4uF_Pxdl-RRS22CCaAaoyEUtSmquQ1N3VfT8GCVNl3rW1w04jjhIr4YnAdSKmWSfCKBy8S142rUcR5t3CtUzt9e_66N_10b_ro3_Xxz_Quz4e_z6Pv9-bOuYEbCkcAERlxY6XdQhSmpd1tCm73ws7HlRjevu92k3z6u3Oowg2Qwa1NrVFSJbFCo9OJAo7mDiGordUmGTtcI6eDwJbkXuWrXwCQz6si4iEEXDXjUw94o4XWiGjzLMp2dVFVNdo3t1F9Fxcu3_f05b3dhtft1eY_iI1taaj28zhRuD5uudHTkTsyA2oTSPfjYDT3NGpy13qcOK4DPxEPTJ8JwhZYBKf0Wj3kjaraq1z3Z_YwcT2tlTVspDaHrOtvqq2r6rtq2r7qtq-qravqu2ravuq2r6qtq-q7atq-6ravqq2r6rtq2r7qtq-qravqu2ravuq2r6qtq-q7atq-6ravqq2r6rtq2r7qtq-qravqu2ravuq2qdU1UY2OBAs1L3Atvuq2r9DVe3NqiBZt9pUBl3GoJKTGOMbAMildVRRQlEGJk8vytgGWbPXB4c_Hpy_Pnk7O_vj7386Pjs7PnnbF_P2xbx9MW9fzNsX8_46ink_fP0feOc4pg)