stream ture

app.py

@@ -11,75 +11,92 @@ if not api_key:
 
 client = AsyncOpenAI(api_key=api_key)
 
+async def generate_stream(prompt, model="gpt-4o", max_tokens=2048):
+    """
+    非同期ストリーミングを行い、
+    レスポンスをチャンクごとに返すジェネレータ。
+    """
+    response = await client.chat.completions.create(
+        model=model,
+        messages=[{"role": "user", "content": prompt}],
+        max_tokens=max_tokens,
+        stream=True
+    )
+    async for chunk in response:
+        delta = chunk.choices[0].delta.get("content", "")
+        yield delta
+
 async def generate_content(prompt, model="gpt-4o", max_tokens=2048):
-    try:
-        response = await client.chat.completions.create(
-            model=model,
-            messages=[{"role": "user", "content": prompt}],
-            max_tokens=max_tokens
-        )
-        return response.choices[0].message.content.strip()
-    except Exception as e:
-        st.error(f"Error generating content: {str(e)}")
-        return None
+    """
+    全文を組み立てつつストリーミングで返す。
+    """
+    content = ""
+    placeholder = st.empty()
+    # チャンク毎に表示を更新
+    async for delta in generate_stream(prompt, model, max_tokens):
+        content += delta
+        placeholder.write(content)
+    return content
 
 async def generate_context(summaries, system_prompt_prefix, system_prompt_suffix):
     prompt = f"{system_prompt_prefix}\n\n{summaries}\n\n{system_prompt_suffix}"
+    st.subheader("Context Generation")
     return await generate_content(prompt)
 
 async def generate_script(context, heading, system_prompt_prefix, system_prompt_suffix):
     prompt = f"{system_prompt_prefix}\n\n{context}\n\nHeading: {heading}\n\n{system_prompt_suffix}"
+    st.subheader(f"Script for: {heading}")
     return await generate_content(prompt, max_tokens=4000)
 
 def main():
-    st.title("Script Generator")
+    st.title("Script Generator (Streaming & Async)")
 
+    # --- コンテキスト生成用 ---
     context_system_prompt_prefix = st.text_input(
-        "Enter the prompt prefix for context generation:",
-        value="You are an AI assistant. Your task is to provide a concise context that captures the essential information from the given document summary."
+        "Context Prompt Prefix:",
+        value="You are an AI assistant. Provide a concise context from the summary."
     )
-    summaries = st.text_area("Enter the document summary:", height=200)
+    summaries = st.text_area("Document Summary:", height=150)
     context_system_prompt_suffix = st.text_input(
-        "Enter the prompt suffix for context generation:",
-        value="Focus on the key points and main ideas, and present the context in a clear and organized manner."
+        "Context Prompt Suffix:",
+        value="Focus on key points and present clearly."
     )
 
-    outline = st.text_area("Enter the content outline (one heading per line):", height=200)
+    # --- スクリプト生成用 ---
+    outline = st.text_area("Content Outline (one heading per line):", height=150)
     script_system_prompt_prefix = st.text_input(
-        "Enter the system prompt prefix for script generation:",
-        value="You are an AI scriptwriter. Your task is to generate a detailed script based on the given context and the provided heading."
+        "Script Prompt Prefix:",
+        value="You are an AI scriptwriter. Generate a detailed script."
     )
     script_system_prompt_suffix = st.text_input(
-        "Enter the system prompt suffix for script generation:",
-        value="The script should be relevant, informative, engaging, and contain more than 600 characters."
+        "Script Prompt Suffix:",
+        value="Make it informative, engaging, >600 characters."
     )
 
-    if st.button("Generate Context and Scripts"):
+    if st.button("Generate (Streaming)"):
         if not summaries or not outline:
-            st.error("Please enter both the document summary and content outline.")
+            st.error("Please enter both the summary and the outline.")
             return
 
-        context = asyncio.run(generate_context(summaries, context_system_prompt_prefix, context_system_prompt_suffix))
+        # asyncio.run で非同期関数を同期的に実行
+        context = asyncio.run(generate_context(
+            summaries,
+            context_system_prompt_prefix,
+            context_system_prompt_suffix
+        ))
+
         if context:
-            st.header("Generated Context")
+            st.markdown("**Generated Context:**")
             st.write(context)
 
             headings = [h.strip() for h in outline.split("\n") if h.strip()]
-            scripts = []
             for heading in headings:
-                script = asyncio.run(generate_script(context, heading, script_system_prompt_prefix, script_system_prompt_suffix))
-                if script:
-                    scripts.append((heading, script))
-
-            if scripts:
-                st.header("Generated Scripts")
-                for heading, script in scripts:
-                    st.subheader(heading)
-                    st.write(script)
-            else:
-                st.error("Failed to generate scripts. Please try again.")
-        else:
-            st.error("Failed to generate context. Please try again.")
+                _ = asyncio.run(generate_script(
+                    context,
+                    heading,
+                    script_system_prompt_prefix,
+                    script_system_prompt_suffix
+                ))
 
 if __name__ == "__main__":
-    main()
+    main()