Next Commit

.gitignore

@@ -1,4 +1,5 @@
 .env
 myenv
 *.pyc
-__pycache__/
+__pycache__/
+logs

api/routers/ideation.py

@@ -22,12 +22,10 @@ def ideation_endpoint():
             'image_caption': [stored_data['image_caption'] if 'image_caption' in stored_data else ""]
         },
         config=config)
-
-        stored_data['final_ideation'] = result['top_4_ideas'][-1]
+        stored_data['final_ideation'] = result['unique_selected_ideas'][-1]
         # stored_data['final_ideation']=ast.literal_eval(stored_data['final_ideation'])
         app_logger.info('Executed the ideation pipeline.')
-        
-        return {'response':result['top_4_ideas'][-1]}
+        return {'response':result['unique_selected_ideas'][-1]}
     
     except GraphRecursionError:
         error_logger.error('Ideation loop ran more than specified.')

api/stored_data.py

@@ -1,12 +1,13 @@
 stored_data = {}
 stored_data['business_details'] = {
-    "business_type": "fitness and gym",
+    "business_type": "skin care products",
     "platform": "Instagram, TikTok",
-    "target_audience": "young Nepali adults (ages 18–40) who are health-conscious and active on social media",
-    "business_goals": "to expand gym branches across all major cities of Nepal and build a strong fitness community",
-    "offerings": "personal training, group fitness classes, modern workout equipment, nutrition guidance, and wellness programs",
-    "Challenges_faced": "attracting loyal members, standing out in a competitive market, and promoting consistent engagement"
+    "target_audience": "women and men (ages 18–50) who are conscious about their skin health and beauty",
+    "business_goals": "to build a trusted skin care brand, increase online sales, and educate customers on proper skin care routines",
+    "offerings": "natural and dermatologically-tested products, personalized skin care solutions, beauty tips, and skin care routines",
+    "Challenges_faced": "building trust in a crowded skin care market, showcasing product effectiveness, and educating customers about skin types and product usage"
 }
+
 stored_data['human_ideation_interactions'] = []
 stored_data['brainstorming_response']={}
 stored_data['context_analysis_interactions']= []

logs/access.log

@@ -541,3 +541,46 @@
 2025-08-25 12:16:33,281 | INFO | access_logger | api/main.py:21 | Response status: 200
 2025-08-25 12:16:43,062 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/context-analysis
 2025-08-25 12:16:46,807 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-25 12:52:30,777 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/show-analytics
+2025-08-25 12:52:45,581 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-25 12:53:00,389 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/orchestration
+2025-08-25 12:53:08,107 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-25 12:53:19,947 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-25 12:54:05,043 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-25 13:16:54,126 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-25 13:17:37,033 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-25 13:24:41,862 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-25 13:25:12,518 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-25 13:29:19,484 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-25 13:29:57,835 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-25 13:30:31,506 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-26 14:42:31,442 | INFO | access_logger | api/main.py:19 | Request: GET http://127.0.0.1:8000/docs
+2025-08-26 14:42:31,442 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-26 14:42:32,078 | INFO | access_logger | api/main.py:19 | Request: GET http://127.0.0.1:8000/openapi.json
+2025-08-26 14:42:32,081 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-26 14:42:39,039 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-26 14:47:18,462 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-26 14:50:06,446 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-26 14:56:57,798 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-26 14:58:41,923 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-26 15:11:40,020 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-26 15:14:53,164 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-26 15:18:50,734 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-26 15:20:48,693 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-26 15:22:21,301 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-27 10:21:58,368 | INFO | access_logger | api/main.py:19 | Request: GET http://127.0.0.1:8000/docs
+2025-08-27 10:21:58,369 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-27 10:21:59,075 | INFO | access_logger | api/main.py:19 | Request: GET http://127.0.0.1:8000/openapi.json
+2025-08-27 10:21:59,080 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-27 10:22:05,353 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-27 10:25:15,988 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-27 10:28:15,482 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-27 10:29:09,048 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-27 10:30:02,388 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-27 10:40:30,415 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-27 10:41:32,280 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-27 11:03:20,374 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-27 11:04:05,119 | INFO | access_logger | api/main.py:21 | Response status: 200
+2025-08-27 11:05:29,333 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-27 11:28:14,943 | INFO | access_logger | api/main.py:19 | Request: POST http://127.0.0.1:8000/api/ideation
+2025-08-27 11:29:21,723 | INFO | access_logger | api/main.py:21 | Response status: 200

