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34 changes: 30 additions & 4 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -38,13 +38,19 @@ export ANTHROPIC_API_KEY=your_key_here
export S2_API_KEY=your_key_here
```

3. Run the pipeline:
3. Copy the example config and tune defaults:

```bash
cp litresearch.toml.example litresearch.toml
```

4. Run the pipeline:

```bash
litresearch run "What is the impact of large language models on software engineering?"
```

4. Inspect the output directory:
5. Inspect the output directory:

```text
output/
Expand Down Expand Up @@ -74,7 +80,8 @@ litresearch run \
--model anthropic/claude-sonnet-4-20250514 \
--top-n 10 \
--threshold 50 \
--output-dir runs/llm-se
--output-dir runs/llm-se \
--overwrite
```

Resume an interrupted run:
Expand All @@ -101,19 +108,38 @@ Supported environment variables:
- `ANTHROPIC_API_KEY`
- `OPENROUTER_API_KEY`
- `S2_API_KEY`
- `S2_TIMEOUT`
- `S2_REQUESTS_PER_SECOND`
- `SCREENING_SELECTION_MODE`
- `SCREENING_TOP_PERCENT`
- `SCREENING_TOP_K`
- `SCREENING_THRESHOLD`

Example `litresearch.toml`:

```toml
default_model = "openai/gpt-4o-mini"
screening_threshold = 40
screening_selection_mode = "top_percent"
screening_top_percent = 0.3
screening_threshold = 60
top_n = 20
max_results_per_query = 20
s2_timeout = 10
s2_requests_per_second = 1.0
pdf_first_pages = 4
pdf_last_pages = 2
output_dir = "output"
```

Screening selection modes:
- `top_percent` (default): deep-analyze the top share of screened papers globally
- `top_k`: deep-analyze the top K screened papers globally
- `threshold`: deep-analyze papers scoring `>= screening_threshold`

Semantic Scholar tuning:
- `s2_timeout`: request timeout in seconds
- `s2_requests_per_second`: global request rate cap across S2 endpoints

## Output Files
- `report.md`: main literature review report with research questions, search summary, top papers, and synthesis
- `paper_analyses.md`: detailed per-paper analysis for all analyzed papers
Expand Down