feat(core): Support more chat flows

dbgpt/_version.py

@@ -1 +1 @@
-version = "0.4.7"
+version = "0.5.0"

dbgpt/app/openapi/api_v1/api_v1.py

@@ -366,11 +366,7 @@ async def chat_completions(
             context=flow_ctx,
         )
         return StreamingResponse(
-            flow_stream_generator(
-                flow_service.chat_flow(dialogue.select_param, flow_req),
-                dialogue.incremental,
-                dialogue.model_name,
-            ),
+            flow_service.chat_flow(dialogue.select_param, flow_req),
             headers=headers,
             media_type="text/event-stream",
         )
@@ -426,32 +422,6 @@ async def no_stream_generator(chat):
         yield f"data: {msg}\n\n"
 
 
-async def flow_stream_generator(func, incremental: bool, model_name: str):
-    stream_id = f"chatcmpl-{str(uuid.uuid1())}"
-    previous_response = ""
-    async for chunk in func:
-        if chunk:
-            msg = chunk.replace("\ufffd", "")
-            if incremental:
-                incremental_output = msg[len(previous_response) :]
-                choice_data = ChatCompletionResponseStreamChoice(
-                    index=0,
-                    delta=DeltaMessage(role="assistant", content=incremental_output),
-                )
-                chunk = ChatCompletionStreamResponse(
-                    id=stream_id, choices=[choice_data], model=model_name
-                )
-                yield f"data: {chunk.json(exclude_unset=True, ensure_ascii=False)}\n\n"
-            else:
-                # TODO generate an openai-compatible streaming responses
-                msg = msg.replace("\n", "\\n")
-                yield f"data:{msg}\n\n"
-            previous_response = msg
-            await asyncio.sleep(0.02)
-    if incremental:
-        yield "data: [DONE]\n\n"
-
-
 async def stream_generator(chat, incremental: bool, model_name: str):
     """Generate streaming responses
 

dbgpt/core/awel/flow/base.py

@@ -632,16 +632,36 @@ def get_runnable_parameters(
         runnable_parameters: Dict[str, Any] = {}
         if not self.parameters or not view_parameters:
             return runnable_parameters
-        if len(self.parameters) != len(view_parameters):
+        view_required_parameters = {
+            parameter.name: parameter
+            for parameter in view_parameters
+            if not parameter.optional
+        }
+        current_required_parameters = {
+            parameter.name: parameter
+            for parameter in self.parameters
+            if not parameter.optional
+        }
+        current_parameters = {
+            parameter.name: parameter for parameter in self.parameters
+        }
+        if len(view_required_parameters) < len(current_required_parameters):
             # TODO, skip the optional parameters.
             raise FlowParameterMetadataException(
-                f"Parameters count not match. Expected {len(self.parameters)}, "
+                f"Parameters count not match(current key: {self.id}). "
+                f"Expected {len(self.parameters)}, "
                 f"but got {len(view_parameters)} from JSON metadata."
+                f"Required parameters: {current_required_parameters.keys()}, "
+                f"but got {view_required_parameters.keys()}."
             )
-        for i, parameter in enumerate(self.parameters):
-            view_param = view_parameters[i]
+        for view_param in view_parameters:
+            view_param_key = view_param.name
+            if view_param_key not in current_parameters:
+                raise FlowParameterMetadataException(
+                    f"Parameter {view_param_key} not found in the metadata."
+                )
             runnable_parameters.update(
-                parameter.to_runnable_parameter(
+                current_parameters[view_param_key].to_runnable_parameter(
                     view_param.get_typed_value(), resources, key_to_resource_instance
                 )
             )

dbgpt/core/awel/operators/base.py

@@ -122,6 +122,8 @@ class BaseOperator(DAGNode, ABC, Generic[OUT], metaclass=BaseOperatorMeta):
     This class extends DAGNode by adding execution capabilities.
     """
 
+    streaming_operator: bool = False
+
     def __init__(
         self,
         task_id: Optional[str] = None,

dbgpt/core/awel/operators/stream_operator.py

@@ -10,6 +10,8 @@
 class StreamifyAbsOperator(BaseOperator[OUT], ABC, Generic[IN, OUT]):
     """An abstract operator that converts a value of IN to an AsyncIterator[OUT]."""
 
