app

app.py

@@ -9,27 +9,23 @@ from langchain.embeddings import HuggingFaceInferenceAPIEmbeddings
 
 
 
-load_dotenv()
+# load_dotenv()
 
 
-# APIS
-OPENAI_API_KEY=os.getenv("OPENAI_API_KEY")
-PINECONE_API_KEY=os.getenv("PINECONE_API_KEY")
-PINECONE_ENV=os.getenv("PINECONE_ENV")
-PINECONE_INDEX=os.getenv("PINECONE_INDEX")
-TEXT_EMBEDDING_MODEL=os.getenv("TEXT_EMBEDDING_MODEL")
-HF_MODEL=os.getenv("HF_MODEL")
-HF_API=os.getenv("HF_API")
+# # APIS
+# OPENAI_API_KEY=os.getenv("OPENAI_API_KEY")
+# PINECONE_API_KEY=os.getenv("PINECONE_API_KEY")
+# HF_API=os.getenv("HF_API")
 
 
 def model(query):
     pinecone.init(
     api_key=PINECONE_API_KEY,  # find at app.pinecone.io
-    environment=PINECONE_ENV,  # next to api key in console
+    environment='gcp-starter',  # next to api key in console
     )
 
-    embeddings = HuggingFaceInferenceAPIEmbeddings(api_key=HF_API ,model_name=HF_MODEL)
-    vectorstore = Pinecone.from_existing_index(PINECONE_INDEX, embeddings)
+    embeddings = HuggingFaceInferenceAPIEmbeddings(api_key=HF_API ,model_name="llmrails/ember-v1")
+    vectorstore = Pinecone.from_existing_index('legal-gpt', embeddings)
 
     docs = vectorstore.similarity_search(query,k=5)