diff --git a/src/ragbuilder/executor.py b/src/ragbuilder/executor.py
index 1b69e10..fa397fe 100644
--- a/src/ragbuilder/executor.py
+++ b/src/ragbuilder/executor.py
@@ -86,6 +86,7 @@ def rag_builder_bayes_optmization(**kwargs):
     max_chunk_size=kwargs.get('max_chunk_size', 1000)
     hf_embedding=kwargs.get('hf_embedding')
     hf_llm=kwargs.get('hf_llm')
+    num_runs=kwargs.get('num_runs')
     test_data=kwargs['test_data'] #loader_kwargs ={'source':'url','input_path': url1},
     test_df=pd.read_csv(test_data)
     test_ds = Dataset.from_pandas(test_df)
@@ -104,10 +105,10 @@ def rag_builder_bayes_optmization(**kwargs):
     logger.info(f"Number of RAG combinations : {cnt_combos}")
     configs_evaluated=dict()
     
-    if cnt_combos < BAYESIAN_RUNS:
+    if cnt_combos < num_runs:
         total_runs=cnt_combos
     else:
-        total_runs = BAYESIAN_RUNS + len(configs_to_run)
+        total_runs = num_runs + len(configs_to_run)
     progress_state.set_total_runs(total_runs)
 
     # Run Templates first if templates have been selected
@@ -183,7 +184,7 @@ def objective(**params):
         
         # Run Bayesian optimization
         logger.info(f"Running Bayesian optimization...")
-        result = gp_minimize(objective, space, n_calls=BAYESIAN_RUNS, random_state=42) #, callback=DeltaXStopper(1e-8))
+        result = gp_minimize(objective, space, n_calls=num_runs, random_state=42) #, callback=DeltaXStopper(1e-8))
         logger.info(f"Completed Bayesian optimization...")
 
         best_params = result.x
diff --git a/src/ragbuilder/ragbuilder.py b/src/ragbuilder/ragbuilder.py
index 857cfa2..c2b7a2c 100644
--- a/src/ragbuilder/ragbuilder.py
+++ b/src/ragbuilder/ragbuilder.py
@@ -291,6 +291,7 @@ class ProjectData(BaseModel):
     criticLLM: Optional[str] = Field(default=None)
     generatorLLM: Optional[str] = Field(default=None)
     embedding: Optional[str] = Field(default=None)
+    numRuns: Optional[str] = Field(default=None)
 
 @app.post("/rbuilder")
 def rbuilder_route(project_data: ProjectData, db: sqlite3.Connection = Depends(get_db)):
@@ -429,6 +430,7 @@ def parse_config(config: dict, db: sqlite3.Connection):
     try:
         if optimization=='bayesianOptimization':
             logger.info(f"Using Bayesian optimization to find optimal RAG configs...")
+            num_runs = int(config.get("numRuns", 50))
             res = rag_builder_bayes_optmization(
                 run_id=run_id, 
                 compare_templates=compare_templates, 
@@ -440,6 +442,7 @@ def parse_config(config: dict, db: sqlite3.Connection):
                 max_chunk_size=max_chunk_size, 
                 hf_embedding=hf_embedding,
                 hf_llm=hf_llm,
+                num_runs=num_runs,
                 disabled_opts=disabled_opts
             )
         elif optimization=='fullParameterSearch' :
diff --git a/src/ragbuilder/static/main.js b/src/ragbuilder/static/main.js
index 02f02d2..be67e34 100644
--- a/src/ragbuilder/static/main.js
+++ b/src/ragbuilder/static/main.js
@@ -62,6 +62,15 @@ $(document).ready(function () {
         }
     });
 
+    // Show or hide the number of runs input based on the selected optimization option
+    $('input[name="optimization"]').change(function () {
+        if ($('#bayesianOptimization').is(':checked')) {
+            $('#numRunsContainer').show();
+        } else {
+            $('#numRunsContainer').hide();
+        }
+    });
+
     $('#nextStep1').click(function () {
         const sourceData = $('#sourceData').val();
         $.ajax({
@@ -305,6 +314,10 @@ $(document).ready(function () {
                 embedding: $('#embedding').val()
             };
         }
+
+        if (projectData.optimization === "bayesianOptimization") {
+            projectData.numRuns = $('#numRuns').val();
+        }
     
         console.log(JSON.stringify(projectData));
 
diff --git a/src/ragbuilder/templates/layouts.html b/src/ragbuilder/templates/layouts.html
index e7fcade..8620c2d 100644
--- a/src/ragbuilder/templates/layouts.html
+++ b/src/ragbuilder/templates/layouts.html
@@ -247,12 +247,16 @@ <h5 class="mt-5">Advanced Optimization Settings</h5>
                                     Ragbuilder uses Bayesian optimization for efficient hyperparameter tuning. Alternatively, you can generate and assess all parameter combinations for exhaustive insights, but this approach is long-running, costly, and computationally intensive.
                                 </p>
                                 <div class="form-group mx-3">
-                                    <input type="radio" class="form-check-input" id="bayesianOptimization" name="optimization" checked>
+                                    <input type="radio" class="form-check-input me-2" id="bayesianOptimization" name="optimization" checked>
                                     <label class="form-check-label" for="bayesianOptimization">Use Bayesian Optimization (Recommended)</label>
+                                    <div id="numRunsContainer" class="ms-5">
+                                        <label for="numRuns" class="form-label me-2">Number of Runs:</label>
+                                        <input type="number" class="form-control d-inline-block" id="numRuns" value="50" min="1" style="width: 80px;">
+                                    </div>
                                 </div>
                                 <div class="form-group mx-3">
-                                    <input type="radio" class="form-check-input" id="fullParameterSearch" name="optimization">
-                                    <label class="form-check-label" for="fullParameterSearch">Evaluate All Possible Combinations </label>
+                                    <input type="radio" class="form-check-input me-2" id="fullParameterSearch" name="optimization">
+                                    <label class="form-check-label" for="fullParameterSearch">Evaluate All Possible Combinations</label>
                                 </div>
                             </div>
                             <div class="d-grid gap-2 pt-2 d-md-flex justify-content-md-end">