add openrouter api
Browse files
app.py
CHANGED
@@ -1,23 +1,14 @@
|
|
1 |
-
import urllib.request
|
2 |
-
import fitz
|
3 |
-
import re
|
4 |
-
import numpy as np
|
5 |
-
import tensorflow_hub as hub
|
6 |
from openai import OpenAI
|
7 |
import gradio as gr
|
8 |
import os
|
9 |
import shutil
|
10 |
from pathlib import Path
|
11 |
from tempfile import NamedTemporaryFile
|
12 |
-
from sklearn.neighbors import NearestNeighbors
|
13 |
-
import anthropic
|
14 |
|
15 |
-
|
16 |
-
|
17 |
-
|
18 |
-
|
19 |
-
|
20 |
-
client = anthropic.Anthropic()
|
21 |
|
22 |
from util import pdf_to_text, text_to_chunks, SemanticSearch
|
23 |
|
@@ -30,45 +21,14 @@ def load_recommender(path, start_page=1):
|
|
30 |
return 'Corpus Loaded.'
|
31 |
|
32 |
|
33 |
-
|
34 |
-
|
35 |
-
|
36 |
-
# message = clinet.chat.completions.create(
|
37 |
-
# model=model,
|
38 |
-
# messages=[
|
39 |
-
# {"role": "user", "content": prompt}
|
40 |
-
# ],
|
41 |
-
# max_tokens=max_tokens,
|
42 |
-
# ).choices[0].message.content
|
43 |
-
# return message
|
44 |
-
|
45 |
-
def claude_generate_text(prompt, model = "claude-3-haiku-20240307"):
|
46 |
-
message = client.messages.create(
|
47 |
-
model=model,
|
48 |
-
max_tokens=1000,
|
49 |
-
temperature=0.0,
|
50 |
-
# system="Respond only in mandarin",
|
51 |
messages=[
|
52 |
{"role": "user", "content": prompt}
|
53 |
-
]
|
54 |
-
)
|
55 |
-
return message
|
56 |
-
|
57 |
-
def generate_answer(question):
|
58 |
-
topn_chunks = recommender(question)
|
59 |
-
prompt = 'search results:\n\n'
|
60 |
-
for c in topn_chunks:
|
61 |
-
prompt += c + '\n\n'
|
62 |
-
|
63 |
-
prompt += "Instructions: Compose a comprehensive reply to the query using the search results given. "\
|
64 |
-
"Cite each reference using [ Page Number] notation. "\
|
65 |
-
"Only answer what is asked. The answer should be short and concise. "\
|
66 |
-
"If asked in Chinese, respond in Chinese; if asked in English, respond"\
|
67 |
-
"in English \n\nQuery: "
|
68 |
-
|
69 |
-
prompt += f"{question}\nAnswer:"
|
70 |
-
answer = claude_generate_text(prompt)
|
71 |
-
return answer
|
72 |
|
73 |
def question_answer(chat_history, file, question):
|
74 |
suffix = Path(file.name).suffix
|
@@ -77,7 +37,7 @@ def question_answer(chat_history, file, question):
|
|
77 |
tmp_path = Path(tmp.name)
|
78 |
|
79 |
load_recommender(str(tmp_path))
|
80 |
-
answer =
|
81 |
chat_history.append([question, answer])
|
82 |
return chat_history
|
83 |
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
from openai import OpenAI
|
2 |
import gradio as gr
|
3 |
import os
|
4 |
import shutil
|
5 |
from pathlib import Path
|
6 |
from tempfile import NamedTemporaryFile
|
|
|
|
|
7 |
|
8 |
+
client = OpenAI(
|
9 |
+
base_url="https://openrouter.ai/api/v1",
|
10 |
+
api_key=os.getenv('OPENROUTER_API_KEY')
|
11 |
+
)
|
|
|
|
|
12 |
|
13 |
from util import pdf_to_text, text_to_chunks, SemanticSearch
|
14 |
|
|
|
21 |
return 'Corpus Loaded.'
|
22 |
|
23 |
|
24 |
+
def generate_text(prompt):
|
25 |
+
message = client.chat.completions.create(
|
26 |
+
model="google/gemini-pro",
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
27 |
messages=[
|
28 |
{"role": "user", "content": prompt}
|
29 |
+
],
|
30 |
+
).choices[0].message.content
|
31 |
+
return message
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
32 |
|
33 |
def question_answer(chat_history, file, question):
|
34 |
suffix = Path(file.name).suffix
|
|
|
37 |
tmp_path = Path(tmp.name)
|
38 |
|
39 |
load_recommender(str(tmp_path))
|
40 |
+
answer = generate_text(question)
|
41 |
chat_history.append([question, answer])
|
42 |
return chat_history
|
43 |
|