update to streaming

app.py

@@ -52,7 +52,7 @@ if generate_button:
                 generated_plan_container.empty()
 
                 # Stream OpenAI API Response
-                response = client.chat.completions.create(
+                response_stream = client.chat.completions.create(
                     model=MODEL,
                     messages=messages,
                     temperature=0.45,
@@ -60,32 +60,30 @@ if generate_button:
                     top_p=1,
                     frequency_penalty=0,
                     presence_penalty=0,
-                    response_format={"type": "json_object"},
+                    stream=True,
                 )
 
-                # Parse the response
-                generated_response = response.choices[0].message.content.strip()
-                content_plan = json.loads(generated_response)
-
-                # Extract key (assuming there is only one key in the JSON response)
-                plan_key = list(content_plan.keys())[0]
-                clip_plans = content_plan.get(plan_key, [])
-
-                # Display final output
-                if clip_plans:
-                    with generated_plan_container.container():
-                        for i, clip in enumerate(clip_plans):
-                            st.markdown(f"### 🎬 Clip {i + 1}")
-                            st.write(f"**Title:** {clip.get('Title', 'N/A')}")
-                            st.write(f"**Focus Prompt:** {clip.get('Focus Prompt', 'N/A')}")
-                            st.write(f"**Duration:** {clip.get('Duration Target', 'N/A')} seconds")
-                            st.write(f"**Aspect Ratio:** {clip.get('Aspect Ratio', 'N/A')}")
-                            st.markdown("---")
-                else:
-                    st.error("⚠️ No clips were generated. Try again.")
-
-            except json.JSONDecodeError:
-                st.error("⚠️ Failed to parse OpenAI response. Try again.")
-            except Exception as e:
-                st.error(f"❌ Error: {str(e)}")
+                # Process streamed response line-by-line
+                buffer = ""  # Stores partial text before a newline
+                output_text = ""
+
+                for chunk in response_stream:
+                    if chunk.choices:
+                        buffer += chunk.choices[0].delta.content or ""  # Append new text
+
+                        # Check if we received a complete line
+                        while "\n" in buffer:
+                            line, buffer = buffer.split("\n", 1)
+                            line = line.strip()
+
+                            if not line:
+                                continue  # Ignore empty lines
 
+                            # Append new line to output
+                            output_text += f"{line}\n"
+
+                            # Display dynamically
+                            generated_plan_container.markdown(f"```\n{output_text}\n```")
+
+            except Exception as e:
+                st.error(f"❌ Error: {str(e)}")

prompts.py

@@ -15,7 +15,12 @@ Your goal is to analyze the provided transcript and generate a **high-level plan
    - **Duration Target:** Estimated duration (in seconds) based on the transcript length and complexity.  
    - **Aspect Ratio:** Recommended format (Landscape, Square, Vertical) based on content type.
 
-Format the response as a JSON object with Title, Focus Prompt, Duration Target, and Aspect Ratio for each clip concept.
+Format the response as:
+Clip 1
+- Title: <Title>
+- Focus Prompt: <Focus Prompt>
+- Duration Target: <Duration Target> seconds
+- Aspect Ratio: <Aspect Ratio>
 '''
 
 USER_MESSAGE = '''