+    streaming_operator = True
+
     async def _do_run(self, dag_ctx: DAGContext) -> TaskOutput[OUT]:
         curr_task_ctx: TaskContext[OUT] = dag_ctx.current_task_context
         call_data = curr_task_ctx.call_data
@@ -83,6 +85,8 @@ class TransformStreamAbsOperator(BaseOperator[OUT], Generic[IN, OUT]):
     AsyncIterator[IN] to another AsyncIterator[OUT].
     """
 
+    streaming_operator = True
+
     async def _do_run(self, dag_ctx: DAGContext) -> TaskOutput[OUT]:
         curr_task_ctx: TaskContext[OUT] = dag_ctx.current_task_context
         output: TaskOutput[OUT] = await curr_task_ctx.task_input.parent_outputs[

dbgpt/core/interface/operators/prompt_operator.py

@@ -74,11 +74,11 @@ class CommonChatPromptTemplate(ChatPromptTemplate):
     def pre_fill(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         """Pre fill the messages."""
         if "system_message" not in values:
-            raise ValueError("No system message")
+            values["system_message"] = "You are a helpful AI Assistant."
         if "human_message" not in values:
-            raise ValueError("No human message")
+            values["human_message"] = "{user_input}"
         if "message_placeholder" not in values:
-            raise ValueError("No message placeholder")
+            values["message_placeholder"] = "chat_history"
         system_message = values.pop("system_message")
         human_message = values.pop("human_message")
         message_placeholder = values.pop("message_placeholder")

dbgpt/serve/flow/service/service.py

@@ -1,6 +1,7 @@
+import json
 import logging
 import traceback
-from typing import List, Optional, cast
+from typing import Any, List, Optional, cast
 
 from fastapi import HTTPException
 
@@ -14,6 +15,7 @@
 from dbgpt.core.awel.dag.dag_manager import DAGManager
 from dbgpt.core.awel.flow.flow_factory import FlowCategory, FlowFactory
 from dbgpt.core.awel.trigger.http_trigger import CommonLLMHttpTrigger
+from dbgpt.core.interface.llm import ModelOutput
 from dbgpt.serve.core import BaseService
 from dbgpt.storage.metadata import BaseDao
 from dbgpt.storage.metadata._base_dao import QUERY_SPEC
@@ -276,12 +278,39 @@ def get_list_by_page(
         """
         return self.dao.get_list_page(request, page, page_size)
 
-    async def chat_flow(self, flow_uid: str, request: CommonLLMHttpRequestBody):
+    async def chat_flow(
+        self,
+        flow_uid: str,
+        request: CommonLLMHttpRequestBody,
+        incremental: bool = False,
+    ):
         """Chat with the AWEL flow.
 
         Args:
             flow_uid (str): The flow uid
             request (CommonLLMHttpRequestBody): The request
+            incremental (bool): Whether to return the result incrementally
+        """
+        try:
+            async for output in self._call_chat_flow(flow_uid, request, incremental):
+                yield output
+        except HTTPException as e:
+            yield f"data:[SERVER_ERROR]{e.detail}\n\n"
+        except Exception as e:
+            yield f"data:[SERVER_ERROR]{str(e)}\n\n"
+
+    async def _call_chat_flow(
+        self,
+        flow_uid: str,
+        request: CommonLLMHttpRequestBody,
+        incremental: bool = False,
+    ):
+        """Chat with the AWEL flow.
+
+        Args:
+            flow_uid (str): The flow uid
+            request (CommonLLMHttpRequestBody): The request
+            incremental (bool): Whether to return the result incrementally
         """
         flow = self.get({"uid": flow_uid})
         if not flow:
@@ -291,18 +320,18 @@ async def chat_flow(self, flow_uid: str, request: CommonLLMHttpRequestBody):
             raise HTTPException(
                 status_code=404, detail=f"Flow {flow_uid}'s dag id not found"
             )
-        if flow.flow_category != FlowCategory.CHAT_FLOW:
-            raise ValueError(f"Flow {flow_uid} is not a chat flow")
         dag = self.dag_manager.dag_map[dag_id]
+        if (
+            flow.flow_category != FlowCategory.CHAT_FLOW
+            and self._parse_flow_category(dag) != FlowCategory.CHAT_FLOW
+        ):
+            raise ValueError(f"Flow {flow_uid} is not a chat flow")
         leaf_nodes = dag.leaf_nodes
         if len(leaf_nodes) != 1:
             raise ValueError("Chat Flow just support one leaf node in dag")
         end_node = cast(BaseOperator, leaf_nodes[0])
-        if request.stream:
-            async for output in await end_node.call_stream(request):
-                yield output
-        else:
-            yield await end_node.call(request)
+        async for output in _chat_with_dag_task(end_node, request, incremental):
+            yield output
 
