Move podcast cost estimates to backend pricing catalog

backend/api/podcast/cost_estimator.py

@@ -0,0 +1,133 @@
+"""
+Podcast cost estimation helpers.
+
+Builds user-facing podcast estimates from the subscription pricing catalog
+instead of hard-coded frontend heuristics.
+"""
+
+from __future__ import annotations
+
+from typing import Any, Dict, Optional
+from sqlalchemy.orm import Session
+
+from models.subscription_models import APIProvider
+from services.subscription.pricing_service import PricingService
+
+
+def _round_money(value: float) -> float:
+    return round(float(value), 4)
+
+
+def _load_pricing(
+    pricing_service: PricingService,
+    provider: APIProvider,
+    preferred_model: str,
+) -> Optional[Dict[str, Any]]:
+    pricing = pricing_service.get_pricing_for_provider_model(provider, preferred_model)
+    if pricing:
+        return pricing
+    # Fallback to provider default model row (if configured).
+    return pricing_service.get_pricing_for_provider_model(provider, "default")
+
+
+def estimate_podcast_cost(
+    *,
+    db: Session,
+    duration_minutes: int,
+    speakers: int,
+    query_count: int,
+    include_avatar_phase: bool = True,
+) -> Optional[Dict[str, Any]]:
+    """
+    Compute a backend estimate for podcast creation.
+
+    Returns None when pricing rows are unavailable so UI can display "Unavailable".
+    """
+    pricing_service = PricingService(db)
+
+    gemini_pricing = _load_pricing(pricing_service, APIProvider.GEMINI, "gemini-2.5-flash")
+    exa_pricing = _load_pricing(pricing_service, APIProvider.EXA, "exa-search")
+    audio_pricing = _load_pricing(pricing_service, APIProvider.AUDIO, "minimax/speech-02-hd")
+    video_pricing = _load_pricing(pricing_service, APIProvider.VIDEO, "default")
+    image_pricing = _load_pricing(pricing_service, APIProvider.STABILITY, "qwen-image")
+
+    if not gemini_pricing:
+        return None
+
+    minutes = max(1, int(duration_minutes or 1))
+    speaker_count = max(1, int(speakers or 1))
+    research_queries = max(1, int(query_count or 1))
+
+    # Phase-level usage assumptions (token/request proxies for pre-creation estimate).
+    analysis_input_tokens = 1800
+    analysis_output_tokens = 1000
+    research_synthesis_input_tokens = 2200
+    research_synthesis_output_tokens = 900
+    script_input_tokens = max(1800, minutes * 300)
+    script_output_tokens = max(2200, minutes * 700)
+
+    # TTS token proxy: ~900 chars per minute per speaker.
+    estimated_tts_tokens = max(900, minutes * 900 * speaker_count)
+
+    analysis_cost = (
+        analysis_input_tokens * float(gemini_pricing.get("cost_per_input_token") or 0.0)
+        + analysis_output_tokens * float(gemini_pricing.get("cost_per_output_token") or 0.0)
+        + float(gemini_pricing.get("cost_per_request") or 0.0)
+    )
+    research_llm_cost = (
+        research_synthesis_input_tokens * float(gemini_pricing.get("cost_per_input_token") or 0.0)
+        + research_synthesis_output_tokens * float(gemini_pricing.get("cost_per_output_token") or 0.0)
+        + float(gemini_pricing.get("cost_per_request") or 0.0)
+    )
+    script_cost = (
+        script_input_tokens * float(gemini_pricing.get("cost_per_input_token") or 0.0)
+        + script_output_tokens * float(gemini_pricing.get("cost_per_output_token") or 0.0)
+        + float(gemini_pricing.get("cost_per_request") or 0.0)
+    )
+
+    research_search_cost = 0.0
+    if exa_pricing:
+        research_search_cost = research_queries * float(exa_pricing.get("cost_per_request") or 0.0)
+
+    tts_cost = 0.0
+    if audio_pricing:
+        tts_cost = (
+            estimated_tts_tokens * float(audio_pricing.get("cost_per_input_token") or 0.0)
+            + float(audio_pricing.get("cost_per_request") or 0.0)
+        )
+
+    # Assume one video render request per minute (upper-bound planning estimate).
+    video_cost = 0.0
+    if video_pricing:
+        video_cost = minutes * float(video_pricing.get("cost_per_request") or 0.0)
+
+    avatar_cost = 0.0
+    if include_avatar_phase and image_pricing:
+        image_unit = float(image_pricing.get("cost_per_image") or image_pricing.get("cost_per_request") or 0.0)
+        avatar_cost = speaker_count * image_unit
+
+    research_cost = research_search_cost + research_llm_cost
+    total = analysis_cost + research_cost + script_cost + tts_cost + video_cost + avatar_cost
+
+    return {
+        "ttsCost": _round_money(tts_cost),
+        "avatarCost": _round_money(avatar_cost),
+        "videoCost": _round_money(video_cost),
+        "researchCost": _round_money(research_cost),
+        "analysisCost": _round_money(analysis_cost),
+        "scriptCost": _round_money(script_cost),
+        "total": _round_money(total),
+        "currency": "USD",
+        "source": "pricing_catalog",
+        "assumptions": {
+            "analysis_input_tokens": analysis_input_tokens,
+            "analysis_output_tokens": analysis_output_tokens,
+            "research_synthesis_input_tokens": research_synthesis_input_tokens,
+            "research_synthesis_output_tokens": research_synthesis_output_tokens,
+            "script_input_tokens": script_input_tokens,
+            "script_output_tokens": script_output_tokens,
+            "estimated_tts_tokens": estimated_tts_tokens,
+            "research_queries": research_queries,
+            "video_requests": minutes,
+        },
+    }

