diff --git a/convert/convert.go b/convert/convert.go index fe5592345..110113d0b 100644 --- a/convert/convert.go +++ b/convert/convert.go @@ -193,6 +193,8 @@ func ConvertModel(fsys fs.FS, ws io.WriteSeeker) error { conv = &bertModel{} case "CohereForCausalLM": conv = &commandrModel{} + case "Cohere2ForCausalLM": + conv = &cohere2Model{} default: return errors.New("unsupported architecture") } diff --git a/convert/convert_cohere2.go b/convert/convert_cohere2.go new file mode 100644 index 000000000..31ba8909d --- /dev/null +++ b/convert/convert_cohere2.go @@ -0,0 +1,85 @@ +package convert + +import ( + "cmp" + + "github.com/ollama/ollama/llm" +) + +type cohere2Model struct { + ModelParameters + MaxPositionEmbeddings uint32 `json:"max_position_embeddings"` + HiddenSize uint32 `json:"hidden_size"` + HiddenLayers uint32 `json:"num_hidden_layers"` + IntermediateSize uint32 `json:"intermediate_size"` + NumAttentionHeads uint32 `json:"num_attention_heads"` + NumKeyValueHeads uint32 `json:"num_key_value_heads"` + LayerNormEPS float32 `json:"layer_norm_eps"` + RopeTheta float32 `json:"rope_theta"` + UseQKNorm bool `json:"use_qk_norm"` + MaxLength uint32 `json:"model_max_length"` + LogitScale float32 `json:"logit_scale"` + NCtx uint32 `json:"n_ctx"` + SlidingWindow uint32 `json:"sliding_window"` + HeadDim uint32 `json:"head_dim"` + RotaryPct float32 `json:"rotary_pct"` + VocabSize uint32 `json:"vocab_size"` +} + +var _ ModelConverter = (*cohere2Model)(nil) + +func (p *cohere2Model) KV(t *Tokenizer) llm.KV { + kv := p.ModelParameters.KV(t) + kv["general.architecture"] = "cohere2" + kv["general.name"] = "C4Ai Command R7B" + kv["cohere2.context_length"] = cmp.Or(p.MaxLength, p.MaxPositionEmbeddings, p.NCtx) + kv["cohere2.embedding_length"] = p.HiddenSize + kv["cohere2.block_count"] = p.HiddenLayers + kv["cohere2.feed_forward_length"] = p.IntermediateSize + kv["cohere2.attention.head_count"] = p.NumAttentionHeads + kv["cohere2.attention.head_count_kv"] = p.NumKeyValueHeads + kv["cohere2.attention.key_length"] = p.HeadDim + kv["cohere2.attention.layer_norm_epsilon"] = p.LayerNormEPS + kv["cohere2.attention.sliding_window"] = p.SlidingWindow + kv["cohere2.attention.value_length"] = p.HeadDim + kv["cohere2.max_position_embeddings"] = cmp.Or(p.MaxLength, p.MaxPositionEmbeddings) + kv["cohere2.logit_scale"] = p.LogitScale + kv["cohere2.rope.dimension_count"] = uint32(p.RotaryPct * float32(p.HiddenSize / p.NumAttentionHeads)) + kv["cohere2.rope.freq_base"] = p.RopeTheta + kv["cohere2.rope.scaling.type"] = "none" + kv["cohere2.vocab_size"] = p.VocabSize + + return kv +} + +func (p *cohere2Model) Tensors(ts []Tensor) []llm.Tensor { + var out []llm.Tensor + for _, t := range ts { + out = append(out, llm.Tensor{ + Name: t.Name(), + Kind: t.Kind(), + Shape: t.Shape(), + WriterTo: t, + }) + } + + return out +} + +func (p *cohere2Model) Replacements() []string { + return []string{ + "self_attn.q_norm", "attn_q_norm", + "self_attn.k_norm", "attn_k_norm", + "model.layers", "blk", + "input_layernorm", "attn_norm", + "mlp.down_proj", "ffn_down", + "mlp.gate_proj", "ffn_gate", + "mlp.up_proj", "ffn_up", + "self_attn.k_proj", "attn_k", + "self_attn.o_proj", "attn_output", + "self_attn.q_proj", "attn_q", + "self_attn.v_proj", "attn_v", + "model.norm", "output_norm", + "model.embed_tokens", "token_embd", + } +} diff --git a/convert/convert_test.go b/convert/convert_test.go index bb213ce23..60e22ed36 100644 --- a/convert/convert_test.go +++ b/convert/convert_test.go @@ -29,6 +29,8 @@ type tensorData struct { Shape []int `json:"shape"` } +var generate string + func convertFull(t *testing.T, fsys fs.FS) (*os.File, llm.KV, *llm.Tensors) { t.Helper() @@ -91,6 +93,7 @@ func generateResultsJSON(t *testing.T, f *os.File, kv llm.KV, tensors *llm.Tenso func TestMain(m *testing.M) { var level slog.Level flag.TextVar(&level, "level", slog.LevelInfo, "log level") + flag.StringVar(&generate, "generate", "", "generate model data") flag.Parse() slog.SetLogLoggerLevel(level) os.Exit(m.Run()) @@ -110,6 +113,7 @@ func TestConvertModel(t *testing.T) { "gemma-2-9b-it", "Qwen2.5-0.5B-Instruct", "c4ai-command-r-v01", + "c4ai-command-r7b-12-2024", } for i := range cases { @@ -127,6 +131,19 @@ func TestConvertModel(t *testing.T) { f, kv, tensors := convertFull(t, os.DirFS(p)) actual := generateResultsJSON(t, f, kv, tensors) + if generate != "" && generate == tt { + outFile := filepath.Join("testdata", fmt.Sprintf("%s.json", tt)) + data, err := json.MarshalIndent(actual, "", " ") + if err != nil { + t.Fatal(err) + } + if err := os.WriteFile(outFile, data, 0644); err != nil { + t.Fatal(err) + } + t.Logf("Generated expected results for %s", tt) + return + } + expectFile, err := os.Open(filepath.Join("testdata", fmt.Sprintf("%s.json", tt))) if err != nil { t.Fatal(err) diff --git a/convert/testdata/c4ai-command-r7b-12-2024.json