forked from Archives/langchain
Replaced SQLDatabaseChain
deprecated direct initialisation with from_llm
method (#4778)
# Removed usage of deprecated methods Replaced `SQLDatabaseChain` deprecated direct initialisation with `from_llm` method ## Who can review? @hwchase17 @agola11 --------- Co-authored-by: imeckr <chandanroutray2012@gmail.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
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@ -42,7 +42,7 @@
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"search = SerpAPIWrapper()\n",
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"llm_math_chain = LLMMathChain(llm=llm, verbose=True)\n",
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"db = SQLDatabase.from_uri(\"sqlite:///../../../../../notebooks/Chinook.db\")\n",
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"db_chain = SQLDatabaseChain(llm=llm, database=db, verbose=True)\n",
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"db_chain = SQLDatabaseChain.from_llm(llm, db, verbose=True)\n",
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"tools = [\n",
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" Tool(\n",
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" name = \"Search\",\n",
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@ -44,7 +44,7 @@
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"search = SerpAPIWrapper()\n",
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"llm_math_chain = LLMMathChain(llm=llm1, verbose=True)\n",
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"db = SQLDatabase.from_uri(\"sqlite:///../../../../../notebooks/Chinook.db\")\n",
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"db_chain = SQLDatabaseChain(llm=llm1, database=db, verbose=True)\n",
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"db_chain = SQLDatabaseChain.from_llm(llm1, db, verbose=True)\n",
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"tools = [\n",
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" Tool(\n",
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" name = \"Search\",\n",
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@ -213,7 +213,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"chain = SQLDatabaseChain(llm=llm, database=db, input_key=\"question\")"
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"chain = SQLDatabaseChain.from_llm(llm, db, input_key=\"question\")"
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]
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},
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{
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@ -415,7 +415,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.1"
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"version": "3.11.3"
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}
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},
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"nbformat": 4,
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@ -307,7 +307,9 @@ def _load_sql_database_chain(config: dict, **kwargs: Any) -> SQLDatabaseChain:
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if "prompt" in config:
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prompt_config = config.pop("prompt")
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prompt = load_prompt_from_config(prompt_config)
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return SQLDatabaseChain(database=database, llm=llm, prompt=prompt, **config)
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else:
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prompt = None
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return SQLDatabaseChain.from_llm(llm, database, prompt=prompt, **config)
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def _load_vector_db_qa_with_sources_chain(
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@ -223,8 +223,8 @@ class SQLDatabaseSequentialChain(Chain):
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**kwargs: Any,
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) -> SQLDatabaseSequentialChain:
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"""Load the necessary chains."""
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sql_chain = SQLDatabaseChain(
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llm=llm, database=database, prompt=query_prompt, **kwargs
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sql_chain = SQLDatabaseChain.from_llm(
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llm, database, prompt=query_prompt, **kwargs
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)
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decider_chain = LLMChain(
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llm=llm, prompt=decider_prompt, output_key="table_names"
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