Spaces:
Running
Running
Abid Ali Awan
commited on
Commit
·
c84dd0f
1
Parent(s):
00e0504
trigger_mode="always_last" added
Browse files
app.py
CHANGED
@@ -14,9 +14,8 @@ groq_api_key = os.getenv("Groq_API_Key")
|
|
14 |
llm = ChatGroq(model="llama-3.1-70b-versatile", api_key=groq_api_key)
|
15 |
|
16 |
# Initialize the embedding model
|
17 |
-
embed_model = HuggingFaceEmbeddings(
|
18 |
-
|
19 |
-
)
|
20 |
|
21 |
# Load the vector store from a local directory
|
22 |
vectorstore = Chroma(
|
@@ -49,28 +48,13 @@ rag_chain = (
|
|
49 |
| StrOutputParser()
|
50 |
)
|
51 |
|
52 |
-
|
53 |
# Define the function to stream the RAG memory
|
54 |
-
def rag_memory_stream(text
|
55 |
-
if change_tracker.get("changed", False):
|
56 |
-
return # Stop the generation if input has changed
|
57 |
-
|
58 |
partial_text = ""
|
59 |
for new_text in rag_chain.stream(text):
|
60 |
-
if change_tracker.get("changed", False):
|
61 |
-
return # Stop the generation if input has changed
|
62 |
partial_text += new_text
|
63 |
-
|
64 |
-
|
65 |
-
|
66 |
-
def input_listener(text, change_tracker):
|
67 |
-
change_tracker["changed"] = True
|
68 |
-
change_tracker["changed"] = False
|
69 |
-
return text
|
70 |
-
|
71 |
-
|
72 |
-
# Initialize a change tracker
|
73 |
-
change_tracker = {"changed": False}
|
74 |
|
75 |
# Set up the Gradio interface
|
76 |
title = "Real-time AI App with Groq API and LangChain"
|
@@ -80,21 +64,11 @@ description = """
|
|
80 |
</center>
|
81 |
"""
|
82 |
|
83 |
-
# Define input components with event listeners
|
84 |
-
text_input = gr.Textbox(label="Enter your question", elem_id="question")
|
85 |
-
text_input.change(
|
86 |
-
fn=input_listener,
|
87 |
-
inputs=[text_input],
|
88 |
-
outputs=[text_input],
|
89 |
-
change_tracker=change_tracker,
|
90 |
-
)
|
91 |
-
|
92 |
-
# Create the Gradio interface
|
93 |
demo = gr.Interface(
|
94 |
title=title,
|
95 |
description=description,
|
96 |
-
fn=
|
97 |
-
inputs=
|
98 |
outputs="text",
|
99 |
live=True,
|
100 |
batch=True,
|
@@ -102,8 +76,9 @@ demo = gr.Interface(
|
|
102 |
concurrency_limit=12,
|
103 |
allow_flagging="never",
|
104 |
theme=gr.themes.Soft(),
|
|
|
105 |
)
|
106 |
|
107 |
# Launch the Gradio interface
|
108 |
demo.queue()
|
109 |
-
demo.launch()
|
|
|
14 |
llm = ChatGroq(model="llama-3.1-70b-versatile", api_key=groq_api_key)
|
15 |
|
16 |
# Initialize the embedding model
|
17 |
+
embed_model = HuggingFaceEmbeddings(model_name="mixedbread-ai/mxbai-embed-large-v1",
|
18 |
+
model_kwargs = {'device': 'cpu'})
|
|
|
19 |
|
20 |
# Load the vector store from a local directory
|
21 |
vectorstore = Chroma(
|
|
|
48 |
| StrOutputParser()
|
49 |
)
|
50 |
|
|
|
51 |
# Define the function to stream the RAG memory
|
52 |
+
def rag_memory_stream(text):
|
|
|
|
|
|
|
53 |
partial_text = ""
|
54 |
for new_text in rag_chain.stream(text):
|
|
|
|
|
55 |
partial_text += new_text
|
56 |
+
# Yield the updated conversation history
|
57 |
+
yield partial_text
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
58 |
|
59 |
# Set up the Gradio interface
|
60 |
title = "Real-time AI App with Groq API and LangChain"
|
|
|
64 |
</center>
|
65 |
"""
|
66 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
67 |
demo = gr.Interface(
|
68 |
title=title,
|
69 |
description=description,
|
70 |
+
fn=rag_memory_stream,
|
71 |
+
inputs="text",
|
72 |
outputs="text",
|
73 |
live=True,
|
74 |
batch=True,
|
|
|
76 |
concurrency_limit=12,
|
77 |
allow_flagging="never",
|
78 |
theme=gr.themes.Soft(),
|
79 |
+
trigger_mode="always_last",
|
80 |
)
|
81 |
|
82 |
# Launch the Gradio interface
|
83 |
demo.queue()
|
84 |
+
demo.launch()
|