kamuy-shennai
commited on
Commit
·
4591b75
1
Parent(s):
3de1bb5
update function call
Browse files- docs/function_call_guide.md +86 -53
- docs/function_call_guide_cn.md +86 -53
- tokenizer_config.json +1 -1
docs/function_call_guide.md
CHANGED
@@ -18,21 +18,19 @@ from transformers import AutoTokenizer
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def get_default_tools():
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return [
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{
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},
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}
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"required": ["location"],
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"type": "object"
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}
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}
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]
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@@ -54,6 +52,22 @@ text = tokenizer.apply_chat_template(
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add_generation_prompt=True,
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tools=tools
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)
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```
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## 🛠️ Function Call Definition
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@@ -102,9 +116,9 @@ Function calls need to be defined in the `tools` field of the request body. Each
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When processed internally by the model, function definitions are converted to a special format and concatenated to the input text:
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```
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-
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-
MiniMax AI is an AI assistant independently developed by MiniMax.
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-
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You are provided with these tools:
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<tools>
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{"name": "search_web", "description": "Search function.", "parameters": {"properties": {"query_list": {"description": "Keywords for search, with list element count of 1.", "items": {"type": "string"}, "type": "array"}, "query_tag": {"description": "Classification of the query", "items": {"type": "string"}, "type": "array"}}, "required": ["query_list", "query_tag"], "type": "object"}}
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@@ -114,10 +128,10 @@ If you need to call tools, please respond with <tool_calls></tool_calls> XML tag
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<tool_calls>
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{"name": <tool-name>, "arguments": <args-json-object>}
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...
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-
</tool_calls>
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-
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When were the most recent launch events for OpenAI and Gemini
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-
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```
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### Model Output Format
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@@ -193,23 +207,33 @@ def execute_function_call(function_name: str, arguments: dict):
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# Build function execution result
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return {
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"role": "tool",
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"
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"
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"
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elif function_name == "search_web":
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query_list = arguments.get("query_list", [])
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query_tag = arguments.get("query_tag", [])
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# Simulate search results
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return {
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"role": "tool",
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"
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return None
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```
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@@ -224,47 +248,56 @@ If the model decides to call `search_web`, we suggest you to return the function
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```json
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{
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"
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-
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-
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-
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]
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}
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```
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Corresponding model input format:
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```
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-
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-
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```
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#### Multiple Result
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-
If the model decides to call `search_web` and `get_current_weather` at the same time, we suggest you to return the multiple function results in the following format,
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```json
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{
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-
"
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-
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-
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-
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-
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]
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}
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```
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Corresponding model input format:
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```
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-
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-
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-
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-
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-
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```
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-
While we suggest following the above formats, as long as the model input is easy to understand, the specific values of `name` and `
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def get_default_tools():
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return [
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{
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"name": "get_current_weather",
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"description": "Get the latest weather for a location",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "A certain city, such as Beijing, Shanghai"
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}
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},
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}
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"required": ["location"],
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"type": "object"
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}
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]
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add_generation_prompt=True,
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tools=tools
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)
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+
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# Post request
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import requests
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payload = {
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"model": "MiniMaxAI/MiniMax-M1-40k",
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"prompt": text,
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"max_tokens": 4000
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}
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response = requests.post(
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"http://localhost:8000/v1/completions",
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headers={"Content-Type": "application/json"},
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json=payload,
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stream=False,
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)
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print(response.json()["choices"][0]["text"])
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```
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## 🛠️ Function Call Definition
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When processed internally by the model, function definitions are converted to a special format and concatenated to the input text:
|
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|
118 |
```
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+
<begin_of_document><beginning_of_sentence>system ai_setting=MiniMax AI
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+
MiniMax AI is an AI assistant independently developed by MiniMax. <end_of_sentence>
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+
<beginning_of_sentence>system tool_setting=tools
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You are provided with these tools:
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<tools>
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{"name": "search_web", "description": "Search function.", "parameters": {"properties": {"query_list": {"description": "Keywords for search, with list element count of 1.", "items": {"type": "string"}, "type": "array"}, "query_tag": {"description": "Classification of the query", "items": {"type": "string"}, "type": "array"}}, "required": ["query_list", "query_tag"], "type": "object"}}
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<tool_calls>
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{"name": <tool-name>, "arguments": <args-json-object>}
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...
