forked from SciSharp/BotSharp
-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathChatCompletionProvider.cs
More file actions
427 lines (367 loc) · 17.5 KB
/
ChatCompletionProvider.cs
File metadata and controls
427 lines (367 loc) · 17.5 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
using Azure;
using BotSharp.Abstraction.Files.Utilities;
using BotSharp.Abstraction.Hooks;
using OpenAI.Chat;
using System.ClientModel;
namespace BotSharp.Plugin.AzureOpenAI.Providers.Chat;
public class ChatCompletionProvider : IChatCompletion
{
protected readonly AzureOpenAiSettings _settings;
protected readonly IServiceProvider _services;
protected readonly ILogger<ChatCompletionProvider> _logger;
private List<string> renderedInstructions = [];
protected string _model;
public virtual string Provider => "azure-openai";
public string Model => _model;
public ChatCompletionProvider(
AzureOpenAiSettings settings,
ILogger<ChatCompletionProvider> logger,
IServiceProvider services)
{
_settings = settings;
_logger = logger;
_services = services;
}
public async Task<RoleDialogModel> GetChatCompletions(Agent agent, List<RoleDialogModel> conversations)
{
var contentHooks = _services.GetHooks<IContentGeneratingHook>(agent.Id);
// Before chat completion hook
foreach (var hook in contentHooks)
{
await hook.BeforeGenerating(agent, conversations);
}
var client = ProviderHelper.GetClient(Provider, _model, _services);
var chatClient = client.GetChatClient(_model);
var (prompt, messages, options) = PrepareOptions(agent, conversations);
ClientResult<ChatCompletion>? response = null;
ChatCompletion value = default;
RoleDialogModel responseMessage;
try
{
response = chatClient.CompleteChat(messages, options);
value = response.Value;
var reason = value.FinishReason;
var content = value.Content;
var text = content.FirstOrDefault()?.Text ?? string.Empty;
if (reason == ChatFinishReason.FunctionCall || reason == ChatFinishReason.ToolCalls)
{
var toolCall = value.ToolCalls.FirstOrDefault();
responseMessage = new RoleDialogModel(AgentRole.Function, text)
{
CurrentAgentId = agent.Id,
MessageId = conversations.LastOrDefault()?.MessageId ?? string.Empty,
FunctionName = toolCall?.FunctionName,
FunctionArgs = toolCall?.FunctionArguments?.ToString(),
RenderedInstruction = string.Join("\r\n", renderedInstructions)
};
// Somethings LLM will generate a function name with agent name.
if (!string.IsNullOrEmpty(responseMessage.FunctionName))
{
responseMessage.FunctionName = responseMessage.FunctionName.Split('.').Last();
}
}
else
{
responseMessage = new RoleDialogModel(AgentRole.Assistant, text)
{
CurrentAgentId = agent.Id,
MessageId = conversations.LastOrDefault()?.MessageId ?? string.Empty,
RenderedInstruction = string.Join("\r\n", renderedInstructions)
};
}
}
catch (ClientResultException ex)
{
_logger.LogError(ex, ex.Message);
responseMessage = new RoleDialogModel(AgentRole.Assistant, "The response was filtered due to the prompt triggering our content management policy. Please modify your prompt and retry.")
