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app.py

@@ -34,6 +34,7 @@ try:
     import tinytroupe
     from tinytroupe.agent import TinyPerson
     from tinytroupe.factory.tiny_person_factory import TinyPersonFactory
+    from tinytroupe import config_manager
     print("TinyTroupe imported successfully")
 except ImportError as e:
     print(f"Error importing TinyTroupe: {e}")
@@ -82,6 +83,10 @@ def get_repo_branches(repo_full_name):
         return ["main"]
 
 def generate_personas(theme, customer_profile, num_personas):
+    # Override model if alias-large is failing
+    config_manager.update("model", "alias-fast")
+    config_manager.update("reasoning_model", "alias-fast")
+    
     context = f"A company related to {theme}. Target customers: {customer_profile}"
     factory = TinyPersonFactory(context=context)
     people = factory.generate_people(number_of_people=int(num_personas), verbose=True)
@@ -111,27 +116,33 @@ def generate_tasks(theme, customer_profile):
     4. Emotional connection to the persona and content/styling
     
     The tasks must be in sequential order.
-    Return the tasks as a JSON list of strings.
+    Return the tasks as a JSON list of strings in the format: {{"tasks": ["task1", "task2", ...]}}
     """
     
-    response = client.chat.completions.create(
-        model="alias-large",
-        messages=[{"role": "user", "content": prompt}],
-        response_format={"type": "json_object"}
-    )
-    
-    try:
-        content = response.choices[0].message.content
-        tasks_json = json.loads(content)
-        if "tasks" in tasks_json:
-            return tasks_json["tasks"]
-        elif isinstance(tasks_json, list):
-            return tasks_json
-        else:
-            return list(tasks_json.values())[0]
-    except Exception as e:
-        print(f"Error parsing tasks: {e}")
-        return [f"Task {i+1} for {theme}" for i in range(10)]
+    # Try alias-large first, then alias-fast
+    for model_name in ["alias-large", "alias-fast"]:
+        try:
+            response = client.chat.completions.create(
+                model=model_name,
+                messages=[{"role": "user", "content": prompt}]
+                # Removed response_format="json_object" as it might not be supported
+            )
+            content = response.choices[0].message.content
+            # Extract JSON from content (it might be wrapped in code blocks)
+            json_str = re.search(r"\{.*\}", content, re.DOTALL)
+            if json_str:
+                tasks_json = json.loads(json_str.group())
+                if "tasks" in tasks_json:
+                    return tasks_json["tasks"]
+                elif isinstance(tasks_json, list):
+                    return tasks_json
+                else:
+                    return list(tasks_json.values())[0]
+        except Exception as e:
+            print(f"Error with model {model_name}: {e}")
+            continue
+
+    return [f"Task {i+1} for {theme} (Failed to generate)" for i in range(10)]
 
 def handle_generate(theme, customer_profile, num_personas):
     try:

test_remote_api.py

@@ -0,0 +1,27 @@
+from gradio_client import Client
+import json
+
+client = Client("https://harvesthealth-xxg-backup.hf.space/")
+
+print("--- Testing /get_repo_branches ---")
+try:
+    result = client.predict(
+            repo_full_name="JsonLord/tiny_web",
+            api_name="/get_repo_branches"
+    )
+    print(f"Result: {result}")
+except Exception as e:
+    print(f"Error: {e}")
+
+print("\n--- Testing /handle_generate ---")
+try:
+    # Using small values for quick test
+    result = client.predict(
+            theme="Education",
+            customer_profile="Student looking for online courses",
+            num_personas=1,
+            api_name="/handle_generate"
+    )
+    print(f"Result: {result}")
+except Exception as e:
+    print(f"Error: {e}")