headroom/examples/README.md

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# Headroom Examples
This directory contains examples demonstrating Headroom's capabilities.
## Quick Start Examples
### basic_usage.py
Basic integration with OpenAI client:
```bash
export OPENAI_API_KEY='your-key'
python examples/basic_usage.py
```
### anthropic_example.py
Integration with Anthropic Claude:
```bash
export ANTHROPIC_API_KEY='your-key'
python examples/anthropic_example.py
```
### streaming_example.py
Streaming responses with optimization:
```bash
export OPENAI_API_KEY='your-key'
python examples/streaming_example.py
```
feat(transforms): tabular + spreadsheet (.xlsx/.xls) compression (#1128) ## Description Adds a content-type-aware path for **tabular data** — CSV/TSV, markdown tables, fixed-width text, and binary `.xlsx`/`.xls` spreadsheets — by routing them through the existing, battle-tested `SmartCrusher` instead of letting them fall through to `PLAIN_TEXT → Kompress`. The pipeline already compressed tables losslessly when handed a JSON array of records. This wires up the missing front door: detect tabular text (and ingest binary spreadsheets), convert to JSON records, and reuse `SmartCrusher.crush()`. No new compression algorithm. Closes # ## Type of Change - [ ] Bug fix (non-breaking change that fixes an issue) - [x] New feature (non-breaking change that adds functionality) - [ ] Breaking change (fix or feature that would cause existing functionality to change) - [ ] Documentation update - [ ] Performance improvement - [ ] Code refactoring (no functional changes) ## Changes Made - **Detection** (`content_detector.py`): new `ContentType.TABULAR` + `_try_detect_tabular()` for CSV/TSV, markdown tables, and fixed-width columns. Ordered after search/log (which also look "delimited") and before code, with a prose-rejection guard so it never steals `file:line:content` search output, `key: value` logs, or sentences with incidental commas. Rust backend returns `plain_text` for unknown types and the router already falls back to the Python detector, so **no Rust change**. - **Bridge** (`tabular_ingest.py`): stdlib parsers + `to_records()` + a `TabularCompressor` that parses → JSON records → `SmartCrusher` (lossless `csv-schema` first; lossy row-drop with reversible `<<ccr:HASH>>` markers stays SmartCrusher's built-in fallback). Only adopts a result when it actually saves bytes. - **Spreadsheets** (`spreadsheet_ingest.py`): `.xlsx`/`.xls` → per-sheet CSV text at the SDK boundary. Optional deps (`pip install headroom-ai[spreadsheet]`) fail loudly with an install hint, never silently degrade. - **Routing** (`content_router.py`): `CompressionStrategy.TABULAR`, `enable_tabular_compressor` flag, lazy getter, apply branch, strategy maps, Kompress fallback eligibility. - **SDK** (`compress.py`): `compress_spreadsheet(path, ...)` helper (one message per sheet). - **Packaging** (`pyproject.toml`): new `[spreadsheet]` extra; `openpyxl` added to `[dev]` so the xlsx path is exercised in CI. - **Docs/demo**: `examples/tabular_compression_demo.py` + README entry. ### Design note: lossless-only Compact, all-unique tables with no query yield ~0 savings — this is correct, not a bug. SmartCrusher returns `skip:unique_entities_no_signal` and won't drop unique rows without a duplicate/relevance signal. Real wins come from verbose/redundant tables and query-driven selection. A pressure-driven lossy row sampler was considered and intentionally not added. ## Testing - [x] Unit tests pass (`pytest`) - [x] Linting passes (`ruff check .`) - [x] Type checking passes (`mypy headroom`) - [x] New tests added for new functionality - [x] Manual testing performed ### Test Output ```text $ python -m pytest tests/test_transforms_tabular.py -q collected 20 items tests/test_transforms_tabular.py .................... [100%] ============================== 20 passed in 7.15s ============================== $ ruff check headroom/transforms/tabular_ingest.py headroom/transforms/spreadsheet_ingest.py All checks passed! $ mypy headroom/transforms/tabular_ingest.py headroom/transforms/spreadsheet_ingest.py Success: no issues found in 2 source files ``` `tests/test_transforms_tabular.py` (20 tests): detection true positives + no-misroute negatives (search/log/JSON/prose), parser units (incl. fixed-width), the CSV→SmartCrusher bridge, router routing + disable flag, and `.xlsx` ingestion (skipif openpyxl missing) + error paths. `spreadsheet_ingest` 100% / `tabular_ingest` 90% line coverage. ## Real Behavior Proof - **Environment:** local checkout of `feat/tabular-compression`, Python 3.x, `pip install -e ".