🎉 initial commit

README.md

@@ -1,6 +1,6 @@
 ---
-title: Langchain Pdf Qa
-emoji: 🦀
+title: Langchain PFF QA
+emoji: 📁
 colorFrom: blue
 colorTo: red
 sdk: gradio

app.py

@@ -0,0 +1,49 @@
+import gradio as gr
+from langchain.document_loaders import PyPDFLoader
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.chat_models import ChatOpenAI
+from langchain.chains import RetrievalQA
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain.vectorstores import Chroma
+
+embeddings = HuggingFaceEmbeddings()
+text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+
+def chat(openai_key,message, history,file):
+    history = history or []
+
+    loader = PyPDFLoader(file.name)
+    documents = loader.load()
+
+    texts = text_splitter.split_documents(documents)
+    vectordb = Chroma.from_documents(texts, embeddings)
+    
+    qa = RetrievalQA.from_chain_type(llm=ChatOpenAI(temperature=0,model_name="gpt-3.5-turbo",openai_api_key=openai_key), chain_type="stuff", retriever=vectordb.as_retriever())
+    answer = qa.run(message)
+
+    history.append((message, answer))
+
+    return history, history
+    
+    
+inputs = [
+    gr.Textbox(lines=1, label="OpenAI API Key",placeholder="openai api here...", type="password"),
+    gr.Textbox(lines=2,label="prompt"),
+    gr.State([]),
+    gr.File(label="PDF File")
+]
+
+outputs = [
+    gr.Chatbot(label="Chatbot"),
+    gr.State([])
+]
+
+app = gr.Interface(
+    fn=chat,
+    inputs=inputs,
+    outputs=outputs,
+    allow_flagging='never',
+)
+
+if __name__ == '__main__':
+    app.launch()

requirements.txt

@@ -0,0 +1,7 @@
+langchain==0.0.235
+openai==0.27.8
+transformers==4.25.1
+sentence-transformers==2.2.2
+pypdf==3.12.2
+pycryptodome==3.18.0
+chromadb==0.4.0