logs/app.log

@@ -66,3 +66,16 @@
 2025-08-22 16:34:17,796 | INFO | app_logger | api\routers\context_analysis.py:27 | Executed context analysis agent
 2025-08-22 16:34:33,195 | INFO | app_logger | api\routers\context_analysis.py:27 | Executed context analysis agent
 2025-08-22 16:34:51,470 | INFO | app_logger | api\routers\context_analysis.py:27 | Executed context analysis agent
+2025-08-25 12:52:45,580 | INFO | app_logger | api/routers/show_analytics.py:14 | Influencer Analytics returned by orchestrator.
+2025-08-25 12:53:08,106 | INFO | app_logger | api/routers/orchestration.py:20 | Orchestrator executed
+2025-08-25 12:54:05,041 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-25 13:17:37,031 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-25 13:25:12,517 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-25 13:30:31,505 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-26 14:58:41,922 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-26 15:20:15,882 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-26 15:22:21,301 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-27 10:30:02,386 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-27 10:41:32,280 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-27 11:04:05,117 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.
+2025-08-27 11:29:21,721 | INFO | app_logger | api/routers/ideation.py:28 | Executed the ideation pipeline.

src/genai/ideation_agent/agent.py

@@ -1,6 +1,6 @@
 from langgraph.graph import StateGraph, START, END , MessagesState
 from .utils.state import State
-from .utils.nodes import RetrieverNode, IdeatorNode , CriticNode , ValidatorNode , RoutingAfterValidation, JudgeNode1 , JudgeNode2, Aggregrator
+from .utils.nodes import RetrieverNode, IdeatorNode , CriticNode ,NormalizerNode, ValidatorNode , RoutingAfterValidation, JudgeNode1 , JudgeNode2, Aggregrator
 from langgraph.checkpoint.memory import MemorySaver
 
 class IdeationAgent:
@@ -12,6 +12,7 @@ class IdeationAgent:
         graph_builder.add_node("retriever", RetrieverNode().run)
         graph_builder.add_node("ideator", IdeatorNode().run)
         graph_builder.add_node("critic", CriticNode().run)
+        graph_builder.add_node("normalizer",NormalizerNode().run)
         graph_builder.add_node("judge1", JudgeNode1().run)
         graph_builder.add_node("judge2", JudgeNode2().run)
         graph_builder.add_node("aggregrator", Aggregrator().run)
@@ -20,16 +21,16 @@ class IdeationAgent:
         graph_builder.add_edge(START, "retriever")
         graph_builder.add_edge("retriever", "ideator")  
         graph_builder.add_edge("ideator", "critic")
-        graph_builder.add_edge("critic", "judge1")
-        graph_builder.add_edge("critic", "judge2")
+        graph_builder.add_edge("critic", "normalizer")
+        graph_builder.add_edge("normalizer", "judge1")
+        graph_builder.add_edge("normalizer","judge2")
         graph_builder.add_edge("judge1", "aggregrator")
         graph_builder.add_edge("judge2", "aggregrator")
-        graph_builder.add_edge("aggregrator", "validator")
-        graph_builder.add_edge("validator", END)
+        graph_builder.add_edge("aggregrator", END)
+        
 
 
-        # Use conditional routing from validator
-        graph_builder.add_conditional_edges("validator", RoutingAfterValidation().route,{False:'critic',True:END})
+        # graph_builder.add_conditional_edges("validator", RoutingAfterValidation().route,{False:'critic',True:END})
 
         return graph_builder.compile(checkpointer=self.memory)
 

