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from fastapi import FastAPI, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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import google.generativeai as genai
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import os
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import requests
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import pandas as pd
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import validators
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from sklearn.feature_extraction.text import TfidfVectorizer
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from dotenv import load_dotenv
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load_dotenv()
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
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df=pd.read_csv("salaries.csv")
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app = FastAPI()
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origins=[
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"http://localhost:5173",
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]
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app.add_middleware(
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CORSMiddleware,
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allow_origins=origins,
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allow_credentials=True,
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allow_methods=['*'],
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allow_headers=['*']
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)
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model=genai.GenerativeModel("gemini-1.5-flash")
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df_combined = df.astype(str).apply(lambda x: ' '.join(x), axis=1).tolist()
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vectorizer = TfidfVectorizer()
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X = vectorizer.fit_transform(df_combined)
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def genetate_gemini_content(prompt,content):
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response=model.generate_content([prompt,content])
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return response.text
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work_year = df['work_year']
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job_titles = df['job_title']
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salaries = df['salary']
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experience_level = df['experience_level']
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employment_type = df['employment_type']
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salary_in_usd = df['salary_in_usd']
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company_size = df['company_size']
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df_combined = df.astype(str).apply(lambda x: ' '.join(x), axis=1).tolist()
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vectorizer = TfidfVectorizer()
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X = vectorizer.fit_transform(df_combined)
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prompt = f"""
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I have a dataset with the following salary information:
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Work Year: {work_year.tolist()}
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Job Titles: {job_titles.tolist()}
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Salaries (in USD): {salary_in_usd.tolist()}
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Experience Level: {experience_level.tolist()}
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Employment Type: {employment_type.tolist()}
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Company Size: {company_size.tolist()}
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Based on this data, can you answer the following question:
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Please provide a short and direct answer based on the data. No extra explanations are needed, just the answer less than 2 lines and dont use "\ n" or any special charcher other than related to the data .
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"""
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@app.get("/hi")
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async def ee():
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return {"de":"hehe"}
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@app.post("/webqa")
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async def webchat(question:str):
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try:
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response=model.generate_content([prompt,question])
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print(response.text)
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return response.text
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except:
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raise HTTPException(status_code=500, detail="Internal Server Error")
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