Skip to main content

A simple tool that automates the qualification of a partner(reseller/integrator/editor) by finding its website, industries, business functions and services.

Project description

Background

A simple tool that automates the qualification of a partner(reseller/integrator/editor) by finding its website, industries, business functions and services in a structured way.

  • It provides browsing ability to reduce hallucination problem and improve the information precision.

  • It provides single mode and batch mode so that you can integrate as an API or in a scheduler easily.

An example of qualification result:

  • (industry column) Target your industry
  • (job column) The jobs that can be targeted through their industry
  • (offers column) The services they offer.

alt text

Install

pip install partenaire-qualif

Usage

The tool provides browsing ability which can be activated by setting the parameter browsing to True. Sample code below.

from qualif import CompanyQualificationTool
from openai import AzureOpenAI, OpenAI
import pandas as pd


# Necessary Variables
azure_endpoint = "https://..."  # azure openai endpoint
apikey = "..." # azure openai apikey
apiversion = "..." # azure openai api version
model = "..." # azure openai model name

# Setup OpenAI CLI
client = AzureOpenAI(
    azure_endpoint=azure_endpoint,
    api_key=apikey,
    api_version=apiversion,
)

# Use QualificationTool without browsing
browsing = False
tool = CompanyQualificationTool(client=client, model=model, temperature=0, browsing=browsing)
result = tool.qualify(partner_name="Your_Partner_Name")


# Use QualificationTool with browsing
browsing = True
browsing_key = '...' # azure bing search apikey
tool = CompanyQualificationTool(client=client, model=model, temperature=0, browsing=browsing, browsing_key=browsing_key)
result = tool.qualify(partner_name="Your_Partner_Name")
print(result)

The tool also allow to execute in batch mode by providing a panda dataframe. Sample code as below.

# Construct panda dataframe from a excel file that has a column containing the name of partners
df_partenaires = pd.read_excel("Partenaires.xlsx",sheet_name="Partenaires")

# Use the batch method to execute the qualification in batch
final_df = tool.batch(df_partners=df_partenaires, col_name_partner="Nom_Partenaire")
final_df.to_excel("Partenaires_qualified.xlsx")

Release

source release.sh {NEW_VERSION}  # example 1.1.1

Maintainers

@YMURONG

License

License: MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

partenaire-qualif-0.2.4.tar.gz (8.6 kB view details)

Uploaded Source

Built Distribution

partenaire_qualif-0.2.4-py3-none-any.whl (9.4 kB view details)

Uploaded Python 3

File details

Details for the file partenaire-qualif-0.2.4.tar.gz.

File metadata

  • Download URL: partenaire-qualif-0.2.4.tar.gz
  • Upload date:
  • Size: 8.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.0 CPython/3.10.11

File hashes

Hashes for partenaire-qualif-0.2.4.tar.gz
Algorithm Hash digest
SHA256 5b81b477b05a1299cfd450d6eafe9a2f0f0e431f3e61c1f598c8bb0fbec70927
MD5 2762f20a0bd901254bb1cf19737df633
BLAKE2b-256 2f206b47e7def3371c449000fc8ec572011d96eeadb54f24a71cf767f61821c3

See more details on using hashes here.

File details

Details for the file partenaire_qualif-0.2.4-py3-none-any.whl.

File metadata

File hashes

Hashes for partenaire_qualif-0.2.4-py3-none-any.whl
Algorithm Hash digest
SHA256 42c8853c5cf20593223fe20b6c526286b4bd4f625ada12a8eaf10b1b8ec59ac7
MD5 8fc09391f4da209e8b1d793614982455
BLAKE2b-256 afc19a58d08d15ec70e231ebfb3ca39977672168f05ae6d08cda5eb44f2ccd2a

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page