add custom langchain wrappers

.gitignore

@@ -1 +1,2 @@
 __pycache__/
+*.env

aimakerspace/langchain_wrappers/langchain_chat_models.py

@@ -0,0 +1,50 @@
+import os
+from dotenv import load_dotenv
+from typing import Optional
+from langchain_openai import ChatOpenAI
+import inspect
+
+load_dotenv(os.path.join(os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) , '.env'))
+
+class MyChatOpenAI:
+    @classmethod
+    def from_model(
+        cls, 
+        model: str = 'gpt-4o-mini',
+        *,
+        langsmith_project: str = 'default',
+        temperature: float = 0.7,
+        max_tokens: Optional[int] = 4096,
+        max_retries: int = 1,
+        **kwargs
+        )-> ChatOpenAI:
+        
+        os.environ['LANGCHAIN_PROJECT'] = langsmith_project
+        if model in ['gpt-4o', 'GPT-4o', 'GPT-4O', 'gpt-4O', 'gpt4o', 'GPT4o', 'GPT4O', 'gpt4O']:
+            model = 'gpt-4o'
+        elif model in ['gpt-4o-mini', 'GPT-4o-mini', 'GPT-4O-mini', 'gpt-4O-mini', 'gpt4o-mini', 'GPT4o-mini', 'GPT4O-mini', 'gpt4O-mini', 'gpt4omini', 'GPT4omini', 'GPT4Omini', 'gpt4Omini']:
+            model = 'gpt-4o-mini'
+        else:
+            raise ValueError(f"Model {model} is currently not supported. Supported models are: ['gpt-4o', 'gpt-4o-mini']")
+
+        
+        return ChatOpenAI(
+            openai_api_key=os.getenv("OPENAI_API_KEY"), 
+            model=model,
+            temperature=temperature,
+            max_tokens=max_tokens,
+            max_retries=max_retries,
+            **kwargs
+            )
+
+
+    @classmethod
+    def get_model_price(cls)-> dict:
+        # Dictionary to store the cost of input and output tokens for each model
+        supported_models = {'gpt-4o' : (5, 15)}  # gpt-4o model: input cost = $5 per 1M tokens, output cost = $15 per 1M tokens
+        supported_models.update({'gpt-4o-mini' : (0.15, 0.6)})  # gpt-4o-mini model: input cost = $0.15 per 1M tokens, output cost = $0.6 per 1M tokens
+
+        return supported_models
+
+
+

aimakerspace/langchain_wrappers/langchain_embedding_models.py

@@ -0,0 +1,48 @@
+import os
+from dotenv import load_dotenv
+from typing import Optional
+from langchain_openai.embeddings import OpenAIEmbeddings
+import inspect
+
+load_dotenv(os.path.join(os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) , '.env'))
+
+class MyOpenAIEmbeddings:
+    @classmethod
+    def from_model(
+        cls, 
+        model: str = 'small',
+        *,
+        dimensions: Optional[int] = None,
+        max_retries: int = 1,
+        **kwargs
+        )-> OpenAIEmbeddings:
+        
+        if model in ['text-embedding-3-small', 'TEXT-EMBEDDING-3-SMALL', 'small', 'SMALL']:
+            model = 'text-embedding-3-small'
+            dimensions = 1536 if dimensions is None else dimensions
+        elif model in ['text-embedding-3-large', 'TEXT-EMBEDDING-3-LARGE', 'large', 'LARGE']:
+            model = 'text-embedding-3-large'
+            dimensions = 3072 if dimensions is None else dimensions
+        else:
+            raise ValueError(f"Model {model} is currently not supported. Supported models are: ['text-embedding-3-small', 'text-embedding-3-large']")
+
+        
+        return OpenAIEmbeddings(
+            openai_api_key=os.getenv("OPENAI_API_KEY"), 
+            model=model,
+            dimensions=dimensions,
+            max_retries=max_retries,
+            **kwargs
+            )
+
+
+    @classmethod
+    def get_model_price(cls)-> dict:
+        # Dictionary to store the cost of input and output tokens for each model
+        supported_models = {'text-embedding-3-small' : 0.02}  # text-embedding-3-small model: $0.02 per 1M tokens
+        supported_models.update({'text-embedding-3-large' : 0.13})  # text-embedding-3-large model: $0.13 per 1M tokens
+
+        return supported_models
+
+
+