Implement llm-connect ADHOC diagnostics

README.md

@@ -73,15 +73,15 @@ config = RunConfig(
 )
 ```
 
-| Field | Default | Description |
-|---|---|---|
-| `model_name` | `"gpt-4"` | Model identifier (adapter may override) |
-| `temperature` | `0.7` | Sampling temperature |
-| `max_tokens` | `2000` | Maximum output tokens |
-| `model_params` | `{}` | Extra provider-specific parameters |
-| `max_depth` | `3` | Max nesting depth for recursive calls |
-| `skip_if_exists` | `True` | Skip if identical input hash already processed |
-| `timeout_seconds` | `300` | Request timeout |
+| Field | Default | Description |
+|---|---|---|
+| `model_name` | `"gpt-4"` | Model identifier (adapter may override) |
+| `temperature` | `0.7` | Sampling temperature |
+| `max_tokens` | `2000` | Maximum output tokens |
+| `model_params` | `{}` | Portable extras translated by each adapter; see `docs/adapter-model-params.md` |
+| `max_depth` | `3` | Max nesting depth for recursive calls |
+| `skip_if_exists` | `True` | Skip if identical input hash already processed |
+| `timeout_seconds` | `300` | Request timeout |
 
 ### `LLMResponse`
 
@@ -92,8 +92,24 @@ response = adapter.execute_prompt(prompt, config)
 print(response.content)       # generated text
 print(response.model)         # model actually used
 print(response.usage)         # {"prompt_tokens": …, "completion_tokens": …, "total_tokens": …}
-print(response.finish_reason) # "stop", "length", etc.
-```
+print(response.finish_reason) # "stop", "length", etc.
+```
+
+## Server diagnostics
+
+Serve mode can include a debug envelope without changing normal responses:
+
+```bash
+LLM_CONNECT_DEBUG=1 python -m llm_connect.server --provider openrouter
+curl 'http://127.0.0.1:8080/execute?debug=1' -d '{"prompt":"hi"}'
+```
+
+Set `LLM_CONNECT_AUDIT_DIR=/path/to/audit` to write per-call replay records,
+then parse one without another provider call:
+
+```bash
+python -m llm_connect.replay /path/to/audit/record.json --json
+```
 
 ## Writing your own adapter