mirror of
https://github.com/hwchase17/langchain
synced 2024-11-10 01:10:59 +00:00
6da0cfea0e
**Description**
The `SmartLLMChain` was was fixed to output key "resolution".
Unfortunately, this prevents the ability to use multiple `SmartLLMChain`
in a `SequentialChain` because of colliding output keys. This change
simply gives the option the customize the output key to allow for
sequential chaining. The default behavior is the same as the current
behavior.
Now, it's possible to do the following:
```
from langchain.chat_models import ChatOpenAI
from langchain.prompts import PromptTemplate
from langchain_experimental.smart_llm import SmartLLMChain
from langchain.chains import SequentialChain
joke_prompt = PromptTemplate(
input_variables=["content"],
template="Tell me a joke about {content}.",
)
review_prompt = PromptTemplate(
input_variables=["scale", "joke"],
template="Rate the following joke from 1 to {scale}: {joke}"
)
llm = ChatOpenAI(temperature=0.9, model_name="gpt-4-32k")
joke_chain = SmartLLMChain(llm=llm, prompt=joke_prompt, output_key="joke")
review_chain = SmartLLMChain(llm=llm, prompt=review_prompt, output_key="review")
chain = SequentialChain(
chains=[joke_chain, review_chain],
input_variables=["content", "scale"],
output_variables=["review"],
verbose=True
)
response = chain.run({"content": "chickens", "scale": "10"})
print(response)
```
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
|
||
|---|---|---|
| .. | ||
| agents | ||
| autonomous_agents | ||
| chat_models | ||
| comprehend_moderation | ||
| cpal | ||
| data_anonymizer | ||
| fallacy_removal | ||
| generative_agents | ||
| graph_transformers | ||
| llm_bash | ||
| llm_symbolic_math | ||
| llms | ||
| open_clip | ||
| openai_assistant | ||
| pal_chain | ||
| plan_and_execute | ||
| prompt_injection_identifier | ||
| prompts | ||
| pydantic_v1 | ||
| retrievers | ||
| rl_chain | ||
| smart_llm | ||
| sql | ||
| synthetic_data | ||
| tabular_synthetic_data | ||
| tools | ||
| tot | ||
| utilities | ||
| __init__.py | ||
| py.typed | ||