b/convert/testdata/c4ai-command-r7b-12-2024.json new file mode 100644 index 000000000..10b0c6612 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"84d019440139485383c6884b92ff63931aec9ce056686375224a52d1feb6e8b4", + "blk.9.attn_output.weight": "a01df3ef76a329a3b489f4bf0826d599cfa04c9d9432a20a67f7a96af184b969", + "blk.9.attn_q.weight": "0f36094187997195ea1963b101f62bab416c1eea5ff12c8c9ffd6f1ab096f27f", + "blk.9.attn_v.weight": "8f0c2b2feb34e76865521caf11f9ddd20ca3cb280fad007770915a362cc5ba4e", + "blk.9.ffn_down.weight": "648ee7a57d01d0476efb30c8141ddba79ed3c854b0991d04fc3d959dfc7b4aef", + "blk.9.ffn_gate.weight": "3a9d39fdf5fc6447b799f6f4d1b397190a52ffd90eaa10bc448a455c996a99db", + "blk.9.ffn_up.weight": "1c37f5feeb7f8efabb445b65b4ab3538be0f8d2c9742d1e4d3f916873fb4e9bb", + "cohere2.attention.head_count": "32", + "cohere2.attention.head_count_kv": "8", + "cohere2.attention.key_length": "128", + "cohere2.attention.layer_norm_epsilon": "1e-05", + "cohere2.attention.sliding_window": "4096", + "cohere2.attention.value_length": "128", + "cohere2.block_count": "32", + "cohere2.context_length": "8192", + "cohere2.embedding_length": "4096", + "cohere2.feed_forward_length": "14336", + "cohere2.logit_scale": "0.25", + "cohere2.max_position_embeddings": "8192", + "cohere2.rope.dimension_count": "128", + "cohere2.rope.freq_base": "50000", + "cohere2.rope.scaling.type": "none", + "cohere2.vocab_size": "256000", + "general.architecture": "cohere2", + "general.file_type": "1", + "general.name": "C4Ai Command R7B", + "general.parameter_count": "8028033024", + "general.quantization_version": "2", + "output_norm.weight": "0067549600670e489c3fd7c14b21c17fa0d23f2b91536acead95917f167eccda", + "token_embd.weight": "37de019700be8fa6b43ab0ed382c9c834fe84bc7cea4d758942ef56e933c3994", + "tokenizer.chat_template": "{% if documents %}\n{% set tools = [] %}\n{%- macro document_turn(documents) -%}\n{# format documents into chat turn #}\n\u003c|START_OF_TURN_TOKEN|\u003e\u003c|CHATBOT_TOKEN|\u003e\u003c|START_THINKING|\u003eI will look through the document to address the users needs.\u003c|END_THINKING|\u003e\u003c|START_ACTION|\u003e[\n {\"tool_call_id\": \"0\", \"tool_name\": \"direct-injected-document\", \"parameters\": {}}\n]\u003c|END_ACTION|\u003e\u003c|END_OF_TURN_TOKEN|\u003e\u003c|START_OF_TURN_TOKEN|\u003e\u003c|SYSTEM_TOKEN|\u003e\u003c|START_TOOL_RESULT|\u003e[\n {\n \"tool_call_id\": \"0\",\n \"results\": {\n{% for doc in documents %}\n \"{{ loop.index0 }}\": {{doc|tojson}}{% if not loop.last %},\n {% endif %}\n{% endfor %}\n\n },\n \"is_error\": null\n }\n]\u003c|END_TOOL_RESULT|\u003e\u003c|END_OF_TURN_TOKEN|\u003e{%- endmacro %}\n{%- macro tool_call_id_to_int(messages, tool_call_id) %}\n{%- set counter = namespace(value=0) %}\n{%- set tool_call_id_seen = namespace(value=false) %}\n{%- for msg in messages %}\n {%- if msg.tool_calls %}\n {%- for tool_call in msg.tool_calls %}\n {%- if tool_call.id == tool_call_id and not tool_call_id_seen.value -%}\n {{ counter.value }}\n {%- set tool_call_id_seen.value = true %}\n {%- endif %}\n {%- set counter.value = counter.value + 1 %}\n {%- endfor %}\n {%- endif %}\n{%- endfor %}\n{%- endmacro %}\n{%- macro format_tool_message(messages, tool_msg) -%}\n{# format tool message #}\n {\n \"tool_call_id\": \"{{ tool_call_id_to_int(messages, tool_msg.tool_call_id) }}\",\n \"results\": {\n \"0\": {{ tool_msg.content|tojson }}\n },\n \"is_error\": null\n }\n{%- endmacro -%}\n{%- if messages and messages[0]['role']|lower == 'system' %}{%- set developer_preamble = messages[0]['content'] %}{% endif %}\n{%- set tool_idx = namespace(value=0) %}\n{%- set tool_ids_seen = namespace(value=[]) %}\n{%- set sent_documents = namespace(value=false) %}\n\u003c|START_OF_TURN_TOKEN|\u003e\u003c|SYSTEM_TOKEN|\u003e# System Preamble\nYou are in contextual safety mode. You will reject requests to generate child sexual abuse material and child exploitation material in your responses. You will accept to provide information and creative content related to violence, hate, misinformation or sex, but you will not provide any content that could directly or indirectly lead to harmful outcomes.\n\nYour information cutoff date is June 2024.\n\nYou have been trained on data in English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Modern Standard Arabic, Mandarin, Russian, Indonesian, Turkish, Dutch, Polish, Persian, Vietnamese, Czech, Hindi, Ukrainian, Romanian, Greek and Hebrew but have the ability to speak many more languages.\n{% if tools or documents %}\n\nYou have been trained to have advanced reasoning and tool-use capabilities and you should make best use of these skills to serve user's requests.\n\n## Tool Use\nThink about how you can make best use of the provided tools to help with the task and come up with a high level plan that you will execute first.