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</tool_calls><end_of_sentence>
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<beginning_of_sentence>user name=User
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When were the most recent launch events for OpenAI and Gemini?<end_of_sentence>
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<beginning_of_sentence>ai name=MiniMax AI
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```
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### Model Output Format
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# Build function execution result
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return {
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"role": "tool",
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"content": [
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{
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"name": function_name,
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"type": "text",
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"text": json.dumps({
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"location": location,
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"temperature": "25",
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"unit": "celsius",
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"weather": "Sunny"
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}, ensure_ascii=False)
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}
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]
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}
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elif function_name == "search_web":
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query_list = arguments.get("query_list", [])
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query_tag = arguments.get("query_tag", [])
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# Simulate search results
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return {
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"role": "tool",
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"content": [
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{
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"name": function_name,
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"type": "text",
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"text": f"Search keywords: {query_list}, Categories: {query_tag}\nSearch results: Relevant information found"
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}
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]
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}
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return None
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```
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```json
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{
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"role": "tool",
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"content": [
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{
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"name": "search_web",
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"type": "text",
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"text": "test_result"
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}
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]
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}
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```
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Corresponding model input format:
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```
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<beginning_of_sentence>tool name=tools
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tool name: search_web
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tool result: test_result
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<end_of_sentence>
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```
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#### Multiple Result
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+
If the model decides to call `search_web` and `get_current_weather` at the same time, we suggest you to return the multiple function results in the following format, use the `content` field to contain multiple results.
|
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```json
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{
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+
"role": "tool",
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"content": [
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{
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"name": "search_web",
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"type": "text",
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"text": "test_result1"
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},
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{
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"name": "get_current_weather",
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"type": "text",
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"text": "test_result2"
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}
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]
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}
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```
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Corresponding model input format:
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```
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+
<beginning_of_sentence>tool name=tools
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+
tool name: search_web
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+
tool result: test_result1
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tool name: get_current_weather
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tool result: test_result2<end_of_sentence>
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```
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+
While we suggest following the above formats, as long as the model input is easy to understand, the specific values of `name` and `text` is entirely up to the caller.
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docs/function_call_guide_cn.md
CHANGED
@@ -16,21 +16,19 @@ from transformers import AutoTokenizer
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def get_default_tools():
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return [
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{
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-
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},
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}
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"required": ["location"],
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"type": "object"
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}
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}
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]
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add_generation_prompt=True,
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tools=tools
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)
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```
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## 🛠️ 函数调用的定义
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@@ -100,9 +114,9 @@ text = tokenizer.apply_chat_template(
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在模型内部处理时,函数定义会被转换为特殊格式并拼接到输入文本中:
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|
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```
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103 |
-
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104 |
-
MiniMax AI是由上海稀宇科技有限公司(MiniMax)自主研发的AI
|
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-
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You are provided with these tools:
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<tools>
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{"name": "search_web", "description": "搜索函数。", "parameters": {"properties": {"query_list": {"description": "进行搜索的关键词,列表元素个数为1。", "items": {"type": "string"}, "type": "array"}, "query_tag": {"description": "query的分类", "items": {"type": "string"}, "type": "array"}}, "required": ["query_list", "query_tag"], "type": "object"}}
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@@ -112,10 +126,10 @@ If you need to call tools, please respond with <tool_calls></tool_calls> XML tag
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<tool_calls>
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{"name": <tool-name>, "arguments": <args-json-object>}
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...
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-
</tool_calls>
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-
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-
OpenAI 和 Gemini
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-
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```
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### 模型输出格式
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@@ -191,23 +205,33 @@ def execute_function_call(function_name: str, arguments: dict):
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# 构建函数执行结果
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return {
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"role": "tool",
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"
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elif function_name == "search_web":
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query_list = arguments.get("query_list", [])
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query_tag = arguments.get("query_tag", [])
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# 模拟搜索结果
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return {
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"role": "tool",
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"
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return None
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```
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```json
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{
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]
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}
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```
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对应如下的模型输入格式:
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```
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-
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-
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```
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#### 多个结果
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-
假如模型同时调用了 `search_web` 和 `get_current_weather` 函数,您可以参考如下格式添加执行结果,`
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```json
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{
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-
"
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-
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]
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}
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```
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对应如下的模型输入格式:
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```
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-
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-
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-
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-
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```
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-
虽然我们建议您参考以上格式,但只要返回给模型的输入易于理解,`name` 和 `
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def get_default_tools():
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return [
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{
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+
"name": "get_current_weather",
|
20 |
+
"description": "Get the latest weather for a location",
|
21 |
+
"parameters": {
|
22 |
+
"type": "object",
|
23 |
+
"properties": {
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24 |
+
"location": {
|
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+
"type": "string",
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+
"description": "A certain city, such as Beijing, Shanghai"
|
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+
}
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+
},
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}
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"required": ["location"],
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+
"type": "object"
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}
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]
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add_generation_prompt=True,
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tools=tools
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)
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+
|
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+
# 发送请求
|
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+
import requests
|
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+
payload = {
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"model": "MiniMaxAI/MiniMax-M1-40k",
|
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+
"prompt": text,
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"max_tokens": 4000
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}
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+
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+
response = requests.post(
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"http://localhost:8000/v1/completions",
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headers={"Content-Type": "application/json"},
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+
json=payload,
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+
stream=False,
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)
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68 |
+
print(response.json()["choices"][0]["text"])
|
69 |
```
|
70 |
|
71 |
## 🛠️ 函数调用的定义
|
|
|
114 |
在模型内部处理时,函数定义会被转换为特殊格式并拼接到输入文本中:
|
115 |
|
116 |
```
|
117 |
+
<begin_of_document><beginning_of_sentence>system ai_setting=MiniMax AI
|
118 |
+
MiniMax AI是由上海稀宇科技有限公司(MiniMax)自主研发的AI助理。<end_of_sentence>
|
119 |
+
<beginning_of_sentence>system tool_setting=tools
|
120 |
You are provided with these tools:
|
121 |
<tools>
|
122 |
{"name": "search_web", "description": "搜索函数。", "parameters": {"properties": {"query_list": {"description": "进行搜索的关键词,列表元素个数为1。", "items": {"type": "string"}, "type": "array"}, "query_tag": {"description": "query的分类", "items": {"type": "string"}, "type": "array"}}, "required": ["query_list", "query_tag"], "type": "object"}}
|
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|
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<tool_calls>
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{"name": <tool-name>, "arguments": <args-json-object>}
|
128 |
...