{
CurrentAgentId = agent.Id,
MessageId = conversations.LastOrDefault()?.MessageId ?? string.Empty,
RenderedInstruction = string.Join("\r\n", renderedInstructions)
};
}
catch (Exception ex)
{
_logger.LogError(ex, ex.Message);
responseMessage = new RoleDialogModel(AgentRole.Assistant, ex.Message)
{
CurrentAgentId = agent.Id,
MessageId = conversations.LastOrDefault()?.MessageId ?? string.Empty,
RenderedInstruction = string.Join("\r\n", renderedInstructions)
};
}
var tokenUsage = response?.Value?.Usage;
var inputTokenDetails = response?.Value?.Usage?.InputTokenDetails;
// After chat completion hook
foreach (var hook in contentHooks)
{
await hook.AfterGenerated(responseMessage, new TokenStatsModel
{
Prompt = prompt,
Provider = Provider,
Model = _model,
TextInputTokens = (tokenUsage?.InputTokenCount ?? 0) - (inputTokenDetails?.CachedTokenCount ?? 0),
CachedTextInputTokens = inputTokenDetails?.CachedTokenCount ?? 0,
TextOutputTokens = tokenUsage?.OutputTokenCount ?? 0
});
}
return responseMessage;
}
public async Task<bool> GetChatCompletionsAsync(Agent agent,
List<RoleDialogModel> conversations,
Func<RoleDialogModel, Task> onMessageReceived,
Func<RoleDialogModel, Task> onFunctionExecuting)
{
var hooks = _services.GetHooks<IContentGeneratingHook>(agent.Id);
// Before chat completion hook
foreach (var hook in hooks)
{
await hook.BeforeGenerating(agent, conversations);
}
var client = ProviderHelper.GetClient(Provider, _model, _services);
var chatClient = client.GetChatClient(_model);
var (prompt, messages, options) = PrepareOptions(agent, conversations);
var response = await chatClient.CompleteChatAsync(messages, options);
var value = response.Value;
var reason = value.FinishReason;
var content = value.Content;
var text = content.FirstOrDefault()?.Text ?? string.Empty;
var msg = new RoleDialogModel(AgentRole.Assistant, text)
{
CurrentAgentId = agent.Id,
RenderedInstruction = string.Join("\r\n", renderedInstructions)
};
var tokenUsage = response?.Value?.Usage;
var inputTokenDetails = response?.Value?.Usage?.InputTokenDetails;
// After chat completion hook
foreach (var hook in hooks)
{
await hook.AfterGenerated(msg, new TokenStatsModel
{
Prompt = prompt,
Provider = Provider,
Model = _model,
TextInputTokens = (tokenUsage?.InputTokenCount ?? 0) - (inputTokenDetails?.CachedTokenCount ?? 0),
CachedTextInputTokens = inputTokenDetails?.CachedTokenCount ?? 0,
TextOutputTokens = tokenUsage?.OutputTokenCount ?? 0
});
}
if (reason == ChatFinishReason.FunctionCall || reason == ChatFinishReason.ToolCalls)
{
var toolCall = value.ToolCalls?.FirstOrDefault();
_logger.LogInformation($"[{agent.Name}]: {toolCall?.FunctionName}({toolCall?.FunctionArguments})");
var funcContextIn = new RoleDialogModel(AgentRole.Function, text)
{
CurrentAgentId = agent.Id,
MessageId = conversations.LastOrDefault()?.MessageId ?? string.Empty,
ToolCallId = toolCall?.Id,
FunctionName = toolCall?.FunctionName,
FunctionArgs = toolCall?.FunctionArguments?.ToString(),
RenderedInstruction = string.Join("\r\n", renderedInstructions)
};
// Somethings LLM will generate a function name with agent name.