backend/api/podcast/handlers/analysis.py

@@ -27,6 +27,7 @@ from ..models import (
     PodcastEnhanceIdeaRequest,
     PodcastEnhanceIdeaResponse
 )
+from ..cost_estimator import estimate_podcast_cost
 
 # Check if running in podcast-only demo mode
 def _is_podcast_only_mode() -> bool:
@@ -372,6 +373,13 @@ Requirements:
     listener_cta = data.get("listener_cta") or ""
     research_queries = data.get("research_queries") or []
     exa_suggested_config = data.get("exa_suggested_config") or None
+    estimate = estimate_podcast_cost(
+        db=db,
+        duration_minutes=request.duration,
+        speakers=request.speakers,
+        query_count=len(research_queries) if isinstance(research_queries, list) else 0,
+        include_avatar_phase=podcast_mode != "audio_only",
+    )
 
     return PodcastAnalyzeResponse(
         audience=audience,
@@ -388,6 +396,7 @@ Requirements:
         bible=bible_obj.model_dump() if bible_obj else None,
         avatar_url=final_avatar_url,
         avatar_prompt=final_avatar_prompt,
+        estimate=estimate,
     )
 
 
@@ -492,4 +501,3 @@ Requirements:
     except Exception as exc:
         logger.error(f"[Regenerate Queries] Failed for user {user_id}: {exc}")
         raise HTTPException(status_code=500, detail=f"Regenerate queries failed: {exc}")
-

backend/api/podcast/handlers/research.py

@@ -9,13 +9,16 @@ from typing import Dict, Any, List
 from types import SimpleNamespace
 import json
 import re
+from sqlalchemy.orm import Session
 
 from middleware.auth_middleware import get_current_user
 from api.story_writer.utils.auth import require_authenticated_user
+from services.database import get_db
 from services.blog_writer.research.exa_provider import ExaResearchProvider
 from services.llm_providers.main_text_generation import llm_text_gen
 from services.podcast_bible_service import PodcastBibleService
 from loguru import logger
+from ..cost_estimator import estimate_podcast_cost
 from ..models import (
     PodcastExaResearchRequest,
     PodcastExaResearchResponse,
@@ -32,6 +35,7 @@ router = APIRouter()
 async def podcast_research_exa(
     request: PodcastExaResearchRequest,
     current_user: Dict[str, Any] = Depends(get_current_user),
+    db: Session = Depends(get_db),
 ):
     """
     Run podcast research via Exa and then use LLM to extract deep insights.
@@ -297,6 +301,20 @@ QUALITY STANDARDS:
                 "credibility_score": src.get("credibility_score"),
             }))
 
