tool-call: support Command R7B (+ return tool_plan "thoughts" in API) (#11585)
* `tool-call`: support Command R7B (w/ tool_plan return) * `tool-call`: cleaner preservation of tokens + warn when likely bad chat template override * `tool-call`: test cleanup / handle lazy grammar triggers
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Olivier Chafik
GitHub
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8 changed files with 420 additions and 56 deletions
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@ -1128,6 +1128,7 @@ curl http://localhost:8080/v1/chat/completions \
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- Hermes 2/3, Qwen 2.5
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- Mistral Nemo
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- Firefunction v2
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- Command R7B
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- DeepSeek R1 (WIP / seems reluctant to call any tools?)
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<details>
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@ -1202,21 +1203,28 @@ curl http://localhost:8080/v1/chat/completions \
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```shell
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# Native support:
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llama-server --jinja -fa -hf bartowski/Qwen2.5-7B-Instruct-GGUF:Q4_K_M
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llama-server --jinja -fa -hf bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q4_K_M
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llama-server --jinja -fa -hf bartowski/Llama-3.2-3B-Instruct-GGUF:Q6_K
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llama-server --jinja -fa -hf bartowski/Mistral-Nemo-Instruct-2407-GGUF:Q6_K_L
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llama-server --jinja -fa -hf bartowski/functionary-small-v3.2-GGUF:Q4_K_M
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llama-server --jinja -fa -hf bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M \
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--chat-template-file <( python scripts/get_chat_template.py NousResearch/Hermes-2-Pro-Llama-3-8B )
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llama-server --jinja -fa -hf bartowski/Llama-3.3-70B-Instruct-GGUF:Q4_K_M
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# Native support requires the right template for these GGUFs:
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llama-server --jinja -fa -hf bartowski/Hermes-2-Pro-Llama-3-8B-GGUF:Q4_K_M \
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--chat-template-file <( python scripts/get_chat_template.py NousResearch/Hermes-2-Pro-Llama-3-8B tool_use )
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llama-server --jinja -fa -hf bartowski/Hermes-3-Llama-3.1-8B-GGUF:Q4_K_M \
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--chat-template-file <( python scripts/get_chat_template.py NousResearch/Hermes-3-Llama-3.1-8B tool_use )
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llama-server --jinja -fa -hf bartowski/firefunction-v2-GGUF -hff firefunction-v2-IQ1_M.gguf \
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--chat-template-file <( python scripts/get_chat_template.py fireworks-ai/firellama-3-firefunction-v2 )
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--chat-template-file <( python scripts/get_chat_template.py fireworks-ai/llama-3-firefunction-v2 tool_use )
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llama-server --jinja -fa -hf bartowski/c4ai-command-r7b-12-2024-GGUF:Q6_K_L \
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--chat-template-file <( python scripts/get_chat_template.py CohereForAI/c4ai-command-r7b-12-2024 tool_use )
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# Generic format support
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llama-server --jinja -fa -hf bartowski/Phi-3.5-mini-instruct-GGUF:Q4_K_M
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llama-server --jinja -fa -hf bartowski/gemma-2-2b-it-GGUF:Q4_K_M
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llama-server --jinja -fa -hf bartowski/phi-4-GGUF:Q4_0
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llama-server --jinja -fa -hf bartowski/gemma-2-2b-it-GGUF:Q8_0
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llama-server --jinja -fa -hf bartowski/c4ai-command-r-v01-GGUF:Q2_K
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```
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- Test in CLI:
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@ -131,6 +131,11 @@ struct slot_params {
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lora.push_back({{"id", i}, {"scale", this->lora[i].scale}});
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}
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std::vector<std::string> grammar_trigger_words;
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for (const auto & trigger : sampling.grammar_trigger_words) {
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grammar_trigger_words.push_back(trigger.word);
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}
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return json {
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{"n_predict", n_predict}, // Server configured n_predict
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{"seed", sampling.seed},
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@ -165,8 +170,9 @@ struct slot_params {
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{"n_probs", sampling.n_probs},
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{"min_keep", sampling.min_keep},
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{"grammar", sampling.grammar},
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// {"grammar_trigger_words", sampling.grammar_trigger_words},
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{"grammar_trigger_words", grammar_trigger_words},
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{"grammar_trigger_tokens", sampling.grammar_trigger_tokens},
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{"preserved_tokens", sampling.preserved_tokens},
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{"samplers", samplers},
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{"speculative.n_max", speculative.n_max},
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{"speculative.n_min", speculative.n_min},
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@ -363,12 +369,26 @@ struct server_task {
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if (ids.size() == 1) {
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LOG_DBG("Grammar trigger token: %d (`%s`)\n", ids[0], trigger.word.c_str());
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params.sampling.grammar_trigger_tokens.push_back(ids[0]);
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params.sampling.preserved_tokens.insert(ids[0]);
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continue;
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}
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LOG_DBG("Grammar trigger word: `%s`\n", trigger.word.c_str());
