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https://github.com/hwchase17/langchain
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Co-authored-by: jacoblee93 <jacoblee93@gmail.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
52 lines
1.3 KiB
Plaintext
52 lines
1.3 KiB
Plaintext
```python
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from langchain import OpenAI, ConversationChain
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llm = OpenAI(temperature=0)
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conversation = ConversationChain(llm=llm, verbose=True)
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conversation.run("Hi there!")
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```
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here's what's going on under the hood
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```pycon
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> Entering new chain...
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Prompt after formatting:
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The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.
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Current conversation:
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Human: Hi there!
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AI:
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> Finished chain.
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>> 'Hello! How are you today?'
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```
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Now if we run the chain again
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```python
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conversation.run("I'm doing well! Just having a conversation with an AI.")
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```
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we'll see that the full prompt that's passed to the model contains the input and output of our first interaction, along with our latest input
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```pycon
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> Entering new chain...
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Prompt after formatting:
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The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.
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Current conversation:
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Human: Hi there!
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AI: Hello! How are you today?
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Human: I'm doing well! Just having a conversation with an AI.
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AI:
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> Finished chain.
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>> "That's great! What would you like to talk about?"
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```
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