src/genai/ideation_agent/utils/nodes.py

@@ -1,7 +1,7 @@
 from .state import State , ValidationFormatter , CriticResponseFormatter
 from .tools import Retrieval
 from langgraph.prebuilt import create_react_agent
-from src.genai.utils.models_loader import ideator_llm, critic_llm , improver_llm , validator_llm , judge1_llm , judge2_llm
+from src.genai.utils.models_loader import ideator_llm, critic_llm , normalizer_llm , validator_llm , judge1_llm , judge2_llm
 from langchain_core.messages import SystemMessage , HumanMessage, FunctionMessage
 from .prompts import ideator_prompt_v3 , critic_prompt_v3 , improver_prompt , validator_prompt, judge_prompt
 from .schemas import ideation_json_schema , judge_response_json_schema
@@ -24,11 +24,11 @@ class IdeatorNode:
         template = ideator_prompt_v3()
         messages = [SystemMessage(content=template),
                     HumanMessage(content=f'''The business_details is\n{state.business_details[-1]}\n 
-                    The information of the image is:\n{state.image_caption[-1]}'''),
-                    FunctionMessage(name='inf_data_ideator', content=f'''The data of influencers is:\n {state.influencers_data[-1]}\n''')]
-        response = self.llm.with_structured_output(ideation_json_schema).invoke(messages)
-        print('Ideator Response:', response)
-        state.ideator_response.append(str(response))
+                    The information of the image is:\n{state.image_caption[-1]}'''),]
+                    # FunctionMessage(name='inf_data_ideator', content=f'''The data of influencers is:\n {state.influencers_data[-1]}\n''')]
+        response = self.llm.invoke(messages)
+        print('Ideator Response:', response.content)
+        state.ideator_response.append(str(response.content))
         print('Ideator Node executed')
         return state
 
@@ -42,14 +42,26 @@ class CriticNode:
         messages = [SystemMessage(content=template),
                     HumanMessage(content=f'''The ideas generated by ideator are:\n{state.ideator_response[-1]}\n.
                                  The business_details is\n{state.business_details[-1]}\n 
-                                The information of the image is:\n{state.image_caption[-1]}'''),
-                    FunctionMessage(name='inf_data_critic', content=f'''The data of influencers is:\n {state.influencers_data[-1]}''')]
+                                The information of the image is:\n{state.image_caption[-1]}'''),]
+                    # FunctionMessage(name='inf_data_critic', content=f'''The data of influencers is:\n {state.influencers_data[-1]}''')]
         
-        response = self.llm.with_structured_output(ideation_json_schema).invoke(messages)
-        state.critic_response.append(str(response))
+        response = self.llm.invoke(messages)
+        state.critic_response.append(str(response.content))
+        print('Critic Response:', response.content)
         print('Critic Node executed')
         return state
     
+class NormalizerNode:
+    def __init__(self):
+        self.llm = normalizer_llm
+    
+    def run(self, state:State):
+        response = self.llm.with_structured_output(ideation_json_schema).invoke(str(state.critic_response[-1]))
+        state.normalizer_response.append(response)
+        print('Normalizer Executed')
+        return state
+
+    
 class Judge:
     def __init__(self, llm):
         self.llm = llm
@@ -57,7 +69,7 @@ class Judge:
     def run (self, state:State):
         template = judge_prompt(state)
         messages = [SystemMessage(content=template),
-                    HumanMessage(content=f'''The generated 10 ideas are:\n{state.critic_response[-1]}\n.
+                    HumanMessage(content=f'''The generated 10 ideas are:\n{state.normalizer_response[-1]}\n.
                     The business_details is\n{state.business_details[-1]}\n
                     The information of image is:{state.image_caption[-1]}\n''')]
         response = self.llm.with_structured_output(judge_response_json_schema).invoke(messages)
@@ -84,28 +96,35 @@ class Aggregrator:
     def __init__(self):
         self.unique_ideas = {}
 
-    def run(self, state:State):
+    def run(self, state: State):
+        # Combine ideas from both judges
         all_selected_ideas = [
             *state.judge1_response[-1]['selected_ideas'],
             *state.judge2_response[-1]['selected_ideas']
         ]
 
