feat: Store LLM request params (max_tokens, model, modality) in pipeline events

- _make_llm_callback now accepts request_params dict
- All 6 LLM call sites pass max_tokens, model_override, modality, response_model, hard_limit
- request_params stored in payload JSONB on every llm_call event (always, not just debug mode)
- Frontend JSON export includes full payload + request_params at top level
- DebugPayloadViewer shows 'Request Params' section even with debug mode off
- Answers whether max_tokens is actually being sent on pipeline requests

backend/pipeline/stages.py

@@ -141,11 +141,19 @@ def _make_llm_callback(
     user_prompt: str | None = None,
     run_id: str | None = None,
     context_label: str | None = None,
+    request_params: dict | None = None,
 ):
     """Create an on_complete callback for LLMClient that emits llm_call events.
 
     When debug mode is enabled, captures full system prompt, user prompt,
     and response text on each llm_call event.
+
+    Parameters
+    ----------
+    request_params:
+        Dict of LLM request parameters (max_tokens, model_override, modality,
+        response_model, temperature, etc.) to store in the event payload for
+        debugging which parameters were actually sent to the API.
     """
     debug = _is_debug_mode()
 
@@ -169,6 +177,7 @@ def _make_llm_callback(
                 "finish_reason": finish_reason,
                 "is_fallback": is_fallback,
                 **({"context": context_label} if context_label else {}),
+                **({"request_params": request_params} if request_params else {}),
             },
             system_prompt_text=system_prompt if debug else None,
             user_prompt_text=user_prompt if debug else None,
@@ -367,7 +376,8 @@ def stage2_segmentation(self, video_id: str, run_id: str | None = None) -> str:
         hard_limit = get_settings().llm_max_tokens_hard_limit
         max_tokens = estimate_max_tokens(system_prompt, user_prompt, stage="stage2_segmentation", hard_limit=hard_limit)
         logger.info("Stage 2 using model=%s, modality=%s, max_tokens=%d", model_override or "default", modality, max_tokens)
-        raw = llm.complete(system_prompt, user_prompt, response_model=SegmentationResult, on_complete=_make_llm_callback(video_id, "stage2_segmentation", system_prompt=system_prompt, user_prompt=user_prompt, run_id=run_id),
+        _s2_request_params = {"max_tokens": max_tokens, "model_override": model_override, "modality": modality, "response_model": "SegmentationResult", "hard_limit": hard_limit}
+        raw = llm.complete(system_prompt, user_prompt, response_model=SegmentationResult, on_complete=_make_llm_callback(video_id, "stage2_segmentation", system_prompt=system_prompt, user_prompt=user_prompt, run_id=run_id, request_params=_s2_request_params),
                            modality=modality, model_override=model_override, max_tokens=max_tokens)
         result = _safe_parse_llm_response(raw, SegmentationResult, llm, system_prompt, user_prompt,
                                           modality=modality, model_override=model_override, max_tokens=max_tokens)
@@ -459,7 +469,8 @@ def stage3_extraction(self, video_id: str, run_id: str | None = None) -> str:
             )
 
             max_tokens = estimate_max_tokens(system_prompt, user_prompt, stage="stage3_extraction", hard_limit=hard_limit)
-            raw = llm.complete(system_prompt, user_prompt, response_model=ExtractionResult, on_complete=_make_llm_callback(video_id, "stage3_extraction", system_prompt=system_prompt, user_prompt=user_prompt, run_id=run_id, context_label=topic_label),
+            _s3_request_params = {"max_tokens": max_tokens, "model_override": model_override, "modality": modality, "response_model": "ExtractionResult", "hard_limit": hard_limit}
+            raw = llm.complete(system_prompt, user_prompt, response_model=ExtractionResult, on_complete=_make_llm_callback(video_id, "stage3_extraction", system_prompt=system_prompt, user_prompt=user_prompt, run_id=run_id, context_label=topic_label, request_params=_s3_request_params),
                                modality=modality, model_override=model_override, max_tokens=max_tokens)
             result = _safe_parse_llm_response(raw, ExtractionResult, llm, system_prompt, user_prompt,
                                               modality=modality, model_override=model_override, max_tokens=max_tokens)
@@ -556,6 +567,7 @@ def _classify_moment_batch(
             video_id, "stage4_classification",
             system_prompt=system_prompt, user_prompt=user_prompt,
             run_id=run_id, context_label=batch_label,
+            request_params={"max_tokens": max_tokens, "model_override": model_override, "modality": modality, "response_model": "ClassificationResult", "hard_limit": hard_limit},
         ),
         modality=modality, model_override=model_override,
         max_tokens=max_tokens,
@@ -865,6 +877,7 @@ def _synthesize_chunk(
             video_id, "stage5_synthesis",
             system_prompt=system_prompt, user_prompt=user_prompt,
             run_id=run_id, context_label=chunk_label,
+            request_params={"max_tokens": estimated_input, "model_override": model_override, "modality": modality, "response_model": "SynthesisResult", "hard_limit": hard_limit},
         ),
         modality=modality, model_override=model_override, max_tokens=estimated_input,
     )
@@ -946,6 +959,7 @@ def _merge_pages_by_slug(
                 system_prompt=merge_system_prompt,
                 user_prompt=merge_user_prompt,
                 run_id=run_id, context_label=f"merge:{slug}",
+                request_params={"max_tokens": max_tokens, "model_override": model_override, "modality": modality, "response_model": "SynthesisResult", "hard_limit": hard_limit},
             ),
             modality=modality, model_override=model_override,
             max_tokens=max_tokens,

frontend/src/pages/AdminPipeline.tsx

@@ -131,6 +131,7 @@ interface DebugSection {
 
 function DebugPayloadViewer({ event }: { event: PipelineEvent }) {
   const sections: DebugSection[] = [];
+  if (event.payload?.request_params) sections.push({ label: "Request Params", content: JSON.stringify(event.payload.request_params, null, 2) });
   if (event.system_prompt_text) sections.push({ label: "System Prompt", content: event.system_prompt_text });
   if (event.user_prompt_text) sections.push({ label: "User Prompt", content: event.user_prompt_text });
   if (event.response_text) sections.push({ label: "Response", content: event.response_text });
@@ -171,11 +172,19 @@ function DebugPayloadViewer({ event }: { event: PipelineEvent }) {
   };
 
   const exportAsJson = () => {
-    const data: Record<string, string | null> = {
+    // Dump everything — full rawdog debug payload with request params
+    const data: Record<string, unknown> = {
       event_id: event.id,
       stage: event.stage,
       event_type: event.event_type,
       model: event.model,
+      prompt_tokens: event.prompt_tokens,
+      completion_tokens: event.completion_tokens,
+      total_tokens: event.total_tokens,
+      duration_ms: event.duration_ms,
+      created_at: event.created_at,
+      payload: event.payload,
+      request_params: event.payload?.request_params ?? null,
       system_prompt_text: event.system_prompt_text,
       user_prompt_text: event.user_prompt_text,
       response_text: event.response_text,