File size: 2,933 Bytes
b486b3a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 |
from fastapi import FastAPI, Form
from langchain_core.runnables.base import RunnableSequence
from langchain_core.prompts import ChatPromptTemplate
from langchain_groq import ChatGroq
import os
import requests
from dotenv import load_dotenv
from langgraph.checkpoint.memory import MemorySaver
from langgraph.prebuilt import create_react_agent
from langchain_community.tools.tavily_search import TavilySearchResults
load_dotenv()
app = FastAPI()
llm = ChatGroq(
model="llama-3.1-70b-versatile",
temperature=0,
max_tokens=None,
timeout=None,
max_retries=5,
groq_api_key=os.getenv("GROQ_API_KEY")
)
search = TavilySearchResults(
max_results=2,
)
tools = [search]
memory = MemorySaver()
agent_executor = create_react_agent(llm, tools, checkpointer=memory)
def translate(target, text):
'''
Translates given text into target language
Parameters:
target (string): 2 character code to specify the target language.
text (string): Text to be translated.
Returns:
res (string): Translated text.
'''
url = "https://microsoft-translator-text.p.rapidapi.com/translate"
querystring = {"api-version":"3.0","profanityAction":"NoAction","textType":"plain", "to":target}
payload = [{ "Text": text }]
headers = {
"x-rapidapi-key": os.getenv("RAPIDAPI_LANG_TRANS"),
"x-rapidapi-host": "microsoft-translator-text.p.rapidapi.com",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers, params=querystring)
res = response.json()
return res[0]["translations"][0]["text"]
@app.post('/infer/{user_id}')
def infer(user_id: str, user_input: str = Form(...)):
'''
Returns the translated response from the LLM in response to a user query.
Parameters:
user_id (string): User ID of a user.
user_input (string): User query.
Returns:
JSON Response (Dictionary): Returns a translated response from the LLM.
'''
user_input = translate("en", user_input) # translate user query to english
prompt = ChatPromptTemplate.from_messages( # define a prompt
[
(
"system",
"You're a compassionate AI virtual Assistant"
),
("human", "{user_input}")
]
)
runnable = prompt | agent_executor # define a chain
conversation = RunnableSequence( # wrap the chain along with chat history and user input
runnable,
)
response = conversation.invoke( # invoke the chain by giving the user input and the chat history
{"user_input": user_input},
config={"configurable": {"thread_id":user_id}}
)
res = translate("ur", response["messages"][-1].content) # translate the response to Urdu
return {
"data": res
} |