if (!string.IsNullOrEmpty(funcContextIn.FunctionName))
{
funcContextIn.FunctionName = funcContextIn.FunctionName.Split('.').Last();
}
// Execute functions
await onFunctionExecuting(funcContextIn);
}
else
{
// Text response received
await onMessageReceived(msg);
}
return true;
}
public async Task<bool> GetChatCompletionsStreamingAsync(Agent agent, List<RoleDialogModel> conversations, Func<RoleDialogModel, Task> onMessageReceived)
{
var client = ProviderHelper.GetClient(Provider, _model, _services);
var chatClient = client.GetChatClient(_model);
var (prompt, messages, options) = PrepareOptions(agent, conversations);
var response = chatClient.CompleteChatStreamingAsync(messages, options);
await foreach (var choice in response)
{
if (choice.FinishReason == ChatFinishReason.FunctionCall || choice.FinishReason == ChatFinishReason.ToolCalls)
{
var update = choice.ToolCallUpdates?.FirstOrDefault()?.FunctionArgumentsUpdate?.ToString() ?? string.Empty;
Console.Write(update);
await onMessageReceived(new RoleDialogModel(AgentRole.Assistant, update)
{
RenderedInstruction = string.Join("\r\n", renderedInstructions)
});
continue;
}
if (choice.ContentUpdate.IsNullOrEmpty()) continue;
_logger.LogInformation(choice.ContentUpdate[0]?.Text);
await onMessageReceived(new RoleDialogModel(choice.Role?.ToString() ?? ChatMessageRole.Assistant.ToString(), choice.ContentUpdate[0]?.Text ?? string.Empty)
{
RenderedInstruction = string.Join("\r\n", renderedInstructions)
});
}
return true;
}
protected (string, IEnumerable<ChatMessage>, ChatCompletionOptions) PrepareOptions(Agent agent, List<RoleDialogModel> conversations)
{
var agentService = _services.GetRequiredService<IAgentService>();
var state = _services.GetRequiredService<IConversationStateService>();
var fileStorage = _services.GetRequiredService<IFileStorageService>();
var settingsService = _services.GetRequiredService<ILlmProviderService>();
var settings = settingsService.GetSetting(Provider, _model);
var allowMultiModal = settings != null && settings.MultiModal;
renderedInstructions = [];
var messages = new List<ChatMessage>();
var temperature = float.Parse(state.GetState("temperature", "0.0"));
var maxTokens = int.TryParse(state.GetState("max_tokens"), out var tokens)
? tokens
: agent.LlmConfig?.MaxOutputTokens ?? LlmConstant.DEFAULT_MAX_OUTPUT_TOKEN;
var options = new ChatCompletionOptions()
{
Temperature = temperature,
MaxOutputTokenCount = maxTokens
};
var functions = agent.Functions.Concat(agent.SecondaryFunctions ?? []);
foreach (var function in functions)
{
if (!agentService.RenderFunction(agent, function)) continue;
var property = agentService.RenderFunctionProperty(agent, function);
options.Tools.Add(ChatTool.CreateFunctionTool(
functionName: function.Name,
functionDescription: function.Description,
functionParameters: BinaryData.FromObjectAsJson(property)));
}
if (!string.IsNullOrEmpty(agent.Instruction) || !agent.SecondaryInstructions.IsNullOrEmpty())
{
var instruction = agentService.RenderedInstruction(agent);
renderedInstructions.Add(instruction);
messages.Add(new SystemChatMessage(instruction));
}
if (!string.IsNullOrEmpty(agent.Knowledges))
{
messages.Add(new SystemChatMessage(agent.Knowledges));
}
var samples = ProviderHelper.GetChatSamples(agent.Samples);
foreach (var sample in samples)
{
messages.Add(sample.Role == AgentRole.User ? new UserChatMessage(sample.Content) : new AssistantChatMessage(sample.Content));
}
var filteredMessages = conversations.Select(x => x).ToList();
var firstUserMsgIdx = filteredMessages.FindIndex(x => x.Role == AgentRole.User);
if (firstUserMsgIdx > 0)
{
filteredMessages = filteredMessages.Where((_, idx) => idx >= firstUserMsgIdx).ToList();
}
foreach (var message in filteredMessages)