+    duration_minutes = 10
+    speakers = 1
+    if request.analysis:
+        duration_minutes = int(request.analysis.get("duration", 10) or 10)
+        speakers = int(request.analysis.get("speakers", 1) or 1)
+
+    estimate = estimate_podcast_cost(
+        db=db,
+        duration_minutes=duration_minutes,
+        speakers=speakers,
+        query_count=len(queries),
+        include_avatar_phase=True,
+    )
+
     return PodcastExaResearchResponse(
         sources=sources_payload,
         search_queries=result.get("search_queries", queries) if isinstance(result, dict) else queries,
@@ -306,5 +324,5 @@ QUALITY STANDARDS:
         search_type=result.get("search_type") if isinstance(result, dict) else None,
         provider=result.get("provider", "exa") if isinstance(result, dict) else "exa",
         content=raw_content,
+        estimate=estimate,
     )
-

backend/api/podcast/models.py

@@ -73,6 +73,7 @@ class PodcastAnalyzeResponse(BaseModel):
     bible: Optional[Dict[str, Any]] = None
     avatar_url: Optional[str] = None
     avatar_prompt: Optional[str] = None
+    estimate: Optional[Dict[str, Any]] = None
 
 
 class PodcastEnhanceIdeaRequest(BaseModel):
@@ -193,6 +194,7 @@ class PodcastExaResearchResponse(BaseModel):
     mapped_angles: List[Dict[str, Any]] = []  # Content angles for the episode
     expert_quotes: List[Dict[str, Any]] = []  # Expert quotes from research
     listener_cta_suggestions: List[str] = []  # CTA suggestions
+    estimate: Optional[Dict[str, Any]] = None
 
 
 class PodcastScriptResponse(BaseModel):
@@ -450,4 +452,3 @@ class VoiceCloneResult(BaseModel):
     file_size: int
     task_id: str
     status: str = "completed"
-

frontend/src/components/PodcastMaker/CreateModal.tsx

@@ -253,26 +253,6 @@ export const CreateModal: React.FC<CreateModalProps> = ({ onCreate, open, defaul
     setShowAIDetailsButton(topicInput.trim().length > 0 && !isUrl);
   }, [topicInput, isUrl]);
 
-  // Calculate estimated cost
-  const estimatedCost = useMemo(() => {
-    const chars = Math.max(1000, duration * 900); // ~900 chars per minute
-    const secs = duration * 60;
-    
-    const ttsCost = (chars / 1000) * 0.05;
-    const avatarCost = speakers * 0.15;
-    const videoRate = knobs.bitrate === 'hd' ? 0.06 : 0.03;
-    const videoCost = secs * videoRate;
-    const researchCost = 0.3; // Fixed research cost
-    
-    return {
-      ttsCost: +ttsCost.toFixed(2),
-      avatarCost: +avatarCost.toFixed(2),
-      videoCost: +videoCost.toFixed(2),
-      researchCost: +researchCost.toFixed(2),
-      total: +(ttsCost + avatarCost + videoCost + researchCost).toFixed(2),
-    };
-  }, [duration, speakers, knobs.bitrate, knobs.scene_length_target]);
-
   // Check if avatar is present (from any source: upload, brand avatar, or generated)
   const hasAvatar = Boolean(
     avatarFile ||                         // User uploaded an image
@@ -560,7 +540,7 @@ export const CreateModal: React.FC<CreateModalProps> = ({ onCreate, open, defaul
               placeholderIndex={placeholderIndex}
               loading={enhancingTopic}
               loadingMessage={enhanceTopicMessage}
-              estimatedCost={estimatedCost}
+              estimatedCost={null}
               duration={duration}
               speakers={speakers}
               knobs={knobs}

