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Support send tool_calls back to internlm2 #2147

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Aug 14, 2024
Merged

Support send tool_calls back to internlm2 #2147

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f8d55d5
Support send tool_calls back to internlm2
AllentDan Jul 26, 2024
a387098
Merge branch 'main' into internlm2-sendback
AllentDan Jul 26, 2024
18ab805
Merge branch 'main' into internlm2-sendback
AllentDan Jul 31, 2024
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update documents
AllentDan Aug 5, 2024
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Merge branch 'main' into internlm2-sendback
AllentDan Aug 7, 2024
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Merge branch 'main' into internlm2-sendback
AllentDan Aug 8, 2024
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Merge branch 'main' into internlm2-sendback
AllentDan Aug 12, 2024
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AllentDan Aug 12, 2024
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13 changes: 5 additions & 8 deletions docs/en/llm/api_server_tools.md
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Original file line number Diff line number Diff line change
Expand Up @@ -119,14 +119,11 @@ func1_args = response.choices[0].message.tool_calls[0].function.arguments
func1_out = eval(f'{func1_name}(**{func1_args})')
print(func1_out)

messages.append(response.choices[0].message)
messages.append({
'role': 'assistant',
'content': response.choices[0].message.content
})
messages.append({
'role': 'environment',
'role': 'tool',
'content': f'3+5={func1_out}',
'name': 'plugin'
'tool_call_id': response.choices[0].message.tool_calls[0].id
})
response = client.chat.completions.create(
model=model_name,
Expand All @@ -145,9 +142,9 @@ print(func2_out)
Using the InternLM2-Chat-7B model to execute the above example, the following results will be printed.

```
ChatCompletion(id='1', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content='', role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='1', function=Function(arguments={'a': 3, 'b': 5}, name='add'), type='function')]))], created=1719369986, model='/nvme/shared_data/InternLM/internlm2-chat-7b', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=25, prompt_tokens=263, total_tokens=288))
ChatCompletion(id='1', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content='', role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='0', function=Function(arguments='{"a": 3, "b": 5}', name='add'), type='function')]))], created=1722852901, model='/nvme/shared_data/InternLM/internlm2-chat-7b', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=25, prompt_tokens=263, total_tokens=288))
8
ChatCompletion(id='2', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content='', role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='2', function=Function(arguments={'a': 8, 'b': 2}, name='mul'), type='function')]))], created=1719369987, model='/nvme/shared_data/InternLM/internlm2-chat-7b', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=25, prompt_tokens=282, total_tokens=307))
ChatCompletion(id='2', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content='', role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='1', function=Function(arguments='{"a": 8, "b": 2}', name='mul'), type='function')]))], created=1722852901, model='/nvme/shared_data/InternLM/internlm2-chat-7b', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=25, prompt_tokens=293, total_tokens=318))
16
```

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13 changes: 5 additions & 8 deletions docs/zh_cn/llm/api_server_tools.md
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Original file line number Diff line number Diff line change
Expand Up @@ -119,14 +119,11 @@ func1_args = response.choices[0].message.tool_calls[0].function.arguments
func1_out = eval(f'{func1_name}(**{func1_args})')
print(func1_out)

messages.append(response.choices[0].message)
messages.append({
'role': 'assistant',
'content': response.choices[0].message.content
})
messages.append({
'role': 'environment',
'role': 'tool',
'content': f'3+5={func1_out}',
'name': 'plugin'
'tool_call_id': response.choices[0].message.tool_calls[0].id
})
response = client.chat.completions.create(
model=model_name,
Expand All @@ -145,9 +142,9 @@ print(func2_out)
实际使用 InternLM2-Chat-7B 模型执行上述例子，可以得到下面的结果：

```
ChatCompletion(id='1', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content='', role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='1', function=Function(arguments={'a': 3, 'b': 5}, name='add'), type='function')]))], created=1719369986, model='/nvme/shared_data/InternLM/internlm2-chat-7b', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=25, prompt_tokens=263, total_tokens=288))
ChatCompletion(id='1', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content='', role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='0', function=Function(arguments='{"a": 3, "b": 5}', name='add'), type='function')]))], created=1722852901, model='/nvme/shared_data/InternLM/internlm2-chat-7b', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=25, prompt_tokens=263, total_tokens=288))
8
ChatCompletion(id='2', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content='', role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='2', function=Function(arguments={'a': 8, 'b': 2}, name='mul'), type='function')]))], created=1719369987, model='/nvme/shared_data/InternLM/internlm2-chat-7b', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=25, prompt_tokens=282, total_tokens=307))
ChatCompletion(id='2', choices=[Choice(finish_reason='tool_calls', index=0, logprobs=None, message=ChatCompletionMessage(content='', role='assistant', function_call=None, tool_calls=[ChatCompletionMessageToolCall(id='1', function=Function(arguments='{"a": 8, "b": 2}', name='mul'), type='function')]))], created=1722852901, model='/nvme/shared_data/InternLM/internlm2-chat-7b', object='chat.completion', system_fingerprint=None, usage=CompletionUsage(completion_tokens=25, prompt_tokens=293, total_tokens=318))
16
```

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12 changes: 10 additions & 2 deletions lmdeploy/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -485,11 +485,13 @@ def messages2prompt(self,
box_map = dict(user=self.user,
assistant=self.assistant,
system=self.system,
environment=self.environment)
environment=self.environment,
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Do we still need "environment"? What's the difference between "environment" and "tool"?

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Do we still need "environment"? What's the difference between "environment" and "tool"?

"environment" is from internlm2. "tool" is from openai.

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Should we update the user guide?

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Original user guide works fine.

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Let's follow the openai API

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llama3.1 should also be updated.

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ipython tool is not a customized tool. We don't need to update it.

tool=self.environment)
eox_map = dict(user=self.eoh,
assistant=self.eoa + self.separator,
system=self.eosys,
environment=self.eoenv)
environment=self.eoenv,
tool=self.eoenv)
name_map = dict(plugin=self.plugin, interpreter=self.interpreter)
ret = ''
if self.meta_instruction is not None and sequence_start:
Expand All @@ -508,6 +510,12 @@ def messages2prompt(self,
for message in messages:
role = message['role']
content = message['content']
if role == 'assistant' and message.get('tool_calls',
None) is not None:
for tool_call in message['tool_calls']:
function = tool_call.get('function', {})
function['arguments'] = function.pop('parameters', {})
content += f'<|action_start|><|plugin|>\n{json.dumps(function)}<|action_end|>'
if 'name' in message and message['name'] in name_map:
begin = box_map[role].strip(
) + f" name={name_map[message['name']]}\n"
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3 changes: 2 additions & 1 deletion lmdeploy/serve/async_engine.py
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Expand Up @@ -627,7 +627,8 @@ def parse_tool_response(self, text, tools, **kwargs):
action = action.split('<|action_end|>'.strip())[0]
action = action[action.find('{'):]
action = json.loads(action)
name, parameters = action['name'], json.dumps(action['parameters'])
name, parameters = action['name'], json.dumps(
action.get('parameters', action.get('arguments', {})))
elif '<function=' in text: # llama3.1
action, _ = text.split('</function>')
parameters = action[action.find('{'):]
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