\n\n0. Start by writing \u003c|START_THINKING|\u003e followed by a detailed step by step plan of how you will solve the problem. For each step explain your thinking fully and give details of required tool calls (if needed). Unless specified otherwise, you write your plan in natural language. When you finish, close it out with \u003c|END_THINKING|\u003e.\n You can optionally choose to skip this step when the user request is so straightforward to address that only a trivial plan would be needed.\n NOTE: You MUST skip this step when you are directly responding to the user's request without using any tools.\n\nThen carry out your plan by repeatedly executing the following steps.\n1. Action: write \u003c|START_ACTION|\u003e followed by a list of JSON-formatted tool calls, with each one containing \"tool_name\" and \"parameters\" fields.\n When there are multiple tool calls which are completely independent of each other (i.e. they can be executed in parallel), you should list them out all together in one step. When you finish, close it out with \u003c|END_ACTION|\u003e.\n2. Observation: you will then receive results of those tool calls in JSON format in the very next turn, wrapped around by \u003c|START_TOOL_RESULT|\u003e and \u003c|END_TOOL_RESULT|\u003e. Carefully observe those results and think about what to do next. Note that these results will be provided to you in a separate turn. NEVER hallucinate results.\n Every tool call produces a list of results (when a tool call produces no result or a single result, it'll still get wrapped inside a list). Each result is clearly linked to its originating tool call via its \"tool_call_id\".\n3. Reflection: start the next turn by writing \u003c|START_THINKING|\u003e followed by what you've figured out so far, any changes you need to make to your plan, and what you will do next. When you finish, close it out with \u003c|END_THINKING|\u003e.\n You can optionally choose to skip this step when everything is going according to plan and no special pieces of information or reasoning chains need to be recorded.\n NOTE: You MUST skip this step when you are done with tool-use actions and are ready to respond to the user.\n\nYou can repeat the above 3 steps multiple times (could be 0 times too if no suitable tool calls are available or needed), until you decide it's time to finally respond to the user.\n\n4. Response: then break out of the loop and write \u003c|START_RESPONSE|\u003e followed by a piece of text which serves as a response to the user's last request. Use all previous tool calls and results to help you when formulating your response. When you finish, close it out with \u003c|END_RESPONSE|\u003e.\n{% if enable_citations %}\n\n## Grounding\nImportantly, note that \"Reflection\" and \"Response\" above can be grounded.\nGrounding means you associate pieces of texts (called \"spans\") with those specific tool results that support them (called \"sources\"). And you use a pair of tags \"\u003cco\u003e\" and \"\u003c/co\u003e\" to indicate when a span can be grounded onto a list of sources, listing them out in the closing tag. Sources from the same tool call are grouped together and listed as \"{tool_call_id}:[{list of result indices}]\", before they are joined together by \",\". E.g., \"\u003cco\u003espan\u003c/co: 0:[1,2],1:[0]\u003e\" means that \"span\" is supported by result 1 and 2 from \"tool_call_id=0\" as well as result 0 from \"tool_call_id=1\".\n{% endif %}\n\n## Available Tools\nHere is the list of tools that you have available to you.\nYou can ONLY use the tools listed here. When a tool is not listed below, it is NOT available and you should NEVER attempt to use it.\nEach tool is represented as a JSON object with fields like \"name\", \"description\", \"parameters\" (per JSON Schema), and optionally, \"responses\" (per JSON Schema).\n\n```json\n[\n{% if documents %}\n {\"name\": \"direct-injected-document\", \"description\": \"This is a special tool to directly inject user-uploaded documents into the chat as additional context. DO NOT use this tool by yourself!\", \"parameters\": {\"type\": \"object\", \"properties\": {}, \"required\": []}, \"responses\": {\"200\": {\"description\": \"Successfully returned a list of chunked text snippets from the directly uploaded documents.\", \"content\": {\"application/json\": {\"schema\": {\"type\": \"array\", \"items\": {\"type\": \"object\", \"required\": [\"url\", \"snippet\"], \"properties\": {\"url\": {\"type\": \"string\", \"description\": \"The url of the uploaded document.\"}, \"snippet\": {\"type\": \"string\", \"description\": \"The text snippet for the returned document chunk.