Added support for Ollama running locally or publicly hosted api

README.md

@@ -152,6 +152,12 @@ This file contains sensitive information. Never share or commit this file to ver
   - Replace with your OpenAI API key for GPT integration
   - To obtain an API key, follow the tutorial at: https://medium.com/@lorenzozar/how-to-get-your-own-openai-api-key-f4d44e60c327
   - Note: You need to add credit to your OpenAI account to use the API. You can add credit by visiting the [OpenAI billing dashboard](https://platform.openai.com/account/billing).
+- `openai_api_free_hosted_url`: 
+  - Optional paramter, if you want to use freely hosted GPT model, set `openai_api_key: "freehosted"` and `openai_api_free_hosted_url` with the URL of the endpoint
+- Ollama local support
+  - If you want to use Ollama which is deployed locally, leave `openai_api_key` blank.
+  - To setup Ollama to run locally follow the instructions here: [Ollama installation](https://github.com/ollama/ollama).
+  - Download mistral model by pulling mistral:v0.3
   
 
 

data_folder/secrets.yaml

@@ -1,3 +1,4 @@
 email: myemaillinkedin@gmail.com
 password: ImpossiblePassowrd10
 openai_api_key: sk-11KRr4uuTwpRGfeRTfj1T9BlbkFJjP8QTrswHU1yGruru2FR
+openai_api_free_hosted_url: https://api.pawan.krd/cosmosrp/v1

data_folder_example/secrets.yaml

@@ -1,3 +1,4 @@
 email: myemaillinkedin@gmail.com
 password: ImpossiblePassowrd10
 openai_api_key: sk-11KRr4uuTwpRGfeRTfj1T9BlbkFJjP8QTrswHU1yGruru2FR
+openai_api_free_hosted_url: https://api.pawan.krd/cosmosrp/v1

main.py

@@ -101,7 +101,7 @@ class ConfigValidator:
     @staticmethod
     def validate_secrets(secrets_yaml_path: Path) -> tuple:
         secrets = ConfigValidator.validate_yaml_file(secrets_yaml_path)
-        mandatory_secrets = ['email', 'password', 'openai_api_key']
+        mandatory_secrets = ['email', 'password']
 
         for secret in mandatory_secrets:
             if secret not in secrets:
@@ -114,7 +114,7 @@ class ConfigValidator:
         if not secrets['openai_api_key']:
             raise ConfigError(f"OpenAI API key cannot be empty in secrets file {secrets_yaml_path}.")
 
-        return secrets['email'], str(secrets['password']), secrets['openai_api_key']
+        return secrets['email'], str(secrets['password']), secrets['openai_api_key'], secrets['openai_api_free_hosted_url']
 
 class FileManager:
     @staticmethod
@@ -158,7 +158,7 @@ def init_browser() -> webdriver.Chrome:
     except Exception as e:
         raise RuntimeError(f"Failed to initialize browser: {str(e)}")
 
-def create_and_run_bot(email: str, password: str, parameters: dict, openai_api_key: str):
+def create_and_run_bot(email, password, parameters, openai_api_key, openai_api_free_hosted_url):
     try:
         style_manager = StyleManager()
         resume_generator = ResumeGenerator()
@@ -175,7 +175,7 @@ def create_and_run_bot(email: str, password: str, parameters: dict, openai_api_k
         browser = init_browser()
         login_component = LinkedInAuthenticator(browser)
         apply_component = LinkedInJobManager(browser)
-        gpt_answerer_component = GPTAnswerer(openai_api_key)
+        gpt_answerer_component = GPTAnswerer(openai_api_key, openai_api_free_hosted_url)
         bot = LinkedInBotFacade(login_component, apply_component)
         bot.set_secrets(email, password)
         bot.set_job_application_profile_and_resume(job_application_profile_object, resume_object)
@@ -197,12 +197,12 @@ def main(resume: Path = None):
         secrets_file, config_file, plain_text_resume_file, output_folder = FileManager.validate_data_folder(data_folder)
         
         parameters = ConfigValidator.validate_config(config_file)
-        email, password, openai_api_key = ConfigValidator.validate_secrets(secrets_file)
+        email, password, openai_api_key, openai_api_free_hosted_url = ConfigValidator.validate_secrets(secrets_file)
         
         parameters['uploads'] = FileManager.file_paths_to_dict(resume, plain_text_resume_file)
         parameters['outputFileDirectory'] = output_folder
         
-        create_and_run_bot(email, password, parameters, openai_api_key)
+        create_and_run_bot(email, password, parameters, openai_api_key, openai_api_free_hosted_url)
     except ConfigError as ce:
         print(f"Configuration error: {str(ce)}")
         print("Refer to the configuration guide for troubleshooting: https://github.com/feder-cr/LinkedIn_AIHawk_automatic_job_application/blob/main/readme.md#configuration")

src/gpt.py

@@ -3,7 +3,7 @@ import os
 import re
 import textwrap
 from datetime import datetime
-from typing import Dict, List
+from typing import Dict, List, Union
 from pathlib import Path
 from dotenv import load_dotenv
 from langchain_core.messages.ai import AIMessage
@@ -11,6 +11,7 @@ from langchain_core.output_parsers import StrOutputParser
 from langchain_core.prompt_values import StringPromptValue
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_openai import ChatOpenAI
+from langchain_ollama import ChatOllama
 from Levenshtein import distance
 
 import src.strings as strings
@@ -20,7 +21,7 @@ load_dotenv()
 
 class LLMLogger:
     
-    def __init__(self, llm: ChatOpenAI):
+    def __init__(self, llm: Union[ChatOpenAI, ChatOllama]):
         self.llm = llm
 
     @staticmethod
@@ -78,12 +79,12 @@ class LLMLogger:
 
 class LoggerChatModel:
 
-    def __init__(self, llm: ChatOpenAI):
+    def __init__(self, llm: Union[ChatOpenAI, ChatOllama]):
         self.llm = llm
 
     def __call__(self, messages: List[Dict[str, str]]) -> str:
         # Call the LLM with the provided messages and log the response.
-        reply = self.llm(messages)
+        reply = self.llm.invoke(messages)
         parsed_reply = self.parse_llmresult(reply)
         LLMLogger.log_request(prompts=messages, parsed_reply=parsed_reply)
         return reply
@@ -113,10 +114,18 @@ class LoggerChatModel:
 
 
 class GPTAnswerer:
-    def __init__(self, openai_api_key):
+    def __init__(self, openai_api_key, openai_api_free_hosted_url):
-        self.llm_cheap = LoggerChatModel(
+        if openai_api_key == "":
-            ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=openai_api_key, temperature=0.4)
+            print('Using locally hosted mistral:v0.3')
-        )
+            self.llm_model = ChatOllama(model = "mistral:v0.3", temperature = 0.4, num_predict = 256)
+        elif openai_api_key == "freehosted":
+            print('Using free hosted gpt-4o-mini')
+            self.llm_model = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key="anything", temperature=0.4,
+                                base_url=openai_api_free_hosted_url)
+        else: 
+            print("Using gpt-4o-mini")
+            self.llm_model = ChatOpenAI(model_name="gpt-4o-mini", openai_api_key=openai_api_key, temperature=0.4)
+        self.llm_cheap = LoggerChatModel(self.llm_model)
     @property
     def job_description(self):
         return self.job.description