mirror of
https://github.com/hwchase17/langchain
synced 2024-11-08 07:10:35 +00:00
ed789be8f4
- chat models, messages - documents - agentaction/finish - baseretriever,document - stroutputparser - more messages - basemessage - format_document - baseoutputparser --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
43 lines
1.2 KiB
Python
43 lines
1.2 KiB
Python
import os
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import cassio
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import langchain
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from langchain.cache import CassandraCache
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from langchain_community.chat_models import ChatOpenAI
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from langchain_core.messages import BaseMessage
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from langchain_core.prompts import ChatPromptTemplate
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from langchain_core.runnables import RunnableLambda
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use_cassandra = int(os.environ.get("USE_CASSANDRA_CLUSTER", "0"))
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if use_cassandra:
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from .cassandra_cluster_init import get_cassandra_connection
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session, keyspace = get_cassandra_connection()
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cassio.init(
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session=session,
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keyspace=keyspace,
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)
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else:
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cassio.init(
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token=os.environ["ASTRA_DB_APPLICATION_TOKEN"],
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database_id=os.environ["ASTRA_DB_ID"],
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keyspace=os.environ.get("ASTRA_DB_KEYSPACE"),
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)
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# inits
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langchain.llm_cache = CassandraCache(session=None, keyspace=None)
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llm = ChatOpenAI()
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# custom runnables
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def msg_splitter(msg: BaseMessage):
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return [w.strip() for w in msg.content.split(",") if w.strip()]
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# synonym-route preparation
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synonym_prompt = ChatPromptTemplate.from_template(
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"List up to five comma-separated synonyms of this word: {word}"
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)
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chain = synonym_prompt | llm | RunnableLambda(msg_splitter)
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