gpt,cphovo

How to use

Go to the proxy directory and build the gpt-proxy image.
```
cd proxy
docker image build -t gpt-proxy:latest .
```
Copy your agent's configuration file to config.yaml
```
cp config.yaml.example config.yaml
vim config.yaml
```

Start services with docker compose.

# v2
docker compose up -d
# v1
docker-compose up -d

Populate environment variables in the .env file
```
cp example.env .env
vim .env
```

Run main.py and enter your question.

> pip install -r requirements.txt
> python main.py --help
Usage: main.py [OPTIONS] COMMAND [ARGS]...

─ Options ─────────────────────────────────────────────────────────────────────────────────────────────────────────
| --install-completion          Install completion for the current shell.                                         |
| --show-completion             Show completion for the current shell, to copy it or customize the installation.  |
| --help                        Show this message and exit.                                                       |
─ Commands ────────────────────────────────────────────────────────────────────────────────────────────────────────
| bard                                                                                                            |
| chatgpt                                                                                                         |
| translate                                                                                                       |
───────────────────────────────────────────────────────────────────────────────────────────────────────────────────

Examples

translate

> python main.py translate
> Source [zh]: en
> Target [en]: zh
ask for answer(press Enter twice to finish):
> how old are you?
你多大了？

chatgpt

> python main.py chatgpt
> Plus [y/N]:
Using ChatGPT...
http://127.0.0.1:19090/api/
ask for answer(press Enter twice to finish):
> 如何使用 KMP 算法，请用 Python 为我详细举例解释，我很希望可以学会 KMP 算法

当然！KMP（Knuth-Morris-Pratt）算法是一种用于在文本中快速查找子串的字符串匹配算法。它通过利用已经匹配的信息，避免在文本中重复比较已经比较过的字符。

下面是使用 Python 实现 KMP 算法的示例代码：

def compute_lps(pattern):
   """
   计算最长公共前缀和最长公共后缀的部分匹配表（Longest Proper Prefix/Suffix）
   """
   length = len(pattern)
   lps = [0] * length  # 初始化部分匹配表

   prefix_len = 0  # 当前最长公共前缀的长度
   i = 1

   while i < length:
      if pattern[i] == pattern[prefix_len]:
            prefix_len += 1
            lps[i] = prefix_len
            i += 1
      else:
            if prefix_len != 0:
               prefix_len = lps[prefix_len - 1]
            else:
               lps[i] = 0
               i += 1

   return lps


def kmp_search(text, pattern):
   """
   使用 KMP 算法在文本中查找模式串
   """
   n = len(text)
   m = len(pattern)
   result = []

   lps = compute_lps(pattern)
   i = 0  # text 中当前字符的索引
   j = 0  # pattern 中当前字符的索引

   while i < n:
      if text[i] == pattern[j]:
            i += 1
            j += 1

            if j == m:
               result.append(i - j)  # 找到匹配，将索引添加到结果列表
               j = lps[j - 1]
      else:
            if j != 0:
               j = lps[j - 1]
            else:
               i += 1

   return result


# 示例用法
text = "ABABDABACDABABCABAB"
pattern = "ABABCABAB"
result = kmp_search(text, pattern)
print("在文本中的匹配位置：", result)

bard

> python main.py bard
Using Google Bard...
ask for answer(press Enter twice to finish):
> implement fib method via python

Sure, here is the implementation of the Fibonacci sequence in Python:


def fib(n):
   """
   Calculates the nth Fibonacci number.

   Args:
   n: The nth Fibonacci number to calculate.

   Returns:
   The nth Fibonacci number.
   """

   if n == 0 or n == 1:
       return n
   else:
       return fib(n - 1) + fib(n - 2)


This function works by recursively calculating the Fibonacci numbers. The base cases are when n is 0 or 1, in which case the function simply returns n. Otherwise, the function returns the sum of the two previous Fibonacci numbers.

Here is an example of how to use the function:


>>> fib(10)
55


This code will print the 10th Fibonacci number, which is 55.

The Fibonacci sequence is a famous mathematical sequence that has many interesting properties. It can be used to solve a variety of problems, including finding the golden ratio and calculating the number of ways to arrange a set of
objects.

Todos

Use Mongo Persistence.
~~Add New Bing.~~
Use LangChain doing some interesting things.

Thanks

This demo reference acheong08's open source project, many thanks 🙏.

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