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Dockerfile

@@ -0,0 +1,23 @@
+FROM python:3.10-slim
+
+WORKDIR /app
+
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    git \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+# Set environment variables
+ENV PYTHONUNBUFFERED=1
+ENV GRADIO_SERVER_NAME="0.0.0.0"
+ENV GRADIO_SERVER_PORT=7860
+
+EXPOSE 7860
+
+CMD ["python", "app.py"]

README.md

@@ -3,9 +3,8 @@ title: Tiny Factory
 emoji: 💻
 colorFrom: yellow
 colorTo: gray
-sdk: gradio
-sdk_version: 6.3.0
-app_file: app.py
+sdk: docker
+app_port: 7860
 pinned: false
 ---
 

app.py

@@ -42,80 +42,44 @@ def save_persona_base(personas):
     except Exception as e:
         print(f"Error saving persona base to Hub: {e}")
 
-# --- CHANGE 1: The function now accepts an optional API key. ---
 def generate_personas(business_description, customer_profile, num_personas, blablador_api_key=None):
-    """
-    Generates a list of TinyPerson instances based on the provided inputs.
-    It prioritizes the API key passed as an argument, but falls back to the
-    environment variable if none is provided (for UI use).
-    """
-    # --- CHANGE 2: Logic to determine which key to use. ---
-    # Use the key from the API call if provided, otherwise get it from the Space secrets.
     api_key_to_use = blablador_api_key or os.getenv("BLABLADOR_API_KEY")
-
     if not api_key_to_use:
         return {"error": "BLABLADOR_API_KEY not found. Please provide it in your API call or set it as a secret in the Space settings."}
-
-    # Store the original state of the environment variable, if it exists
     original_key = os.getenv("BLABLADOR_API_KEY")
-    
     try:
-        # --- CHANGE 3: Securely set the correct environment variable for this request. ---
-        # The underlying tinytroupe library will look for this variable.
         os.environ["BLABLADOR_API_KEY"] = api_key_to_use
-
         num_personas = int(num_personas)
-
         factory = TinyPersonFactory(
             context=business_description,
             sampling_space_description=customer_profile,
             total_population_size=num_personas
         )
-
         people = factory.generate_people(number_of_people=num_personas, parallelize=False)
         personas_data = [person._persona for person in people]
-        
-        # --- NEW: Update the Tresor ---
         current_base = load_persona_base()
         current_base.extend(personas_data)
         save_persona_base(current_base)
-        # ------------------------------
-
         return personas_data
-
     except Exception as e:
         return {"error": str(e)}
-
     finally:
-        # --- CHANGE 4: A robust cleanup using a 'finally' block. ---
-        # This ensures the environment is always restored to its original state,
-        # whether the function succeeds or fails.
         if original_key is None:
-            # If the variable didn't exist originally, remove it.
             if "BLABLADOR_API_KEY" in os.environ:
                 del os.environ["BLABLADOR_API_KEY"]
         else:
-            # If it existed, restore its original value.
             os.environ["BLABLADOR_API_KEY"] = original_key
 
-
 def find_best_persona(criteria):
-    """
-    Loads the persona base and finds the best matching persona based on criteria.
-    """
     personas = load_persona_base()
     if not personas:
         return {"error": "Persona base is empty. Generate some personas first!"}
-
     try:
-        # select_best_persona uses LLM to find the best index
         idx = select_best_persona(criteria=criteria, personas=personas)
-
         try:
             idx = int(idx)
         except (ValueError, TypeError):
             return {"error": f"LLM returned an invalid index: {idx}"}
-
         if idx >= 0 and idx < len(personas):
             return personas[idx]
         else:
@@ -123,7 +87,6 @@ def find_best_persona(criteria):
     except Exception as e:
         return {"error": f"Error during persona matching: {str(e)}"}
 
-
 with gr.Blocks() as demo:
     gr.Markdown("<h1>Tiny Persona Generator</h1>")
     with gr.Row():
@@ -131,32 +94,20 @@ with gr.Blocks() as demo:
             business_description_input = gr.Textbox(label="What is your business about?", lines=5)
             customer_profile_input = gr.Textbox(label="Information about your customer profile", lines=5)
             num_personas_input = gr.Number(label="Number of personas to generate", value=1, minimum=1, step=1)
-            
-            # --- CHANGE 5: The API key input is now INVISIBLE. ---
-            # It still exists, so the API endpoint is created, but it's hidden from UI users.
-            blablador_api_key_input = gr.Textbox(
-                label="Blablador API Key (for API client use)", 
-                visible=False
-            )
-
+            blablador_api_key_input = gr.Textbox(label="Blablador API Key (for API client use)", visible=False)
             generate_button = gr.Button("Generate Personas")
-
             gr.Markdown("---")
             gr.Markdown("<h3>Search Tresor</h3>")
             criteria_input = gr.Textbox(label="Criteria to find best matching persona", lines=2)
             find_button = gr.Button("Find Best Persona in Tresor")
-
         with gr.Column():
             output_json = gr.JSON(label="Output (Generated or Matched Persona)")
-
     generate_button.click(
         fn=generate_personas,
-        # --- CHANGE 6: Pass the invisible textbox to the function. ---
         inputs=[business_description_input, customer_profile_input, num_personas_input, blablador_api_key_input],
         outputs=output_json,
         api_name="generate_personas"
     )
-
     find_button.click(
         fn=find_best_persona,
         inputs=[criteria_input],
@@ -174,7 +125,11 @@ def health():
 def api_docs():
     return RedirectResponse(url="/docs")
 
-app = gr.mount_gradio_app(app, demo, path="/")
+# Disabling SSR to fix the port 7861 error in Spaces
+try:
+    app = gr.mount_gradio_app(app, demo, path="/", ssr=False)
+except Exception:
+    app = gr.mount_gradio_app(app, demo, path="/")
 
 if __name__ == "__main__":
     uvicorn.run(app, host="0.0.0.0", port=7860)