├── constants.py
├── README.md
├── requirements.txt
├── main.py
└── example1.py


/constants.py:
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1 | openai_key=""


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/README.md:
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1 | # Langchain-Tutorials


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/requirements.txt:
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1 | openai
2 | langchain
3 | streamlit


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/main.py:
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 1 | ## Integrate our code OpenAI API
 2 | import os
 3 | from constants import openai_key
 4 | from langchain.llms import OpenAI
 5 | 
 6 | import streamlit as st
 7 | 
 8 | os.environ["OPENAI_API_KEY"]=openai_key
 9 | 
10 | # streamlit framework
11 | 
12 | st.title('Langchain Demo With OPENAI API')
13 | input_text=st.text_input("Search the topic u want")
14 | 
15 | ## OPENAI LLMS
16 | llm=OpenAI(temperature=0.8)
17 | 
18 | 
19 | 
20 | if input_text:
21 |     st.write(llm(input_text))
22 | 


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/example1.py:
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 1 | ## Integrate our code OpenAI API
 2 | import os
 3 | from constants import openai_key
 4 | from langchain.llms import OpenAI
 5 | from langchain import PromptTemplate
 6 | from langchain.chains import LLMChain
 7 | 
 8 | from langchain.memory import ConversationBufferMemory
 9 | 
10 | from langchain.chains import SequentialChain
11 | 
12 | import streamlit as st
13 | 
14 | os.environ["OPENAI_API_KEY"]=openai_key
15 | 
16 | # streamlit framework
17 | 
18 | st.title('Celebrity Search Results')
19 | input_text=st.text_input("Search the topic u want")
20 | 
21 | # Prompt Templates
22 | 
23 | first_input_prompt=PromptTemplate(
24 |     input_variables=['name'],
25 |     template="Tell me about celebrity {name}"
26 | )
27 | 
28 | # Memory
29 | 
30 | person_memory = ConversationBufferMemory(input_key='name', memory_key='chat_history')
31 | dob_memory = ConversationBufferMemory(input_key='person', memory_key='chat_history')
32 | descr_memory = ConversationBufferMemory(input_key='dob', memory_key='description_history')
33 | 
34 | ## OPENAI LLMS
35 | llm=OpenAI(temperature=0.8)
36 | chain=LLMChain(
37 |     llm=llm,prompt=first_input_prompt,verbose=True,output_key='person',memory=person_memory)
38 | 
39 | # Prompt Templates
40 | 
41 | second_input_prompt=PromptTemplate(
42 |     input_variables=['person'],
43 |     template="when was {person} born"
44 | )
45 | 
46 | chain2=LLMChain(
47 |     llm=llm,prompt=second_input_prompt,verbose=True,output_key='dob',memory=dob_memory)
48 | # Prompt Templates
49 | 
50 | third_input_prompt=PromptTemplate(
51 |     input_variables=['dob'],
52 |     template="Mention 5 major events happened around {dob} in the world"
53 | )
54 | chain3=LLMChain(llm=llm,prompt=third_input_prompt,verbose=True,output_key='description',memory=descr_memory)
55 | parent_chain=SequentialChain(
56 |     chains=[chain,chain2,chain3],input_variables=['name'],output_variables=['person','dob','description'],verbose=True)
57 | 
58 | 
59 | 
60 | if input_text:
61 |     st.write(parent_chain({'name':input_text}))
62 | 
63 |     with st.expander('Person Name'): 
64 |         st.info(person_memory.buffer)
65 | 
66 |     with st.expander('Major Events'): 
67 |         st.info(descr_memory.buffer)
68 | 


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