🐛 fix(chat.py): remove unused user dependency in stream_build function
🐛 fix(chat.py): handle KeyError when retrieving user_id from cache_service ✨ feat(chat.py): use user_id from cache_service instead of user.id in try_running_celery_task and vertex.build functions 🔧 chore(config.yaml): comment out ConversationChain in chains configuration 🔧 chore(base.py): import SQLDatabaseChain from langchain_experimental.sql module and add it to type_dict
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3 changed files with 11 additions and 6 deletions
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@ -127,7 +127,6 @@ async def stream_build(
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flow_id: str,
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chat_service: "ChatService" = Depends(get_chat_service),
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cache_service: "BaseCacheService" = Depends(get_cache_service),
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user=Depends(get_current_active_user),
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):
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"""Stream the build process based on stored flow data."""
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@ -161,6 +160,11 @@ async def stream_build(
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number_of_nodes = len(graph.nodes)
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update_build_status(cache_service, flow_id, BuildStatus.IN_PROGRESS)
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try:
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user_id = cache_service[flow_id]["user_id"]
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except KeyError:
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logger.debug("No user_id found in cache_service")
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user_id = None
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for i, vertex in enumerate(graph.generator_build(), 1):
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try:
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log_dict = {
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@ -168,9 +172,9 @@ async def stream_build(
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}
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yield str(StreamData(event="log", data=log_dict))
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if vertex.is_task:
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vertex = try_running_celery_task(vertex, user.id)
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vertex = try_running_celery_task(vertex, user_id)
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else:
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vertex.build(user_id=user.id)
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vertex.build(user_id=user_id)
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params = vertex._built_object_repr()
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valid = True
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logger.debug(f"Building node {str(vertex.vertex_type)}")
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@ -20,8 +20,8 @@ chains:
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documentation: "https://python.langchain.com/docs/modules/chains/additional/llm_math"
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LLMCheckerChain:
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documentation: "https://python.langchain.com/docs/modules/chains/additional/llm_checker"
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ConversationChain:
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documentation: ""
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# ConversationChain:
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# documentation: ""
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SeriesCharacterChain:
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documentation: ""
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MidJourneyPromptChain:
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@ -9,6 +9,7 @@ from langflow.template.frontend_node.chains import ChainFrontendNode
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from loguru import logger
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from langflow.utils.util import build_template_from_class, build_template_from_method
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from langchain import chains
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from langchain_experimental.sql import SQLDatabaseChain
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# Assuming necessary imports for Field, Template, and FrontendNode classes
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@ -37,7 +38,7 @@ class ChainCreator(LangChainTypeCreator):
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}
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from langflow.interface.chains.custom import CUSTOM_CHAINS
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# self.type_dict["SQLDatabaseChain"] = SQLDatabaseChain
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self.type_dict["SQLDatabaseChain"] = SQLDatabaseChain
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self.type_dict.update(CUSTOM_CHAINS)
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# Filter according to settings.chains
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