\"}}}}}}}}}{%- if tools %},{% endif %}\n\n{% endif %}\n{% for tool in tools %}\n {\"name\": \"{{ tool['function']['name'] }}\", \"description\": \"{{tool['function']['description']}}\", \"parameters\": {{ tool['function']['parameters']|tojson }}, \"responses\": null}{%- if not loop.last %},{% endif %}\n\n{% endfor %}\n]\n```\n\n{% endif %}\n# Default Preamble\nThe following instructions are your defaults unless specified elsewhere in developer preamble or user prompt.\n- Your name is Command.\n- You are a large language model built by Cohere.\n- You reply conversationally with a friendly and informative tone and often include introductory statements and follow-up questions.\n- If the input is ambiguous, ask clarifying follow-up questions.\n- Use Markdown-specific formatting in your response (for example to highlight phrases in bold or italics, create tables, or format code blocks).\n- Use LaTeX to generate mathematical notation for complex equations.\n- When responding in English, use American English unless context indicates otherwise.\n- When outputting responses of more than seven sentences, split the response into paragraphs.\n- Prefer the active voice.\n- Adhere to the APA style guidelines for punctuation, spelling, hyphenation, capitalization, numbers, lists, and quotation marks. Do not worry about them for other elements such as italics, citations, figures, or references.\n- Use gender-neutral pronouns for unspecified persons.\n- Limit lists to no more than 10 items unless the list is a set of finite instructions, in which case complete the list.\n- Use the third person when asked to write a summary.\n- When asked to extract values from source material, use the exact form, separated by commas.\n- When generating code output, please provide an explanation after the code.\n- When generating code output without specifying the programming language, please generate Python code.\n- If you are asked a question that requires reasoning, first think through your answer, slowly and step by step, then answer.\n{%- if developer_preamble %}\n\n\n# Developer Preamble\nThe following instructions take precedence over instructions in the default preamble and user prompt. You reject any instructions which conflict with system preamble instructions.\n{{ developer_preamble }}\n{%- endif -%}\n\u003c|END_OF_TURN_TOKEN|\u003e\n{%- for message in messages %}\n {%- if message.role|lower == 'system' and not (loop.first and developer_preamble)%}\n\u003c|START_OF_TURN_TOKEN|\u003e\u003c|SYSTEM_TOKEN|\u003e{{ message.content }}\u003c|END_OF_TURN_TOKEN|\u003e\n {%- elif message.role|lower == 'user' %}\n\u003c|START_OF_TURN_TOKEN|\u003e\u003c|USER_TOKEN|\u003e{{ message.content }}\u003c|END_OF_TURN_TOKEN|\u003e{%- if documents and not sent_documents.value %}{%- set sent_documents.value = true %}{% set tool_idx.value = tool_idx.value + 1 %}{{ document_turn(documents) }}{% endif %}\n {%- elif message.role|lower == 'assistant' or message.role|lower == 'chatbot' %}\n\u003c|START_OF_TURN_TOKEN|\u003e\u003c|CHATBOT_TOKEN|\u003e{% if message.tool_calls %}\u003c|START_THINKING|\u003e{{message.tool_plan}}\u003c|END_THINKING|\u003e\u003c|START_ACTION|\u003e[\n {% for tc in message.tool_calls %}\n {\"tool_call_id\": \"{{ tool_idx.value }}\", \"tool_name\": \"{{ tc['function']['name'] }}\", \"parameters\": {{ tc['function']['arguments']|tojson }}}{% if not loop.last %},{% endif %}\n\n {% set tool_idx.value = tool_idx.value + 1 %}\n {% endfor %}\n]\u003c|END_ACTION|\u003e\u003c|END_OF_TURN_TOKEN|\u003e{% else %}\u003c|START_RESPONSE|\u003e{{message.content}}\u003c|END_RESPONSE|\u003e\u003c|END_OF_TURN_TOKEN|\u003e{% endif %}\n {% elif message.role|lower == 'tool' and message.tool_call_id not in tool_ids_seen.value %}\n\u003c|START_OF_TURN_TOKEN|\u003e\u003c|SYSTEM_TOKEN|\u003e\u003c|START_TOOL_RESULT|\u003e[\n{{ format_tool_message(messages, message) }}\n {%- for msg in messages[loop.index0 + 1:] %}\n {%- if msg.role|lower == 'tool' %},\n{{ format_tool_message(messages, msg) }}\n {%- set tool_ids_seen.value = tool_ids_seen.value + [msg.tool_call_id] %}\n {%- else %}\n {%- break %}\n {%- endif %}\n {%- endfor %}\n\n]\u003c|END_TOOL_RESULT|\u003e\u003c|END_OF_TURN_TOKEN|\u003e\n {%- endif %}\n{%- endfor %}\u003c|START_OF_TURN_TOKEN|\u003e\u003c|CHATBOT_TOKEN|\u003e\n{%- else -%}\n{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}\n {%- set system_message = messages[0]['content'] %}{% elif false == true %}\n {%- set loop_messages = messages %}{% set system_message = '' %}\n{%- else %}\n {%- set loop_messages = messages %}\n {%- set system_message = false %}\n{%- endif %}\n{%- if system_message != false -%}\n {{ '\u003c|START_OF_TURN_TOKEN|\u003e\u003c|SYSTEM_TOKEN|\u003e' + system_message + '\u003c|END_OF_TURN_TOKEN|\u003e' }}\n{%- else -%}\n {{ '\u003c|START_OF_TURN_TOKEN|\u003e\u003c|SYSTEM_TOKEN|\u003e\u003c|END_OF_TURN_TOKEN|\u003e' }}\n{%- endif %}\n{%- for message in loop_messages %}\n {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}\n {%- endif -%}\n {%- set