Update functions.md (#461)
This commit is contained in:
Charles Packer
@@ -30,53 +30,79 @@ There are three steps to adding more MemGPT functions:
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2. (Optional) Create a new system prompt that instructs MemGPT how to use these functions
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3. Create a new preset that imports these functions (and optionally uses the new system prompt)
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### Step 1: Writing the functions
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### Example: giving MemGPT the ability to use the Jira API
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!!! warning "Function requirements"
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The functions you write MUST have proper docstrings and type hints - this is because MemGPT will use these docstrings and types to automatically create a JSON schema that is used in the LLM prompt. Use the docstrings and types annotations from the [example functions](https://github.com/cpacker/MemGPT/blob/main/memgpt/functions/function_sets/base.py) for guidance.
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As an example, if you wanted to give MemGPT the ability to make HTTP requests, you would write the function in Python (you would save this python file inside `~/.memgpt/functions/your_new_functions.py`):
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```python
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import json
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import requests
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_Example taken from [this pull request](https://github.com/cpacker/MemGPT/pull/282) by @cevatkerim_
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def http_request(self, method: str, url: str, payload_json: Optional[str] = None):
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As an example, if you wanted to give MemGPT the ability to make calls to Jira Cloud, you would write the function in Python (you would save this python file inside `~/.memgpt/functions/jira_cloud.py`):
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```python
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import os
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from jira import JIRA
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from jira.exceptions import JIRAError
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def get_jira(self, issue_key: str) -> dict:
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"""
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Generates an HTTP request and returns the response.
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Makes a request to user's JIRA instance with the jira issue id that is provided and returns the issue details
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Args:
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method (str): The HTTP method (e.g., 'GET', 'POST').
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url (str): The URL for the request.
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payload_json (Optional[str]): A JSON string representing the request payload.
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issue_key (str): the issue key (MAIN-1 for example).
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Returns:
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dict: The response from the HTTP request.
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dict: The response from the JIRA request.
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"""
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if self.jira is None:
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server = os.getenv("JIRA_SERVER")
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username = os.getenv("JIRA_USER")
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password = os.getenv("JIRA_KEY")
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self.jira = JIRA({"server": server}, basic_auth=(username, password))
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try:
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headers = {"Content-Type": "application/json"}
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issue = self.jira.issue(issue_key)
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return {
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"issue": {
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"key": issue.key,
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"summary": issue.fields.summary,
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"description": issue.fields.description,
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"created": issue.fields.created,
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"assignee": issue.fields.creator.displayName,
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"status": issue.fields.status.name,
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"status_category": issue.fields.status.statusCategory.name,
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}
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}
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except JIRAError as e:
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print(f"Error: {e.text}")
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return {"error": str(e.text)}
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# For GET requests, ignore the payload
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if method.upper() == "GET":
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print(f"[HTTP] launching GET request to {url}")
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response = requests.get(url, headers=headers)
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else:
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# Validate and convert the payload for other types of requests
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if payload_json:
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payload = json.loads(payload_json)
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else:
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payload = {}
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print(f"[HTTP] launching {method} request to {url}, payload=\n{json.dumps(payload, indent=2)}")
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response = requests.request(method, url, json=payload, headers=headers)
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return {"status_code": response.status_code, "headers": dict(response.headers), "body": response.text}
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except Exception as e:
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return {"error": str(e)}
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def run_jql(self, jql: str) -> dict:
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"""
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Makes a request to user's JIRA instance with the jql that is provided and returns the issues
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Args:
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jql (str): the JQL.
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Returns:
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dict: The response from the JIRA request.
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"""
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if self.jira is None:
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server = os.getenv("JIRA_SERVER")
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username = os.getenv("JIRA_USER")
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password = os.getenv("JIRA_KEY")
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self.jira = JIRA({"server": server}, basic_auth=(username, password))
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try:
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issues = self.jira.search_issues(jql)
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return {"issues": [issue.key for issue in issues]}
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except JIRAError as e:
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print(f"Error: {e.text}")
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return {"error": str(e.text)}
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```
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### Step 3: Create a new preset file
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Now we need to create a new preset file, let's create one called `~/.memgpt/presets/memgpt_http.yaml`:
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Now we need to create a new preset file, let's create one called `~/.memgpt/presets/memgpt_jira.yaml`:
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```yaml
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# if we had created a new system prompt, we would replace "memgpt_chat" with the new prompt filename (no .txt)
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system_prompt: "memgpt_chat"
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@@ -89,8 +115,23 @@ functions:
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- "conversation_search_date"
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- "archival_memory_insert"
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- "archival_memory_search"
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# internet access
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- "http_request"
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# Jira functions that we made inside of `~/.memgpt/functions/jira_cloud.py`
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- "get_jira"
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- "run_jql"
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```
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Now when we run `memgpt configure`, we should see the option to use `memgpt_http` as a preset.
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Now when we run `memgpt configure`, we should see the option to use `memgpt_jira` as a preset:
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```sh
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memgpt configure
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```
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```text
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...
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? Select default preset: (Use arrow keys)
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memgpt_extras
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memgpt_docs
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memgpt_chat
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» memgpt_jira
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```
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Now, if we create a new MemGPT agent (with `memgpt run`) using this `memgpt_jira` preset, it will have the ability to call Jira cloud:
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