2023-10-26 01:47:42 +00:00
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import os
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import cassio
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import langchain
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2023-10-27 02:44:30 +00:00
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from langchain.cache import CassandraCache
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2023-10-26 01:47:42 +00:00
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from langchain.chat_models import ChatOpenAI
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from langchain.prompts import ChatPromptTemplate
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from langchain.schema import BaseMessage
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docs[patch], templates[patch]: Import from core (#14575)
Update imports to use core for the low-hanging fruit changes. Ran
following
```bash
git grep -l 'langchain.schema.runnable' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.runnable/langchain_core.runnables/g'
git grep -l 'langchain.schema.output_parser' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.output_parser/langchain_core.output_parsers/g'
git grep -l 'langchain.schema.messages' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.messages/langchain_core.messages/g'
git grep -l 'langchain.schema.chat_histry' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.chat_history/langchain_core.chat_history/g'
git grep -l 'langchain.schema.prompt_template' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.prompt_template/langchain_core.prompts/g'
git grep -l 'from langchain.pydantic_v1' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.pydantic_v1/from langchain_core.pydantic_v1/g'
git grep -l 'from langchain.tools.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.tools\.base/from langchain_core.tools/g'
git grep -l 'from langchain.chat_models.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.chat_models.base/from langchain_core.language_models.chat_models/g'
git grep -l 'from langchain.llms.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.llms\.base\ /from langchain_core.language_models.llms\ /g'
git grep -l 'from langchain.embeddings.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.embeddings\.base/from langchain_core.embeddings/g'
git grep -l 'from langchain.vectorstores.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.vectorstores\.base/from langchain_core.vectorstores/g'
git grep -l 'from langchain.agents.tools' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.agents\.tools/from langchain_core.tools/g'
git grep -l 'from langchain.schema.output' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.output\ /from langchain_core.outputs\ /g'
git grep -l 'from langchain.schema.embeddings' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.embeddings/from langchain_core.embeddings/g'
git grep -l 'from langchain.schema.document' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.document/from langchain_core.documents/g'
git grep -l 'from langchain.schema.agent' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.agent/from langchain_core.agents/g'
git grep -l 'from langchain.schema.prompt ' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.prompt\ /from langchain_core.prompt_values /g'
git grep -l 'from langchain.schema.language_model' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.language_model/from langchain_core.language_models/g'
```
2023-12-12 00:49:10 +00:00
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from langchain_core.runnables import RunnableLambda
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2023-10-26 01:47:42 +00:00
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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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2023-10-29 22:50:09 +00:00
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2023-10-26 01:47:42 +00:00
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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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2023-10-29 22:50:09 +00:00
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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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2023-10-26 01:47:42 +00:00
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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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