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app.py

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+import gradio as gr
+from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
+from langchain.chains import RetrievalQA
+from langchain.embeddings import LlamaCppEmbeddings
+from langchain.llms import GPT4All, LlamaCpp
+from langchain.vectorstores import Chroma
+from dotenv import load_dotenv
+import os
+from langchain.embeddings import HuggingFaceEmbeddings
+load_dotenv()
+from constants import CHROMA_SETTINGS
+import openai
+#from langchain_community.embeddings import HuggingFaceInferenceAPIEmbeddings
+
+from gptcall import generate
+#from yy_main import return_qa
+# Set your OpenAI API key
+api_key = os.environ.get('OPEN_AI_KEY')  # Replace with your actual API key
+openai.api_key = api_key
+'''
+def ask_gpt3(question):
+    response = openai.Completion.create(
+        engine="gpt-3.5-turbo",
+        prompt=question,
+        max_tokens=50
+    )
+    return response.choices[0].text.strip()
+
+def generate(prompt):
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": prompt}
+            ],
+            max_tokens=1000,
+            temperature=0.9
+        )
+        return response['choices'][0]['message']['content']
+    except Exception as e:
+        return str(e)
+'''
+hf = os.environ.get("HF_TOKEN")
+embeddings_model_name = os.environ.get("EMBEDDINGS_MODEL_NAME")
+persist_directory = os.environ.get('PERSIST_DIRECTORY')
+
+model_type = os.environ.get('MODEL_TYPE')
+model_path = os.environ.get('MODEL_PATH')
+model_n_ctx = os.environ.get('MODEL_N_CTX')
+target_source_chunks = int(os.environ.get('TARGET_SOURCE_CHUNKS',4))
+server_error_msg = "**NETWORK ERROR DUE TO HIGH TRAFFIC. PLEASE REGENERATE OR REFRESH THIS PAGE.**"
+
+def clear_history(request: gr.Request):
+    state = None
+    return ([], state, "")
+
+def post_process_code(code):
+    sep = "\n```"
+    if sep in code:
+        blocks = code.split(sep)
+        if len(blocks) % 2 == 1:
+            for i in range(1, len(blocks), 2):
+                blocks[i] = blocks[i].replace("\\_", "_")
+        code = sep.join(blocks)
+    return code
+
+def post_process_answer(answer):
+    answer += f"<br><br>"
+    answer = answer.replace("\n", "<br>")
+    return answer
+
+def predict(
+    question: str,
+    system_content: str,
+    use_api: bool,
+    chatbot: list = [],
+    history: list = [],
+):
+    try:
+        if use_api:  # Check if API call is requested
+            history.append(question)
+            answer = generate(question)
+            history.append(answer)
+        else:
+            model_n_ctx = 2048
+            print(" print state in order", system_content, persist_directory, model_type, model_path, model_n_ctx, chatbot, history)
+            print("going inside embedding dunction",embeddings_model_name)
+            embeddings = HuggingFaceEmbeddings(model_name=embeddings_model_name)
+            
+            #embeddings = HuggingFaceInferenceAPIEmbeddings(api_key=hf, model_name="sentence-transformers/all-MiniLM-l6-v2")
+            db = Chroma(persist_directory=persist_directory, embedding_function=embeddings, client_settings=CHROMA_SETTINGS)
+            retriever = db.as_retriever(search_kwargs={"k": target_source_chunks})
+            # Prepare the LLM
+            callbacks = [StreamingStdOutCallbackHandler()]
+            
+            if model_type == "LlamaCpp":
+                llm = LlamaCpp(model_path=model_path, n_ctx=model_n_ctx, n_threads=6, n_gpu_layers=12, callbacks=callbacks, verbose=False)
+            elif model_type == "GPT4All":
+                llm = GPT4All(model=model_path, n_ctx=2048, backend='gptj', callbacks=callbacks, n_batch=8, verbose=False)
+            else:
+                print(f"Model {model_type} not supported!")
+                exit()
+            
+            qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=False)
+            
+            # Get the answer from the chain
+            prompt = system_content + f"\n Question: {question}"
+            res = qa(prompt)    
+            print(res)
+            answer = res['result']
+            answer = post_process_answer(answer)
+            history.append(question)
+            history.append(answer)
+        
+        # Ensure history has an even number of elements
+        if len(history) % 2 != 0:
+            history.append("")
+
+        chatbot = [(history[i], history[i + 1]) for i in range(0, len(history), 2)]
+        return chatbot, history 
+    
+    except Exception as e:
+        history.append("")
+        answer = server_error_msg + f" (error_code: 503)"
+        history.append(answer)
+        
+        # Ensure history has an even number of elements
+        if len(history) % 2 != 0:
+            history.append("")
+
+        chatbot = [(history[i], history[i + 1]) for i in range(0, len(history), 2)]
+        return chatbot, history
+
+            
+
+def reset_textbox():    return gr.update(value="")
+
+llama_embeddings_model = "models/ggml-model-q4_0.bin"
+
+def main():
+    title = """
+<h1 align="center">Chat with TxGpt 🤖</h1>"""
+
+    css = """
+@import url('https://fonts.googleapis.com/css2?family=Poppins:wght@400;700&display=swap');
+
+/* Hide the footer */
+footer .svelte-1lyswbr { 
+    display: none !important; 
+}
+
+/* Center the column container */
+#prompt_container { 
+    margin-left: auto; 
+    margin-right: auto;
+    background: linear-gradient(to right, #48c6ef, #6f86d6); /* Gradient background */
+    padding: 20px; /* Decreased padding */
+    border-radius: 10px;
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+    color: black;
+    font-family: 'Poppins', sans-serif; /* Poppins font */
+    font-weight: 600; /* Bold font */
+    resize: none;
+    font-size: 18px;