[dev]"`. - **Exact command / steps:** `python examples/tabular_compression_demo.py` (no API key required). - **Observed result:** ```text === Raw tabular text (ContentRouter, char-level) === compact unique CSV strat=tabular chars 1306 -> 1072 ( 17.9% saved) redundant CSV strat=tabular chars 2661 -> 1350 ( 49.3% saved) verbose markdown strat=tabular chars 2019 -> 1580 ( 21.7% saved) === Full pipeline (real tokenizer) === redundant CSV tokens 768 -> 394 ( 48.7% saved) === Binary spreadsheet (.xlsx) === 2-sheet workbook tokens 1092 -> 683 ( 37.5% saved) ``` - **Not tested:** legacy `.xls` binary path (needs optional `xlrd` + binary fixture; `# pragma: no cover`); base64-embedded `.xlsx` inside multimodal blocks (out of scope, noted as a follow-up). ## Review Readiness - [x] I have performed a self-review - [x] This PR is ready for human review ## Checklist - [x] My code follows the project's style guidelines - [x] I have performed a self-review of my code - [x] I have commented my code, particularly in hard-to-understand areas - [x] I have made corresponding changes to the documentation - [x] My changes generate no new warnings - [x] I have added tests that prove my fix is effective or that my feature works - [x] New and existing unit tests pass locally with my changes - [ ] I have updated the CHANGELOG.md if applicable ## Additional Notes - CHANGELOG/version are intentionally untouched: this repo uses **release-please**, which bumps the version and CHANGELOG via automated `chore: release main` PRs, not per-feature PRs. - The `.xls` path is `# pragma: no cover` (legacy, needs optional `xlrd` + a binary fixture). - Follow-up (out of scope): base64-embedded `.xlsx` inside tool-result/multimodal blocks; porting tabular parsers into the Rust core for parity. --------- Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-19 09:30:20 -07:00
### tabular_compression_demo.py
Tabular + spreadsheet compression on generated sample data (no API key needed).
Shows where CSV/markdown tables and `.xlsx` workbooks compress and where compact,
all-unique data correctly passes through:
```bash
python examples/tabular_compression_demo.py # run all scenarios
python examples/tabular_compression_demo.py --write DIR # also save the sample files
```
## Evaluation Examples
### smart_vs_naive_eval.py
Compare SmartCrusher against naive truncation:
```bash
export OPENAI_API_KEY='your-key'
python examples/smart_vs_naive_eval.py
```
### real_world_eval.py
Comprehensive evaluation with Anthropic models:
```bash
export ANTHROPIC_API_KEY='your-key'
python examples/real_world_eval.py
```
### real_world_openai_eval.py
Comprehensive evaluation with OpenAI models:
```bash
export OPENAI_API_KEY='your-key'
python examples/real_world_openai_eval.py
```
## Demo Directories
### langchain_demo/
Full LangChain agent integration demo:
```bash
# No API key needed for compression demo
PYTHONPATH=. python -m examples.langchain_demo.show_compression
# Full comparison (requires API key)
export OPENAI_API_KEY='your-key'
PYTHONPATH=. python -m examples.langchain_demo.run_comparison
```
See [langchain_demo/README.md](langchain_demo/README.md) for details.
### mcp_demo/
MCP (Model Context Protocol) integration demo:
```bash
export OPENAI_API_KEY='your-key'
PYTHONPATH=. python -m examples.mcp_demo.run_agent_eval
```
feat: Add AWS Strands Agents SDK integration ## Description Add Headroom integration with AWS Strands Agents SDK, enabling automatic context optimization and tool output compression for Strands-based agents. Fixes #14 ## Type of Change - [x] New feature (non-breaking change that adds functionality) - [x] Documentation update ## Changes Made ### Core Integration (`headroom/integrations/strands/`) - **HeadroomHookProvider** - Implements Strands `HookProvider` interface for automatic tool output compression via `AfterToolCallEvent`. Compresses verbose tool outputs before they enter conversation context. - **HeadroomStrandsModel** - Model wrapper that extends Strands `Model` base class for message-level optimization. Implements all required abstract methods: `stream()`, `get_config()`, `update_config()`, `structured_output()`. - **Provider auto-detection** - Automatically detects appropriate Headroom provider (Anthropic, OpenAI, Google) based on wrapped Strands model type. - **`strands-agents` as optional dependency** - Install with `pip install headroom-ai[strands]` ### Testing (`tests/integrations/test_strands/`) - **Real integration tests (25 tests)** - Use actual AWS Bedrock API calls with Claude 3 Haiku. Skip automatically when credentials unavailable. - **Unit tests (57 tests)** - Mock-based tests for internal logic, edge cases, and error handling. No credentials required. ### Demo (`examples/strands_bedrock_demo.py`) - Interactive demo showcasing both integration patterns - Visual before/after compression comparison with token savings - 4 verbose tools (search, logs, database, metrics) demonstrating real savings - Supports `--hook` and `--model` flags for individual demos ## Testing All tests verified: - [x] Unit tests pass (57 tests) - [x] Integration tests pass (25 tests with real Bedrock API) - [x] Linting passes (`ruff check .`) - [x] Type checking passes (`mypy headroom/integrations/strands/`) - [x] Formatting passes (`ruff format --check`) - [x] Demo runs successfully with ~50% token savings ## Test Output ``` $ pytest tests/integrations/test_strands/ -v =================== 82 passed in 90.09s =================== $ ruff check headroom/integrations/strands/ --ignore E402 All checks passed! $ mypy headroom/integrations/strands/ --ignore-missing-imports Success: no issues found ``` ## Demo Results ``` ╭────────────────────────────────────────────────────────────╮ │ HeadroomHookProvider Results │ │────────────────────────────────────────────────────────────│ │ Tokens BEFORE compression: 51,961 │ │ Tokens AFTER compression: 25,658 │ │ Tokens SAVED: 26,303 (50.6%) │ ╰────────────────────────────────────────────────────────────╯ ```
