Spaces:

agency888
/

TaoGPT

Sleeping

App Files Files Community

AdithyaSK commited on Nov 9, 2023

Commit

5e36bda

1 Parent(s): 1bd57df

added application - Adithya S K

Browse files

Files changed (4) hide show

TaoGPT-embeddings/put_your_embeddings_here +0 -0
app.py +153 -0
requirements.txt +13 -0
style.css +16 -0

TaoGPT-embeddings/put_your_embeddings_here ADDED Viewed

File without changes

app.py ADDED Viewed

	@@ -0,0 +1,153 @@

+from huggingface_hub import InferenceClient
+import gradio as gr
+from langchain.embeddings import HuggingFaceEmbeddings
+from langchain.vectorstores import FAISS
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
+vector_store = FAISS.load_local("TaoGPT-Embeddings", embeddings)
+client = InferenceClient(
+    "mistralai/Mistral-7B-Instruct-v0.1"
+)
+NOMIC = """
+<!DOCTYPE html>
+<html>
+  <head>
+    <title>TaoGPT - DataMap</title>
+    <style>
+      iframe {
+        width: 100%;
+        height: 600px; /* You can adjust the height as needed */
+        border: 0;
+      }
+    </style>
+  </head>
+  <body>
+    <iframe
+      src="https://atlas.nomic.ai/map/a59e104a-e4d0-4701-bbd9-3d552aae92a2/a3a2aacd-0787-4389-863a-ab3670015367?xs=-41.70341&xf=41.36850&ys=-23.57587&yf=23.20673"
+    ></iframe>
+  </body>
+</html>
+"""
+RAG = True
+def format_prompt(message, history):
+    global RAG
+    if RAG == True:
+        results = vector_store.similarity_search(message ,k=3)
+        context = [result.page_content for result in results]
+        context = "\n\n".join(context)
+        print(context)
+        prompt = "<s>"
+        for user_prompt, bot_response in history:
+            prompt += f"[INST] {user_prompt} [/INST]"
+            prompt += f" {bot_response}</s> "
+        prompt += f"[INST]Given the following Information:\n{context} \n answer the following question {message} [/INST]"
+        return prompt
+    else:
+        prompt = "<s>"
+        for user_prompt, bot_response in history:
+            prompt += f"[INST] {user_prompt} [/INST]"
+            prompt += f" {bot_response}</s> "
+        prompt += f"[INST] {message} [/INST]"
+        return prompt
+def generate(
+    prompt, history, temperature=0.9, max_new_tokens=256, top_p=0.95, repetition_penalty=1.0,
+):
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+    generate_kwargs = dict(
+        temperature=temperature,
+        max_new_tokens=max_new_tokens,
+        top_p=top_p,
+        repetition_penalty=repetition_penalty,
+        do_sample=True,
+        seed=42,
+    )
+    formatted_prompt = format_prompt(prompt, history)
+    stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False)
+    output = ""
+    for response in stream:
+        output += response.token.text
+        yield output
+    return output
+additional_inputs=[
+    gr.Slider(
+        label="Temperature",
+        value=0.9,
+        minimum=0.0,
+        maximum=1.0,
+        step=0.05,
+        interactive=True,
+        info="Higher values produce more diverse outputs",
+    ),
+    gr.Slider(
+        label="Max new tokens",
+        value=256,
+        minimum=0,
+        maximum=1048,
+        step=64,
+        interactive=True,
+        info="The maximum numbers of new tokens",
+    ),
+    gr.Slider(
+        label="Top-p (nucleus sampling)",
+        value=0.90,
+        minimum=0.0,
+        maximum=1,
+        step=0.05,
+        interactive=True,
+        info="Higher values sample more low-probability tokens",
+    ),
+    gr.Slider(
+        label="Repetition penalty",
+        value=1.2,
+        minimum=1.0,
+        maximum=2.0,
+        step=0.05,
+        interactive=True,
+        info="Penalize repeated tokens",
+    )
+]
+css = """
+  #mkd {
+    height: 500px;
+    overflow: auto;
+    border: 1px solid #ccc;
+  }
+"""
+with gr.Blocks(css=css) as demo:
+    # gr.HTML("<h1><center>Mistral 7B Instruct<h1><center>")
+    # gr.HTML("<h3><center>In this demo, you can chat with <a href='https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1'>Mistral-7B-Instruct</a> model. 💬<h3><center>")
+    # gr.HTML("<h3><center>Learn more about the model <a href='https://huggingface.co/docs/transformers/main/model_doc/mistral'>here</a>. 📚<h3><center>")
+    gr.HTML("<h1><center>TaoGPT<center></h1>")
+    gr.HTML("<h3><center>TaoGPT is Fine-tuned Mistal-7B model on TaoScience related Information Check out- <a href='https://github.com/agencyxr/taogpt7B'>Github Repo</a> For More Information. 💬<h3><center>")
+    with gr.Row():
+        with gr.Column():
+            gr.HTML("<h3>Chat with TaoGPT</h3>")
+            gr.ChatInterface(
+                generate,
+                additional_inputs=additional_inputs,
+                examples=[["What is TaoScience"], ["Give me a Summary about TaoScience"]]
+            )
+            RAG_Checkbox = gr.Checkbox(label="Use Retrival Augmented Generation" , value=True , interactive=False)
+        with gr.Column():
+            gr.HTML("<h3>Look into the Dataset we used to Finetune our Model</h3>")
+            gr.HTML(NOMIC)
+demo.queue(concurrency_count=75, max_size=100).launch(debug=True)

requirements.txt ADDED Viewed

	@@ -0,0 +1,13 @@

+langchain
+# faiss-gpu
+faiss-cpu
+torch==2.0.0
+accelerate==0.23.0
+bitsandbytes==0.41.1
+gradio==3.48.0
+protobuf==3.20.3
+scipy==1.11.2
+sentencepiece==0.1.99
+spaces==0.16.1
+transformers==4.34.0
+sentence-transformers

style.css ADDED Viewed

	@@ -0,0 +1,16 @@

+h1 {
+  text-align: center;
+}
+#duplicate-button {
+  margin: auto;
+  color: white;
+  background: #1565c0;
+  border-radius: 100vh;
+}
+.contain {
+  max-width: 900px;
+  margin: auto;
+  padding-top: 1.5rem;
+}