afiqzudinhadi/linkedIn_auto_jobs_applier_with_AI
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Adding Google Gemini

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Khalid F. Ahmed 2024-09-10 09:16:04 +03:00
parent 2242b3e0b7
commit 0d036f6a6e
2 changed files with 16 additions and 4 deletions
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1
requirements.txt
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@ -17,6 +17,7 @@ pdfminer.six==20221105
inputimeout==1.0.4 inputimeout==1.0.4
langchain-ollama==0.1.3 langchain-ollama==0.1.3
langchain-anthropic==0.1.3 langchain-anthropic==0.1.3
langchain-google-genai==1.0.10
jsonschema==4.23.0 jsonschema==4.23.0
jsonschema-specifications==2023.12.1 jsonschema-specifications==2023.12.1
httpx~=0.27.2 httpx~=0.27.2

19
src/gpt.py
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@ -62,6 +62,16 @@ class OllamaModel(AIModel):
return response return response
class GeminiModel(AIModel):
def __init__(self, api_key:str, llm_model: str, llm_api_url: str):
from langchain_google_genai import ChatGoogleGenerativeAI
self.model = ChatGoogleGenerativeAI(model=llm_model, google_api_key=api_key)
def invoke(self, prompt: str) -> str:
response = self.model.invoke(prompt)
return response
class AIAdapter: class AIAdapter:
def __init__(self, config: dict, api_key: str): def __init__(self, config: dict, api_key: str):
self.model = self._create_model(config, api_key) self.model = self._create_model(config, api_key)
@ -79,6 +89,8 @@ class AIAdapter:
return ClaudeModel(api_key, llm_model, llm_api_url) return ClaudeModel(api_key, llm_model, llm_api_url)
elif llm_model_type == "ollama": elif llm_model_type == "ollama":
return OllamaModel(api_key, llm_model, llm_api_url) return OllamaModel(api_key, llm_model, llm_api_url)
elif llm_model_type == "gemini":
return GeminiModel(api_key, llm_model, llm_api_url)
else: else:
raise ValueError(f"Unsupported model type: {llm_model_type}") raise ValueError(f"Unsupported model type: {llm_model_type}")
@ -88,7 +100,7 @@ class AIAdapter:
class LLMLogger: class LLMLogger:
def __init__(self, llm: Union[OpenAIModel, OllamaModel, ClaudeModel]): def __init__(self, llm: Union[OpenAIModel, OllamaModel, ClaudeModel, GeminiModel]):
self.llm = llm self.llm = llm
logger.debug("LLMLogger successfully initialized with LLM: %s", llm) logger.debug("LLMLogger successfully initialized with LLM: %s", llm)
@ -203,7 +215,7 @@ class LLMLogger:
class LoggerChatModel: class LoggerChatModel:
def __init__(self, llm: Union[OpenAIModel, OllamaModel, ClaudeModel]): def __init__(self, llm: Union[OpenAIModel, OllamaModel, ClaudeModel, GeminiModel]):
self.llm = llm self.llm = llm
logger.debug( logger.debug(
"LoggerChatModel successfully initialized with LLM: %s", llm) "LoggerChatModel successfully initialized with LLM: %s", llm)
@ -494,8 +506,7 @@ class GPTAnswerer:
if resume_section is None: if resume_section is None:
logger.error( logger.error(
"Section '%s' not found in either resume or job_application_profile.", section_name) "Section '%s' not found in either resume or job_application_profile.", section_name)
raise ValueError(f"Section '{ raise ValueError(f"Section '{section_name}' not found in either resume or job_application_profile.")
section_name}' not found in either resume or job_application_profile.")
chain = chains.get(section_name) chain = chains.get(section_name)
if chain is None: if chain is None:
logger.error("Chain not defined for section '%s'", section_name) logger.error("Chain not defined for section '%s'", section_name)