2026-01-31 00:31:37 -08:00
### strands_bedrock_demo.py
AWS Strands Agents + Bedrock integration demo. Showcases two Headroom integration patterns:
1. **HeadroomHookProvider** - Compresses tool outputs in real-time
2. **HeadroomStrandsModel** - Optimizes entire conversation context
```bash
# Configure AWS credentials
export AWS_ACCESS_KEY_ID='your-access-key'
export AWS_SECRET_ACCESS_KEY='your-secret-key'
export AWS_DEFAULT_REGION='us-west-2' # Optional, defaults to us-west-2
# Or use AWS profile
export AWS_PROFILE='your-profile-name'
# Run the full demo (both integration patterns)
python examples/strands_bedrock_demo.py
# Run only the hook provider demo
python examples/strands_bedrock_demo.py --hook
# Run only the model wrapper demo
python examples/strands_bedrock_demo.py --model
# Specify a different AWS region
python examples/strands_bedrock_demo.py --region us-east-1
```
The demo uses Claude 3 Haiku via Bedrock for cost efficiency. It creates agents with
4 tools that return verbose JSON output (search results, logs, database records, metrics)
and displays compression statistics with visual comparisons.
**Requirements:**
- AWS account with Bedrock enabled
- Claude 3 Haiku model access in your region
- `pip install strands-agents headroom-ai[strands]`
## Running Examples
All examples can be run from the repository root:
```bash
# Install dependencies
pip install -e ".[dev]"
# Run any example
python examples/<example_name>.py
```
## Expected Results
| Example | Token Savings | Notes |
|---------|---------------|-------|
| basic_usage | 50-70% | Simple tool output compression |
| langchain_demo | 70-85% | Real agent with multiple tools |
| mcp_demo | 60-80% | MCP tool outputs |
feat: Add AWS Strands Agents SDK integration ## Description Add Headroom integration with AWS Strands Agents SDK, enabling automatic context optimization and tool output compression for Strands-based agents. Fixes #14 ## Type of Change - [x] New feature (non-breaking change that adds functionality) - [x] Documentation update ## Changes Made ### Core Integration (`headroom/integrations/strands/`) - **HeadroomHookProvider** - Implements Strands `HookProvider` interface for automatic tool output compression via `AfterToolCallEvent`. Compresses verbose tool outputs before they enter conversation context. - **HeadroomStrandsModel** - Model wrapper that extends Strands `Model` base class for message-level optimization. Implements all required abstract methods: `stream()`, `get_config()`, `update_config()`, `structured_output()`. - **Provider auto-detection** - Automatically detects appropriate Headroom provider (Anthropic, OpenAI, Google) based on wrapped Strands model type. - **`strands-agents` as optional dependency** - Install with `pip install headroom-ai[strands]` ### Testing (`tests/integrations/test_strands/`) - **Real integration tests (25 tests)** - Use actual AWS Bedrock API calls with Claude 3 Haiku. Skip automatically when credentials unavailable. - **Unit tests (57 tests)** - Mock-based tests for internal logic, edge cases, and error handling. No credentials required. ### Demo (`examples/strands_bedrock_demo.py`) - Interactive demo showcasing both integration patterns - Visual before/after compression comparison with token savings - 4 verbose tools (search, logs, database, metrics) demonstrating real savings - Supports `--hook` and `--model` flags for individual demos ## Testing All tests verified: - [x] Unit tests pass (57 tests) - [x] Integration tests pass (25 tests with real Bedrock API) - [x] Linting passes (`ruff check .`) - [x] Type checking passes (`mypy headroom/integrations/strands/`) - [x] Formatting passes (`ruff format --check`) - [x] Demo runs successfully with ~50% token savings ## Test Output ``` $ pytest tests/integrations/test_strands/ -v =================== 82 passed in 90.09s =================== $ ruff check headroom/integrations/strands/ --ignore E402 All checks passed! $ mypy headroom/integrations/strands/ --ignore-missing-imports Success: no issues found ``` ## Demo Results ``` ╭────────────────────────────────────────────────────────────╮ │ HeadroomHookProvider Results │ │────────────────────────────────────────────────────────────│ │ Tokens BEFORE compression: 51,961 │ │ Tokens AFTER compression: 25,658 │ │ Tokens SAVED: 26,303 (50.6%) │ ╰────────────────────────────────────────────────────────────╯ ```
2026-01-31 00:31:37 -08:00
| strands_bedrock_demo | 60-85% | Strands + Bedrock with verbose tools |
| real_world_eval | 50-90% | Varies by scenario |
## Troubleshooting
**ModuleNotFoundError: No module named 'headroom'**
Run from the repository root with PYTHONPATH:
```bash
PYTHONPATH=. python examples/basic_usage.py
```
Or install in development mode:
```bash
pip install -e .