content = message['content'] -%}\n {%- if message['role'] == 'user' -%}\n {{ '\u003c|START_OF_TURN_TOKEN|\u003e\u003c|USER_TOKEN|\u003e' + content.strip() + '\u003c|END_OF_TURN_TOKEN|\u003e' }}\n {%- elif message['role'] == 'assistant' -%}\n {{ '\u003c|START_OF_TURN_TOKEN|\u003e\u003c|CHATBOT_TOKEN|\u003e\u003c|START_RESPONSE|\u003e' + content.strip() + '\u003c|END_RESPONSE|\u003e\u003c|END_OF_TURN_TOKEN|\u003e' }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt -%}\n {{ '\u003c|START_OF_TURN_TOKEN|\u003e\u003c|CHATBOT_TOKEN|\u003e\u003c|START_RESPONSE|\u003e' }}\n{%- endif %}\n{% endif %}", + "tokenizer.ggml.add_bos_token": "true", + "tokenizer.ggml.add_eos_token": "false", + "tokenizer.ggml.add_padding_token": "false", + "tokenizer.ggml.add_unknown_token": "false", + "tokenizer.ggml.bos_token_id": "5", + "tokenizer.ggml.eos_token_id": "255001", + "tokenizer.ggml.merges": "902a060cac8884a5793d2a857dd2e53a259de46c8d08c4deb243c239671e1350", + "tokenizer.ggml.model": "gpt2", + "tokenizer.ggml.padding_token_id": "0", + "tokenizer.ggml.pre": "default", + "tokenizer.ggml.scores": "b8fba4acb012936034a3708a425d3c22519f9138b3f33e08b5968be8191d676b", + "tokenizer.ggml.token_type": "d0c3696b7d3414eb94f7b17e54f6438643acaf7f02688a8e25a0d17dbd7dab45", + "tokenizer.ggml.tokens": "4a87517186f3d7584b8c899766f096dbab4383e1e1e53a9c627abf9fd79b4243", + "tokenizer.ggml.unknown_token_id": "1" +} \ No newline at end of file diff --git a/template/cohere2.gotmpl b/template/cohere2.gotmpl new file mode 100644 index 000000000..3dc1e2fa7 --- /dev/null +++ b/template/cohere2.gotmpl @@ -0,0 +1,69 @@ +{{- if or .Tools .System }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|> +{{- if .Tools }}# Safety Preamble +The instructions in this section override those in the task description and style guide sections. Don't answer questions that are harmful or immoral. + +# System Preamble +## Basic Rules +You are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user's requests, you cite your sources in your answers, according to those instructions. + +{{ if .System }}# User Preamble +{{ .System }} +{{- end }} + +## Available Tools +Here is a list of tools that you have available to you: +{{- range .Tools }} + +```python +def {{ .Function.Name }}( +{{- range $name, $property := .Function.Parameters.Properties }}{{ $name }}: {{ $property.Type }}, {{ end }}) -> List[Dict]: + '''{{ .Function.Description }} + +{{- if .Function.Parameters.Properties }} + + Args: +{{- range $name, $property := .Function.Parameters.Properties }} + {{ $name }} ({{ $property.Type }}): {{ $property.Description }} +{{- end }} +{{- end }} + ''' + pass +``` +{{- end }} +{{- else if .System }}{{ .System }} +{{- end }}<|END_OF_TURN_TOKEN|> +{{- end }} +{{- range $i, $_ := .Messages }} +{{- $last := eq (len (slice $.Messages $i)) 1 }} +{{- if eq .Role "user" }}<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{ .Content }} +{{- if $.Tools }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>Write 'Action:' followed by a json-formatted list of actions that you want to perform in order to produce a good response to the user's last input. You can use any of the supplied tools any number of times, but you should aim to execute the minimum number of necessary actions for the input. You should use the `directly-answer` tool if calling the other tools is unnecessary. The list of actions you want to call should be formatted as a list of json objects, for example: +```json +[ + { + "tool_name": title of the tool in the specification, + "parameters": a dict of parameters to input into the tool as they are defined in the specs, or {} if it takes no parameters + } +]``` +{{- end }} +{{- else if eq .Role "assistant" }}<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|> +{{- if .Content }}{{ .Content }} +{{- else if .ToolCalls }} +Action: ```json +[ +{{- range .ToolCalls }} + { + "tool_name": "{{ .Function.Name }}", + "parameters": {{ .Function.Arguments }} + } +{{- end }} +]``` +{{- end }} +{{- else if eq .Role "tool" }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|> +console_output: {{ .Content }} + +{{- end }} +{{- if not $last }}<|END_OF_TURN_TOKEN|> +{{- else }} +{{- if ne .Role "assistant" }}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>{{- end }} +{{- end }} +{{- end }} diff --git a/template/index.json b/template/index.json index 7a27747c5..dda639949 100644 --- a/template/index.json +++ b/template/index.json @@ -142,5 +142,9 @@ { "template": "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif false == true %}{% set loop_messages = messages %}{% set system_message = 'You are Command-R, a brilliant, sophisticated, AI-assistant trained to assist human users by providing thorough responses. You are trained by Cohere.