Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -3,21 +3,18 @@ from langchain.llms import Replicate
|
|
3 |
from langchain.vectorstores import Pinecone
|
4 |
from langchain.text_splitter import CharacterTextSplitter
|
5 |
from langchain.document_loaders import PyPDFLoader
|
|
|
|
|
6 |
from langchain.embeddings import HuggingFaceEmbeddings
|
7 |
from langchain.chains import ConversationalRetrievalChain
|
8 |
from datasets import load_dataset
|
9 |
import os
|
10 |
-
import pinecone
|
11 |
|
12 |
|
13 |
key = os.environ.get('API')
|
14 |
-
yeh = os.environ.get('pineapi')
|
15 |
os.environ["REPLICATE_API_TOKEN"] = key
|
16 |
-
pinecone.init(api_key=yeh, environment='gcp-starter')
|
17 |
-
|
18 |
|
19 |
import sentence_transformers
|
20 |
-
import faiss
|
21 |
|
22 |
def loading_pdf():
|
23 |
return "Loading..."
|
@@ -31,9 +28,8 @@ def pdf_changes(pdf_doc):
|
|
31 |
|
32 |
embeddings = HuggingFaceEmbeddings()
|
33 |
|
34 |
-
|
35 |
-
|
36 |
-
vectordb = Pinecone.from_documents(texts, embeddings, index_name=index_name)
|
37 |
|
38 |
llm = Replicate(
|
39 |
model="a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5",
|
@@ -42,7 +38,7 @@ def pdf_changes(pdf_doc):
|
|
42 |
global qa
|
43 |
qa = ConversationalRetrievalChain.from_llm(
|
44 |
llm,
|
45 |
-
|
46 |
return_source_documents=True
|
47 |
)
|
48 |
return "Ready"
|
|
|
3 |
from langchain.vectorstores import Pinecone
|
4 |
from langchain.text_splitter import CharacterTextSplitter
|
5 |
from langchain.document_loaders import PyPDFLoader
|
6 |
+
from langchain.llms import HuggingFaceHub
|
7 |
+
from langchain.vectorstores import Chroma
|
8 |
from langchain.embeddings import HuggingFaceEmbeddings
|
9 |
from langchain.chains import ConversationalRetrievalChain
|
10 |
from datasets import load_dataset
|
11 |
import os
|
|
|
12 |
|
13 |
|
14 |
key = os.environ.get('API')
|
|
|
15 |
os.environ["REPLICATE_API_TOKEN"] = key
|
|
|
|
|
16 |
|
17 |
import sentence_transformers
|
|
|
18 |
|
19 |
def loading_pdf():
|
20 |
return "Loading..."
|
|
|
28 |
|
29 |
embeddings = HuggingFaceEmbeddings()
|
30 |
|
31 |
+
db = Chroma.from_documents(texts, embeddings)
|
32 |
+
retriever = db.as_retriever(search_kwargs={'k': 2})
|
|
|
33 |
|
34 |
llm = Replicate(
|
35 |
model="a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5",
|
|
|
38 |
global qa
|
39 |
qa = ConversationalRetrievalChain.from_llm(
|
40 |
llm,
|
41 |
+
retriever,
|
42 |
return_source_documents=True
|
43 |
)
|
44 |
return "Ready"
|