Add chat_id, variables, detail, timeout_sec, and send_system_prompt to LLMConfig; update create_llm_service to accept new parameters and handle FastGPT integration. Modify pipeline to utilize chat_id and adjust message handling based on provider settings.

engine/pipeline.py

@@ -1,5 +1,7 @@
 from __future__ import annotations
 
+import uuid
+
 from loguru import logger
 
 from pipecat.audio.vad.silero import SileroVADAnalyzer
@@ -82,12 +84,26 @@ async def run_pipeline_with_serializer(
     )
 
     stt = create_stt_service(config.services.stt, config.audio)
-    llm = create_llm_service(config.services.llm)
+
+    llm_config = config.services.llm
+    chat_id = llm_config.chat_id or f"voice_{uuid.uuid4().hex[:16]}"
+    llm = create_llm_service(
+        llm_config,
+        chat_id=chat_id,
+        session_variables={"session_id": chat_id, "channel": "voice"},
+        greeting_prompt=config.agent.greeting,
+    )
+    if llm_config.provider == "fastgpt":
+        logger.info(f"FastGPT chatId={chat_id}")
+
     tts = create_tts_service(config.services.tts, config.audio)
 
-    messages = [{"role": "system", "content": config.agent.system_prompt}]
-    if config.agent.greeting and config.agent.greeting_mode == "generated":
-        messages.append({"role": "system", "content": config.agent.greeting})
+    use_fastgpt = llm_config.provider == "fastgpt" and not llm_config.send_system_prompt
+    messages: list[dict[str, str]] = []
+    if not use_fastgpt:
+        messages = [{"role": "system", "content": config.agent.system_prompt}]
+        if config.agent.greeting and config.agent.greeting_mode == "generated":
+            messages.append({"role": "system", "content": config.agent.greeting})
 
     context = LLMContext(messages)