|
129 |
+
</tool_calls><end_of_sentence>
|
130 |
+
<beginning_of_sentence>user name=用户
|
131 |
+
OpenAI 和 Gemini 的最近一次发布会都是什么时候?<end_of_sentence>
|
132 |
+
<beginning_of_sentence>ai name=MiniMax AI
|
133 |
```
|
134 |
|
135 |
### 模型输出格式
|
|
|
205 |
# 构建函数执行结果
|
206 |
return {
|
207 |
"role": "tool",
|
208 |
+
"content": [
|
209 |
+
{
|
210 |
+
"name": function_name,
|
211 |
+
"type": "text",
|
212 |
+
"text": json.dumps({
|
213 |
+
"location": location,
|
214 |
+
"temperature": "25",
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215 |
+
"unit": "celsius",
|
216 |
+
"weather": "晴朗"
|
217 |
+
}, ensure_ascii=False)
|
218 |
+
}
|
219 |
+
]
|
220 |
+
}
|
221 |
elif function_name == "search_web":
|
222 |
query_list = arguments.get("query_list", [])
|
223 |
query_tag = arguments.get("query_tag", [])
|
224 |
# 模拟搜索结果
|
225 |
return {
|
226 |
"role": "tool",
|
227 |
+
"content": [
|
228 |
+
{
|
229 |
+
"name": function_name,
|
230 |
+
"type": "text",
|
231 |
+
"text": f"搜索关键词: {query_list}, 分类: {query_tag}\n搜索结果: 相关信息已找到"
|
232 |
+
}
|
233 |
+
]
|
234 |
+
}
|
235 |
|
236 |
return None
|
237 |
```
|
|
|
246 |
|
247 |
```json
|
248 |
{
|
249 |
+
"role": "tool",
|
250 |
+
"content": [
|
251 |
+
{
|
252 |
+
"name": "search_web",
|
253 |
+
"type": "text",
|
254 |
+
"text": "test_result"
|
255 |
+
}
|
256 |
]
|
257 |
}
|
258 |
```
|
259 |
|
260 |
对应如下的模型输入格式:
|
261 |
```
|
262 |
+
<beginning_of_sentence>tool name=tools
|
263 |
+
tool name: search_web
|
264 |
+
tool result: test_result
|
265 |
+
<end_of_sentence>
|
266 |
```
|
267 |
|
268 |
|
269 |
#### 多个结果
|
270 |
+
假如模型同时调用了 `search_web` 和 `get_current_weather` 函数,您可以参考如下格式添加执行结果,`content`包含多个结果。
|
271 |
|
272 |
```json
|
273 |
{
|
274 |
+
"role": "tool",
|
275 |
+
"content": [
|
276 |
+
{
|
277 |
+
"name": "search_web",
|
278 |
+
"type": "text",
|
279 |
+
"text": "test_result1"
|
280 |
+
},
|
281 |
+
{
|
282 |
+
"name": "get_current_weather",
|
283 |
+
"type": "text",
|
284 |
+
"text": "test_result2"
|
285 |
+
}
|
286 |
]
|
287 |
}
|
288 |
```
|
289 |
|
290 |
对应如下的模型输入格式:
|
291 |
```
|
292 |
+
<beginning_of_sentence>tool name=tools
|
293 |
+
tool name: search_web
|
294 |
+
tool result: test_result1
|
295 |
|
296 |
+
tool name: get_current_weather
|
297 |
+
tool result: test_result2<end_of_sentence>
|
298 |
```
|
299 |
|
300 |
+
虽然我们建议您参考以上格式,但只要返回给模型的输入易于理解,`name` 和 `text` 的具体内容完全由您自主决定。
|
tokenizer_config.json
CHANGED
@@ -6,5 +6,5 @@
|
|
6 |
"model_max_length": 40960000,
|
7 |
"tokenizer_class": "GPT2Tokenizer",
|
8 |
"unk_token": "<end_of_document>",
|
9 |
-
"chat_template": "{{ '<begin_of_document>' -}}{% set ns = namespace(system_prompt='') -%}{% for message in messages -%}{% if message['role'] == 'system' -%}{% set ns.system_prompt = ns.system_prompt + message['content'][0]['text'] -%}{% endif -%}{%- endfor -%}{% if ns.system_prompt != '' -%}{{ '<beginning_of_sentence>system ai_setting=assistant\n' + ns.system_prompt + '<end_of_sentence>\n' -}}{%- endif -%}{% if tools -%}{{ '<beginning_of_sentence>system tool_setting=tools\nYou are provided with these tools:\n<tools>\n' -}}{% for tool in tools -%}{{ tool | tojson ~ '\n' -}}{%- endfor -%}{{ '</tools>\n\nIf you need to call tools, please respond with <tool_calls></tool_calls> XML tags, and provide tool-name and json-object of arguments, following the format below:\n<tool_calls>\n{''name'': <tool-name-1>, ''arguments'': <args-json-object-1>}\n...