+}
+
+/* Chatbot container styling */
+#chatbot_container { 
+    margin: 0 auto; /* Remove left and right margins */
+    max-width: 80%; /* Adjust the maximum width as needed */
+    background: linear-gradient(to right, #ff7e5f, #feb47b); /* Gradient background */
+    padding: 20px;
+    border-radius: 10px;
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+}
+
+/* Chatbot message area styling */
+#chatbot .wrap.svelte-13f7djk { 
+    height: 60vh; /* Adjusted height */
+    max-height: 60vh; /* Adjusted height */
+    border: 2px solid #007bff;
+    border-radius: 10px;
+    overflow-y: auto;
+    padding: 20px;
+    background-color: #e9f5ff;
+}
+
+/* User message styling */
+#chatbot .message.user.svelte-13f7djk.svelte-13f7djk { 
+    width: fit-content; 
+    background: #007bff; 
+    color: white;
+    border-bottom-right-radius: 0;
+    border-top-left-radius: 10px;
+    border-top-right-radius: 10px;
+    border-bottom-left-radius: 10px;
+    margin-bottom: 10px;
+    padding: 10px 15px;
+    font-size: 14px;
+    font-family: 'Poppins', sans-serif; /* Poppins font */
+    font-weight: 700; /* Bold font */
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
+}
+
+/* Bot message styling */
+#chatbot .message.bot.svelte-13f7djk.svelte-13f7djk { 
+    width: fit-content; 
+    background: #e1e1e1; 
+    color: black;
+    border-bottom-left-radius: 0;
+    border-top-right-radius: 10px;
+    border-top-left-radius: 10px;
+    border-bottom-right-radius: 10px;
+    margin-bottom: 10px;
+    padding: 10px 15px;
+    font-size: 14px;
+    font-family: 'Poppins', sans-serif; /* Poppins font */
+    font-weight: 700; /* Bold font */
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.2);
+}
+
+/* Preformatted text styling */
+#chatbot .pre { 
+    border: 2px solid #f1f1f1;
+    padding: 10px;
+    border-radius: 5px;
+    background-color: #ffffff;
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.05);
+    font-family: 'Poppins', sans-serif; /* Poppins font */
+    font-size: 14px;
+    font-weight: 400; /* Regular font */
+}
+
+/* General preformatted text styling */
+pre {
+    white-space: pre-wrap;       /* Since CSS 2.1 */
+    white-space: -moz-pre-wrap;  /* Mozilla, since 1999 */
+    white-space: -pre-wrap;      /* Opera 4-6 */
+    white-space: -o-pre-wrap;    /* Opera 7 */
+    word-wrap: break-word;       /* Internet Explorer 5.5+ */
+    font-family: 'Poppins', sans-serif; /* Poppins font */
+    font-size: 14px;
+    font-weight: 400; /* Regular font */
+    line-height: 1.5;
+    color: #333;
+    background-color: #f8f9fa;
+    padding: 10px;
+    border-radius: 5px;
+}
+
+/* Styling for accordion sections */
+.accordion.svelte-1lyswbr {
+    background-color: #e9f5ff; /* Light blue background for accordions */
+    border: 1px solid #007bff;
+    border-radius: 10px;
+    padding: 10px;
+    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
+    resize: both;
+}
+
+/* Prompt styling */
+#prompt_title {
+    font-size: 24px;
+    margin-bottom: 10px;
+    resize= none;
+}
+
+/* Styling for Copy button */
+.copy_button {
+    display: inline-block;
+    padding: 5px 10px;
+    margin: 5px 0;
+    font-size: 14px;
+    cursor: pointer;
+    color: #007bff;
+    border: 1px solid #007bff;
+    border-radius: 5px;
+    background-color: #ffffff;
+    transition: background-color 0.3s;
+}
+
+.copy_button:hover {
+    background-color: #007bff;
+    color: #ffffff;
+}
+"""
+    with gr.Blocks(css=css) as demo:
+        gr.HTML(title)
+        with gr.Row():
+            with gr.Column(elem_id="prompt_container", scale=0.3):  # Separate column for prompt
+                with gr.Accordion("Description", open=True):
+                    system_content = gr.Textbox(value="TxGpt talk to your local documents without internet. If you need information on public data, please enable the ChatGpt checkbox and start querying!",show_label=False,lines=5)
+                    
+            with gr.Column(elem_id="chatbot_container", scale=0.7):  # Right column for chatbot interface
+                chatbot = gr.Chatbot(elem_id="chatbot", label="TxGpt")
+                question = gr.Textbox(placeholder="Ask something", show_label=False, value="")
+                state = gr.State([])
+                use_api_toggle = gr.Checkbox(label="Enable ChatGpt", default=False, key="use_api")
+                with gr.Row():
+                    with gr.Column():
+                        submit_btn = gr.Button(value="🚀 Send")
+                    with gr.Column():
+                        clear_btn = gr.Button(value="🗑️ Clear history")
+                
+        question.submit(
+            predict,
+            [question, system_content, use_api_toggle, chatbot, state],
+            [chatbot, state],
+        )
+        submit_btn.click(
+            predict,
+            [question, system_content, chatbot, state],
+            [chatbot, state],
+        )
+        submit_btn.click(reset_textbox, [], [question])
+        clear_btn.click(clear_history, None, [chatbot, state, question])
+        question.submit(reset_textbox, [], [question])
+        demo.queue(concurrency_count=10, status_update_rate="auto")
+        #demo.launch(server_name=args.server_name, server_port=args.server_port, share=args.share, debug=args.debug)
+        demo.launch(share=True, server_name='192.168.6.78')
+
+if __name__ == '__main__':
+    """ import argparse
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--server-name", default="0.0.0.0")
+    parser.add_argument("--server-port", default=8071)
+    parser.add_argument("--share", action="store_true")
+    parser.add_argument("--debug", action="store_true")
+    parser.add_argument("--verbose", action="store_true")
+    args = parser.parse_args() """
+    
+    main()

