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Update utils/database.py
Browse files- utils/database.py +5 -5
utils/database.py
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@@ -10,7 +10,8 @@ from langchain_core.messages import (
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from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
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from langchain_core.runnables import RunnablePassthrough
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from langchain.chains import ConversationalRetrievalChain
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from langchain.chat_models import ChatOpenAI
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from langchain.agents import AgentExecutor, Tool, create_openai_tools_agent
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from langchain.agents.format_scratchpad.tools import format_to_tool_messages
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from langchain.agents.output_parsers.openai_tools import OpenAIToolsAgentOutputParser
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@@ -335,12 +336,11 @@ def display_vector_store_info():
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def initialize_qa_system(vector_store):
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"""Initialize QA system with proper chat handling."""
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try:
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llm =
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temperature=0.5,
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api_key=os.environ.get("GEMINI_API_KEY")
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# Create retriever function
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retriever = vector_store.as_retriever(search_kwargs={"k": 2})
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from langchain.prompts import ChatPromptTemplate, MessagesPlaceholder
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from langchain_core.runnables import RunnablePassthrough
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from langchain.chains import ConversationalRetrievalChain
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#from langchain.chat_models import ChatOpenAI
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from langchain.chat_models import ChatGemini # Import ChatGemini
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from langchain.agents import AgentExecutor, Tool, create_openai_tools_agent
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from langchain.agents.format_scratchpad.tools import format_to_tool_messages
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from langchain.agents.output_parsers.openai_tools import OpenAIToolsAgentOutputParser
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def initialize_qa_system(vector_store):
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"""Initialize QA system with proper chat handling."""
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try:
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llm = ChatGemini(
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temperature=0.5,
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model="gemini-1.5-pro",
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api_key=os.environ.get("GEMINI_API_KEY")
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# Create retriever function
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retriever = vector_store.as_retriever(search_kwargs={"k": 2})
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