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% if system_message != false %}{{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% elif message['role'] == 'assistant' %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}{% endif %}", "name": "command-r" + }, + { + "template": "{% if documents %}\n{% set tools = [] %}\n{%- macro document_turn(documents) -%}\n{# format documents into chat turn #}\n<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_THINKING|>I will look through the document to address the users needs.<|END_THINKING|><|START_ACTION|>[\n {\"tool_call_id\": \"0\", \"tool_name\": \"direct-injected-document\", \"parameters\": {}}\n]<|END_ACTION|><|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|START_TOOL_RESULT|>[\n {\n \"tool_call_id\": \"0\",\n \"results\": {\n{% for doc in documents %}\n \"{{ loop.index0 }}\": {{doc|tojson}}{% if not loop.last %},\n {% endif %}\n{% endfor %}\n\n },\n \"is_error\": null\n }\n]<|END_TOOL_RESULT|><|END_OF_TURN_TOKEN|>{%- endmacro %}\n{%- macro tool_call_id_to_int(messages, tool_call_id) %}\n{%- set counter = namespace(value=0) %}\n{%- set tool_call_id_seen = namespace(value=false) %}\n{%- for msg in messages %}\n {%- if msg.tool_calls %}\n {%- for tool_call in msg.tool_calls %}\n {%- if tool_call.id == tool_call_id and not tool_call_id_seen.value -%}\n {{ counter.value }}\n {%- set tool_call_id_seen.value = true %}\n {%- endif %}\n {%- set counter.value = counter.value + 1 %}\n {%- endfor %}\n {%- endif %}\n{%- endfor %}\n{%- endmacro %}\n{%- macro format_tool_message(messages, tool_msg) -%}\n{# format tool message #}\n {\n \"tool_call_id\": \"{{ tool_call_id_to_int(messages, tool_msg.tool_call_id) }}\",\n \"results\": {\n \"0\": {{ tool_msg.content|tojson }}\n },\n \"is_error\": null\n }\n{%- endmacro -%}\n{%- if messages and messages[0]['role']|lower == 'system' %}{%- set developer_preamble = messages[0]['content'] %}{% endif %}\n{%- set tool_idx = namespace(value=0) %}\n{%- set tool_ids_seen = namespace(value=[]) %}\n{%- set sent_documents = namespace(value=false) %}\n<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|># System Preamble\nYou are in contextual safety mode. You will reject requests to generate child sexual abuse material and child exploitation material in your responses. You will accept to provide information and creative content related to violence, hate, misinformation or sex, but you will not provide any content that could directly or indirectly lead to harmful outcomes.\n\nYour information cutoff date is June 2024.\n\nYou have been trained on data in English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Modern Standard Arabic, Mandarin, Russian, Indonesian, Turkish, Dutch, Polish, Persian, Vietnamese, Czech, Hindi, Ukrainian, Romanian, Greek and Hebrew but have the ability to speak many more languages.\n{% if tools or documents %}\n\nYou have been trained to have advanced reasoning and tool-use capabilities and you should make best use of these skills to serve user's requests.\n\n## Tool Use\nThink about how you can make best use of the provided tools to help with the task and come up with a high level plan that you will execute first.\n\n0. Start by writing <|START_THINKING|> followed by a detailed step by step plan of how you will solve the problem. For each step explain your thinking fully and give details of required tool calls (if needed). Unless specified otherwise, you write your plan in natural language. When you finish, close it out with <|END_THINKING|>.\n You can optionally choose to skip this step when the user request is so straightforward to address that only a trivial plan would be needed.\n NOTE: You MUST skip this step when you are directly responding to the user's request without using any tools.\n\nThen carry out your plan by repeatedly executing the following steps.\n1. Action: write <|START_ACTION|> followed by a list of JSON-formatted tool calls, with each one containing \"tool_name\" and \"parameters\" fields.\n When there are multiple tool calls which are completely independent of each other (i.e. they can be executed in parallel), you should list them out all together in one step. When you finish, close it out with <|END_ACTION|>.\n2. Observation: you will then receive results of those tool calls in JSON format in the very next turn, wrapped around by <|START_TOOL_RESULT|> and <|END_TOOL_RESULT|>. Carefully observe those results and think about what to do next. Note that these results will be provided to you in a separate turn. NEVER hallucinate results.\n Every tool call produces a list of results (when a tool call produces no result or a single result, it'll still get wrapped inside a list). Each result is clearly linked to its originating tool call via its \"tool_call_id\".\n3. Reflection: start the next turn by writing <|START_THINKING|> followed by what you've figured out so far, any changes you need to make to your plan, and what you will do next. When you finish, close it out with <|END_THINKING|>.