frontend/src/components/PodcastMaker/CreateStep/TopicUrlInput.tsx

@@ -27,7 +27,7 @@ interface TopicUrlInputProps {
     videoCost: number;
     researchCost: number;
     total: number;
-  };
+  } | null;
   duration?: number;
   speakers?: number;
   knobs?: Knobs;
@@ -115,9 +115,9 @@ export const TopicUrlInput: React.FC<TopicUrlInputProps> = ({
             </Typography>
           </Stack>
           
-          {estimatedCost && (
+          <Tooltip
-            <Tooltip
+            title={
-              title={
+              estimatedCost ? (
                 <Box>
                   <Typography variant="body2" sx={{ fontWeight: 600, mb: 0.5 }}>
                     Estimated Cost Breakdown:
@@ -135,43 +135,49 @@ export const TopicUrlInput: React.FC<TopicUrlInputProps> = ({
                     </Typography>
                   </Typography>
                 </Box>
-              }
+              ) : (
-              arrow
+                "Estimate unavailable until returned by the server."
-              placement="top"
+              )
-              componentsProps={{
+            }
-                tooltip: {
+            arrow
-                  sx: {
+            placement="top"
-                    bgcolor: "#0f172a",
+            componentsProps={{
-                    color: "#ffffff",
+              tooltip: {
-                    maxWidth: 280,
+                sx: {
-                    fontSize: "0.875rem",
+                  bgcolor: "#0f172a",
-                    p: 1.5,
+                  color: "#ffffff",
-                    boxShadow: "0 4px 12px rgba(0,0,0,0.15)",
+                  maxWidth: 280,
-                  },
+                  fontSize: "0.875rem",
+                  p: 1.5,
+                  boxShadow: "0 4px 12px rgba(0,0,0,0.15)",
                 },
-                arrow: {
+              },
-                  sx: {
+              arrow: {
-                    color: "#0f172a",
+                sx: {
-                  },
+                  color: "#0f172a",
                 },
+              },
+            }}
+          >
+            <Chip
+              icon={<AttachMoneyIcon sx={{ fontSize: "0.875rem !important" }} />}
+              label={estimatedCost ? `Est. $${estimatedCost.total}` : "Est. Unavailable"}
+              size="small"
+              sx={{
+                background: estimatedCost
+                  ? "linear-gradient(135deg, rgba(16, 185, 129, 0.12) 0%, rgba(5, 150, 105, 0.12) 100%)"
+                  : "rgba(100, 116, 139, 0.12)",
+                color: estimatedCost ? "#059669" : "#475569",
+                fontWeight: 600,
+                border: estimatedCost
+                  ? "1px solid rgba(16, 185, 129, 0.2)"
+                  : "1px solid rgba(100, 116, 139, 0.25)",
+                fontSize: "0.75rem",
+                height: 26,
+                cursor: "help",
               }}
-            >
+            />
-              <Chip 
+          </Tooltip>
-                icon={<AttachMoneyIcon sx={{ fontSize: "0.875rem !important" }} />}
-                label={`Est. $${estimatedCost.total}`} 
-                size="small"
-                sx={{
-                  background: "linear-gradient(135deg, rgba(16, 185, 129, 0.12) 0%, rgba(5, 150, 105, 0.12) 100%)",
-                  color: "#059669",
-                  fontWeight: 600,
-                  border: "1px solid rgba(16, 185, 129, 0.2)",
-                  fontSize: "0.75rem",
-                  height: 26,
-                  cursor: "help",
-                }}
-              />
-            </Tooltip>
-          )}
         </Stack>
         <Tooltip
           title={