db/chroma-collections.parquet

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db/chroma-embeddings.parquet

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db/index/id_to_uuid_b87fed10-6865-4f48-a7d0-62a535bc5ee3.pkl

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db/index/index_b87fed10-6865-4f48-a7d0-62a535bc5ee3.bin

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db/index/index_metadata_b87fed10-6865-4f48-a7d0-62a535bc5ee3.pkl

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db/index/uuid_to_id_b87fed10-6865-4f48-a7d0-62a535bc5ee3.pkl

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+size 3346

env

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+OPEN_AI_KEY=sk-proj-yZH391O3W6Xk5hVL5xxOT3BlbkFJkpcqeUYhTy8yrUwB0LXl

gptcall.py

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+import requests
+import json
+from aaa
+import openai
+import configparser
+from dotenv import load_dotenv
+load_dotenv()
+import os
+# Load configuration
+config = configparser.ConfigParser()
+config.read('test.env')
+API_KEY = config.get('API', 'OPEN_AI_KEY')
+API_URL = config.get('API', 'OPEN_AI_URL')
+# print(API_URL,API_KEY)
+# Set the OpenAI API key
+openai.api_key = API_KEY
+
+def generate(prompt):
+    # print(API_URL,API_KEY)
+
+    try:
+        response = openai.ChatCompletion.create(
+            model="gpt-4-turbo",
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": prompt}
+            ],
+            max_tokens=2000,
+            temperature=0.9
+        )
+        return response['choices'][0]['message']['content']
+    except Exception as e:
+        return str(e)

models/koala-7B.ggmlv3.q4_K_S.bin

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+oid sha256:60621334d6f3907047c82e2bd4b72955a67a902c1edd0f6dce96cabc7bf10743
+size 3791725184

requirements.txt

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+openai==0.28
+configparser
+gradio
+spaces
+python-dotenv

test.env

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+[API]
+OPEN_AI_KEY=sk-proj-yZH391O3W6Xk5hVL5xxOT3BlbkFJkpcqeUYhTy8yrUwB0LXl
+OPEN_AI_URL=https://api.openai.com/v1/completions