docs: rebrand evalwire as framework-agnostic evaluation tool

README.md

@@ -2,7 +2,7 @@
 
 ![evalwire logo](docs/assets/logo.svg)
 
-> Systematic, reproducible evaluation of LangGraph nodes and subgraphs against human-curated testsets, tracked in Arize Phoenix.
+> Systematic, reproducible evaluation of any async callable — LangGraph nodes, plain Python functions, REST API endpoints, and more — tracked in Arize Phoenix.
 
 ---
 
@@ -12,12 +12,12 @@
 
 ## What it does
 
-When iterating on a LangGraph agent, it is hard to know whether a change to a specific node improved or degraded its behaviour. Running the full graph end-to-end is expensive and makes it difficult to attribute a score change to a specific component.
+When iterating on any LLM-powered callable — a LangGraph node, a plain Python function, or a REST endpoint — it is hard to know whether a change improved or degraded behaviour. Running the full system end-to-end is expensive and makes it difficult to attribute a score change to a specific component.
 
 `evalwire` solves this by:
 
 - Turning a human-curated CSV of queries and expected outputs into versioned [Arize Phoenix](https://phoenix.arize.com/) datasets.
-- Letting you define a **task** that isolates and invokes individual LangGraph nodes independently of the rest of the graph.
+- Letting you define a **task** — any `async def` callable — that isolates and invokes the component under test.
 - Running those tasks against the stored datasets, scoring each output with one or more **evaluators**, and recording results in Phoenix — giving you a reproducible, comparable experiment per run.
 
 ---

docs/index.md

@@ -1,15 +1,18 @@
 # evalwire
 
-**evalwire** is a Python package for systematic evaluation of [LangGraph](https://github.com/langchain-ai/langgraph) nodes using [Arize Phoenix](https://github.com/Arize-ai/phoenix) experiments.
+**evalwire** is a Python package for systematic evaluation of any async callable — including [LangGraph](https://github.com/langchain-ai/langgraph) nodes, plain functions, REST API endpoints, and other LLM frameworks — using [Arize Phoenix](https://github.com/Arize-ai/phoenix) experiments.
 
 ## Features
 
 - Upload CSV testsets to Phoenix as named datasets
-- Run experiments against any LangGraph node with pluggable evaluators
-- 9 built-in evaluator factories covering retrieval, classification, string matching, structured output, numeric, and LLM-as-a-judge use cases
+- Run experiments against any async callable with pluggable evaluators
+- 12 built-in evaluator factories covering retrieval, classification, string matching, structured output, numeric, LLM-as-a-judge, and evaluator composition
+- Export experiment results to CSV or JSON, compare runs, and generate markdown reports
+- Validate testsets before upload to catch structural and content issues early
+- First-class LangGraph integration via the optional `evalwire[langgraph]` extra
 - OpenTelemetry tracing via `observability.py`
 - Config-file driven via `evalwire.toml`
-- CLI: `evalwire upload` and `evalwire run`
+- CLI: `evalwire upload`, `evalwire run`, `evalwire validate`, `evalwire export`, `evalwire compare`, `evalwire report`
 
 ## Built-in evaluators
 
@@ -24,6 +27,9 @@
 | `make_schema_evaluator` | `bool` | JSON Schema conformance |
 | `make_numeric_tolerance_evaluator` | `bool` | Math / calculation tasks with tolerance |
 | `make_llm_judge_evaluator` | `float \| bool` | LLM-as-a-judge with structured output |
+| `make_weighted_evaluator` | `float` | Weighted average of multiple evaluators |
+| `make_all_pass_evaluator` | `bool` | AND-composition: all evaluators must pass |
+| `make_any_pass_evaluator` | `bool` | OR-composition: at least one evaluator must pass |
 
 ## Navigation
 

src/evalwire/__init__.py

@@ -1,4 +1,4 @@
-"""evalwire — systematic evaluation of LangGraph nodes with Arize Phoenix."""
+"""evalwire — evaluate any async callable with Arize Phoenix experiments."""
 
 import logging
 from importlib.metadata import version

src/evalwire/cli.py

@@ -26,7 +26,7 @@ def _make_client():
 
 @click.group()
 def main() -> None:
-    """evalwire — systematic evaluation of LangGraph nodes with Arize Phoenix."""
+    """evalwire — evaluate any async callable with Arize Phoenix."""
 
 
 @main.command("upload")