changed model

app/embedding/embeder.py

@@ -11,12 +11,12 @@ def get_query_embedding(query_spec: QuerySpec, embedding_model):
     q = query_spec.raw_query
     e_main =  embedding_model.embed_query(q)
     expansions = []
-    if "procedure" in query_spec.entities:
-        procedure_value = query_spec.entities['procedure']
-        # Handle both string and list values
-        if isinstance(procedure_value, list):
-            procedure_str = ", ".join(procedure_value)
-        else:
-            procedure_str = procedure_value
-        expansions.append(f"{q} OR {procedure_str} procedures related")
+    # if "procedure" in query_spec.entities:
+    #     procedure_value = query_spec.entities['procedure']
+    #     # Handle both string and list values
+    #     if isinstance(procedure_value, list):
+    #         procedure_str = ", ".join(procedure_value)
+    #     else:
+    #         procedure_str = procedure_value
+    #     expansions.append(f"{q} OR {procedure_str} procedures related")
     return e_main,expansions

app/schemas/request_models.py

@@ -4,8 +4,10 @@ import json
 class QuerySpec(BaseModel):
     raw_query: str
     intent: str
-    entities: Dict[str, Union[str, List[str]]]
-    constraints : Dict[str, Any]
+    # entities: Dict[str, Union[str, List[str]]]
+    # constraints : Dict[str, Any]
+    entities: Optional[Any] = None
+    constraints: Optional[Any] = None
     answer_type: str
     followups: Optional[List[str]] = []
 

app/utils/model_loader.py

@@ -9,6 +9,7 @@ from langchain_google_genai import ChatGoogleGenerativeAI
 from dotenv import load_dotenv
 # from langchain_openai import OpenAIEmbeddings
 from langchain_community.embeddings import OpenAIEmbeddings
+from langchain_openai import ChatOpenAI 
 class ConfigLoader:
     def __init__(self):
         print(f"Loading config....")
@@ -42,12 +43,16 @@ class ModelLoader(BaseModel):
         elif self.model_provider =="gemini":
             print("Loading model from gemini:")
             load_dotenv()
-            gemini_api_key = os.getenv("GEMINI_API_KEY")
-            model_name = self.config["llm"]["gemini"]["model_name"]
-            llm = ChatGoogleGenerativeAI(
-                model=model_name,
-                google_api_key= gemini_api_key
-            )
+            # gemini_api_key = os.getenv("GEMINI_API_KEY")
+            # model_name = self.config["llm"]["gemini"]["model_name"]
+            # llm = ChatGoogleGenerativeAI(
+            #     model=model_name,
+            #     google_api_key= gemini_api_key
+            # )
+            openai_api_key = os.getenv("OPENAI_API_KEY")
+            llm = ChatOpenAI(model="gpt-4o-mini",api_key=openai_api_key )
+
+
         elif self.model_provider =="openai":
             load_dotenv()
             print("Loading model from openai:")