frontend/src/components/PodcastMaker/PodcastDashboard/usePodcastWorkflow.ts

@@ -354,7 +354,7 @@ export const usePodcastWorkflow = ({ projectState, onError }: UsePodcastWorkflow
       try {
         console.log('[Research] Starting research with:', { topic: project.idea, approvedQueries, provider: researchProvider });
         console.log('[Research] Calling podcastApi.runResearch...');
-        const { research: mapped, raw } = await podcastApi.runResearch({
+        const { research: mapped, raw, estimate } = await podcastApi.runResearch({
           projectId: project.id,
           topic: project.idea,
           approvedQueries,
@@ -369,6 +369,9 @@ export const usePodcastWorkflow = ({ projectState, onError }: UsePodcastWorkflow
         console.log('[Research] Response received:', { mapped, raw });
         setResearch(mapped);
         setRawResearch(raw);
+        if (estimate) {
+          setEstimate(estimate);
+        }
         setAnnouncement("Research complete — review fact cards below");
       } catch (researchError) {
         const errorMessage = researchError instanceof Error
@@ -392,7 +395,7 @@ export const usePodcastWorkflow = ({ projectState, onError }: UsePodcastWorkflow
     } finally {
       setIsResearching(false);
     }
-  }, [isResearching, project, selectedQueries, queries, researchProvider, preflightCheck, analysis, setResearch, setRawResearch, setScriptData, setShowScriptEditor, setShowRenderQueue, projectState.bible]);
+  }, [isResearching, project, selectedQueries, queries, researchProvider, preflightCheck, analysis, setResearch, setRawResearch, setEstimate, setScriptData, setShowScriptEditor, setShowRenderQueue, projectState.bible]);
 
 // Add a ref to track if we're currently generating to prevent double calls
   const isGeneratingRef = useRef(false);
@@ -625,4 +628,3 @@ export const usePodcastWorkflow = ({ projectState, onError }: UsePodcastWorkflow
     handleDeleteQuery,
   };
 };
-

frontend/src/components/PodcastMaker/types.ts

@@ -186,7 +186,7 @@ export type CreateProjectPayload = {
 export type CreateProjectResult = {
   projectId: string;
   analysis: PodcastAnalysis;
-  estimate: PodcastEstimate;
+  estimate: PodcastEstimate | null;
   queries: Query[];
   bible?: PodcastBible;
   avatar_url?: string | null;
@@ -222,4 +222,3 @@ export type TaskStatus = {
   created_at?: string;
   updated_at?: string;
 };
-

frontend/src/services/podcastApi.ts

@@ -59,39 +59,41 @@ const deriveSegments = (option?: OptionLike): string[] => {
   return segments.slice(0, 5);
 };
 