{
if (message.Role == AgentRole.Function)
{
messages.Add(new AssistantChatMessage(new List<ChatToolCall>
{
ChatToolCall.CreateFunctionToolCall(message.FunctionName, message.FunctionName, BinaryData.FromString(message.FunctionArgs ?? string.Empty))
}));
messages.Add(new ToolChatMessage(message.FunctionName, message.Content));
}
else if (message.Role == AgentRole.User)
{
var text = !string.IsNullOrWhiteSpace(message.Payload) ? message.Payload : message.Content;
var textPart = ChatMessageContentPart.CreateTextPart(text);
var contentParts = new List<ChatMessageContentPart> { textPart };
if (allowMultiModal && !message.Files.IsNullOrEmpty())
{
foreach (var file in message.Files)
{
if (!string.IsNullOrEmpty(file.FileData))
{
var (contentType, bytes) = FileUtility.GetFileInfoFromData(file.FileData);
var contentPart = ChatMessageContentPart.CreateImagePart(BinaryData.FromBytes(bytes), contentType, ChatImageDetailLevel.Auto);
contentParts.Add(contentPart);
}
else if (!string.IsNullOrEmpty(file.FileStorageUrl))
{
var contentType = FileUtility.GetFileContentType(file.FileStorageUrl);
var bytes = fileStorage.GetFileBytes(file.FileStorageUrl);
var contentPart = ChatMessageContentPart.CreateImagePart(BinaryData.FromBytes(bytes), contentType, ChatImageDetailLevel.Auto);
contentParts.Add(contentPart);
}
else if (!string.IsNullOrEmpty(file.FileUrl))
{
var uri = new Uri(file.FileUrl);
var contentPart = ChatMessageContentPart.CreateImagePart(uri, ChatImageDetailLevel.Auto);
contentParts.Add(contentPart);
}
}
}
messages.Add(new UserChatMessage(contentParts) { ParticipantName = message.FunctionName });
}
else if (message.Role == AgentRole.Assistant)
{
messages.Add(new AssistantChatMessage(message.Content));
}
}
var prompt = GetPrompt(messages, options);
return (prompt, messages, options);
}
private string GetPrompt(IEnumerable<ChatMessage> messages, ChatCompletionOptions options)
{
var prompt = string.Empty;
if (!messages.IsNullOrEmpty())
{
// System instruction
var verbose = string.Join("\r\n", messages
.Select(x => x as SystemChatMessage)
.Where(x => x != null)
.Select(x =>
{
if (!string.IsNullOrEmpty(x.ParticipantName))
{
// To display Agent name in log
return $"[{x.ParticipantName}]: {x.Content.FirstOrDefault()?.Text ?? string.Empty}";
}
return $"{AgentRole.System}: {x.Content.FirstOrDefault()?.Text ?? string.Empty}";
}));
prompt += $"{verbose}\r\n";
prompt += "\r\n[CONVERSATION]";
verbose = string.Join("\r\n", messages
.Where(x => x as SystemChatMessage == null)
.Select(x =>
{
var fnMessage = x as ToolChatMessage;
if (fnMessage != null)
{
return $"{AgentRole.Function}: {fnMessage.Content.FirstOrDefault()?.Text ?? string.Empty}";
}
var userMessage = x as UserChatMessage;
if (userMessage != null)
{
var content = x.Content.FirstOrDefault()?.Text ?? string.Empty;
return !string.IsNullOrEmpty(userMessage.ParticipantName) && userMessage.ParticipantName != "route_to_agent" ?
$"{userMessage.ParticipantName}: {content}" :
$"{AgentRole.User}: {content}";
}
var assistMessage = x as AssistantChatMessage;
if (assistMessage != null)
{
var toolCall = assistMessage.ToolCalls?.FirstOrDefault();
return toolCall != null ?
$"{AgentRole.Assistant}: Call function {toolCall?.FunctionName}({toolCall?.FunctionArguments})" :
$"{AgentRole.Assistant}: {assistMessage.Content.FirstOrDefault()?.Text ?? string.Empty}";
}
return string.Empty;
}));
prompt += $"\r\n{verbose}\r\n";
}
if (!options.Tools.IsNullOrEmpty())
{
var functions = string.Join("\r\n", options.Tools.Select(fn =>
{
return $"\r\n{fn.FunctionName}: {fn.FunctionDescription}\r\n{fn.FunctionParameters}";
}));
prompt += $"\r\n[FUNCTIONS]{functions}\r\n";
}
return prompt;
}
public void SetModelName(string model)
{
_model = model;
}
}