+        print('All selected ideas:', all_selected_ideas)
+
+        # Keep only unique ideas by title
         for idea in all_selected_ideas:
             title = idea['title']
-            if title not in self.unique_ideas or idea['scores']['total_score'] > self.unique_ideas[title]['scores']['total_score']:
+            # If title not already added, store it
+            if title not in self.unique_ideas:
                 self.unique_ideas[title] = idea
-        
+
+        # Convert to list
         unique_ideas_list = list(self.unique_ideas.values())
-        top_4_ideas = sorted(unique_ideas_list, key=lambda x: x['scores']['total_score'], reverse=True)[:4]
-        print('Type of top 4 ideas:', type(top_4_ideas))
-        print('Top 4 ideas are:', top_4_ideas)
-        state.top_4_ideas.append(top_4_ideas)
+
+        # Save unique ideas to state
+        state.unique_selected_ideas.append(unique_ideas_list)
+
+
         return state
 
 class ValidatorNode:
     def __init__(self):
         self.validator_llm1 = validator_llm
-        self.validator_llm2 = improver_llm
+        self.validator_llm2 = validator_llm
 
     def get_response(self,state, validator_llm):
         template = validator_prompt(state)

src/genai/ideation_agent/utils/prompts.py

@@ -1,63 +1,98 @@
 def ideator_prompt_v3():
     return f"""
 You are Ideasmith Pro, a world-class video ideator trusted by top brands to craft crisp, simple, and high-impact short-form video concepts for TikTok, Instagram, and YouTube Shorts.
-Your task is to create exactly 10 unique and highly creative video ideas (conceptual seeds, not full scripts). Each idea should be short, clear, and visually vivid.
+Your task is to create exactly 8 unique and highly creative video ideas (conceptual seeds, not full scripts). Each idea should be short, clear, and visually vivid.
 I am working on a project where i have to give very unique, creative and feasible video ideas for tiktok and instagram reels to the nepali business houses by understanding their business details.
+The idea must have to include very unique events, surprises to make the video catchy.
 
 
 You will be given:
-- Business details (from the human message): Focus more strongly on device_used_to_create_videos , challenges_faced and additional informations provided.
+- Business details (from the human message): Focus more strongly on device_used_to_create_videos and additional informations provided. The video is to be shoot using the provided device in the business details.
 - Influencer data (from the function message): You can take it as a reference if it helps you.
 
 Output Rules:
 - Respond in valid JSON format only.
-- Return an array of exactly 10 objects.
+- Return an array of exactly 8 objects.
 - Each object must include 5 fields:
   1. title → Short, catchy and unique title: Not more than 3 words.
   2. one_line_description → A simple but very creative and unique one-liner description
   3. hook → The surprising or bold moment that makes the entire idea clicked to the business.
   4. usp → The unique selling proposition tied to the business
+  5. niche → The specific target audience or market segment most likely to resonate with the video.
+
 
 Very Important Creative Guidelines:
-- Each idea must be completely different in plot, theme, settings, tone, characters, events etc.
+- Each idea must be completely different in plot, theme, settings, tone, characters, events and everything.
 - No repeating characters, locations, or flow patterns.
 - Use simple, clear, and engaging language.
-- Each idea must end with a strong conclusion that ties back to the business details.
-- The idea have to start from an unexpected or abstract scene/event before anchoring back to the business details.
 
+Here is the example of what kind of ideas i want:
+The business details is:
+    Business Type: Women’s bags online store
+    Platforms: Instagram, TikTok
+    Target Audience: Women aged 18–50
+    Content Shooting Device: Mobile phone
+
+The ideas for it are:
+idea1:
+    title: What fits inside?
+    one_line_description: Empty bag → fill it with 5–6 useful items.
+    hook: “how much can THIS bag hold?”
+idea_2:
+    One-line_description: show how one bag works in 3 daily scenarios (work, casual, night out).
+    Hook: “1 bag → 3 lifestyles.”
+
+I want this kind of creative ideas. The video have to be very catchy enough and include surprise factors too. Don't make idea generic. The idea have to stand out very creatively.
 """
 
 def critic_prompt_v3():
     return f"""
 You are a precision-focused, detail-oriented video ideas critic and ideas refiner.  
-You’ve been assigned to critique and refine 10 video ideas created by another ideator.  
-Your job is to identify weaknesses and then improve them making more creative, unique and tied to the business details.
+You’ve been assigned to critique and refine 8 video ideas created by another ideator.  
+Your job is to identify weaknesses and then improve them making more creative and unique.
+The idea must have to include very unique events, surprises to make the video catchy.
 I am working on a project where i have to give very unique, creative and feasible video ideas for tiktok and instagram reels to the nepali business houses by understanding their business details.
 