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params.sampling.grammar_trigger_words.push_back(trigger);
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}
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}
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const auto preserved_tokens = data.find("preserved_tokens");
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if (preserved_tokens != data.end()) {
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for (const auto & t : *preserved_tokens) {
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auto ids = common_tokenize(vocab, t.get<std::string>(), /* add_special= */ false, /* parse_special= */ true);
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if (ids.size() == 1) {
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LOG_DBG("Preserved token: %d\n", ids[0]);
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params.sampling.preserved_tokens.insert(ids[0]);
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} else {
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// This may happen when using a tool call style meant for a model with special tokens to preserve on a model without said tokens.
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LOG_WRN("Not preserved because more than 1 token (wrong chat template override?): %s\n", t.get<std::string>().c_str());
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}
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}
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}
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if (params.sampling.grammar_lazy) {
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GGML_ASSERT(params.sampling.grammar_trigger_tokens.size() > 0 || params.sampling.grammar_trigger_words.size() > 0);
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}
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@ -695,19 +715,19 @@ struct server_task_result_cmpl_final : server_task_result {
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json to_json_oaicompat_chat() {
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std::string finish_reason = "length";
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common_chat_msg message;
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common_chat_msg msg;
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if (stop == STOP_TYPE_WORD || stop == STOP_TYPE_EOS) {
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LOG_DBG("Parsing chat message: %s\n", content.c_str());
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message = common_chat_parse(content, oaicompat_chat_format);
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finish_reason = message.tool_calls.empty() ? "stop" : "tool_calls";
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msg = common_chat_parse(content, oaicompat_chat_format);
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finish_reason = msg.tool_calls.empty() ? "stop" : "tool_calls";
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} else {
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message.content = content;
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msg.content = content;
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}
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json tool_calls;
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if (!message.tool_calls.empty()) {
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if (!msg.tool_calls.empty()) {
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tool_calls = json::array();
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for (const auto & tc : message.tool_calls) {
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for (const auto & tc : msg.tool_calls) {
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tool_calls.push_back({
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{"type", "function"},
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{"function", {
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@ -719,14 +739,19 @@ struct server_task_result_cmpl_final : server_task_result {
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}
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}
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json message {
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{"content", msg.content},
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{"tool_calls", tool_calls},
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{"role", "assistant"},
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};
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if (!msg.tool_plan.empty()) {
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message["tool_plan"] = msg.tool_plan;
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}
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json choice {
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{"finish_reason", finish_reason},
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{"index", 0},
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{"message", json {
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{"content", message.content},
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{"tool_calls", tool_calls},
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{"role", "assistant"},
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}},
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{"message", message},
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};
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if (!stream && probs_output.size() > 0) {
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@ -2833,8 +2858,7 @@ struct server_context {
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server_slot * slot_batched = nullptr;
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auto accept_special_token = [&](server_slot & slot, llama_token token) {
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const auto & trigger_tokens = slot.params.sampling.grammar_trigger_tokens;
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return params_base.special || std::find(trigger_tokens.begin(), trigger_tokens.end(), token) != trigger_tokens.end();
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return params_base.special || slot.params.sampling.preserved_tokens.find(token) != slot.params.sampling.preserved_tokens.end();
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};
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// frist, add sampled tokens from any ongoing sequences
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@ -662,6 +662,7 @@ static json oaicompat_completion_params_parse(
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});
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}
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llama_params["grammar_triggers"] = grammar_triggers;
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llama_params["preserved_tokens"] = chat_params.preserved_tokens;
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for (const auto & stop : chat_params.additional_stops) {
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llama_params["stop"].push_back(stop);
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}
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