Merge pull request #341 from khalid-faiz/v3

Adding Google Gemini Implementation

README.md

@@ -153,7 +153,7 @@ This file contains sensitive information. Never share or commit this file to ver
   - Replace with your LinkedIn account email address
 - `password: [Your LinkedIn password]`
   - Replace with your LinkedIn account password
-- `llm_api_key: [Your OpenAI or Ollama API key]`
+- `llm_api_key: [Your OpenAI or Ollama API key or Gemini API key]`
   - 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).
@@ -162,6 +162,7 @@ This file contains sensitive information. Never share or commit this file to ver
     `{'error': {'message': 'Rate limit reached for gpt-4o-mini in organization <org> on requests per day (RPD): Limit 200, Used 200, Requested 1.}}`  
     OpenAI will update your account automatically, but it might take some time, ranging from a couple of hours to a few days.  
     You can find more about your organization limits on the [official page](https://platform.openai.com/settings/organization/limits).
+  - For obtaining Gemini API key visit [Google AI for Devs](https://ai.google.dev/gemini-api/docs/api-key)
 
 
 ### 2. config.yaml
@@ -225,17 +226,19 @@ This file defines your job search parameters and bot behavior. Each section cont
 #### 2.1 config.yaml - Customize LLM model endpoint
 
 - `llm_model_type`:
-  - Choose the model type, supported: openai / ollama / claude
+  - Choose the model type, supported: openai / ollama / claude / gemini
 - `llm_model`: 
   - Choose the LLM model, currently supported: 
     - openai: gpt-4o
     - ollama: llama2, mistral:v0.3
     - claude: any model 
+    - gemini: any model
 - `llm_api_url`: 
   - Link of the API endpoint for the LLM model
     - openai: https://api.pawan.krd/cosmosrp/v1
     - ollama: http://127.0.0.1:11434/
     - claude: https://api.anthropic.com/v1
+    - gemini: no api_url
  - Note: To run local Ollama, follow the guidelines here: [Guide to Ollama deployment](https://github.com/ollama/ollama)
   
 ### 3. plain_text_resume.yaml

requirements.txt

@@ -17,6 +17,7 @@ pdfminer.six==20221105
 inputimeout==1.0.4
 langchain-ollama==0.1.3
 langchain-anthropic==0.1.3
+langchain-google-genai==1.0.10
 jsonschema==4.23.0
 jsonschema-specifications==2023.12.1
 httpx~=0.27.2

src/gpt.py

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