Update app.py

app.py

@@ -19,7 +19,8 @@ from langchain.document_loaders import UnstructuredPowerPointLoader
 # from langchain.document_loaders.image import UnstructuredImageLoader
 
 
-
+from langchain.chains.question_answering import load_qa_chain
+from langchain import OpenAI
 
 from sentence_transformers import SentenceTransformer, models, util
 word_embedding_model = models.Transformer('sentence-transformers/all-MiniLM-L6-v2', do_lower_case=True)
@@ -28,6 +29,7 @@ embedder = SentenceTransformer(modules=[word_embedding_model, pooling_model])
 ocr = CnOcr()
 # chat_url = 'https://Raghav001-API.hf.space/sale'
 chat_url = 'https://Raghav001-API.hf.space/chatpdf'
+chat_emd = 'https://Raghav001-API.hf.space/embedd'
 headers = {
     'Content-Type': 'application/json',
 }
@@ -254,8 +256,13 @@ def pine(data):
         c = c+1
 
 
-    Embedding_model = "text-embedding-ada-002"
-    embeddings = OpenAIEmbeddings(openai_api_key="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")
+    # Embedding_model = "text-embedding-ada-002"
+    # embeddings = OpenAIEmbeddings(openai_api_key="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")
+
+    embeddings = requests.post(url=chat_emd,
+                           data=json.dumps(data),
+                           headers=headers
+                           )
 
     pinecone.init(api_key = "ffb1f594-0915-4ebf-835f-c1eaa62fdcdc",
               environment = "us-west4-gcp-free"
@@ -266,7 +273,13 @@ def pine(data):
 
     return ''
 
-
+def get_answer(query_live):
+    
+    llm = OpenAI(temperature=0, openai)
+    qa_chain = load_qa_chain(llm,chain_type='stuff')
+    query = query_live
+    docs = docstore.similarity_search(query)
+    qa_chain.run(input_documents = docs, question = query)
 
 with gr.Blocks() as demo:
     with gr.Row():