 You are be provided with:
-- Business details (from the human message): Focus more strongly on device_used_to_create_videos , challenges_faced and additional informations provided.
+- Business details (from the human message): Focus more strongly on device_used_to_create_videos and additional informations provided. The video is to be shoot using the provided device in the business details.
 - Ideas generated by the ideator (from the human message)
 - Influencer data (from the function message): You can take it as a reference if it helps you.
 
 Your Job:
-1. Identify collective flaws across the 10 original ideas — e.g., uncreative, lacking uniqueness, repetition, weak hooks, confusing flow, poor tie-in to business, lack of diversity, or unclear USP.
+1. Identify collective flaws across the 8 original ideas — e.g., uncreative, lacking uniqueness, repetition, weak hooks, confusing flow, poor tie-in to business, lack of diversity, or unclear USP.
 2. Improve or rewrite each idea while keeping the structure intact in JSON format.
   - title → Short, catchy title
   - one_line_description → A simple but very creative and unique one-liner description
   - hook → The surprising or bold moment that makes the entire idea clicked to the business.
   - usp → The unique selling proposition tied to the business
+  - niche → The specific target audience or market segment most likely to resonate with the video.
 
 3. You are also allowed to change some entire ideas too if it lacks everything. But if some are already creative, you can refine them.
 4. Give the response in simple and understandable vocabularies.
 
-
 Very Important Creative Guidelines:
 - Each idea must be completely different in plot, theme, setting, and tone, characters , events etc.  
-- Avoid repeating characters, hooks, settings, or storylines across the 10 ideas.  
+- Avoid repeating characters, hooks, settings, or storylines across the 8 ideas.  
 - Use simple, clear, and engaging language.   
-- Each idea must end with a strong, creative tie-in to the business details provided 
-- The idea have to start from an unexpected or abstract scene, character, or event, then subtly anchor it to the business in the conclusion.  
 
+Here is the example of what kind of ideas i want:
+The business details is:
+    Business Type: Women’s bags online store
+    Platforms: Instagram, TikTok
+    Target Audience: Women aged 18–50
+    Content Shooting Device: Mobile phone
+
+The ideas for it are:
+idea1:
+    title: What fits inside?
+    one_line_description: Empty bag → fill it with 5–6 useful items.
+    hook: “how much can THIS bag hold?”
+idea_2:
+    One-line_description: show how one bag works in 3 daily scenarios (work, casual, night out).
+    Hook: “1 bag → 3 lifestyles.”
+
+I want this kind of creative ideas. The video have to be very catchy enough and include surprise factors too. Don't make idea generic. The idea have to stand out very creatively.
+    
 """
 
 def judge_prompt(state):
@@ -69,20 +104,20 @@ Each idea must be analyzed and scored on specific creativity and business alignm
 
