User can choose model

src/streamlit_app.py

@@ -205,6 +205,14 @@ def main():
                 help="The more detailed your description, the better the validation will be."
             )
             
+            # Model selection toggle
+            model_id = st.selectbox(
+                "🤖 Model to use:",
+                options=["gpt-4o", "gpt-4o-mini", "o1", "o3-mini"],
+                index=0,  # Default to gpt-4o
+                help="Choose which AI model to use for the validation analysis"
+            )
+            
             submitted = st.form_submit_button("🔍 Validate My Idea", use_container_width=True)
     
     with col2:
@@ -232,7 +240,7 @@ def main():
         # Keep the example in session state until form is submitted
     
     # Process the form submission
-    if submitted and startup_idea:
+    if submitted and startup_idea and model_id:
         # Clear the selected example when submitting
         if 'selected_example' in st.session_state:
             del st.session_state.selected_example
@@ -253,6 +261,7 @@ def main():
                 return await startup_validation_workflow.arun(
                     message=message,
                     startup_idea=startup_idea,
+                    model_id=model_id,  # Pass the selected model
                     progress_callback=tracker.update_progress  # Pass the real-time callback
                 )
             

src/workflows_v2.py

@@ -20,18 +20,19 @@ load_dotenv(env_path)
 from atla_insights import configure, instrument, instrument_agno, instrument_openai, mark_success, mark_failure, tool
 
 # Model configuration - using same model across all agents but you can change them to any model you want
-MODEL_ID = "o3-mini"
+DEFAULT_MODEL_ID = "gpt-4o"
 
 # Define metadata for tracing
-metadata = {
-    "model": MODEL_ID,
-    "prompt": "v1.1",
-    "environment": "prod",
-    "agent_name": "Startup Idea Validator"
-}
+def get_metadata(model_id):
+    return {
+        "model": model_id,
+        "prompt": "v1.1",
+        "environment": "prod",
+        "agent_name": "Startup Idea Validator"
+    }
 
 # Configure Atla Insights with metadata - REQUIRED FIRST
-configure(token=os.getenv("ATLA_INSIGHTS_TOKEN"), metadata=metadata)
+configure(token=os.getenv("ATLA_INSIGHTS_TOKEN"), metadata=get_metadata(DEFAULT_MODEL_ID))
 
 # Instrument based on detected framework and LLM provider
 instrument_agno("openai")  # Agno framework with OpenAI
@@ -95,71 +96,76 @@ class ValidationReport(BaseModel):
     next_steps: str = Field(..., description="Recommended next steps.")
 
 
-# --- Agents ---
-
-idea_clarifier_agent = Agent(
-    name="Idea Clarifier",
-    model=OpenAIChat(id=MODEL_ID),
-    instructions=[
-        "Given a user's startup idea, your goal is to refine that idea.",
-        "Evaluate the originality of the idea by comparing it with existing concepts.",
-        "Define the mission and objectives of the startup.",
-        "Provide clear, actionable insights about the core business concept.",
-    ],
-    add_history_to_messages=True,
-    add_datetime_to_instructions=True,
-    response_model=IdeaClarification,
-    debug_mode=False,
-)
+# --- Agent creation functions ---
+def create_agents(model_id: str = DEFAULT_MODEL_ID):
+    """Create all agents with the specified model"""
+    
+    idea_clarifier_agent = Agent(
+        name="Idea Clarifier",
+        model=OpenAIChat(id=model_id),
+        instructions=[
+            "Given a user's startup idea, your goal is to refine that idea.",
+            "Evaluate the originality of the idea by comparing it with existing concepts.",
+            "Define the mission and objectives of the startup.",
+            "Provide clear, actionable insights about the core business concept.",
+        ],
+        add_history_to_messages=True,
+        add_datetime_to_instructions=True,
+        response_model=IdeaClarification,
+        debug_mode=False,
+    )
 
-market_research_agent = Agent(
-    name="Market Research Agent",
-    model=OpenAIChat(id=MODEL_ID), 
-    tools=[GoogleSearchTools()],
-    instructions=[
-        "You are provided with a startup idea and the company's mission and objectives.",
-        "Estimate the total addressable market (TAM), serviceable available market (SAM), and serviceable obtainable market (SOM).",
-        "Define target customer segments and their characteristics.",
-        "Search the web for resources and data to support your analysis.",
-        "Provide specific market size estimates with supporting data sources.",
-    ],
-    add_history_to_messages=True,
-    add_datetime_to_instructions=True,
-    response_model=MarketResearch,
-)
+    market_research_agent = Agent(
+        name="Market Research Agent",
+        model=OpenAIChat(id=model_id), 
+        tools=[GoogleSearchTools()],
+        instructions=[
+            "You are provided with a startup idea and the company's mission and objectives.",
+            "Estimate the total addressable market (TAM), serviceable available market (SAM), and serviceable obtainable market (SOM).",
+            "Define target customer segments and their characteristics.",
+            "Search the web for resources and data to support your analysis.",
+            "Provide specific market size estimates with supporting data sources.",
+        ],
+        add_history_to_messages=True,
+        add_datetime_to_instructions=True,
+        response_model=MarketResearch,
+        debug_mode=False,
+    )
 