     def _parse_flow_category(self, dag: DAG) -> FlowCategory:
         """Parse the flow category
@@ -335,9 +364,104 @@ def _parse_flow_category(self, dag: DAG) -> FlowCategory:
         output = leaf_node.metadata.outputs[0]
         try:
             real_class = _get_type_cls(output.type_cls)
-            if common_http_trigger and (
-                real_class == str or real_class == CommonLLMHttpResponseBody
-            ):
+            if common_http_trigger and _is_chat_flow_type(real_class, is_class=True):
                 return FlowCategory.CHAT_FLOW
         except Exception:
             return FlowCategory.COMMON
+
+
+def _is_chat_flow_type(obj: Any, is_class: bool = False) -> bool:
+    try:
+        from dbgpt.model.utils.chatgpt_utils import OpenAIStreamingOutputOperator
+    except ImportError:
+        OpenAIStreamingOutputOperator = None
+    if is_class:
+        return (
+            obj == str
+            or obj == CommonLLMHttpResponseBody
+            or (OpenAIStreamingOutputOperator and obj == OpenAIStreamingOutputOperator)
+        )
+    else:
+        chat_types = (str, CommonLLMHttpResponseBody)
+        if OpenAIStreamingOutputOperator:
+            chat_types += (OpenAIStreamingOutputOperator,)
+        return isinstance(obj, chat_types)
+
+
+async def _chat_with_dag_task(
+    task: BaseOperator,
+    request: CommonLLMHttpRequestBody,
+    incremental: bool = False,
+):
+    """Chat with the DAG task.
+
+    Args:
+        task (BaseOperator): The task
+        request (CommonLLMHttpRequestBody): The request
+    """
+    if request.stream and task.streaming_operator:
+        try:
+            from dbgpt.model.utils.chatgpt_utils import OpenAIStreamingOutputOperator
+        except ImportError:
+            OpenAIStreamingOutputOperator = None
+        if incremental:
+            async for output in await task.call_stream(request):
+                yield output
+        else:
+            if OpenAIStreamingOutputOperator and isinstance(
+                task, OpenAIStreamingOutputOperator
+            ):
+                from fastchat.protocol.openai_api_protocol import (
+                    ChatCompletionResponseStreamChoice,
+                )
+
+                previous_text = ""
+                async for output in await task.call_stream(request):
+                    if not isinstance(output, str):
+                        yield "data:[SERVER_ERROR]The output is not a stream format\n\n"
+                        return
+                    if output == "data: [DONE]\n\n":
+                        return
+                    json_data = "".join(output.split("data: ")[1:])
+                    dict_data = json.loads(json_data)
+                    if "choices" not in dict_data:
+                        error_msg = dict_data.get("text", "Unknown error")
+                        yield f"data:[SERVER_ERROR]{error_msg}\n\n"
+                        return
+                    choices = dict_data["choices"]
+                    if choices:
+                        choice = choices[0]
+                        delta_data = ChatCompletionResponseStreamChoice(**choice)
+                        if delta_data.delta.content:
+                            previous_text += delta_data.delta.content
+                        if previous_text:
+                            full_text = previous_text.replace("\n", "\\n")
+                            yield f"data:{full_text}\n\n"
+            else:
+                async for output in await task.call_stream(request):
+                    if isinstance(output, str):
+                        if output.strip():
+                            yield output
+                    else:
+                        yield "data:[SERVER_ERROR]The output is not a stream format\n\n"
+                        return
+    else:
+        result = await task.call(request)
+        if result is None:
+            yield "data:[SERVER_ERROR]The result is None\n\n"
+        elif isinstance(result, str):
+            yield f"data:{result}\n\n"
+        elif isinstance(result, ModelOutput):
+            if result.error_code != 0:
+                yield f"data:[SERVER_ERROR]{result.text}\n\n"
+            else:
+                yield f"data:{result.text}\n\n"
+        elif isinstance(result, CommonLLMHttpResponseBody):
+            if result.error_code != 0:
+                yield f"data:[SERVER_ERROR]{result.text}\n\n"
+            else:
+                yield f"data:{result.text}\n\n"
+        elif isinstance(result, dict):
+            yield f"data:{json.dumps(result, ensure_ascii=False)}\n\n"
+        else:
+            yield f"data:[SERVER_ERROR]The result is not a valid format({type(result)})\n\n"

dbgpt/util/dbgpts/repo.py

@@ -140,7 +140,7 @@ def update_repo(repo: str):
         logger.info(f"Repo '{repo}' is not a git repository.")
         return
     logger.info(f"Updating repo '{repo}'...")
-    subprocess.run(["git", "pull"], check=True)
+    subprocess.run(["git", "pull"], check=False)
 
 
 def install(

docs/docs/upgrade/v0.5.0.md

@@ -1,4 +1,4 @@
-# Upgrade To v0.5.0(Draft)
+# Upgrade To v0.5.0
 
 ## Overview
 

setup.py

@@ -18,7 +18,7 @@
 IS_DEV_MODE = os.getenv("IS_DEV_MODE", "true").lower() == "true"
 # If you modify the version, please modify the version in the following files:
 # dbgpt/_version.py
-DB_GPT_VERSION = os.getenv("DB_GPT_VERSION", "0.4.7")
+DB_GPT_VERSION = os.getenv("DB_GPT_VERSION", "0.5.0")
 
 BUILD_NO_CACHE = os.getenv("BUILD_NO_CACHE", "true").lower() == "true"
 LLAMA_CPP_GPU_ACCELERATION = (