1from openai import OpenAI
2import requests
3import json
4
5client = OpenAI()
6BASE_URL = "https://api.diveaccess.com/articles"
7ACCESS_KEY = "YOUR_ACCESS_KEY_HERE"
8
9def get_articles(query, from_date=None, to_date=None):
10    """
11    Fetch articles from the DiveAccess API based on the given query and optional date range.
12    """
13    params = {
14        "access_key": ACCESS_KEY,
15        "query": query,
16    }
17    if from_date:
18        params["from_date"] = from_date
19    if to_date:
20        params["to_date"] = to_date
21
22    response = requests.get(BASE_URL, params=params)
23    if response.status_code == 200:
24        return json.dumps(response.json())
25    else:
26        return json.dumps({
27            "error": f"Error: {response.status_code}, {response.text}"
28        })
29
30tools = [
31    {
32        "type": "function",
33        "function": {
34            "name": "get_articles",
35            "description": "Get articles from Industry Dive publications based on keywords extracted from user input. " +
36                           "Tool will return a list of articles. " +
37                           "Should be used when the message indicates the need for information about a specific topic.",
38            "parameters": {
39                "type": "object",
40                "properties": {
41                    "query": {
42                        "type": "string",
43                        "description": "The search query for articles extracted from the user message."
44                    },
45                    "from_date": {
46                        "type": "string",
47                        "description": "Start date for article search (YYYY-MM-DD)." +
48                                       "The default is 30 days ago. Only include when a specific time frame is necessary.",
49                    },
50                    "to_date": {
51                        "type": "string",
52                        "description": "End date for article search (YYYY-MM-DD)." +
53                                       "The default is today. Only include when a specific time frame is necessary.",
54                    },
55                },
56                "required": ["query"],
57            },
58        },
59    }
60]
61
62def run_conversation():
63    prompt = (
64      "What are the latest developments in artificial intelligence? "
65      "Include sources and links where applicable."
66    )
67    messages = [{
68        "role": "user",
69        "content": prompt
70    }]
71
72    response = client.chat.completions.create(
73        model="gpt-4o",
74        messages=messages,
75        tools=tools,
76        tool_choice="auto",
77    )
78    response_message = response.choices[0].message
79    tool_calls = response_message.tool_calls
80
81    if tool_calls:
82        messages.append(response_message)
83        for tool_call in tool_calls:
84            function_name = tool_call.function.name
85            function_args = json.loads(tool_call.function.arguments)
86            function_response = get_articles(
87                query=function_args.get("query"),
88                from_date=function_args.get("from_date"),
89                to_date=function_args.get("to_date"),
90            )
91            messages.append(
92                {
93                    "tool_call_id": tool_call.id,
94                    "role": "tool",
95                    "name": function_name,
96                    "content": function_response,
97                }
98            )
99
100        second_response = client.chat.completions.create(
101            model="gpt-4o",
102            messages=messages,
103        )
104
105        return second_response
106    else:
107        return response
108
109print(run_conversation())

1import anthropic
2import requests
3import json
4
5client = anthropic.Anthropic()
6BASE_URL = "https://api.diveaccess.com/articles"
7ACCESS_KEY = "YOUR_ACCESS_KEY_HERE"
8
9def get_articles(query, from_date=None, to_date=None):
10    """
11    Fetch articles from the DiveAccess API based on the given query and optional date range
12    """
13    params = {
14        "access_key": ACCESS_KEY,
15        "query": query,
16    }
17    if from_date:
18        params["from_date"] = from_date
19    if to_date:
20        params["to_date"] = to_date
21
22    response = requests.get(BASE_URL, params=params)
23    if response.status_code == 200:
24        return response.json()
25    else:
26        return {"error": f"Error: {response.status_code}, {response.text}"}
27
28tools = [
29    {
30        "name": "get_articles",
31        "description": "Get articles from Industry Dive publications based on keywords extracted from user input. " +
32                       "Tool will return a list of articles. " +
33                       "Should be used when the message indicates the need for information about a specific topic.",
34        "input_schema": {
35            "type": "object",
36            "properties": {
37                "query": {
38                    "type": "string",
39                    "description": "The search query for articles extracted from the user message.",
40                },
41                "from_date": {
42                    "type": "string",
43                    "description": "Start date for article search (YYYY-MM-DD)." +
44                                   "The default is 30 days ago. Only include when a specific time frame is necessary.",
45                },
46                "to_date": {
47                    "type": "string",
48                    "description": "End date for article search (YYYY-MM-DD)." +
49                                   "The default is today. Only include when a specific time frame is necessary.",
50                },
51            },
52            "required": ["query"]
53        }
54    }
55]
56
57def run_conversation():
58    prompt = (
59      "What are the latest developments in artificial intelligence? "
60      "Include sources and links where applicable."
61    )
62
63  # First API call to get tool use
64    response = client.messages.create(
65        model="claude-3-5-sonnet-20240620",
66        max_tokens=1024,
67        tools=tools,
68        messages=[{
69            "role": "user",
70            "content": prompt
71        }]
72    )
73
74    # Check if the model used the tool
75    tool_use = next((content for content in response.content if content.type == "tool_use"), None)
76
77    if tool_use:
78        # If tool was used, fetch articles and make a second API call
79        articles = get_articles(**tool_use.input)
80
81        second_response = client.messages.create(
82            model="claude-3-5-sonnet-20240620",
83            max_tokens=1024,
84            tools=tools,
85            messages=[
86                {
87                    "role": "user",
88                    "content": prompt
89                },
90                {
91                    "role": "assistant",
92                    "content": response.content
93                },
94                {
95                    "role": "user",
96                    "content": [
97                        {
98                            "type": "tool_result",
99                            "tool_use_id": tool_use.id,
100                            "content": json.dumps(articles)
101                        }
102                    ]
103                }
104            ]
105        )
106
107        return second_response
108
109    else:
110        # If no tool was used, return the first response
111        return response
112
113print(run_conversation())