\n You can optionally choose to skip this step when everything is going according to plan and no special pieces of information or reasoning chains need to be recorded.\n NOTE: You MUST skip this step when you are done with tool-use actions and are ready to respond to the user.\n\nYou can repeat the above 3 steps multiple times (could be 0 times too if no suitable tool calls are available or needed), until you decide it's time to finally respond to the user.\n\n4. Response: then break out of the loop and write <|START_RESPONSE|> followed by a piece of text which serves as a response to the user's last request. Use all previous tool calls and results to help you when formulating your response. When you finish, close it out with <|END_RESPONSE|>.\n{% if enable_citations %}\n\n## Grounding\nImportantly, note that \"Reflection\" and \"Response\" above can be grounded.\nGrounding means you associate pieces of texts (called \"spans\") with those specific tool results that support them (called \"sources\"). And you use a pair of tags \"\" and \"\" to indicate when a span can be grounded onto a list of sources, listing them out in the closing tag. Sources from the same tool call are grouped together and listed as \"{tool_call_id}:[{list of result indices}]\", before they are joined together by \",\". E.g., \"span\" means that \"span\" is supported by result 1 and 2 from \"tool_call_id=0\" as well as result 0 from \"tool_call_id=1\".\n{% endif %}\n\n## Available Tools\nHere is the list of tools that you have available to you.\nYou can ONLY use the tools listed here. When a tool is not listed below, it is NOT available and you should NEVER attempt to use it.\nEach tool is represented as a JSON object with fields like \"name\", \"description\", \"parameters\" (per JSON Schema), and optionally, \"responses\" (per JSON Schema).\n\n```json\n[\n{% if documents %}\n {\"name\": \"direct-injected-document\", \"description\": \"This is a special tool to directly inject user-uploaded documents into the chat as additional context. DO NOT use this tool by yourself!\", \"parameters\": {\"type\": \"object\", \"properties\": {}, \"required\": []}, \"responses\": {\"200\": {\"description\": \"Successfully returned a list of chunked text snippets from the directly uploaded documents.\", \"content\": {\"application/json\": {\"schema\": {\"type\": \"array\", \"items\": {\"type\": \"object\", \"required\": [\"url\", \"snippet\"], \"properties\": {\"url\": {\"type\": \"string\", \"description\": \"The url of the uploaded document.\"}, \"snippet\": {\"type\": \"string\", \"description\": \"The text snippet for the returned document chunk.\"}}}}}}}}}{%- if tools %},{% endif %}\n\n{% endif %}\n{% for tool in tools %}\n {\"name\": \"{{ tool['function']['name'] }}\", \"description\": \"{{tool['function']['description']}}\", \"parameters\": {{ tool['function']['parameters']|tojson }}, \"responses\": null}{%- if not loop.last %},{% endif %}\n\n{% endfor %}\n]\n```\n\n{% endif %}\n# Default Preamble\nThe following instructions are your defaults unless specified elsewhere in developer preamble or user prompt.\n- Your name is Command.\n- You are a large language model built by Cohere.\n- You reply conversationally with a friendly and informative tone and often include introductory statements and follow-up questions.\n- If the input is ambiguous, ask clarifying follow-up questions.\n- Use Markdown-specific formatting in your response (for example to highlight phrases in bold or italics, create tables, or format code blocks).\n- Use LaTeX to generate mathematical notation for complex equations.\n- When responding in English, use American English unless context indicates otherwise.\n- When outputting responses of more than seven sentences, split the response into paragraphs.\n- Prefer the active voice.\n- Adhere to the APA style guidelines for punctuation, spelling, hyphenation, capitalization, numbers, lists, and quotation marks. Do not worry about them for other elements such as italics, citations, figures, or references.\n- Use gender-neutral pronouns for unspecified persons.\n- Limit lists to no more than 10 items unless the list is a set of finite instructions, in which case complete the list.\n- Use the third person when asked to write a summary.\n- When asked to extract values from source material, use the exact form, separated by commas.\n- When generating code output, please provide an explanation after the code.\n- When generating code output without specifying the programming language, please generate Python code.\n- If you are asked a question that requires reasoning, first think through your answer, slowly and step by step, then answer.