-const estimateCosts = ({
+const toPodcastEstimate = (raw: any, voiceId?: string): PodcastEstimate | null => {
-  minutes,
+  if (!raw || typeof raw !== "object") return null;
-  scenes,
+  const numeric = ["ttsCost", "avatarCost", "videoCost", "researchCost", "total"] as const;
-  chars,
+  if (numeric.some((key) => typeof raw[key] !== "number" || Number.isNaN(raw[key]))) {
-  quality,
+    return null;
-  avatars,
+  }
-  queryCount = 3,
+  const isCustomVoice = Boolean(
-  voiceId,
+    voiceId &&
-}: {
+      ![
-  minutes: number;
+        "Wise_Woman",
-  scenes: number;
+        "Friendly_Person",
-  chars: number;
+        "Inspirational_girl",
-  quality: string;
+        "Deep_Voice_Man",
-  avatars: number;
+        "Calm_Woman",
-  queryCount?: number;
+        "Casual_Guy",
-  voiceId?: string;
+        "Lively_Girl",
-}): PodcastEstimate => {
+        "Patient_Man",
-  const secs = Math.max(60, minutes * 60);
+        "Young_Knight",
-  const ttsCost = (chars / 1000) * 0.05;
+        "Determined_Man",
-  const avatarCost = avatars * 0.15;
+        "Lovely_Girl",
-  const videoRate = quality === "hd" ? 0.06 : 0.03;
+        "Decent_Boy",
-  const videoCost = secs * videoRate;
+        "Imposing_Manner",
-  const researchCost = +(Math.max(1, queryCount) * 0.1).toFixed(2);
+        "Elegant_Man",
-  const total = +(ttsCost + avatarCost + videoCost + researchCost).toFixed(2);
+        "Abbess",
-  const isCustomVoice = Boolean(voiceId && !["Wise_Woman", "Friendly_Person", "Inspirational_girl", "Deep_Voice_Man", "Calm_Woman", "Casual_Guy", "Lively_Girl", "Patient_Man", "Young_Knight", "Determined_Man", "Lovely_Girl", "Decent_Boy", "Imposing_Manner", "Elegant_Man", "Abbess", "Sweet_Girl_2", "Exuberant_Girl"].includes(voiceId));
+        "Sweet_Girl_2",
-  const voiceName = isCustomVoice ? "My Voice Clone" : (!voiceId ? "Wise Woman" : voiceId.replace(/_/g, " "));
+        "Exuberant_Girl",
+      ].includes(voiceId)
+  );
   return {
-    ttsCost: +ttsCost.toFixed(2),
+    ttsCost: raw.ttsCost,
-    avatarCost: +avatarCost.toFixed(2),
+    avatarCost: raw.avatarCost,
-    videoCost: +videoCost.toFixed(2),
+    videoCost: raw.videoCost,
-    researchCost,
+    researchCost: raw.researchCost,
-    total,
+    total: raw.total,
-    voiceName,
+    voiceName: isCustomVoice ? "My Voice Clone" : (!voiceId ? "Wise Woman" : voiceId.replace(/_/g, " ")),
     isCustomVoice,
   };
 };
@@ -174,6 +176,7 @@ type ExaResearchResult = {
   sources: ExaSource[];
   search_queries?: string[];
   cost?: { total?: number };
+  estimate?: PodcastEstimate | null;
   search_type?: string;
   provider?: string;
   content?: string;
@@ -290,15 +293,7 @@ export const podcastApi = {
     // so users can manually choose which queries to run
 
     const projectId = createId("podcast");
-    const estimate = estimateCosts({
+    const estimate = toPodcastEstimate(analysisResp.data?.estimate, payload.knobs.voice_id);
-      minutes: payload.duration,
-      scenes: Math.ceil((payload.duration * 60) / (payload.knobs.scene_length_target || DEFAULT_KNOBS.scene_length_target)),
-      chars: Math.max(1000, payload.duration * 900),
-      quality: payload.knobs.bitrate || "standard",
-      avatars: payload.speakers,
-      queryCount: queries.length || 3,
-      voiceId: payload.knobs.voice_id,
-    });
 
     return {
       projectId,
@@ -325,7 +320,7 @@ export const podcastApi = {
     bible?: any;
     analysis?: PodcastAnalysis | null;
     onProgress?: (message: string) => void;
-  }): Promise<{ research: Research; raw: any }> {
+  }): Promise<{ research: Research; raw: any; estimate?: PodcastEstimate | null }> {
     const keywords = params.approvedQueries.map((q) => q.query).filter(Boolean);
     if (!keywords.length) {
       throw new Error("At least one query must be approved for research.");
@@ -372,7 +367,11 @@ export const podcastApi = {
       params.onProgress("Deep research completed with Exa.");
     }
     const mapped = mapExaResearchResponse(exaResult);
-    return { research: mapped, raw: exaResult };
+    return {
+      research: mapped,
+      raw: exaResult,
+      estimate: toPodcastEstimate(exaResult.estimate, params.analysis?.suggestedKnobs?.voice_id),
+    };
   },
 
   async generateScript(params: {
@@ -953,4 +952,3 @@ export const podcastApi = {
 };
 
 export type PodcastApi = typeof podcastApi;
-