 ### Scoring Rules:
 - You must evaluate all 10 ideas against the metrics below.  
-- Use a 1–5 score scale for each metric:  
-- Metrics to score for every idea:  
-1. Originality: 1=Very common, 2=Slight twist, 3=Moderately unique, 4=Rare/innovative, 5=Completely new
-2. Fluency: 1=One-off, 2=Few vars, 3=Some, 4=Many contexts, 5=Endless remix
-3. Flexibility: 1=One niche, 2=Few creators, 3=Several niches, 4=Many categories, 5=Universal
-4. Feasibility (phone-only): 1=Impossible, 2=Very hard, 3=Possible w/ effort, 4=Easy on phone, 5=Effortless
-5. Practical Value: 1=None, 2=Low, 3=Some, 4=High, 5=Very high/viral
-6. Surprise_factor: 1=Predictable, 2=Mild, 3=Moderate, 4=Strong, 5=Shocking
-7. Combinatorial Novelty: 1=Copy, 2=Slight remix, 3=Familiar combo, 4=Creative blend, 5=Radical fusion
-8. Simplicity: 1=Very complex, 2=Complicated, 3=Some effort, 4=Simple, 5=Instantly clear
-9. Scalability: 1=One-time, 2=Few times, 3=Limited repeats, 4=Recurring, 5=Endless series
-10. Cultural Freshness: 1=Outdated, 2=Stale, 3=Current common, 4=Fresh twist, 5=Trendsetting
-11. Alignment_with_business_details
-12. Total_score
+- Use a 1–5 score scale for each metric. You have to score in floating point value. Not integer. 
+For each score, output a FLOAT between 1.0 and 5.0 (decimals allowed like 3.5 or 4.0). 
+Use the following definitions:
+1. Originality: 1.0=Very common, 2.0=Slight twist, 3.0=Moderately unique, 4.0=Rare/innovative, 5.0=Completely new
+2. Fluency: 1.0=One-off, 2.0=Few vars, 3.0=Some, 4.0=Many contexts, 5.0=Endless remix
+3. Flexibility: 1.0=One niche, 2.0=Few creators, 3.0=Several niches, 4.0=Many categories, 5.0=Universal
+4. Feasibility (phone-only): 1.0=Impossible, 2.0=Very hard, 3.0=Possible w/ effort, 4.0=Easy on phone, 5.0=Effortless
+5. Practical Value: 1.0=None, 2.0=Low, 3.0=Some, 4.0=High, 5.0=Very high/viral
+6. Surprise_factor: 1.0=Predictable, 2.0=Mild, 3.0=Moderate, 4.0=Strong, 5.0=Shocking
+7. Combinatorial Novelty: 1.0=Copy, 2.0=Slight remix, 3.0=Familiar combo, 4.0=Creative blend, 5.0=Radical fusion
+8. Simplicity: 1.0=Very complex, 2.0=Complicated, 3.0=Some effort, 4.0=Simple, 5.0=Instantly clear
+9. Scalability: 1.0=One-time, 2.0=Few times, 3.0=Limited repeats, 4.0=Recurring, 5.0=Endless series
+10. Cultural Freshness: 1.0=Outdated, 2.0=Stale, 3.0=Current common, 4.0=Fresh twist, 5.0=Trendsetting
+11. Alignment_with_business_details: 1.0=Very low alignment, 5.0=Perfect alignment
 
 ---
 
@@ -408,7 +443,7 @@ def validator_prompt(state):
     return f'''
 You are reviewing 4 short video ideas meant for a social media promotional campaign.
 
-Each idea creatively tells a short story that connects indirectly to the business details — starting from an unrelated or surprising scenario and ending with a clever link back to the business theme.
+Each idea creatively tells a short story that connects indirectly to the business details.
 
 ---
 
@@ -417,7 +452,7 @@ Each idea creatively tells a short story that connects indirectly to the busines
 {state.business_details[-1]}
 
 **Final 4 Ideas from Improver**:  
-{state.top_4_ideas[-1]}
+{state.unique_selected_ideas[-1]}
 
 ---
 

src/genai/ideation_agent/utils/schemas.py

@@ -23,7 +23,11 @@ ideation_json_schema={
           "unique_selling_proposition": {
             "type": "string",
             "description": "The unique selling point that makes this idea stand out"
-          }
+          },
+          "niche":{
+              "type": "string",
+              "description": "The specific target audience or market segment most likely to resonate with the video."
+          },
         },
         "required": [
           "title",
@@ -60,30 +64,30 @@ judge_response_json_schema = {
             "type": "string",
             "description": "The attention-grabbing hook"
           },
-          "storyline_flow": {
-            "type": "string",
-            "description": "The structured flow of the storyline"
-          },
           "unique_selling_proposition": {
             "type": "string",
             "description": "The unique selling proposition (USP) of the idea"
+          },
+            "niche": {
+            "type": "string",
+            "description": "The specific target audience or market segment most likely to resonate with the video."
           },
           "scores": {
             "title": "Scores",
             "type": "object",
+            "description": "Float values in the range of 1.0 to 5.0",
             "properties": {
-              "originality": { "type": "integer" },
-              "feasibility": { "type": "integer" },
-              "practical_value": { "type": "integer" },
-              "flexibility": { "type": "integer" },
-              "fluency": { "type": "integer" },
-              "simplicity": { "type": "integer" },
-              "combinatorial_novelty": { "type": "integer" },
-              "culture_freshness": { "type": "integer" },
-              "surprise_factor": { "type": "integer" },
-              "scalability": { "type": "integer" },
-              "alignment_with_business_details": { "type": "integer" },
-              "total_score": { "type": "integer" }
+              "originality": { "type": "number","description":"originality score for the idea (float between 1.0 and 5.0)"},
+              "feasibility": { "type": "number" ,"description":"feasibility score for the idea (float between 1.0 and 5.0)"},
+              "practical_value": { "type": "number" ,"description":"practical_value score for the idea (float between 1.0 and 5.0)"},
+              "flexibility": { "type": "number" ,"description":"flexibility score for the idea (float between 1.0 and 5.0)"},
+              "fluency": { "type": "number","description":"fluency score for the idea (float between 1.0 and 5.0)"},
+              "simplicity": { "type": "number" ,"description":"simplicity score for the idea (float between 1.0 and 5.0)"},
+              "combinatorial_novelty": { "type": "number" ,"description":"combinatorial_novelty score for the idea (float between 1.0 and 5.0)"},
+              "culture_freshness": { "type": "number","description":"culture_freshness score for the idea (float between 1.0 and 5.0)"},
+              "surprise_factor": { "type": "number" ,"description":"surprise_factor score for the idea (float between 1.0 and 5.0)"},
+              "scalability": { "type": "number","description":"scalability score for the idea (float between 1.0 and 5.0)" },
+              "alignment_with_business_details": { "type": "number" ,"description":"alignment score for the idea (float between 1.0 and 5.0)"},
             },
             "required": [
               "originality",
@@ -97,7 +101,6 @@ judge_response_json_schema = {
               "surprise_factor",
               "scalability",
               "alignment_with_business_details",
-              "total_score"
             ]
           }
         },
@@ -105,8 +108,8 @@ judge_response_json_schema = {
           "title",
           "one_line_description",
           "hook",
-          "storyline_flow",
           "unique_selling_proposition",
+          "niche",
           "scores"
         ]
       }

