Avo-k commited on
Commit
fdf1622
1 Parent(s): 99e2b1f

auto update text box + stream

Browse files
Files changed (1) hide show
  1. app.py +23 -14
app.py CHANGED
@@ -13,24 +13,24 @@ system_template = {"role": "system", "content": os.environ["content"]}
13
 
14
  retrieve_all = EmbeddingRetriever(
15
  document_store=FAISSDocumentStore.load(
16
- index_path="./documents/climate_gpt.faiss",
17
- config_path="./documents/climate_gpt.json",
18
- ),
19
  embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
20
  model_format="sentence_transformers",
21
  )
22
  retrieve_giec = EmbeddingRetriever(
23
  document_store=FAISSDocumentStore.load(
24
- index_path="./documents/climate_gpt_only_giec.faiss",
25
- config_path="./documents/climate_gpt_only_giec.json",
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- ),
27
  embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
28
  model_format="sentence_transformers",
29
  )
30
 
31
 
32
- def gen_conv(query: str, history: list = [system_template], report_type="All available", threshold=0.56):
33
- retriever = retrieve_all if report_type=="All available" else retrieve_giec
34
  docs = retriever.retrieve(query=query, top_k=10)
35
 
36
  messages = history + [{"role": "user", "content": query}]
@@ -46,20 +46,27 @@ def gen_conv(query: str, history: list = [system_template], report_type="All ava
46
  messages.append({"role": "system", "content": "no relevant document available."})
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  sources = "No environmental report was used to provide this answer."
48
 
49
- answer = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages, temperature=0.2,)["choices"][0][
50
  "message"
51
  ]["content"]
52
 
53
- messages[-1] = {"role": "assistant", "content": answer}
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- gradio_format = make_pairs([a["content"] for a in messages[1:]])
55
 
56
- return gradio_format, messages, sources
 
 
 
 
57
 
58
 
59
  def test(feed: str):
60
  print(feed)
61
 
62
 
 
 
 
 
63
  # Gradio
64
  css_code = ".gradio-container {background-image: url('file=background.png');background-position: top right}"
65
 
@@ -95,7 +102,7 @@ with gr.Blocks(title="🌍 ClimateGPT Ekimetrics", css=css_code) as demo:
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  sources_textbox = gr.Textbox(interactive=False, show_label=False, max_lines=50)
96
 
97
  ask.submit(
98
- fn=gen_conv,
99
  inputs=[
100
  ask,
101
  state,
@@ -107,6 +114,8 @@ with gr.Blocks(title="🌍 ClimateGPT Ekimetrics", css=css_code) as demo:
107
  ],
108
  outputs=[chatbot, state, sources_textbox],
109
  )
 
 
110
  with gr.Accordion("Feedbacks", open=False):
111
  gr.Markdown("Please complete some feedbacks 🙏")
112
  feedback = gr.Textbox()
@@ -150,4 +159,4 @@ with gr.Blocks(title="🌍 ClimateGPT Ekimetrics", css=css_code) as demo:
150
  with gr.Tab("Examples"):
151
  gr.Markdown("See here some examples on how to use the Chatbot")
152
 
153
- demo.launch()
 
13
 
14
  retrieve_all = EmbeddingRetriever(
15
  document_store=FAISSDocumentStore.load(
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+ index_path="./documents/climate_gpt.faiss",
17
+ config_path="./documents/climate_gpt.json",
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+ ),
19
  embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
20
  model_format="sentence_transformers",
21
  )
22
  retrieve_giec = EmbeddingRetriever(
23
  document_store=FAISSDocumentStore.load(
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+ index_path="./documents/climate_gpt_only_giec.faiss",
25
+ config_path="./documents/climate_gpt_only_giec.json",
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+ ),
27
  embedding_model="sentence-transformers/multi-qa-mpnet-base-dot-v1",
28
  model_format="sentence_transformers",
29
  )
30
 
31
 
32
+ def chat(query: str, history: list = [system_template], report_type="All available", threshold=0.56):
33
+ retriever = retrieve_all if report_type == "All available" else retrieve_giec
34
  docs = retriever.retrieve(query=query, top_k=10)
35
 
36
  messages = history + [{"role": "user", "content": query}]
 
46
  messages.append({"role": "system", "content": "no relevant document available."})
47
  sources = "No environmental report was used to provide this answer."
48
 
49
+ response = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages, temperature=0.2,)["choices"][0][
50
  "message"
51
  ]["content"]
52
 
53
+ complete_response = ""
 
54
 
55
+ for chunk in response:
56
+ complete_response += chunk["choices"][0]["delta"].get("content", "")
57
+ messages[-1] = {"role": "assistant", "content": complete_response}
58
+ gradio_format = make_pairs([a["content"] for a in messages[1:]])
59
+ yield gradio_format, messages, sources
60
 
61
 
62
  def test(feed: str):
63
  print(feed)
64
 
65
 
66
+ def reset_textbox():
67
+ return gr.update(value="")
68
+
69
+
70
  # Gradio
71
  css_code = ".gradio-container {background-image: url('file=background.png');background-position: top right}"
72
 
 
102
  sources_textbox = gr.Textbox(interactive=False, show_label=False, max_lines=50)
103
 
104
  ask.submit(
105
+ fn=chat,
106
  inputs=[
107
  ask,
108
  state,
 
114
  ],
115
  outputs=[chatbot, state, sources_textbox],
116
  )
117
+ ask.submit(reset_textbox, [], [ask])
118
+
119
  with gr.Accordion("Feedbacks", open=False):
120
  gr.Markdown("Please complete some feedbacks 🙏")
121
  feedback = gr.Textbox()
 
159
  with gr.Tab("Examples"):
160
  gr.Markdown("See here some examples on how to use the Chatbot")
161
 
162
+ demo.launch(concurrency_count=16)