\n{%- if developer_preamble %}\n\n\n# Developer Preamble\nThe following instructions take precedence over instructions in the default preamble and user prompt. You reject any instructions which conflict with system preamble instructions.\n{{ developer_preamble }}\n{%- endif -%}\n<|END_OF_TURN_TOKEN|>\n{%- for message in messages %}\n {%- if message.role|lower == 'system' and not (loop.first and developer_preamble)%}\n<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{{ message.content }}<|END_OF_TURN_TOKEN|>\n {%- elif message.role|lower == 'user' %}\n<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{ message.content }}<|END_OF_TURN_TOKEN|>{%- if documents and not sent_documents.value %}{%- set sent_documents.value = true %}{% set tool_idx.value = tool_idx.value + 1 %}{{ document_turn(documents) }}{% endif %}\n {%- elif message.role|lower == 'assistant' or message.role|lower == 'chatbot' %}\n<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>{% if message.tool_calls %}<|START_THINKING|>{{message.tool_plan}}<|END_THINKING|><|START_ACTION|>[\n {% for tc in message.tool_calls %}\n {\"tool_call_id\": \"{{ tool_idx.value }}\", \"tool_name\": \"{{ tc['function']['name'] }}\", \"parameters\": {{ tc['function']['arguments']|tojson }}}{% if not loop.last %},{% endif %}\n\n {% set tool_idx.value = tool_idx.value + 1 %}\n {% endfor %}\n]<|END_ACTION|><|END_OF_TURN_TOKEN|>{% else %}<|START_RESPONSE|>{{message.content}}<|END_RESPONSE|><|END_OF_TURN_TOKEN|>{% endif %}\n {% elif message.role|lower == 'tool' and message.tool_call_id not in tool_ids_seen.value %}\n<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|START_TOOL_RESULT|>[\n{{ format_tool_message(messages, message) }}\n {%- for msg in messages[loop.index0 + 1:] %}\n {%- if msg.role|lower == 'tool' %},\n{{ format_tool_message(messages, msg) }}\n {%- set tool_ids_seen.value = tool_ids_seen.value + [msg.tool_call_id] %}\n {%- else %}\n {%- break %}\n {%- endif %}\n {%- endfor %}\n\n]<|END_TOOL_RESULT|><|END_OF_TURN_TOKEN|>\n {%- endif %}\n{%- endfor %}<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>\n{%- else -%}\n{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}\n {%- set system_message = messages[0]['content'] %}{% elif false == true %}\n {%- set loop_messages = messages %}{% set system_message = '' %}\n{%- else %}\n {%- set loop_messages = messages %}\n {%- set system_message = false %}\n{%- endif %}\n{%- if system_message != false -%}\n {{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}\n{%- else -%}\n {{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|END_OF_TURN_TOKEN|>' }}\n{%- endif %}\n{%- for message in loop_messages %}\n {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}\n {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}\n {%- endif -%}\n {%- set content = message['content'] -%}\n {%- if message['role'] == 'user' -%}\n {{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}\n {%- elif message['role'] == 'assistant' -%}\n {{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>' + content.strip() + '<|END_RESPONSE|><|END_OF_TURN_TOKEN|>' }}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt -%}\n {{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>' }}\n{%- endif %}\n{% endif %}", + "name": "cohere2" } ] diff --git a/template/testdata/cohere2.gotmpl/system-user-assistant-user b/template/testdata/cohere2.gotmpl/system-user-assistant-user new file mode 100644 index 000000000..434e0e4fc --- /dev/null +++ b/template/testdata/cohere2.gotmpl/system-user-assistant-user @@ -0,0 +1 @@ +<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>You are a helpful assistant.<|END_OF_TURN_TOKEN|><|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hello, how are you?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>I'm doing great. How can I help you today?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>I'd like to show off how chat templating works!<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|> diff --git a/template/testdata/cohere2.gotmpl/user b/template/testdata/cohere2.gotmpl/user new file mode 100644 index 000000000..49908a620 --- /dev/null +++ b/template/testdata/cohere2.gotmpl/user @@ -0,0 +1 @@ +<|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hello, how are you?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|> diff --git a/template/testdata/cohere2.gotmpl/user-assistant-user b/template/testdata/cohere2.gotmpl/user-assistant-user new file mode 100644 index 000000000..5aec07da6 --- /dev/null +++ b/template/testdata/cohere2.gotmpl/user-assistant-user @@ -0,0 +1 @@ +<|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hello, how are you?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>I'm doing great. How can I help you today?<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>I'd like to show off how chat templating works!<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>