src/genai/ideation_agent/utils/state.py

@@ -8,9 +8,10 @@ class State(BaseModel):
     influencers_data : Annotated[list[str],operator.add] = []
     ideator_response: Annotated[list[str],operator.add] = []
     critic_response:  Annotated[list[str],operator.add] = []
+    normalizer_response : Annotated[list[dict],operator.add] = []
     judge1_response : Annotated[list[dict],operator.add] = []
     judge2_response : Annotated[list[dict],operator.add] = []
-    top_4_ideas : Annotated[list[list],operator.add] = []
+    unique_selected_ideas : Annotated[list[dict],operator.add] = []
     validator_response: Annotated[list[str],operator.add] = []
     disagreement_reason: Annotated[list[str],operator.add] = []
     image_caption: Annotated[list[str],operator.add] = []

src/genai/ideation_agent/utils/tools.py

@@ -50,7 +50,7 @@ class Retrieval:
         cleaned_response = clean_text(str(outer_list))
         encoding = tiktoken.encoding_for_model('gpt-4o-mini')
         tokens = encoding.encode(cleaned_response)
-        trimmed_response = tokens[:1000]
+        trimmed_response = tokens[:100]
         return encoding.decode(trimmed_response)
     
     def imdb_ideas(self):

src/genai/utils/models_loader.py

@@ -14,17 +14,18 @@ login(os.environ['HUGGINGFACEHUB_ACCESS_TOKEN'])
 
 
 embedding_model = OpenAIEmbeddings(model="text-embedding-3-small", dimensions=1536)
-llm_anthropic = ChatAnthropic(model='claude-3-5-sonnet-20241022', temperature=0.7, max_tokens=500)
+llm_anthropic = ChatAnthropic(model='claude-3-7-sonnet-latest', temperature=1)
 llm_gemini = ChatGoogleGenerativeAI(model="gemini-1.5-flash")
 llm_groq = ChatGroq(model="llama-3.1-8b-instant",temperature=0.7)
 llm_gpt = ChatOpenAI(model="gpt-4o-mini",temperature=0.3)
+llm_gpt_high = ChatOpenAI(model="gpt-4o",temperature=0.5)
 
 captioning_model = "meta-llama/llama-4-scout-17b-16e-instruct"
 image_generation_model = "black-forest-labs/FLUX.1-schnell"
 
-improver_llm = llm_gpt
 ideator_llm = llm_gpt
 critic_llm = llm_gpt
+normalizer_llm = llm_gpt
 validator_llm = llm_gpt  
 judge1_llm = llm_gpt
 judge2_llm = llm_gpt