```
**API Key Errors**
Ensure your API keys are set:
```bash
export OPENAI_API_KEY='sk-...'
export ANTHROPIC_API_KEY='sk-ant-...'
```
feat: Add AWS Strands Agents SDK integration ## Description Add Headroom integration with AWS Strands Agents SDK, enabling automatic context optimization and tool output compression for Strands-based agents. Fixes #14 ## Type of Change - [x] New feature (non-breaking change that adds functionality) - [x] Documentation update ## Changes Made ### Core Integration (`headroom/integrations/strands/`) - **HeadroomHookProvider** - Implements Strands `HookProvider` interface for automatic tool output compression via `AfterToolCallEvent`. Compresses verbose tool outputs before they enter conversation context. - **HeadroomStrandsModel** - Model wrapper that extends Strands `Model` base class for message-level optimization. Implements all required abstract methods: `stream()`, `get_config()`, `update_config()`, `structured_output()`. - **Provider auto-detection** - Automatically detects appropriate Headroom provider (Anthropic, OpenAI, Google) based on wrapped Strands model type. - **`strands-agents` as optional dependency** - Install with `pip install headroom-ai[strands]` ### Testing (`tests/integrations/test_strands/`) - **Real integration tests (25 tests)** - Use actual AWS Bedrock API calls with Claude 3 Haiku. Skip automatically when credentials unavailable. - **Unit tests (57 tests)** - Mock-based tests for internal logic, edge cases, and error handling. No credentials required. ### Demo (`examples/strands_bedrock_demo.py`) - Interactive demo showcasing both integration patterns - Visual before/after compression comparison with token savings - 4 verbose tools (search, logs, database, metrics) demonstrating real savings - Supports `--hook` and `--model` flags for individual demos ## Testing All tests verified: - [x] Unit tests pass (57 tests) - [x] Integration tests pass (25 tests with real Bedrock API) - [x] Linting passes (`ruff check .`) - [x] Type checking passes (`mypy headroom/integrations/strands/`) - [x] Formatting passes (`ruff format --check`) - [x] Demo runs successfully with ~50% token savings ## Test Output ``` $ pytest tests/integrations/test_strands/ -v =================== 82 passed in 90.09s =================== $ ruff check headroom/integrations/strands/ --ignore E402 All checks passed! $ mypy headroom/integrations/strands/ --ignore-missing-imports Success: no issues found ``` ## Demo Results ``` ╭────────────────────────────────────────────────────────────╮ │ HeadroomHookProvider Results │ │────────────────────────────────────────────────────────────│ │ Tokens BEFORE compression: 51,961 │ │ Tokens AFTER compression: 25,658 │ │ Tokens SAVED: 26,303 (50.6%) │ ╰────────────────────────────────────────────────────────────╯ ```
2026-01-31 00:31:37 -08:00
**AWS Credentials Errors (for Strands demo)**
Ensure AWS credentials are configured:
```bash
# Option 1: Environment variables
export AWS_ACCESS_KEY_ID='your-access-key'
export AWS_SECRET_ACCESS_KEY='your-secret-key'
# Option 2: AWS profile
export AWS_PROFILE='your-profile-name'
# Option 3: AWS credentials file (~/.aws/credentials)
```
Also ensure Bedrock and the Claude 3 Haiku model are enabled in your AWS account.