\n</tool_calls><end_of_sentence>\n' -}}{%- endif -%}{% for message in messages -%}{% if message['role'] == 'user' -%}{{ '<beginning_of_sentence>user name=user\n' + message['content'][0]['text'] + '<end_of_sentence>\n' -}}{% elif message['role'] == 'assistant' -%}{{ '<beginning_of_sentence>ai name=assistant\n' -}}{% for content in message['content'] | selectattr('type', 'equalto', 'text') -%}{{ content['text'] -}}{%- endfor -%}{{ '<end_of_sentence>\n' -}}{% elif message['role'] == 'tool' -%}{{ '<beginning_of_sentence>tool name=tools\n' }} {%- for content in message['content'] -%}{{- 'tool name: ' + content['name'] + '\n' + 'tool result: ' + content['text'] + '\n\n' -}} {%- endfor -%}{{- '<end_of_sentence>\n' -}}{% endif -%}{%- endfor -%}{% if add_generation_prompt -%}{{ '<beginning_of_sentence>ai name=assistant\n' -}}{%- endif -%}"
|
10 |
}
|
|
|
6 |
"model_max_length": 40960000,
|
7 |
"tokenizer_class": "GPT2Tokenizer",
|
8 |
"unk_token": "<end_of_document>",
|
9 |
+
"chat_template": "{{ '<begin_of_document>' -}}{% set ns = namespace(system_prompt='') -%}{% for message in messages -%}{% if message['role'] == 'system' -%}{% set ns.system_prompt = ns.system_prompt + message['content'][0]['text'] -%}{% endif -%}{%- endfor -%}{% if ns.system_prompt != '' -%}{{ '<beginning_of_sentence>system ai_setting=assistant\n' + ns.system_prompt + '<end_of_sentence>\n' -}}{%- endif -%}{% if tools -%}{{ '<beginning_of_sentence>system tool_setting=tools\nYou are provided with these tools:\n<tools>\n' -}}{% for tool in tools -%}{{ tool | tojson ~ '\n' -}}{%- endfor -%}{{ '</tools>\n\nIf you need to call tools, please respond with <tool_calls></tool_calls> XML tags, and provide tool-name and json-object of arguments, following the format below:\n<tool_calls>\n{''\"name\"'': <tool-name-1>, ''\"arguments\"'': <args-json-object-1>}\n...\n</tool_calls><end_of_sentence>\n' -}}{%- endif -%}{% for message in messages -%}{% if message['role'] == 'user' -%}{{ '<beginning_of_sentence>user name=user\n' + message['content'][0]['text'] + '<end_of_sentence>\n' -}}{% elif message['role'] == 'assistant' -%}{{ '<beginning_of_sentence>ai name=assistant\n' -}}{% for content in message['content'] | selectattr('type', 'equalto', 'text') -%}{{ content['text'] -}}{%- endfor -%}{{ '<end_of_sentence>\n' -}}{% elif message['role'] == 'tool' -%}{{ '<beginning_of_sentence>tool name=tools\n' }} {%- for content in message['content'] -%}{{- 'tool name: ' + content['name'] + '\n' + 'tool result: ' + content['text'] + '\n\n' -}} {%- endfor -%}{{- '<end_of_sentence>\n' -}}{% endif -%}{%- endfor -%}{% if add_generation_prompt -%}{{ '<beginning_of_sentence>ai name=assistant\n' -}}{%- endif -%}"
|
10 |
}
|