-competitor_analysis_agent = Agent(
-    name="Competitor Analysis Agent",
-    model=OpenAIChat(id=MODEL_ID),  
-    tools=[GoogleSearchTools()],
-    instructions=[
-        "You are provided with a startup idea and market research data.",
-        "Identify existing competitors in the market.",
-        "Perform Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis for each competitor.",
-        "Assess the startup's potential positioning relative to competitors.",
-        "Search for recent competitor information and market positioning.",
-    ],
-    add_history_to_messages=True,
-    add_datetime_to_instructions=True,
-    response_model=CompetitorAnalysis,
-    debug_mode=False,
-)
+    competitor_analysis_agent = Agent(
+        name="Competitor Analysis Agent",
+        model=OpenAIChat(id=model_id),  
+        tools=[GoogleSearchTools()],
+        instructions=[
+            "You are provided with a startup idea and market research data.",
+            "Identify existing competitors in the market.",
+            "Perform Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis for each competitor.",
+            "Assess the startup's potential positioning relative to competitors.",
+            "Search for recent competitor information and market positioning.",
+        ],
+        add_history_to_messages=True,
+        add_datetime_to_instructions=True,
+        response_model=CompetitorAnalysis,
+        debug_mode=False,
+    )
 
-report_agent = Agent(
-    name="Report Generator",
-    model=OpenAIChat(id=MODEL_ID),  
-    instructions=[
-        "You are provided with comprehensive data about a startup idea including clarification, market research, and competitor analysis.",
-        "Synthesize all information into a comprehensive validation report.",
-        "Provide clear executive summary, assessment, and actionable recommendations.",
-        "Structure the report professionally with clear sections and insights.",
-        "Include specific next steps for the entrepreneur.",
-    ],
-    add_history_to_messages=True,
-    add_datetime_to_instructions=True,
-    response_model=ValidationReport,
-    debug_mode=False,
-)
+    report_agent = Agent(
+        name="Report Generator",
+        model=OpenAIChat(id=model_id),  
+        instructions=[
+            "You are provided with comprehensive data about a startup idea including clarification, market research, and competitor analysis.",
+            "Synthesize all information into a comprehensive validation report.",
+            "Provide clear executive summary, assessment, and actionable recommendations.",
+            "Structure the report professionally with clear sections and insights.",
+            "Include specific next steps for the entrepreneur.",
+        ],
+        add_history_to_messages=True,
+        add_datetime_to_instructions=True,
+        response_model=ValidationReport,
+        debug_mode=False,
+    )
+    
+    return idea_clarifier_agent, market_research_agent, competitor_analysis_agent, report_agent
 
 
 # --- Execution function ---
@@ -168,11 +174,15 @@ async def startup_validation_execution(
     workflow: Workflow,
     execution_input: WorkflowExecutionInput,
     startup_idea: str,
+    model_id: str = DEFAULT_MODEL_ID,
     progress_callback=None,
     **kwargs: Any,
 ) -> str:
     """Execute the complete startup idea validation workflow"""
 
+    # Create agents with the specified model
+    idea_clarifier_agent, market_research_agent, competitor_analysis_agent, report_agent = create_agents(model_id)
+
     # Get inputs
     message: str = execution_input.message
     idea: str = startup_idea
@@ -184,9 +194,11 @@ async def startup_validation_execution(
     if progress_callback:
         progress_callback(f"🚀 Starting startup idea validation for: {idea}")
         progress_callback(f"💡 Validation request: {message}")
+        progress_callback(f"🤖 Using model: {model_id}")
     else:
         print(f"🚀 Starting startup idea validation for: {idea}")
         print(f"💡 Validation request: {message}")
+        print(f"🤖 Using model: {model_id}")
 
     # Phase 1: Idea Clarification
     if progress_callback:
@@ -451,6 +463,7 @@ if __name__ == "__main__":
             result = await startup_validation_workflow.arun(
                 message="Please validate this startup idea with comprehensive market research and competitive analysis",
                 startup_idea=idea,
+                model_id=DEFAULT_MODEL_ID,
             )
 
             pprint_run_response(result, markdown=True)